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465 Commits

Author SHA1 Message Date
Bruce MacDonald 6dea455b2d remove docs for now 2026-06-01 17:28:09 -07:00
Bruce MacDonald d44fdea1ef integrations: oh-my-pi
Add omp (oh my pi) as a launch integration. This an opinionated extension of pi. It is a coding agent.
2026-06-01 17:15:02 -07:00
Eva H 4e807fdedd cmd/launch: add Qwen code integration (#15900) 2026-06-01 19:51:32 -04:00
Daniel Hiltgen 7d3a6c3ae5 log template details to aid troubleshooting (#16403)
This cleans up the capabilities logic so we can log more information about the various options we consider as well as the final template version we use.
2026-06-01 16:25:44 -07:00
Eva H 06ff728246 feat(launch): show and auto-install Cline CLI (#16402) 2026-06-01 19:04:08 -04:00
Parth Sareen 2c71d8d7ca launch: migrate Codex config (#16397)
* launch: migrate Codex config
2026-06-01 13:46:41 -07:00
Eva H 00381496a3 cmd/launch: fix configure cline ollama provider via providers.json (#16352) 2026-06-01 16:41:40 -04:00
ZiTian Zhao 5e9636fa05 launch: avoid legacy Codex App profiles (#16364)
* launch: avoid legacy Codex App profiles
---------

Co-authored-by: ParthSareen <parth.sareen@ollama.com>
2026-06-01 11:49:56 -07:00
Daniel Hiltgen 630882621b llama-server followups (#16353)
* llama-server followups

Misc fixes for #16031
- Add back dropped ROCm build flag for multi-GPU support on windows
- Fix amdhip64_*.dll version detection for "latest" selection
- Fix embeddings API for consistent normalize behavior with prior versions

* ci: set up for automated llama.cpp update testing

* reduce batch for fa-disabled, and constrained vram

* mlx: fix v3 load bug on m5

Imagegen was incorrectly loading v3 first.  This DRYs out the loading code so imagegen gets the same new v4/v3 selection logic.

* fix reload bug on embedding models

* bump version

* steer user how to enable iGPU when disabled
2026-06-01 10:44:21 -07:00
Patrick Devine 0e93ccc2cd convert: fixes for qwen3next model conversion (#16354)
This change addresses some problems with GGUF conversion including:
 * correctly naming the MoE tensors
 * correctly quantizing the nextn.eh_proj.weight MTP tensor
2026-06-01 09:43:11 -07:00
Jeffrey Morgan e7766a4a47 model: improvements to laguna-xs.2 parser/renderer (#16362) 2026-05-31 14:11:07 -07:00
Jeffrey Morgan be7de10c41 llama: handle Gemma 4 and LFM2 BOS override in llama server (#16367) 2026-05-31 14:05:39 -07:00
Daniel Hiltgen 11be8f6ac8 mlx: fix dev mode search path (#16355)
The superbuild from the llama-server work changed paths but missed updating the MLX library resolution code to match.
2026-05-29 16:33:40 -07:00
Daniel Hiltgen 9db4bdbad6 runner: Remove CGO engines, use llama-server exclusively for GGML models (#16031)
* broad lint fixes to sidestep CI scope glitch

* runner: Remove CGO engines, use llama-server exclusively for GGML models

Remove the vendored GGML and llama.cpp backend, CGO runner, Go model
implementations, and sample.  llama-server (built from upstream llama.cpp via
FetchContent) is now the sole inference engine for GGUF-based models.
(Safetensor based models continue to run on the new MLX engine.)  This allows
us to more rapidly pick up new capabilities and fixes from llama.cpp as they
come out.

On windows this now requires recent AMD driver versions to support ROCm v7 as
llama.cpp currently does not support building against v6.

* llama/compat: load Ollama-format GGUFs in llama-server

Squashed from upstream/jmorganca/llama-compat on 2026-04-29.
Source tip: 0c33775d37.

Original source commits:
- 25223160d llama/compat: add in-memory shim so llama-server can load Ollama-format GGUFs
- 7449b539a llm,server: route Ollama-format gemma3 blobs through llama/compat
- 436f2e2b1 llama/compat: make patch-apply idempotent
- 8c2c9d4c8 llama/compat: extend gemma3 handler to cover 1B and 270M blobs
- 021389f7b llama/compat: shrink clip.cpp injection from 18 lines to 1
- 61b367ec2 llama/compat: shrink patch to pure call-site hooks (34 -> 20 lines)
- 36049361c llama/compat: simplify shim (gemma3-tested)
- 8fa664865 llama/compat: add qwen35moe text handler
- db0c74530 llama/compat: add qwen35moe vision (clip) support
- 2a388da77 llama/compat: split shared infra into a util TU
- 9a69a17dc llama/compat: document non-public API dependencies
- d0f38a915 llama/compat: add gpt-oss and lfm2 handlers
- 086071822 llama/compat: add mistral3 text handler (vision TODO)
- 63bde9ff7 llama/compat: add mistral3 vision (clip) support
- 3a57b89d5 llama/compat: apply LLaMA RoPE permute to mistral3 vision Q/K
- 99cb87439 llama/compat: add qwen35, gemma4, deepseek-ocr handlers
- 2c7850dba llama/compat: add nemotron_h_moe handler (latent FFN + MTP skip)
- 9e3b54225 llama/compat: add llama4 text + clip handlers
- 034fee349 llama/compat: add gemma4 clip handler (gemma4v projector)
- 9945c5a93 server: remove dhiltgen/* compat redirect table
- 5d4539101 llama/compat: rewrite gemma4 tokenizer model to BPE
- 7e0765327 llama/compat: add glm-ocr text handler + text-loader load-op hook
- f1bd1a25a llama/compat: add glm-ocr clip handler (glm4v projector)
- 4b5cf3420 llama/compat: collapse text-loader hook back to one new patch line
- eb4ecf4fc llama/compat: extend gemma4 clip handler to gemma4a (audio)
- a23a5e76f llama/compat: fix gemma4a per-block norm tensor mapping
- cd2dcaff4 llama/compat: add embeddinggemma handler
- 1ce8a6b26 llama/compat: add qwen3-vl + qwen2.5-vl handlers
- fd98ffa1e llama/compat: add gemma3n + glm4moelite handlers
- cc7bdf0bc llama/compat: handle null buft in maybe_load_tensor
- 0c33775d3 llama/compat: disable mmap when load_op transforms text-side tensors

* refine implementation

* ci: fix windows MLX build

* ci: fix windows llama-server build

* ci: fix windows rocm build

* ci: windows mlx tuning

Shorten long-tail on build, and get OllamaSetup.exe back under 2g limit

* ci: fix windows dependencies

* win: fix dependency gathering

* disable openmp

* win: arm64 cross-compile build

also DRY out CI steps

* scheduler improvements

* ci: improvements from #15982

* win: favor ninja for faster developer builds

* win: fix build

* win: fix arm64 cross-compile

* win: avoid spaces in compiler path

* misc discovery fixes, and bos handling

* lint fixes

* win: fix arm cross-compile build/CI bugs

* llama.cpp update

* win: handle multiple CRT dirs

* vulkan: add windows iGPU detection

* fix creation bugs for patched models, other refactoring work

* tune batch size for better performance

* ci and lint fixes

* fix repeat_last_n bug

* build: revamp build for better developer UX

* amd, sampler, qwen3next fixes

* version bump

* fix mlx build

* revamp GPU discovery

Scanning the output of llama-server is turning out to be too error prone across
llama.cpp updates, so this switches to a thin dynamic library load against the
bundled GGML libraries so more details can be gathered from the API.

* version bump

* missing file

* ci: fix cache miss on rocm build

* refine vulkan dep handling

* fix ps reporting bug on full GPU load

* improve cmake wiring for customized local builds

* version bump

* docker build arg cleanup

* improve windows exit error logs

* fix community gemma4 support and ci flakes

* fix mlx unit test

* tighten up ps logic to avoid double counting fit log lines

* version bump

* fix ps view for full gpu layer offload

* add MTP wiring for llama-server and create with GGUFs

* pick best template by capabilities

* version bump

* ci: harden apt repos

* remove unused cpu core discovery

* adjust batch default logic to reduce OOMs

* support larger tool calls

* fix audio support, template show

* qwen35 mtp patch support

* flesh out dtypes

* rocm deps

* version bump

* lint fix

* block broken gfx1150 on windows

* fix qwen3.5 moe mtp tensors in patch

* mmproj oom fallback and vulkan on by default

* qwen MTP compat fix

* version bump

* ci: fix WoA cross-compile

* ci: workaround ui tool in cross-compile

* version bump

* win: enable OpenMP for CPU builds

* build: improve developer UX

* ci: windows path workaround for CPU build

* win: fix WoA dependencies

* win: fix large offset reads for mmproj patched loads

* version bump

* fix vulkan dup detection

* add OLLAMA_IGPU_ENABLE and largely disable iGPUs by default

* opt-in MTP, win large offset, integraton fixes

* fix unit test scheduler interaction hang

* fix multi-gpu filtering

* version bump

* review comments

* fix thinking level

* fix linux rocm ordering and granite 3.3 template

* version bump

* ci fix - non-shallow MLX checkout

* bypass linux sysfs unit test on windows

---------

Co-authored-by: jmorganca <jmorganca@gmail.com>
2026-05-29 13:35:47 -07:00
Patrick Devine f63eea3d27 mlx: fix reported information in ollama show (#16289)
This change updates the show API for MLX models to:
  * display the correct quantization in mixed precision models
  * not display the global_scale scalar value
  * not duplicate the `tools` capability
2026-05-24 14:08:06 -07:00
Anto jones 632ff00798 server: remove duplicate template parsing (#16287) 2026-05-24 13:27:24 -07:00
Jesse Gross 275f122cda mlxrunner: keep gated-delta recurrent state in float32
Split the gated-delta Metal/CUDA kernels' dtype template into separate
input (InT) and state (StT) types so activations can stay in bf16/fp16
while the accumulated delta state stays in float32. Allocate the delta
state and qwen3_5's no-cache zero state in float32 to match.
2026-05-22 09:32:09 -07:00
Jesse Gross 32568531bd create: read draft architecture from its config.json
Previously the draft architecture was hardcoded to
Gemma4AssistantForCausalLM. Read it from the draft model's config so
any draft architecture can be packaged.
2026-05-22 09:32:09 -07:00
Jesse Gross 438fb991e4 mlxrunner: move YaRN RoPE helpers into x/models/nn
Move RopeParameters, BuildYarnRopeFreqs, and ScaleRotaryPart out of
laguna and into x/models/nn so other models can reuse them.
2026-05-22 09:32:09 -07:00
Jesse Gross 358af4af23 Revert "mlxrunner: add DFlash speculative decoding (#16134)"
This reverts commit 98e26b8c37.

The DFlash integration is too invasive to keep at this stage: it
threads DFlash-specific logic through the pipeline, base model
interfaces, and the cache layer. The recurrent cache also now
has qwen3.5 model-specific code. Revert it now and reintroduce
the self-contained, generally-useful pieces (YaRN RoPE DRY-out, draft
architecture autodetection, gated-delta fp32 state) as separate
follow-up commits.
2026-05-22 09:32:09 -07:00
Parth Sareen 91c8e5e1a8 launch: enriched model inventory (#16230) 2026-05-21 11:57:20 -07:00
Daniel Hiltgen 4b2d529966 Reduce startup model hydration (#16215)
* Reduce startup model hydration

Add a lightweight model list cache for tags and launch inventory, while keeping show cache population lazy. This avoids loading every local model at startup on large model stores.

* harden flaky scheduler unit test

* remove extra launch model metadata text

* review comments

* review comments
2026-05-19 15:53:08 -07:00
Bruce MacDonald e6b1d751f2 codex: omit patch tool type (#16231)
Including this value can cause schema compatibility issues. It was removed from codex in a new version.
2026-05-19 13:37:05 -07:00
Eva H 56b319f457 launch: add codex model metadata catalog (#15795)
Co-authored-by: Bruce MacDonald <brucewmacdonald@gmail.com>
2026-05-18 15:26:43 -07:00
Daniel Hiltgen 42e6f56c2a ci: speed up release builds (#15982)
* ci: speed up release builds

This should help speed things up for release.  It also will help
speed up local developer builds a little.

* ci: dedup linux build steps and optimize

* review comments
2026-05-15 14:53:15 -07:00
Daniel Hiltgen da679adcde quiet down kv log spew (#16105) 2026-05-15 13:28:32 -07:00
Parth Sareen b9c0421f03 docs: add codex app (#16163) 2026-05-14 17:53:15 -07:00
Patrick Devine 98e26b8c37 mlxrunner: add DFlash speculative decoding (#16134)
This change adds dflash block diffusion speculative decoding to the MLX runner. Included in this change:

support for qwen3.6 moe/dense speculative decoding
draft model recurrent cache playback
RoPE/YaRN changes (DRY out the laguna/dflash MoE YaRN implementation)
support for greedy sampling / leviathan/chen sampling
2026-05-14 14:02:34 -07:00
Parth Sareen c28ddc0a7b launch: codex app restarts (#16155) 2026-05-14 12:08:13 -07:00
Parth Sareen 3ad2fa3fb5 launch: update codex app UI copy (#16157) 2026-05-14 12:08:08 -07:00
Parth Sareen 6b6f45ef0e docs: hide codex app till launch (#16153) 2026-05-14 10:56:52 -07:00
Patrick Devine 4860130f83 mlx: rework the MLX sampler (#16122)
* mlx: rework the MLX sampler

Replace the MLX sampler transform chain with an explicit distribution pipeline that applies:
  1. penalties
  2. top-k
  3. temperature/softmax
  4. top-p
  5. min-p
  6. normalize
  7. categorical

The common top_k path now keeps sparse [B,K] token ids/probabilities on GPU instead of carrying full-vocab
scores, and sampled MTP reuses those draft/target distributions for acceptance, bonus, and residual sampling.

This change also fixes the seed parameter so that temperature sampling and sampled MTP are reproducible.
2026-05-13 17:18:27 -07:00
Parth Sareen ac7295ccab launch: codex app integration (#16120) 2026-05-13 17:11:52 -07:00
Daniel Hiltgen 6398cd5b78 mlx: add memory trace logging (#16131)
This should help narrow down the root cause of #16030
2026-05-13 13:37:31 -07:00
Eva H 3af1a008e2 launch/opencode: add image modalities for vision models (#15922) 2026-05-12 15:51:46 -04:00
Eva H 6bdb73073b anthropic: Preserve Claude local image-path tool results in renderer-owned prompt formatting (#16047) 2026-05-12 00:02:17 -04:00
Daniel Hiltgen 421faa0263 mlx: fix macOS 26 target leakage in v3 metallib (#16053)
MLX compiles the AIR objects with the requested -mmacosx-version-min, but its final metallib step invokes metal instead of metallib. With the macOS 26 SDK, that can stamp the Metal v3 library with a macOS 26 deployment target.

Relink the generated AIR files with metallib before install until this is fixed upstream.
2026-05-11 16:37:57 -07:00
Daniel Hiltgen 206b049508 mlx: avoid status timeout during inference (#16086)
The MLX runner now routes model work through a locked worker thread. Status also used that worker only to sample memory, so a scheduler health ping could sit behind long prefill or generation until its 10s context expired, causing /v1/status to return 500 and the server to treat the runner as unhealthy.

While Metal doesn't change VRAM reporting, CUDA does. Cache the last memory sample and make status perform only a short best-effort refresh. If the worker is busy, status returns the cached value while a single background refresh continues and updates the cache when the worker becomes available. The in-flight guard and lifecycle context keep this from spawning unbounded refreshes while preserving live VRAM refresh behavior for CUDA.

Fixes #16081
2026-05-11 16:03:38 -07:00
Patrick Devine d819ef0f97 mlx: update the imagegen runner for mlx thread affinity (#16096) 2026-05-11 13:05:06 -07:00
Daniel Hiltgen 3d5a011a2e app: harden update flows (#16100)
* app: harden update flows

This hardens the windows update flows and adds a new opt-in and CI triggered unit test to verify Mac/Windows updates with verification.

* test: harden unit tests for OLLAMA_MODELS being set

* app: harden updater
2026-05-11 12:24:01 -07:00
Daniel Hiltgen c2f2d90a67 test: integration test hardening (#13532)
* test: integration test hardening

Improve reliability on slower systems, and some flakes.  Fix
a few logic flaws on the newer tests, general hardening.

* tighten up vision logging

* add new models

* remove some older models - still covered by library scenarios
2026-05-08 15:54:17 -07:00
Daniel Hiltgen 1e1b34dada mlx: refined model push behavior (#15431)
* mlx: refined model push behavior

Refine the algorithm for parallel push of safetensors based models to get
better reliability and throughput.

* review comments, hardening, and performance tuning for slow links

* review comments
2026-05-08 14:25:30 -07:00
Parth Sareen f866e7608f launch: disable Claude Desktop launch (#16028) 2026-05-07 10:46:18 -07:00
Parth Sareen bab59072fb launch: add plan-aware model gating (#16027) 2026-05-06 14:34:26 -07:00
Eva H 7c2c36bda2 cmd/launch: improve integration backup UX (#15907) 2026-05-06 11:32:54 -04:00
Parth Sareen d319227df0 server: cache show responses (#15967) 2026-05-05 14:40:18 -07:00
Daniel Hiltgen 2d84ec939c mlx: partial cleanup of imagegen layout (#15435)
* mlx: partial cleanup of imagegen layout

This moves part of the imagegen safetensors code to the new package.

* test: remove flaky timing test
2026-05-05 14:15:30 -07:00
Patrick Devine 15e6076d79 mlx: Gemma4 MTP speculative decoding (#15980)
This change adds support for MTP (multi-token prediction) speculative decoding for the
gemma4 model family.

It includes:
  * support for importing safetensors based gemma4 draft models with `ollama create`
  * a new DRAFT command in the Modelfile for specifying draft models
  * a --quantize-draft flag for the ollama create command to quantize the draft model
  * cache support for speculation
  * changes to the rotating cache to be able to handle MTP correctly
  * sampling support for draft model token prediction

---------

Co-authored-by: Daniel Hiltgen <daniel@ollama.com>
2026-05-05 08:55:04 -07:00
Parth Sareen 4017af96cd go: bump to 1.26 (#15904) 2026-05-03 23:24:35 -07:00
Daniel Hiltgen 534342e7e2 Update MLX and MLX-C with threading fixes (#15845)
* Update MLX and MLX-C

* Run MLX CGO work on a locked OS thread

MLX now relies on OS-thread-local execution state for streams, encoders, and caches. Add an mlxthread executor backed by runtime.LockOSThread and route runner initialization, model load, inference, status memory reads, and cleanup through the worker so Go goroutine migration cannot split MLX state across native threads.

Also stop caching default MLX streams before the runner owns the thread and add worker/threaded MLX regression tests.

* mlx: use common status writer

* mlx: bundle missing libjaccl on arm64

Inspired by #15793

* review comments
2026-05-03 10:03:14 -07:00
Parth Sareen 9ba5a04914 launch: claude app (#15937) 2026-05-02 19:19:57 -07:00
Bruce MacDonald 938ca6e274 app: source featured models from experimental recommendations endpoint (#15909)
Replace the hardcoded FEATURED_MODELS list with the
/api/experimental/model-recommendations endpoint so the picker stays in
sync with server-driven recommendations. Inline the merge into useModels
(recommendations first, then the rest of /api/tags) and drop the
standalone mergeModels util.
2026-05-01 11:10:20 -07:00
Pratham Agarwal 8f39fff70b fix: resolve OpenClaw gateway launch timeout on Windows by enforcing IPv4 loopback (#15726) 2026-04-30 22:20:08 -04:00
Daniel Hiltgen 4fe5609563 metal: harden for ggml initialization failures (#15755)
* metal: harden for ggml initialization failures

ggml_metal_device_init performs a probe to verify the tensor API compiles.  On
some systems this passes, even though kernel coverage isn't complete, which
results in a later crash when compiling the real kernels.  This change adds a
single retry if any of the error strings match this failure mode to disable the
tensor API.  It also hardens an error case in the Go initDevices to detect
device initialization failures and panic instead of crashing later on a nil
array entry.

Fixes #15734

* review comments

* review comments
2026-04-30 16:28:03 -07:00
Bruce MacDonald 917324bb4d app: remove ollama update url env var used for testing (#15905) 2026-04-30 13:14:08 -07:00
Parth Sareen c7c2837c96 renderers: update gemma4 renderer (#15886) 2026-04-29 18:40:23 -07:00
Parth Sareen b6447caebc launch: use vram bytes for model recommendations (#15885) 2026-04-29 18:40:14 -07:00
Eva H bad32c7244 launch/docs: fix title for pool (#15883) 2026-04-29 17:18:44 -04:00
Eva H ab2e005bf7 app: align the app launch page with ollama launch (#15753) 2026-04-29 14:45:19 -04:00
Parth Sareen 321cc8a2ba server/launch: add model recommendations cache endpoint (#15868) 2026-04-28 17:09:04 -07:00
Daniel Hiltgen 87288ced4f New models (#15861)
* mlx: add laguna model support

* convert: support fp8 safetensors import

Decode HF F8_E4M3 safetensors with block scale companions into GGUF-supported tensor types, and record which output tensors came from FP8 source weights.

Use that source-precision metadata during create quantization: default FP8-sourced GGUFs to Q8_0, keep non-FP8 tensors at their original precision for Q8_0, and promote non-FP8 quantizable tensors to Q8_0 for Q4_K requests.

* ggml: add laguna model support

* server: preserve generate logprobs with builtin parsers

Generate requests were dropping logprob-only chunks whenever a builtin parser buffered visible content. Chat already handled this case, but generate only forwarded chunks with visible response, thinking, or tool-call output.

Keep generate chunks that carry logprobs even when the builtin parser has not flushed visible content yet, and add a regression test that exercises the behavior with a generic thinking parser.

* review comments - perf improvements

* ggml: implement nemotron 3 nano omni

* add poolside integration

* update poolside doc

* adapt to new cache setup

* fix test

* fix test

---------

Co-authored-by: Eva Ho <hoyyeva@gmail.com>
2026-04-28 11:50:12 -07:00
Jesse Gross 2bbe2405fe mlxrunner: decouple models from attention cache storage layout
Models build their own attention masks and read K/V directly from
the cache's buffers, which ties them to the cache's storage layout.
That blocks multi-sequence batching — right-padded rows need a
query-padding mask composed onto every model — and rules out
variants like paged attention where K/V isn't one contiguous tensor.

Caches now hand back a per-layer KVHistory holding post-update K, V,
and a MaskApplier that merges the cache's storage restrictions into
the model's logical mask. Models describe their mask in logical
terms; SDPA composes model, padding, and applier contributions and
dispatches to the kernel's causal or no-mask fast path when it can.
KVHistory still exposes K, V, and the composed mask for manual
attention paths (e.g. CUDA prefill at head_dim > 128).

Performance for single-sequence inference is unchanged.
2026-04-27 20:04:46 -07:00
Jesse Gross bd21678b16 mlxrunner: apply RoPE at per-row positions
Switch RoPE from the scalar-offset kernel (mlx_fast_rope) to the
array-offset one (mlx_fast_rope_dynamic) so each batch row can start
at its own position. The pipeline tracks the current position locally
and passes it to the model through Batch.SeqOffsets; each model
materializes that slice into an int32 array for the RoPE call.

Single-sequence behavior is unchanged; this is the wiring needed
before the runner can batch independent sequences.
2026-04-27 20:04:46 -07:00
Jesse Gross 088dfd89a8 mlxrunner: wrap model forward inputs in a Batch struct
Gives a single extension point for per-call context (positions,
sequence IDs, masks) as multi-sequence batching grows, without having
to churn every model's Forward signature again.
2026-04-27 20:04:46 -07:00
Eva H 3cab8a7b02 app/server: fix desktop app startup killing active ollama launch sessions (#15657) 2026-04-27 22:52:53 -04:00
Daniel Hiltgen 03aee88186 mlx: Support NVIDIA TensorRT Model Optimizer import (#15566)
* mlx: Support NVIDIA TensorRT Model Optimizer import

* x/create: support FP8 safetensors import

Decode HF F8_E4M3 safetensors with block scale companions into MLX-importable tensor blobs, including compressed-tensors weight_scale metadata, packed NVFP4 layouts, and mixed-precision tensor headers.

Use that source-precision metadata during create quantization: default FP8-sourced imports to mxfp8, allow source FP8 to target MLX low-bit formats, preserve source-quantized NVFP4 layouts, selectively keep or promote tensors based on their source precision, and detect quantized dtype from mixed-precision safetensors manifests.

* review comments
2026-04-27 18:28:10 -07:00
Daniel Hiltgen ec9b4e9e47 tokenizer: fix multi-regex BPE offset handling (#15844)
Use the current fragment offset when emitting unmatched spans during multi-regex BPE splitting. This avoids duplicating earlier prompt text and inflating token counts for multi-stage BPE tokenizers.
2026-04-27 14:14:27 -07:00
Jesse Gross 4656a07e56 mlxrunner: batch the sampler across multiple sequences
Register sequences with Add/Remove; each Sample call takes any subset of
registered slots and samples one token per row, appending to each slot's
ring-buffer history. When all slots share Options and penalty rings are
full, one fused transform pass runs over the whole batch via a persistent
pooled history tensor; otherwise calls fall back to per-slot serial
processing indexed against the same pool.

Performance is unchanged for a single sequence, which is all that is
exposed for now.
2026-04-25 09:53:53 -07:00
Jesse Gross 30f86cb9dd mlxrunner: track sampler history in a fixed-size ring buffer
AppendToken used to concatenate the new token onto the history tensor
and slice it back to RepeatLastN every decode step, churning the graph
shape and reallocating a fresh tensor each call. The stateful penalties
don't care about order within the window, so a fixed-capacity ring with
one SliceUpdate per append keeps the tensor shape constant across
steps.
2026-04-25 09:53:53 -07:00
Parth Sareen ea01af6f76 openai: map responses reasoning effort to think (#15789) 2026-04-24 02:49:36 -07:00
Parth Sareen c2ebb4d57c api: accept "max" as a think value (#15787) 2026-04-24 01:49:39 -07:00
Parth Sareen 590109c835 launch: harden OpenClaw onboarding flow (#15777) 2026-04-23 16:47:20 -07:00
Eva H b4442c6d17 launch: resave managed integration config when live config drifts (#15776) 2026-04-23 19:32:36 -04:00
Eva H 85ff8e4a21 launch: keep launch recommended models in a fixed canonical order (#15750) 2026-04-23 16:33:00 -04:00
Parth Sareen 160660e572 launch: use bundled OpenClaw ollama web search (#15757) 2026-04-22 16:34:19 -07:00
madflow 3b43b9bc4b docs: update structured outputs doc for cloud (#15733)
---------

Co-authored-by: Parth Sareen <parth.sareen@ollama.com>
2026-04-22 00:42:39 -07:00
Parth Sareen 21883571b7 launch: replace kimi-k2.5 with k2.6 as top recommended model (#15737) 2026-04-21 15:13:20 -07:00
Jesse Gross ce99f24731 mlxrunner: tokenize prompts in request handler goroutines
Move tokenization out of the single GPU processing goroutine and
into each request's HTTP handler goroutine. This allows the next
request's prompt to be tokenized on the CPU while the current
request is executing on the GPU.
2026-04-21 14:38:49 -07:00
Jesse Gross 04f5f0cdb4 mlx: improve thread safety of array management
Use atomic.Int32 for Array.pinned and a sync.Mutex for the global
arrays slice so MLX arrays can be created and pinned from multiple
goroutines without racing on those structures. Convert Array value
receivers to pointer receivers and struct fields from Array to
*Array to avoid copying the atomic.

This does not fully achieve thread safety even when building
completely independent graphs. The tracing flag and traceScratch
slice in compile.go are unprotected, so concurrent Compile calls
will race. MLX itself is not fully thread-safe either although
it is working to improve.
2026-04-21 14:38:49 -07:00
Matteo Celani fb36a01ffe app/ui: fix model picker showing stale model after switching chats (#15280)
* app/ui: fix model picker showing stale model after switching chats

Optimistic messages created during streaming were storing the full
Model object instead of the model name string. When switching back
to a chat with cached streaming data, the restore effect read an
object where it expected a string, causing the model picker to fail
matching and remain stuck on the previous chat's model.

* app/ui: fix two more instances of Model object passed as model name

Fix the same bug at lines 523 and 536 in the assistant_with_tools
event handler, where selectedModel (object) was used instead of
selectedModel.model (string).
2026-04-21 15:08:06 -04:00
Michael Verrilli 0c65ed33bc cmd: populate model capabilities in launchInteractiveModel (#15712)
launchInteractiveModel was introduced in PR #14609 without the
client.Show() capability-detection block that RunHandler uses.
This left opts.MultiModal always false in the TUI path, causing
image/audio file paths to always be treated as unknown commands
instead of being loaded as multimodal attachments.

Mirror the Show() call, pull-on-404 fallback, cloud auth handling,
and MultiModal/Think population from RunHandler into
launchInteractiveModel.

Fixes #15711
2026-04-21 14:37:36 -04:00
Jesse Gross 22d6c817f8 mlxrunner: fuse top-P and top-K into a single sort pass
When both filters are active, avoid paying for a full sort in top-P
and a partial sort in top-K. Single-filter paths are unchanged.
Improves generation throughput on gemma4:e4b by 1.5%.
2026-04-20 17:43:00 -07:00
Jesse Gross ca01373b28 mlxrunner: use MaxAxis in the min-P sampler
One reduction op instead of Argmax + TakeAlongAxis.
2026-04-20 17:43:00 -07:00
Jesse Gross 24e038d56a mlxrunner: add logprobs support
Match the ollamarunner and OpenAI semantics: raw, full-vocab log-softmax
with the top-K ranked by probability. Skipped on the GPU when the request
doesn't ask for logprobs so decode doesn't pay for it otherwise.
2026-04-20 17:43:00 -07:00
Parth Sareen 5d1021603a server: apply format when think=false for gemma4 (#15678) 2026-04-20 17:42:29 -07:00
Parth Sareen 8e05d734b9 launch: add kimi cli integration with installer flow (#15723) 2026-04-20 15:33:32 -07:00
Jesse Gross 05e0f21bec mlx: fuse sigmoid router head in glm4_moe_lite
DeepSeek-V2-style aux-loss-free routing computes sigmoid(gates) once but
needs it twice: the raw sigmoid output is gathered after top-k, while the
post-bias negation is the argpartition key. Fuse into a single multi-output
Compiled kernel returning both, saving two launches on the routing path
per token. Exposed as a general SigmoidRouter since the same pattern is
shared across DeepSeek-V2 descendants.

Improves glm4.7 generation performance by approximately 1%.
2026-04-20 15:02:14 -07:00
Daniel Hiltgen ff23dd343f mlx: apply repeat penalties in sampler (#15631) 2026-04-18 07:49:38 -07:00
Parth Sareen 123b300af6 docs: update hermes (#15655) 2026-04-17 14:20:59 -07:00
Parth Sareen 57653b8e42 cmd/launch: show WSL guidance on Windows instead of handing off (#15637) 2026-04-16 17:18:04 -07:00
Parth Sareen a50ce61c54 launch: skip unchanged managed-single rewrite (#15633) 2026-04-16 16:20:42 -07:00
Daniel Hiltgen 2bb7ea00d2 create: avoid gc race with create (#15628)
If you have a long running create, and start another ollama server with the
same model dir, the GC algorithm deletes the pending blobs and breaks the
create.  This adds a 1h grace period to avoid deleting in-flight creation
operations.
2026-04-16 13:29:16 -07:00
Daniel Hiltgen 55fa80d07a mlx: additional gemma4 cache fixes (#15607)
Harden additional corner cases
2026-04-16 13:07:19 -07:00
Daniel Hiltgen b9cb535407 mlx: fix gemma4 cache to use logical view (#15617) 2026-04-16 11:54:30 -07:00
Daniel Hiltgen 031baef094 mlx: fix imagegen lookup (#15588)
* mlx: fix imagegen lookup

Fixes #15533 - imagegen had fallen out of sync with the new layout
for multiple mlx libraries on Metal.

* review comments
2026-04-16 10:39:00 -07:00
Mike Wallio 7d271e6dc9 cmd/launch: add Copilot CLI integration (#15583)
---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Co-authored-by: ParthSareen <parth.sareen@ollama.com>
2026-04-15 17:22:53 -07:00
Devon Rifkin c88dae2d6b Merge pull request #15612 from ollama/drifkin/gemma4-split-templates
gemma4: render differently based on model size
2026-04-15 17:15:35 -07:00
Devon Rifkin 9e3618d663 make empty block conditional 2026-04-15 15:35:25 -07:00
Daniel Hiltgen 5d920cc6bc Keep Gemma4 router projection in source precision (#15613) 2026-04-15 15:04:23 -07:00
Devon Rifkin e585ecd11f gemma4: render differently based on model size
Following up on #15560, this change now has e2b/e4b render differently
from 26b/31b.

For backwards compatibility, we take the existing renderer name `gemma4`
and make it do dynamic resolution based on the model name/size, but the
intended use is for the models to be republished with the renderer
variant specified explicitly: `gemma4-small` or `gemma4-large`.
2026-04-15 14:37:16 -07:00
Eva H cdddea0592 launch: always list cloud recommendations first (#15593) 2026-04-15 13:17:35 -07:00
Parth Sareen 43f90def04 launch: add hermes (#15569) 2026-04-15 12:00:23 -07:00
Daniel Hiltgen 06ae6367bd mlx: fix RotatingKVCache.concat() dropping context on mid-rotation (#15591)
After the rotating buffer has wrapped (c.offset > c.maxSize) a subsequent
L>1 Update() went through a slice-to-[0, c.idx) path that discarded all
slots in [c.idx, Dim), losing the older-but-still-in-window tokens the
first Q of the new batch needs for its sliding-window attention.

Linearize the circular buffer to logical order in that wrapped case so
the existing trim + concat preserves the last (maxSize - 1) old tokens.
When the buffer has not yet wrapped (c.offset <= c.maxSize), slots
[c.idx, Dim) are grow padding or stale post-rewind data, so keep
dropping them.
2026-04-14 18:29:06 -07:00
Daniel Hiltgen 48ad7085c4 mlx: Improve gemma4 performance with fused operations (#15587)
* mlx: Improve gemma4 performance with fused operations

* review comments
2026-04-14 18:04:04 -07:00
Jesse Gross e1e3cec8d0 models: fuse MLP activation functions via mlx_compile
Converts SiLU/GELUApprox to compiled kernels and adds SwiGLU,
matching upstream mlx/mlx_lm's activations pattern. Routes llama,
qwen3, qwen3_5 (dense + MoE), and glm4_moe_lite MLP paths through
mlx.SwiGLU so each MLP invocation runs as one fused Metal/CUDA
kernel rather than a chain of per-op launches.
2026-04-14 16:38:32 -07:00
Jesse Gross d3e67e305c mlx: add compiled closure support
Wraps MLX's mlx_compile API so Go functions can be traced into fused
kernels. Contiguous elementwise chains collapse into a single
Metal/CUDA kernel instead of launching one per op.

Exposes Compile plus arity helpers (Compile1/2/3) that mirror Python's
@mx.compile decorator shape, lazily building the closure on first call
so package-level declarations work before the MLX dylib loads.
2026-04-14 16:38:32 -07:00
Eva H 698e04a14b launch: OpenCode inline config (#15586) 2026-04-14 15:08:42 -07:00
Eva H 1d9537bc33 launch/openclaw: fix --yes flag behaviour to skip channels configuration (#15589) 2026-04-14 13:57:35 -07:00
Eva H 120424d832 Revert "launch/opencode: use inline config (#15462)" (#15568) 2026-04-13 18:40:17 -07:00
Eva H 5818001610 launch: skip unchanged integration rewrite configration (#15491) 2026-04-13 17:18:56 -07:00
Daniel Hiltgen 2cba7756c5 Gemma4 on MLX (#15244)
* gemma4: implement Gemma 4 model for MLX (text-only runtime)

* gemma4: two MoE + SWA prefill perf fixes

Two performance optimizations in the gemma4 forward pass

1. Memoize the sliding-window prefill mask across layers.
2. Softmax only over the selected experts in Router.Forward.

* review comments
2026-04-13 16:36:51 -07:00
Devon Rifkin bf2a421727 gemma4: restore e2b-style nothink prompt (#15560)
Gemma 4 prompts differ when thinking is disabled for different sized
models: 26b/31b emit an empty thought block, while e2b/e4b do not.

Before #15490, our shared Gemma 4 renderer effectively matched the
e2b behavior. #15490 changed it to always emit the empty thought block,
which regressed e2b/e4b nothink behavior and led to #15536 (and possibly

This change restores the previous shared behavior by removing the empty
trailing thought block. It also renames the checked-in upstream chat
templates so the e2b and 31b fixtures are tracked separately.

A follow-up will split Gemma 4 rendering by model size.

Fixes: #15536
2026-04-13 14:26:15 -07:00
Eva H f3cf6b75fb launch/opencode: use inline config (#15462) 2026-04-13 13:41:31 -07:00
Devon Rifkin 5dfac387a6 Revert "gemma4: fix nothink case renderer (#15553)" (#15556)
This reverts commit 4d75f5da03.
2026-04-13 13:12:18 -07:00
Daniel Hiltgen a99e5d9c22 mac: prevent generate on cross-compiles (#15120)
For some versions of Xcode, cmake builds are failing due to header problems in
cross-compiling during the generate phase.  Since generate is producing arch
independent generated output, we can skip this during cross-compiling.
2026-04-13 13:04:58 -07:00
Daniel Hiltgen 0abf3aca36 cgo: suppress deprecated warning to quiet down go build (#15438) 2026-04-13 13:04:11 -07:00
Devon Rifkin ee0266462a Revert "gemma4: add nothink renderer tests (#15554)" (#15555)
This reverts commit 1b70bb8a10.
2026-04-13 13:00:59 -07:00
Daniel Hiltgen c88fb286ec mlx: add op wrappers for Conv2d, Pad, activations, trig, and masked SDPA (#14913)
* mlx: add op wrappers for Conv2d, Pad, activations, trig, and masked SDPA

Add Conv2d, flexible Pad (with axes/mode), PadConstant, Maximum,
Minimum, Softplus, ReLU, GLU, Clamp, Sin, Cos, Clip,
ScaledDotProductAttentionMasked, and RoPEWithFreqs. Refactor
RoPEWithBase to delegate to RoPEWithFreqs.

* review comments

* mlx: fix ScaledDotProductAttentionMasked to consult the mask argument
2026-04-13 11:43:24 -07:00
Daniel Hiltgen d3da29cbfc mlx: mixed-precision quant and capability detection improvements (#15409)
Improve the MLX model creation pipeline with several model-agnostic changes:

- Rewrite supportsVision to use vision_config instead of architecture name
- Add supportsAudio for audio encoder detection
- Add alignment checking (isAligned) for quantization group sizes
- Support per-projection mixed quantization in MoE expert packing
- Record per-tensor quant metadata in safetensors blobs
- Parse per-tensor quant metadata at model load time
- Validate quantize output is non-empty before storing
- Fix pin/unpin cleanup in expert group quantization
- Promote v_proj/k_proj/down_proj to INT8 for INT4 base quant
- Add MetalIsAvailable() utility
- Skip audio encoder tensors from quantization
2026-04-13 11:43:07 -07:00
Devon Rifkin 1b70bb8a10 gemma4: add nothink renderer tests (#15554)
Meant to include in #15553
2026-04-13 11:38:19 -07:00
Daniel Hiltgen ec29ce4ce3 gemma4: fix compiler error on metal (#15550)
On some systems, the metal runtime compiler is failing due to an
uninitialized variable from #15378.

Fixes #15548
2026-04-13 11:32:00 -07:00
Devon Rifkin 4d75f5da03 gemma4: fix nothink case renderer (#15553)
Regressed in #15490

Fixes: #15536
2026-04-13 11:23:19 -07:00
saman-amd 798fd09bfe Update to ROCm 7.2.1 (#15483)
Co-authored-by: Samiii777 <58442200+Samiii777@users.noreply.github.com>
2026-04-12 12:11:58 -07:00
Devon Rifkin 9330bb9120 gemma4: be less strict about whitespace before bare keys (#15494) 2026-04-11 16:30:27 -07:00
Devon Rifkin 40a1317dfd gemma4: update renderer to match new jinja template (#15490)
* gemma4: update renderer to match new jinja template

Google has updated their jinja template for gemma4, and so this change
gives us parity with the new template. The parsing also slightly changed
upstream, so we make a small change to our parser as well.

I've also corrected a few probably existing edge cases, especially
around type unions. The upstream output format is weird (a stringified
array), but in practice the models seem to understand it well.

* gemma4: special case simple `AnyOf`s

The upstream template doesn't handle `AnyOf`s, but since in the previous
commit we saw type unions work reasonably well, I'm now treating very
simple `AnyOf`s as type unions to help in cases where they might be used

* fix lint

* gemma4: prefer empty instead of `None`

We can't currently distinguish between a result being not-present vs.
empty. The empty case seems more important (e.g., a legitimately empty
tool call)

* gemma4: be more careful for tool results with missing IDs
2026-04-10 15:45:27 -07:00
Devon Rifkin fdfe9cec98 model/parsers: fix missing parallel tool call indices (#15467)
We were missing setting the function index for several models that can
make parallel tool calls.

In the future we may want to consider putting some sort of post-parse
hook and relieve the parsers of this duty.

Fixes: #15457
2026-04-10 15:23:21 -07:00
Matteo Celani 9517864603 app/ui: re-validate image attachments when selected model changes (#15272) 2026-04-10 14:03:51 -07:00
Bruce MacDonald 8e6d86dbe3 docs: add hermes agent integration guide (#15488)
Update cloud and local model recommendations to match current
models.go: add qwen3.5:cloud and glm-5.1:cloud, replace glm-4.7-flash
with gemma4 and qwen3.5 as local options.

Add documentation for Hermes Agent by Nous Research, covering
installation, Ollama setup via custom endpoint, messaging configuration,
and recommended models.
2026-04-10 13:13:36 -07:00
Parth Sareen 80d3744c5d launch: update openclaw channel message (#15463)
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2026-04-09 09:51:34 -07:00
Patrick Devine eb97274e5c modelfiles: fix /save command and add shortname for safetensors based models (#15413)
This change fixes two issues with Modelfiles:

  1. If a user uses `ollama show --modelfile` to show a safetensors based
     model, the Model would leave the "FROM" field blank which won't allow
     a user to recreate the model. This change adds the model's current
     canonical short name to the FROM field.
  2. If a user uses the `/save` command in the CLI any messages which were
     saved in a previous model wouldn't get saved (only the set of messages
     from the current session).
2026-04-08 21:05:39 -07:00
Daniel Hiltgen 6b5db12aa2 mlx: remove stale x86 libmlx library (#15443)
Fixes #15433
2026-04-08 20:51:47 -07:00
7. Sun 612f0a17d3 fix: improve error message for unknown input item type in responses API (#15424)
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The default branch in unmarshalResponsesInputItem had two issues:
- It referenced typeField.Type instead of itemType; these differ when the
  shorthand role-based format promotes an empty type to "message", meaning
  an unhandled type would show the wrong value in the error string.
- It used %s formatting, so an empty type field produced the unhelpful
  message "unknown input item type: " with no indication what was missing.

Fix by using itemType (the resolved value) with %q quoting, and add a
dedicated message when itemType is empty (both type and role absent):
"input item missing required 'type' field".

Tests added for the empty-type and missing-type cases.

Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-08 17:41:12 -07:00
Parth Sareen 673726fa0e app: restore launch default and refine launch sidebar open for app (#15437) 2026-04-08 16:59:21 -07:00
Daniel Hiltgen b5918f9785 pull/push: refine safetensors (#14946)
* pull: refine safetensors pull

 - Body drain in resolve() — drain response body before close so Go's HTTP
   client can reuse TCP connections instead of opening a new one per blob
   (1,075 extra TCP+TLS handshakes eliminated)
 - Skip speed recording for tiny blobs (<100KB) — prevents
   HTTP-overhead-dominated transfer times from poisoning the median, which the
   stall detector uses to cancel "too slow" downloads
 - Resume support for large blobs (>=64MB) — on failure, preserves partial .tmp
   files; on retry, re-hashes existing datak and sends Range header to download
   only remaining bytes; gracefully falls back to full download if server returns
   200 instead of 206; SHA256 verification catches corrupt partials

* harden push

- Prevents killing TCP connections after every request.
- Stronger backoff to handle server back-pressure and rate limiting
- Larger buffered reads for improve safetensor upload performance
- Better error message handling from server
- Handle 201 if server says blob exists
- Fix progress reporting on already uploaded blobs
- Trace logging to help troubleshoot and tune going forward

* review comments

* review comments
2026-04-08 14:15:39 -07:00
Eva H d17f482d50 launch/opencode: detect curl installed opencode at ~/.opencode/bin (#15197) 2026-04-08 13:54:51 -07:00
Parth Sareen 4e16f562c0 launch: add openclaw channels setup (#15407) 2026-04-08 13:25:27 -07:00
Parth Sareen 55308f1421 launch: update ctx length for glm-5.1 and gemma4 (#15411)
Also adds glm-5.1 in recommended models
2026-04-08 12:11:50 -07:00
Eva H d64812eb5d cmd: improve multi-select sorting and selection status (#15200) 2026-04-08 10:39:18 -07:00
Devon Rifkin f86a969f27 responses: add support for fn call output arrays (#15406)
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In addition to strings (which we already supported), OpenResponses
supports arrays of text content, image content, or file content (see
<https://www.openresponses.org/reference#object-FunctionCallOutput-title>).
We were missing support for these arrays, which caused unmarshal errors
like

```
json: cannot unmarshal array into Go struct field ResponsesFunctionCallOutput.output of type string
```

This change adds support for text content and image content, as those
are more straightforwardly mappable to Ollama message formats (though
image and text interleaving is lost), but it's less clear what to do for
files. In the future we can partially support this by inlining
reasonably sized text files, but wanted to get this change out first.

Fixes: #15250
2026-04-07 16:47:30 -07:00
Matteo Celani 9fa80a1660 app/ui: fix lint errors for unused vars, prefer-const, and empty catch (#15282) 2026-04-07 16:28:36 -07:00
Daniel Hiltgen dde09129d1 gemma4: Disable FA on older GPUs where it doesn't work (#15403)
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CUDA older than 7.5 lack the support to enable flash attention for the model.
2026-04-07 14:54:25 -07:00
Patrick Devine 780556c4d0 mlx: use default http client (#15405) 2026-04-07 14:53:23 -07:00
Daniel Hiltgen dfae363b5b gemma4: add missing file (#15394)
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File accidentally omitted from #15378
2026-04-07 09:18:01 -07:00
Daniel Hiltgen 30fdd229a4 create: Clean up experimental paths, fix create from existing safetensor model (#14679)
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* create:  Clean up experimental paths

This cleans up the experimental features, and adds both unit and integration test coverage to verify no regressions.

* create: preserve config and layer names when creating from safetensors models

When creating a model FROM an existing safetensors model, ModelFormat,
Capabilities, and layer Name fields were lost. ModelFormat stayed empty
because it's only set from GGML layers (which safetensors models lack),
and layer names weren't copied in parseFromModel. This caused derived
models to fail loading ("config.json not found in manifest").

* review comments
2026-04-07 08:12:57 -07:00
Daniel Hiltgen e823bff873 gemma4: enable flash attention (#15378)
Backport GGML kernels so we can enable flash attention for the gemma 4 model on
Metal and CUDA.
2026-04-07 08:12:36 -07:00
Daniel Hiltgen 8968740836 mlx: Improve M5 performance with NAX (#15345)
* mlx: Improve M5 performance with NAX

This modifies the Mac release to now have 2 builds of MLX for broader
compatibility while supporting the latest M5 hardware features.  NAX requires
building with xcode 26.2 and targetting support only for OS v26 and up.  Since
we want to support older MacOS versions as well, we now need 2 different MLX
builds and runtime detection logic to select the optimal version.  The newer
build will detect NAX missing at runtime, so it is safe to run on pre M5 macs.

* mac: prevent generate on cross-compiles

For some versions of Xcode, cmake builds are failing due to header problems in
cross-compiling during the generate phase.  Since generate is producing arch
independent generated output, we can skip this during cross-compiling.
2026-04-07 08:12:24 -07:00
Devon Rifkin 8c8f8f3450 model/parsers: add gemma4 tool call repair (#15374)
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The existing strict gemma4 tool parser is still the primary path, but if
this fails, we try to repair by fixing some of the most commonly seen
mistakes these models seem to make in practice.

We repair by building up a set of candidates, and use the first candidate
that parses.

Repairs cover:

- missing Gemma string delimiters
- single-quoted string values, including a dangling Gemma delimiter
- raw terminal string values (if the corresponding tool schema indicates
  it should be a string)
- missing object close only after a concrete repair

Add regression coverage for malformed tool calls from issue #15315 and
focused unit tests for the individual repair helpers and candidate
pipeline.
2026-04-06 18:47:17 -07:00
Parth Sareen 82f0139587 launch/openclaw: patch approvedScopes baseline for TUI pairing (#15375) 2026-04-06 18:00:12 -07:00
Bruce MacDonald 26a58b294c app: update featured models (#15373)
Featured models in the app are out of date. Update them to a more recent list of models.
2026-04-06 16:35:35 -07:00
Devon Rifkin 34a790a2e6 model/parsers: suppress extra gemma4 closing tool tags (#15370)
We've observed Gemma 4 occasionally emitting extra <tool_call|> tags
after a valid tool call. We suppress leading close tags in this
immediate post-tool-call state so the extra close tags do not leak into
assistant content. The tradeoff is that if the model intentionally
begins its next content span with the literal string "<tool_call|>", we
will erroneously treat it as noise and drop it.
2026-04-06 12:41:33 -07:00
Jeffrey Morgan 4589fa2cf5 app: default app home view to new chat instead of launch (#15312)
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2026-04-03 21:50:55 -07:00
Daniel Hiltgen 4bc2728047 Revert "enable flash attention for gemma4 (#15296)" (#15311)
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This reverts commit c8e0878814.
2026-04-03 17:44:44 -07:00
Devon Rifkin 49d5fd5a3e model/parsers: rework gemma4 tool call handling (#15306)
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Replace the custom Gemma4 argument normalizer with a stricter
reference-style conversion: preserve Gemma-quoted strings, quote bare
keys, and then unmarshal the result as JSON.

This keeps quoted scalars as strings, preserves typed unquoted values,
and adds test coverage for malformed raw-quoted inputs that the
reference implementation rejects.
2026-04-03 14:35:00 -07:00
Jesse Gross 3cd2b03a5e ggml: fix ROCm build for cublasGemmBatchedEx reserve wrapper
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Add missing cublasGemmAlgo_t to hipblasGemmAlgo_t type mapping and
cast away const qualifiers that hipblasGemmBatchedEx doesn't accept.
2026-04-03 14:22:46 -07:00
Daniel Hiltgen c8e0878814 enable flash attention for gemma4 (#15296)
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2026-04-03 12:46:18 -07:00
Jesse Gross bb0c58e134 ggml: skip cublasGemmBatchedEx during graph reservation
cublasGemmBatchedEx fails during graph capture when pool allocations
return fake pointers. This is triggered when NUM_PARALLEL is greater
than 1 for models like gemma4 that use batched matmuls. Skip it
during reservation since the memory tracking is already handled by
the pool allocations.

Fixes #15249
2026-04-03 12:41:09 -07:00
Devon Rifkin 036ed1b9b5 model/parsers: fix gemma4 arg parsing when quoted strings contain " (#15254)
* model/parsers: fix gemma4 arg parsing when quoted strings contain "

Fixes: #15241

* add more tests, be careful about what we escape

We want Windows-style paths to not get misinterpreted

* fix backslash-quote case, it really should be a literal backslash

h/t to @chathaway-codes for pointing this out!

Co-Authored-By: Charles H <2773397+chathaway-codes@users.noreply.github.com>

---------

Co-authored-by: Charles H <2773397+chathaway-codes@users.noreply.github.com>
2026-04-02 22:52:51 -07:00
Daniel Hiltgen 3536ef58f6 bench: add prompt calibration, context size flag, and NumCtx reporting (#15158)
Add --num-ctx flag to set context size, and report NumCtx in model info
header. Calibrate tokens-per-word ratio during warmup using actual
tokenization metrics from the model, replacing the fixed 1.3 heuristic.
This produces more accurate prompt token counts for --prompt-tokens.

Also add fetchContextLength() to query running model context via /api/ps.
2026-04-02 14:23:53 -07:00
Daniel Hiltgen de9673ac3f tokenizer: add byte fallback for SentencePiece BPE encoding (#15232)
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* tokenizer: add byte fallback for SentencePiece BPE encoding

When BPE merging produces tokens not in the vocabulary, fall back to
encoding each UTF-8 byte as <0xHH> byte tokens instead of silently
dropping the character. Also teach Decode to convert <0xHH> tokens
back to raw bytes.

Fixes #15229, fixes #15231

* tokenizer fixes
2026-04-02 13:04:45 -07:00
Daniel Hiltgen 96b202d34b Add support for gemma4 (#15214)
* bench: add prompt calibration, context size flag, and NumCtx reporting

Add --num-ctx flag to set context size, and report NumCtx in model info
header. Calibrate tokens-per-word ratio during warmup using actual
tokenization metrics from the model, replacing the fixed 1.3 heuristic.
This produces more accurate prompt token counts for --prompt-tokens.

Also add fetchContextLength() to query running model context via /api/ps.

* integration: improve vision test robustness and add thinking tests

Add skipIfNoVisionOverride() to skip vision tests when OLLAMA_TEST_MODEL
is set to a non-vision model. Add Think:false to context exhaustion test
to prevent thinking models from using all context before the test can
measure it. Add third test image (ollama homepage) and replace OCR test
with ImageDescription test using it. Relax match strings for broader
model compatibility. Add TestThinkingEnabled and TestThinkingSuppressed
to verify thinking output and channel tag handling.

* gemma4: add Gemma 4 GGML model support

Add full Gemma 4 model family support (E2B, E4B, 26B MoE, 31B Dense)
for the GGML backend including text, vision, converter, parser, and
renderer.

Text model features:
- Sliding window + full attention with per-layer patterns
- KV sharing across layers with donor map
- Per-layer embeddings (PLE) with learned projections
- MoE routing with RMSNorm + learned scale
- Proportional RoPE with freq_factors for global attention
- Final logit softcapping

Vision model features:
- SigLIP vision encoder with 2D RoPE
- ClippableLinear with input/output clamping via packed v.clamp_data
- Adaptive average pooling with nMerge kernel
- Multi-modal projection with unweighted RMSNorm

Converter:
- Safetensors to GGUF with vision tensor renaming
- Fused MoE gate_up_proj splitting
- Vision patch embedding reshape (HF to Conv2D layout)
- Packed clamp data tensor for ClippableLinear bounds
- Proportional RoPE freq_factors generation

Also includes:
- BackendGet() on ml.Tensor for reading weight tensor data
- Q6_K CUDA get_rows kernel support
- MoE-aware ffn_down quantization layer counting
- Gemma4 parser with tool calling and thinking support
- Gemma4 renderer with structured tool format
- Architecture-based auto-detection of renderer/parser/stop tokens
- Integration test gemma4 model list additions

* gemma4: add audio support with USM conformer encoder

Add audio encoding for Gemma 4 using the USM conformer architecture:
- Converter: audio tensor mapping, SSCP/conformer/embedder name replacements,
  softplus repacker for per_dim_scale, F32 enforcement for conv weights
- GGML backend: Conv1DDW and PadExt tensor ops
- Audio encoder: SSCP Conv2D, 12 conformer blocks (FFW + block-local
  attention with relative position embeddings + LightConv1d + FFW),
  output projection, audio-to-text embedding projector
- Audio preprocessing: WAV decode, mel spectrogram, FFT (pure Go)
- Model wiring: WAV detection, audio token handling, unified PostTokenize

Correctly transcribes "why is the sky blue" from test audio.

* integration: add gemma4 audio tests including OpenAI API coverage

Test audio transcription and response via the Ollama native API, plus
two new tests exercising the OpenAI-compatible endpoints:
- /v1/audio/transcriptions (multipart form upload)
- /v1/chat/completions with input_audio content type

All tests use capability checks and skip models without audio support.

* gemma4: add OpenAI audio API support and capability detection

- Add CapabilityAudio and detect from audio.block_count in GGUF
- Add /v1/audio/transcriptions endpoint with TranscriptionMiddleware
- Add input_audio content type support in /v1/chat/completions
- Add TranscriptionRequest/Response types in openai package

* gemma4: add audio input support for run command

- /audio toggle in interactive mode for voice chat
- Platform-specific microphone recording (AVFoundation on macOS,
  PulseAudio/ALSA on Linux, WASAPI on Windows)
- Space to start/stop recording, automatic chunking for long audio

* gemma4: add transcribe command (ollama transcribe MODEL)

- Interactive mode with readline prompt and slash commands
- Non-interactive mode for piped audio or record-until-Ctrl+C
- Chunked streaming transcription for long recordings
- Word-wrapped output matching run command style

* gemma4: add parser, renderer, and integration test plumbing

* gemma4: fix renderer to emit BOS token

* gemma4: add OpenAI audio transcription API and input_audio support

* gemma4: update converter for new weight drop naming

* gemma4: add per_expert_scale to MoE router and fix moe_intermediate_size config

* gemma4: rewrite renderer to match HF Jinja2 template exactly

Fix 8 bugs found by building 55 reference tests verified against the
HF Jinja2 chat template (VERIFY_JINJA2=1 shells out to Python):

- Tool responses use separate <|turn>tool turns (not inline tags)
- Tool calls emitted before content in assistant messages
- Thinking content stripped from assistant history (strip_thinking)
- User, tool, and system content trimmed (template does | trim)
- Empty system message still emits system turn (check role, not content)
- Nested object properties rendered recursively with required field
- Array items specification rendered for array-type properties
- OBJECT/ARRAY type-specific rendering comma logic matches template

Also adds Required field to api.ToolProperty for nested object schemas,
replaces old gemma4_test.go with comprehensive gemma4_reference_test.go,
and commits the Jinja2 template as testdata for verification.

* gemma4: fix MoE fused gate_up split and multiline tool-call arg parsing

- Text MoE: split `ffn_gate_up_exps` into contiguous `[gate|up]` halves instead of stride-2 slices.
- Parser: escape control characters in `<|"|>...<|"|>` string literals when converting tool-call args to JSON.
- Fixes warnings like `invalid character '\n' in string literal` for multiline tool arguments.
- Add Gemma4 parser regressions for multiline tool-call args and `gemma4ArgsToJSON`.

* cmd: simplify audio input to dropped file attachments

* gemma4: use full SWA memory for better cache reuse

* gemma4: initialize clamps after backend load

* convert: align gemma4 audio tensor renames with llama.cpp

* Remove redundant comments in gemma4 vision model

* Format Gemma4 MoE block field alignment

* use 4096 kvcache.NewSWAMemCache

* convert: support new Gemma4 audio_tower tensor naming (#15221)

Co-authored-by: jmorganca <jmorganca@gmail.com>

* fix integration test defaults for audio

* review comments and lint fixes

* remove unused audio/video files

---------

Co-authored-by: jmorganca <jmorganca@gmail.com>
2026-04-02 11:33:33 -07:00
Devon Rifkin 79865e6c5a app: use the same client for inference and other requests (#15204)
Previously we were accidentally using different clients/UAs depending on
whether it was an inference call or a different call. This change makes
them consistent, other than the timeout being different.
2026-04-02 11:07:50 -07:00
Parth Sareen 5ab10d347a app: add launch page for a simple way to launch integrations (#15182) 2026-04-02 10:31:19 -07:00
Eva H a8292dd85f launch: replace deprecated OPENAI_BASE_URL with config.toml profile for codex (#15041) 2026-04-01 11:43:23 -04:00
Daniel Hiltgen cb0033598e tokenizer: add SentencePiece-style BPE support (#15162)
* tokenizer: add SentencePiece-style BPE support

Add WithSentencePieceNormalizer option to BytePairEncoding for models
that use BPE with SentencePiece-style space markers (space to/from
U+2581).

NewBytePairEncoding is unchanged; the new NewBytePairEncodingWithOptions
constructor accepts BPEOption functions. Decoding handles the reverse
mapping of U+2581 back to spaces.

* review comments
2026-03-31 17:00:36 -07:00
Daniel Hiltgen 4d14b0ff92 mlx: respect tokenizer add_bos_token setting in pipeline (#15185)
Replace hardcoded Encode(prompt, true) with
Encode(prompt, r.Tokenizer.AddBOS()) so the pipeline respects each
model's tokenizer configuration.

Models with add_bos_token=true (gemma3, llama): unchanged, tokenizer
still prepends BOS.

Models with bos_token=null (qwen3, qwen3.5): unchanged, the BOS
guard (vocab.BOS >= 0) already prevented prepending regardless of
the flag.

This aligns the pipeline with the /v1/tokenize endpoint which already
uses Tokenizer.AddBOS().
2026-03-31 16:46:30 -07:00
Parth Sareen d9cb70c270 docs: update pi docs (#15152) 2026-03-31 16:37:55 -07:00
Jeffrey Morgan 31f968fe1f cmd: set OpenCode default model in config (#15127)
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2026-03-29 12:11:36 -07:00
Jeffrey Morgan b7bda92d52 model: add qwen3-next compatibility for legacy ssm_in projections (#15133) 2026-03-29 11:50:47 -07:00
Parth Sareen 8e54823fd3 revert context length warnings change (#15121) 2026-03-28 16:43:59 -07:00
Parth Sareen 7c8da5679e launch: improve multi-select for already added models (#15113) 2026-03-28 13:44:40 -07:00
Parth Sareen 6214103e66 launch: auto-install pi and manage web-search lifecycle (#15118) 2026-03-28 13:06:20 -07:00
Patrick Devine 9e7cb9697e mlx: fix vision capability + min version (#15106)
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2026-03-27 17:09:28 -07:00
Bruce MacDonald 3824e380a8 server: preserve raw manifest bytes during pull (#15104)
pullModelManifest unmarshals the registry response into a Go struct
then re-marshals with json.Marshal before writing to disk. When the
registry's JSON formatting or field ordering differs from Go's
output, the local SHA256 won't match the registry's
Ollama-Content-Digest header, causing false "out of date" warnings.

Preserve the raw bytes from the registry response and write them
directly to disk so the local manifest is byte-for-byte identical
to what the registry serves.
2026-03-27 15:42:31 -07:00
Devon Rifkin c9b2dcfc52 anthropic: fix empty inputs in content blocks (#15105)
* anthropic: fix empty inputs in content blocks

When we switched to `api.ToolCallFunctionArguments`, `omitempty` stopped
doing what we were relying on it for before. This would cause non-tool
content blocks to have an `"input": {}` field, which doesn't match our
old behavior.

* use omitzero instead
2026-03-27 15:41:27 -07:00
Parth Sareen b00bd1dfd4 launch: skip context length warning for MLX models and show model name (#15102) 2026-03-27 15:01:33 -07:00
Jesse Gross ac83ac20c4 anthropic: fix KV cache reuse degraded by tool call argument reordering
Use typed structs for tool call arguments instead of map[string]any to
preserve JSON key order, which Go maps do not guarantee.
2026-03-27 14:30:16 -07:00
Bruce MacDonald e7ccc129ea app: fix false "out of date" model warnings (#15101)
The staleness check compared the local manifest digest (SHA256 of the
file on disk) against the registry's Ollama-Content-Digest header.
These never matched because PullModel re-serializes the manifest JSON
before writing, producing different bytes than the registry's original.

The fallback comparison (local modified_at vs upstream push time) was
also broken: the generated TypeScript Time class discards the actual
timestamp value, so Date parsing always produced NaN.

Fix by moving the staleness comparison server-side where we have
reliable access to both the local manifest file mtime and the upstream
push time. The /api/v1/model/upstream endpoint now returns a simple
`stale` boolean instead of raw digests for the frontend to compare.

Also adds User-Agent to the CORS allowed headers for dev mode.
2026-03-27 14:15:10 -07:00
Jeffrey Morgan 69ed0c2729 parsers: qwen3.5 streaming tool-call parsing and add regression test (#15098) 2026-03-27 14:04:14 -07:00
Alfredo Matas 1cefa749aa model/parsers: close think block if tool block starts in Qwen3.5 (#15022) 2026-03-27 11:28:34 -07:00
Daniel Hiltgen aec2fef95d ci: harden cuda include path handling (#15093)
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On windows we can get multiple include dirs, so find where the headers are then
copy from that location.
2026-03-27 07:57:07 -07:00
Eva H 366625a831 launch: warn when server context length is below 64k for local models (#15044)
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A stop-gap for now to guide users better. We'll add more in-depth recommendations per integration as well.

---------

Co-authored-by: Parth Sareen <parth.sareen@ollama.com>
2026-03-27 00:15:53 -07:00
Daniel Hiltgen 516ebd8548 ci: include mlx jit headers on linux (#15083)
* ci: include mlx jit headers on linux

* handle CUDA JIT headers
2026-03-26 23:10:07 -07:00
Parth Sareen f567abc63f tui: update chat title (#15082) 2026-03-26 18:06:53 -07:00
Eva H 1adfc27f04 launch/vscode: prefer known vs code paths over code on PATH (#15073) 2026-03-26 18:06:28 -04:00
Parth Sareen 4a2b9f9dbc launch: hide cline integration (#15080) 2026-03-26 14:33:43 -07:00
Parth Sareen e46b67a6cc launch: hide vs code (#15076)
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2026-03-26 13:52:50 -07:00
Eva H c000afe76c doc: update vscode doc (#15064)
---------

Co-authored-by: ParthSareen <parth.sareen@ollama.com>
2026-03-26 13:45:48 -07:00
Jesse Gross 9d7b18f81e mlxrunner: combine setStateRaw and setStateDetached into setState 2026-03-26 13:32:11 -07:00
Jesse Gross 4f5999fd3f mlxrunner: schedule periodic snapshots during prefill
Add periodic snapshots every 8k tokens and near the end of the prompt
so that long prompts can be partially restored and thinking/generation
can be retried without full reprocessing.
2026-03-26 13:32:11 -07:00
Jesse Gross ac5f0dbb6a mlxrunner: improve eviction and LRU tracking
Update LRU last used time just on the nodes that actually used
during processing rather than all snapshots along the path. This
allows eviction to remove nodes more accurately so we can avoid
other heuristics to auto-merge nodes.
2026-03-26 13:32:11 -07:00
Jesse Gross d1151e18a1 mlx: fix KV cache snapshot memory leak
mlx.Copy shares the backing buffer with its source (via
copy_shared_buffer) rather than allocating independent storage.
When used to snapshot a slice of the KV cache, the snapshot array
holds the entire original cache buffer alive through the shared
data pointer — even after eval detaches the computation graph.

Replace Copy with Contiguous in Snapshot and Split. Contiguous
allocates a compact buffer when the source buffer is significantly
larger than the logical slice (Contiguous::eval checks
buffer_size > nbytes + 16384), which is always the case for KV
cache slices.
2026-03-25 17:26:34 -07:00
rick ebbce136c7 ggml: force flash attention off for grok 2026-03-25 16:15:49 -07:00
Devon Rifkin 26b9f53f8e api/show: overwrite basename for copilot chat (#15062)
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Copilot Chat prefers to use `general.basename` in the built-in Ollama
integration, but this name isn't usually shown directly to users (and
there may be many models that share this name). Instead we pass back
`req.Model`, which for this extension is the value that we return from
`/api/tags`
2026-03-25 14:02:22 -07:00
Eva H 7575438366 cmd: ollama launch vscode (#15060)
Co-authored-by: Parth Sareen <parth.sareen@ollama.com>
2026-03-25 16:37:02 -04:00
Eva H 7d7c90d702 tui: add left arrow back navigation in model selector (#14940) 2026-03-25 11:53:48 -07:00
Daniel Hiltgen 4fda69809a ci: fix windows cgo compiler error (#15046)
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2026-03-24 16:45:36 -07:00
Daniel Hiltgen c9b5da6b0c integration: improve ability to test individual models (#14948)
* integration: improve ability to test individual models

Add OLLAMA_TEST_MODEL env var to run integration tests against a
single model.

Enhance vision tests: multi-turn chat with cached image tokens, object
counting, spatial reasoning, detail recognition, scene understanding, OCR, and
multi-image comparison.

Add tool calling stress tests with complex agent-style prompts, large
system messages, and multi-turn tool response handling.

* review comments
2026-03-24 14:28:23 -07:00
Patrick Devine de5cb7311f mlx: add mxfp4/mxfp8/nvfp4 importing (#15015)
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This change allows importing bf16 and converting to mxfp4/mxfp8/nvfp4
and also importing fp8 and converting directly to mxfp8.
2026-03-24 13:45:44 -07:00
Jesse Gross 95ee7fbd29 mlxrunner: panic on double unpin 2026-03-23 17:44:19 -07:00
Jesse Gross ec55536734 mlxrunner: show time since last used in cache dump tree 2026-03-23 17:44:19 -07:00
Jesse Gross 77491439c2 mlxrunner: support partial match on pure transformer caches
Previously, a partial match within a node's edge would truncate the path
to the parent snapshot - effectively making all cache types behave as
recurrent caches. Caches with only transformer layers can rewind to
arbitrary boundary so this restores this capability to improve cache
hits
2026-03-23 17:44:19 -07:00
Parth Sareen b166b36cd2 docs: update Claude Code with Telegram guide (#15026) 2026-03-23 16:31:21 -07:00
Daniel Hiltgen c2b0bb7a52 mlx: update as of 3/23 (#14789)
* mlx: update to HEAD on 3/23

Also fixes a few misc vendoring bugs uncovered with this first update.
This also renames the version files to make them clearer.

* CUDA Fast Gated Delta kernel

* mlx: detect eval errors and panic

On model errors or missing kernels, don't mask the error, bubble it up.
2026-03-23 11:28:44 -07:00
Bruce MacDonald 22c2bdbd8a docs: nemoclaw integration (#14962)
---------

Co-authored-by: ParthSareen <parth.sareen@ollama.com>
2026-03-20 15:27:37 -07:00
Bruce MacDonald 6df6d097d9 launch: skip openclaw gateway health check when no daemon install (#14984) 2026-03-20 15:20:14 -07:00
Jesse Gross d7c176ab91 llm, mlxrunner: fix done channel value consumed by first receiver
Receiving from a buffered chan error consumes the value, so only the
first caller (WaitUntilRunning, HasExited, or Close) sees the signal.
Subsequent receivers block or take the wrong branch. Replace with a
closed chan struct{} which can be received from any number of times,
and store the error in a separate field.
2026-03-19 17:44:28 -07:00
Jesse Gross 0ff7d724ff mlx: fix subprocess log deadlock
The stderr reader used bufio.Scanner which has a 64KB max line size.
If the subprocess wrote a line exceeding this limit, the scanner would
stop reading, the OS pipe buffer would fill, and the subprocess would
deadlock.

Replace the scanner with a statusWriter that wraps io.Copy. The writer
forwards all stderr to os.Stderr while capturing the last short line
(≤256 bytes) for error reporting, avoiding both the deadlock and the
need to buffer arbitrarily long lines.
2026-03-19 17:44:28 -07:00
Devon Rifkin 46cb7795e1 add ability to turn on debug request logging (#14106)
If `OLLAMA_DEBUG_LOG_REQUESTS` is set, then on server startup a temp
folder will be created. Upon any inference request, the body will be
logged to a file in this folder, as well as a small shell script to
"replay" the request using cURL.

This is just intended for debugging scenarios, not as something to turn
on normally.
2026-03-19 17:08:17 -07:00
Bruce MacDonald 126d8db7f3 parsers: robust xml tool repair (#14961)
Previous xml repair for glm was a good start, but we need to go further and repair any incorrect open or closing tags

Co-authored-by: Dongluo Chen <dongluo.chen@gmail.com>
2026-03-19 11:24:48 -07:00
Eva H 3f3a24b418 app: fix desktop app stuck loading when OLLAMA_HOST is an unspecified bind address (#14885) 2026-03-19 12:57:57 -04:00
Jesse Gross 96e36c0d90 mlxrunner: share KV cache across conversations with common prefixes
Enable multiple conversations to reuse cached computations when they
share token prefixes (e.g. the same system prompt). A prefix trie
tracks shared regions so switching between conversations only
recomputes tokens that diverge. Inactive conversation state is paged
from active GPU memory to other memory and restored on demand, with LRU
eviction to keep memory usage bounded.
2026-03-18 16:06:33 -07:00
Jesse Gross 6f8ddbb26b mlxrunner: fix Slice(0, 0) returning full dimension instead of empty
Slice used cmp.Or to resolve a zero stop value to the dimension size,
intended to support open-ended slices like a[i:]. This made Slice(0, 0)
indistinguishable from Slice(), so any slice with a zero stop would
silently include the entire dimension instead of being empty.

Replace cmp.Or with an explicit End sentinel and resolve negative
indices against the dimension size, matching Python/PyTorch semantics.
2026-03-18 16:06:33 -07:00
Eva H b5e7888414 cmd/launch: skip redundant config writes when model unchanged (#14941) 2026-03-18 17:36:52 -04:00
Parth Sareen eab4d22269 docs: update claude code and openclaw for web search (#14922) 2026-03-18 14:18:49 -07:00
Bruce MacDonald 5759c2d2d2 launch: fix openclaw not picking up newly selected model (#14943)
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Sessions with a stale model field were not updated when the primary
changed, so the old model continued to be used.
2026-03-18 13:20:10 -07:00
Bruce MacDonald 42b1c2642b docs: update minimax-m2.5 references to m2.7 (#14942) 2026-03-18 12:59:28 -07:00
Bruce MacDonald 727d69ddf3 tui: fix signin on headless Linux systems (#14627)
Defensively handle environments without a display server to ensure signin remains usable on headless VMs and SSH sessions.

- Skip calling xdg-open when neither DISPLAY nor WAYLAND_DISPLAY is set, preventing silent failures or unexpected browser handlers
- Render the signin URL as plain text instead of wrapping it in OSC 8 hyperlink escape sequences, which can be garbled or hidden by terminals that don't support them
2026-03-18 11:11:17 -07:00
Jesse Gross f622b0c5fc launch: disable claude attribution header to preserve KV cache
Claude Code sends an x-anthropic-billing-header that changes on every
request. This is embedded in the system prompt and consequently
breaks the KV cache for every request. Given the size of the prompts
that Claude Code usees, this has significant performance impact.
2026-03-17 20:48:03 -07:00
Bruce MacDonald 5d0000634c cmd/launch: check for both npm and git before installing OpenClaw (#14888)
The OpenClaw installer requires git in addition to npm. Update the
dependency check to detect both and provide specific install guidance
for whichever dependencies are missing.
2026-03-17 18:20:05 -07:00
Parth Sareen 676d9845ba launch: register websearch for openclaw (#14914)
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2026-03-17 15:03:15 -07:00
Devon Rifkin e37a9b4c01 cloud_proxy: for the web_search legacy path, flush on newlines (#14897)
`WebSearchAnthropicWriter` expects a single object per write. The new
transparent proxy will instead send it whatever bytes it sees. This
cloud-model + local-orchestration + cloud-search is a temporary code
path, so instead of making the web search code more robust to this, I
put an adapter in the middle that will flush line-by-line to preserve
the old behavior.
2026-03-17 13:30:17 -07:00
Patrick Devine d727aacd04 mlx: quantized embeddings, fast SwiGLU, and runtime fixes (#14884)
Add QuantizedEmbedding and EmbeddingLayer interface so models can
use quantized embedding weights and expose tied output projections.
This change updates gemma3, glm4_moe_lite, llama, qwen3, and qwen3_5
to use the new interface.
2026-03-17 11:21:38 -07:00
Patrick Devine fa69b833cd mlx: add prequantized tensor packing + changes for qwen35 (#14878)
This change adds a tensorImportTransform interface for model-specific
tensor transformations during safetensors import. This allows importing
and modifying the standard HF based weights as well as the mlx-community
derived pre-quantized safetensors repos to be directly
imported into `ollama create`. Right now this only works with Qwen3.5
importing which does tensor renaming, norm weight shifting (it
adds +1 to each value of the norm vectors), conv1d transposition,
and casts to BF16s for F32 based vectors.
2026-03-17 11:21:18 -07:00
Jesse Gross bbbad97686 sched: Model eviction for MLX
MLX runners (image generation and LLM) previously bypassed the
scheduler's standard load path via a separate loadMLX method. This meant
they skipped VRAM fitting checks and couldn't participate in model
eviction.

Now all model types flow through the same load function. Model eviction
for MLX is based on weights as KV cache and compute graph are dynamic.
This means that eviction does not take into account the worst case
memory and models can still compete for memory but it is a significant
improvement.
2026-03-16 17:40:29 -07:00
Parth Sareen bcf6d55b54 launch: fix web search, add web fetch, and enable both for local (#14886)
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2026-03-16 16:26:19 -07:00
easonysliu 810d4f9c22 runner: fix swallowed error in allocModel graph reservation
In allocModel(), the first call to reserveWorstCaseGraph(true) had its
error silently discarded — `return nil` was used instead of `return err`.

This meant that if the prompt-sized graph reservation failed (e.g. due
to insufficient memory), the error was swallowed, allocModel reported
success, and the model appeared to load correctly. Subsequent inference
would then fail in unexpected ways because the worst-case graph was
never properly reserved.

Fix: return the actual error so the caller can handle the failure
(retry with reduced parallelism, report OOM, etc.).

Co-Authored-By: Claude (claude-opus-4-6) <noreply@anthropic.com>
2026-03-16 15:48:45 -07:00
Bruce MacDonald 856c047a6c cmd/launch: skip --install-daemon when systemd is unavailable (#14883)
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In container environments without systemd, `openclaw onboard
--install-daemon` exits non-zero because it cannot create a systemd
user service. This causes `ollama launch openclaw` to abort even
though the gateway can be started as a foreground child process.

Only pass --install-daemon when systemd user services are reachable
(Linux with /run/systemd/system present and XDG_RUNTIME_DIR set).
On all other platforms the flag is still included by default.
2026-03-16 13:50:04 -07:00
Daniel Hiltgen 79c1e93c00 bench: improve benchmarking tool (#14240)
New features:
- Warmup phase to eliminate cold-start outliers
- time-to-first-token measured in each epoch
- VRAM/memory tracking to identify CPU spillover
- Controlled prompt length
- Defaults to 6 epochs and 200 tokens max

Benchstat fixes:
- ns/request instead of ns/op — non-standard unit created a separate group instead of grouping with timing metrics
- Token count as the N field — benchstat interprets N as iteration count for statistical weighting, not as a token count
2026-03-15 11:47:31 -07:00
Parth Sareen f8b657c967 cmd/launch: add guards for headless mode (#14837) 2026-03-14 00:10:02 -07:00
Bruce MacDonald 10fefe0d57 config: use native OpenClaw Ollama onboarding (#14829)
OpenClaw now accepts the Ollama onboarding flags directly upstream, so rely on its wizard state instead of the legacy integration onboarding flag.

Update first-run setup to pass the Ollama auth and model flags during onboarding, perform a best-effort update before onboarding when needed, and drop the stale test that asserted persistence of the old onboarding flag.
2026-03-13 16:28:40 -07:00
Daniel Hiltgen 2f9a68f9e9 rocm: doc driver constraints (#14833) 2026-03-13 15:53:35 -07:00
Bruce MacDonald 3980c0217d server: decompress zstd request bodies in cloud passthrough middleware (#14827)
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When a zstd-compressed request (e.g. from Codex CLI) hits /v1/responses
with a cloud model the request failed.

Fix by decompressing zstd bodies before
model extraction, so cloud models are detected and proxied directly
without the writer being wrapped.
2026-03-13 15:06:47 -07:00
Parth Sareen 870599f5da launch: remove warning for default policy (#14830) 2026-03-13 15:01:38 -07:00
Bruce MacDonald abf8e8e9c8 middleware: handle non-JSON error responses gracefully (#14828)
writeError in both OpenAI and Anthropic middleware writers would return
a raw json.SyntaxError when the error payload wasn't valid JSON (e.g.
"invalid character 'e' looking for beginning of value"). Fall back to
using the raw bytes as the error message instead.

Also use the actual HTTP status code rather than hardcoding 500, so
error types map correctly
2026-03-13 14:50:49 -07:00
Shivam Tiwari f3f31a8192 anthropic: close thinking block before tool_use when no text in between (#14825)
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Root cause: StreamConverter.Process() only incremented contentIndex when
closing a thinking block if text content was present. When a model emitted
thinking followed directly by a tool_use block (no text in between),
thinkingDone was never set and contentIndex was not incremented, causing the
tool_use content_block_start to reuse index 0. Clients expecting sequential
indices would then fail to find the tool content block.

Fix: In the tool call loop, close any open thinking block (thinkingStarted &&
!thinkingDone) and increment contentIndex before opening the tool_use block,
mirroring the existing logic that closes an open text block.

Fixes #14816
2026-03-13 13:12:05 -07:00
Devon Rifkin 9e7ba835da cmd: still populate ollama ls when using ollama run <model:cloud> (#14824)
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This is temporary until `api/tags` supports cloud natively
2026-03-13 12:24:45 -07:00
Parth Sareen 347f17b8d1 launch: add compact window for claude code (#14823) 2026-03-13 12:09:23 -07:00
Devon Rifkin 081b9eb423 api/create: always propagate :cloud source for cloud models (#14822)
Otherwise, using `/save` would try to run the local model instead
2026-03-13 11:58:00 -07:00
Parth Sareen bb867c6fdb launch: fix headless --yes integration flow and policy scoping (#14815) 2026-03-13 11:45:36 -07:00
Cadu 81f4506a61 docs: document reasoning_effort support in OpenAI-compatible API (#14821)
Add reasoning_effort and reasoning to the supported features and
request fields for /v1/chat/completions. These fields control
thinking on thinking-capable models but were previously undocumented.

Closes #14820
2026-03-13 10:57:14 -07:00
Parth Sareen 76925f1284 cmd: TUI model ordering (#14814) 2026-03-13 10:19:22 -07:00
Devon Rifkin f676231de9 server: remove experimental aliases support (#14810)
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Parth Sareen af5f7c0a9e cmd: refactor tui and launch (#14609) 2026-03-12 18:39:06 -07:00
Daniel Hiltgen a6b27d776b ci: fix missing windows zip file (#14807)
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Use 7z compression (better compression rate) if found in path.  That
alone isn't sufficient to get us under 2G, so MLX is now split out as a
discrete download.  Fix CI so it will fail if artifacts fail to upload.
2026-03-12 16:14:00 -07:00
Daniel Hiltgen 539741199e mlx: perf improvements (#14768)
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* mlx: perf improvements

Fix nn.go to call mlx_fast_layer_norm instead of manually implementing (mean,
subtract, variance, rsqrt, multiply, add — 6 ops)

Fix llama.go, gemma3.go to remove RepeatKV to tile K/V tensors to match the Q
head count, since scaled_dot_product_attention natively handles GQA (it just
requires n_q_heads % n_kv_heads == 0)

* review comments
2026-03-12 12:01:28 -07:00
Eva H 8f45236d09 middleware: enable local tool model for web search (#14787) 2026-03-11 17:51:39 -04:00
Parth Sareen 97013a190c openai: split mixed thinking stream chunks via ToChunks (#14648) 2026-03-11 14:21:29 -07:00
Daniel Hiltgen c222735c02 mlx: only log load errors when MLX is needed (#14764)
This suppresses irrelevant/noisy errors in the GGML runner.
2026-03-11 10:31:31 -07:00
Daniel Hiltgen 87d21c7fc0 MLX: harden for init failures (#14777)
The CLI now links to the lazy-load MLX code, but that still happens in
init functions.  On internal MLX errors, the CLI exits before it has a
chance to start.  This change re-wires the MLX error handling so it
doesn't exit by default.  The MLX based runners currently expect exits
on failure, so they re-initialize the default error handling.  We can
refine error handling for better go stack traces in the future.
2026-03-10 22:52:23 -07:00
Jeffrey Morgan 54e05172a0 Revert "runner: add token history sampling parameters to ollama runner (#14537)" (#14776)
This reverts commit 86513cb697.
2026-03-10 21:07:52 -07:00
Parth Sareen 464186e995 config: qwen3.5 recommendations (#14758) 2026-03-10 18:04:57 -07:00
Devon Rifkin 8c4d5d6c2f cloud_proxy: send ollama client version (#14769)
This was previously included in the user agent, and we've made use of it
in the past to hotpatch bugs server-side for particular Ollama versions.
2026-03-10 15:53:25 -07:00
Parth Sareen bc72b14016 docs: update claude code docs (#14770) 2026-03-10 15:52:41 -07:00
Parth Sareen 61086083eb server: add experimental web search and web fetch routes (#14753) 2026-03-09 21:52:12 -07:00
Daniel Hiltgen 62d1f01ab4 ci: Fix windows build (#14754)
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Instead of relying on sh for wildcard, do it in Go for better windows
compatibility.
2026-03-09 19:27:59 -07:00
Daniel Hiltgen 10e51c5177 MLX: add header vendoring and remove go build tag (#14642)
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* prefer rocm v6 on windows

Avoid building with v7 - more changes are needed

* MLX: add header vendoring and remove go build tag

This switches to using a vendoring approach for the mlx-c headers so that Go
can build without requiring a cmake first.  This enables building the new MLX
based code by default.  Every time cmake runs, the headers are refreshed, so we
can easily keep them in sync when we bump mlx versions.  Basic Windows
and Linux support are verified.

* ci: harden for flaky choco repo servers

CI sometimes fails due to choco not actually installing cache.  Since it just speeds up the build, we can proceed without.

* review comments
2026-03-09 17:24:45 -07:00
Patrick Devine 3e06bde643 mlx: get parameters from modelfile during model creation (#14747) 2026-03-09 15:33:24 -07:00
Eva H 6be2de8214 app: auto update should be enabled when reset to defaults (#14741) 2026-03-09 15:02:36 -04:00
Daniel Hiltgen ebb1b9ec14 rocm: update linux to v7.2 (#14391)
* rocm: update linux to v7.2

* review comments
2026-03-09 08:26:55 -07:00
Patrick Devine d126467d5d x/mlxrunner: replace sampler interface chain with single stateful Sampler (#14652)
- Collapse MLX sampling state into a single sample.Sampler struct (options + history).
- Replace interface-based sampler chain (TopP, TopK, penalty, etc.) with function-based transforms.
- Update request/pipeline wiring to use *sample.Sampler, seed history from prompt tokens, and append generated tokens each step.
- Implement top_p, min_p, repeat_penalty, and frequency_penalty
2026-03-07 17:50:57 -08:00
Devon Rifkin afb4c62fbf cloud_proxy: handle stream disconnects gracefully (#14685)
Previously we were printing out bad errors for expected cases like
clients disconnecting. Now we only debug log when that happens (which
still might help in cases where we're figuring out why an integration
isn't working). For other errors, we print out a proper warning now
2026-03-06 19:18:52 -08:00
Patrick Devine e790dc435b mlx: int4 groupsize 64 (#14682)
Change affine 4bit integers to use groupsize 64
2026-03-06 16:39:47 -08:00
Daniel Hiltgen 288077c3a3 build: smarter docker parallelism (#14653)
Our Dockerfile leverages parallel stages for more efficient builds.  However,
our old parallel settings were naive and lead to under/over utilization
depending on the capabilities of your build system.

This change switches to using Ninja for all our docker cmake builds to leverage
its smarter parallel logic.  We tell Ninja to target a load of nproc so each of
the build stages will share the load on the system aiming for full CPU use
without oversaturation.

The GPU parallelism settings are also adjusted to 4 to avoid a long-tail for
the last few GPU targets as they work through the long list of GPU
architectures.

This also fixes the Dockerfile to move Vulkan install to just the stage that
needs it instead of blocking most other GPU installs.  This should speed up CI
which always has a clean build cache.
2026-03-06 16:36:22 -08:00
Daniel Hiltgen 4425c54eda create: fix localhost handling (#14681) 2026-03-06 16:35:58 -08:00
Michael Yang 778899a5d2 docs: format compat docs (#14678) 2026-03-06 14:53:17 -08:00
Jeffrey Morgan 4eab60c1e2 Reapply "don't require pulling stubs for cloud models" again (#14608)
* Revert "Revert "Reapply "don't require pulling stubs for cloud models"" (#14606)"

This reverts commit 39982a954e.

* fix test + do cloud lookup only when seeing cloud models

---------

Co-authored-by: ParthSareen <parth.sareen@ollama.com>
2026-03-06 14:27:47 -08:00
Bruce MacDonald 1af850e6e3 parsers: repair unclosed arg_value tags in GLM tool calls (#14656)
GLM models sometimes omits </arg_value> closing tags in tool call XML, causing xml.Unmarshal to fail with "element <arg_value> closed by </tool_call>".

This is a known issue across the GLM family.

Sanitize the input to fix closing arg_key values so encoding/xml can handle it.
2026-03-06 14:08:34 -08:00
Parth Sareen 9b0c7cc7b9 cmd: override stale entries for context window pi (#14655)
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2026-03-05 16:30:24 -08:00
Daniel Hiltgen 6928630601 mlx: prevent remote creation mismatch (#14651)
If the user is pointing at a remote OLLAMA_HOST, fail experimental safetensor
based create operations as we only support local creation currently.
2026-03-05 14:59:00 -08:00
Parth Sareen 9896e3627f cmd/config: fix cloud model limit lookups in integrations (#14650)
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2026-03-05 13:57:28 -08:00
Bruce MacDonald 15732f0ea7 cmd: use native Ollama API endpoint for OpenClaw (#14649)
Remove the /v1 suffix from the OpenClaw provider baseUrl so it uses
the native Ollama API instead of the OpenAI-compatible endpoint. The
/v1 endpoint my break tool calling in OpenClaw.
2026-03-05 13:29:17 -08:00
Parth Sareen 562c76d7cc cmd: add qwen3.5 context length for launch (#14626)
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2026-03-04 14:10:52 -08:00
Parth Sareen 122c68c151 server: loosen thinking level constraint (#14625) 2026-03-04 13:42:18 -08:00
Jeffrey Morgan 82848a7806 model: fix renderer and parser for qwen3.5 (#14605)
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2026-03-03 20:58:29 -08:00
Jeffrey Morgan 39982a954e Revert "Reapply "don't require pulling stubs for cloud models"" (#14606)
This reverts commit 799e51d419.
2026-03-03 20:56:10 -08:00
Patrick Devine e9f6ea232f Add qwen3.5-next-moe support to MLX runner and models (#14417)
This change adds support for qwen3.5-next-moe models (qwen3-next/qwen3.5-next/qwen3-coder) to the MLX runner. It also:

* introduces recurrent cache support and related MLX ops
* updates pipeline/runner integration and adds tests
* properly quantizes stacked expert tensors
* a Gated Delta Metal kernel for fast SSM inference
* adds new MLX calls for Conv1d, DepthwideConv1d, Contiguous, Exp, Log, SoftmaxAxis
2026-03-03 16:39:22 -08:00
Patrick Devine 110eff01a9 chore: remove old imagegen LLMs models (#14597)
These models are implemented in the x/mlxrunner instead.
2026-03-03 13:23:40 -08:00
Jeffrey Morgan 799e51d419 Reapply "don't require pulling stubs for cloud models"
This reverts commit 97d2f05a6d.
2026-03-03 13:17:10 -08:00
Victor-Quqi e8fcb29586 model/renderers: fix glm-ocr image tags in renderer prompts (#14584) 2026-03-03 12:51:34 -08:00
Jeffrey Morgan 97d2f05a6d Revert "don't require pulling stubs for cloud models (#14574)" (#14596)
This reverts commit 8207e55ec7.
2026-03-03 12:51:23 -08:00
Devon Rifkin 8207e55ec7 don't require pulling stubs for cloud models (#14574)
* don't require pulling stubs for cloud models

This is a first in a series of PRs that will better integrate Ollama's
cloud into the API and CLI. Previously we used to have a layer of
indirection where you'd first have to pull a "stub" model that contains
a reference to a cloud model. With this change, you don't have to pull
first, you can just use a cloud model in various routes like `/api/chat`
and `/api/show`. This change respects
<https://github.com/ollama/ollama/pull/14221>, so if cloud is disabled,
these models won't be accessible.

There's also a new, simpler pass-through proxy that doesn't convert the
requests ahead of hitting the cloud models, which they themselves
already support various formats (e.g., `v1/chat/completions` or Open
Responses, etc.). This will help prevent issues caused by double
converting (e.g., `v1/chat/completions` converted to `api/chat` on the
client, then calling cloud and converting back to a
`v1/chat/completions` response instead of the cloud model handling the
original `v1/chat/completions` request first).

There's now a notion of "source tags", which can be mixed with existing
tags. So instead of having different formats like`gpt-oss:20b-cloud` vs.
`kimi-k2.5:cloud` (`-cloud` suffix vs. `:cloud`), you can now specify
cloud by simply appending `:cloud`. This PR doesn't change model
resolution yet, but sets us up to allow for things like omitting the
non-source tag, which would make something like `ollama run
gpt-oss:cloud` work the same way that `ollama run gpt-oss` already works
today.

More detailed changes:

- Added a shared model selector parser in `types/modelselector`:
  - supports `:cloud` and `:local`
  - accepts source tags in any position
  - supports legacy `:<tag>-cloud`
  - rejects conflicting source tags
- Integrated selector handling across server inference/show routes:
  - `GenerateHandler`, `ChatHandler`, `EmbedHandler`,
    `EmbeddingsHandler`, `ShowHandler`
- Added explicit-cloud passthrough proxy for ollama.com:
  - same-endpoint forwarding for `/api/*`, `/v1/*`, and `/v1/messages`
  - normalizes `model` (and `name` for `/api/show`) before forwarding
  - forwards request headers except hop-by-hop/proxy-managed headers
  - uses bounded response-header timeout
  - handles auth failures in a friendly way
- Preserved cloud-disable behavior (`OLLAMA_NO_CLOUD`)
- Updated create flow to support `FROM ...:cloud` model sources (though
  this flow uses the legacy proxy still, supporting Modelfile overrides
  is more complicated with the direct proxy approach)
- Updated CLI/TUI/config cloud detection to use shared selector logic
- Updated CLI preflight behavior so explicit cloud requests do not
  auto-pull local stubs

What's next?

- Cloud discovery/listing and cache-backed `ollama ls` / `/api/tags`
- Modelfile overlay support for virtual cloud models on OpenAI/Anthropic
  request families
- Recommender/default-selection behavior for ambiguous model families
- Fully remove the legacy flow

Fixes: https://github.com/ollama/ollama/issues/13801

* consolidate pull logic into confirmAndPull helper

pullIfNeeded and ShowOrPull shared identical confirm-and-pull logic.
Extract confirmAndPull to eliminate the duplication.

* skip local existence checks for cloud models

ModelExists and the TUI's modelExists both check the local model list,
which causes cloud models to appear missing. Return true early for
explicit cloud models so the TUI displays them beside the integration
name and skips re-prompting the model picker on relaunch.

* support optionally pulling stubs for newly-style names

We now normalize names like `<family>:<size>:cloud` into legacy-style
names like `<family>:<size>-cloud` for pulling and deleting (this also
supports stripping `:local`). Support for pulling cloud models is
temporary, once we integrate properly into `/api/tags` we won't need
this anymore.

* Fix server alias syncing

* Update cmd/cmd.go

Co-authored-by: Parth Sareen <parth.sareen@ollama.com>

* address comments

* improve some naming

---------

Co-authored-by: ParthSareen <parth.sareen@ollama.com>
2026-03-03 10:46:33 -08:00
Jesse Gross ad16bffc7d mlx: Remove peak memory from the API
This is still in flux so it is better to just log it for now.
2026-03-02 15:56:18 -08:00
Jesse Gross c1e3ef4bcc mlxrunner: Refcount pinned tensors
Otherwise, it is error prone to manage multiple components working
with the same tensor.
2026-03-02 15:56:06 -08:00
Parth Sareen a3093cd5e5 cmd/opencode: rename provider from "Ollama (local)" to "Ollama" (#14566)
The "(local)" qualifier is unnecessary since there's only one Ollama
provider. Existing configs with the old name are migrated automatically;
custom names are left unchanged.
2026-03-02 14:17:18 -08:00
Bruce MacDonald 23d4cad1a2 server: verify digest is not empty on create (#14555)
An empty digest is not a valid digest for an incoming create request. Reject empty digests at the api level.
2026-03-02 13:43:35 -08:00
Jeffrey Morgan 86513cb697 runner: add token history sampling parameters to ollama runner (#14537)
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2026-03-01 19:16:07 -08:00
Jeffrey Morgan 3490e9590b model/qwen3next: avoid crash in in DeltaNet when offloading (#14541)
Co-authored-by: Yossi Ovadia <jabadia@gmail.com>
2026-03-01 18:44:04 -08:00
Jeffrey Morgan 8da09b1e7e qwen3next: add compatibility with imported GGUF models (#14517) 2026-02-28 14:21:42 -08:00
Jesse Gross a60b9adcce mlxrunner: Fix prompt eval timing and count metrics
Only the last token's processing time is included in prompt processing,
giving an artificially high rate. In addition, the number of tokens
only included the tokens that miss the cache, instead of our historic
total tokens.
2026-02-27 17:29:47 -08:00
Jesse Gross a16f96658b mlxrunner: Enforce model context limit
Currently, context length is unbounded - the cache will keep
growing forever independent of the model's trained context
length. This caps it and enforces semantics similar to most
cloud services:
 - Long prompts will result in an error, not truncation.
 - Generation that exceeds the context will be stopped
2026-02-27 17:29:47 -08:00
Jesse Gross 18ab09b431 mlxrunner: Propagate pipeline errors to client via api.StatusError
Errors that occur during pipeline processing are currently only
logged but not sent back to the client. Rather than using HTTP
status codes as we have historically done, this serializes errors
as messages to allow sending them at any time during the stream.
2026-02-27 17:29:47 -08:00
Jesse Gross 638faeac54 mlxrunner: Report actual memory usage from runner
The MLX runner previously reported a static VRAM estimate that was
computed at load time and consisted only of the weights. This is
strictly less than the actual memory usage, as it does not include
the KV cache or compute graph.
2026-02-27 17:29:47 -08:00
Jesse Gross dd5eb6337d mlxrunner: Fix panic on full KV cache hit
When the entire prompt was already cached (e.g. repeated prompt),
findRemaining returned an empty slice, causing FromValues to panic
on an index-out-of-range accessing a zero-length byte slice.

Fix by always keeping at least one token to re-evaluate so the
pipeline can seed token generation. Also reject empty prompts
early rather than panicking.
2026-02-27 11:07:03 -08:00
Patrick Devine 79917cf80b show peak memory usage (#14485) 2026-02-26 18:38:27 -08:00
Parth Sareen cc90a035a0 model/parsers: add stable tool call indexing for glm47 and qwen3 parsers (#14484)
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Jeffrey Morgan d98dda4676 model: fix qwen3 tool calling in thinking (#14477)
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Align Qwen parser behavior with Transformers serve by allowing <tool_call> parsing while still in thinking collection.

Changes:

- qwen3vl: detect <tool_call> before </think> in thinking state and transition to tool parsing

- qwen3: same thinking-state tool detection and partial-tag overlap handling

- tests: update qwen3vl thinking/tool interleaving expectations

- tests: add qwen3 cases for tool call before </think> and split <tool_call> streaming
2026-02-26 16:13:18 -08:00
Eva H d69ddc1edc fix: window app crash on startup when update is pending (#14451)
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2026-02-26 16:47:12 -05:00
Eva H 9bf41969f0 app: fix first update check delayed by 1 hour (#14427)
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2026-02-25 18:29:55 -05:00
Jesse Gross 0f23b7bff5 mlxrunner: Cancel in-flight requests when the client disconnects
Currently, a canceled request can result in computation continuing
in the background to completion. It can also trigger a deadlock
when there is nobody to read the output tokens and the pipeline
cannot continue to the next request.
2026-02-25 14:00:42 -08:00
Jesse Gross 4e57d2094e mlxrunner: Simplify pipeline memory and cache management
Particularly in error cases, it can be difficult to ensure that
all pinned memory is unpinned, MLX buffers are released and cache
state is consistent. This encapsulates those pieces and sets up
proper deferrals so that this happens automatically on exit.
2026-02-25 14:00:42 -08:00
Jeffrey Morgan 7f9efd53df model: add support for qwen3.5-27b model (#14415)
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Jeffrey Morgan da70c3222e model: support for qwen3.5 architecture (#14378)
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2026-02-24 20:08:05 -08:00
Bruce MacDonald 9d902d63ce ggml: ensure tensor size is valid (#14406)
When quantizing tensors during model creation validate that the resulting sizes match what is expected based on the shape.
2026-02-24 21:52:44 -04:00
Daniel Hiltgen f4f0a4a471 update mlx-c bindings to 0.5.0 (#14380)
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* chore: update mlx-c bindings to 0.5.0 (#14303)

* linux: use gcc 11

---------

Co-authored-by: Patrick Devine <patrick@infrahq.com>
2026-02-23 16:44:29 -08:00
Eva H 3323c1d319 app: add upgrade configuration to settings page (#13512) 2026-02-23 18:08:52 -05:00
Jesse Gross f20dc6b698 mlx: don't default to affine quantization for unquantized models
Otherwise the BF16 version of models trigger segfaults when they
call into quantized kernels.
2026-02-23 15:03:53 -08:00
Jeffrey Morgan 4b2ac1f369 model: improvements to LFM architectures (#14368) 2026-02-23 14:38:10 -08:00
Jesse Gross 8daf47fb3a mlxrunner: Fix duplicate log prefixes and reduce log noise
Pass subprocess stdout/stderr through to the parent's stderr directly
instead of re-wrapping each line with slog. The subprocess already
writes structured slog output, so the re-wrapping produced nested
timestamps, levels, and message fields that were hard to read.

Also downgrade verbose KV cache debug logs to trace level.
2026-02-23 14:09:20 -08:00
Eva H 6c980579cd ui: use capability-based detection for web search (#14336) 2026-02-23 15:00:09 -05:00
Jesse Gross 5c73c4e2ee mlxrunner: Simplify KV cache to single-entry prefix matching
The KV cache previously used a tree structure which could
store multiple divergent sequences, which is good for cache
reuse. However, this is typically used in conjunction with
paged attention so each node in the tree can store just a
chunk of the KV cache and they can be stitched together later.
We don't currently do this, so the cache was storing copies of
the full cache for each past sequence.

This redundancy plus the lack of resource limits, caused significant
memory use as a conversation grew. Instead, this changes to store
a single entry for the cache, which can be prefix matched. Although
it is less ideal for multiple users, it largely matches Ollama's
current behavior. It can be improved as additional pieces are fleshed
out.
2026-02-23 09:50:07 -08:00
Jesse Gross 5daf59cc66 mlxrunner: Fix memory leaks with pin/sweep lifecycle management
The previous approach tracked array lifecycles through reference
counting, where each array recorded its inputs and a reference count
that was decremented as dependents were freed. This is not really
necessary as MLX tracks references internally. It is also error
prone as it is easy to create new arrays and forget to free them
when the Go variable goes out of scope.

Instead, we can pin just the arrays we want (typically outputs and
specific intermediates, like the cache). All other arrays are freed
by default when we run sweep. This avoids most causes of memory leaks
while still giving the freedom to save what we want.
2026-02-23 09:50:07 -08:00
Jeffrey Morgan 0ade9205cc models: add nemotronh architecture support (#14356) 2026-02-22 15:09:14 -08:00
Parth Sareen 06edabdde1 cmd/config: install web search plugin to user-level extensions dir (#14362)
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2026-02-22 02:17:03 -08:00
Jeffrey Morgan 8b4e5a82a8 mlx: remove noisy error output from dynamic library loading (#14346)
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The recent change in #14322 added tryLoadByName() which attempts to
load libmlxc.dylib via rpath before searching directories. This is an
optimization for Homebrew installations where rpath is correctly set.

However, when rpath isn't set (which is the common case for app bundle
installations), dlopen fails and the CHECK macro prints an error to
stderr:

  ERROR - dynamic.c:21 - CHECK failed: handle->ctx != NULL

This error is misleading because it's an expected failure path - the
code correctly falls back to searching the executable directory and
loads the library successfully. The error message causes user confusion
and makes it appear that something is broken.

Replace the CHECK macro with a simple return code so the C code fails
silently. The Go code already handles error logging appropriately:
tryLoadByName() fails silently (intentional fallback), while
tryLoadFromDir() logs via slog.Error() when explicit path loading fails.
2026-02-20 23:46:07 -08:00
Parth Sareen 3445223311 cmd: openclaw onboarding (#14344)
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2026-02-20 19:08:38 -08:00
Jeffrey Morgan fa6c0127e6 app: expose server's default context length to UI (#14037)
Parse the default_num_ctx from the server's "vram-based default context"
log line and expose it through the inference compute API. This eliminates
duplicate VRAM tier calculation logic in the frontend.

- Add InferenceInfo struct with Computes and DefaultContextLength
- Rename GetInferenceComputer to GetInferenceInfo
- Handle missing default context line gracefully (older servers)
- Add DefaultContextLength to InferenceComputeResponse
- Update Settings UI to use server's default, disable slider while loading
- Add disabled prop to Slider component (grays out + hides handle)
- Migrate existing users with context_length=4096 to 0 (auto mode)
2026-02-20 18:56:30 -08:00
Patrick Devine 97323d1c68 consolidate the tokenizer (#14327)
This change adds a new x/tokenizer package which includes:
  * New BPE and SentencePiece tokenizers
  * Removing the dependency on the imagegen tokenizers
  * Fixes to multibyte decoding in the pipeline
  * Various correctness and benchmark tests

Not included in this PR is the WordPiece tokenizer for BERT models which will be
added when we add embedding models. The imagegen tokenizers will also be removed in
a follow-up PR.
2026-02-19 15:55:45 -08:00
natl-set 458dd1b9d9 mlx: try loading library via rpath before searching directories (#14322)
The existing code manually searches directories for libmlxc.* and passes
full paths to dlopen, bypassing the binary's rpath. This means MLX
libraries installed via package managers (e.g., Homebrew) aren't found
even when rpath is correctly set at link time.

This change adds a fallback that tries loading via rpath first (using
just the library name), before falling back to the existing directory
search. This follows standard Unix/macOS conventions and works with any
installation that sets rpath.

Fixes library loading on macOS with Homebrew-installed mlx-c without
requiring OLLAMA_LIBRARY_PATH environment variable.

Co-authored-by: Natl <nat@MacBook-Pro.local>
2026-02-19 10:55:02 -08:00
Bruce MacDonald 9d02d1d767 install: prevent partial download script execution (#14311)
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Wrap script in main function so that a truncated partial download doesn't end up executing half a script.
2026-02-18 18:32:45 -08:00
Bruce MacDonald 1a636fb47a cmd: set codex env vars on launch and handle zstd request bodies (#14122)
The Codex runner was not setting OPENAI_BASE_URL or OPENAI_API_KEY, this prevents Codex from sending requests to api.openai.com instead of the local Ollama server. This mirrors the approach used by the Claude runner.

Codex v0.98.0 sends zstd-compressed request bodies to the /v1/responses endpoint. Add decompression support in ResponsesMiddleware with an 8MB max decompressed size limit to prevent resource exhaustion.
2026-02-18 17:19:36 -08:00
Patrick Devine 0759fface9 Revert "chore: update mlx-c bindings to 0.5.0 (#14303)" (#14316)
This reverts commit f01a9a7859.
2026-02-18 17:01:25 -08:00
Parth Sareen 325b72bc31 cmd/tui: default to single-select for editor integrations (#14302)
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Patrick Devine f01a9a7859 chore: update mlx-c bindings to 0.5.0 (#14303) 2026-02-17 16:48:16 -08:00
Patrick Devine 9aefd2dfee model: add qwen3 support to mlxrunner (#14293)
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2026-02-17 13:58:49 -08:00
Patrick Devine d07e4a1dd3 bugfix: better mlx model scheduling (#14290)
This fixes a bug with current MLX based models which don't get loaded/unloaded correctly. The first model currently gets loaded and then subsequent model starts get shunted to the first runner which results in the wrong model being run.
2026-02-17 13:57:05 -08:00
Parth Sareen 8a257ec00a docs: make integrations more discoverable (#14301)
* docs: add Pi integration page

* docs: flatten integration sidebar with expanded subheadings

* docs: add OpenClaw and Claude Code to quickstart
2026-02-17 13:27:25 -08:00
Parth Sareen 2f4de1acf7 cmd: ollama launch always show model picker (#14299) 2026-02-17 12:02:14 -08:00
Parth Sareen ec95c45f70 cmd/config: ollama launch cline CLI (#14294) 2026-02-17 11:37:53 -08:00
Patrick Devine 3a88f7eb20 bugfix: add missing linear layer factory (#14289) 2026-02-16 17:22:20 -08:00
Patrick Devine 0d5da826d4 bugfix: display the parameter count correctly in mlx for ollama show (#14285) 2026-02-16 13:03:34 -08:00
Patrick Devine 9b795698b8 model: add llama3 architecture to mlxrunner (#14277) 2026-02-15 23:06:28 -08:00
Patrick Devine 041fb77639 model: add gemma3 to the mlxrunner (#14276)
This change adds the gemma3 model to the mlxrunner and simplifies some of the quantization
code for loading weights.
2026-02-15 22:47:59 -08:00
Saumil Shah 8224cce583 readme: update download link for macOS (#1) (#14271) 2026-02-15 15:25:15 -08:00
Patrick Devine d18dcd7775 mlxrunner fixes (#14247)
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* load glm4_moe_lite from the mlxrunner

* fix loading diffusion models

* remove log lines

* fix --imagegen flag
2026-02-13 22:30:42 -08:00
Parth Sareen 5f5ef20131 anthropic: enable websearch (#14246) 2026-02-13 19:20:46 -08:00
Parth Sareen f0a07a353b cmd/tui: fix powershell search (#14242) 2026-02-13 15:53:11 -08:00
Devon Rifkin 948de6bbd2 add ability to disable cloud (#14221)
* add ability to disable cloud

Users can now easily opt-out of cloud inference and web search by
setting

```
"disable_ollama_cloud": true
```

in their `~/.ollama/server.json` settings file. After a setting update,
the server must be restarted.

Alternatively, setting the environment variable `OLLAMA_NO_CLOUD=1` will
also disable cloud features. While users previously were able to avoid
cloud models by not pulling or `ollama run`ing them, this gives them an
easy way to enforce that decision. Any attempt to run a cloud model when
cloud is disabled will fail.

The app's old "airplane mode" setting, which did a similar thing for
hiding cloud models within the app is now unified with this new cloud
disabled mode. That setting has been replaced with a "Cloud" toggle,
which behind the scenes edits `server.json` and then restarts the
server.

* gate cloud models across TUI and launch flows when cloud is disabled

Block cloud models from being selected, launched, or written to
integration configs when cloud mode is turned off:

- TUI main menu: open model picker instead of launching with a
  disabled cloud model
- cmd.go: add IsCloudModelDisabled checks for all Selection* paths
- LaunchCmd: filter cloud models from saved Editor configs before
  launch, fall through to picker if none remain
- Editor Run() methods (droid, opencode, openclaw): filter cloud
  models before calling Edit() and persist the cleaned list
- Export SaveIntegration, remove SaveIntegrationModel wrapper that
  was accumulating models instead of replacing them

* rename saveIntegration to SaveIntegration in config.go and tests

* cmd/config: add --model guarding and empty model list fixes

* Update docs/faq.mdx

Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>

* Update internal/cloud/policy.go

Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>

* Update internal/cloud/policy.go

Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>

* Update server/routes.go

Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>

* Revert "Update internal/cloud/policy.go"

This reverts commit 8bff8615f9b5751fc5c0d1273b07c9de651e07f9.

Since this error shows up in other integrations, we want it to be
prefixed with Ollama

* rename cloud status

* more status renaming

* fix tests that weren't updated after rename

---------

Co-authored-by: ParthSareen <parth.sareen@ollama.com>
Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>
2026-02-12 15:47:00 -08:00
Parth Sareen 598b74d42c cmd/config: add minimax-m2.5 (#14223)
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2026-02-12 14:29:50 -08:00
Jeffrey Morgan 935a48ed1a scripts: skip macOS symlink creation if already correct (#14142) 2026-02-12 12:44:42 -08:00
Daniel Hiltgen de39e24bf7 win: progress reporting on install download (#14219)
* win: progress reporting on install download

Downloading Ollama...
  [####################################    ] 91%  1106.6 / 1204.2 MB

* review comments
2026-02-12 12:06:56 -08:00
Eva H 519b11eba1 site: update readme (#14217) 2026-02-12 12:14:13 -05:00
Eva H 379fd64fa8 Revert "update README (#14213)" (#14215) 2026-02-12 12:06:00 -05:00
frob 59c019a6fb x: configurable model load timeout (#14204)
Co-authored-by: rick <rick@frob.com.au>
2026-02-12 09:05:42 -08:00
Eva H fad3bcccb2 update README (#14213) 2026-02-12 11:59:42 -05:00
Bruce MacDonald bd6697ad95 docs: update quickstart for tui (#14208) 2026-02-12 08:44:33 -08:00
SamareshSingh f8dc7c9f54 docs: fix openapi schema for /api/ps and /api/tags endpoints (#14210)
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Patrick Devine 4a3741129d bug: fix loading non-mlx models when ollama is built with mlx support (#14211)
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This change fixes an issue where GGML based models (for either the Ollama runner or
the legacy llama.cpp runner) would try to load the mlx library. That would panic
and the model fails to start.
2026-02-11 14:48:33 -08:00
Parth Sareen 77ba9404ac cmd/tui: improve model picker UX (#14209) 2026-02-11 14:36:54 -08:00
Patrick Devine 0aaf6119ec feature: add ctrl-g to allow users to use an editor to edit their prompt (#14197) 2026-02-11 13:04:41 -08:00
Parth Sareen f08427c138 cmd: TUI UX improvements (#14198) 2026-02-11 10:18:41 -08:00
Maternion 2dbb000908 update context length format. 2026-02-10 17:06:05 -08:00
Maternion c980e19995 Fix formatting of context length notes in documentation 2026-02-10 17:06:05 -08:00
Maternion 6162374ca9 Update context-length.mdx 2026-02-10 17:06:05 -08:00
Patrick Devine 44bdd9a2ef Add MLX runner with GLM4-MoE-Lite model support (#14185)
This change adds a new MLX based runner which includes:

  * Method-based MLX bindings
  * Subprocess-based MLX runner (x/mlxrunner)
  * KV cache with tree management
  * A basic sampler

The GLM4-MoE-Lite model has been ported to use the new bindings.

---------

Co-authored-by: Michael Yang <git@mxy.ng>
2026-02-10 14:57:57 -08:00
Michael db493d6e5e docs: update broken links on FAQ and quick cleanup (#14194)
docs: update broken links on FAQ and quick cleanup
2026-02-10 16:52:20 -05:00
Bruce MacDonald 75695f16a5 docs: integration overview (#13831)
Group integrations into high-level types
2026-02-10 11:41:09 -08:00
Patrick Devine a0407d07fa safetensors quantization for mlx (#14184)
This change includes:
  - changes to the safetensors metadata format
  - changes to the create command to properly create the blobs with the new format
  - changes to load the new format
  - fixes ollama show to properly show each tensor
2026-02-10 11:29:17 -08:00
Jeffrey Morgan 9ec733e527 cmd: make 'ollama login' and 'ollama logout' aliases for 'ollama signin' and 'ollama signout' respectively (#14144) 2026-02-09 19:12:42 -08:00
Parth Sareen 5ef04dab52 cmd: ollama launch pi (#14084) 2026-02-09 19:07:41 -08:00
Daniel Hiltgen aea316f1e9 win: add curl-style install script (#14178)
This adds a new powershell install script suitable for running via

  irm https://ollama.com/install.ps1 | iex

If you download the script and run '-?' it reports basic usage
information, as well as usage examples for common customization
options.  The script is signed as part of the release process
to ensure it can run on a typically configured Windows system.

This does not include doc updates - we can merge those after a release
ships to avoid user confusion.
2026-02-09 15:28:11 -08:00
Patrick Devine 235ba3df5c cmd: ollama menu and launch improvements (#14038) 2026-02-09 11:30:16 -08:00
Jeffrey Morgan 099a0f18ef build: fix Dockerfile mlx directory (#14131)
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2026-02-06 17:08:53 -08:00
Richard Lyons fff696ee31 docs: increased RAM requirement for parallelism 2026-02-06 15:49:39 -08:00
Jeffrey Morgan 2e3ce6eab3 anthropic: do not count image tokens for now (#14127) 2026-02-06 15:33:18 -08:00
Parth Sareen 9e2003f88a cmd/config: offer to pull missing models instead of erroring (#14113) 2026-02-06 10:19:47 -08:00
Parth Sareen 42e1d49fbe cmd: fix context limits for droid and add qwen3-coder-next ctx (#14112) 2026-02-05 22:29:53 -08:00
Michael Yang 814630ca60 Revert "move tokenizers to separate package (#13825)" (#14111) 2026-02-05 20:49:08 -08:00
Parth Sareen 87cf187774 cmd: set claude code env vars on launch (#14109)
Set ANTHROPIC_DEFAULT_OPUS_MODEL, ANTHROPIC_DEFAULT_SONNET_MODEL,
ANTHROPIC_DEFAULT_HAIKU_MODEL, and CLAUDE_CODE_SUBAGENT_MODEL when
launching Claude Code so all model tiers route through Ollama.
2026-02-05 19:04:53 -08:00
Michael Yang 6ddd8862cd chore: move x/mlxrunner into x/imagegen (#14100) 2026-02-05 18:25:56 -08:00
Michael Yang f1373193dc move tokenizers to separate package (#13825) 2026-02-05 17:44:11 -08:00
Parth Sareen 8a4b77f9da cmd: set context limits for cloud models in opencode (#14107)
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2026-02-05 16:36:46 -08:00
Parth Sareen 5f53fe7884 cmd: ollama launch improvements (#14099)
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2026-02-05 15:08:17 -08:00
Bruce MacDonald 7ab4ca0e7f scripts: add macOS support to install.sh (#14060)
Allow installing Ollama on MacOS directly from the command line. This is in line with other CLI tools and results in a more streamlined experience when the user is looking to use the CLI specifically.
2026-02-05 14:59:01 -08:00
Jeffrey Morgan e36f389e82 scheduler: default parallel=1 for qwen3next/lfm (#14103) 2026-02-05 12:48:25 -08:00
Jesse Gross c61023f554 ollamarunner: Fix off by one error with numPredict
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When numPredict is set, the user will receive one less token
than the requested limit. In addition, the stats will incorrectly
show the number of tokens returned as the limit. In cases where
numPredict is not set, the number of tokens is reported correctly.

This occurs because numPredict is checked when setting up the next
batch but hitting the limit will terminate the current batch as well.
Instead, is is better to check the limit as we actually predict them.
2026-02-04 17:14:24 -08:00
Jeffrey Morgan d25535c3f3 qwen3next: avoid inplace sigmoid for shared gate (#14077) 2026-02-04 15:50:02 -08:00
Bruce MacDonald c323161f24 cmd: helpful error message for remote models (#14057)
When trying to use cloud model with OLLAMA_HOST="ollama.com" while not signed in a helpful error message is displayed when the user is not signed in telling them they must sign in to use cloud models. This should be the same experience for models which specify a remote instance.
2026-02-04 14:55:11 -08:00
Jeffrey Morgan 255579aaa7 qwen3next: fix issue in delta net (#14075)
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gDiffExp was being broadcast across the wrong axis when multiplying with k. This fix reshapes gDiffExp to [1, chunkSize, nChunks, ...]
2026-02-04 13:40:38 -08:00
Jeffrey Morgan f7102ba826 runner: discard compute results if sequence replaced mid-batch (#14072)
If a sequence is replaced in s.seqs while a batch is computing, the old logits can be decoded into the new sequence. This change rechecks the sequence pointer after compute and skips decoding for replaced entries, preventing stale results from being applied.
2026-02-04 13:19:48 -08:00
Jeffrey Morgan cefabd79a8 Revert "cmd: claude launch improvements (#14064)" (#14071)
This reverts commit ee25219edd.
2026-02-04 09:10:37 -08:00
Jeffrey Morgan df70249520 server: optimize chatPrompt to reduce tokenization calls (#14040)
Change the truncation algorithm to start with all messages and remove
from the front until it fits, rather than adding messages one at a time
from the back. This reduces tokenization calls from O(n) to O(1) in the
common case where all messages fit in context.
2026-02-04 01:21:31 -08:00
Jeffrey Morgan 77eb2ca619 model: add qwen3-next architecture (#14051)
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2026-02-03 23:27:21 -08:00
Parth Sareen ee25219edd cmd: claude launch improvements (#14064) 2026-02-03 19:33:58 -08:00
Jeffrey Morgan b1fccabb34 Revert "Update vendored llama.cpp to b7847" (#14061) 2026-02-03 18:39:36 -08:00
Bruce MacDonald a6355329bf cmd: open browser on ollama signin when available (#14055)
When a browser is available open it to the connect URL automatically when running the `ollama signin` command. Browser is not opened in any other unauthorized scenario.
2026-02-03 16:42:09 -08:00
Parth Sareen 0398b24b42 cmd: launch defaults (#14035)
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2026-02-02 23:19:11 -08:00
Parth Sareen 75b1dddf91 cmd: launch extra params (#14039) 2026-02-03 02:03:33 -05:00
Parth Sareen e1e80ffc3e cmd/config: move config location (#14034) 2026-02-02 22:48:51 -05:00
Aleksandr Vukmirovich 71896485fd anthropic: add InputTokens to streaming response (#13934)
---------

Co-authored-by: ParthSareen <parth.sareen@ollama.com>
2026-02-02 18:29:37 -08:00
Jeffrey Morgan ef00199fb4 Update vendor ggml code to a5bb8ba4 (#13832)
Co-authored-by: Daniel Hiltgen <daniel@ollama.com>
Co-authored-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Shalini Salomi Bodapati <Shalini.Salomi.Bodapati@ibm.com>
2026-02-02 17:31:59 -08:00
Jeffrey Morgan 8f4a008139 Add GLM-OCR vision model support (#14024)
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2026-02-02 15:39:18 -08:00
Patrick Devine d8cc798c2b glm 4.7 flash support on experimental engine (#13838) 2026-02-02 15:22:11 -08:00
Richard Lyons 6582f6da5c llm: Make "do load request" error message more informative 2026-02-02 11:13:21 -08:00
Jesse Gross 0334ffa625 server: use tiered VRAM-based default context length
Replace binary low VRAM mode with tiered VRAM thresholds that set
default context lengths for all models:

- < 24 GiB VRAM: 4,096 context
- 24-48 GiB VRAM: 32,768 context
- >= 48 GiB VRAM: 262,144 context
2026-02-02 10:47:09 -08:00
Jesse Gross d11fbd2c60 server: fix ollama ps showing configured instead of actual context length
When context length is clamped to the model's trained context length,
ollama ps now shows the actual clamped value instead of the originally
configured value.
2026-02-02 10:47:09 -08:00
Jeffrey Morgan 6a7c3f188e openclaw: run onboarding for fresh installs (#14006)
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When launching OpenClaw without prior onboarding, run the onboarding
wizard instead of going straight to gateway. This ensures proper
gateway configuration (mode, token, etc.) before first use.

- Add onboarded() to check for wizard.lastRunAt marker in config
- Run onboard with --auth-choice skip --gateway-token ollama for fresh installs
- Existing installs (onboarding completed) run gateway directly
2026-02-01 13:46:45 -08:00
Jeffrey Morgan 427e2c962a docs: add redirect from clawdbot to openclaw (#14004) 2026-01-31 20:50:42 -08:00
Thanh Nguyen 27db7f806f cmd/config: rename integration to openclaw (#13979)
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---------

Co-authored-by: ParthSareen <parth.sareen@ollama.com>
2026-01-31 18:31:13 -05:00
Dhiraj Lochib 3590fbfa76 runner: fix typo 'baackend' -> 'backend' in error messages (#13645)
Fix typo in three error messages where 'baackend' was written instead
of 'backend' in the /health endpoint handler when initializing the
dummy model load.
2026-01-31 13:26:20 -08:00
noureldin-azzab cd0094f772 added stakpak to web & desktop (#13961) 2026-01-31 13:04:34 -08:00
Louis Beaumont 06bc8e6712 docs: add Screenpipe to Community Integrations (#13906)
Screenpipe is a 24/7 screen & mic recording tool that uses Ollama
for local LLM-powered search and AI features. 16k+ GitHub stars.
2026-01-31 12:49:52 -08:00
frob fc5f9bb448 docs: remove unsupported quantizations (#13982) 2026-01-31 12:46:20 -08:00
frob a0740f7ef7 docs: add GB10 to supported devices (#13987) 2026-01-31 12:45:27 -08:00
Parth Sareen a0923cbdd0 cmd: ollama launch add placeholder text for selector (#13966) 2026-01-29 09:48:49 -08:00
Seokrin Taron Sung f92e362b2e cmd: capitalize Ollama in serve command help text (#13965) 2026-01-29 09:47:53 -08:00
Tincho aa23d8ecd2 docs: update installation command for OpenCode CLI (#13971) 2026-01-29 09:47:02 -08:00
Gabe Goodhart 7b62c41060 cmd/config: use envconfig.Host() for base API in launch config packages (#13937) 2026-01-27 13:30:00 -08:00
Parth Sareen 26acab64b7 docs: add clawdbot (#13925) 2026-01-26 18:32:54 -08:00
Gyungrai Wang e0f03790b1 parsers/ministral: fix nested tool call parsing by counting brace nesting (#13905)
* parsers/ministral: fix nested tool call parsing by counting brace nesting

* fix lint error

* parsers: refactor ministral parser

The old one was very tied to expecting to see only one token at a time,
which I don't like to assume (who knows what the future might hold wrt
speculative decoding, etc). This new one follows a similar structure to
qwen3-coder's parser, which incidentally makes it easier to test as well
(since we can test the individual events that come out when given
particular inputs).

---------

Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2026-01-26 15:03:43 -08:00
Parth Sareen 3ab842b0f5 cmd: clawdbot config fixes (#13922)
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2026-01-26 14:34:29 -08:00
Parth Sareen b8e8ef8929 cmd: ollama launch clawdbot (#13921) 2026-01-26 13:40:59 -08:00
Parth Sareen 465d124183 cmd: fix opencode config (#13894)
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2026-01-24 18:42:56 -08:00
Parth Sareen d310e56fa3 cmd: add fallback for claude (#13892) 2026-01-24 18:26:01 -08:00
Jeffrey Morgan a1ca428c90 glm4moelite: fix attention scale calculation (#13893)
Use the original key dimension (qkNopeHeadDim + qkRopeHeadDim = 256) for
the attention scale instead of the MLA absorbed dimension (kvLoraRank +
qkRopeHeadDim = 576).

MLA absorption is a mathematically equivalent reorganization of the
attention computation - it should not change the effective attention
scale. The scale should match training, which uses 1/sqrt(256).

This improves tool calling and model looping issues.
2026-01-24 17:48:09 -08:00
Jeffrey Morgan 16750865d1 glm4moelite: quantize more tensors to q8_0 and avoid double BOS token (#13891)
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Jeffrey Morgan f3b476c592 build: add -O3 optimization to CGO flags (#13877)
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CGO_CFLAGS and CGO_CXXFLAGS were being set without optimization flags,
which overrides Go's default -O2 and results in unoptimized C++ code.

This caused significant performance degradation in release builds
compared to local `go build` which uses the default optimization.

- build_darwin.sh: add -O3 to CGO_CFLAGS and CGO_CXXFLAGS exports
- Dockerfile: preserve CGO_CFLAGS/CGO_CXXFLAGS from build args instead
  of overwriting them
- app/README.md: update documentation to include -O3
2026-01-24 10:55:38 -08:00
Parth Sareen 5267d31d56 docs: ollama launch (#13852) 2026-01-23 23:18:50 -08:00
Stillhart b44f56319f README: Update the "Ollama for ruby" to the most popular and maintained ruby gem. (#13855)
* update README ruby link

the ollama-ai ruby gem is vastly less popular and seems unmaintained
https://rubygems.org/gems/ollama-ai

the defacto standard with the most downloads in the ruby ecosystem is ruby_llm
https://rubygems.org/gems/ruby_llm

I would link to that to avoid complication and guarantee feature compatibility with ollama.

* Update gem link ruby_llm from website to GitHub

ollama links mostly to github, not project websites, hence link to ruby_llm github.
2026-01-24 01:24:52 -05:00
Jeffrey Morgan 0209c268bb llama: fix CUDA MMA errors in release build (#13874)
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2026-01-23 20:10:04 -08:00
Jeffrey Morgan 912d984346 llama: fix fattn-tile shared memory overflow on sm_50/52 (#13872)
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Use nthreads=128 for ncols=4 configurations in flash attention tile
kernel to reduce shared memory usage below 48KB limit on Maxwell
architectures (sm_50/52).

With nthreads=256 and ncols=4, np=2 which caused shared memory to
exceed 48KB. With nthreads=128 and ncols=4, np=1 keeps shared memory
under the limit.
2026-01-23 19:22:32 -08:00
Parth Sareen aae6ecbaff cmd: rename ollama config to ollama launch (#13871)
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2026-01-23 18:40:40 -08:00
Jeffrey Morgan 64737330a4 Re-apply "model: add MLA absorption for glm4moelite" with fix (#13870)
The nvidia_fp32 config for (576, 512) head sizes had nbatch_fa=32,
which caused zero-sized arrays when computing array dimensions:
  nbatch_fa / (np * warp_size) = 32 / (2 * 32) = 0

This resulted in CUDA compilation failures on CUDA 12 (Windows and
Linux arm64):
- "static assertion failed with nbatch_fa % (np*warp_size) != 0"
- "the size of an array must be greater than zero"

Fix by changing nbatch_fa from 32 to 64 for all (576, 512) configs
in the nvidia_fp32 function, matching the nvidia_fp16 and AMD configs.
2026-01-23 18:40:28 -08:00
Jeffrey Morgan 2eda97f1c3 Revert "model: add MLA absorption for glm4moelite (#13810)" (#13869)
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This reverts commit 1044b0419a.
2026-01-23 17:14:15 -08:00
Jeffrey Morgan 66831dcf70 x/imagegen: fix image editing support (#13866)
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- Fix panic in ollama show for image gen models (safe type assertion)
- Add vision capability for Flux2KleinPipeline models at create time
- Flatten transparent PNG images onto white background for better results
2026-01-23 15:37:17 -08:00
Jeffrey Morgan 1044b0419a model: add MLA absorption for glm4moelite (#13810)
* model: add MLA absorption for glm4moelite

Split the combined KV_B tensor into separate K_B and V_B tensors
during conversion, enabling MLA (Multi-head Latent Attention)
absorption which compresses the KV cache for improved efficiency.

* ggml: enable MLA flash attention for GLM-4.7-flash

Add support for gqa_ratio 4 in MLA flash attention kernels. GLM-4.7-flash
uses head size 576 with gqa_ratio 4, which was previously only supported
for gqa_ratio 16 (DeepSeek).

Metal changes:
- Enable head size 576 for flash attention
- Increase simdgroups to 8 for large heads (>=512)
- Add case 8 kernel dispatch for 8 simdgroups

CUDA changes:
- Add gqa_ratio 4 support for head 576/512
- Add tile configs for (576, 512, 4) and (576, 512, 8)
- Add MMA config cases for ncols 4
- Add template instances for ncols2=4

* model: add compatibility validation for glm4moelite architecture
2026-01-23 14:47:42 -08:00
Parth Sareen 771d9280ec cmd: ollama config fix droid model name configuration (#13856) 2026-01-23 11:44:22 -08:00
Jeffrey Morgan 862bc0a3bf x/imagegen: respect stream=false in /api/generate (#13853)
When stream=false is set for image generation requests, return a single
JSON response instead of streaming multiple ndjson progress updates.
2026-01-22 22:16:39 -08:00
Jeffrey Morgan c01608b6a1 x/imagegen: add image edit capabilities (#13846)
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2026-01-22 20:35:08 -08:00
Parth Sareen 199c41e16e cmd: ollama config command to help configure integrations to use Ollama (#13712) 2026-01-22 20:17:11 -08:00
Jeffrey Morgan 3b3bf6c217 x/imagegen: replace memory estimation with actual weight size (#13848)
Remove static VRAM estimation (EstimateVRAM, CheckMemoryRequirements)
which wasn't helpful. Instead, report the actual tensor weight size
from the manifest for ollama ps.

- Remove memory estimation check from runner startup
- Remove EstimateVRAM, CheckMemoryRequirements, modelVRAMEstimates
- Add TotalTensorSize() to get actual weight size from manifest
- Use weight size for Server.vramSize instead of estimates

Note: This is better than showing 0 or inaccurate estimates, but the
weight size is a drastic underestimation of actual memory usage since
it doesn't account for activations, intermediate tensors, or MLX
overhead. Future work should query real-time memory from MLX
(e.g., MetalGetActiveMemory) for accurate reporting.
2026-01-22 18:32:41 -08:00
Parth Sareen f52c21f457 fix: handle Enter key pressed during model loading (#13839) 2026-01-22 18:32:02 -08:00
Jeffrey Morgan b5d0f72f16 x/imagegen: remove qwen_image and qwen_image_edit models (#13827)
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Remove the Qwen image generation and image editing model packages
to clean up the codebase. These models will be reintroduced later.

- Delete x/imagegen/models/qwen_image/ (10 files)
- Delete x/imagegen/models/qwen_image_edit/ (5 files)
- Remove related CLI flags and imports from cmd/engine/main.go
- Update comments in cache/step.go to remove Qwen-specific references
2026-01-21 13:37:08 -08:00
Patrick Devine 148a1be0a3 Clean up the manifest and modelpath (#13807) 2026-01-21 11:46:17 -08:00
next-n d6dd430abd x/imagegen: respect OLLAMA_MODELS for manifests and blobs (#13797)
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2026-01-20 13:01:52 -08:00
Daniel Hiltgen ae78112c50 test: add lfm2.5-thinking coverage (#13802) 2026-01-20 12:57:02 -08:00
Jeffrey Morgan 01cf7445f3 model: add lfm2 architecture and LFM2.5-1.2B-Thinking support (#13792)
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Co-Authored-By: TommyBoiss <165361500+TommyBoiss@users.noreply.github.com>
2026-01-20 12:20:53 -08:00
Jeffrey Morgan 31085d5e53 fix: use api.GenerateRequest for image generation test (#13793)
Remove non-existent x/imagegen/api import and use the standard
api.GenerateRequest/GenerateResponse with the Image field instead.
2026-01-20 03:23:31 -08:00
Daniel Hiltgen c42e9d244f test: add image gen test case (#13698)
* test: fix type regression in tools test.

* test: add image gen integration test
2026-01-19 16:01:31 -08:00
Devon Rifkin e98b5e8b4e /api/show: default to empty model_info (#13785)
For `/api/show`, a fully missing `model_info` field trips up various
integrators (including a recent Android Studio integration).

The primary source of missing info tends to come from models with a
remote that are also missing other data. It seems better to me to return
an empty `model_info` than making up some other fields within
`model_info` (like saying the architecture is `remote` or something like
that). So this does slightly change `/api/show`'s behavior that possibly
someone is relying on, but it seems more important to ensure the field
is always there (from a quick sampling integrations seem to be robust to
missing fields _within_ it).

Fixes: https://github.com/ollama/ollama/issues/13783
2026-01-19 15:26:17 -08:00
Jeffrey Morgan 68e00c7c36 fix: prevent image generation models from loading during deletion (#13781)
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Move the unload check (empty prompt + KeepAlive=0) before the image
generation model dispatch in GenerateHandler. This prevents models like
flux from being loaded into memory just to be immediately unloaded when
running `ollama rm`.

Also fix a bug in DeleteHandler where `args[0]` was used instead of
`arg` in the delete loop, causing only the first model to be unloaded
when deleting multiple models.
2026-01-19 12:48:34 -08:00
Jeffrey Morgan 4f138a1749 model: add Glm4MoeLiteForCausalLM architecture to support GLM-4.7-Flash (#13779) 2026-01-19 12:47:17 -08:00
Jeffrey Morgan 03bf241c33 x/imagegen: add FP4 quantization support for image generation models (#13773)
Add --quantize fp4 support to ollama create for image generation models
(flux2, z-image-turbo), using MLX's affine 4-bit quantization.

Changes:
- Add fp4 to validation in CreateImageGenModel
- Add FP4 case to quantizeTensor (group_size=32, bits=4, affine mode)
- Add GetQuantization() to WeightSource interface for dynamic params
- Update LoadLinearLayer to use quantization params from model metadata
2026-01-19 00:54:54 -08:00
Jeffrey Morgan a887406c24 x/imagegen: add preliminary support for FLUX.2-klein model (#13772) 2026-01-18 22:30:49 -08:00
Jeffrey Morgan d51e95ba7e server: prevent image generation models from reloading on every request (#13771)
The loadImageGen function was not setting Options on the runnerRef,
causing needsReload() to always return true (since it checks if
runner.Options == nil). This resulted in the image generation
subprocess being killed and restarted for every request.
2026-01-18 20:50:04 -08:00
Jeffrey Morgan 3d01f2aa34 parsers: refactor Nemotron parser to reuse Qwen3Coder for tool calls (#13764)
Simplify Nemotron3NanoParser by delegating tool call parsing to
Qwen3CoderParser instead of duplicating the parsing logic. The
Nemotron parser now only handles the thinking state machine and
transitions to Qwen3CoderParser for content and tool call parsing.

This also fixes an issue where tool calls without </think> would
cause the parser to get stuck in thinking mode.
2026-01-17 18:28:52 -08:00
Jeffrey Morgan 634c416645 Add experimental image generation fields to /api/generate (#13753)
Request fields (experimental):
- width: image width (max 4096)
- height: image height (max 4096)
- steps: denoising steps
- seed: random seed

Response fields (experimental):
- images: base64-encoded generated images
- completed: current step progress
- total: total steps

Other changes:
- Fix lifecycle bug where image models wouldn't unload (refCount issue)
- Fix "headers already written" error on Ctrl+C during streaming
- Add gin middleware for OpenAI /v1/images/generations compatibility
- Update CLI to use /api/generate with progress bar
- Add preload support in interactive mode
2026-01-17 18:27:41 -08:00
Michael 57de86cc61 docs: update claude code docs (#13757)
* docs: update claude code docs
2026-01-16 22:41:34 -08:00
Daniel Hiltgen 12719b6e87 MLX - dynamic loading of mlx-c (#13735)
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* MLX - dynamic loading of mlx-c

Create a wrapper layer to indirect the dependency on mlx-c so
the main ollama binary does not have a load-time dependency on mlx-c, mlx, and on linux, cuda.  Lazy load the library via dlopen
so we can adjust the path to ensure the dependencies are found
and fail gracefully if not present.

* review comments

* fix broken tests
2026-01-16 16:34:22 -08:00
Patrick Devine a077d996e3 Fix create and show commands for experimental models (#13741)
* x: make `ollama create --experimental` import from safetensors

This change allows pulling in safetensors models into the new experimental model format, and also
fixes the `ollama show` command to be able to correctly display the model information.

* gofumpt the linter

* gofumpt the linter again

* validate the model name
2026-01-16 14:31:55 -08:00
Jeffrey Morgan c23d5095de x/imagegen: clean up image generation code (#13725) 2026-01-16 12:19:25 -08:00
Bruce MacDonald 7601f0e93e server: reject unexpected auth hosts (#13738)
Added validation to ensure auth redirects stay on the same host as the original request. The fix is a single check in getAuthorizationToken comparing the realm URL's host against the request host. Added tests for the auth flow.

Co-Authored-By: Gecko Security <188164982+geckosecurity@users.noreply.github.com>

* gofmt

---------

Co-authored-by: Gecko Security <188164982+geckosecurity@users.noreply.github.com>
2026-01-16 14:10:36 -05:00
Eva H aad3f03890 app: allow macOS app to terminate during system shutdown (#13737)
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Gyungrai Wang 55d0b6e8b9 integration: fix tools_test.go for ToolCallFunctionArguments API change (#13731)
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Devon Rifkin 38eac40d56 openai: tweak v1/responses to conform better (#13736)
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* openai: tweak v1/responses to conform better

* openai: provide better error for image URLs

* lint
2026-01-15 15:46:36 -08:00
Jeffrey Morgan 80f3f1bc25 readme: add instructions to build with MLX (#13733)
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2026-01-15 11:03:52 -08:00
Parth Sareen b1a0db547b docs: add env var needed for claude code in docs (#13721) 2026-01-15 10:11:00 -08:00
Parth Sareen 75d7b5f926 cmd: enable multi-line input and shift enter (#13694) 2026-01-14 17:52:46 -08:00
vincent d warmerdam 349d814814 docs: add marimo integration (#13326)
* docs added

* fix title

* add marimo to docs.json

---------

Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2026-01-14 17:37:38 -08:00
Yuhong Sun c8743031e0 docs: add onyx integration (#13135)
* Ready for team review

* Update docs/integrations/onyx.mdx

Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>

* update docs.json

---------

Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>
Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2026-01-14 17:32:05 -08:00
Jeffrey Morgan 4adb9cf4bb scripts: fix macOS auto-update signature verification failure (#13713)
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Add --norsrc flag to ditto commands when creating Ollama-darwin.zip
to exclude AppleDouble resource fork files (._* files) from the archive.

The mlx.metallib file has extended attributes, which causes ditto to
include a ._mlx.metallib AppleDouble file in the zip. Since this file
is not part of the code signature seal, macOS rejects the bundle during
auto-update verification with:

  "a sealed resource is missing or invalid"
  "file added: .../._mlx.metallib"

The --norsrc flag prevents ditto from preserving resource forks and
extended attributes, ensuring only signed files are included in the
release archive.
2026-01-14 07:48:10 -08:00
Daniel Hiltgen 74f475e735 Revert "Documentation edits made through Mintlify web editor" (#13688)
This reverts commit c6d4c0c7f2.

Merge after 0.14.0 ships for the updated Linux documentation.
2026-01-14 07:42:34 -08:00
Maternion 875cecba74 docs: update default context window size to 4096 tokens (#13709) 2026-01-14 01:01:28 -08:00
Josh Daniel Bañares 7d411a4686 docs: update web search param in examples (#13711) 2026-01-14 00:38:39 -08:00
Daniel Hiltgen 02a2401596 mlx: bundle openblas dependency (#13706)
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2026-01-13 15:29:47 -08:00
1650 changed files with 198963 additions and 443950 deletions
+324 -113
View File
@@ -16,7 +16,7 @@ jobs:
outputs:
GOFLAGS: ${{ steps.goflags.outputs.GOFLAGS }}
VERSION: ${{ steps.goflags.outputs.VERSION }}
vendorsha: ${{ steps.changes.outputs.vendorsha }}
vendorsha: ${{ steps.goflags.outputs.vendorsha }}
steps:
- uses: actions/checkout@v4
- name: Set environment
@@ -24,10 +24,10 @@ jobs:
run: |
echo GOFLAGS="'-ldflags=-w -s \"-X=github.com/ollama/ollama/version.Version=${GITHUB_REF_NAME#v}\" \"-X=github.com/ollama/ollama/server.mode=release\"'" | tee -a $GITHUB_OUTPUT
echo VERSION="${GITHUB_REF_NAME#v}" | tee -a $GITHUB_OUTPUT
echo vendorsha=$(make -f Makefile.sync print-base) | tee -a $GITHUB_OUTPUT
echo vendorsha=$(cat LLAMA_CPP_VERSION)-$(cat MLX_VERSION)-$(cat MLX_C_VERSION) | tee -a $GITHUB_OUTPUT
darwin-build:
runs-on: macos-14-xlarge
runs-on: macos-26-xlarge
environment: release
needs: setup-environment
env:
@@ -57,7 +57,9 @@ jobs:
go-version-file: go.mod
cache-dependency-path: |
go.sum
Makefile.sync
LLAMA_CPP_VERSION
MLX_VERSION
MLX_C_VERSION
- run: |
./scripts/build_darwin.sh
- name: Log build results
@@ -73,15 +75,18 @@ jobs:
dist/*.dmg
windows-depends:
needs: setup-environment
strategy:
matrix:
os: [windows]
arch: [amd64]
preset: ['CPU']
build-steps: ['cpu cpuArm64']
include:
- os: windows
arch: amd64
preset: 'CUDA 12'
build-steps: cuda12
install: https://developer.download.nvidia.com/compute/cuda/12.8.0/local_installers/cuda_12.8.0_571.96_windows.exe
cuda-components:
- '"cudart"'
@@ -89,10 +94,10 @@ jobs:
- '"cublas"'
- '"cublas_dev"'
cuda-version: '12.8'
flags: ''
- os: windows
arch: amd64
preset: 'CUDA 13'
build-steps: cuda13
install: https://developer.download.nvidia.com/compute/cuda/13.0.0/local_installers/cuda_13.0.0_windows.exe
cuda-components:
- '"cudart"'
@@ -103,30 +108,67 @@ jobs:
- '"nvvm"'
- '"nvptxcompiler"'
cuda-version: '13.0'
flags: ''
- os: windows
arch: amd64
preset: 'ROCm 6'
install: https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q4-WinSvr2022-For-HIP.exe
rocm-version: '6.2'
flags: '-DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_C_FLAGS="-parallel-jobs=4 -Wno-ignored-attributes -Wno-deprecated-pragma" -DCMAKE_CXX_FLAGS="-parallel-jobs=4 -Wno-ignored-attributes -Wno-deprecated-pragma"'
runner_dir: 'rocm'
preset: 'ROCm 7'
build-steps: rocm7
install: https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-26.Q1-Win11-For-HIP.exe
rocm-version: '7.1'
- os: windows
arch: amd64
preset: Vulkan
build-steps: vulkan
install: https://sdk.lunarg.com/sdk/download/1.4.321.1/windows/vulkansdk-windows-X64-1.4.321.1.exe
flags: ''
runner_dir: 'vulkan'
- os: windows
arch: amd64
preset: 'MLX CUDA 13'
build-steps: mlxCuda13
build-parallel: '16'
cmake-cuda-flags: '-t 6'
install: https://developer.download.nvidia.com/compute/cuda/13.0.0/local_installers/cuda_13.0.0_windows.exe
cudnn-install: https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/windows-x86_64/cudnn-windows-x86_64-9.18.1.3_cuda13-archive.zip
cuda-components:
- '"cudart"'
- '"nvcc"'
- '"cublas"'
- '"cublas_dev"'
- '"cufft"'
- '"cufft_dev"'
- '"nvrtc"'
- '"nvrtc_dev"'
- '"crt"'
- '"nvvm"'
- '"nvptxcompiler"'
cuda-version: '13.0'
runs-on: ${{ matrix.arch == 'arm64' && format('{0}-{1}', matrix.os, matrix.arch) || matrix.os }}
environment: release
env:
GOFLAGS: ${{ needs.setup-environment.outputs.GOFLAGS }}
VERSION: ${{ needs.setup-environment.outputs.VERSION }}
steps:
- if: startsWith(matrix.preset, 'MLX ')
name: Increase pagefile to 200 GB
uses: al-cheb/configure-pagefile-action@v1.5
with:
minimum-size: 16GB
maximum-size: 200GB
disk-root: "D:"
- name: Install system dependencies
run: |
choco install -y --no-progress ccache ninja
ccache -o cache_dir=${{ github.workspace }}\.ccache
- if: startsWith(matrix.preset, 'CUDA ') || startsWith(matrix.preset, 'ROCm ') || startsWith(matrix.preset, 'Vulkan')
if (Get-Command ccache -ErrorAction SilentlyContinue) {
ccache -o cache_dir=${{ github.workspace }}\.ccache
}
- if: matrix.preset == 'CPU'
name: Install Windows ARM64 cross compiler
run: |
Invoke-WebRequest -Uri "https://github.com/mstorsjo/llvm-mingw/releases/download/20240619/llvm-mingw-20240619-ucrt-x86_64.zip" -OutFile "${{ runner.temp }}\llvm-mingw-ucrt.zip"
Expand-Archive -Path ${{ runner.temp }}\llvm-mingw-ucrt.zip -DestinationPath "C:\Program Files\"
$installPath=(Resolve-Path -Path "C:\Program Files\llvm-mingw-*-ucrt-x86_64").path
if (!(Test-Path "$installPath\bin\aarch64-w64-mingw32-gcc.exe")) {
throw "llvm-mingw x86_64 package is missing the aarch64 cross compiler"
}
- if: startsWith(matrix.preset, 'CUDA ') || startsWith(matrix.preset, 'ROCm ') || startsWith(matrix.preset, 'Vulkan') || startsWith(matrix.preset, 'MLX ')
id: cache-install
uses: actions/cache/restore@v4
with:
@@ -134,8 +176,9 @@ jobs:
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA
C:\Program Files\AMD\ROCm
C:\VulkanSDK
key: ${{ matrix.install }}
- if: startsWith(matrix.preset, 'CUDA ')
C:\Program Files\NVIDIA\CUDNN
key: ${{ matrix.install }}-${{ matrix.cudnn-install }}
- if: startsWith(matrix.preset, 'CUDA ') || startsWith(matrix.preset, 'MLX ')
name: Install CUDA ${{ matrix.cuda-version }}
run: |
$ErrorActionPreference = "Stop"
@@ -173,12 +216,29 @@ jobs:
}
$vulkanPath = (Resolve-Path "C:\VulkanSDK\*").path
$vulkanRuntime = Join-Path $vulkanPath "Helpers\VulkanRT.exe"
if (Test-Path $vulkanRuntime) {
Start-Process -FilePath $vulkanRuntime -ArgumentList "/s" -NoNewWindow -Wait
}
echo "$vulkanPath\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "VULKAN_SDK=$vulkanPath" >> $env:GITHUB_ENV
- if: matrix.preset == 'CPU'
- if: startsWith(matrix.preset, 'MLX ')
name: Install cuDNN for MLX
run: |
echo "CC=clang.exe" | Out-File -FilePath $env:GITHUB_ENV -Append
echo "CXX=clang++.exe" | Out-File -FilePath $env:GITHUB_ENV -Append
$ErrorActionPreference = "Stop"
$cudnnRoot = "C:\Program Files\NVIDIA\CUDNN"
if ("${{ steps.cache-install.outputs.cache-hit }}" -ne 'true') {
Invoke-WebRequest -Uri "${{ matrix.cudnn-install }}" -OutFile "cudnn.zip"
Expand-Archive -Path cudnn.zip -DestinationPath cudnn-extracted
$cudnnDir = (Get-ChildItem -Path cudnn-extracted -Directory)[0].FullName
New-Item -ItemType Directory -Force -Path $cudnnRoot
Copy-Item -Path "$cudnnDir\*" -Destination "$cudnnRoot\" -Recurse
}
echo "CUDNN_ROOT_DIR=$cudnnRoot" | Out-File -FilePath $env:GITHUB_ENV -Append
echo "CUDNN_INCLUDE_PATH=$cudnnRoot\include" | Out-File -FilePath $env:GITHUB_ENV -Append
echo "CUDNN_LIBRARY_PATH=$cudnnRoot\lib\x64" | Out-File -FilePath $env:GITHUB_ENV -Append
echo "$cudnnRoot\bin\x64" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
- if: ${{ !cancelled() && steps.cache-install.outputs.cache-hit != 'true' }}
uses: actions/cache/save@v4
with:
@@ -186,78 +246,70 @@ jobs:
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA
C:\Program Files\AMD\ROCm
C:\VulkanSDK
key: ${{ matrix.install }}
C:\Program Files\NVIDIA\CUDNN
key: ${{ matrix.install }}-${{ matrix.cudnn-install }}
- uses: actions/checkout@v4
- uses: actions/cache@v4
with:
path: ${{ github.workspace }}\.ccache
key: ccache-${{ matrix.os }}-${{ matrix.arch }}-${{ matrix.preset }}-${{ needs.setup-environment.outputs.vendorsha }}
- name: Build target "${{ matrix.preset }}"
- name: Build Windows dependencies
run: |
Import-Module 'C:\Program Files\Microsoft Visual Studio\2022\Enterprise\Common7\Tools\Microsoft.VisualStudio.DevShell.dll'
Enter-VsDevShell -VsInstallPath 'C:\Program Files\Microsoft Visual Studio\2022\Enterprise' -SkipAutomaticLocation -DevCmdArguments '-arch=x64 -no_logo'
cmake --preset "${{ matrix.preset }}" ${{ matrix.flags }} --install-prefix "$((pwd).Path)\dist\${{ matrix.os }}-${{ matrix.arch }}"
cmake --build --parallel ([Environment]::ProcessorCount) --preset "${{ matrix.preset }}"
cmake --install build --component "${{ startsWith(matrix.preset, 'CUDA ') && 'CUDA' || startsWith(matrix.preset, 'ROCm ') && 'HIP' || startsWith(matrix.preset, 'Vulkan') && 'Vulkan' || 'CPU' }}" --strip
Remove-Item -Path dist\lib\ollama\rocm\rocblas\library\*gfx906* -ErrorAction SilentlyContinue
$steps = "${{ matrix.build-steps }}".Split(' ', [System.StringSplitOptions]::RemoveEmptyEntries)
./scripts/build_windows.ps1 @steps
env:
CMAKE_GENERATOR: Ninja
OLLAMA_BUILD_PARALLEL: ${{ matrix.build-parallel || '' }}
OLLAMA_CMAKE_CUDA_FLAGS: ${{ matrix.cmake-cuda-flags || '' }}
- name: Log build results
run: |
gci -path .\dist -Recurse -File | ForEach-Object { get-filehash -path $_.FullName -Algorithm SHA256 } | format-list
- if: matrix.preset == 'CPU'
name: Verify Windows CPU payloads
shell: bash
run: |
set -euo pipefail
for payload in \
dist/windows-amd64/lib/ollama/llama-server.exe \
dist/windows-arm64/lib/ollama/llama-server.exe
do
[ -f "$payload" ] || { echo "missing $payload"; exit 1; }
done
- uses: actions/upload-artifact@v4
with:
name: depends-${{ matrix.os }}-${{ matrix.arch }}-${{ matrix.preset }}
path: dist\*
windows-build:
strategy:
matrix:
os: [windows]
arch: [amd64, arm64]
include:
- os: windows
arch: amd64
llvmarch: x86_64
- os: windows
arch: arm64
llvmarch: aarch64
runs-on: ${{ matrix.arch == 'arm64' && format('{0}-{1}', matrix.os, matrix.arch) || matrix.os }}
runs-on: windows
environment: release
needs: [setup-environment]
env:
GOFLAGS: ${{ needs.setup-environment.outputs.GOFLAGS }}
VERSION: ${{ needs.setup-environment.outputs.VERSION }}
steps:
- name: Install ARM64 system dependencies
if: matrix.arch == 'arm64'
run: |
$ErrorActionPreference = "Stop"
Set-ExecutionPolicy Bypass -Scope Process -Force
[System.Net.ServicePointManager]::SecurityProtocol = [System.Net.ServicePointManager]::SecurityProtocol -bor 3072
iex ((New-Object System.Net.WebClient).DownloadString('https://community.chocolatey.org/install.ps1'))
echo "C:\ProgramData\chocolatey\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
Invoke-WebRequest -Uri https://aka.ms/vs/17/release/vc_redist.arm64.exe -OutFile "${{ runner.temp }}\vc_redist.arm64.exe"
Start-Process -FilePath "${{ runner.temp }}\vc_redist.arm64.exe" -ArgumentList @("/install", "/quiet", "/norestart") -NoNewWindow -Wait
choco install -y --no-progress git gzip
echo "C:\Program Files\Git\cmd" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
- name: Install clang and gcc-compat
run: |
$ErrorActionPreference = "Stop"
Set-ExecutionPolicy Bypass -Scope Process -Force
Invoke-WebRequest -Uri "https://github.com/mstorsjo/llvm-mingw/releases/download/20240619/llvm-mingw-20240619-ucrt-${{ matrix.llvmarch }}.zip" -OutFile "${{ runner.temp }}\llvm-mingw-ucrt.zip"
Invoke-WebRequest -Uri "https://github.com/mstorsjo/llvm-mingw/releases/download/20240619/llvm-mingw-20240619-ucrt-x86_64.zip" -OutFile "${{ runner.temp }}\llvm-mingw-ucrt.zip"
Expand-Archive -Path ${{ runner.temp }}\llvm-mingw-ucrt.zip -DestinationPath "C:\Program Files\"
$installPath=(Resolve-Path -Path "C:\Program Files\llvm-mingw-*-ucrt*").path
$installPath=(Resolve-Path -Path "C:\Program Files\llvm-mingw-*-ucrt-x86_64").path
echo "$installPath\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
if (!(Test-Path "$installPath\bin\aarch64-w64-mingw32-gcc.exe")) {
throw "llvm-mingw x86_64 package is missing the aarch64 cross compiler"
}
- uses: actions/checkout@v4
- uses: actions/setup-go@v5
with:
go-version-file: go.mod
cache-dependency-path: |
go.sum
Makefile.sync
LLAMA_CPP_VERSION
MLX_VERSION
MLX_C_VERSION
- name: Verify gcc is actually clang
run: |
$ErrorActionPreference='Continue'
@@ -274,20 +326,30 @@ jobs:
with:
node-version: "20"
- run: |
./scripts/build_windows ollama app
./scripts/build_windows ollama ollamaArm64 app appArm64
- name: Verify Windows build payloads
shell: bash
run: |
set -euo pipefail
for payload in \
dist/windows-amd64/ollama.exe \
dist/windows-arm64/ollama.exe
do
[ -f "$payload" ] || { echo "missing $payload"; exit 1; }
done
- name: Log build results
run: |
gci -path .\dist -Recurse -File | ForEach-Object { get-filehash -path $_.FullName -Algorithm SHA256 } | format-list
- uses: actions/upload-artifact@v4
with:
name: build-${{ matrix.os }}-${{ matrix.arch }}
name: build-windows-amd64
path: |
dist\*
windows-app:
runs-on: windows
environment: release
needs: [windows-build, windows-depends]
needs: [setup-environment, windows-build, windows-depends]
env:
GOFLAGS: ${{ needs.setup-environment.outputs.GOFLAGS }}
VERSION: ${{ needs.setup-environment.outputs.VERSION }}
@@ -313,7 +375,9 @@ jobs:
go-version-file: go.mod
cache-dependency-path: |
go.sum
Makefile.sync
LLAMA_CPP_VERSION
MLX_VERSION
MLX_C_VERSION
- uses: actions/download-artifact@v4
with:
pattern: depends-windows*
@@ -327,6 +391,18 @@ jobs:
- name: Log dist contents after download
run: |
gci -path .\dist -recurse
- name: Verify Windows package inputs
shell: bash
run: |
set -euo pipefail
for payload in \
dist/windows-amd64/ollama.exe \
dist/windows-amd64/lib/ollama/llama-server.exe \
dist/windows-arm64/ollama.exe \
dist/windows-arm64/lib/ollama/llama-server.exe
do
[ -f "$payload" ] || { echo "missing $payload"; exit 1; }
done
- run: |
./scripts/build_windows.ps1 deps sign installer zip
- name: Log contents after build
@@ -337,22 +413,36 @@ jobs:
name: bundles-windows
path: |
dist/*.zip
dist/*.ps1
dist/OllamaSetup.exe
linux-build:
linux-depends:
strategy:
matrix:
include:
- os: linux
arch: amd64
target: archive
- os: linux
arch: amd64
target: rocm
- os: linux
arch: arm64
target: archive
runs-on: ${{ matrix.arch == 'arm64' && format('{0}-{1}', matrix.os, matrix.arch) || matrix.os }}
- arch: amd64
target: llama-server-cpu
- arch: amd64
target: llama-server-cuda_v12
- arch: amd64
target: llama-server-cuda_v13
- arch: amd64
target: mlx
- arch: amd64
target: llama-server-rocm_v7_2
- arch: amd64
target: llama-server-vulkan
- arch: arm64
target: llama-server-cpu
- arch: arm64
target: llama-server-cuda_v12
- arch: arm64
target: llama-server-cuda_v13
- arch: arm64
target: jetpack-5
- arch: arm64
target: jetpack-6
runs-on: ${{ matrix.arch == 'arm64' && 'linux-arm64' || 'linux' }}
environment: release
needs: setup-environment
env:
@@ -360,79 +450,114 @@ jobs:
steps:
- uses: actions/checkout@v4
- uses: docker/setup-buildx-action@v3
- uses: docker/login-action@v3
with:
username: ${{ vars.DOCKER_USER }}
password: ${{ secrets.DOCKER_ACCESS_TOKEN }}
- if: matrix.target == 'mlx'
name: Increase Linux swap to 200 GB
shell: bash
run: |
set -e
SWAP_PATH=/swapfile-mlx
SWAP_SIZE_GB=200
if [ -f "$SWAP_PATH" ]; then
sudo swapoff "$SWAP_PATH" 2>/dev/null || true
sudo rm -f "$SWAP_PATH"
fi
if ! sudo fallocate -l ${SWAP_SIZE_GB}G "$SWAP_PATH" 2>/dev/null; then
echo "fallocate unsupported, falling back to dd"
sudo dd if=/dev/zero of="$SWAP_PATH" bs=1M count=$((SWAP_SIZE_GB * 1024))
fi
sudo chmod 600 "$SWAP_PATH"
sudo mkswap "$SWAP_PATH"
sudo swapon "$SWAP_PATH"
swapon --show
free -h
- uses: docker/build-push-action@v6
with:
context: .
platforms: ${{ matrix.os }}/${{ matrix.arch }}
platforms: linux/${{ matrix.arch }}
target: ${{ matrix.target }}
provenance: false
sbom: false
build-args: |
GOFLAGS=${{ env.GOFLAGS }}
CGO_CFLAGS=${{ env.CGO_CFLAGS }}
CGO_CXXFLAGS=${{ env.CGO_CXXFLAGS }}
outputs: type=local,dest=dist/${{ matrix.os }}-${{ matrix.arch }}
cache-from: type=registry,ref=${{ vars.DOCKER_REPO }}:latest
cache-to: type=inline
- name: Deduplicate CUDA libraries
run: |
./scripts/deduplicate_cuda_libs.sh dist/${{ matrix.os }}-${{ matrix.arch }}
- run: |
for COMPONENT in bin/* lib/ollama/*; do
case "$COMPONENT" in
bin/ollama*) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
lib/ollama/*.so*) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
lib/ollama/cuda_v*) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
lib/ollama/vulkan*) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
lib/ollama/mlx*) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
lib/ollama/cuda_jetpack5) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-jetpack5.tar.in ;;
lib/ollama/cuda_jetpack6) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-jetpack6.tar.in ;;
lib/ollama/rocm) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-rocm.tar.in ;;
esac
done
working-directory: dist/${{ matrix.os }}-${{ matrix.arch }}
- run: |
echo "Manifests"
for ARCHIVE in dist/${{ matrix.os }}-${{ matrix.arch }}/*.tar.in ; do
echo $ARCHIVE
cat $ARCHIVE
done
- run: |
for ARCHIVE in dist/${{ matrix.os }}-${{ matrix.arch }}/*.tar.in; do
tar c -C dist/${{ matrix.os }}-${{ matrix.arch }} -T $ARCHIVE --owner 0 --group 0 | zstd --ultra -22 -T0 >$(basename ${ARCHIVE//.*/}.tar.zst);
done
- uses: actions/upload-artifact@v4
with:
name: bundles-${{ matrix.os }}-${{ matrix.arch }}-${{ matrix.target }}
path: |
*.tar.zst
OLLAMA_MLX_BUILD_JOBS=16
OLLAMA_MLX_NVCC_THREADS=6
APT_MIRROR=http://azure.archive.ubuntu.com/ubuntu
APT_PORTS_MIRROR=http://azure.ports.ubuntu.com/ubuntu-ports
cache-from: |
type=registry,ref=ollama/release:cache-${{ matrix.arch }}-${{ matrix.target }}
type=registry,ref=${{ vars.DOCKER_REPO }}:latest
cache-to: type=registry,ref=ollama/release:cache-${{ matrix.arch }}-${{ matrix.target }},mode=max
# Build each Docker variant (OS, arch, and flavor) separately. Using QEMU is unreliable and slower.
# Heavy stages were pre-built by linux-depends; this job is cache-hit-only for those layers
# and just assembles, runs the Go build, pushes the final image, and extracts release bundles.
docker-build-push:
strategy:
matrix:
include:
- os: linux
arch: arm64
archive-target: archive
build-args: |
CGO_CFLAGS
CGO_CXXFLAGS
GOFLAGS
APT_MIRROR=http://azure.archive.ubuntu.com/ubuntu
APT_PORTS_MIRROR=http://azure.ports.ubuntu.com/ubuntu-ports
OLLAMA_MLX_BUILD_JOBS=16
OLLAMA_MLX_NVCC_THREADS=6
cache-from: |
type=registry,ref=ollama/release:cache-arm64-llama-server-cpu
type=registry,ref=ollama/release:cache-arm64-llama-server-cuda_v12
type=registry,ref=ollama/release:cache-arm64-llama-server-cuda_v13
type=registry,ref=ollama/release:cache-arm64-jetpack-5
type=registry,ref=ollama/release:cache-arm64-jetpack-6
type=registry,ref=${{ vars.DOCKER_REPO }}:latest
- os: linux
arch: amd64
archive-target: archive
build-args: |
CGO_CFLAGS
CGO_CXXFLAGS
GOFLAGS
APT_MIRROR=http://azure.archive.ubuntu.com/ubuntu
APT_PORTS_MIRROR=http://azure.ports.ubuntu.com/ubuntu-ports
OLLAMA_MLX_BUILD_JOBS=16
OLLAMA_MLX_NVCC_THREADS=6
cache-from: |
type=registry,ref=ollama/release:cache-amd64-llama-server-cpu
type=registry,ref=ollama/release:cache-amd64-llama-server-cuda_v12
type=registry,ref=ollama/release:cache-amd64-llama-server-cuda_v13
type=registry,ref=ollama/release:cache-amd64-mlx
type=registry,ref=ollama/release:cache-amd64-llama-server-rocm_v7_2
type=registry,ref=ollama/release:cache-amd64-llama-server-vulkan
type=registry,ref=${{ vars.DOCKER_REPO }}:latest
- os: linux
arch: amd64
suffix: '-rocm'
archive-target: image-archive
build-args: |
CGO_CFLAGS
CGO_CXXFLAGS
GOFLAGS
FLAVOR=rocm
APT_MIRROR=http://azure.archive.ubuntu.com/ubuntu
APT_PORTS_MIRROR=http://azure.ports.ubuntu.com/ubuntu-ports
OLLAMA_MLX_BUILD_JOBS=16
OLLAMA_MLX_NVCC_THREADS=6
cache-from: |
type=registry,ref=ollama/release:cache-amd64-llama-server-cpu
type=registry,ref=ollama/release:cache-amd64-llama-server-rocm_v7_2
type=registry,ref=${{ vars.DOCKER_REPO }}:latest
runs-on: ${{ matrix.arch == 'arm64' && format('{0}-{1}', matrix.os, matrix.arch) || matrix.os }}
environment: release
needs: setup-environment
needs: [setup-environment, linux-depends]
env:
GOFLAGS: ${{ needs.setup-environment.outputs.GOFLAGS }}
steps:
@@ -447,9 +572,11 @@ jobs:
with:
context: .
platforms: ${{ matrix.os }}/${{ matrix.arch }}
provenance: false
sbom: false
build-args: ${{ matrix.build-args }}
outputs: type=image,name=${{ vars.DOCKER_REPO }},push-by-digest=true,name-canonical=true,push=true
cache-from: type=registry,ref=${{ vars.DOCKER_REPO }}:latest
cache-from: ${{ matrix.cache-from }}
cache-to: type=inline
- run: |
mkdir -p ${{ matrix.os }}-${{ matrix.arch }}
@@ -460,6 +587,64 @@ jobs:
name: digest-${{ matrix.os }}-${{ matrix.arch }}-${{ matrix.suffix }}
path: |
${{ runner.temp }}/${{ matrix.os }}-${{ matrix.arch }}-${{ matrix.suffix }}.txt
- uses: docker/build-push-action@v6
with:
context: .
platforms: ${{ matrix.os }}/${{ matrix.arch }}
target: ${{ matrix.archive-target }}
provenance: false
sbom: false
build-args: ${{ matrix.build-args }}
outputs: type=local,dest=dist/${{ matrix.os }}-${{ matrix.arch }}
cache-from: ${{ matrix.cache-from }}
- name: Deduplicate CUDA libraries
run: |
./scripts/deduplicate_cuda_libs.sh dist/${{ matrix.os }}-${{ matrix.arch }}
- name: Verify Linux build payloads
shell: bash
run: |
set -euo pipefail
base="dist/${{ matrix.os }}-${{ matrix.arch }}"
for payload in \
"$base/bin/ollama" \
"$base/lib/ollama/llama-server"
do
[ -f "$payload" ] || { echo "missing $payload"; exit 1; }
done
- run: |
for COMPONENT in bin/* lib/ollama/*; do
case "$COMPONENT" in
bin/ollama*) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
lib/ollama/*.so*) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
lib/ollama/llama-server*|lib/ollama/llama-quantize*) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
lib/ollama/cuda_v*) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
lib/ollama/vulkan*) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
lib/ollama/mlx*) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-mlx.tar.in ;;
lib/ollama/include*) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-mlx.tar.in ;;
lib/ollama/cuda_jetpack5) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-jetpack5.tar.in ;;
lib/ollama/cuda_jetpack6) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-jetpack6.tar.in ;;
lib/ollama/rocm_v*) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-rocm.tar.in ;;
esac
done
working-directory: dist/${{ matrix.os }}-${{ matrix.arch }}
- if: matrix.suffix == '-rocm'
run: rm -f dist/${{ matrix.os }}-${{ matrix.arch }}/ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in
- run: |
echo "Manifests"
for ARCHIVE in dist/${{ matrix.os }}-${{ matrix.arch }}/*.tar.in ; do
echo $ARCHIVE
cat $ARCHIVE
done
- run: |
for ARCHIVE in dist/${{ matrix.os }}-${{ matrix.arch }}/*.tar.in; do
tar c -C dist/${{ matrix.os }}-${{ matrix.arch }} -T $ARCHIVE --owner 0 --group 0 | zstd -19 -T0 >$(basename ${ARCHIVE//.*/}.tar.zst) &
done
wait
- uses: actions/upload-artifact@v4
with:
name: bundles-${{ matrix.os }}-${{ matrix.arch }}${{ matrix.suffix }}
path: |
*.tar.zst
# Merge Docker images for the same flavor into a single multi-arch manifest
docker-merge-push:
@@ -499,7 +684,7 @@ jobs:
release:
runs-on: ubuntu-latest
environment: release
needs: [darwin-build, windows-app, linux-build]
needs: [darwin-build, windows-app, docker-build-push]
permissions:
contents: write
env:
@@ -514,6 +699,24 @@ jobs:
- name: Log dist contents
run: |
ls -l dist/
- name: Copy install scripts to dist
run: |
cp scripts/install.sh dist/install.sh
- name: Verify release artifacts
run: |
required=(
dist/OllamaSetup.exe
dist/install.ps1
dist/install.sh
dist/ollama-windows-amd64.zip
dist/ollama-windows-arm64.zip
)
for payload in "${required[@]}"; do
if [ ! -f "$payload" ]; then
echo "::error::Missing expected release artifact: $payload"
exit 1
fi
done
- name: Generate checksum file
run: find . -type f -not -name 'sha256sum.txt' | xargs sha256sum | tee sha256sum.txt
working-directory: dist
@@ -536,14 +739,22 @@ jobs:
- name: Upload release artifacts
run: |
pids=()
for payload in dist/*.txt dist/*.zip dist/*.tgz dist/*.tar.zst dist/*.exe dist/*.dmg ; do
for payload in dist/*.txt dist/*.zip dist/*.tgz dist/*.tar.zst dist/*.exe dist/*.dmg dist/*.ps1 dist/*.sh ; do
echo "Uploading $payload"
gh release upload ${GITHUB_REF_NAME} $payload --clobber &
pids[$!]=$!
pids+=($!)
sleep 1
done
echo "Waiting for uploads to complete"
for pid in "${pids[*]}"; do
wait $pid
failed=0
for pid in "${pids[@]}"; do
if ! wait $pid; then
echo "::error::Upload failed (pid $pid)"
failed=1
fi
done
if [ $failed -ne 0 ]; then
echo "One or more uploads failed"
exit 1
fi
echo "done"
+22
View File
@@ -0,0 +1,22 @@
name: test-install
on:
pull_request:
paths:
- 'scripts/install.sh'
- '.github/workflows/test-install.yaml'
jobs:
test:
strategy:
matrix:
os: [ubuntu-latest, macos-latest]
runs-on: ${{ matrix.os }}
steps:
- uses: actions/checkout@v4
- name: Run install script
run: sh ./scripts/install.sh
env:
OLLAMA_NO_START: 1 # do not start app
- name: Verify ollama is available
run: ollama --version
+596
View File
@@ -0,0 +1,596 @@
name: test-llamacpp-update
# PR validation artifacts from this workflow are intentionally unsigned and not
# notarized. They are for llama.cpp update testing only and must not be
# published as release artifacts.
on:
pull_request:
paths:
- 'LLAMA_CPP_VERSION'
permissions:
contents: read
env:
CGO_CFLAGS: '-O3'
CGO_CXXFLAGS: '-O3'
jobs:
setup-environment:
runs-on: ubuntu-latest
outputs:
GOFLAGS: ${{ steps.goflags.outputs.GOFLAGS }}
VERSION: ${{ steps.goflags.outputs.VERSION }}
vendorsha: ${{ steps.goflags.outputs.vendorsha }}
steps:
- uses: actions/checkout@v4
- name: Set environment
id: goflags
shell: bash
run: |
set -euo pipefail
VERSION="0.0.0-llamacpp-${GITHUB_SHA::7}"
{
echo "GOFLAGS='-ldflags=-w -s \"-X=github.com/ollama/ollama/version.Version=${VERSION}\" \"-X=github.com/ollama/ollama/server.mode=release\"'"
echo "VERSION=${VERSION}"
echo "vendorsha=$(cat LLAMA_CPP_VERSION)-$(cat MLX_VERSION)-$(cat MLX_C_VERSION)"
} >>"${GITHUB_OUTPUT}"
darwin-build:
runs-on: macos-26-xlarge
needs: setup-environment
env:
GOFLAGS: ${{ needs.setup-environment.outputs.GOFLAGS }}
VERSION: ${{ needs.setup-environment.outputs.VERSION }}
CGO_CFLAGS: '-mmacosx-version-min=14.0 -O3'
CGO_CXXFLAGS: '-mmacosx-version-min=14.0 -O3'
CGO_LDFLAGS: '-mmacosx-version-min=14.0 -O3'
steps:
- uses: actions/checkout@v4
- uses: actions/setup-go@v5
with:
go-version-file: go.mod
cache-dependency-path: |
go.sum
LLAMA_CPP_VERSION
MLX_VERSION
MLX_C_VERSION
- name: Build unsigned Darwin runtime
run: ./scripts/build_darwin.sh build package
- name: Log build results
run: ls -l dist/
- uses: actions/upload-artifact@v4
with:
name: ollama-darwin.tgz
path: dist/ollama-darwin.tgz
compression-level: 0
# Build payload export stages independently and combine the exported
# filesystem artifacts below. This preserves parallelism without Docker
# registry credentials or oversized GitHub layer caches.
linux-payloads:
runs-on: ${{ matrix.arch == 'arm64' && 'linux-arm64' || 'linux' }}
needs: setup-environment
strategy:
fail-fast: false
matrix:
include:
- arch: amd64
target: publish-llama-server-cpu
payload: cpu
- arch: amd64
target: publish-llama-server-cuda_v12
payload: cuda_v12
- arch: amd64
target: publish-llama-server-cuda_v13
payload: cuda_v13
- arch: amd64
target: publish-llama-server-rocm_v7_2
payload: rocm_v7_2
- arch: amd64
target: publish-llama-server-vulkan
payload: vulkan
- arch: arm64
target: publish-llama-server-cpu
payload: cpu
- arch: arm64
target: publish-llama-server-cuda_v12
payload: cuda_v12
- arch: arm64
target: publish-llama-server-cuda_v13
payload: cuda_v13
- arch: arm64
target: publish-llama-server-cuda_jetpack5
payload: cuda_jetpack5
- arch: arm64
target: publish-llama-server-cuda_jetpack6
payload: cuda_jetpack6
steps:
- uses: actions/checkout@v4
- uses: docker/setup-buildx-action@v3
- uses: docker/build-push-action@v6
with:
context: .
platforms: linux/${{ matrix.arch }}
target: ${{ matrix.target }}
provenance: false
sbom: false
build-args: |
GOFLAGS=${{ needs.setup-environment.outputs.GOFLAGS }}
CGO_CFLAGS=${{ env.CGO_CFLAGS }}
CGO_CXXFLAGS=${{ env.CGO_CXXFLAGS }}
APT_MIRROR=http://azure.archive.ubuntu.com/ubuntu
APT_PORTS_MIRROR=http://azure.ports.ubuntu.com/ubuntu-ports
outputs: type=local,dest=${{ runner.temp }}/payload
- name: Pack Linux payload
shell: bash
run: |
set -euo pipefail
tar -C "${{ runner.temp }}/payload" -cf - . | zstd -9 -T0 >"${{ runner.temp }}/linux-payload-${{ matrix.arch }}-${{ matrix.payload }}.tar.zst"
- uses: actions/upload-artifact@v4
with:
name: linux-payload-${{ matrix.arch }}-${{ matrix.payload }}
path: ${{ runner.temp }}/linux-payload-${{ matrix.arch }}-${{ matrix.payload }}.tar.zst
compression-level: 0
linux-go:
runs-on: ${{ matrix.arch == 'arm64' && 'linux-arm64' || 'linux' }}
needs: setup-environment
strategy:
fail-fast: false
matrix:
arch: [amd64, arm64]
steps:
- uses: actions/checkout@v4
- uses: docker/setup-buildx-action@v3
- uses: docker/build-push-action@v6
with:
context: .
platforms: linux/${{ matrix.arch }}
target: publish-go
provenance: false
sbom: false
build-args: |
GOFLAGS=${{ needs.setup-environment.outputs.GOFLAGS }}
CGO_CFLAGS=${{ env.CGO_CFLAGS }}
CGO_CXXFLAGS=${{ env.CGO_CXXFLAGS }}
APT_MIRROR=http://azure.archive.ubuntu.com/ubuntu
APT_PORTS_MIRROR=http://azure.ports.ubuntu.com/ubuntu-ports
outputs: type=local,dest=${{ runner.temp }}/payload
- name: Pack Linux Go payload
shell: bash
run: |
set -euo pipefail
tar -C "${{ runner.temp }}/payload" -cf - . | zstd -9 -T0 >"${{ runner.temp }}/linux-payload-${{ matrix.arch }}-go.tar.zst"
- uses: actions/upload-artifact@v4
with:
name: linux-payload-${{ matrix.arch }}-go
path: ${{ runner.temp }}/linux-payload-${{ matrix.arch }}-go.tar.zst
compression-level: 0
# MLX payloads are intentionally excluded from this workflow; the Dockerfile
# still exposes publish-mlx for a separate MLX-specific workflow.
linux-bundles:
runs-on: ${{ matrix.arch == 'arm64' && 'linux-arm64' || 'linux' }}
needs: [linux-payloads, linux-go]
strategy:
fail-fast: false
matrix:
arch: [amd64, arm64]
steps:
- uses: actions/checkout@v4
- uses: actions/download-artifact@v4
with:
pattern: linux-payload-${{ matrix.arch }}-*
path: ${{ runner.temp }}/payloads
merge-multiple: true
- name: Assemble Linux payload tree
shell: bash
run: |
set -euo pipefail
src="${{ runner.temp }}/payloads"
arch="${{ matrix.arch }}"
dest="dist/linux-${arch}"
copy_payload() {
local name="$1"
local payload="${src}/linux-payload-${arch}-${name}.tar.zst"
if [ ! -f "${payload}" ]; then
echo "missing payload ${payload}"
exit 1
fi
zstd -d <"${payload}" | tar -C "${dest}" -xf -
}
mkdir -p "${dest}"
copy_payload go
copy_payload cpu
copy_payload cuda_v12
copy_payload cuda_v13
if [ "${arch}" = "amd64" ]; then
copy_payload vulkan
copy_payload rocm_v7_2
else
copy_payload cuda_jetpack5
copy_payload cuda_jetpack6
fi
./scripts/deduplicate_cuda_libs.sh "${dest}"
- name: Verify Linux build payloads
shell: bash
run: |
set -euo pipefail
base="dist/linux-${{ matrix.arch }}"
for payload in \
"${base}/bin/ollama" \
"${base}/lib/ollama/llama-server"
do
[ -f "${payload}" ] || { echo "missing ${payload}"; exit 1; }
done
- name: Create archive input lists
shell: bash
run: |
set -euo pipefail
for COMPONENT in bin/* lib/ollama/*; do
case "${COMPONENT}" in
bin/ollama*) echo "${COMPONENT}" >>ollama-linux-${{ matrix.arch }}.tar.in ;;
lib/ollama/*.so*) echo "${COMPONENT}" >>ollama-linux-${{ matrix.arch }}.tar.in ;;
lib/ollama/llama-server*|lib/ollama/llama-quantize*) echo "${COMPONENT}" >>ollama-linux-${{ matrix.arch }}.tar.in ;;
lib/ollama/cuda_v*) echo "${COMPONENT}" >>ollama-linux-${{ matrix.arch }}.tar.in ;;
lib/ollama/vulkan*) echo "${COMPONENT}" >>ollama-linux-${{ matrix.arch }}.tar.in ;;
lib/ollama/mlx*) echo "${COMPONENT}" >>ollama-linux-${{ matrix.arch }}-mlx.tar.in ;;
lib/ollama/include*) echo "${COMPONENT}" >>ollama-linux-${{ matrix.arch }}-mlx.tar.in ;;
lib/ollama/cuda_jetpack5) echo "${COMPONENT}" >>ollama-linux-${{ matrix.arch }}-jetpack5.tar.in ;;
lib/ollama/cuda_jetpack6) echo "${COMPONENT}" >>ollama-linux-${{ matrix.arch }}-jetpack6.tar.in ;;
lib/ollama/rocm_v*) echo "${COMPONENT}" >>ollama-linux-${{ matrix.arch }}-rocm.tar.in ;;
esac
done
working-directory: dist/linux-${{ matrix.arch }}
- name: Log archive input lists
shell: bash
run: |
set -euo pipefail
for ARCHIVE in dist/linux-${{ matrix.arch }}/*.tar.in; do
echo "${ARCHIVE}"
cat "${ARCHIVE}"
done
- name: Create Linux archives
shell: bash
run: |
set -euo pipefail
for ARCHIVE in dist/linux-${{ matrix.arch }}/*.tar.in; do
tar c -C dist/linux-${{ matrix.arch }} -T "${ARCHIVE}" --owner 0 --group 0 | zstd -19 -T0 >"$(basename "${ARCHIVE//.*/}.tar.zst")" &
done
wait
- uses: actions/upload-artifact@v4
with:
name: ollama-linux-${{ matrix.arch }}.tar.zst
path: ollama-linux-${{ matrix.arch }}.tar.zst
compression-level: 0
- if: matrix.arch == 'amd64'
uses: actions/upload-artifact@v4
with:
name: ollama-linux-amd64-rocm.tar.zst
path: ollama-linux-amd64-rocm.tar.zst
compression-level: 0
- if: matrix.arch == 'arm64'
uses: actions/upload-artifact@v4
with:
name: ollama-linux-arm64-jetpack5.tar.zst
path: ollama-linux-arm64-jetpack5.tar.zst
compression-level: 0
- if: matrix.arch == 'arm64'
uses: actions/upload-artifact@v4
with:
name: ollama-linux-arm64-jetpack6.tar.zst
path: ollama-linux-arm64-jetpack6.tar.zst
compression-level: 0
windows-depends:
needs: setup-environment
strategy:
fail-fast: false
matrix:
os: [windows]
arch: [amd64]
preset: ['CPU']
build-steps: ['cpu cpuArm64']
include:
- os: windows
arch: amd64
preset: 'CUDA 12'
build-steps: cuda12
install: https://developer.download.nvidia.com/compute/cuda/12.8.0/local_installers/cuda_12.8.0_571.96_windows.exe
cuda-components:
- '"cudart"'
- '"nvcc"'
- '"cublas"'
- '"cublas_dev"'
cuda-version: '12.8'
- os: windows
arch: amd64
preset: 'CUDA 13'
build-steps: cuda13
install: https://developer.download.nvidia.com/compute/cuda/13.0.0/local_installers/cuda_13.0.0_windows.exe
cuda-components:
- '"cudart"'
- '"nvcc"'
- '"cublas"'
- '"cublas_dev"'
- '"crt"'
- '"nvvm"'
- '"nvptxcompiler"'
cuda-version: '13.0'
- os: windows
arch: amd64
preset: 'ROCm 7'
build-steps: rocm7
install: https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-26.Q1-Win11-For-HIP.exe
rocm-version: '7.1'
- os: windows
arch: amd64
preset: Vulkan
build-steps: vulkan
install: https://sdk.lunarg.com/sdk/download/1.4.321.1/windows/vulkansdk-windows-X64-1.4.321.1.exe
runs-on: ${{ matrix.arch == 'arm64' && format('{0}-{1}', matrix.os, matrix.arch) || matrix.os }}
env:
GOFLAGS: ${{ needs.setup-environment.outputs.GOFLAGS }}
VERSION: ${{ needs.setup-environment.outputs.VERSION }}
steps:
- name: Install system dependencies
run: |
choco install -y --no-progress ccache ninja
if (Get-Command ccache -ErrorAction SilentlyContinue) {
ccache -o cache_dir=${{ github.workspace }}\.ccache
}
- if: matrix.preset == 'CPU'
name: Install Windows ARM64 cross compiler
run: |
Invoke-WebRequest -Uri "https://github.com/mstorsjo/llvm-mingw/releases/download/20240619/llvm-mingw-20240619-ucrt-x86_64.zip" -OutFile "${{ runner.temp }}\llvm-mingw-ucrt.zip"
Expand-Archive -Path ${{ runner.temp }}\llvm-mingw-ucrt.zip -DestinationPath "C:\Program Files\"
$installPath=(Resolve-Path -Path "C:\Program Files\llvm-mingw-*-ucrt-x86_64").path
if (!(Test-Path "$installPath\bin\aarch64-w64-mingw32-gcc.exe")) {
throw "llvm-mingw x86_64 package is missing the aarch64 cross compiler"
}
- if: startsWith(matrix.preset, 'CUDA ') || startsWith(matrix.preset, 'ROCm ') || startsWith(matrix.preset, 'Vulkan')
id: cache-install
uses: actions/cache/restore@v4
with:
path: |
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA
C:\Program Files\AMD\ROCm
C:\VulkanSDK
key: ${{ matrix.install }}
- if: startsWith(matrix.preset, 'CUDA ')
name: Install CUDA ${{ matrix.cuda-version }}
run: |
$ErrorActionPreference = "Stop"
if ("${{ steps.cache-install.outputs.cache-hit }}" -ne 'true') {
Invoke-WebRequest -Uri "${{ matrix.install }}" -OutFile "install.exe"
$subpackages = @(${{ join(matrix.cuda-components, ', ') }}) | Foreach-Object {"${_}_${{ matrix.cuda-version }}"}
Start-Process -FilePath .\install.exe -ArgumentList (@("-s") + $subpackages) -NoNewWindow -Wait
}
$cudaPath = (Resolve-Path "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\*").path
echo "$cudaPath\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
- if: startsWith(matrix.preset, 'ROCm')
name: Install ROCm ${{ matrix.rocm-version }}
run: |
$ErrorActionPreference = "Stop"
if ("${{ steps.cache-install.outputs.cache-hit }}" -ne 'true') {
Invoke-WebRequest -Uri "${{ matrix.install }}" -OutFile "install.exe"
Start-Process -FilePath .\install.exe -ArgumentList '-install' -NoNewWindow -Wait
}
$hipPath = (Resolve-Path "C:\Program Files\AMD\ROCm\*").path
echo "$hipPath\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "CC=$hipPath\bin\clang.exe" | Out-File -FilePath $env:GITHUB_ENV -Append
echo "CXX=$hipPath\bin\clang++.exe" | Out-File -FilePath $env:GITHUB_ENV -Append
echo "HIPCXX=$hipPath\bin\clang++.exe" | Out-File -FilePath $env:GITHUB_ENV -Append
echo "HIP_PLATFORM=amd" | Out-File -FilePath $env:GITHUB_ENV -Append
echo "CMAKE_PREFIX_PATH=$hipPath" | Out-File -FilePath $env:GITHUB_ENV -Append
- if: matrix.preset == 'Vulkan'
name: Install Vulkan
run: |
$ErrorActionPreference = "Stop"
if ("${{ steps.cache-install.outputs.cache-hit }}" -ne 'true') {
Invoke-WebRequest -Uri "${{ matrix.install }}" -OutFile "install.exe"
Start-Process -FilePath .\install.exe -ArgumentList "-c","--am","--al","in" -NoNewWindow -Wait
}
$vulkanPath = (Resolve-Path "C:\VulkanSDK\*").path
$vulkanRuntime = Join-Path $vulkanPath "Helpers\VulkanRT.exe"
if (Test-Path $vulkanRuntime) {
Start-Process -FilePath $vulkanRuntime -ArgumentList "/s" -NoNewWindow -Wait
}
echo "$vulkanPath\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "VULKAN_SDK=$vulkanPath" >> $env:GITHUB_ENV
- if: ${{ !cancelled() && matrix.preset != 'CPU' && steps.cache-install.outputs.cache-hit != 'true' }}
uses: actions/cache/save@v4
with:
path: |
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA
C:\Program Files\AMD\ROCm
C:\VulkanSDK
key: ${{ matrix.install }}
- uses: actions/checkout@v4
- uses: actions/cache@v4
with:
path: ${{ github.workspace }}\.ccache
key: ccache-${{ matrix.os }}-${{ matrix.arch }}-${{ matrix.preset }}-${{ needs.setup-environment.outputs.vendorsha }}
- name: Build Windows dependencies
run: |
Import-Module 'C:\Program Files\Microsoft Visual Studio\2022\Enterprise\Common7\Tools\Microsoft.VisualStudio.DevShell.dll'
Enter-VsDevShell -VsInstallPath 'C:\Program Files\Microsoft Visual Studio\2022\Enterprise' -SkipAutomaticLocation -DevCmdArguments '-arch=x64 -no_logo'
$steps = "${{ matrix.build-steps }}".Split(' ', [System.StringSplitOptions]::RemoveEmptyEntries)
./scripts/build_windows.ps1 @steps
env:
CMAKE_GENERATOR: Ninja
- name: Log build results
run: |
gci -path .\dist -Recurse -File | ForEach-Object { get-filehash -path $_.FullName -Algorithm SHA256 } | format-list
- if: matrix.preset == 'CPU'
name: Verify Windows CPU payloads
shell: bash
run: |
set -euo pipefail
for payload in \
dist/windows-amd64/lib/ollama/llama-server.exe \
dist/windows-arm64/lib/ollama/llama-server.exe
do
[ -f "$payload" ] || { echo "missing $payload"; exit 1; }
done
- uses: actions/upload-artifact@v4
with:
name: depends-${{ matrix.os }}-${{ matrix.arch }}-${{ matrix.preset }}
path: dist\*
compression-level: 0
windows-build:
runs-on: windows
needs: setup-environment
env:
GOFLAGS: ${{ needs.setup-environment.outputs.GOFLAGS }}
VERSION: ${{ needs.setup-environment.outputs.VERSION }}
steps:
- name: Install clang and gcc-compat
run: |
$ErrorActionPreference = "Stop"
Set-ExecutionPolicy Bypass -Scope Process -Force
Invoke-WebRequest -Uri "https://github.com/mstorsjo/llvm-mingw/releases/download/20240619/llvm-mingw-20240619-ucrt-x86_64.zip" -OutFile "${{ runner.temp }}\llvm-mingw-ucrt.zip"
Expand-Archive -Path ${{ runner.temp }}\llvm-mingw-ucrt.zip -DestinationPath "C:\Program Files\"
$installPath=(Resolve-Path -Path "C:\Program Files\llvm-mingw-*-ucrt-x86_64").path
echo "$installPath\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
if (!(Test-Path "$installPath\bin\aarch64-w64-mingw32-gcc.exe")) {
throw "llvm-mingw x86_64 package is missing the aarch64 cross compiler"
}
- uses: actions/checkout@v4
- uses: actions/setup-go@v5
with:
go-version-file: go.mod
cache-dependency-path: |
go.sum
LLAMA_CPP_VERSION
MLX_VERSION
MLX_C_VERSION
- name: Verify gcc is actually clang
run: |
$ErrorActionPreference='Continue'
$version=& gcc -v 2>&1
$version=$version -join "`n"
echo "gcc is $version"
if ($version -notmatch 'clang') {
echo "ERROR: GCC must be clang for proper utf16 handling"
exit 1
}
$ErrorActionPreference='Stop'
- name: Setup Node.js
uses: actions/setup-node@v4
with:
node-version: "20"
- name: Build Windows binaries and app launchers
run: ./scripts/build_windows.ps1 ollama ollamaArm64 app appArm64
- name: Verify Windows build payloads
shell: bash
run: |
set -euo pipefail
for payload in \
dist/windows-amd64/ollama.exe \
dist/windows-arm64/ollama.exe
do
[ -f "$payload" ] || { echo "missing $payload"; exit 1; }
done
- name: Log build results
run: |
gci -path .\dist -Recurse -File | ForEach-Object { get-filehash -path $_.FullName -Algorithm SHA256 } | format-list
- uses: actions/upload-artifact@v4
with:
name: build-windows-amd64
path: dist\*
compression-level: 0
windows-package:
runs-on: windows
needs: [setup-environment, windows-build, windows-depends]
env:
GOFLAGS: ${{ needs.setup-environment.outputs.GOFLAGS }}
VERSION: ${{ needs.setup-environment.outputs.VERSION }}
steps:
- uses: actions/checkout@v4
- uses: actions/setup-go@v5
with:
go-version-file: go.mod
cache-dependency-path: |
go.sum
LLAMA_CPP_VERSION
MLX_VERSION
MLX_C_VERSION
- uses: actions/download-artifact@v4
with:
pattern: depends-windows*
path: dist
merge-multiple: true
- uses: actions/download-artifact@v4
with:
pattern: build-windows*
path: dist
merge-multiple: true
- name: Copy unsigned install script
run: Copy-Item -Path .\scripts\install.ps1 -Destination .\dist\install.ps1 -ErrorAction Stop
- name: Log dist contents after download
run: gci -path .\dist -recurse
- name: Verify Windows package inputs
shell: bash
run: |
set -euo pipefail
for payload in \
dist/windows-amd64/ollama.exe \
dist/windows-amd64/lib/ollama/llama-server.exe \
dist/windows-arm64/ollama.exe \
dist/windows-arm64/lib/ollama/llama-server.exe
do
[ -f "$payload" ] || { echo "missing $payload"; exit 1; }
done
- name: Build unsigned Windows installer and zips
run: ./scripts/build_windows.ps1 deps installer zip
- name: Log contents after build
run: |
gci -path .\dist -Recurse -File | ForEach-Object { get-filehash -path $_.FullName -Algorithm SHA256 } | format-list
- name: Verify Windows package outputs
shell: bash
run: |
set -euo pipefail
for payload in \
dist/ollama-windows-amd64.zip \
dist/ollama-windows-arm64.zip \
dist/ollama-windows-amd64-rocm.zip \
dist/OllamaSetup.exe \
dist/install.ps1
do
[ -f "$payload" ] || { echo "missing $payload"; exit 1; }
done
- uses: actions/upload-artifact@v4
with:
name: ollama-windows-amd64.zip
path: dist/ollama-windows-amd64.zip
compression-level: 0
- uses: actions/upload-artifact@v4
with:
name: ollama-windows-arm64.zip
path: dist/ollama-windows-arm64.zip
compression-level: 0
- uses: actions/upload-artifact@v4
with:
name: ollama-windows-amd64-rocm.zip
path: dist/ollama-windows-amd64-rocm.zip
compression-level: 0
- uses: actions/upload-artifact@v4
with:
name: OllamaSetup.exe
path: dist/OllamaSetup.exe
compression-level: 0
- uses: actions/upload-artifact@v4
with:
name: install.ps1
path: dist/install.ps1
compression-level: 0
+212 -37
View File
@@ -22,7 +22,8 @@ jobs:
runs-on: ubuntu-latest
outputs:
changed: ${{ steps.changes.outputs.changed }}
vendorsha: ${{ steps.changes.outputs.vendorsha }}
app_changed: ${{ steps.changes.outputs.app_changed }}
enginehash: ${{ steps.changes.outputs.enginehash }}
steps:
- uses: actions/checkout@v4
with:
@@ -37,8 +38,42 @@ jobs:
| xargs python3 -c "import sys; from pathlib import Path; print(any(Path(x).match(glob) for x in sys.argv[1:] for glob in '$*'.split(' ')))"
}
echo changed=$(changed 'llama/llama.cpp/**/*' 'ml/backend/ggml/ggml/**/*') | tee -a $GITHUB_OUTPUT
echo vendorsha=$(make -f Makefile.sync print-base) | tee -a $GITHUB_OUTPUT
echo changed=$(changed \
'CMakeLists.txt' \
'CMakePresets.json' \
'cmake/**' \
'cmake/**/*' \
'llama/server/**/*' \
'llama/compat/**/*' \
'LLAMA_CPP_VERSION' \
'MLX_VERSION' \
'MLX_C_VERSION' \
'llama/llama.cpp/**/*' \
'ml/backend/ggml/ggml/**/*' \
'x/imagegen/mlx/**' \
'x/imagegen/mlx/**/*' \
'.github/**/*') | tee -a $GITHUB_OUTPUT
echo app_changed=$(changed 'app/**' 'app/**/*') | tee -a $GITHUB_OUTPUT
echo enginehash=$(cat LLAMA_CPP_VERSION)-$(cat MLX_VERSION)-$(cat MLX_C_VERSION) | tee -a $GITHUB_OUTPUT
patches:
strategy:
matrix:
os: [ubuntu-latest, windows-latest]
runs-on: ${{ matrix.os }}
steps:
- uses: actions/checkout@v4
- name: Verify patches apply cleanly
shell: bash
run: |
cmake -S llama/server -B "$RUNNER_TEMP/llama-server-patch-check" \
-DCMAKE_BUILD_TYPE=Release \
-DBUILD_SHARED_LIBS=ON \
-DGGML_BACKEND_DL=ON \
-DGGML_NATIVE=OFF \
-DGGML_OPENMP=OFF \
-DGGML_CPU_ALL_VARIANTS=ON \
-DOLLAMA_RUNNER_DIR=
linux:
needs: [changes]
@@ -47,19 +82,42 @@ jobs:
matrix:
include:
- preset: CPU
superbuild_target: ollama-local
superbuild_dir: build/local-superbuild
superbuild_args: ''
expected_payload: lib/ollama/llama-server
install-go: true
- preset: CUDA
container: nvidia/cuda:13.0.0-devel-ubuntu22.04
flags: '-DCMAKE_CUDA_ARCHITECTURES=87'
superbuild_target: ollama-llama-server-cuda_v13
superbuild_dir: build/local-superbuild-cuda_v13
superbuild_args: '-DOLLAMA_LLAMA_BACKENDS=cuda_v13 -DCMAKE_CUDA_ARCHITECTURES=87'
expected_payload: lib/ollama/cuda_v13/libggml-cuda.so
- preset: ROCm
container: rocm/dev-ubuntu-22.04:6.1.2
container: rocm/dev-ubuntu-22.04:7.2.1
extra-packages: rocm-libs
flags: '-DAMDGPU_TARGETS=gfx1010 -DCMAKE_PREFIX_PATH=/opt/rocm'
superbuild_target: ollama-llama-server-rocm_v7_2
superbuild_dir: build/local-superbuild-rocm_v7_2
superbuild_args: '-DOLLAMA_LLAMA_BACKENDS=rocm_v7_2 -DAMDGPU_TARGETS=gfx1010 -DCMAKE_PREFIX_PATH=/opt/rocm'
expected_payload: lib/ollama/rocm_v7_2/libggml-hip.so
- preset: Vulkan
container: ubuntu:22.04
extra-packages: >
mesa-vulkan-drivers vulkan-tools
libvulkan1 libvulkan-dev
vulkan-sdk cmake ccache g++ make
vulkan-sdk spirv-headers cmake ccache g++ make
superbuild_target: ollama-llama-server-vulkan
superbuild_dir: build/local-superbuild-vulkan
superbuild_args: '-DOLLAMA_LLAMA_BACKENDS=vulkan'
expected_payload: lib/ollama/vulkan/libggml-vulkan.so
- preset: 'MLX CUDA 13'
container: nvidia/cuda:13.0.0-devel-ubuntu22.04
extra-packages: libcudnn9-dev-cuda-13 libopenblas-dev liblapack-dev liblapacke-dev git curl
superbuild_target: ollama-mlx-cuda_v13
superbuild_dir: build/local-superbuild-mlx-cuda_v13
superbuild_args: '-DOLLAMA_MLX_BACKENDS=cuda_v13 -DCMAKE_CUDA_ARCHITECTURES=87 -DMLX_CUDA_ARCHITECTURES=80-virtual -DBLAS_INCLUDE_DIRS=/usr/include/x86_64-linux-gnu -DLAPACK_INCLUDE_DIRS=/usr/include/x86_64-linux-gnu'
expected_payload: lib/ollama/mlx_cuda_v13/libmlx.so
install-go: true
runs-on: linux
container: ${{ matrix.container }}
steps:
@@ -75,21 +133,42 @@ jobs:
echo "deb [signed-by=/usr/share/keyrings/lunarg-archive-keyring.gpg] https://packages.lunarg.com/vulkan/1.4.313 jammy main" | $sudo tee /etc/apt/sources.list.d/lunarg-vulkan-1.4.313-jammy.list > /dev/null
$sudo apt-get update
fi
$sudo apt-get install -y cmake ccache ${{ matrix.extra-packages }}
$sudo apt-get install -y cmake ccache curl git ${{ matrix.extra-packages }}
# Use a current CMake for upstream llama.cpp and Vulkan dependency discovery.
curl -fsSL https://github.com/Kitware/CMake/releases/download/v3.31.2/cmake-3.31.2-linux-$(uname -m).tar.gz | $sudo tar xz -C /usr/local --strip-components 1
# Export VULKAN_SDK if provided by LunarG package (defensive)
if [ -d "/usr/lib/x86_64-linux-gnu/vulkan" ] && [ "${{ matrix.preset }}" = "Vulkan" ]; then
echo "VULKAN_SDK=/usr" >> $GITHUB_ENV
fi
env:
DEBIAN_FRONTEND: noninteractive
- if: matrix.install-go
name: Install Go
run: |
[ -n "${{ matrix.container }}" ] || sudo=sudo
GO_VERSION=$(awk '/^go / { print $2 }' go.mod)
curl -fsSL "https://golang.org/dl/go${GO_VERSION}.linux-$(dpkg --print-architecture).tar.gz" | $sudo tar xz -C /usr/local
echo "/usr/local/go/bin" >> $GITHUB_PATH
- uses: actions/cache@v4
with:
path: /github/home/.cache/ccache
key: ccache-${{ runner.os }}-${{ runner.arch }}-${{ matrix.preset }}-${{ needs.changes.outputs.vendorsha }}
- run: |
cmake --preset ${{ matrix.preset }} ${{ matrix.flags }}
cmake --build --preset ${{ matrix.preset }} --parallel
key: ccache-${{ runner.os }}-${{ runner.arch }}-${{ matrix.preset }}-${{ needs.changes.outputs.enginehash }}
- name: Build native superbuild
if: matrix.superbuild_target
run: |
cmake -S . -B "${{ matrix.superbuild_dir }}" ${{ matrix.superbuild_args }}
CMAKE_BUILD_PARALLEL_LEVEL=$(nproc) cmake --build "${{ matrix.superbuild_dir }}" --target "${{ matrix.superbuild_target }}" -- -l $(nproc)
test -e "${{ matrix.superbuild_dir }}/${{ matrix.expected_payload }}"
- name: Verify local superbuild install
if: matrix.superbuild_target == 'ollama-local'
run: |
./ollama --version
"${{ matrix.superbuild_dir }}/lib/ollama/llama-server" --version
test -x "${{ matrix.superbuild_dir }}/lib/ollama/llama-quantize"
cmake --install "${{ matrix.superbuild_dir }}" --component ollama-local --prefix "$RUNNER_TEMP/ollama-local"
"$RUNNER_TEMP/ollama-local/bin/ollama" --version
"$RUNNER_TEMP/ollama-local/lib/ollama/llama-server" --version
test -x "$RUNNER_TEMP/ollama-local/lib/ollama/llama-quantize"
windows:
needs: [changes]
if: needs.changes.outputs.changed == 'True'
@@ -97,9 +176,16 @@ jobs:
matrix:
include:
- preset: CPU
superbuild_target: ollama-local
superbuild_dir: build\local-superbuild
superbuild_args: ''
expected_payload: lib\ollama\llama-server.exe
- preset: CUDA
install: https://developer.download.nvidia.com/compute/cuda/13.0.0/local_installers/cuda_13.0.0_windows.exe
flags: '-DCMAKE_CUDA_ARCHITECTURES=80'
superbuild_target: ollama-llama-server-cuda_v13
superbuild_dir: build\local-superbuild-cuda_v13
superbuild_args: '-DOLLAMA_LLAMA_BACKENDS=cuda_v13 -DCMAKE_CUDA_ARCHITECTURES=80'
expected_payload: lib\ollama\cuda_v13\ggml-cuda.dll
cuda-components:
- '"cudart"'
- '"nvcc"'
@@ -110,16 +196,47 @@ jobs:
- '"nvptxcompiler"'
cuda-version: '13.0'
- preset: ROCm
install: https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q4-WinSvr2022-For-HIP.exe
flags: '-DAMDGPU_TARGETS=gfx1010 -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_C_FLAGS="-parallel-jobs=4 -Wno-ignored-attributes -Wno-deprecated-pragma" -DCMAKE_CXX_FLAGS="-parallel-jobs=4 -Wno-ignored-attributes -Wno-deprecated-pragma"'
install: https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-26.Q1-Win11-For-HIP.exe
rocm-version: '7.1'
superbuild_target: ollama-llama-server-rocm_v7_1
superbuild_dir: build\local-superbuild-rocm_v7_1
superbuild_args: '-DOLLAMA_LLAMA_BACKENDS=rocm_v7_1 -DAMDGPU_TARGETS=gfx1010'
expected_payload: lib\ollama\rocm_v7_1\ggml-hip.dll
- preset: Vulkan
install: https://sdk.lunarg.com/sdk/download/1.4.321.1/windows/vulkansdk-windows-X64-1.4.321.1.exe
superbuild_target: ollama-llama-server-vulkan
superbuild_dir: build\local-superbuild-vulkan
superbuild_args: '-DOLLAMA_LLAMA_BACKENDS=vulkan'
expected_payload: lib\ollama\vulkan\ggml-vulkan.dll
- preset: 'MLX CUDA 13'
install: https://developer.download.nvidia.com/compute/cuda/13.0.0/local_installers/cuda_13.0.0_windows.exe
cudnn-install: https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/windows-x86_64/cudnn-windows-x86_64-9.18.1.3_cuda13-archive.zip
superbuild_target: ollama-mlx-cuda_v13
superbuild_dir: build\local-superbuild-mlx-cuda_v13
superbuild_args: '-DOLLAMA_MLX_BACKENDS=cuda_v13 -DCMAKE_CUDA_ARCHITECTURES=80 -DMLX_CUDA_ARCHITECTURES=80-virtual'
expected_payload: lib\ollama\mlx_cuda_v13\mlx.dll
install-go: true
cuda-components:
- '"cudart"'
- '"nvcc"'
- '"cublas"'
- '"cublas_dev"'
- '"cufft"'
- '"cufft_dev"'
- '"nvrtc"'
- '"nvrtc_dev"'
- '"crt"'
- '"nvvm"'
- '"nvptxcompiler"'
cuda-version: '13.0'
runs-on: windows
steps:
- run: |
choco install -y --no-progress ccache ninja
ccache -o cache_dir=${{ github.workspace }}\.ccache
- if: matrix.preset == 'CUDA' || matrix.preset == 'ROCm' || matrix.preset == 'Vulkan'
if (Get-Command ccache -ErrorAction SilentlyContinue) {
ccache -o cache_dir=${{ github.workspace }}\.ccache
}
- if: matrix.preset == 'CUDA' || matrix.preset == 'ROCm' || matrix.preset == 'Vulkan' || matrix.preset == 'MLX CUDA 13'
id: cache-install
uses: actions/cache/restore@v4
with:
@@ -127,8 +244,9 @@ jobs:
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA
C:\Program Files\AMD\ROCm
C:\VulkanSDK
key: ${{ matrix.install }}
- if: matrix.preset == 'CUDA'
C:\Program Files\NVIDIA\CUDNN
key: ${{ matrix.install }}-${{ matrix.cudnn-install }}
- if: matrix.preset == 'CUDA' || matrix.preset == 'MLX CUDA 13'
name: Install CUDA ${{ matrix.cuda-version }}
run: |
$ErrorActionPreference = "Stop"
@@ -164,10 +282,31 @@ jobs:
Invoke-WebRequest -Uri "${{ matrix.install }}" -OutFile "install.exe"
Start-Process -FilePath .\install.exe -ArgumentList "-c","--am","--al","in" -NoNewWindow -Wait
}
$vulkanPath = (Resolve-Path "C:\VulkanSDK\*").path
$vulkanRuntime = Join-Path $vulkanPath "Helpers\VulkanRT.exe"
if (Test-Path $vulkanRuntime) {
Start-Process -FilePath $vulkanRuntime -ArgumentList "/s" -NoNewWindow -Wait
}
echo "$vulkanPath\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "VULKAN_SDK=$vulkanPath" >> $env:GITHUB_ENV
- if: matrix.preset == 'MLX CUDA 13'
name: Install cuDNN for MLX
run: |
$ErrorActionPreference = "Stop"
$cudnnRoot = "C:\Program Files\NVIDIA\CUDNN"
if ("${{ steps.cache-install.outputs.cache-hit }}" -ne 'true') {
Invoke-WebRequest -Uri "${{ matrix.cudnn-install }}" -OutFile "cudnn.zip"
Expand-Archive -Path cudnn.zip -DestinationPath cudnn-extracted
$cudnnDir = (Get-ChildItem -Path cudnn-extracted -Directory)[0].FullName
New-Item -ItemType Directory -Force -Path $cudnnRoot
Copy-Item -Path "$cudnnDir\*" -Destination "$cudnnRoot\" -Recurse
}
echo "CUDNN_ROOT_DIR=$cudnnRoot" | Out-File -FilePath $env:GITHUB_ENV -Append
echo "CUDNN_INCLUDE_PATH=$cudnnRoot\include" | Out-File -FilePath $env:GITHUB_ENV -Append
echo "CUDNN_LIBRARY_PATH=$cudnnRoot\lib\x64" | Out-File -FilePath $env:GITHUB_ENV -Append
echo "$cudnnRoot\bin\x64" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
- if: ${{ !cancelled() && steps.cache-install.outputs.cache-hit != 'true' }}
uses: actions/cache/save@v4
with:
@@ -175,20 +314,47 @@ jobs:
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA
C:\Program Files\AMD\ROCm
C:\VulkanSDK
key: ${{ matrix.install }}
C:\Program Files\NVIDIA\CUDNN
key: ${{ matrix.install }}-${{ matrix.cudnn-install }}
- uses: actions/checkout@v4
- if: matrix.superbuild_target == 'ollama-local' || matrix.install-go
uses: actions/setup-go@v5
with:
go-version-file: 'go.mod'
- uses: actions/cache@v4
with:
path: ${{ github.workspace }}\.ccache
key: ccache-${{ runner.os }}-${{ runner.arch }}-${{ matrix.preset }}-${{ needs.changes.outputs.vendorsha }}
- run: |
key: ccache-${{ runner.os }}-${{ runner.arch }}-${{ matrix.preset }}-${{ needs.changes.outputs.enginehash }}
- name: Build native superbuild
if: matrix.superbuild_target
run: |
$ErrorActionPreference = "Stop"
Import-Module 'C:\Program Files\Microsoft Visual Studio\2022\Enterprise\Common7\Tools\Microsoft.VisualStudio.DevShell.dll'
Enter-VsDevShell -VsInstallPath 'C:\Program Files\Microsoft Visual Studio\2022\Enterprise' -SkipAutomaticLocation -DevCmdArguments '-arch=x64 -no_logo'
cmake --preset "${{ matrix.preset }}" ${{ matrix.flags }}
cmake --build --parallel --preset "${{ matrix.preset }}"
cmake -S . -B "${{ matrix.superbuild_dir }}" ${{ matrix.superbuild_args }}
$env:CMAKE_BUILD_PARALLEL_LEVEL = [Environment]::ProcessorCount
cmake --build "${{ matrix.superbuild_dir }}" --target "${{ matrix.superbuild_target }}" -- -l $([Environment]::ProcessorCount)
if (!(Test-Path "${{ matrix.superbuild_dir }}\${{ matrix.expected_payload }}")) {
throw "missing ${{ matrix.expected_payload }}"
}
env:
CMAKE_GENERATOR: Ninja
- name: Verify local superbuild install
if: matrix.superbuild_target == 'ollama-local'
run: |
$ErrorActionPreference = "Stop"
& ".\ollama.exe" --version
& "${{ matrix.superbuild_dir }}\lib\ollama\llama-server.exe" --version
if (!(Test-Path "${{ matrix.superbuild_dir }}\lib\ollama\llama-quantize.exe")) {
throw "missing llama-quantize.exe"
}
$installPrefix = Join-Path $env:RUNNER_TEMP "ollama-local"
cmake --install "${{ matrix.superbuild_dir }}" --component ollama-local --prefix "$installPrefix"
& "$installPrefix\bin\ollama.exe" --version
& "$installPrefix\lib\ollama\llama-server.exe" --version
if (!(Test-Path "$installPrefix\lib\ollama\llama-quantize.exe")) {
throw "missing installed llama-quantize.exe"
}
go_mod_tidy:
runs-on: ubuntu-latest
steps:
@@ -197,6 +363,7 @@ jobs:
run: go mod tidy --diff || (echo "Please run 'go mod tidy'." && exit 1)
test:
needs: [changes]
strategy:
matrix:
os: [ubuntu-latest, macos-latest, windows-latest]
@@ -210,7 +377,9 @@ jobs:
go-version-file: 'go.mod'
cache-dependency-path: |
go.sum
Makefile.sync
LLAMA_CPP_VERSION
MLX_VERSION
MLX_C_VERSION
- uses: actions/setup-node@v4
with:
node-version: '20'
@@ -224,6 +393,17 @@ jobs:
if: ${{ startsWith(matrix.os, 'ubuntu') }}
working-directory: ./app/ui/app
run: npm test
- name: Verify MLX generated files are current
if: ${{ startsWith(matrix.os, 'ubuntu') }}
run: |
cmake -S . -B build/mlx-generate -DOLLAMA_MLX_BACKENDS=cuda_v13
cmake --build build/mlx-generate --target ollama-mlx-generate-wrappers
git diff --exit-code -- \
x/imagegen/mlx/mlx.h \
x/imagegen/mlx/mlx.c \
x/mlxrunner/mlx/generated.h \
x/mlxrunner/mlx/generated.c \
x/mlxrunner/mlx/include/mlx/c
- name: Run go generate
run: go generate ./...
@@ -231,15 +411,10 @@ jobs:
if: always()
run: go test -count=1 -benchtime=1x ./...
- name: go test app with live updater tag
if: ${{ needs.changes.outputs.app_changed == 'True' && contains(fromJSON('["macos-latest","windows-latest"]'), matrix.os) }}
run: go test -count=1 -tags updater_live ./app/...
- uses: golangci/golangci-lint-action@v9
with:
only-new-issues: true
patches:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Verify patches apply cleanly and do not change files
run: |
make -f Makefile.sync clean checkout apply-patches sync
git diff --compact-summary --exit-code
+1
View File
@@ -15,3 +15,4 @@ __debug_bin*
llama/build
llama/vendor
/ollama
integration/testdata/models/
+21 -174
View File
@@ -1,4 +1,4 @@
cmake_minimum_required(VERSION 3.21)
cmake_minimum_required(VERSION 3.24)
project(Ollama C CXX)
@@ -23,30 +23,23 @@ include(GNUInstallDirs)
find_package(Threads REQUIRED)
set(CMAKE_BUILD_TYPE Release)
set(BUILD_SHARED_LIBS ON)
if(NOT CMAKE_CONFIGURATION_TYPES AND NOT CMAKE_BUILD_TYPE)
set(CMAKE_BUILD_TYPE Release CACHE STRING "Build type" FORCE)
endif()
# These defaults can be overridden by presets (e.g., for static macOS llama-server builds)
if(NOT DEFINED BUILD_SHARED_LIBS)
set(BUILD_SHARED_LIBS ON)
endif()
set(CMAKE_CXX_STANDARD 17)
set(CMAKE_CXX_STANDARD_REQUIRED ON)
set(CMAKE_CXX_EXTENSIONS ON) # Recent versions of MLX Requires gnu++17 extensions to compile properly
set(CMAKE_CXX_EXTENSIONS ON) # Recent versions of MLX require gnu++17 extensions to compile properly
set(GGML_BUILD ON)
set(GGML_SHARED ON)
set(GGML_CCACHE ON)
set(GGML_BACKEND_DL ON)
set(GGML_BACKEND_SHARED ON)
set(GGML_SCHED_MAX_COPIES 4)
set(GGML_LLAMAFILE ON)
set(GGML_CUDA_PEER_MAX_BATCH_SIZE 128)
set(GGML_CUDA_GRAPHS ON)
set(GGML_CUDA_FA ON)
set(GGML_CUDA_COMPRESSION_MODE default)
if((CMAKE_OSX_ARCHITECTURES AND NOT CMAKE_OSX_ARCHITECTURES MATCHES "arm64")
OR (NOT CMAKE_OSX_ARCHITECTURES AND NOT CMAKE_SYSTEM_PROCESSOR MATCHES "arm|aarch64|ARM64|ARMv[0-9]+"))
set(GGML_CPU_ALL_VARIANTS ON)
endif()
# GGML backend for inference is provided by llama-server (built separately via
# llama/server/CMakeLists.txt using FetchContent from the pinned llama.cpp source).
# The root CMake project is the orchestration entrypoint; backend-specific
# build rules live in subprojects under cmake/.
if(APPLE)
set(CMAKE_BUILD_RPATH "@loader_path")
@@ -55,7 +48,8 @@ if(APPLE)
endif()
set(OLLAMA_BUILD_DIR ${CMAKE_BINARY_DIR}/lib/ollama)
set(OLLAMA_INSTALL_DIR ${CMAKE_INSTALL_PREFIX}/lib/ollama/${OLLAMA_RUNNER_DIR})
set(OLLAMA_LIB_DIR "lib/ollama" CACHE STRING "Install destination for Ollama runtime payloads")
set(OLLAMA_INSTALL_DIR ${OLLAMA_LIB_DIR}/${OLLAMA_RUNNER_DIR})
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${OLLAMA_BUILD_DIR})
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY_DEBUG ${OLLAMA_BUILD_DIR})
@@ -64,156 +58,9 @@ set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${OLLAMA_BUILD_DIR})
set(CMAKE_LIBRARY_OUTPUT_DIRECTORY_DEBUG ${OLLAMA_BUILD_DIR})
set(CMAKE_LIBRARY_OUTPUT_DIRECTORY_RELEASE ${OLLAMA_BUILD_DIR})
include_directories(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src)
include_directories(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/include)
include_directories(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/ggml-cpu)
include_directories(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/ggml-cpu/amx)
add_compile_definitions(NDEBUG GGML_VERSION=0x0 GGML_COMMIT=0x0)
# Define GGML version variables for shared library SOVERSION
# These are required by ggml/src/CMakeLists.txt for proper library versioning
set(GGML_VERSION_MAJOR 0)
set(GGML_VERSION_MINOR 0)
set(GGML_VERSION_PATCH 0)
set(GGML_VERSION "${GGML_VERSION_MAJOR}.${GGML_VERSION_MINOR}.${GGML_VERSION_PATCH}")
set(GGML_CPU ON)
add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src)
set_property(TARGET ggml PROPERTY EXCLUDE_FROM_ALL TRUE)
get_target_property(CPU_VARIANTS ggml-cpu MANUALLY_ADDED_DEPENDENCIES)
if(NOT CPU_VARIANTS)
set(CPU_VARIANTS "ggml-cpu")
if(EXISTS "${CMAKE_CURRENT_SOURCE_DIR}/llama/server/CMakeLists.txt")
set(OLLAMA_HAVE_LLAMA_SERVER TRUE)
else()
set(OLLAMA_HAVE_LLAMA_SERVER FALSE)
endif()
install(TARGETS ggml-base ${CPU_VARIANTS}
RUNTIME_DEPENDENCIES
PRE_EXCLUDE_REGEXES ".*"
RUNTIME DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT CPU
LIBRARY DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT CPU
FRAMEWORK DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT CPU
)
check_language(CUDA)
if(CMAKE_CUDA_COMPILER)
if(CMAKE_VERSION VERSION_GREATER_EQUAL "3.24" AND NOT CMAKE_CUDA_ARCHITECTURES)
set(CMAKE_CUDA_ARCHITECTURES "native")
endif()
find_package(CUDAToolkit)
add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/ggml-cuda)
install(TARGETS ggml-cuda
RUNTIME_DEPENDENCIES
DIRECTORIES ${CUDAToolkit_BIN_DIR} ${CUDAToolkit_BIN_DIR}/x64 ${CUDAToolkit_LIBRARY_DIR}
PRE_INCLUDE_REGEXES cublas cublasLt cudart
PRE_EXCLUDE_REGEXES ".*"
RUNTIME DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT CUDA
LIBRARY DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT CUDA
)
endif()
set(WINDOWS_AMDGPU_TARGETS_EXCLUDE_REGEX "^gfx(908|90a|1200|1201):xnack[+-]$"
CACHE STRING
"Regular expression describing AMDGPU_TARGETS not supported on Windows. Override to force building these targets. Default \"^gfx(908|90a|1200|1201):xnack[+-]$\"."
)
check_language(HIP)
if(CMAKE_HIP_COMPILER)
set(HIP_PLATFORM "amd")
if(NOT AMDGPU_TARGETS)
find_package(hip REQUIRED)
list(FILTER AMDGPU_TARGETS INCLUDE REGEX "^gfx(94[012]|101[02]|1030|110[012]|120[01])$")
endif()
if(WIN32 AND WINDOWS_AMDGPU_TARGETS_EXCLUDE_REGEX)
list(FILTER AMDGPU_TARGETS EXCLUDE REGEX ${WINDOWS_AMDGPU_TARGETS_EXCLUDE_REGEX})
endif()
if(AMDGPU_TARGETS)
find_package(hip REQUIRED)
add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/ggml-hip)
if (WIN32)
target_compile_definitions(ggml-hip PRIVATE GGML_CUDA_NO_PEER_COPY)
endif()
target_compile_definitions(ggml-hip PRIVATE GGML_HIP_NO_VMM)
install(TARGETS ggml-hip
RUNTIME_DEPENDENCY_SET rocm
RUNTIME DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT HIP
LIBRARY DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT HIP
)
install(RUNTIME_DEPENDENCY_SET rocm
DIRECTORIES ${HIP_BIN_INSTALL_DIR} ${HIP_LIB_INSTALL_DIR}
PRE_INCLUDE_REGEXES hipblas rocblas amdhip64 rocsolver amd_comgr hsa-runtime64 rocsparse tinfo rocprofiler-register drm drm_amdgpu numa elf
PRE_EXCLUDE_REGEXES ".*"
POST_EXCLUDE_REGEXES "system32"
RUNTIME DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT HIP
LIBRARY DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT HIP
)
foreach(HIP_LIB_BIN_INSTALL_DIR IN ITEMS ${HIP_BIN_INSTALL_DIR} ${HIP_LIB_INSTALL_DIR})
if(EXISTS ${HIP_LIB_BIN_INSTALL_DIR}/rocblas)
install(DIRECTORY ${HIP_LIB_BIN_INSTALL_DIR}/rocblas DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT HIP)
break()
endif()
endforeach()
endif()
endif()
if(NOT APPLE)
find_package(Vulkan)
if(Vulkan_FOUND)
add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/ggml-vulkan)
install(TARGETS ggml-vulkan
RUNTIME_DEPENDENCIES
PRE_INCLUDE_REGEXES vulkan
PRE_EXCLUDE_REGEXES ".*"
RUNTIME DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT Vulkan
LIBRARY DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT Vulkan
)
endif()
endif()
option(MLX_ENGINE "Enable MLX backend" OFF)
if(MLX_ENGINE)
message(STATUS "Setting up MLX (this takes a while...)")
add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/x/ml/backend/mlx)
# Find CUDA toolkit if MLX is built with CUDA support
find_package(CUDAToolkit)
install(TARGETS mlx mlxc
RUNTIME_DEPENDENCIES
DIRECTORIES ${CUDAToolkit_BIN_DIR} ${CUDAToolkit_BIN_DIR}/x64 ${CUDAToolkit_LIBRARY_DIR}
PRE_INCLUDE_REGEXES cublas cublasLt cudart nvrtc cudnn nccl
PRE_EXCLUDE_REGEXES ".*"
RUNTIME DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT MLX
LIBRARY DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT MLX
FRAMEWORK DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT MLX
)
# Install the Metal library for macOS arm64 (must be colocated with the binary)
# Metal backend is only built for arm64, not x86_64
if(APPLE AND CMAKE_SYSTEM_PROCESSOR STREQUAL "arm64")
install(FILES ${CMAKE_BINARY_DIR}/_deps/mlx-build/mlx/backend/metal/kernels/mlx.metallib
DESTINATION ${OLLAMA_INSTALL_DIR}
COMPONENT MLX)
endif()
# Manually install cudart and cublas since they might not be picked up as direct dependencies
if(CUDAToolkit_FOUND)
file(GLOB CUDART_LIBS
"${CUDAToolkit_LIBRARY_DIR}/libcudart.so*"
"${CUDAToolkit_LIBRARY_DIR}/libcublas.so*")
if(CUDART_LIBS)
install(FILES ${CUDART_LIBS}
DESTINATION ${OLLAMA_INSTALL_DIR}
COMPONENT MLX)
endif()
endif()
endif()
include(${CMAKE_CURRENT_SOURCE_DIR}/cmake/local.cmake)
+5 -154
View File
@@ -11,99 +11,10 @@
}
},
{
"name": "CPU",
"inherits": [ "Default" ]
},
{
"name": "CUDA",
"inherits": [ "Default" ]
},
{
"name": "CUDA 11",
"inherits": [ "CUDA" ],
"cacheVariables": {
"CMAKE_CUDA_ARCHITECTURES": "50-virtual;60-virtual;61-virtual;70-virtual;75-virtual;80-virtual;86-virtual;87-virtual;89-virtual;90-virtual",
"CMAKE_CUDA_FLAGS": "-Wno-deprecated-gpu-targets -t 2",
"OLLAMA_RUNNER_DIR": "cuda_v11"
}
},
{
"name": "CUDA 12",
"inherits": [ "CUDA" ],
"cacheVariables": {
"CMAKE_CUDA_ARCHITECTURES": "50;52;60;61;70;75;80;86;89;90;90a;120",
"CMAKE_CUDA_FLAGS": "-Wno-deprecated-gpu-targets -t 2",
"OLLAMA_RUNNER_DIR": "cuda_v12"
}
},
{
"name": "CUDA 13",
"inherits": [ "CUDA" ],
"cacheVariables": {
"CMAKE_CUDA_ARCHITECTURES": "75-virtual;80-virtual;86-virtual;87-virtual;89-virtual;90-virtual;90a-virtual;100-virtual;103-virtual;110-virtual;120-virtual;121-virtual",
"CMAKE_CUDA_FLAGS": "-t 4",
"OLLAMA_RUNNER_DIR": "cuda_v13"
}
},
{
"name": "JetPack 5",
"inherits": [ "CUDA" ],
"cacheVariables": {
"CMAKE_CUDA_ARCHITECTURES": "72;87",
"OLLAMA_RUNNER_DIR": "cuda_jetpack5"
}
},
{
"name": "JetPack 6",
"inherits": [ "CUDA" ],
"cacheVariables": {
"CMAKE_CUDA_ARCHITECTURES": "87",
"OLLAMA_RUNNER_DIR": "cuda_jetpack6"
}
},
{
"name": "ROCm",
"name": "MLX Metal",
"inherits": [ "Default" ],
"cacheVariables": {
"CMAKE_HIP_PLATFORM": "amd"
}
},
{
"name": "ROCm 6",
"inherits": [ "ROCm" ],
"cacheVariables": {
"CMAKE_HIP_FLAGS": "-parallel-jobs=4",
"AMDGPU_TARGETS": "gfx940;gfx941;gfx942;gfx1010;gfx1012;gfx1030;gfx1100;gfx1101;gfx1102;gfx1151;gfx1200;gfx1201;gfx908:xnack-;gfx90a:xnack+;gfx90a:xnack-",
"OLLAMA_RUNNER_DIR": "rocm"
}
},
{
"name": "Vulkan",
"inherits": [ "Default" ],
"cacheVariables": {
"OLLAMA_RUNNER_DIR": "vulkan"
}
},
{
"name": "MLX",
"inherits": [ "Default" ],
"cacheVariables": {
"MLX_ENGINE": "ON",
"OLLAMA_RUNNER_DIR": "mlx"
}
},
{
"name": "MLX CUDA 12",
"inherits": [ "MLX", "CUDA 12" ],
"cacheVariables": {
"OLLAMA_RUNNER_DIR": "mlx_cuda_v12"
}
},
{
"name": "MLX CUDA 13",
"inherits": [ "MLX", "CUDA 13" ],
"cacheVariables": {
"OLLAMA_RUNNER_DIR": "mlx_cuda_v13"
"OLLAMA_MLX_BACKENDS": "metal_v3;metal_v4"
}
}
],
@@ -114,69 +25,9 @@
"configuration": "Release"
},
{
"name": "CPU",
"configurePreset": "Default",
"targets": [ "ggml-cpu" ]
},
{
"name": "CUDA",
"configurePreset": "CUDA",
"targets": [ "ggml-cuda" ]
},
{
"name": "CUDA 11",
"inherits": [ "CUDA" ],
"configurePreset": "CUDA 11"
},
{
"name": "CUDA 12",
"inherits": [ "CUDA" ],
"configurePreset": "CUDA 12"
},
{
"name": "CUDA 13",
"inherits": [ "CUDA" ],
"configurePreset": "CUDA 13"
},
{
"name": "JetPack 5",
"inherits": [ "CUDA" ],
"configurePreset": "JetPack 5"
},
{
"name": "JetPack 6",
"inherits": [ "CUDA" ],
"configurePreset": "JetPack 6"
},
{
"name": "ROCm",
"configurePreset": "ROCm",
"targets": [ "ggml-hip" ]
},
{
"name": "ROCm 6",
"inherits": [ "ROCm" ],
"configurePreset": "ROCm 6"
},
{
"name": "Vulkan",
"targets": [ "ggml-vulkan" ],
"configurePreset": "Vulkan"
},
{
"name": "MLX",
"targets": [ "mlx", "mlxc" ],
"configurePreset": "MLX"
},
{
"name": "MLX CUDA 12",
"targets": [ "mlx", "mlxc" ],
"configurePreset": "MLX CUDA 12"
},
{
"name": "MLX CUDA 13",
"targets": [ "mlx", "mlxc" ],
"configurePreset": "MLX CUDA 13"
"name": "MLX Metal",
"targets": [ "ollama-mlx-backends" ],
"configurePreset": "MLX Metal"
}
]
}
+218 -118
View File
@@ -1,140 +1,207 @@
# vim: filetype=dockerfile
ARG FLAVOR=${TARGETARCH}
ARG PARALLEL=8
ARG ROCMVERSION=6.3.3
ARG ROCMVERSION=7.2.1
ARG JETPACK5VERSION=r35.4.1
ARG JETPACK6VERSION=r36.4.0
ARG CMAKEVERSION=3.31.2
ARG NINJAVERSION=1.12.1
ARG VULKANVERSION=1.4.321.1
# We require gcc v10 minimum. v10.3 has regressions, so the rockylinux 8.5 AppStream has the latest compatible version
# Default empty stages for local MLX source overrides.
# Override with: docker build --build-context local-mlx=../mlx --build-context local-mlx-c=../mlx-c
FROM scratch AS local-mlx
FROM scratch AS local-mlx-c
FROM --platform=linux/amd64 rocm/dev-almalinux-8:${ROCMVERSION}-complete AS base-amd64
RUN yum install -y yum-utils \
&& yum-config-manager --add-repo https://dl.rockylinux.org/vault/rocky/8.5/AppStream/\$basearch/os/ \
&& rpm --import https://dl.rockylinux.org/pub/rocky/RPM-GPG-KEY-Rocky-8 \
&& dnf install -y yum-utils ccache gcc-toolset-10-gcc-10.2.1-8.2.el8 gcc-toolset-10-gcc-c++-10.2.1-8.2.el8 gcc-toolset-10-binutils-2.35-11.el8 \
&& dnf install -y ccache \
RUN dnf install -y yum-utils ccache gcc-toolset-11-gcc gcc-toolset-11-gcc-c++ gcc-toolset-11-binutils \
&& yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel8/x86_64/cuda-rhel8.repo
ENV PATH=/opt/rh/gcc-toolset-10/root/usr/bin:$PATH
ARG VULKANVERSION
RUN wget https://sdk.lunarg.com/sdk/download/${VULKANVERSION}/linux/vulkansdk-linux-x86_64-${VULKANVERSION}.tar.xz -O /tmp/vulkansdk-linux-x86_64-${VULKANVERSION}.tar.xz \
&& tar xvf /tmp/vulkansdk-linux-x86_64-${VULKANVERSION}.tar.xz \
&& dnf -y install ninja-build \
&& ln -s /usr/bin/python3 /usr/bin/python \
&& /${VULKANVERSION}/vulkansdk -j 8 vulkan-headers \
&& /${VULKANVERSION}/vulkansdk -j 8 shaderc
RUN cp -r /${VULKANVERSION}/x86_64/include/* /usr/local/include/ \
&& cp -r /${VULKANVERSION}/x86_64/lib/* /usr/local/lib
ENV PATH=/${VULKANVERSION}/x86_64/bin:$PATH
ENV PATH=/opt/rh/gcc-toolset-11/root/usr/bin:$PATH
FROM --platform=linux/arm64 almalinux:8 AS base-arm64
# install epel-release for ccache
RUN yum install -y yum-utils epel-release \
&& dnf install -y clang ccache \
&& dnf install -y clang ccache git \
&& yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel8/sbsa/cuda-rhel8.repo
ENV CC=clang CXX=clang++
FROM base-${TARGETARCH} AS base
ARG CMAKEVERSION
ARG NINJAVERSION
RUN curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKEVERSION}/cmake-${CMAKEVERSION}-linux-$(uname -m).tar.gz | tar xz -C /usr/local --strip-components 1
RUN dnf install -y unzip \
&& curl -fsSL -o /tmp/ninja.zip https://github.com/ninja-build/ninja/releases/download/v${NINJAVERSION}/ninja-linux$([ "$(uname -m)" = "aarch64" ] && echo "-aarch64").zip \
&& unzip /tmp/ninja.zip -d /usr/local/bin \
&& rm /tmp/ninja.zip
ENV CMAKE_GENERATOR=Ninja
ENV LDFLAGS=-s
FROM base AS cpu
#
# GPU toolchain stages — provide compilers for llama-server GPU builds
#
FROM base AS cpu-deps
RUN dnf install -y gcc-toolset-11-gcc gcc-toolset-11-gcc-c++
ENV PATH=/opt/rh/gcc-toolset-11/root/usr/bin:$PATH
ARG PARALLEL
COPY CMakeLists.txt CMakePresets.json .
COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
RUN --mount=type=cache,target=/root/.ccache \
cmake --preset 'CPU' \
&& cmake --build --parallel ${PARALLEL} --preset 'CPU' \
&& cmake --install build --component CPU --strip --parallel ${PARALLEL}
FROM base AS cuda-11
ARG CUDA11VERSION=11.8
RUN dnf install -y cuda-toolkit-${CUDA11VERSION//./-}
ENV PATH=/usr/local/cuda-11/bin:$PATH
ARG PARALLEL
COPY CMakeLists.txt CMakePresets.json .
COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
RUN --mount=type=cache,target=/root/.ccache \
cmake --preset 'CUDA 11' \
&& cmake --build --parallel ${PARALLEL} --preset 'CUDA 11' \
&& cmake --install build --component CUDA --strip --parallel ${PARALLEL}
FROM base AS cuda-12
FROM base AS cuda-12-deps
ARG CUDA12VERSION=12.8
RUN dnf install -y cuda-toolkit-${CUDA12VERSION//./-}
ENV PATH=/usr/local/cuda-12/bin:$PATH
ARG PARALLEL
COPY CMakeLists.txt CMakePresets.json .
COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
RUN --mount=type=cache,target=/root/.ccache \
cmake --preset 'CUDA 12' \
&& cmake --build --parallel ${PARALLEL} --preset 'CUDA 12' \
&& cmake --install build --component CUDA --strip --parallel ${PARALLEL}
FROM base AS cuda-13
FROM base AS cuda-13-deps
ARG CUDA13VERSION=13.0
RUN dnf install -y cuda-toolkit-${CUDA13VERSION//./-}
ENV PATH=/usr/local/cuda-13/bin:$PATH
ARG PARALLEL
COPY CMakeLists.txt CMakePresets.json .
COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
RUN --mount=type=cache,target=/root/.ccache \
cmake --preset 'CUDA 13' \
&& cmake --build --parallel ${PARALLEL} --preset 'CUDA 13' \
&& cmake --install build --component CUDA --strip --parallel ${PARALLEL}
FROM base AS rocm-7-deps
ENV PATH=/opt/rocm/llvm/bin:/opt/rocm/hcc/bin:/opt/rocm/hip/bin:/opt/rocm/bin:$PATH
FROM base AS rocm-6
ENV PATH=/opt/rocm/hcc/bin:/opt/rocm/hip/bin:/opt/rocm/bin:/opt/rocm/hcc/bin:$PATH
ARG PARALLEL
COPY CMakeLists.txt CMakePresets.json .
COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
FROM base AS vulkan-deps
ARG VULKANVERSION
RUN ln -s /usr/bin/python3 /usr/bin/python \
&& wget https://sdk.lunarg.com/sdk/download/${VULKANVERSION}/linux/vulkansdk-linux-x86_64-${VULKANVERSION}.tar.xz -O /tmp/vulkansdk.tar.xz \
&& tar xvf /tmp/vulkansdk.tar.xz -C /tmp \
&& /tmp/${VULKANVERSION}/vulkansdk -j 8 vulkan-headers \
&& /tmp/${VULKANVERSION}/vulkansdk -j 8 spirv-headers \
&& /tmp/${VULKANVERSION}/vulkansdk -j 8 shaderc \
&& cp -r /tmp/${VULKANVERSION}/x86_64/include/* /usr/local/include/ \
&& cp -r /tmp/${VULKANVERSION}/x86_64/lib/* /usr/local/lib \
&& cp -r /tmp/${VULKANVERSION}/x86_64/share/* /usr/local/share/ \
&& cp -r /tmp/${VULKANVERSION}/x86_64/bin/* /usr/local/bin/ \
&& rm -rf /tmp/${VULKANVERSION} /tmp/vulkansdk.tar.xz
ENV VULKAN_SDK=/usr/local
#
# llama-server stages — rebuild when LLAMA_CPP_VERSION, llama/server/, or llama/compat/ changes.
#
# CPU stage: llama-server + ggml-base + ggml-cpu variants → lib/ollama/
# GPU stages: GPU backend .so only → lib/ollama/<variant>/
#
FROM cpu-deps AS llama-server-cpu
COPY LLAMA_CPP_VERSION .
COPY llama/server llama/server
COPY llama/compat llama/compat
RUN --mount=type=cache,target=/root/.ccache \
cmake --preset 'ROCm 6' \
&& cmake --build --parallel ${PARALLEL} --preset 'ROCm 6' \
&& cmake --install build --component HIP --strip --parallel ${PARALLEL}
RUN rm -f dist/lib/ollama/rocm/rocblas/library/*gfx90[06]*
cmake -S llama/server --preset cpu \
&& cmake --build build/llama-server-cpu -- -l $(nproc) \
&& cmake --install build/llama-server-cpu --component llama-server --strip \
&& for lib in \
/usr/lib64/libgomp.so* \
/usr/lib64/libomp.so* \
/opt/rh/gcc-toolset-11/root/usr/lib64/libgomp.so* \
/opt/rh/gcc-toolset-11/root/usr/lib64/libomp.so*; do \
[ -e "$lib" ] && cp -a "$lib" dist/lib/ollama/ || true; \
done
FROM scratch AS publish-llama-server-cpu
COPY --from=llama-server-cpu dist/lib/ollama /lib/ollama/
FROM cuda-12-deps AS llama-server-cuda_v12
COPY LLAMA_CPP_VERSION .
COPY llama/server llama/server
COPY llama/compat llama/compat
RUN --mount=type=cache,target=/root/.ccache \
cmake -S llama/server --preset llama_cuda_v12_linux \
&& cmake --build build/llama-server-cuda_v12 -- -l $(nproc) \
&& cmake --install build/llama-server-cuda_v12 --component llama-server --strip
FROM scratch AS publish-llama-server-cuda_v12
COPY --from=llama-server-cuda_v12 dist/lib/ollama /lib/ollama/
FROM cuda-13-deps AS llama-server-cuda_v13
COPY LLAMA_CPP_VERSION .
COPY llama/server llama/server
COPY llama/compat llama/compat
RUN --mount=type=cache,target=/root/.ccache \
cmake -S llama/server --preset llama_cuda_v13_linux \
&& cmake --build build/llama-server-cuda_v13 -- -l $(nproc) \
&& cmake --install build/llama-server-cuda_v13 --component llama-server --strip
FROM scratch AS publish-llama-server-cuda_v13
COPY --from=llama-server-cuda_v13 dist/lib/ollama /lib/ollama/
FROM rocm-7-deps AS llama-server-rocm_v7_2
ENV CC=clang CXX=clang++
COPY LLAMA_CPP_VERSION .
COPY llama/server llama/server
COPY llama/compat llama/compat
RUN --mount=type=cache,target=/root/.ccache \
cmake -S llama/server --preset rocm_v7_2_linux \
&& cmake --build build/llama-server-rocm_v7_2 -- -l $(nproc) \
&& cmake --install build/llama-server-rocm_v7_2 --component llama-server --strip
RUN rm -f dist/lib/ollama/rocm_v7_2/rocblas/library/*gfx90[06]*
FROM scratch AS publish-llama-server-rocm_v7_2
COPY --from=llama-server-rocm_v7_2 dist/lib/ollama /lib/ollama/
FROM vulkan-deps AS llama-server-vulkan
COPY LLAMA_CPP_VERSION .
COPY llama/server llama/server
COPY llama/compat llama/compat
RUN --mount=type=cache,target=/root/.ccache \
cmake -S llama/server --preset vulkan \
&& cmake --build build/llama-server-vulkan -- -l $(nproc) \
&& cmake --install build/llama-server-vulkan --component llama-server --strip
FROM scratch AS publish-llama-server-vulkan
COPY --from=llama-server-vulkan dist/lib/ollama /lib/ollama/
#
# JetPack stages — self-contained with their own base images
#
FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK5VERSION} AS jetpack-5
ARG CMAKEVERSION
RUN apt-get update && apt-get install -y curl ccache \
&& curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKEVERSION}/cmake-${CMAKEVERSION}-linux-$(uname -m).tar.gz | tar xz -C /usr/local --strip-components 1
COPY CMakeLists.txt CMakePresets.json .
COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
ARG PARALLEL
ARG NINJAVERSION
RUN apt-get update && apt-get install -y curl ccache git unzip \
&& curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKEVERSION}/cmake-${CMAKEVERSION}-linux-$(uname -m).tar.gz | tar xz -C /usr/local --strip-components 1 \
&& curl -fsSL -o /tmp/ninja.zip https://github.com/ninja-build/ninja/releases/download/v${NINJAVERSION}/ninja-linux-aarch64.zip \
&& unzip /tmp/ninja.zip -d /usr/local/bin \
&& rm /tmp/ninja.zip
ENV CMAKE_GENERATOR=Ninja
COPY LLAMA_CPP_VERSION .
COPY llama/server llama/server
COPY llama/compat llama/compat
RUN --mount=type=cache,target=/root/.ccache \
cmake --preset 'JetPack 5' \
&& cmake --build --parallel ${PARALLEL} --preset 'JetPack 5' \
&& cmake --install build --component CUDA --strip --parallel ${PARALLEL}
cmake -S llama/server --preset llama_cuda_jetpack5 \
&& cmake --build build/llama-server-cuda_jetpack5 -- -l $(nproc) \
&& cmake --install build/llama-server-cuda_jetpack5 --component llama-server --strip
FROM scratch AS publish-llama-server-cuda_jetpack5
COPY --from=jetpack-5 dist/lib/ollama /lib/ollama/
FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK6VERSION} AS jetpack-6
ARG CMAKEVERSION
RUN apt-get update && apt-get install -y curl ccache \
&& curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKEVERSION}/cmake-${CMAKEVERSION}-linux-$(uname -m).tar.gz | tar xz -C /usr/local --strip-components 1
COPY CMakeLists.txt CMakePresets.json .
COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
ARG PARALLEL
ARG NINJAVERSION
RUN apt-get update && apt-get install -y curl ccache git unzip \
&& curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKEVERSION}/cmake-${CMAKEVERSION}-linux-$(uname -m).tar.gz | tar xz -C /usr/local --strip-components 1 \
&& curl -fsSL -o /tmp/ninja.zip https://github.com/ninja-build/ninja/releases/download/v${NINJAVERSION}/ninja-linux-aarch64.zip \
&& unzip /tmp/ninja.zip -d /usr/local/bin \
&& rm /tmp/ninja.zip
ENV CMAKE_GENERATOR=Ninja
COPY LLAMA_CPP_VERSION .
COPY llama/server llama/server
COPY llama/compat llama/compat
RUN --mount=type=cache,target=/root/.ccache \
cmake --preset 'JetPack 6' \
&& cmake --build --parallel ${PARALLEL} --preset 'JetPack 6' \
&& cmake --install build --component CUDA --strip --parallel ${PARALLEL}
cmake -S llama/server --preset llama_cuda_jetpack6 \
&& cmake --build build/llama-server-cuda_jetpack6 -- -l $(nproc) \
&& cmake --install build/llama-server-cuda_jetpack6 --component llama-server --strip
FROM base AS vulkan
COPY CMakeLists.txt CMakePresets.json .
COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
RUN --mount=type=cache,target=/root/.ccache \
cmake --preset 'Vulkan' \
&& cmake --build --parallel --preset 'Vulkan' \
&& cmake --install build --component Vulkan --strip --parallel 8
FROM scratch AS publish-llama-server-cuda_jetpack6
COPY --from=jetpack-6 dist/lib/ollama /lib/ollama/
#
# MLX stage
#
FROM base AS mlx
ARG CUDA13VERSION=13.0
ARG OLLAMA_MLX_BUILD_JOBS=
ARG OLLAMA_MLX_NVCC_THREADS=2
ARG MLX_CUDA_RAM_MB=
RUN dnf install -y cuda-toolkit-${CUDA13VERSION//./-} \
&& dnf install -y openblas-devel lapack-devel \
&& dnf install -y libcudnn9-cuda-13 libcudnn9-devel-cuda-13 \
@@ -143,27 +210,33 @@ ENV PATH=/usr/local/cuda-13/bin:$PATH
ENV BLAS_INCLUDE_DIRS=/usr/include/openblas
ENV LAPACK_INCLUDE_DIRS=/usr/include/openblas
ENV CGO_LDFLAGS="-L/usr/local/cuda-13/lib64 -L/usr/local/cuda-13/targets/x86_64-linux/lib/stubs"
ARG PARALLEL
WORKDIR /go/src/github.com/ollama/ollama
COPY CMakeLists.txt CMakePresets.json .
COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
COPY x/ml/backend/mlx x/ml/backend/mlx
COPY cmake cmake
COPY x/imagegen/mlx x/imagegen/mlx
COPY go.mod go.sum .
COPY MLX_VERSION MLX_C_VERSION .
RUN curl -fsSL https://golang.org/dl/go$(awk '/^go/ { print $2 }' go.mod).linux-$(case $(uname -m) in x86_64) echo amd64 ;; aarch64) echo arm64 ;; esac).tar.gz | tar xz -C /usr/local
ENV PATH=/usr/local/go/bin:$PATH
RUN go mod download
RUN --mount=type=cache,target=/root/.ccache \
cmake --preset 'MLX CUDA 13' -DBLAS_INCLUDE_DIRS=/usr/include/openblas -DLAPACK_INCLUDE_DIRS=/usr/include/openblas \
&& cmake --build --parallel ${PARALLEL} --preset 'MLX CUDA 13' \
&& cmake --install build --component MLX --strip --parallel ${PARALLEL}
COPY . .
ARG GOFLAGS="'-ldflags=-w -s'"
ENV CGO_ENABLED=1
ARG CGO_CFLAGS
ARG CGO_CXXFLAGS
RUN mkdir -p dist/bin
RUN --mount=type=cache,target=/root/.cache/go-build \
go build -tags mlx -trimpath -buildmode=pie -o dist/bin/ollama-mlx .
--mount=type=bind,from=local-mlx,target=/tmp/local-mlx \
--mount=type=bind,from=local-mlx-c,target=/tmp/local-mlx-c \
if [ -f /tmp/local-mlx/CMakeLists.txt ]; then \
export OLLAMA_MLX_SOURCE=/tmp/local-mlx; \
fi \
&& if [ -f /tmp/local-mlx-c/CMakeLists.txt ]; then \
export OLLAMA_MLX_C_SOURCE=/tmp/local-mlx-c; \
fi \
&& cmake -S . -B build/mlx_cuda_v13 -DOLLAMA_MLX_BACKENDS=cuda_v13 -DBLAS_INCLUDE_DIRS=/usr/include/openblas -DLAPACK_INCLUDE_DIRS=/usr/include/openblas -DCMAKE_CUDA_FLAGS="-t ${OLLAMA_MLX_NVCC_THREADS}" ${MLX_CUDA_RAM_MB:+-DMLX_CUDA_RAM_MB=${MLX_CUDA_RAM_MB}} -DOLLAMA_PAYLOAD_INSTALL_PREFIX=/go/src/github.com/ollama/ollama/dist \
&& cmake --build build/mlx_cuda_v13 --target ollama-mlx-cuda_v13 -- -l $(nproc) ${OLLAMA_MLX_BUILD_JOBS:+-j ${OLLAMA_MLX_BUILD_JOBS}}
FROM scratch AS publish-mlx
COPY --from=mlx /go/src/github.com/ollama/ollama/dist/lib/ollama /lib/ollama/
#
# Go build
#
FROM base AS build
WORKDIR /go/src/github.com/ollama/ollama
@@ -176,40 +249,67 @@ ARG GOFLAGS="'-ldflags=-w -s'"
ENV CGO_ENABLED=1
ARG CGO_CFLAGS
ARG CGO_CXXFLAGS
ENV CGO_CFLAGS="${CGO_CFLAGS}"
ENV CGO_CXXFLAGS="${CGO_CXXFLAGS}"
RUN --mount=type=cache,target=/root/.cache/go-build \
go build -trimpath -buildmode=pie -o /bin/ollama .
FROM scratch AS publish-go
COPY --from=build /bin/ollama /bin/ollama
#
# Assembly stages — combine llama-server variants + GPU runtime libs
#
FROM --platform=linux/amd64 scratch AS amd64
# COPY --from=cuda-11 dist/lib/ollama/ /lib/ollama/
COPY --from=cuda-12 dist/lib/ollama /lib/ollama/
COPY --from=cuda-13 dist/lib/ollama /lib/ollama/
COPY --from=vulkan dist/lib/ollama /lib/ollama/
COPY --from=llama-server-cpu dist/lib/ollama /lib/ollama/
COPY --from=llama-server-cuda_v12 dist/lib/ollama /lib/ollama/
COPY --from=llama-server-cuda_v13 dist/lib/ollama /lib/ollama/
COPY --from=llama-server-vulkan dist/lib/ollama /lib/ollama/
COPY --from=mlx /go/src/github.com/ollama/ollama/dist/lib/ollama /lib/ollama/
COPY --from=mlx /go/src/github.com/ollama/ollama/dist/bin/ /bin/
FROM --platform=linux/arm64 scratch AS arm64
# COPY --from=cuda-11 dist/lib/ollama/ /lib/ollama/
COPY --from=cuda-12 dist/lib/ollama /lib/ollama/
COPY --from=cuda-13 dist/lib/ollama/ /lib/ollama/
COPY --from=llama-server-cpu dist/lib/ollama /lib/ollama/
COPY --from=llama-server-cuda_v12 dist/lib/ollama /lib/ollama/
COPY --from=llama-server-cuda_v13 dist/lib/ollama /lib/ollama/
COPY --from=jetpack-5 dist/lib/ollama/ /lib/ollama/
COPY --from=jetpack-6 dist/lib/ollama/ /lib/ollama/
FROM scratch AS rocm
COPY --from=rocm-6 dist/lib/ollama /lib/ollama
COPY --from=llama-server-cpu dist/lib/ollama /lib/ollama
COPY --from=llama-server-rocm_v7_2 dist/lib/ollama /lib/ollama
FROM ${FLAVOR} AS archive
ARG VULKANVERSION
COPY --from=cpu dist/lib/ollama /lib/ollama
FROM --platform=linux/amd64 scratch AS amd64-archive
COPY --from=amd64 /lib/ollama /lib/ollama/
COPY --from=llama-server-rocm_v7_2 dist/lib/ollama /lib/ollama/
FROM --platform=linux/arm64 scratch AS arm64-archive
COPY --from=arm64 /lib/ollama /lib/ollama/
FROM ${TARGETARCH}-archive AS archive
COPY --from=build /bin/ollama /bin/ollama
FROM ${FLAVOR} AS image-archive
COPY --from=build /bin/ollama /bin/ollama
FROM ubuntu:24.04
RUN apt-get update \
ARG APT_MIRROR=http://archive.ubuntu.com/ubuntu
ARG APT_PORTS_MIRROR=http://ports.ubuntu.com/ubuntu-ports
RUN sed -i \
-e "s|http://archive.ubuntu.com/ubuntu|$APT_MIRROR|g" \
-e "s|http://ports.ubuntu.com/ubuntu-ports|$APT_PORTS_MIRROR|g" \
/etc/apt/sources.list.d/ubuntu.sources \
&& apt-get update \
&& apt-get install -y ca-certificates libvulkan1 libopenblas0 \
&& sed -i \
-e "s|$APT_MIRROR|http://archive.ubuntu.com/ubuntu|g" \
-e "s|$APT_PORTS_MIRROR|http://ports.ubuntu.com/ubuntu-ports|g" \
/etc/apt/sources.list.d/ubuntu.sources \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/*
COPY --from=archive /bin /usr/bin
COPY --from=image-archive /bin /usr/bin
ENV PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
COPY --from=archive /lib/ollama /usr/lib/ollama
COPY --from=image-archive /lib/ollama /usr/lib/ollama
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
ENV NVIDIA_VISIBLE_DEVICES=all
+1
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b9452
+1
View File
@@ -0,0 +1 @@
fba4470b89073180056c9ea46c443051375f7399
+1
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@@ -0,0 +1 @@
2165dc08d7b33258260aa849d39f087d50e62962
-76
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@@ -1,76 +0,0 @@
UPSTREAM=https://github.com/ggml-org/llama.cpp.git
WORKDIR=llama/vendor
FETCH_HEAD=ec98e2002
.PHONY: help
help:
@echo "Available targets:"
@echo " sync Sync with upstream repositories"
@echo " checkout Checkout upstream repository"
@echo " apply-patches Apply patches to local repository"
@echo " format-patches Format patches from local repository"
@echo " clean Clean local repository"
@echo
@echo "Example:"
@echo " make -f $(lastword $(MAKEFILE_LIST)) clean apply-patches sync"
.PHONY: sync
sync: llama/build-info.cpp ml/backend/ggml/ggml/src/ggml-metal/ggml-metal-embed.metal
llama/build-info.cpp: llama/build-info.cpp.in llama/llama.cpp
sed -e 's|@FETCH_HEAD@|$(FETCH_HEAD)|' <$< >$@
ml/backend/ggml/ggml/src/ggml-metal/ggml-metal-embed.metal: ml/backend/ggml/ggml
go generate ./$(@D)
.PHONY: llama/llama.cpp
llama/llama.cpp: llama/vendor
rsync -arvzc --delete -f "include LICENSE" -f "merge $@/.rsync-filter" $(addprefix $<,/LICENSE /) $@
.PHONY: ml/backend/ggml/ggml
ml/backend/ggml/ggml: llama/vendor
rsync -arvzc --delete -f "include LICENSE" -f "merge $@/.rsync-filter" $(addprefix $<,/LICENSE /ggml/) $@
PATCHES=$(wildcard llama/patches/*.patch)
PATCHED=$(join $(dir $(PATCHES)), $(addsuffix ed, $(addprefix ., $(notdir $(PATCHES)))))
.PHONY: apply-patches
.NOTPARALLEL:
apply-patches: $(PATCHED)
llama/patches/.%.patched: llama/patches/%.patch
@if git -c user.name=nobody -c 'user.email=<>' -C $(WORKDIR) am -3 $(realpath $<); then \
touch $@; \
else \
echo "Patch failed. Resolve any conflicts then continue."; \
echo "1. Run 'git -C $(WORKDIR) am --continue'"; \
echo "2. Run 'make -f $(lastword $(MAKEFILE_LIST)) format-patches'"; \
echo "3. Run 'make -f $(lastword $(MAKEFILE_LIST)) clean apply-patches'"; \
exit 1; \
fi
.PHONY: checkout
checkout: $(WORKDIR)
git -C $(WORKDIR) fetch
git -C $(WORKDIR) checkout -f $(FETCH_HEAD)
$(WORKDIR):
git clone $(UPSTREAM) $(WORKDIR)
.PHONY: format-patches
format-patches: llama/patches
git -C $(WORKDIR) format-patch \
--no-signature \
--no-numbered \
--zero-commit \
-o $(realpath $<) \
$(FETCH_HEAD)
.PHONY: clean
clean: checkout
@git -C $(WORKDIR) am --abort || true
$(RM) llama/patches/.*.patched
.PHONY: print-base
print-base:
@echo $(FETCH_HEAD)
+292 -583
View File
@@ -1,20 +1,30 @@
<div align="center">
  <a href="https://ollama.com">
<img alt="ollama" width="240" src="https://github.com/ollama/ollama/assets/3325447/0d0b44e2-8f4a-4e99-9b52-a5c1c741c8f7">
<p align="center">
<a href="https://ollama.com">
<img src="https://github.com/ollama/ollama/assets/3325447/0d0b44e2-8f4a-4e99-9b52-a5c1c741c8f7" alt="ollama" width="200"/>
</a>
</div>
</p>
# Ollama
Get up and running with large language models.
Start building with open models.
## Download
### macOS
[Download](https://ollama.com/download/Ollama.dmg)
```shell
curl -fsSL https://ollama.com/install.sh | sh
```
or [download manually](https://ollama.com/download/Ollama.dmg)
### Windows
[Download](https://ollama.com/download/OllamaSetup.exe)
```shell
irm https://ollama.com/install.ps1 | iex
```
or [download manually](https://ollama.com/download/OllamaSetup.exe)
### Linux
@@ -36,612 +46,311 @@ The official [Ollama Docker image](https://hub.docker.com/r/ollama/ollama) `olla
### Community
- [Discord](https://discord.gg/ollama)
- [𝕏 (Twitter)](https://x.com/ollama)
- [Reddit](https://reddit.com/r/ollama)
## Quickstart
## Get started
To run and chat with [Gemma 3](https://ollama.com/library/gemma3):
```
ollama
```
```shell
You'll be prompted to run a model or connect Ollama to your existing agents or applications such as `Claude Code`, `OpenClaw`, `OpenCode` , `Codex`, `Copilot`, and more.
### Coding
To launch a specific integration:
```
ollama launch claude
```
Supported integrations include [Claude Code](https://docs.ollama.com/integrations/claude-code), [Codex](https://docs.ollama.com/integrations/codex), [Copilot CLI](https://docs.ollama.com/integrations/copilot-cli), [Droid](https://docs.ollama.com/integrations/droid), and [OpenCode](https://docs.ollama.com/integrations/opencode).
### AI assistant
Use [OpenClaw](https://docs.ollama.com/integrations/openclaw) to turn Ollama into a personal AI assistant across WhatsApp, Telegram, Slack, Discord, and more:
```
ollama launch openclaw
```
### Chat with a model
Run and chat with [Gemma 3](https://ollama.com/library/gemma3):
```
ollama run gemma3
```
## Model library
See [ollama.com/library](https://ollama.com/library) for the full list.
Ollama supports a list of models available on [ollama.com/library](https://ollama.com/library 'ollama model library')
Here are some example models that can be downloaded:
| Model | Parameters | Size | Download |
| ------------------ | ---------- | ----- | -------------------------------- |
| Gemma 3 | 1B | 815MB | `ollama run gemma3:1b` |
| Gemma 3 | 4B | 3.3GB | `ollama run gemma3` |
| Gemma 3 | 12B | 8.1GB | `ollama run gemma3:12b` |
| Gemma 3 | 27B | 17GB | `ollama run gemma3:27b` |
| QwQ | 32B | 20GB | `ollama run qwq` |
| DeepSeek-R1 | 7B | 4.7GB | `ollama run deepseek-r1` |
| DeepSeek-R1 | 671B | 404GB | `ollama run deepseek-r1:671b` |
| Llama 4 | 109B | 67GB | `ollama run llama4:scout` |
| Llama 4 | 400B | 245GB | `ollama run llama4:maverick` |
| Llama 3.3 | 70B | 43GB | `ollama run llama3.3` |
| Llama 3.2 | 3B | 2.0GB | `ollama run llama3.2` |
| Llama 3.2 | 1B | 1.3GB | `ollama run llama3.2:1b` |
| Llama 3.2 Vision | 11B | 7.9GB | `ollama run llama3.2-vision` |
| Llama 3.2 Vision | 90B | 55GB | `ollama run llama3.2-vision:90b` |
| Llama 3.1 | 8B | 4.7GB | `ollama run llama3.1` |
| Llama 3.1 | 405B | 231GB | `ollama run llama3.1:405b` |
| Phi 4 | 14B | 9.1GB | `ollama run phi4` |
| Phi 4 Mini | 3.8B | 2.5GB | `ollama run phi4-mini` |
| Mistral | 7B | 4.1GB | `ollama run mistral` |
| Moondream 2 | 1.4B | 829MB | `ollama run moondream` |
| Neural Chat | 7B | 4.1GB | `ollama run neural-chat` |
| Starling | 7B | 4.1GB | `ollama run starling-lm` |
| Code Llama | 7B | 3.8GB | `ollama run codellama` |
| Llama 2 Uncensored | 7B | 3.8GB | `ollama run llama2-uncensored` |
| LLaVA | 7B | 4.5GB | `ollama run llava` |
| Granite-3.3 | 8B | 4.9GB | `ollama run granite3.3` |
> [!NOTE]
> You should have at least 8 GB of RAM available to run the 7B models, 16 GB to run the 13B models, and 32 GB to run the 33B models.
## Customize a model
### Import from GGUF
Ollama supports importing GGUF models in the Modelfile:
1. Create a file named `Modelfile`, with a `FROM` instruction with the local filepath to the model you want to import.
```
FROM ./vicuna-33b.Q4_0.gguf
```
2. Create the model in Ollama
```shell
ollama create example -f Modelfile
```
3. Run the model
```shell
ollama run example
```
### Import from Safetensors
See the [guide](https://docs.ollama.com/import) on importing models for more information.
### Customize a prompt
Models from the Ollama library can be customized with a prompt. For example, to customize the `llama3.2` model:
```shell
ollama pull llama3.2
```
Create a `Modelfile`:
```
FROM llama3.2
# set the temperature to 1 [higher is more creative, lower is more coherent]
PARAMETER temperature 1
# set the system message
SYSTEM """
You are Mario from Super Mario Bros. Answer as Mario, the assistant, only.
"""
```
Next, create and run the model:
```
ollama create mario -f ./Modelfile
ollama run mario
>>> hi
Hello! It's your friend Mario.
```
For more information on working with a Modelfile, see the [Modelfile](https://docs.ollama.com/modelfile) documentation.
## CLI Reference
### Create a model
`ollama create` is used to create a model from a Modelfile.
```shell
ollama create mymodel -f ./Modelfile
```
### Pull a model
```shell
ollama pull llama3.2
```
> This command can also be used to update a local model. Only the diff will be pulled.
### Remove a model
```shell
ollama rm llama3.2
```
### Copy a model
```shell
ollama cp llama3.2 my-model
```
### Multiline input
For multiline input, you can wrap text with `"""`:
```
>>> """Hello,
... world!
... """
I'm a basic program that prints the famous "Hello, world!" message to the console.
```
### Multimodal models
```
ollama run llava "What's in this image? /Users/jmorgan/Desktop/smile.png"
```
> **Output**: The image features a yellow smiley face, which is likely the central focus of the picture.
### Pass the prompt as an argument
```shell
ollama run llama3.2 "Summarize this file: $(cat README.md)"
```
> **Output**: Ollama is a lightweight, extensible framework for building and running language models on the local machine. It provides a simple API for creating, running, and managing models, as well as a library of pre-built models that can be easily used in a variety of applications.
### Show model information
```shell
ollama show llama3.2
```
### List models on your computer
```shell
ollama list
```
### List which models are currently loaded
```shell
ollama ps
```
### Stop a model which is currently running
```shell
ollama stop llama3.2
```
### Generate embeddings from the CLI
```shell
ollama run embeddinggemma "Your text to embed"
```
You can also pipe text for scripted workflows:
```shell
echo "Your text to embed" | ollama run embeddinggemma
```
### Start Ollama
`ollama serve` is used when you want to start ollama without running the desktop application.
## Building
See the [developer guide](https://github.com/ollama/ollama/blob/main/docs/development.md)
### Running local builds
Next, start the server:
```shell
./ollama serve
```
Finally, in a separate shell, run a model:
```shell
./ollama run llama3.2
```
See the [quickstart guide](https://docs.ollama.com/quickstart) for more details.
## REST API
Ollama has a REST API for running and managing models.
### Generate a response
```shell
curl http://localhost:11434/api/generate -d '{
"model": "llama3.2",
"prompt":"Why is the sky blue?"
}'
```
### Chat with a model
```shell
curl http://localhost:11434/api/chat -d '{
"model": "llama3.2",
"messages": [
{ "role": "user", "content": "why is the sky blue?" }
]
"model": "gemma3",
"messages": [{
"role": "user",
"content": "Why is the sky blue?"
}],
"stream": false
}'
```
See the [API documentation](./docs/api.md) for all endpoints.
See the [API documentation](https://docs.ollama.com/api) for all endpoints.
### Python
```
pip install ollama
```
```python
from ollama import chat
response = chat(model='gemma3', messages=[
{
'role': 'user',
'content': 'Why is the sky blue?',
},
])
print(response.message.content)
```
### JavaScript
```
npm i ollama
```
```javascript
import ollama from "ollama";
const response = await ollama.chat({
model: "gemma3",
messages: [{ role: "user", content: "Why is the sky blue?" }],
});
console.log(response.message.content);
```
## Supported backends
- [llama.cpp](https://github.com/ggml-org/llama.cpp) project founded by Georgi Gerganov.
## Documentation
- [CLI reference](https://docs.ollama.com/cli)
- [REST API reference](https://docs.ollama.com/api)
- [Importing models](https://docs.ollama.com/import)
- [Modelfile reference](https://docs.ollama.com/modelfile)
- [Building from source](https://github.com/ollama/ollama/blob/main/docs/development.md)
## Community Integrations
### Web & Desktop
> Want to add your project? Open a pull request.
- [Open WebUI](https://github.com/open-webui/open-webui)
- [SwiftChat (macOS with ReactNative)](https://github.com/aws-samples/swift-chat)
- [Enchanted (macOS native)](https://github.com/AugustDev/enchanted)
- [Hollama](https://github.com/fmaclen/hollama)
- [Lollms WebUI (Single user)](https://github.com/ParisNeo/lollms-webui)
- [Lollms (Multi users)](https://github.com/ParisNeo/lollms)
- [LibreChat](https://github.com/danny-avila/LibreChat)
- [Bionic GPT](https://github.com/bionic-gpt/bionic-gpt)
- [HTML UI](https://github.com/rtcfirefly/ollama-ui)
- [AI-UI](https://github.com/bajahaw/ai-ui)
- [Saddle](https://github.com/jikkuatwork/saddle)
- [TagSpaces](https://www.tagspaces.org) (A platform for file-based apps, [utilizing Ollama](https://docs.tagspaces.org/ai/) for the generation of tags and descriptions)
- [Chatbot UI](https://github.com/ivanfioravanti/chatbot-ollama)
- [Chatbot UI v2](https://github.com/mckaywrigley/chatbot-ui)
- [Typescript UI](https://github.com/ollama-interface/Ollama-Gui?tab=readme-ov-file)
- [Minimalistic React UI for Ollama Models](https://github.com/richawo/minimal-llm-ui)
- [Ollamac](https://github.com/kevinhermawan/Ollamac)
- [big-AGI](https://github.com/enricoros/big-AGI)
- [Cheshire Cat assistant framework](https://github.com/cheshire-cat-ai/core)
- [Amica](https://github.com/semperai/amica)
- [chatd](https://github.com/BruceMacD/chatd)
- [Ollama-SwiftUI](https://github.com/kghandour/Ollama-SwiftUI)
- [Dify.AI](https://github.com/langgenius/dify)
- [MindMac](https://mindmac.app)
- [NextJS Web Interface for Ollama](https://github.com/jakobhoeg/nextjs-ollama-llm-ui)
- [Msty](https://msty.app)
- [Chatbox](https://github.com/Bin-Huang/Chatbox)
- [WinForm Ollama Copilot](https://github.com/tgraupmann/WinForm_Ollama_Copilot)
- [NextChat](https://github.com/ChatGPTNextWeb/ChatGPT-Next-Web) with [Get Started Doc](https://docs.nextchat.dev/models/ollama)
- [Alpaca WebUI](https://github.com/mmo80/alpaca-webui)
- [OllamaGUI](https://github.com/enoch1118/ollamaGUI)
- [OpenAOE](https://github.com/InternLM/OpenAOE)
- [Odin Runes](https://github.com/leonid20000/OdinRunes)
- [LLM-X](https://github.com/mrdjohnson/llm-x) (Progressive Web App)
- [AnythingLLM (Docker + MacOs/Windows/Linux native app)](https://github.com/Mintplex-Labs/anything-llm)
- [Ollama Basic Chat: Uses HyperDiv Reactive UI](https://github.com/rapidarchitect/ollama_basic_chat)
- [Ollama-chats RPG](https://github.com/drazdra/ollama-chats)
- [IntelliBar](https://intellibar.app/) (AI-powered assistant for macOS)
- [Jirapt](https://github.com/AliAhmedNada/jirapt) (Jira Integration to generate issues, tasks, epics)
- [ojira](https://github.com/AliAhmedNada/ojira) (Jira chrome plugin to easily generate descriptions for tasks)
- [QA-Pilot](https://github.com/reid41/QA-Pilot) (Interactive chat tool that can leverage Ollama models for rapid understanding and navigation of GitHub code repositories)
- [ChatOllama](https://github.com/sugarforever/chat-ollama) (Open Source Chatbot based on Ollama with Knowledge Bases)
- [CRAG Ollama Chat](https://github.com/Nagi-ovo/CRAG-Ollama-Chat) (Simple Web Search with Corrective RAG)
- [RAGFlow](https://github.com/infiniflow/ragflow) (Open-source Retrieval-Augmented Generation engine based on deep document understanding)
- [StreamDeploy](https://github.com/StreamDeploy-DevRel/streamdeploy-llm-app-scaffold) (LLM Application Scaffold)
- [chat](https://github.com/swuecho/chat) (chat web app for teams)
- [Lobe Chat](https://github.com/lobehub/lobe-chat) with [Integrating Doc](https://lobehub.com/docs/self-hosting/examples/ollama)
- [Ollama RAG Chatbot](https://github.com/datvodinh/rag-chatbot.git) (Local Chat with multiple PDFs using Ollama and RAG)
- [BrainSoup](https://www.nurgo-software.com/products/brainsoup) (Flexible native client with RAG & multi-agent automation)
- [macai](https://github.com/Renset/macai) (macOS client for Ollama, ChatGPT, and other compatible API back-ends)
- [RWKV-Runner](https://github.com/josStorer/RWKV-Runner) (RWKV offline LLM deployment tool, also usable as a client for ChatGPT and Ollama)
- [Ollama Grid Search](https://github.com/dezoito/ollama-grid-search) (app to evaluate and compare models)
- [Olpaka](https://github.com/Otacon/olpaka) (User-friendly Flutter Web App for Ollama)
- [Casibase](https://casibase.org) (An open source AI knowledge base and dialogue system combining the latest RAG, SSO, ollama support, and multiple large language models.)
- [OllamaSpring](https://github.com/CrazyNeil/OllamaSpring) (Ollama Client for macOS)
- [LLocal.in](https://github.com/kartikm7/llocal) (Easy to use Electron Desktop Client for Ollama)
- [Shinkai Desktop](https://github.com/dcSpark/shinkai-apps) (Two click install Local AI using Ollama + Files + RAG)
- [AiLama](https://github.com/zeyoyt/ailama) (A Discord User App that allows you to interact with Ollama anywhere in Discord)
- [Ollama with Google Mesop](https://github.com/rapidarchitect/ollama_mesop/) (Mesop Chat Client implementation with Ollama)
- [R2R](https://github.com/SciPhi-AI/R2R) (Open-source RAG engine)
- [Ollama-Kis](https://github.com/elearningshow/ollama-kis) (A simple easy-to-use GUI with sample custom LLM for Drivers Education)
- [OpenGPA](https://opengpa.org) (Open-source offline-first Enterprise Agentic Application)
- [Painting Droid](https://github.com/mateuszmigas/painting-droid) (Painting app with AI integrations)
- [Kerlig AI](https://www.kerlig.com/) (AI writing assistant for macOS)
- [AI Studio](https://github.com/MindWorkAI/AI-Studio)
- [Sidellama](https://github.com/gyopak/sidellama) (browser-based LLM client)
- [LLMStack](https://github.com/trypromptly/LLMStack) (No-code multi-agent framework to build LLM agents and workflows)
- [BoltAI for Mac](https://boltai.com) (AI Chat Client for Mac)
- [Harbor](https://github.com/av/harbor) (Containerized LLM Toolkit with Ollama as default backend)
- [PyGPT](https://github.com/szczyglis-dev/py-gpt) (AI desktop assistant for Linux, Windows, and Mac)
- [Alpaca](https://github.com/Jeffser/Alpaca) (An Ollama client application for Linux and macOS made with GTK4 and Adwaita)
- [AutoGPT](https://github.com/Significant-Gravitas/AutoGPT/blob/master/docs/content/platform/ollama.md) (AutoGPT Ollama integration)
- [Go-CREW](https://www.jonathanhecl.com/go-crew/) (Powerful Offline RAG in Golang)
- [PartCAD](https://github.com/openvmp/partcad/) (CAD model generation with OpenSCAD and CadQuery)
- [Ollama4j Web UI](https://github.com/ollama4j/ollama4j-web-ui) - Java-based Web UI for Ollama built with Vaadin, Spring Boot, and Ollama4j
- [PyOllaMx](https://github.com/kspviswa/pyOllaMx) - macOS application capable of chatting with both Ollama and Apple MLX models.
- [Cline](https://github.com/cline/cline) - Formerly known as Claude Dev is a VS Code extension for multi-file/whole-repo coding
- [Void](https://github.com/voideditor/void) (Open source AI code editor and Cursor alternative)
- [Cherry Studio](https://github.com/kangfenmao/cherry-studio) (Desktop client with Ollama support)
- [ConfiChat](https://github.com/1runeberg/confichat) (Lightweight, standalone, multi-platform, and privacy-focused LLM chat interface with optional encryption)
- [Archyve](https://github.com/nickthecook/archyve) (RAG-enabling document library)
- [crewAI with Mesop](https://github.com/rapidarchitect/ollama-crew-mesop) (Mesop Web Interface to run crewAI with Ollama)
- [Tkinter-based client](https://github.com/chyok/ollama-gui) (Python tkinter-based Client for Ollama)
- [LLMChat](https://github.com/trendy-design/llmchat) (Privacy focused, 100% local, intuitive all-in-one chat interface)
- [Local Multimodal AI Chat](https://github.com/Leon-Sander/Local-Multimodal-AI-Chat) (Ollama-based LLM Chat with support for multiple features, including PDF RAG, voice chat, image-based interactions, and integration with OpenAI.)
- [ARGO](https://github.com/xark-argo/argo) (Locally download and run Ollama and Huggingface models with RAG and deep research on Mac/Windows/Linux)
- [OrionChat](https://github.com/EliasPereirah/OrionChat) - OrionChat is a web interface for chatting with different AI providers
- [G1](https://github.com/bklieger-groq/g1) (Prototype of using prompting strategies to improve the LLM's reasoning through o1-like reasoning chains.)
- [Web management](https://github.com/lemonit-eric-mao/ollama-web-management) (Web management page)
- [Promptery](https://github.com/promptery/promptery) (desktop client for Ollama.)
- [Ollama App](https://github.com/JHubi1/ollama-app) (Modern and easy-to-use multi-platform client for Ollama)
- [chat-ollama](https://github.com/annilq/chat-ollama) (a React Native client for Ollama)
- [SpaceLlama](https://github.com/tcsenpai/spacellama) (Firefox and Chrome extension to quickly summarize web pages with ollama in a sidebar)
- [YouLama](https://github.com/tcsenpai/youlama) (Webapp to quickly summarize any YouTube video, supporting Invidious as well)
- [DualMind](https://github.com/tcsenpai/dualmind) (Experimental app allowing two models to talk to each other in the terminal or in a web interface)
- [ollamarama-matrix](https://github.com/h1ddenpr0cess20/ollamarama-matrix) (Ollama chatbot for the Matrix chat protocol)
- [ollama-chat-app](https://github.com/anan1213095357/ollama-chat-app) (Flutter-based chat app)
- [Perfect Memory AI](https://www.perfectmemory.ai/) (Productivity AI assists personalized by what you have seen on your screen, heard, and said in the meetings)
- [Hexabot](https://github.com/hexastack/hexabot) (A conversational AI builder)
- [Reddit Rate](https://github.com/rapidarchitect/reddit_analyzer) (Search and Rate Reddit topics with a weighted summation)
- [OpenTalkGpt](https://github.com/adarshM84/OpenTalkGpt) (Chrome Extension to manage open-source models supported by Ollama, create custom models, and chat with models from a user-friendly UI)
- [VT](https://github.com/vinhnx/vt.ai) (A minimal multimodal AI chat app, with dynamic conversation routing. Supports local models via Ollama)
- [Nosia](https://github.com/nosia-ai/nosia) (Easy to install and use RAG platform based on Ollama)
- [Witsy](https://github.com/nbonamy/witsy) (An AI Desktop application available for Mac/Windows/Linux)
- [Abbey](https://github.com/US-Artificial-Intelligence/abbey) (A configurable AI interface server with notebooks, document storage, and YouTube support)
- [Minima](https://github.com/dmayboroda/minima) (RAG with on-premises or fully local workflow)
- [aidful-ollama-model-delete](https://github.com/AidfulAI/aidful-ollama-model-delete) (User interface for simplified model cleanup)
- [Perplexica](https://github.com/ItzCrazyKns/Perplexica) (An AI-powered search engine & an open-source alternative to Perplexity AI)
- [Ollama Chat WebUI for Docker ](https://github.com/oslook/ollama-webui) (Support for local docker deployment, lightweight ollama webui)
- [AI Toolkit for Visual Studio Code](https://aka.ms/ai-tooklit/ollama-docs) (Microsoft-official VS Code extension to chat, test, evaluate models with Ollama support, and use them in your AI applications.)
- [MinimalNextOllamaChat](https://github.com/anilkay/MinimalNextOllamaChat) (Minimal Web UI for Chat and Model Control)
- [Chipper](https://github.com/TilmanGriesel/chipper) AI interface for tinkerers (Ollama, Haystack RAG, Python)
- [ChibiChat](https://github.com/CosmicEventHorizon/ChibiChat) (Kotlin-based Android app to chat with Ollama and Koboldcpp API endpoints)
- [LocalLLM](https://github.com/qusaismael/localllm) (Minimal Web-App to run ollama models on it with a GUI)
- [Ollamazing](https://github.com/buiducnhat/ollamazing) (Web extension to run Ollama models)
- [OpenDeepResearcher-via-searxng](https://github.com/benhaotang/OpenDeepResearcher-via-searxng) (A Deep Research equivalent endpoint with Ollama support for running locally)
- [AntSK](https://github.com/AIDotNet/AntSK) (Out-of-the-box & Adaptable RAG Chatbot)
- [MaxKB](https://github.com/1Panel-dev/MaxKB/) (Ready-to-use & flexible RAG Chatbot)
- [yla](https://github.com/danielekp/yla) (Web interface to freely interact with your customized models)
- [LangBot](https://github.com/RockChinQ/LangBot) (LLM-based instant messaging bots platform, with Agents, RAG features, supports multiple platforms)
- [1Panel](https://github.com/1Panel-dev/1Panel/) (Web-based Linux Server Management Tool)
- [AstrBot](https://github.com/Soulter/AstrBot/) (User-friendly LLM-based multi-platform chatbot with a WebUI, supporting RAG, LLM agents, and plugins integration)
- [Reins](https://github.com/ibrahimcetin/reins) (Easily tweak parameters, customize system prompts per chat, and enhance your AI experiments with reasoning model support.)
- [Flufy](https://github.com/Aharon-Bensadoun/Flufy) (A beautiful chat interface for interacting with Ollama's API. Built with React, TypeScript, and Material-UI.)
- [Ellama](https://github.com/zeozeozeo/ellama) (Friendly native app to chat with an Ollama instance)
- [screenpipe](https://github.com/mediar-ai/screenpipe) Build agents powered by your screen history
- [Ollamb](https://github.com/hengkysteen/ollamb) (Simple yet rich in features, cross-platform built with Flutter and designed for Ollama. Try the [web demo](https://hengkysteen.github.io/demo/ollamb/).)
- [Writeopia](https://github.com/Writeopia/Writeopia) (Text editor with integration with Ollama)
- [AppFlowy](https://github.com/AppFlowy-IO/AppFlowy) (AI collaborative workspace with Ollama, cross-platform and self-hostable)
- [Lumina](https://github.com/cushydigit/lumina.git) (A lightweight, minimal React.js frontend for interacting with Ollama servers)
- [Tiny Notepad](https://pypi.org/project/tiny-notepad) (A lightweight, notepad-like interface to chat with ollama available on PyPI)
- [macLlama (macOS native)](https://github.com/hellotunamayo/macLlama) (A native macOS GUI application for interacting with Ollama models, featuring a chat interface.)
- [GPTranslate](https://github.com/philberndt/GPTranslate) (A fast and lightweight, AI powered desktop translation application written with Rust and Tauri. Features real-time translation with OpenAI/Azure/Ollama.)
- [ollama launcher](https://github.com/NGC13009/ollama-launcher) (A launcher for Ollama, aiming to provide users with convenient functions such as ollama server launching, management, or configuration.)
- [ai-hub](https://github.com/Aj-Seven/ai-hub) (AI Hub supports multiple models via API keys and Chat support via Ollama API.)
- [Mayan EDMS](https://gitlab.com/mayan-edms/mayan-edms) (Open source document management system to organize, tag, search, and automate your files with powerful Ollama driven workflows.)
- [Serene Pub](https://github.com/doolijb/serene-pub) (Beginner friendly, open source AI Roleplaying App for Windows, Mac OS and Linux. Search, download and use models with Ollama all inside the app.)
- [Andes](https://github.com/aqerd/andes) (A Visual Studio Code extension that provides a local UI interface for Ollama models)
- [KDeps](https://github.com/kdeps/kdeps) (Kdeps is an offline-first AI framework for building Dockerized full-stack AI applications declaratively using Apple PKL and integrates APIs with Ollama on the backend.)
- [Clueless](https://github.com/KashyapTan/clueless) (Open Source & Local Cluely: A desktop application LLM assistant to help you talk to anything on your screen using locally served Ollama models. Also undetectable to screenshare)
- [ollama-co2](https://github.com/carbonatedWaterOrg/ollama-co2) (FastAPI web interface for monitoring and managing local and remote Ollama servers with real-time model monitoring and concurrent downloads)
- [Hillnote](https://hillnote.com) (A Markdown-first workspace designed to supercharge your AI workflow. Create documents ready to integrate with Claude, ChatGPT, Gemini, Cursor, and more - all while keeping your work on your device.)
### Chat Interfaces
### Cloud
#### Web
- [Open WebUI](https://github.com/open-webui/open-webui) - Extensible, self-hosted AI interface
- [Onyx](https://github.com/onyx-dot-app/onyx) - Connected AI workspace
- [LibreChat](https://github.com/danny-avila/LibreChat) - Enhanced ChatGPT clone with multi-provider support
- [Lobe Chat](https://github.com/lobehub/lobe-chat) - Modern chat framework with plugin ecosystem ([docs](https://lobehub.com/docs/self-hosting/examples/ollama))
- [NextChat](https://github.com/ChatGPTNextWeb/ChatGPT-Next-Web) - Cross-platform ChatGPT UI ([docs](https://docs.nextchat.dev/models/ollama))
- [Perplexica](https://github.com/ItzCrazyKns/Perplexica) - AI-powered search engine, open-source Perplexity alternative
- [big-AGI](https://github.com/enricoros/big-AGI) - AI suite for professionals
- [Lollms WebUI](https://github.com/ParisNeo/lollms-webui) - Multi-model web interface
- [ChatOllama](https://github.com/sugarforever/chat-ollama) - Chatbot with knowledge bases
- [Bionic GPT](https://github.com/bionic-gpt/bionic-gpt) - On-premise AI platform
- [Chatbot UI](https://github.com/ivanfioravanti/chatbot-ollama) - ChatGPT-style web interface
- [Hollama](https://github.com/fmaclen/hollama) - Minimal web interface
- [Chatbox](https://github.com/Bin-Huang/Chatbox) - Desktop and web AI client
- [chat](https://github.com/swuecho/chat) - Chat web app for teams
- [Ollama RAG Chatbot](https://github.com/datvodinh/rag-chatbot.git) - Chat with multiple PDFs using RAG
- [Tkinter-based client](https://github.com/chyok/ollama-gui) - Python desktop client
#### Desktop
- [Dify.AI](https://github.com/langgenius/dify) - LLM app development platform
- [AnythingLLM](https://github.com/Mintplex-Labs/anything-llm) - All-in-one AI app for Mac, Windows, and Linux
- [Maid](https://github.com/Mobile-Artificial-Intelligence/maid) - Cross-platform mobile and desktop client
- [Witsy](https://github.com/nbonamy/witsy) - AI desktop app for Mac, Windows, and Linux
- [Cherry Studio](https://github.com/kangfenmao/cherry-studio) - Multi-provider desktop client
- [Ollama App](https://github.com/JHubi1/ollama-app) - Multi-platform client for desktop and mobile
- [PyGPT](https://github.com/szczyglis-dev/py-gpt) - AI desktop assistant for Linux, Windows, and Mac
- [Alpaca](https://github.com/Jeffser/Alpaca) - GTK4 client for Linux and macOS
- [SwiftChat](https://github.com/aws-samples/swift-chat) - Cross-platform including iOS, Android, and Apple Vision Pro
- [Enchanted](https://github.com/AugustDev/enchanted) - Native macOS and iOS client
- [RWKV-Runner](https://github.com/josStorer/RWKV-Runner) - Multi-model desktop runner
- [Ollama Grid Search](https://github.com/dezoito/ollama-grid-search) - Evaluate and compare models
- [macai](https://github.com/Renset/macai) - macOS client for Ollama and ChatGPT
- [AI Studio](https://github.com/MindWorkAI/AI-Studio) - Multi-provider desktop IDE
- [Reins](https://github.com/ibrahimcetin/reins) - Parameter tuning and reasoning model support
- [ConfiChat](https://github.com/1runeberg/confichat) - Privacy-focused with optional encryption
- [LLocal.in](https://github.com/kartikm7/llocal) - Electron desktop client
- [MindMac](https://mindmac.app) - AI chat client for Mac
- [Msty](https://msty.app) - Multi-model desktop client
- [BoltAI for Mac](https://boltai.com) - AI chat client for Mac
- [IntelliBar](https://intellibar.app/) - AI-powered assistant for macOS
- [Kerlig AI](https://www.kerlig.com/) - AI writing assistant for macOS
- [Hillnote](https://hillnote.com) - Markdown-first AI workspace
- [Perfect Memory AI](https://www.perfectmemory.ai/) - Productivity AI personalized by screen and meeting history
#### Mobile
- [Ollama Android Chat](https://github.com/sunshine0523/OllamaServer) - One-click Ollama on Android
> SwiftChat, Enchanted, Maid, Ollama App, Reins, and ConfiChat listed above also support mobile platforms.
### Code Editors & Development
- [Cline](https://github.com/cline/cline) - VS Code extension for multi-file/whole-repo coding
- [Continue](https://github.com/continuedev/continue) - Open-source AI code assistant for any IDE
- [Void](https://github.com/voideditor/void) - Open source AI code editor, Cursor alternative
- [Copilot for Obsidian](https://github.com/logancyang/obsidian-copilot) - AI assistant for Obsidian
- [twinny](https://github.com/rjmacarthy/twinny) - Copilot and Copilot chat alternative
- [gptel Emacs client](https://github.com/karthink/gptel) - LLM client for Emacs
- [Ollama Copilot](https://github.com/bernardo-bruning/ollama-copilot) - Use Ollama as GitHub Copilot
- [Obsidian Local GPT](https://github.com/pfrankov/obsidian-local-gpt) - Local AI for Obsidian
- [Ellama Emacs client](https://github.com/s-kostyaev/ellama) - LLM tool for Emacs
- [orbiton](https://github.com/xyproto/orbiton) - Config-free text editor with Ollama tab completion
- [AI ST Completion](https://github.com/yaroslavyaroslav/OpenAI-sublime-text) - Sublime Text 4 AI assistant
- [VT Code](https://github.com/vinhnx/vtcode) - Rust-based terminal coding agent with Tree-sitter
- [QodeAssist](https://github.com/Palm1r/QodeAssist) - AI coding assistant for Qt Creator
- [AI Toolkit for VS Code](https://aka.ms/ai-tooklit/ollama-docs) - Microsoft-official VS Code extension
- [Open Interpreter](https://docs.openinterpreter.com/language-model-setup/local-models/ollama) - Natural language interface for computers
### Libraries & SDKs
- [LiteLLM](https://github.com/BerriAI/litellm) - Unified API for 100+ LLM providers
- [Semantic Kernel](https://github.com/microsoft/semantic-kernel/tree/main/python/semantic_kernel/connectors/ai/ollama) - Microsoft AI orchestration SDK
- [LangChain4j](https://github.com/langchain4j/langchain4j) - Java LangChain ([example](https://github.com/langchain4j/langchain4j-examples/tree/main/ollama-examples/src/main/java))
- [LangChainGo](https://github.com/tmc/langchaingo/) - Go LangChain ([example](https://github.com/tmc/langchaingo/tree/main/examples/ollama-completion-example))
- [Spring AI](https://github.com/spring-projects/spring-ai) - Spring framework AI support ([docs](https://docs.spring.io/spring-ai/reference/api/chat/ollama-chat.html))
- [LangChain](https://python.langchain.com/docs/integrations/chat/ollama/) and [LangChain.js](https://js.langchain.com/docs/integrations/chat/ollama/) with [example](https://js.langchain.com/docs/tutorials/local_rag/)
- [Ollama for Ruby](https://github.com/crmne/ruby_llm) - Ruby LLM library
- [any-llm](https://github.com/mozilla-ai/any-llm) - Unified LLM interface by Mozilla
- [OllamaSharp for .NET](https://github.com/awaescher/OllamaSharp) - .NET SDK
- [LangChainRust](https://github.com/Abraxas-365/langchain-rust) - Rust LangChain ([example](https://github.com/Abraxas-365/langchain-rust/blob/main/examples/llm_ollama.rs))
- [Agents-Flex for Java](https://github.com/agents-flex/agents-flex) - Java agent framework ([example](https://github.com/agents-flex/agents-flex/tree/main/agents-flex-llm/agents-flex-llm-ollama/src/test/java/com/agentsflex/llm/ollama))
- [Elixir LangChain](https://github.com/brainlid/langchain) - Elixir LangChain
- [Ollama-rs for Rust](https://github.com/pepperoni21/ollama-rs) - Rust SDK
- [LangChain for .NET](https://github.com/tryAGI/LangChain) - .NET LangChain ([example](https://github.com/tryAGI/LangChain/blob/main/examples/LangChain.Samples.OpenAI/Program.cs))
- [chromem-go](https://github.com/philippgille/chromem-go) - Go vector database with Ollama embeddings ([example](https://github.com/philippgille/chromem-go/tree/v0.5.0/examples/rag-wikipedia-ollama))
- [LangChainDart](https://github.com/davidmigloz/langchain_dart) - Dart LangChain
- [LlmTornado](https://github.com/lofcz/llmtornado) - Unified C# interface for multiple inference APIs
- [Ollama4j for Java](https://github.com/ollama4j/ollama4j) - Java SDK
- [Ollama for Laravel](https://github.com/cloudstudio/ollama-laravel) - Laravel integration
- [Ollama for Swift](https://github.com/mattt/ollama-swift) - Swift SDK
- [LlamaIndex](https://docs.llamaindex.ai/en/stable/examples/llm/ollama/) and [LlamaIndexTS](https://ts.llamaindex.ai/modules/llms/available_llms/ollama) - Data framework for LLM apps
- [Haystack](https://github.com/deepset-ai/haystack-integrations/blob/main/integrations/ollama.md) - AI pipeline framework
- [Firebase Genkit](https://firebase.google.com/docs/genkit/plugins/ollama) - Google AI framework
- [Ollama-hpp for C++](https://github.com/jmont-dev/ollama-hpp) - C++ SDK
- [PromptingTools.jl](https://github.com/svilupp/PromptingTools.jl) - Julia LLM toolkit ([example](https://svilupp.github.io/PromptingTools.jl/dev/examples/working_with_ollama))
- [Ollama for R - rollama](https://github.com/JBGruber/rollama) - R SDK
- [Portkey](https://portkey.ai/docs/welcome/integration-guides/ollama) - AI gateway
- [Testcontainers](https://testcontainers.com/modules/ollama/) - Container-based testing
- [LLPhant](https://github.com/theodo-group/LLPhant?tab=readme-ov-file#ollama) - PHP AI framework
### Frameworks & Agents
- [AutoGPT](https://github.com/Significant-Gravitas/AutoGPT/blob/master/docs/content/platform/ollama.md) - Autonomous AI agent platform
- [crewAI](https://github.com/crewAIInc/crewAI) - Multi-agent orchestration framework
- [Strands Agents](https://github.com/strands-agents/sdk-python) - Model-driven agent building by AWS
- [Cheshire Cat](https://github.com/cheshire-cat-ai/core) - AI assistant framework
- [any-agent](https://github.com/mozilla-ai/any-agent) - Unified agent framework interface by Mozilla
- [Stakpak](https://github.com/stakpak/agent) - Open source DevOps agent
- [Hexabot](https://github.com/hexastack/hexabot) - Conversational AI builder
- [Neuro SAN](https://github.com/cognizant-ai-lab/neuro-san-studio) - Multi-agent orchestration ([docs](https://github.com/cognizant-ai-lab/neuro-san-studio/blob/main/docs/user_guide.md#ollama))
### RAG & Knowledge Bases
- [RAGFlow](https://github.com/infiniflow/ragflow) - RAG engine based on deep document understanding
- [R2R](https://github.com/SciPhi-AI/R2R) - Open-source RAG engine
- [MaxKB](https://github.com/1Panel-dev/MaxKB/) - Ready-to-use RAG chatbot
- [Minima](https://github.com/dmayboroda/minima) - On-premises or fully local RAG
- [Chipper](https://github.com/TilmanGriesel/chipper) - AI interface with Haystack RAG
- [ARGO](https://github.com/xark-argo/argo) - RAG and deep research on Mac/Windows/Linux
- [Archyve](https://github.com/nickthecook/archyve) - RAG-enabling document library
- [Casibase](https://casibase.org) - AI knowledge base with RAG and SSO
- [BrainSoup](https://www.nurgo-software.com/products/brainsoup) - Native client with RAG and multi-agent automation
### Bots & Messaging
- [LangBot](https://github.com/RockChinQ/LangBot) - Multi-platform messaging bots with agents and RAG
- [AstrBot](https://github.com/Soulter/AstrBot/) - Multi-platform chatbot with RAG and plugins
- [Discord-Ollama Chat Bot](https://github.com/kevinthedang/discord-ollama) - TypeScript Discord bot
- [Ollama Telegram Bot](https://github.com/ruecat/ollama-telegram) - Telegram bot
- [LLM Telegram Bot](https://github.com/innightwolfsleep/llm_telegram_bot) - Telegram bot for roleplay
### Terminal & CLI
- [aichat](https://github.com/sigoden/aichat) - All-in-one LLM CLI with Shell Assistant, RAG, and AI tools
- [oterm](https://github.com/ggozad/oterm) - Terminal client for Ollama
- [gollama](https://github.com/sammcj/gollama) - Go-based model manager for Ollama
- [tlm](https://github.com/yusufcanb/tlm) - Local shell copilot
- [tenere](https://github.com/pythops/tenere) - TUI for LLMs
- [ParLlama](https://github.com/paulrobello/parllama) - TUI for Ollama
- [llm-ollama](https://github.com/taketwo/llm-ollama) - Plugin for [Datasette's LLM CLI](https://llm.datasette.io/en/stable/)
- [ShellOracle](https://github.com/djcopley/ShellOracle) - Shell command suggestions
- [LLM-X](https://github.com/mrdjohnson/llm-x) - Progressive web app for LLMs
- [cmdh](https://github.com/pgibler/cmdh) - Natural language to shell commands
- [VT](https://github.com/vinhnx/vt.ai) - Minimal multimodal AI chat app
### Productivity & Apps
- [AppFlowy](https://github.com/AppFlowy-IO/AppFlowy) - AI collaborative workspace, self-hostable Notion alternative
- [Screenpipe](https://github.com/mediar-ai/screenpipe) - 24/7 screen and mic recording with AI-powered search
- [Vibe](https://github.com/thewh1teagle/vibe) - Transcribe and analyze meetings
- [Page Assist](https://github.com/n4ze3m/page-assist) - Chrome extension for AI-powered browsing
- [NativeMind](https://github.com/NativeMindBrowser/NativeMindExtension) - Private, on-device browser AI assistant
- [Ollama Fortress](https://github.com/ParisNeo/ollama_proxy_server) - Security proxy for Ollama
- [1Panel](https://github.com/1Panel-dev/1Panel/) - Web-based Linux server management
- [Writeopia](https://github.com/Writeopia/Writeopia) - Text editor with Ollama integration
- [QA-Pilot](https://github.com/reid41/QA-Pilot) - GitHub code repository understanding
- [Raycast extension](https://github.com/MassimilianoPasquini97/raycast_ollama) - Ollama in Raycast
- [Painting Droid](https://github.com/mateuszmigas/painting-droid) - Painting app with AI integrations
- [Serene Pub](https://github.com/doolijb/serene-pub) - AI roleplaying app
- [Mayan EDMS](https://gitlab.com/mayan-edms/mayan-edms) - Document management with Ollama workflows
- [TagSpaces](https://www.tagspaces.org) - File management with [AI tagging](https://docs.tagspaces.org/ai/)
### Observability & Monitoring
- [Opik](https://www.comet.com/docs/opik/cookbook/ollama) - Debug, evaluate, and monitor LLM applications
- [OpenLIT](https://github.com/openlit/openlit) - OpenTelemetry-native monitoring for Ollama and GPUs
- [Lunary](https://lunary.ai/docs/integrations/ollama) - LLM observability with analytics and PII masking
- [Langfuse](https://langfuse.com/docs/integrations/ollama) - Open source LLM observability
- [HoneyHive](https://docs.honeyhive.ai/integrations/ollama) - AI observability and evaluation for agents
- [MLflow Tracing](https://mlflow.org/docs/latest/llms/tracing/index.html#automatic-tracing) - Open source LLM observability
### Database & Embeddings
- [pgai](https://github.com/timescale/pgai) - PostgreSQL as a vector database ([guide](https://github.com/timescale/pgai/blob/main/docs/vectorizer-quick-start.md))
- [MindsDB](https://github.com/mindsdb/mindsdb/blob/staging/mindsdb/integrations/handlers/ollama_handler/README.md) - Connect Ollama with 200+ data platforms
- [chromem-go](https://github.com/philippgille/chromem-go/blob/v0.5.0/embed_ollama.go) - Embeddable vector database for Go ([example](https://github.com/philippgille/chromem-go/tree/v0.5.0/examples/rag-wikipedia-ollama))
- [Kangaroo](https://github.com/dbkangaroo/kangaroo) - AI-powered SQL client
### Infrastructure & Deployment
#### Cloud
- [Google Cloud](https://cloud.google.com/run/docs/tutorials/gpu-gemma2-with-ollama)
- [Fly.io](https://fly.io/docs/python/do-more/add-ollama/)
- [Koyeb](https://www.koyeb.com/deploy/ollama)
- [Harbor](https://github.com/av/harbor) - Containerized LLM toolkit with Ollama as default backend
### Tutorial
- [handy-ollama](https://github.com/datawhalechina/handy-ollama) (Chinese Tutorial for Ollama by [Datawhale ](https://github.com/datawhalechina) - China's Largest Open Source AI Learning Community)
### Terminal
- [oterm](https://github.com/ggozad/oterm)
- [Ellama Emacs client](https://github.com/s-kostyaev/ellama)
- [Emacs client](https://github.com/zweifisch/ollama)
- [neollama](https://github.com/paradoxical-dev/neollama) UI client for interacting with models from within Neovim
- [gen.nvim](https://github.com/David-Kunz/gen.nvim)
- [ollama.nvim](https://github.com/nomnivore/ollama.nvim)
- [ollero.nvim](https://github.com/marco-souza/ollero.nvim)
- [ollama-chat.nvim](https://github.com/gerazov/ollama-chat.nvim)
- [ogpt.nvim](https://github.com/huynle/ogpt.nvim)
- [gptel Emacs client](https://github.com/karthink/gptel)
- [Oatmeal](https://github.com/dustinblackman/oatmeal)
- [cmdh](https://github.com/pgibler/cmdh)
- [ooo](https://github.com/npahlfer/ooo)
- [shell-pilot](https://github.com/reid41/shell-pilot)(Interact with models via pure shell scripts on Linux or macOS)
- [tenere](https://github.com/pythops/tenere)
- [llm-ollama](https://github.com/taketwo/llm-ollama) for [Datasette's LLM CLI](https://llm.datasette.io/en/stable/).
- [typechat-cli](https://github.com/anaisbetts/typechat-cli)
- [ShellOracle](https://github.com/djcopley/ShellOracle)
- [tlm](https://github.com/yusufcanb/tlm)
- [podman-ollama](https://github.com/ericcurtin/podman-ollama)
- [gollama](https://github.com/sammcj/gollama)
- [ParLlama](https://github.com/paulrobello/parllama)
- [Ollama eBook Summary](https://github.com/cognitivetech/ollama-ebook-summary/)
- [Ollama Mixture of Experts (MOE) in 50 lines of code](https://github.com/rapidarchitect/ollama_moe)
- [vim-intelligence-bridge](https://github.com/pepo-ec/vim-intelligence-bridge) Simple interaction of "Ollama" with the Vim editor
- [x-cmd ollama](https://x-cmd.com/mod/ollama)
- [bb7](https://github.com/drunkwcodes/bb7)
- [SwollamaCLI](https://github.com/marcusziade/Swollama) bundled with the Swollama Swift package. [Demo](https://github.com/marcusziade/Swollama?tab=readme-ov-file#cli-usage)
- [aichat](https://github.com/sigoden/aichat) All-in-one LLM CLI tool featuring Shell Assistant, Chat-REPL, RAG, AI tools & agents, with access to OpenAI, Claude, Gemini, Ollama, Groq, and more.
- [PowershAI](https://github.com/rrg92/powershai) PowerShell module that brings AI to terminal on Windows, including support for Ollama
- [DeepShell](https://github.com/Abyss-c0re/deepshell) Your self-hosted AI assistant. Interactive Shell, Files and Folders analysis.
- [orbiton](https://github.com/xyproto/orbiton) Configuration-free text editor and IDE with support for tab completion with Ollama.
- [orca-cli](https://github.com/molbal/orca-cli) Ollama Registry CLI Application - Browse, pull, and download models from Ollama Registry in your terminal.
- [GGUF-to-Ollama](https://github.com/jonathanhecl/gguf-to-ollama) - Importing GGUF to Ollama made easy (multiplatform)
- [AWS-Strands-With-Ollama](https://github.com/rapidarchitect/ollama_strands) - AWS Strands Agents with Ollama Examples
- [ollama-multirun](https://github.com/attogram/ollama-multirun) - A bash shell script to run a single prompt against any or all of your locally installed ollama models, saving the output and performance statistics as easily navigable web pages. ([Demo](https://attogram.github.io/ai_test_zone/))
- [ollama-bash-toolshed](https://github.com/attogram/ollama-bash-toolshed) - Bash scripts to chat with tool using models. Add new tools to your shed with ease. Runs on Ollama.
- [hle-eval-ollama](https://github.com/mags0ft/hle-eval-ollama) - Runs benchmarks like "Humanity's Last Exam" (HLE) on your favorite local Ollama models and evaluates the quality of their responses
- [VT Code](https://github.com/vinhnx/vtcode) - VT Code is a Rust-based terminal coding agent with semantic code intelligence via Tree-sitter. Ollama integration for running local/cloud models with configurable endpoints.
### Apple Vision Pro
- [SwiftChat](https://github.com/aws-samples/swift-chat) (Cross-platform AI chat app supporting Apple Vision Pro via "Designed for iPad")
- [Enchanted](https://github.com/AugustDev/enchanted)
### Database
- [pgai](https://github.com/timescale/pgai) - PostgreSQL as a vector database (Create and search embeddings from Ollama models using pgvector)
- [Get started guide](https://github.com/timescale/pgai/blob/main/docs/vectorizer-quick-start.md)
- [MindsDB](https://github.com/mindsdb/mindsdb/blob/staging/mindsdb/integrations/handlers/ollama_handler/README.md) (Connects Ollama models with nearly 200 data platforms and apps)
- [chromem-go](https://github.com/philippgille/chromem-go/blob/v0.5.0/embed_ollama.go) with [example](https://github.com/philippgille/chromem-go/tree/v0.5.0/examples/rag-wikipedia-ollama)
- [Kangaroo](https://github.com/dbkangaroo/kangaroo) (AI-powered SQL client and admin tool for popular databases)
### Package managers
#### Package Managers
- [Pacman](https://archlinux.org/packages/extra/x86_64/ollama/)
- [Gentoo](https://github.com/gentoo/guru/tree/master/app-misc/ollama)
- [Homebrew](https://formulae.brew.sh/formula/ollama)
- [Helm Chart](https://artifacthub.io/packages/helm/ollama-helm/ollama)
- [Guix channel](https://codeberg.org/tusharhero/ollama-guix)
- [Nix package](https://search.nixos.org/packages?show=ollama&from=0&size=50&sort=relevance&type=packages&query=ollama)
- [Helm Chart](https://artifacthub.io/packages/helm/ollama-helm/ollama)
- [Gentoo](https://github.com/gentoo/guru/tree/master/app-misc/ollama)
- [Flox](https://flox.dev/blog/ollama-part-one)
### Libraries
- [LangChain](https://python.langchain.com/docs/integrations/chat/ollama/) and [LangChain.js](https://js.langchain.com/docs/integrations/chat/ollama/) with [example](https://js.langchain.com/docs/tutorials/local_rag/)
- [Firebase Genkit](https://firebase.google.com/docs/genkit/plugins/ollama)
- [crewAI](https://github.com/crewAIInc/crewAI)
- [Yacana](https://remembersoftwares.github.io/yacana/) (User-friendly multi-agent framework for brainstorming and executing predetermined flows with built-in tool integration)
- [Strands Agents](https://github.com/strands-agents/sdk-python) (A model-driven approach to building AI agents in just a few lines of code)
- [Spring AI](https://github.com/spring-projects/spring-ai) with [reference](https://docs.spring.io/spring-ai/reference/api/chat/ollama-chat.html) and [example](https://github.com/tzolov/ollama-tools)
- [LangChainGo](https://github.com/tmc/langchaingo/) with [example](https://github.com/tmc/langchaingo/tree/main/examples/ollama-completion-example)
- [LangChain4j](https://github.com/langchain4j/langchain4j) with [example](https://github.com/langchain4j/langchain4j-examples/tree/main/ollama-examples/src/main/java)
- [LangChainRust](https://github.com/Abraxas-365/langchain-rust) with [example](https://github.com/Abraxas-365/langchain-rust/blob/main/examples/llm_ollama.rs)
- [LangChain for .NET](https://github.com/tryAGI/LangChain) with [example](https://github.com/tryAGI/LangChain/blob/main/examples/LangChain.Samples.OpenAI/Program.cs)
- [LLPhant](https://github.com/theodo-group/LLPhant?tab=readme-ov-file#ollama)
- [LlamaIndex](https://docs.llamaindex.ai/en/stable/examples/llm/ollama/) and [LlamaIndexTS](https://ts.llamaindex.ai/modules/llms/available_llms/ollama)
- [LiteLLM](https://github.com/BerriAI/litellm)
- [OllamaFarm for Go](https://github.com/presbrey/ollamafarm)
- [OllamaSharp for .NET](https://github.com/awaescher/OllamaSharp)
- [Ollama for Ruby](https://github.com/gbaptista/ollama-ai)
- [Ollama-rs for Rust](https://github.com/pepperoni21/ollama-rs)
- [Ollama-hpp for C++](https://github.com/jmont-dev/ollama-hpp)
- [Ollama4j for Java](https://github.com/ollama4j/ollama4j)
- [ModelFusion Typescript Library](https://modelfusion.dev/integration/model-provider/ollama)
- [OllamaKit for Swift](https://github.com/kevinhermawan/OllamaKit)
- [Ollama for Dart](https://github.com/breitburg/dart-ollama)
- [Ollama for Laravel](https://github.com/cloudstudio/ollama-laravel)
- [LangChainDart](https://github.com/davidmigloz/langchain_dart)
- [Semantic Kernel - Python](https://github.com/microsoft/semantic-kernel/tree/main/python/semantic_kernel/connectors/ai/ollama)
- [Haystack](https://github.com/deepset-ai/haystack-integrations/blob/main/integrations/ollama.md)
- [Elixir LangChain](https://github.com/brainlid/langchain)
- [Ollama for R - rollama](https://github.com/JBGruber/rollama)
- [Ollama for R - ollama-r](https://github.com/hauselin/ollama-r)
- [Ollama-ex for Elixir](https://github.com/lebrunel/ollama-ex)
- [Ollama Connector for SAP ABAP](https://github.com/b-tocs/abap_btocs_ollama)
- [Testcontainers](https://testcontainers.com/modules/ollama/)
- [Portkey](https://portkey.ai/docs/welcome/integration-guides/ollama)
- [PromptingTools.jl](https://github.com/svilupp/PromptingTools.jl) with an [example](https://svilupp.github.io/PromptingTools.jl/dev/examples/working_with_ollama)
- [LlamaScript](https://github.com/Project-Llama/llamascript)
- [llm-axe](https://github.com/emirsahin1/llm-axe) (Python Toolkit for Building LLM Powered Apps)
- [Gollm](https://docs.gollm.co/examples/ollama-example)
- [Gollama for Golang](https://github.com/jonathanhecl/gollama)
- [Ollamaclient for Golang](https://github.com/xyproto/ollamaclient)
- [High-level function abstraction in Go](https://gitlab.com/tozd/go/fun)
- [Ollama PHP](https://github.com/ArdaGnsrn/ollama-php)
- [Agents-Flex for Java](https://github.com/agents-flex/agents-flex) with [example](https://github.com/agents-flex/agents-flex/tree/main/agents-flex-llm/agents-flex-llm-ollama/src/test/java/com/agentsflex/llm/ollama)
- [Parakeet](https://github.com/parakeet-nest/parakeet) is a GoLang library, made to simplify the development of small generative AI applications with Ollama.
- [Haverscript](https://github.com/andygill/haverscript) with [examples](https://github.com/andygill/haverscript/tree/main/examples)
- [Ollama for Swift](https://github.com/mattt/ollama-swift)
- [Swollama for Swift](https://github.com/guitaripod/Swollama) with [DocC](https://guitaripod.github.io/Swollama/documentation/swollama)
- [GoLamify](https://github.com/prasad89/golamify)
- [Ollama for Haskell](https://github.com/tusharad/ollama-haskell)
- [multi-llm-ts](https://github.com/nbonamy/multi-llm-ts) (A Typescript/JavaScript library allowing access to different LLM in a unified API)
- [LlmTornado](https://github.com/lofcz/llmtornado) (C# library providing a unified interface for major FOSS & Commercial inference APIs)
- [Ollama for Zig](https://github.com/dravenk/ollama-zig)
- [Abso](https://github.com/lunary-ai/abso) (OpenAI-compatible TypeScript SDK for any LLM provider)
- [Nichey](https://github.com/goodreasonai/nichey) is a Python package for generating custom wikis for your research topic
- [Ollama for D](https://github.com/kassane/ollama-d)
- [OllamaPlusPlus](https://github.com/HardCodeDev777/OllamaPlusPlus) (Very simple C++ library for Ollama)
- [any-llm](https://github.com/mozilla-ai/any-llm) (A single interface to use different llm providers by [mozilla.ai](https://www.mozilla.ai/))
- [any-agent](https://github.com/mozilla-ai/any-agent) (A single interface to use and evaluate different agent frameworks by [mozilla.ai](https://www.mozilla.ai/))
- [Neuro SAN](https://github.com/cognizant-ai-lab/neuro-san-studio) (Data-driven multi-agent orchestration framework) with [example](https://github.com/cognizant-ai-lab/neuro-san-studio/blob/main/docs/user_guide.md#ollama)
- [achatbot-go](https://github.com/ai-bot-pro/achatbot-go) a multimodal(text/audio/image) chatbot.
- [Ollama Bash Lib](https://github.com/attogram/ollama-bash-lib) - A Bash Library for Ollama. Run LLM prompts straight from your shell, and more
### Mobile
- [SwiftChat](https://github.com/aws-samples/swift-chat) (Lightning-fast Cross-platform AI chat app with native UI for Android, iOS, and iPad)
- [Enchanted](https://github.com/AugustDev/enchanted)
- [Maid](https://github.com/Mobile-Artificial-Intelligence/maid)
- [Ollama App](https://github.com/JHubi1/ollama-app) (Modern and easy-to-use multi-platform client for Ollama)
- [ConfiChat](https://github.com/1runeberg/confichat) (Lightweight, standalone, multi-platform, and privacy-focused LLM chat interface with optional encryption)
- [Ollama Android Chat](https://github.com/sunshine0523/OllamaServer) (No need for Termux, start the Ollama service with one click on an Android device)
- [Reins](https://github.com/ibrahimcetin/reins) (Easily tweak parameters, customize system prompts per chat, and enhance your AI experiments with reasoning model support.)
### Extensions & Plugins
- [Raycast extension](https://github.com/MassimilianoPasquini97/raycast_ollama)
- [Discollama](https://github.com/mxyng/discollama) (Discord bot inside the Ollama discord channel)
- [Continue](https://github.com/continuedev/continue)
- [Vibe](https://github.com/thewh1teagle/vibe) (Transcribe and analyze meetings with Ollama)
- [Obsidian Ollama plugin](https://github.com/hinterdupfinger/obsidian-ollama)
- [Logseq Ollama plugin](https://github.com/omagdy7/ollama-logseq)
- [NotesOllama](https://github.com/andersrex/notesollama) (Apple Notes Ollama plugin)
- [Dagger Chatbot](https://github.com/samalba/dagger-chatbot)
- [Discord AI Bot](https://github.com/mekb-turtle/discord-ai-bot)
- [Ollama Telegram Bot](https://github.com/ruecat/ollama-telegram)
- [Hass Ollama Conversation](https://github.com/ej52/hass-ollama-conversation)
- [Rivet plugin](https://github.com/abrenneke/rivet-plugin-ollama)
- [Obsidian BMO Chatbot plugin](https://github.com/longy2k/obsidian-bmo-chatbot)
- [Cliobot](https://github.com/herval/cliobot) (Telegram bot with Ollama support)
- [Copilot for Obsidian plugin](https://github.com/logancyang/obsidian-copilot)
- [Obsidian Local GPT plugin](https://github.com/pfrankov/obsidian-local-gpt)
- [Open Interpreter](https://docs.openinterpreter.com/language-model-setup/local-models/ollama)
- [Llama Coder](https://github.com/ex3ndr/llama-coder) (Copilot alternative using Ollama)
- [Ollama Copilot](https://github.com/bernardo-bruning/ollama-copilot) (Proxy that allows you to use Ollama as a copilot like GitHub Copilot)
- [twinny](https://github.com/rjmacarthy/twinny) (Copilot and Copilot chat alternative using Ollama)
- [Wingman-AI](https://github.com/RussellCanfield/wingman-ai) (Copilot code and chat alternative using Ollama and Hugging Face)
- [Page Assist](https://github.com/n4ze3m/page-assist) (Chrome Extension)
- [Plasmoid Ollama Control](https://github.com/imoize/plasmoid-ollamacontrol) (KDE Plasma extension that allows you to quickly manage/control Ollama model)
- [AI Telegram Bot](https://github.com/tusharhero/aitelegrambot) (Telegram bot using Ollama in backend)
- [AI ST Completion](https://github.com/yaroslavyaroslav/OpenAI-sublime-text) (Sublime Text 4 AI assistant plugin with Ollama support)
- [Discord-Ollama Chat Bot](https://github.com/kevinthedang/discord-ollama) (Generalized TypeScript Discord Bot w/ Tuning Documentation)
- [ChatGPTBox: All in one browser extension](https://github.com/josStorer/chatGPTBox) with [Integrating Tutorial](https://github.com/josStorer/chatGPTBox/issues/616#issuecomment-1975186467)
- [Discord AI chat/moderation bot](https://github.com/rapmd73/Companion) Chat/moderation bot written in python. Uses Ollama to create personalities.
- [Headless Ollama](https://github.com/nischalj10/headless-ollama) (Scripts to automatically install ollama client & models on any OS for apps that depend on ollama server)
- [Terraform AWS Ollama & Open WebUI](https://github.com/xuyangbocn/terraform-aws-self-host-llm) (A Terraform module to deploy on AWS a ready-to-use Ollama service, together with its front-end Open WebUI service.)
- [node-red-contrib-ollama](https://github.com/jakubburkiewicz/node-red-contrib-ollama)
- [Local AI Helper](https://github.com/ivostoykov/localAI) (Chrome and Firefox extensions that enable interactions with the active tab and customisable API endpoints. Includes secure storage for user prompts.)
- [LSP-AI](https://github.com/SilasMarvin/lsp-ai) (Open-source language server for AI-powered functionality)
- [QodeAssist](https://github.com/Palm1r/QodeAssist) (AI-powered coding assistant plugin for Qt Creator)
- [Obsidian Quiz Generator plugin](https://github.com/ECuiDev/obsidian-quiz-generator)
- [AI Summary Helper plugin](https://github.com/philffm/ai-summary-helper)
- [TextCraft](https://github.com/suncloudsmoon/TextCraft) (Copilot in Word alternative using Ollama)
- [Alfred Ollama](https://github.com/zeitlings/alfred-ollama) (Alfred Workflow)
- [TextLLaMA](https://github.com/adarshM84/TextLLaMA) A Chrome Extension that helps you write emails, correct grammar, and translate into any language
- [Simple-Discord-AI](https://github.com/zyphixor/simple-discord-ai)
- [LLM Telegram Bot](https://github.com/innightwolfsleep/llm_telegram_bot) (telegram bot, primary for RP. Oobabooga-like buttons, [A1111](https://github.com/AUTOMATIC1111/stable-diffusion-webui) API integration e.t.c)
- [mcp-llm](https://github.com/sammcj/mcp-llm) (MCP Server to allow LLMs to call other LLMs)
- [SimpleOllamaUnity](https://github.com/HardCodeDev777/SimpleOllamaUnity) (Unity Engine extension for communicating with Ollama in a few lines of code. Also works at runtime)
- [UnityCodeLama](https://github.com/HardCodeDev777/UnityCodeLama) (Unity Editor tool to analyze scripts via Ollama)
- [NativeMind](https://github.com/NativeMindBrowser/NativeMindExtension) (Private, on-device AI Assistant, no cloud dependencies)
- [GMAI - Gradle Managed AI](https://gmai.premex.se/) (Gradle plugin for automated Ollama lifecycle management during build phases)
- [NOMYO Router](https://github.com/nomyo-ai/nomyo-router) (A transparent Ollama proxy with model deployment aware routing which auto-manages multiple Ollama instances in a given network)
### Supported backends
- [llama.cpp](https://github.com/ggml-org/llama.cpp) project founded by Georgi Gerganov.
### Observability
- [Opik](https://www.comet.com/docs/opik/cookbook/ollama) is an open-source platform to debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards. Opik supports native integration to Ollama.
- [Lunary](https://lunary.ai/docs/integrations/ollama) is the leading open-source LLM observability platform. It provides a variety of enterprise-grade features such as real-time analytics, prompt templates management, PII masking, and comprehensive agent tracing.
- [OpenLIT](https://github.com/openlit/openlit) is an OpenTelemetry-native tool for monitoring Ollama Applications & GPUs using traces and metrics.
- [HoneyHive](https://docs.honeyhive.ai/integrations/ollama) is an AI observability and evaluation platform for AI agents. Use HoneyHive to evaluate agent performance, interrogate failures, and monitor quality in production.
- [Langfuse](https://langfuse.com/docs/integrations/ollama) is an open source LLM observability platform that enables teams to collaboratively monitor, evaluate and debug AI applications.
- [MLflow Tracing](https://mlflow.org/docs/latest/llms/tracing/index.html#automatic-tracing) is an open source LLM observability tool with a convenient API to log and visualize traces, making it easy to debug and evaluate GenAI applications.
### Security
- [Ollama Fortress](https://github.com/ParisNeo/ollama_proxy_server)
- [Guix channel](https://codeberg.org/tusharhero/ollama-guix)
Regular → Executable
+641 -152
View File
@@ -1,17 +1,25 @@
package anthropic
import (
"bytes"
"context"
"crypto/rand"
"encoding/base64"
"encoding/json"
"errors"
"fmt"
"io"
"log/slog"
"net/http"
"net/url"
"strconv"
"strings"
"time"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/auth"
internalcloud "github.com/ollama/ollama/internal/cloud"
"github.com/ollama/ollama/logutil"
)
// Error types matching Anthropic API
@@ -60,7 +68,7 @@ type MessagesRequest struct {
Model string `json:"model"`
MaxTokens int `json:"max_tokens"`
Messages []MessageParam `json:"messages"`
System any `json:"system,omitempty"` // string or []ContentBlock
System any `json:"system,omitempty"` // string or []map[string]any (JSON-decoded ContentBlock)
Stream bool `json:"stream,omitempty"`
Temperature *float64 `json:"temperature,omitempty"`
TopP *float64 `json:"top_p,omitempty"`
@@ -70,34 +78,61 @@ type MessagesRequest struct {
ToolChoice *ToolChoice `json:"tool_choice,omitempty"`
Thinking *ThinkingConfig `json:"thinking,omitempty"`
Metadata *Metadata `json:"metadata,omitempty"`
OutputConfig *OutputConfig `json:"output_config,omitempty"`
}
type OutputConfig struct {
Effort string `json:"effort,omitempty"`
}
// MessageParam represents a message in the request
type MessageParam struct {
Role string `json:"role"` // "user" or "assistant"
Content any `json:"content"` // string or []ContentBlock
Role string `json:"role"` // "user" or "assistant"
Content []ContentBlock `json:"content"` // always []ContentBlock; plain strings are normalized on unmarshal
}
func (m *MessageParam) UnmarshalJSON(data []byte) error {
var raw struct {
Role string `json:"role"`
Content json.RawMessage `json:"content"`
}
if err := json.Unmarshal(data, &raw); err != nil {
return err
}
m.Role = raw.Role
var s string
if err := json.Unmarshal(raw.Content, &s); err == nil {
m.Content = []ContentBlock{{Type: "text", Text: &s}}
return nil
}
return json.Unmarshal(raw.Content, &m.Content)
}
// ContentBlock represents a content block in a message.
// Text and Thinking use pointers so they serialize as the field being present (even if empty)
// only when set, which is required for SDK streaming accumulation.
type ContentBlock struct {
Type string `json:"type"` // text, image, tool_use, tool_result, thinking
Type string `json:"type"` // text, image, tool_use, tool_result, thinking, server_tool_use, web_search_tool_result
// For text blocks - pointer so field only appears when set (SDK requires it for accumulation)
Text *string `json:"text,omitempty"`
// For text blocks with citations
Citations []Citation `json:"citations,omitempty"`
// For image blocks
Source *ImageSource `json:"source,omitempty"`
// For tool_use blocks
ID string `json:"id,omitempty"`
Name string `json:"name,omitempty"`
Input any `json:"input,omitempty"`
// For tool_use and server_tool_use blocks
ID string `json:"id,omitempty"`
Name string `json:"name,omitempty"`
Input api.ToolCallFunctionArguments `json:"input,omitzero"`
// For tool_result blocks
// For tool_result and web_search_tool_result blocks
ToolUseID string `json:"tool_use_id,omitempty"`
Content any `json:"content,omitempty"` // string or []ContentBlock
Content any `json:"content,omitempty"` // string, []ContentBlock, []WebSearchResult, or WebSearchToolResultError
IsError bool `json:"is_error,omitempty"`
// For thinking blocks - pointer so field only appears when set (SDK requires it for accumulation)
@@ -105,9 +140,33 @@ type ContentBlock struct {
Signature string `json:"signature,omitempty"`
}
// Citation represents a citation in a text block
type Citation struct {
Type string `json:"type"` // "web_search_result_location"
URL string `json:"url"`
Title string `json:"title"`
EncryptedIndex string `json:"encrypted_index,omitempty"`
CitedText string `json:"cited_text,omitempty"`
}
// WebSearchResult represents a single web search result
type WebSearchResult struct {
Type string `json:"type"` // "web_search_result"
URL string `json:"url"`
Title string `json:"title"`
EncryptedContent string `json:"encrypted_content,omitempty"`
PageAge string `json:"page_age,omitempty"`
}
// WebSearchToolResultError represents an error from web search
type WebSearchToolResultError struct {
Type string `json:"type"` // "web_search_tool_result_error"
ErrorCode string `json:"error_code"`
}
// ImageSource represents the source of an image
type ImageSource struct {
Type string `json:"type"` // "base64" or "url"
Type string `json:"type"` // "base64"
MediaType string `json:"media_type,omitempty"`
Data string `json:"data,omitempty"`
URL string `json:"url,omitempty"`
@@ -115,10 +174,13 @@ type ImageSource struct {
// Tool represents a tool definition
type Tool struct {
Type string `json:"type,omitempty"` // "custom" for user-defined tools
Type string `json:"type,omitempty"` // "custom" for user-defined tools, or "web_search_20250305" for web search
Name string `json:"name"`
Description string `json:"description,omitempty"`
InputSchema json.RawMessage `json:"input_schema,omitempty"`
// Web search specific fields
MaxUses int `json:"max_uses,omitempty"`
}
// ToolChoice controls how the model uses tools
@@ -211,6 +273,7 @@ type MessageDelta struct {
// DeltaUsage contains cumulative token usage
type DeltaUsage struct {
InputTokens int `json:"input_tokens"`
OutputTokens int `json:"output_tokens"`
}
@@ -232,6 +295,8 @@ type StreamErrorEvent struct {
// FromMessagesRequest converts an Anthropic MessagesRequest to an Ollama api.ChatRequest
func FromMessagesRequest(r MessagesRequest) (*api.ChatRequest, error) {
logutil.Trace("anthropic: converting request", "req", TraceMessagesRequest(r))
var messages []api.Message
if r.System != nil {
@@ -258,9 +323,10 @@ func FromMessagesRequest(r MessagesRequest) (*api.ChatRequest, error) {
}
}
for _, msg := range r.Messages {
for i, msg := range r.Messages {
converted, err := convertMessage(msg)
if err != nil {
logutil.Trace("anthropic: message conversion failed", "index", i, "role", msg.Role, "err", err)
return nil, err
}
messages = append(messages, converted...)
@@ -287,8 +353,24 @@ func FromMessagesRequest(r MessagesRequest) (*api.ChatRequest, error) {
}
var tools api.Tools
hasBuiltinWebSearch := false
for _, t := range r.Tools {
tool, err := convertTool(t)
if strings.HasPrefix(t.Type, "web_search") {
hasBuiltinWebSearch = true
break
}
}
for _, t := range r.Tools {
// Anthropic built-in web_search maps to Ollama function name "web_search".
// If a user-defined tool also uses that name in the same request, drop the
// user-defined one to avoid ambiguous tool-call routing.
if hasBuiltinWebSearch && !strings.HasPrefix(t.Type, "web_search") && t.Name == "web_search" {
logutil.Trace("anthropic: dropping colliding custom web_search tool", "tool", TraceTool(t))
continue
}
tool, _, err := convertTool(t)
if err != nil {
return nil, err
}
@@ -296,20 +378,39 @@ func FromMessagesRequest(r MessagesRequest) (*api.ChatRequest, error) {
}
var think *api.ThinkValue
normalizedEffort := ""
if r.OutputConfig != nil {
normalizedEffort = strings.ToLower(strings.TrimSpace(r.OutputConfig.Effort))
if normalizedEffort == "xhigh" {
normalizedEffort = "high"
}
}
if r.Thinking != nil && r.Thinking.Type == "enabled" {
think = &api.ThinkValue{Value: true}
}
if r.Thinking != nil && r.Thinking.Type == "disabled" {
think = &api.ThinkValue{Value: false}
}
if think == nil && r.OutputConfig != nil {
switch normalizedEffort {
case "high", "medium", "low", "max":
think = &api.ThinkValue{Value: normalizedEffort}
}
}
stream := r.Stream
return &api.ChatRequest{
convertedRequest := &api.ChatRequest{
Model: r.Model,
Messages: messages,
Options: options,
Stream: &stream,
Tools: tools,
Think: think,
}, nil
}
logutil.Trace("anthropic: converted request", "req", TraceChatRequest(convertedRequest))
return convertedRequest, nil
}
// convertMessage converts an Anthropic MessageParam to Ollama api.Message(s)
@@ -317,129 +418,227 @@ func convertMessage(msg MessageParam) ([]api.Message, error) {
var messages []api.Message
role := strings.ToLower(msg.Role)
switch content := msg.Content.(type) {
case string:
messages = append(messages, api.Message{Role: role, Content: content})
var textContent strings.Builder
var images []api.ImageData
var toolCalls []api.ToolCall
var thinking string
var toolResults []api.Message
textBlocks := 0
imageBlocks := 0
toolUseBlocks := 0
toolResultBlocks := 0
serverToolUseBlocks := 0
webSearchToolResultBlocks := 0
thinkingBlocks := 0
unknownBlocks := 0
case []any:
var textContent strings.Builder
var images []api.ImageData
var toolCalls []api.ToolCall
var thinking string
var toolResults []api.Message
for _, block := range content {
blockMap, ok := block.(map[string]any)
if !ok {
return nil, errors.New("invalid content block format")
for _, block := range msg.Content {
switch block.Type {
case "text":
textBlocks++
if block.Text != nil {
textContent.WriteString(*block.Text)
}
blockType, _ := blockMap["type"].(string)
switch blockType {
case "text":
if text, ok := blockMap["text"].(string); ok {
textContent.WriteString(text)
}
case "image":
source, ok := blockMap["source"].(map[string]any)
if !ok {
return nil, errors.New("invalid image source")
}
sourceType, _ := source["type"].(string)
if sourceType == "base64" {
data, _ := source["data"].(string)
decoded, err := base64.StdEncoding.DecodeString(data)
if err != nil {
return nil, fmt.Errorf("invalid base64 image data: %w", err)
}
images = append(images, decoded)
} else {
return nil, fmt.Errorf("invalid image source type: %s. Only base64 images are supported.", sourceType)
}
// URL images would need to be fetched - skip for now
case "tool_use":
id, ok := blockMap["id"].(string)
if !ok {
return nil, errors.New("tool_use block missing required 'id' field")
}
name, ok := blockMap["name"].(string)
if !ok {
return nil, errors.New("tool_use block missing required 'name' field")
}
tc := api.ToolCall{
ID: id,
Function: api.ToolCallFunction{
Name: name,
},
}
if input, ok := blockMap["input"].(map[string]any); ok {
tc.Function.Arguments = mapToArgs(input)
}
toolCalls = append(toolCalls, tc)
case "tool_result":
toolUseID, _ := blockMap["tool_use_id"].(string)
var resultContent string
switch c := blockMap["content"].(type) {
case string:
resultContent = c
case []any:
for _, cb := range c {
if cbMap, ok := cb.(map[string]any); ok {
if cbMap["type"] == "text" {
if text, ok := cbMap["text"].(string); ok {
resultContent += text
}
}
}
}
}
toolResults = append(toolResults, api.Message{
Role: "tool",
Content: resultContent,
ToolCallID: toolUseID,
})
case "thinking":
if t, ok := blockMap["thinking"].(string); ok {
thinking = t
}
case "image":
imageBlocks++
if block.Source == nil {
logutil.Trace("anthropic: invalid image source", "role", role)
return nil, errors.New("invalid image source")
}
decoded, err := resolveImageSource(block.Source)
if err != nil {
logutil.Trace("anthropic: unsupported image source", "role", role, "source_type", block.Source.Type, "error", err)
return nil, err
}
images = append(images, decoded)
case "tool_use":
toolUseBlocks++
if block.ID == "" {
logutil.Trace("anthropic: tool_use block missing id", "role", role)
return nil, errors.New("tool_use block missing required 'id' field")
}
if block.Name == "" {
logutil.Trace("anthropic: tool_use block missing name", "role", role)
return nil, errors.New("tool_use block missing required 'name' field")
}
toolCalls = append(toolCalls, api.ToolCall{
ID: block.ID,
Function: api.ToolCallFunction{
Name: block.Name,
Arguments: block.Input,
},
})
case "tool_result":
toolResultBlocks++
resultContent, resultImages, err := convertToolResultContent(block.Content)
if err != nil {
logutil.Trace("anthropic: invalid tool_result content", "role", role, "error", err)
return nil, err
}
toolResults = append(toolResults, api.Message{
Role: "tool",
Content: resultContent,
Images: resultImages,
ToolCallID: block.ToolUseID,
})
case "thinking":
thinkingBlocks++
if block.Thinking != nil {
thinking = *block.Thinking
}
case "server_tool_use":
serverToolUseBlocks++
toolCalls = append(toolCalls, api.ToolCall{
ID: block.ID,
Function: api.ToolCallFunction{
Name: block.Name,
Arguments: block.Input,
},
})
case "web_search_tool_result":
webSearchToolResultBlocks++
toolResults = append(toolResults, api.Message{
Role: "tool",
Content: formatWebSearchToolResultContent(block.Content),
ToolCallID: block.ToolUseID,
})
default:
unknownBlocks++
}
if textContent.Len() > 0 || len(images) > 0 || len(toolCalls) > 0 || thinking != "" {
m := api.Message{
Role: role,
Content: textContent.String(),
Images: images,
ToolCalls: toolCalls,
Thinking: thinking,
}
messages = append(messages, m)
}
// Add tool results as separate messages
messages = append(messages, toolResults...)
default:
return nil, fmt.Errorf("invalid message content type: %T", content)
}
if role == "user" && len(toolResults) > 0 {
messages = append(messages, toolResults...)
}
if textContent.Len() > 0 || len(images) > 0 || len(toolCalls) > 0 || thinking != "" {
m := api.Message{
Role: role,
Content: textContent.String(),
Images: images,
ToolCalls: toolCalls,
Thinking: thinking,
}
messages = append(messages, m)
}
// Add tool results as separate messages.
if role != "user" || len(toolResults) == 0 {
messages = append(messages, toolResults...)
}
logutil.Trace("anthropic: converted block message",
"role", role,
"blocks", len(msg.Content),
"text", textBlocks,
"image", imageBlocks,
"tool_use", toolUseBlocks,
"tool_result", toolResultBlocks,
"server_tool_use", serverToolUseBlocks,
"web_search_result", webSearchToolResultBlocks,
"thinking", thinkingBlocks,
"unknown", unknownBlocks,
"messages", TraceAPIMessages(messages),
)
return messages, nil
}
// convertTool converts an Anthropic Tool to an Ollama api.Tool
func convertTool(t Tool) (api.Tool, error) {
func formatWebSearchToolResultContent(content any) string {
switch c := content.(type) {
case string:
return c
case []WebSearchResult:
var resultContent strings.Builder
for _, item := range c {
if item.Type != "web_search_result" {
continue
}
fmt.Fprintf(&resultContent, "- %s: %s\n", item.Title, item.URL)
}
return resultContent.String()
case []any:
var resultContent strings.Builder
for _, item := range c {
itemMap, ok := item.(map[string]any)
if !ok {
continue
}
switch itemMap["type"] {
case "web_search_result":
title, _ := itemMap["title"].(string)
url, _ := itemMap["url"].(string)
fmt.Fprintf(&resultContent, "- %s: %s\n", title, url)
case "web_search_tool_result_error":
errorCode, _ := itemMap["error_code"].(string)
if errorCode == "" {
return "web_search_tool_result_error"
}
return "web_search_tool_result_error: " + errorCode
}
}
return resultContent.String()
case map[string]any:
if c["type"] == "web_search_tool_result_error" {
errorCode, _ := c["error_code"].(string)
if errorCode == "" {
return "web_search_tool_result_error"
}
return "web_search_tool_result_error: " + errorCode
}
data, err := json.Marshal(c)
if err != nil {
return ""
}
return string(data)
case WebSearchToolResultError:
if c.ErrorCode == "" {
return "web_search_tool_result_error"
}
return "web_search_tool_result_error: " + c.ErrorCode
default:
data, err := json.Marshal(c)
if err != nil {
return ""
}
return string(data)
}
}
// convertTool converts an Anthropic Tool to an Ollama api.Tool, returning true if it's a server tool
func convertTool(t Tool) (api.Tool, bool, error) {
if strings.HasPrefix(t.Type, "web_search") {
props := api.NewToolPropertiesMap()
props.Set("query", api.ToolProperty{
Type: api.PropertyType{"string"},
Description: "The search query to look up on the web",
})
return api.Tool{
Type: "function",
Function: api.ToolFunction{
Name: "web_search",
Description: "Search the web for current information. Use this to find up-to-date information about any topic.",
Parameters: api.ToolFunctionParameters{
Type: "object",
Required: []string{"query"},
Properties: props,
},
},
}, true, nil
}
var params api.ToolFunctionParameters
if len(t.InputSchema) > 0 {
if err := json.Unmarshal(t.InputSchema, &params); err != nil {
return api.Tool{}, fmt.Errorf("invalid input_schema for tool %q: %w", t.Name, err)
logutil.Trace("anthropic: invalid tool schema", "tool", t.Name, "err", err)
return api.Tool{}, false, fmt.Errorf("invalid input_schema for tool %q: %w", t.Name, err)
}
}
@@ -450,7 +649,7 @@ func convertTool(t Tool) (api.Tool, error) {
Description: t.Description,
Parameters: params,
},
}, nil
}, false, nil
}
// ToMessagesResponse converts an Ollama api.ChatResponse to an Anthropic MessagesResponse
@@ -517,24 +716,26 @@ func mapStopReason(reason string, hasToolCalls bool) string {
// StreamConverter manages state for converting Ollama streaming responses to Anthropic format
type StreamConverter struct {
ID string
Model string
firstWrite bool
contentIndex int
inputTokens int
outputTokens int
thinkingStarted bool
thinkingDone bool
textStarted bool
toolCallsSent map[string]bool
ID string
Model string
firstWrite bool
contentIndex int
inputTokens int
outputTokens int
estimatedInputTokens int // Estimated tokens from request (used when actual metrics are 0)
thinkingStarted bool
thinkingDone bool
textStarted bool
toolCallsSent map[string]bool
}
func NewStreamConverter(id, model string) *StreamConverter {
func NewStreamConverter(id, model string, estimatedInputTokens int) *StreamConverter {
return &StreamConverter{
ID: id,
Model: model,
firstWrite: true,
toolCallsSent: make(map[string]bool),
ID: id,
Model: model,
firstWrite: true,
estimatedInputTokens: estimatedInputTokens,
toolCallsSent: make(map[string]bool),
}
}
@@ -550,7 +751,11 @@ func (c *StreamConverter) Process(r api.ChatResponse) []StreamEvent {
if c.firstWrite {
c.firstWrite = false
// Use actual metrics if available, otherwise use estimate
c.inputTokens = r.Metrics.PromptEvalCount
if c.inputTokens == 0 && c.estimatedInputTokens > 0 {
c.inputTokens = c.estimatedInputTokens
}
events = append(events, StreamEvent{
Event: "message_start",
@@ -646,6 +851,19 @@ func (c *StreamConverter) Process(r api.ChatResponse) []StreamEvent {
continue
}
// Close thinking block if still open (thinking → tool_use without text in between)
if c.thinkingStarted && !c.thinkingDone {
c.thinkingDone = true
events = append(events, StreamEvent{
Event: "content_block_stop",
Data: ContentBlockStopEvent{
Type: "content_block_stop",
Index: c.contentIndex,
},
})
c.contentIndex++
}
if c.textStarted {
events = append(events, StreamEvent{
Event: "content_block_stop",
@@ -663,7 +881,6 @@ func (c *StreamConverter) Process(r api.ChatResponse) []StreamEvent {
slog.Error("failed to marshal tool arguments", "error", err, "tool_id", tc.ID)
continue
}
events = append(events, StreamEvent{
Event: "content_block_start",
Data: ContentBlockStartEvent{
@@ -673,7 +890,7 @@ func (c *StreamConverter) Process(r api.ChatResponse) []StreamEvent {
Type: "tool_use",
ID: tc.ID,
Name: tc.Function.Name,
Input: map[string]any{},
Input: api.NewToolCallFunctionArguments(),
},
},
})
@@ -721,6 +938,7 @@ func (c *StreamConverter) Process(r api.ChatResponse) []StreamEvent {
})
}
c.inputTokens = r.Metrics.PromptEvalCount
c.outputTokens = r.Metrics.EvalCount
stopReason := mapStopReason(r.DoneReason, len(c.toolCallsSent) > 0)
@@ -732,6 +950,7 @@ func (c *StreamConverter) Process(r api.ChatResponse) []StreamEvent {
StopReason: stopReason,
},
Usage: DeltaUsage{
InputTokens: c.inputTokens,
OutputTokens: c.outputTokens,
},
},
@@ -763,16 +982,286 @@ func GenerateMessageID() string {
return generateID("msg")
}
func resolveImageSource(source *ImageSource) (api.ImageData, error) {
if source.Type != "base64" {
return nil, fmt.Errorf("invalid image source type: %s. Only base64 images are supported.", source.Type)
}
decoded, err := base64.StdEncoding.DecodeString(source.Data)
if err != nil {
return nil, fmt.Errorf("invalid base64 image data: %w", err)
}
return decoded, nil
}
func convertToolResultContent(content any) (string, []api.ImageData, error) {
switch c := content.(type) {
case nil:
return "", nil, nil
case string:
return c, nil, nil
case []any:
var text strings.Builder
var images []api.ImageData
for _, cb := range c {
cbMap, ok := cb.(map[string]any)
if !ok {
continue
}
switch cbMap["type"] {
case "text":
if t, ok := cbMap["text"].(string); ok {
text.WriteString(t)
}
case "image":
rawSource, ok := cbMap["source"].(map[string]any)
if !ok {
return "", nil, errors.New("invalid tool_result image source")
}
var source ImageSource
if rawType, ok := rawSource["type"].(string); ok {
source.Type = rawType
}
if rawMediaType, ok := rawSource["media_type"].(string); ok {
source.MediaType = rawMediaType
}
if rawData, ok := rawSource["data"].(string); ok {
source.Data = rawData
}
img, err := resolveImageSource(&source)
if err != nil {
return "", nil, err
}
images = append(images, img)
}
}
return text.String(), images, nil
default:
return "", nil, nil
}
}
// ptr returns a pointer to the given string value
func ptr(s string) *string {
return &s
}
// mapToArgs converts a map to ToolCallFunctionArguments
func mapToArgs(m map[string]any) api.ToolCallFunctionArguments {
args := api.NewToolCallFunctionArguments()
for k, v := range m {
args.Set(k, v)
}
return args
// CountTokensRequest represents an Anthropic count_tokens request
type CountTokensRequest struct {
Model string `json:"model"`
Messages []MessageParam `json:"messages"`
System any `json:"system,omitempty"`
Tools []Tool `json:"tools,omitempty"`
Thinking *ThinkingConfig `json:"thinking,omitempty"`
}
// EstimateInputTokens estimates input tokens from a MessagesRequest (reuses CountTokensRequest logic)
func EstimateInputTokens(req MessagesRequest) int {
return estimateTokens(CountTokensRequest{
Model: req.Model,
Messages: req.Messages,
System: req.System,
Tools: req.Tools,
Thinking: req.Thinking,
})
}
// CountTokensResponse represents an Anthropic count_tokens response
type CountTokensResponse struct {
InputTokens int `json:"input_tokens"`
}
// estimateTokens returns a rough estimate of tokens (len/4).
// TODO: Replace with actual tokenization via Tokenize API for accuracy.
// Current len/4 heuristic is a rough approximation (~4 chars/token average).
func estimateTokens(req CountTokensRequest) int {
var totalLen int
// Count system prompt
totalLen += countAnyContent(req.System)
for _, msg := range req.Messages {
// Count role (always present)
totalLen += len(msg.Role)
// Count content
totalLen += countAnyContent(msg.Content)
}
for _, tool := range req.Tools {
totalLen += len(tool.Name) + len(tool.Description) + len(tool.InputSchema)
}
// Return len/4 as rough token estimate, minimum 1 if there's any content
tokens := totalLen / 4
if tokens == 0 && (len(req.Messages) > 0 || req.System != nil) {
tokens = 1
}
return tokens
}
func countAnyContent(content any) int {
if content == nil {
return 0
}
switch c := content.(type) {
case string:
return len(c)
case []ContentBlock:
total := 0
for _, block := range c {
total += countContentBlock(block)
}
return total
case []any:
total := 0
for _, item := range c {
data, err := json.Marshal(item)
if err != nil {
continue
}
var block ContentBlock
if err := json.Unmarshal(data, &block); err == nil {
total += countContentBlock(block)
}
}
return total
default:
if data, err := json.Marshal(content); err == nil {
return len(data)
}
return 0
}
}
func countContentBlock(block ContentBlock) int {
total := 0
if block.Text != nil {
total += len(*block.Text)
}
if block.Thinking != nil {
total += len(*block.Thinking)
}
if block.Type == "tool_use" || block.Type == "tool_result" {
if data, err := json.Marshal(block); err == nil {
total += len(data)
}
}
return total
}
// OllamaWebSearchRequest represents a request to the Ollama web search API
type OllamaWebSearchRequest struct {
Query string `json:"query"`
MaxResults int `json:"max_results,omitempty"`
}
// OllamaWebSearchResult represents a single search result from Ollama API
type OllamaWebSearchResult struct {
Title string `json:"title"`
URL string `json:"url"`
Content string `json:"content"`
}
// OllamaWebSearchResponse represents the response from the Ollama web search API
type OllamaWebSearchResponse struct {
Results []OllamaWebSearchResult `json:"results"`
}
var WebSearchEndpoint = "https://ollama.com/api/web_search"
func WebSearch(ctx context.Context, query string, maxResults int) (*OllamaWebSearchResponse, error) {
if internalcloud.Disabled() {
logutil.TraceContext(ctx, "anthropic: web search blocked", "reason", "cloud_disabled")
return nil, errors.New(internalcloud.DisabledError("web search is unavailable"))
}
if maxResults <= 0 {
maxResults = 5
}
if maxResults > 10 {
maxResults = 10
}
reqBody := OllamaWebSearchRequest{
Query: query,
MaxResults: maxResults,
}
body, err := json.Marshal(reqBody)
if err != nil {
return nil, fmt.Errorf("failed to marshal web search request: %w", err)
}
searchURL, err := url.Parse(WebSearchEndpoint)
if err != nil {
return nil, fmt.Errorf("failed to parse web search URL: %w", err)
}
logutil.TraceContext(ctx, "anthropic: web search request",
"query", TraceTruncateString(query),
"max_results", maxResults,
"url", searchURL.String(),
)
q := searchURL.Query()
q.Set("ts", strconv.FormatInt(time.Now().Unix(), 10))
searchURL.RawQuery = q.Encode()
signature := ""
if strings.EqualFold(searchURL.Hostname(), "ollama.com") {
challenge := fmt.Sprintf("%s,%s", http.MethodPost, searchURL.RequestURI())
signature, err = auth.Sign(ctx, []byte(challenge))
if err != nil {
return nil, fmt.Errorf("failed to sign web search request: %w", err)
}
}
logutil.TraceContext(ctx, "anthropic: web search auth", "signed", signature != "")
req, err := http.NewRequestWithContext(ctx, "POST", searchURL.String(), bytes.NewReader(body))
if err != nil {
return nil, fmt.Errorf("failed to create web search request: %w", err)
}
req.Header.Set("Content-Type", "application/json")
if signature != "" {
req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", signature))
}
resp, err := http.DefaultClient.Do(req)
if err != nil {
return nil, fmt.Errorf("web search request failed: %w", err)
}
defer resp.Body.Close()
logutil.TraceContext(ctx, "anthropic: web search response", "status", resp.StatusCode)
if resp.StatusCode != http.StatusOK {
respBody, _ := io.ReadAll(resp.Body)
return nil, fmt.Errorf("web search returned status %d: %s", resp.StatusCode, string(respBody))
}
var searchResp OllamaWebSearchResponse
if err := json.NewDecoder(resp.Body).Decode(&searchResp); err != nil {
return nil, fmt.Errorf("failed to decode web search response: %w", err)
}
logutil.TraceContext(ctx, "anthropic: web search results", "count", len(searchResp.Results))
return &searchResp, nil
}
func ConvertOllamaToAnthropicResults(ollamaResults *OllamaWebSearchResponse) []WebSearchResult {
var results []WebSearchResult
for _, r := range ollamaResults.Results {
results = append(results, WebSearchResult{
Type: "web_search_result",
URL: r.URL,
Title: r.Title,
})
}
return results
}
Regular → Executable
+1017 -63
View File
@@ -3,6 +3,7 @@ package anthropic
import (
"encoding/base64"
"encoding/json"
"strings"
"testing"
"github.com/google/go-cmp/cmp"
@@ -14,11 +15,16 @@ const (
testImage = `iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNk+A8AAQUBAScY42YAAAAASUVORK5CYII=`
)
// testArgs creates ToolCallFunctionArguments from a map (convenience function for tests)
func testArgs(m map[string]any) api.ToolCallFunctionArguments {
// textContent is a convenience for constructing []ContentBlock with a single text block in tests.
func textContent(s string) []ContentBlock {
return []ContentBlock{{Type: "text", Text: &s}}
}
// makeArgs creates ToolCallFunctionArguments from key-value pairs (convenience function for tests)
func makeArgs(kvs ...any) api.ToolCallFunctionArguments {
args := api.NewToolCallFunctionArguments()
for k, v := range m {
args.Set(k, v)
for i := 0; i < len(kvs)-1; i += 2 {
args.Set(kvs[i].(string), kvs[i+1])
}
return args
}
@@ -28,7 +34,7 @@ func TestFromMessagesRequest_Basic(t *testing.T) {
Model: "test-model",
MaxTokens: 1024,
Messages: []MessageParam{
{Role: "user", Content: "Hello"},
{Role: "user", Content: textContent("Hello")},
},
}
@@ -60,7 +66,7 @@ func TestFromMessagesRequest_WithSystemPrompt(t *testing.T) {
MaxTokens: 1024,
System: "You are a helpful assistant.",
Messages: []MessageParam{
{Role: "user", Content: "Hello"},
{Role: "user", Content: textContent("Hello")},
},
}
@@ -87,7 +93,7 @@ func TestFromMessagesRequest_WithSystemPromptArray(t *testing.T) {
map[string]any{"type": "text", "text": " Be concise."},
},
Messages: []MessageParam{
{Role: "user", Content: "Hello"},
{Role: "user", Content: textContent("Hello")},
},
}
@@ -112,7 +118,7 @@ func TestFromMessagesRequest_WithOptions(t *testing.T) {
req := MessagesRequest{
Model: "test-model",
MaxTokens: 2048,
Messages: []MessageParam{{Role: "user", Content: "Hello"}},
Messages: []MessageParam{{Role: "user", Content: textContent("Hello")}},
Temperature: &temp,
TopP: &topP,
TopK: &topK,
@@ -147,14 +153,14 @@ func TestFromMessagesRequest_WithImage(t *testing.T) {
Messages: []MessageParam{
{
Role: "user",
Content: []any{
map[string]any{"type": "text", "text": "What's in this image?"},
map[string]any{
"type": "image",
"source": map[string]any{
"type": "base64",
"media_type": "image/png",
"data": testImage,
Content: []ContentBlock{
{Type: "text", Text: ptr("What's in this image?")},
{
Type: "image",
Source: &ImageSource{
Type: "base64",
MediaType: "image/png",
Data: testImage,
},
},
},
@@ -189,15 +195,15 @@ func TestFromMessagesRequest_WithToolUse(t *testing.T) {
Model: "test-model",
MaxTokens: 1024,
Messages: []MessageParam{
{Role: "user", Content: "What's the weather in Paris?"},
{Role: "user", Content: textContent("What's the weather in Paris?")},
{
Role: "assistant",
Content: []any{
map[string]any{
"type": "tool_use",
"id": "call_123",
"name": "get_weather",
"input": map[string]any{"location": "Paris"},
Content: []ContentBlock{
{
Type: "tool_use",
ID: "call_123",
Name: "get_weather",
Input: makeArgs("location", "Paris"),
},
},
},
@@ -233,11 +239,11 @@ func TestFromMessagesRequest_WithToolResult(t *testing.T) {
Messages: []MessageParam{
{
Role: "user",
Content: []any{
map[string]any{
"type": "tool_result",
"tool_use_id": "call_123",
"content": "The weather in Paris is sunny, 22°C",
Content: []ContentBlock{
{
Type: "tool_result",
ToolUseID: "call_123",
Content: "The weather in Paris is sunny, 22°C",
},
},
},
@@ -265,11 +271,246 @@ func TestFromMessagesRequest_WithToolResult(t *testing.T) {
}
}
func TestFromMessagesRequest_WithToolResultImage(t *testing.T) {
imgData, _ := base64.StdEncoding.DecodeString(testImage)
req := MessagesRequest{
Model: "test-model",
MaxTokens: 1024,
Messages: []MessageParam{
{
Role: "user",
Content: []ContentBlock{
{
Type: "tool_result",
ToolUseID: "call_img",
Content: []any{
map[string]any{"type": "text", "text": "Attached image"},
map[string]any{
"type": "image",
"source": map[string]any{
"type": "base64",
"media_type": "image/png",
"data": testImage,
},
},
},
},
},
},
},
}
result, err := FromMessagesRequest(req)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if len(result.Messages) != 1 {
t.Fatalf("expected 1 message, got %d", len(result.Messages))
}
msg := result.Messages[0]
if msg.Role != "tool" {
t.Errorf("expected role 'tool', got %q", msg.Role)
}
if msg.ToolCallID != "call_img" {
t.Errorf("expected tool_call_id 'call_img', got %q", msg.ToolCallID)
}
if msg.Content != "Attached image" {
t.Errorf("unexpected content: %q", msg.Content)
}
if len(msg.Images) != 1 {
t.Fatalf("expected 1 image, got %d", len(msg.Images))
}
if string(msg.Images[0]) != string(imgData) {
t.Error("image data mismatch")
}
}
func TestFromMessagesRequest_WithToolResultFollowedByUserText(t *testing.T) {
req := MessagesRequest{
Model: "test-model",
MaxTokens: 1024,
Messages: []MessageParam{
{
Role: "assistant",
Content: []ContentBlock{
{
Type: "tool_use",
ID: "call_read",
Name: "Read",
Input: makeArgs("file_path", "/Users/hoyyeva/Desktop/aaa.png"),
},
},
},
{
Role: "user",
Content: []ContentBlock{
{
Type: "tool_result",
ToolUseID: "call_read",
Content: "Read image (311.5KB)",
},
{
Type: "text",
Text: ptr("Please describe it."),
},
},
},
},
}
result, err := FromMessagesRequest(req)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if len(result.Messages) != 3 {
t.Fatalf("expected 3 messages, got %d", len(result.Messages))
}
if result.Messages[1].Role != "tool" {
t.Fatalf("expected second message to be tool, got %q", result.Messages[1].Role)
}
if result.Messages[1].ToolCallID != "call_read" {
t.Fatalf("expected tool_call_id 'call_read', got %q", result.Messages[1].ToolCallID)
}
if result.Messages[2].Role != "user" {
t.Fatalf("expected third message to be user, got %q", result.Messages[2].Role)
}
if result.Messages[2].Content != "Please describe it." {
t.Fatalf("unexpected user content: %q", result.Messages[2].Content)
}
}
func TestFromMessagesRequest_WithOutputConfigEffort(t *testing.T) {
req := MessagesRequest{
Model: "gemma4",
MaxTokens: 32000,
Messages: []MessageParam{
{
Role: "user",
Content: textContent("Describe the image."),
},
},
OutputConfig: &OutputConfig{
Effort: "high",
},
}
result, err := FromMessagesRequest(req)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if result.Think == nil {
t.Fatal("expected think to be set from output_config.effort")
}
if got := result.Think.String(); got != "high" {
t.Fatalf("expected think level 'high', got %q", got)
}
}
func TestFromMessagesRequest_WithOutputConfigEffortXHighMapsToHigh(t *testing.T) {
req := MessagesRequest{
Model: "gemma4",
MaxTokens: 32000,
Messages: []MessageParam{
{
Role: "user",
Content: textContent("Describe the image."),
},
},
OutputConfig: &OutputConfig{
Effort: "xhigh",
},
}
result, err := FromMessagesRequest(req)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if result.Think == nil {
t.Fatal("expected think to be set from output_config.effort")
}
if got := result.Think.String(); got != "high" {
t.Fatalf("expected think level 'high' for xhigh effort, got %q", got)
}
}
func TestFromMessagesRequest_ThinkingDisabledOverridesOutputConfigEffort(t *testing.T) {
req := MessagesRequest{
Model: "gemma4",
MaxTokens: 32000,
Messages: []MessageParam{
{
Role: "user",
Content: textContent("Describe the image."),
},
},
Thinking: &ThinkingConfig{
Type: "disabled",
},
OutputConfig: &OutputConfig{
Effort: "high",
},
}
result, err := FromMessagesRequest(req)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if result.Think == nil {
t.Fatal("expected think to be set")
}
if got := result.Think.Value; got != false {
t.Fatalf("expected think=false when thinking is disabled, got %v", got)
}
}
func TestFromMessagesRequest_ThinkingAdaptiveUsesOutputConfigEffort(t *testing.T) {
req := MessagesRequest{
Model: "gemma4",
MaxTokens: 32000,
Messages: []MessageParam{
{
Role: "user",
Content: textContent("Describe the image."),
},
},
Thinking: &ThinkingConfig{
Type: "adaptive",
},
OutputConfig: &OutputConfig{
Effort: "high",
},
}
result, err := FromMessagesRequest(req)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if result.Think == nil {
t.Fatal("expected think to be set from output_config.effort")
}
if got := result.Think.String(); got != "high" {
t.Fatalf("expected think level 'high' for adaptive thinking, got %q", got)
}
}
func TestFromMessagesRequest_WithTools(t *testing.T) {
req := MessagesRequest{
Model: "test-model",
MaxTokens: 1024,
Messages: []MessageParam{{Role: "user", Content: "Hello"}},
Messages: []MessageParam{{Role: "user", Content: textContent("Hello")}},
Tools: []Tool{
{
Name: "get_weather",
@@ -300,11 +541,83 @@ func TestFromMessagesRequest_WithTools(t *testing.T) {
}
}
func TestFromMessagesRequest_DropsCustomWebSearchWhenBuiltinPresent(t *testing.T) {
req := MessagesRequest{
Model: "test-model",
MaxTokens: 1024,
Messages: []MessageParam{{Role: "user", Content: textContent("Hello")}},
Tools: []Tool{
{
Type: "web_search_20250305",
Name: "web_search",
},
{
Type: "custom",
Name: "web_search",
Description: "User-defined web search that should be dropped",
InputSchema: json.RawMessage(`{"type":"invalid"}`),
},
{
Type: "custom",
Name: "get_weather",
Description: "Get current weather",
InputSchema: json.RawMessage(`{"type":"object","properties":{"location":{"type":"string"}},"required":["location"]}`),
},
},
}
result, err := FromMessagesRequest(req)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if len(result.Tools) != 2 {
t.Fatalf("expected 2 tools after dropping custom web_search, got %d", len(result.Tools))
}
if result.Tools[0].Function.Name != "web_search" {
t.Fatalf("expected first tool to be built-in web_search, got %q", result.Tools[0].Function.Name)
}
if result.Tools[1].Function.Name != "get_weather" {
t.Fatalf("expected second tool to be get_weather, got %q", result.Tools[1].Function.Name)
}
}
func TestFromMessagesRequest_KeepsCustomWebSearchWhenBuiltinAbsent(t *testing.T) {
req := MessagesRequest{
Model: "test-model",
MaxTokens: 1024,
Messages: []MessageParam{{Role: "user", Content: textContent("Hello")}},
Tools: []Tool{
{
Type: "custom",
Name: "web_search",
Description: "User-defined web search",
InputSchema: json.RawMessage(`{"type":"object","properties":{"query":{"type":"string"}},"required":["query"]}`),
},
},
}
result, err := FromMessagesRequest(req)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if len(result.Tools) != 1 {
t.Fatalf("expected 1 custom tool, got %d", len(result.Tools))
}
if result.Tools[0].Function.Name != "web_search" {
t.Fatalf("expected custom tool name web_search, got %q", result.Tools[0].Function.Name)
}
if result.Tools[0].Function.Description != "User-defined web search" {
t.Fatalf("expected custom description preserved, got %q", result.Tools[0].Function.Description)
}
}
func TestFromMessagesRequest_WithThinking(t *testing.T) {
req := MessagesRequest{
Model: "test-model",
MaxTokens: 1024,
Messages: []MessageParam{{Role: "user", Content: "Hello"}},
Messages: []MessageParam{{Role: "user", Content: textContent("Hello")}},
Thinking: &ThinkingConfig{Type: "enabled", BudgetTokens: 1000},
}
@@ -321,20 +634,18 @@ func TestFromMessagesRequest_WithThinking(t *testing.T) {
}
}
// TestFromMessagesRequest_ThinkingOnlyBlock verifies that messages containing only
// a thinking block (no text, images, or tool calls) are preserved and not dropped.
func TestFromMessagesRequest_ThinkingOnlyBlock(t *testing.T) {
req := MessagesRequest{
Model: "test-model",
MaxTokens: 1024,
Messages: []MessageParam{
{Role: "user", Content: "Hello"},
{Role: "user", Content: textContent("Hello")},
{
Role: "assistant",
Content: []any{
map[string]any{
"type": "thinking",
"thinking": "Let me think about this...",
Content: []ContentBlock{
{
Type: "thinking",
Thinking: ptr("Let me think about this..."),
},
},
},
@@ -363,10 +674,10 @@ func TestFromMessagesRequest_ToolUseMissingID(t *testing.T) {
Messages: []MessageParam{
{
Role: "assistant",
Content: []any{
map[string]any{
"type": "tool_use",
"name": "get_weather",
Content: []ContentBlock{
{
Type: "tool_use",
Name: "get_weather",
},
},
},
@@ -389,10 +700,10 @@ func TestFromMessagesRequest_ToolUseMissingName(t *testing.T) {
Messages: []MessageParam{
{
Role: "assistant",
Content: []any{
map[string]any{
"type": "tool_use",
"id": "call_123",
Content: []ContentBlock{
{
Type: "tool_use",
ID: "call_123",
},
},
},
@@ -412,7 +723,7 @@ func TestFromMessagesRequest_InvalidToolSchema(t *testing.T) {
req := MessagesRequest{
Model: "test-model",
MaxTokens: 1024,
Messages: []MessageParam{{Role: "user", Content: "Hello"}},
Messages: []MessageParam{{Role: "user", Content: textContent("Hello")}},
Tools: []Tool{
{
Name: "bad_tool",
@@ -477,7 +788,7 @@ func TestToMessagesResponse_WithToolCalls(t *testing.T) {
ID: "call_123",
Function: api.ToolCallFunction{
Name: "get_weather",
Arguments: testArgs(map[string]any{"location": "Paris"}),
Arguments: makeArgs("location", "Paris"),
},
},
},
@@ -605,7 +916,7 @@ func TestGenerateMessageID(t *testing.T) {
}
func TestStreamConverter_Basic(t *testing.T) {
conv := NewStreamConverter("msg_123", "test-model")
conv := NewStreamConverter("msg_123", "test-model", 0)
// First chunk
resp1 := api.ChatResponse{
@@ -642,7 +953,7 @@ func TestStreamConverter_Basic(t *testing.T) {
},
Done: true,
DoneReason: "stop",
Metrics: api.Metrics{EvalCount: 5},
Metrics: api.Metrics{PromptEvalCount: 10, EvalCount: 5},
}
events2 := conv.Process(resp2)
@@ -650,6 +961,24 @@ func TestStreamConverter_Basic(t *testing.T) {
// Should have content_block_delta, content_block_stop, message_delta, message_stop
hasStop := false
for _, e := range events2 {
if e.Event == "message_delta" {
if data, ok := e.Data.(MessageDeltaEvent); ok {
if data.Type != "message_delta" {
t.Errorf("unexpected data type: %+v", data)
}
if data.Delta.StopReason != "end_turn" {
t.Errorf("unexpected stop reason: %+v", data.Delta.StopReason)
}
if data.Usage.InputTokens != 10 || data.Usage.OutputTokens != 5 {
t.Errorf("unexpected usage: %+v", data.Usage)
}
} else {
t.Errorf("unexpected data: %+v", e.Data)
}
}
if e.Event == "message_stop" {
hasStop = true
}
@@ -660,7 +989,7 @@ func TestStreamConverter_Basic(t *testing.T) {
}
func TestStreamConverter_WithToolCalls(t *testing.T) {
conv := NewStreamConverter("msg_123", "test-model")
conv := NewStreamConverter("msg_123", "test-model", 0)
resp := api.ChatResponse{
Model: "test-model",
@@ -671,7 +1000,7 @@ func TestStreamConverter_WithToolCalls(t *testing.T) {
ID: "call_123",
Function: api.ToolCallFunction{
Name: "get_weather",
Arguments: testArgs(map[string]any{"location": "Paris"}),
Arguments: makeArgs("location", "Paris"),
},
},
},
@@ -710,10 +1039,111 @@ func TestStreamConverter_WithToolCalls(t *testing.T) {
}
}
// TestStreamConverter_ThinkingDirectlyFollowedByToolCall verifies that when a
// model emits a thinking block followed directly by a tool_use block (with no
// text block in between), the streaming converter correctly closes the thinking
// block and increments the content index before opening the tool_use block.
// Previously, the converter reused contentIndex=0 for the tool_use block,
// which caused "Content block not found" errors in clients. See #14816.
func TestStreamConverter_ThinkingDirectlyFollowedByToolCall(t *testing.T) {
conv := NewStreamConverter("msg_123", "test-model", 0)
// First chunk: thinking content (no text)
resp1 := api.ChatResponse{
Model: "test-model",
Message: api.Message{
Role: "assistant",
Thinking: "I should call the tool.",
},
}
events1 := conv.Process(resp1)
// Should have: message_start, content_block_start(thinking), content_block_delta(thinking)
if len(events1) < 3 {
t.Fatalf("expected at least 3 events for thinking chunk, got %d", len(events1))
}
if events1[0].Event != "message_start" {
t.Errorf("expected first event 'message_start', got %q", events1[0].Event)
}
thinkingStart, ok := events1[1].Data.(ContentBlockStartEvent)
if !ok || thinkingStart.ContentBlock.Type != "thinking" {
t.Errorf("expected content_block_start(thinking) as second event, got %+v", events1[1])
}
if thinkingStart.Index != 0 {
t.Errorf("expected thinking block at index 0, got %d", thinkingStart.Index)
}
// Second chunk: tool call (no text between thinking and tool)
resp2 := api.ChatResponse{
Model: "test-model",
Message: api.Message{
Role: "assistant",
ToolCalls: []api.ToolCall{
{
ID: "call_abc",
Function: api.ToolCallFunction{
Name: "ask_user",
Arguments: makeArgs("question", "cats or dogs?"),
},
},
},
},
Done: true,
DoneReason: "stop",
Metrics: api.Metrics{PromptEvalCount: 10, EvalCount: 5},
}
events2 := conv.Process(resp2)
// Expect: content_block_stop(index=0), content_block_start(tool_use, index=1),
// content_block_delta(input_json_delta, index=1), content_block_stop(index=1),
// message_delta, message_stop
var thinkingStop, toolStart, toolDelta, toolStop *StreamEvent
for i := range events2 {
e := &events2[i]
switch e.Event {
case "content_block_stop":
if stop, ok := e.Data.(ContentBlockStopEvent); ok {
if stop.Index == 0 && thinkingStop == nil {
thinkingStop = e
} else if stop.Index == 1 {
toolStop = e
}
}
case "content_block_start":
if start, ok := e.Data.(ContentBlockStartEvent); ok && start.ContentBlock.Type == "tool_use" {
toolStart = e
}
case "content_block_delta":
if delta, ok := e.Data.(ContentBlockDeltaEvent); ok && delta.Delta.Type == "input_json_delta" {
toolDelta = e
}
}
}
if thinkingStop == nil {
t.Error("expected content_block_stop for thinking block (index 0)")
}
if toolStart == nil {
t.Fatal("expected content_block_start for tool_use block")
}
if start, ok := toolStart.Data.(ContentBlockStartEvent); !ok || start.Index != 1 {
t.Errorf("expected tool_use block at index 1, got %+v", toolStart.Data)
}
if toolDelta == nil {
t.Fatal("expected input_json_delta event for tool call")
}
if delta, ok := toolDelta.Data.(ContentBlockDeltaEvent); !ok || delta.Index != 1 {
t.Errorf("expected tool delta at index 1, got %+v", toolDelta.Data)
}
if toolStop == nil {
t.Error("expected content_block_stop for tool_use block (index 1)")
}
}
func TestStreamConverter_ToolCallWithUnmarshalableArgs(t *testing.T) {
// Test that unmarshalable arguments (like channels) are handled gracefully
// and don't cause a panic or corrupt stream
conv := NewStreamConverter("msg_123", "test-model")
conv := NewStreamConverter("msg_123", "test-model", 0)
// Create a channel which cannot be JSON marshaled
unmarshalable := make(chan int)
@@ -760,7 +1190,7 @@ func TestStreamConverter_ToolCallWithUnmarshalableArgs(t *testing.T) {
func TestStreamConverter_MultipleToolCallsWithMixedValidity(t *testing.T) {
// Test that valid tool calls still work when mixed with invalid ones
conv := NewStreamConverter("msg_123", "test-model")
conv := NewStreamConverter("msg_123", "test-model", 0)
unmarshalable := make(chan int)
badArgs := api.NewToolCallFunctionArguments()
@@ -775,7 +1205,7 @@ func TestStreamConverter_MultipleToolCallsWithMixedValidity(t *testing.T) {
ID: "call_good",
Function: api.ToolCallFunction{
Name: "good_function",
Arguments: testArgs(map[string]any{"location": "Paris"}),
Arguments: makeArgs("location", "Paris"),
},
},
{
@@ -824,10 +1254,6 @@ func TestStreamConverter_MultipleToolCallsWithMixedValidity(t *testing.T) {
}
}
// TestContentBlockJSON_EmptyFieldsPresent verifies that empty text and thinking fields
// are serialized in JSON output. The Anthropic SDK requires these fields to be present
// (even when empty) in content_block_start events to properly accumulate streaming deltas.
// Without these fields, the SDK throws: "TypeError: unsupported operand type(s) for +=: 'NoneType' and 'str'"
func TestContentBlockJSON_EmptyFieldsPresent(t *testing.T) {
tests := []struct {
name string
@@ -881,11 +1307,60 @@ func TestContentBlockJSON_EmptyFieldsPresent(t *testing.T) {
}
}
// TestStreamConverter_ContentBlockStartIncludesEmptyFields verifies that content_block_start
// events include the required empty fields for SDK compatibility.
func TestContentBlockJSON_NonToolBlocksDoNotIncludeInput(t *testing.T) {
tests := []struct {
name string
block ContentBlock
}{
{
name: "text block",
block: ContentBlock{
Type: "text",
Text: ptr("hello"),
},
},
{
name: "thinking block",
block: ContentBlock{
Type: "thinking",
Thinking: ptr("let me think"),
},
},
{
name: "image block",
block: ContentBlock{
Type: "image",
Source: &ImageSource{
Type: "base64",
MediaType: "image/png",
Data: testImage,
},
},
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
data, err := json.Marshal(tt.block)
if err != nil {
t.Fatalf("failed to marshal: %v", err)
}
var result map[string]any
if err := json.Unmarshal(data, &result); err != nil {
t.Fatalf("failed to unmarshal: %v", err)
}
if _, ok := result["input"]; ok {
t.Fatalf("unexpected input field in non-tool block JSON: %s", string(data))
}
})
}
}
func TestStreamConverter_ContentBlockStartIncludesEmptyFields(t *testing.T) {
t.Run("text block start includes empty text", func(t *testing.T) {
conv := NewStreamConverter("msg_123", "test-model")
conv := NewStreamConverter("msg_123", "test-model", 0)
resp := api.ChatResponse{
Model: "test-model",
@@ -903,7 +1378,9 @@ func TestStreamConverter_ContentBlockStartIncludesEmptyFields(t *testing.T) {
// Marshal and verify the text field is present
data, _ := json.Marshal(start)
var result map[string]any
json.Unmarshal(data, &result)
if err := json.Unmarshal(data, &result); err != nil {
t.Fatalf("failed to unmarshal content_block_start JSON: %v", err)
}
cb := result["content_block"].(map[string]any)
if _, ok := cb["text"]; !ok {
t.Error("content_block_start for text should include 'text' field")
@@ -919,7 +1396,7 @@ func TestStreamConverter_ContentBlockStartIncludesEmptyFields(t *testing.T) {
})
t.Run("thinking block start includes empty thinking", func(t *testing.T) {
conv := NewStreamConverter("msg_123", "test-model")
conv := NewStreamConverter("msg_123", "test-model", 0)
resp := api.ChatResponse{
Model: "test-model",
@@ -950,4 +1427,481 @@ func TestStreamConverter_ContentBlockStartIncludesEmptyFields(t *testing.T) {
t.Error("expected thinking content_block_start event")
}
})
t.Run("tool_use block start includes empty input object", func(t *testing.T) {
conv := NewStreamConverter("msg_123", "test-model", 0)
resp := api.ChatResponse{
Model: "test-model",
Message: api.Message{
Role: "assistant",
ToolCalls: []api.ToolCall{
{
ID: "call_123",
Function: api.ToolCallFunction{
Name: "get_weather",
Arguments: makeArgs("location", "Paris"),
},
},
},
},
}
events := conv.Process(resp)
var foundToolStart bool
for _, e := range events {
if e.Event == "content_block_start" {
if start, ok := e.Data.(ContentBlockStartEvent); ok {
if start.ContentBlock.Type == "tool_use" {
foundToolStart = true
if start.ContentBlock.Input.Len() != 0 {
t.Errorf("expected empty input object, got len=%d", start.ContentBlock.Input.Len())
}
data, _ := json.Marshal(start)
var result map[string]any
json.Unmarshal(data, &result)
cb := result["content_block"].(map[string]any)
input, ok := cb["input"]
if !ok {
t.Error("content_block_start for tool_use should include 'input' field")
continue
}
inputMap, ok := input.(map[string]any)
if !ok {
t.Errorf("input field should be an object, got %T", input)
continue
}
if len(inputMap) != 0 {
t.Errorf("expected empty input object in content_block_start, got %v", inputMap)
}
}
}
}
}
if !foundToolStart {
t.Error("expected tool_use content_block_start event")
}
})
}
func TestEstimateTokens_SimpleMessage(t *testing.T) {
req := CountTokensRequest{
Model: "test-model",
Messages: []MessageParam{
{Role: "user", Content: textContent("Hello, world!")},
},
}
tokens := estimateTokens(req)
// "user" (4) + "Hello, world!" (13) = 17 chars / 4 = 4 tokens
if tokens < 1 {
t.Errorf("expected at least 1 token, got %d", tokens)
}
// Sanity check: shouldn't be wildly off
if tokens > 10 {
t.Errorf("expected fewer than 10 tokens for short message, got %d", tokens)
}
}
func TestEstimateTokens_WithSystemPrompt(t *testing.T) {
req := CountTokensRequest{
Model: "test-model",
System: "You are a helpful assistant.",
Messages: []MessageParam{
{Role: "user", Content: textContent("Hello")},
},
}
tokens := estimateTokens(req)
// System prompt adds to count
if tokens < 5 {
t.Errorf("expected at least 5 tokens with system prompt, got %d", tokens)
}
}
func TestEstimateTokens_WithTools(t *testing.T) {
req := CountTokensRequest{
Model: "test-model",
Messages: []MessageParam{
{Role: "user", Content: textContent("What's the weather?")},
},
Tools: []Tool{
{
Name: "get_weather",
Description: "Get the current weather for a location",
InputSchema: json.RawMessage(`{"type":"object","properties":{"location":{"type":"string"}}}`),
},
},
}
tokens := estimateTokens(req)
// Tools add significant content
if tokens < 10 {
t.Errorf("expected at least 10 tokens with tools, got %d", tokens)
}
}
func TestEstimateTokens_WithThinking(t *testing.T) {
req := CountTokensRequest{
Model: "test-model",
Messages: []MessageParam{
{Role: "user", Content: textContent("Hello")},
{
Role: "assistant",
Content: []ContentBlock{
{
Type: "thinking",
Thinking: ptr("Let me think about this carefully..."),
},
{
Type: "text",
Text: ptr("Here is my response."),
},
},
},
},
}
tokens := estimateTokens(req)
// Thinking content should be counted
if tokens < 10 {
t.Errorf("expected at least 10 tokens with thinking content, got %d", tokens)
}
}
func TestEstimateTokens_EmptyContent(t *testing.T) {
req := CountTokensRequest{
Model: "test-model",
Messages: []MessageParam{},
}
tokens := estimateTokens(req)
if tokens != 0 {
t.Errorf("expected 0 tokens for empty content, got %d", tokens)
}
}
// Web Search Tests
func TestConvertTool_WebSearch(t *testing.T) {
tool := Tool{
Type: "web_search_20250305",
Name: "web_search",
MaxUses: 5,
}
result, isServerTool, err := convertTool(tool)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if !isServerTool {
t.Error("expected isServerTool to be true for web_search tool")
}
if result.Type != "function" {
t.Errorf("expected type 'function', got %q", result.Type)
}
if result.Function.Name != "web_search" {
t.Errorf("expected name 'web_search', got %q", result.Function.Name)
}
if result.Function.Description == "" {
t.Error("expected non-empty description for web_search tool")
}
// Check that query parameter is defined
if result.Function.Parameters.Properties == nil {
t.Fatal("expected properties to be defined")
}
queryProp, ok := result.Function.Parameters.Properties.Get("query")
if !ok {
t.Error("expected 'query' property to be defined")
}
if len(queryProp.Type) == 0 || queryProp.Type[0] != "string" {
t.Errorf("expected query type to be 'string', got %v", queryProp.Type)
}
}
func TestConvertTool_RegularTool(t *testing.T) {
tool := Tool{
Type: "custom",
Name: "get_weather",
Description: "Get the weather",
InputSchema: json.RawMessage(`{"type":"object","properties":{"location":{"type":"string"}}}`),
}
result, isServerTool, err := convertTool(tool)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if isServerTool {
t.Error("expected isServerTool to be false for regular tool")
}
if result.Function.Name != "get_weather" {
t.Errorf("expected name 'get_weather', got %q", result.Function.Name)
}
}
func TestConvertMessage_ServerToolUse(t *testing.T) {
msg := MessageParam{
Role: "assistant",
Content: []ContentBlock{
{
Type: "server_tool_use",
ID: "srvtoolu_123",
Name: "web_search",
Input: makeArgs("query", "test query"),
},
},
}
messages, err := convertMessage(msg)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if len(messages) != 1 {
t.Fatalf("expected 1 message, got %d", len(messages))
}
if len(messages[0].ToolCalls) != 1 {
t.Fatalf("expected 1 tool call, got %d", len(messages[0].ToolCalls))
}
tc := messages[0].ToolCalls[0]
if tc.ID != "srvtoolu_123" {
t.Errorf("expected tool call ID 'srvtoolu_123', got %q", tc.ID)
}
if tc.Function.Name != "web_search" {
t.Errorf("expected tool name 'web_search', got %q", tc.Function.Name)
}
}
func TestConvertMessage_WebSearchToolResult(t *testing.T) {
msg := MessageParam{
Role: "user",
Content: []ContentBlock{
{
Type: "web_search_tool_result",
ToolUseID: "srvtoolu_123",
Content: []any{
map[string]any{
"type": "web_search_result",
"title": "Test Result",
"url": "https://example.com",
},
},
},
},
}
messages, err := convertMessage(msg)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
// Should have a tool result message
if len(messages) != 1 {
t.Fatalf("expected 1 message, got %d", len(messages))
}
if messages[0].Role != "tool" {
t.Errorf("expected role 'tool', got %q", messages[0].Role)
}
if messages[0].ToolCallID != "srvtoolu_123" {
t.Errorf("expected tool_call_id 'srvtoolu_123', got %q", messages[0].ToolCallID)
}
if messages[0].Content == "" {
t.Error("expected non-empty content from web search results")
}
}
func TestConvertMessage_WebSearchToolResultEmptyStillCreatesToolMessage(t *testing.T) {
msg := MessageParam{
Role: "user",
Content: []ContentBlock{
{
Type: "web_search_tool_result",
ToolUseID: "srvtoolu_empty",
Content: []any{},
},
},
}
messages, err := convertMessage(msg)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if len(messages) != 1 {
t.Fatalf("expected 1 message, got %d", len(messages))
}
if messages[0].Role != "tool" {
t.Fatalf("expected role tool, got %q", messages[0].Role)
}
if messages[0].ToolCallID != "srvtoolu_empty" {
t.Fatalf("expected tool_call_id srvtoolu_empty, got %q", messages[0].ToolCallID)
}
if messages[0].Content != "" {
t.Fatalf("expected empty content for empty web search results, got %q", messages[0].Content)
}
}
func TestConvertMessage_WebSearchToolResultErrorStillCreatesToolMessage(t *testing.T) {
msg := MessageParam{
Role: "user",
Content: []ContentBlock{
{
Type: "web_search_tool_result",
ToolUseID: "srvtoolu_error",
Content: map[string]any{
"type": "web_search_tool_result_error",
"error_code": "max_uses_exceeded",
},
},
},
}
messages, err := convertMessage(msg)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if len(messages) != 1 {
t.Fatalf("expected 1 message, got %d", len(messages))
}
if messages[0].Role != "tool" {
t.Fatalf("expected role tool, got %q", messages[0].Role)
}
if messages[0].ToolCallID != "srvtoolu_error" {
t.Fatalf("expected tool_call_id srvtoolu_error, got %q", messages[0].ToolCallID)
}
if !strings.Contains(messages[0].Content, "max_uses_exceeded") {
t.Fatalf("expected error code in converted tool content, got %q", messages[0].Content)
}
}
func TestConvertOllamaToAnthropicResults(t *testing.T) {
ollamaResp := &OllamaWebSearchResponse{
Results: []OllamaWebSearchResult{
{
Title: "Test Title",
URL: "https://example.com",
Content: "Test content",
},
{
Title: "Another Result",
URL: "https://example.org",
Content: "More content",
},
},
}
results := ConvertOllamaToAnthropicResults(ollamaResp)
if len(results) != 2 {
t.Fatalf("expected 2 results, got %d", len(results))
}
if results[0].Type != "web_search_result" {
t.Errorf("expected type 'web_search_result', got %q", results[0].Type)
}
if results[0].Title != "Test Title" {
t.Errorf("expected title 'Test Title', got %q", results[0].Title)
}
if results[0].URL != "https://example.com" {
t.Errorf("expected URL 'https://example.com', got %q", results[0].URL)
}
}
func TestWebSearchTypes(t *testing.T) {
// Test that WebSearchResult serializes correctly
result := WebSearchResult{
Type: "web_search_result",
URL: "https://example.com",
Title: "Test",
EncryptedContent: "abc123",
PageAge: "2025-01-01",
}
data, err := json.Marshal(result)
if err != nil {
t.Fatalf("failed to marshal WebSearchResult: %v", err)
}
var unmarshaled WebSearchResult
if err := json.Unmarshal(data, &unmarshaled); err != nil {
t.Fatalf("failed to unmarshal WebSearchResult: %v", err)
}
if unmarshaled.Type != result.Type {
t.Errorf("type mismatch: expected %q, got %q", result.Type, unmarshaled.Type)
}
// Test WebSearchToolResultError
errResult := WebSearchToolResultError{
Type: "web_search_tool_result_error",
ErrorCode: "max_uses_exceeded",
}
data, err = json.Marshal(errResult)
if err != nil {
t.Fatalf("failed to marshal WebSearchToolResultError: %v", err)
}
var unmarshaledErr WebSearchToolResultError
if err := json.Unmarshal(data, &unmarshaledErr); err != nil {
t.Fatalf("failed to unmarshal WebSearchToolResultError: %v", err)
}
if unmarshaledErr.ErrorCode != "max_uses_exceeded" {
t.Errorf("error_code mismatch: expected 'max_uses_exceeded', got %q", unmarshaledErr.ErrorCode)
}
}
func TestCitation(t *testing.T) {
citation := Citation{
Type: "web_search_result_location",
URL: "https://example.com",
Title: "Example",
EncryptedIndex: "enc123",
CitedText: "Some cited text...",
}
data, err := json.Marshal(citation)
if err != nil {
t.Fatalf("failed to marshal Citation: %v", err)
}
var unmarshaled Citation
if err := json.Unmarshal(data, &unmarshaled); err != nil {
t.Fatalf("failed to unmarshal Citation: %v", err)
}
if unmarshaled.Type != "web_search_result_location" {
t.Errorf("type mismatch: expected 'web_search_result_location', got %q", unmarshaled.Type)
}
if unmarshaled.CitedText != "Some cited text..." {
t.Errorf("cited_text mismatch: expected 'Some cited text...', got %q", unmarshaled.CitedText)
}
}
+352
View File
@@ -0,0 +1,352 @@
package anthropic
import (
"encoding/json"
"fmt"
"sort"
"github.com/ollama/ollama/api"
)
// Trace truncation limits.
const (
TraceMaxStringRunes = 240
TraceMaxSliceItems = 8
TraceMaxMapEntries = 16
TraceMaxDepth = 4
)
// TraceTruncateString shortens s to TraceMaxStringRunes, appending a count of
// omitted characters when truncated.
func TraceTruncateString(s string) string {
if len(s) == 0 {
return s
}
runes := []rune(s)
if len(runes) <= TraceMaxStringRunes {
return s
}
return fmt.Sprintf("%s...(+%d chars)", string(runes[:TraceMaxStringRunes]), len(runes)-TraceMaxStringRunes)
}
// TraceJSON round-trips v through JSON and returns a compacted representation.
func TraceJSON(v any) any {
if v == nil {
return nil
}
data, err := json.Marshal(v)
if err != nil {
return map[string]any{"marshal_error": err.Error(), "type": fmt.Sprintf("%T", v)}
}
var out any
if err := json.Unmarshal(data, &out); err != nil {
return TraceTruncateString(string(data))
}
return TraceCompactValue(out, 0)
}
// TraceCompactValue recursively truncates strings, slices, and maps for trace
// output. depth tracks recursion to enforce TraceMaxDepth.
func TraceCompactValue(v any, depth int) any {
if v == nil {
return nil
}
if depth >= TraceMaxDepth {
switch t := v.(type) {
case string:
return TraceTruncateString(t)
case []any:
return fmt.Sprintf("<array len=%d>", len(t))
case map[string]any:
return fmt.Sprintf("<object keys=%d>", len(t))
default:
return fmt.Sprintf("<%T>", v)
}
}
switch t := v.(type) {
case string:
return TraceTruncateString(t)
case []any:
limit := min(len(t), TraceMaxSliceItems)
out := make([]any, 0, limit+1)
for i := range limit {
out = append(out, TraceCompactValue(t[i], depth+1))
}
if len(t) > limit {
out = append(out, fmt.Sprintf("... +%d more items", len(t)-limit))
}
return out
case map[string]any:
keys := make([]string, 0, len(t))
for k := range t {
keys = append(keys, k)
}
sort.Strings(keys)
limit := min(len(keys), TraceMaxMapEntries)
out := make(map[string]any, limit+1)
for i := range limit {
out[keys[i]] = TraceCompactValue(t[keys[i]], depth+1)
}
if len(keys) > limit {
out["__truncated_keys"] = len(keys) - limit
}
return out
default:
return t
}
}
// ---------------------------------------------------------------------------
// Anthropic request/response tracing
// ---------------------------------------------------------------------------
// TraceMessagesRequest returns a compact trace representation of a MessagesRequest.
func TraceMessagesRequest(r MessagesRequest) map[string]any {
return map[string]any{
"model": r.Model,
"max_tokens": r.MaxTokens,
"messages": traceMessageParams(r.Messages),
"system": traceAnthropicContent(r.System),
"stream": r.Stream,
"tools": traceTools(r.Tools),
"tool_choice": TraceJSON(r.ToolChoice),
"thinking": TraceJSON(r.Thinking),
"stop_sequences": r.StopSequences,
"temperature": ptrVal(r.Temperature),
"top_p": ptrVal(r.TopP),
"top_k": ptrVal(r.TopK),
}
}
// TraceMessagesResponse returns a compact trace representation of a MessagesResponse.
func TraceMessagesResponse(r MessagesResponse) map[string]any {
return map[string]any{
"id": r.ID,
"model": r.Model,
"content": TraceJSON(r.Content),
"stop_reason": r.StopReason,
"usage": r.Usage,
}
}
func traceMessageParams(msgs []MessageParam) []map[string]any {
out := make([]map[string]any, 0, len(msgs))
for _, m := range msgs {
out = append(out, map[string]any{
"role": m.Role,
"content": traceAnthropicContent(m.Content),
})
}
return out
}
func traceAnthropicContent(content any) any {
switch c := content.(type) {
case nil:
return nil
case string:
return TraceTruncateString(c)
case []any:
blocks := make([]any, 0, len(c))
for _, block := range c {
blockMap, ok := block.(map[string]any)
if !ok {
blocks = append(blocks, TraceCompactValue(block, 0))
continue
}
blocks = append(blocks, traceAnthropicBlock(blockMap))
}
return blocks
default:
return TraceJSON(c)
}
}
func traceAnthropicBlock(block map[string]any) map[string]any {
blockType, _ := block["type"].(string)
out := map[string]any{"type": blockType}
switch blockType {
case "text":
if text, ok := block["text"].(string); ok {
out["text"] = TraceTruncateString(text)
} else {
out["text"] = TraceCompactValue(block["text"], 0)
}
case "thinking":
if thinking, ok := block["thinking"].(string); ok {
out["thinking"] = TraceTruncateString(thinking)
} else {
out["thinking"] = TraceCompactValue(block["thinking"], 0)
}
case "tool_use", "server_tool_use":
out["id"] = block["id"]
out["name"] = block["name"]
out["input"] = TraceCompactValue(block["input"], 0)
case "tool_result", "web_search_tool_result":
out["tool_use_id"] = block["tool_use_id"]
out["content"] = TraceCompactValue(block["content"], 0)
case "image":
if source, ok := block["source"].(map[string]any); ok {
out["source"] = map[string]any{
"type": source["type"],
"media_type": source["media_type"],
"url": source["url"],
"data_len": len(fmt.Sprint(source["data"])),
}
}
default:
out["block"] = TraceCompactValue(block, 0)
}
return out
}
func traceTools(tools []Tool) []map[string]any {
out := make([]map[string]any, 0, len(tools))
for _, t := range tools {
out = append(out, TraceTool(t))
}
return out
}
// TraceTool returns a compact trace representation of an Anthropic Tool.
func TraceTool(t Tool) map[string]any {
return map[string]any{
"type": t.Type,
"name": t.Name,
"description": TraceTruncateString(t.Description),
"input_schema": TraceJSON(t.InputSchema),
"max_uses": t.MaxUses,
}
}
// ContentBlockTypes returns the type strings from content (when it's []any blocks).
func ContentBlockTypes(content any) []string {
blocks, ok := content.([]any)
if !ok {
return nil
}
types := make([]string, 0, len(blocks))
for _, block := range blocks {
blockMap, ok := block.(map[string]any)
if !ok {
types = append(types, fmt.Sprintf("%T", block))
continue
}
t, _ := blockMap["type"].(string)
types = append(types, t)
}
return types
}
func ptrVal[T any](v *T) any {
if v == nil {
return nil
}
return *v
}
// ---------------------------------------------------------------------------
// Ollama api.* tracing (shared between anthropic and middleware packages)
// ---------------------------------------------------------------------------
// TraceChatRequest returns a compact trace representation of an Ollama ChatRequest.
func TraceChatRequest(req *api.ChatRequest) map[string]any {
if req == nil {
return nil
}
stream := false
if req.Stream != nil {
stream = *req.Stream
}
return map[string]any{
"model": req.Model,
"messages": TraceAPIMessages(req.Messages),
"tools": TraceAPITools(req.Tools),
"stream": stream,
"options": req.Options,
"think": TraceJSON(req.Think),
}
}
// TraceChatResponse returns a compact trace representation of an Ollama ChatResponse.
func TraceChatResponse(resp api.ChatResponse) map[string]any {
return map[string]any{
"model": resp.Model,
"done": resp.Done,
"done_reason": resp.DoneReason,
"message": TraceAPIMessage(resp.Message),
"metrics": TraceJSON(resp.Metrics),
}
}
// TraceAPIMessages returns compact trace representations for a slice of api.Message.
func TraceAPIMessages(msgs []api.Message) []map[string]any {
out := make([]map[string]any, 0, len(msgs))
for _, m := range msgs {
out = append(out, TraceAPIMessage(m))
}
return out
}
// TraceAPIMessage returns a compact trace representation of a single api.Message.
func TraceAPIMessage(m api.Message) map[string]any {
return map[string]any{
"role": m.Role,
"content": TraceTruncateString(m.Content),
"thinking": TraceTruncateString(m.Thinking),
"images": traceImageSizes(m.Images),
"tool_calls": traceToolCalls(m.ToolCalls),
"tool_name": m.ToolName,
"tool_call_id": m.ToolCallID,
}
}
func traceImageSizes(images []api.ImageData) []int {
if len(images) == 0 {
return nil
}
sizes := make([]int, 0, len(images))
for _, img := range images {
sizes = append(sizes, len(img))
}
return sizes
}
// TraceAPITools returns compact trace representations for a slice of api.Tool.
func TraceAPITools(tools api.Tools) []map[string]any {
out := make([]map[string]any, 0, len(tools))
for _, t := range tools {
out = append(out, TraceAPITool(t))
}
return out
}
// TraceAPITool returns a compact trace representation of a single api.Tool.
func TraceAPITool(t api.Tool) map[string]any {
return map[string]any{
"type": t.Type,
"name": t.Function.Name,
"description": TraceTruncateString(t.Function.Description),
"parameters": TraceJSON(t.Function.Parameters),
}
}
// TraceToolCall returns a compact trace representation of an api.ToolCall.
func TraceToolCall(tc api.ToolCall) map[string]any {
return map[string]any{
"id": tc.ID,
"name": tc.Function.Name,
"args": TraceJSON(tc.Function.Arguments),
}
}
func traceToolCalls(tcs []api.ToolCall) []map[string]any {
if len(tcs) == 0 {
return nil
}
out := make([]map[string]any, 0, len(tcs))
for _, tc := range tcs {
out = append(out, TraceToolCall(tc))
}
return out
}
+24
View File
@@ -259,6 +259,10 @@ func (c *Client) stream(ctx context.Context, method, path string, data any, fn f
}
}
if err := scanner.Err(); err != nil {
return err
}
return nil
}
@@ -368,6 +372,16 @@ func (c *Client) List(ctx context.Context) (*ListResponse, error) {
return &lr, nil
}
// ModelRecommendationsExperimental lists model recommendations from the local
// server's experimental recommendations endpoint.
func (c *Client) ModelRecommendationsExperimental(ctx context.Context) (*ModelRecommendationsResponse, error) {
var resp ModelRecommendationsResponse
if err := c.do(ctx, http.MethodGet, "/api/experimental/model-recommendations", nil, &resp); err != nil {
return nil, err
}
return &resp, nil
}
// ListRunning lists running models.
func (c *Client) ListRunning(ctx context.Context) (*ProcessResponse, error) {
var lr ProcessResponse
@@ -449,6 +463,16 @@ func (c *Client) Version(ctx context.Context) (string, error) {
return version.Version, nil
}
// CloudStatusExperimental returns whether cloud features are disabled on the server.
func (c *Client) CloudStatusExperimental(ctx context.Context) (*StatusResponse, error) {
var status StatusResponse
if err := c.do(ctx, http.MethodGet, "/api/status", nil, &status); err != nil {
return nil, err
}
return &status, nil
}
// Signout will signout a client for a local ollama server.
func (c *Client) Signout(ctx context.Context) error {
return c.do(ctx, http.MethodPost, "/api/signout", nil, nil)
+50
View File
@@ -3,6 +3,7 @@ package api
import (
"encoding/json"
"fmt"
"io"
"net/http"
"net/http/httptest"
"net/url"
@@ -192,6 +193,35 @@ func TestClientStream(t *testing.T) {
}
}
func TestClientStreamReportsReadErrors(t *testing.T) {
client := NewClient(
&url.URL{Scheme: "http", Host: "example.com"},
&http.Client{Transport: roundTripFunc(func(*http.Request) (*http.Response, error) {
body := failingReader{
data: []byte(`{"message":{"content":"partial"}}` + "\n"),
err: io.ErrUnexpectedEOF,
}
return &http.Response{
StatusCode: http.StatusOK,
Status: "200 OK",
Body: io.NopCloser(&body),
Header: make(http.Header),
}, nil
})},
)
err := client.stream(t.Context(), http.MethodPost, "/api/chat", nil, func([]byte) error {
return nil
})
if err == nil {
t.Fatal("expected stream read error")
}
if !strings.Contains(err.Error(), io.ErrUnexpectedEOF.Error()) {
t.Fatalf("expected unexpected EOF, got %v", err)
}
}
func TestClientDo(t *testing.T) {
testCases := []struct {
name string
@@ -320,3 +350,23 @@ func TestClientDo(t *testing.T) {
})
}
}
type roundTripFunc func(*http.Request) (*http.Response, error)
func (f roundTripFunc) RoundTrip(req *http.Request) (*http.Response, error) {
return f(req)
}
type failingReader struct {
data []byte
err error
}
func (r *failingReader) Read(p []byte) (int, error) {
if len(r.data) > 0 {
n := copy(p, r.data)
r.data = r.data[n:]
return n, nil
}
return 0, r.err
}
+115 -33
View File
@@ -127,6 +127,20 @@ type GenerateRequest struct {
// each with an associated log probability. Only applies when Logprobs is true.
// Valid values are 0-20. Default is 0 (only return the selected token's logprob).
TopLogprobs int `json:"top_logprobs,omitempty"`
// Experimental: Image generation fields (may change or be removed)
// Width is the width of the generated image in pixels.
// Only used for image generation models.
Width int32 `json:"width,omitempty"`
// Height is the height of the generated image in pixels.
// Only used for image generation models.
Height int32 `json:"height,omitempty"`
// Steps is the number of diffusion steps for image generation.
// Only used for image generation models.
Steps int32 `json:"steps,omitempty"`
}
// ChatRequest describes a request sent by [Client.Chat].
@@ -422,6 +436,7 @@ type ToolProperty struct {
Description string `json:"description,omitempty"`
Enum []any `json:"enum,omitempty"`
Properties *ToolPropertiesMap `json:"properties,omitempty"`
Required []string `json:"required,omitempty"`
}
// ToTypeScriptType converts a ToolProperty to a TypeScript type string
@@ -585,12 +600,13 @@ type Options struct {
// Runner options which must be set when the model is loaded into memory
type Runner struct {
NumCtx int `json:"num_ctx,omitempty"`
NumBatch int `json:"num_batch,omitempty"`
NumGPU int `json:"num_gpu,omitempty"`
MainGPU int `json:"main_gpu,omitempty"`
UseMMap *bool `json:"use_mmap,omitempty"`
NumThread int `json:"num_thread,omitempty"`
NumCtx int `json:"num_ctx,omitempty"`
NumBatch int `json:"num_batch,omitempty"`
NumGPU int `json:"num_gpu,omitempty"`
MainGPU *int `json:"main_gpu,omitempty"`
UseMMap *bool `json:"use_mmap,omitempty"`
NumThread int `json:"num_thread,omitempty"`
DraftNumPredict int `json:"draft_num_predict,omitempty"`
}
// EmbedRequest is the request passed to [Client.Embed].
@@ -657,6 +673,9 @@ type CreateRequest struct {
// Quantize is the quantization format for the model; leave blank to not change the quantization level.
Quantize string `json:"quantize,omitempty"`
// DraftQuantize is the quantization format for the draft model.
DraftQuantize string `json:"draft_quantize,omitempty"`
// From is the name of the model or file to use as the source.
From string `json:"from,omitempty"`
@@ -666,6 +685,9 @@ type CreateRequest struct {
// Files is a map of files include when creating the model.
Files map[string]string `json:"files,omitempty"`
// DraftFiles is a map of draft model files to include when creating the model.
DraftFiles map[string]string `json:"draft_files,omitempty"`
// Adapters is a map of LoRA adapters to include when creating the model.
Adapters map[string]string `json:"adapters,omitempty"`
@@ -735,7 +757,7 @@ type ShowResponse struct {
Messages []Message `json:"messages,omitempty"`
RemoteModel string `json:"remote_model,omitempty"`
RemoteHost string `json:"remote_host,omitempty"`
ModelInfo map[string]any `json:"model_info,omitempty"`
ModelInfo map[string]any `json:"model_info"`
ProjectorInfo map[string]any `json:"projector_info,omitempty"`
Tensors []Tensor `json:"tensors,omitempty"`
Capabilities []model.Capability `json:"capabilities,omitempty"`
@@ -787,6 +809,21 @@ type ListResponse struct {
Models []ListModelResponse `json:"models"`
}
// ModelRecommendationsResponse is the response from [Client.ModelRecommendationsExperimental].
type ModelRecommendationsResponse struct {
Recommendations []ModelRecommendation `json:"recommendations"`
}
// ModelRecommendation is a single recommendation entry in [ModelRecommendationsResponse].
type ModelRecommendation struct {
Model string `json:"model"`
Description string `json:"description"`
ContextLength int `json:"context_length,omitempty"`
MaxOutputTokens int `json:"max_output_tokens,omitempty"`
VRAMBytes int64 `json:"vram_bytes,omitempty"`
RequiredPlan string `json:"required_plan,omitempty"`
}
// ProcessResponse is the response from [Client.Process].
type ProcessResponse struct {
Models []ProcessModelResponse `json:"models"`
@@ -794,14 +831,15 @@ type ProcessResponse struct {
// ListModelResponse is a single model description in [ListResponse].
type ListModelResponse struct {
Name string `json:"name"`
Model string `json:"model"`
RemoteModel string `json:"remote_model,omitempty"`
RemoteHost string `json:"remote_host,omitempty"`
ModifiedAt time.Time `json:"modified_at"`
Size int64 `json:"size"`
Digest string `json:"digest"`
Details ModelDetails `json:"details,omitempty"`
Name string `json:"name"`
Model string `json:"model"`
RemoteModel string `json:"remote_model,omitempty"`
RemoteHost string `json:"remote_host,omitempty"`
ModifiedAt time.Time `json:"modified_at"`
Size int64 `json:"size"`
Digest string `json:"digest"`
Details ModelDetails `json:"details,omitempty"`
Capabilities []model.Capability `json:"capabilities,omitempty"`
}
// ProcessModelResponse is a single model description in [ProcessResponse].
@@ -820,6 +858,16 @@ type TokenResponse struct {
Token string `json:"token"`
}
type CloudStatus struct {
Disabled bool `json:"disabled"`
Source string `json:"source"`
}
// StatusResponse is the response from [Client.CloudStatusExperimental].
type StatusResponse struct {
Cloud CloudStatus `json:"cloud"`
}
// GenerateResponse is the response passed into [GenerateResponseFunc].
type GenerateResponse struct {
// Model is the model name that generated the response.
@@ -860,6 +908,20 @@ type GenerateResponse struct {
// Logprobs contains log probability information for the generated tokens,
// if requested via the Logprobs parameter.
Logprobs []Logprob `json:"logprobs,omitempty"`
// Experimental: Image generation fields (may change or be removed)
// Image contains a base64-encoded generated image.
// Only present for image generation models.
Image string `json:"image,omitempty"`
// Completed is the number of completed steps in image generation.
// Only present for image generation models during streaming.
Completed int64 `json:"completed,omitempty"`
// Total is the total number of steps for image generation.
// Only present for image generation models during streaming.
Total int64 `json:"total,omitempty"`
}
// ModelDetails provides details about a model.
@@ -870,6 +932,8 @@ type ModelDetails struct {
Families []string `json:"families"`
ParameterSize string `json:"parameter_size"`
QuantizationLevel string `json:"quantization_level"`
ContextLength int `json:"context_length,omitempty"`
EmbeddingLength int `json:"embedding_length,omitempty"`
}
// UserResponse provides information about a user.
@@ -992,14 +1056,25 @@ func (opts *Options) FromMap(m map[string]any) error {
}
field.Set(reflect.ValueOf(slice))
case reflect.Pointer:
var b bool
if field.Type() == reflect.TypeOf(&b) {
switch field.Type().Elem().Kind() {
case reflect.Bool:
val, ok := val.(bool)
if !ok {
return fmt.Errorf("option %q must be of type boolean", key)
}
field.Set(reflect.ValueOf(&val))
} else {
case reflect.Int:
var i int
switch t := val.(type) {
case int64:
i = int(t)
case float64:
i = int(t)
default:
return fmt.Errorf("option %q must be of type integer", key)
}
field.Set(reflect.ValueOf(&i))
default:
return fmt.Errorf("unknown type loading config params: %v %v", field.Kind(), field.Type())
}
default:
@@ -1032,16 +1107,17 @@ func DefaultOptions() Options {
Runner: Runner{
// options set when the model is loaded
NumCtx: int(envconfig.ContextLength()),
NumBatch: 512,
NumGPU: -1, // -1 here indicates that NumGPU should be set dynamically
NumThread: 0, // let the runtime decide
UseMMap: nil,
NumCtx: int(envconfig.ContextLength()),
NumBatch: 512,
NumGPU: -1, // -1 here indicates that NumGPU should be set dynamically
NumThread: 0, // let the runtime decide
DraftNumPredict: 4,
UseMMap: nil,
},
}
}
// ThinkValue represents a value that can be a boolean or a string ("high", "medium", "low")
// ThinkValue represents a value that can be a boolean or a string ("high", "medium", "low", "max")
type ThinkValue struct {
// Value can be a bool or string
Value interface{}
@@ -1057,7 +1133,7 @@ func (t *ThinkValue) IsValid() bool {
case bool:
return true
case string:
return v == "high" || v == "medium" || v == "low"
return v == "high" || v == "medium" || v == "low" || v == "max"
default:
return false
}
@@ -1091,8 +1167,8 @@ func (t *ThinkValue) Bool() bool {
case bool:
return v
case string:
// Any string value ("high", "medium", "low") means thinking is enabled
return v == "high" || v == "medium" || v == "low"
// Any string value ("high", "medium", "low", "max") means thinking is enabled
return v == "high" || v == "medium" || v == "low" || v == "max"
default:
return false
}
@@ -1130,14 +1206,14 @@ func (t *ThinkValue) UnmarshalJSON(data []byte) error {
var s string
if err := json.Unmarshal(data, &s); err == nil {
// Validate string values
if s != "high" && s != "medium" && s != "low" {
return fmt.Errorf("invalid think value: %q (must be \"high\", \"medium\", \"low\", true, or false)", s)
if s != "high" && s != "medium" && s != "low" && s != "max" {
return fmt.Errorf("invalid think value: %q (must be \"high\", \"medium\", \"low\", \"max\", true, or false)", s)
}
t.Value = s
return nil
}
return fmt.Errorf("think must be a boolean or string (\"high\", \"medium\", \"low\", true, or false)")
return fmt.Errorf("think must be a boolean or string (\"high\", \"medium\", \"low\", \"max\", true, or false)")
}
// MarshalJSON implements json.Marshaler
@@ -1240,14 +1316,20 @@ func FormatParams(params map[string][]string) (map[string]any, error) {
// TODO: only string slices are supported right now
out[key] = vals
case reflect.Pointer:
var b bool
if field.Type() == reflect.TypeOf(&b) {
switch field.Type().Elem().Kind() {
case reflect.Bool:
boolVal, err := strconv.ParseBool(vals[0])
if err != nil {
return nil, fmt.Errorf("invalid bool value %s", vals)
}
out[key] = &boolVal
} else {
case reflect.Int:
intVal, err := strconv.ParseInt(vals[0], 10, 64)
if err != nil {
return nil, fmt.Errorf("invalid int value %s", vals)
}
out[key] = intVal
default:
return nil, fmt.Errorf("unknown type %s for %s", field.Kind(), key)
}
default:
+56
View File
@@ -20,6 +20,10 @@ func testPropsMap(m map[string]ToolProperty) *ToolPropertiesMap {
return props
}
func testIntPtr(v int) *int {
return &v
}
// testArgs creates ToolCallFunctionArguments from a map (convenience function for tests, order not preserved)
func testArgs(m map[string]any) ToolCallFunctionArguments {
args := NewToolCallFunctionArguments()
@@ -168,6 +172,47 @@ func TestUseMmapParsingFromJSON(t *testing.T) {
}
}
func TestMainGPUParsingFromJSON(t *testing.T) {
tests := []struct {
name string
req string
wantGPU *int
}{
{
name: "Undefined",
req: `{}`,
},
{
name: "Zero",
req: `{ "main_gpu": 0 }`,
wantGPU: testIntPtr(0),
},
{
name: "Nonzero",
req: `{ "main_gpu": 1 }`,
wantGPU: testIntPtr(1),
},
}
for _, test := range tests {
t.Run(test.name, func(t *testing.T) {
var oMap map[string]any
err := json.Unmarshal([]byte(test.req), &oMap)
require.NoError(t, err)
opts := DefaultOptions()
err = opts.FromMap(oMap)
require.NoError(t, err)
if test.wantGPU == nil {
assert.Nil(t, opts.MainGPU)
} else if assert.NotNil(t, opts.MainGPU) {
assert.Equal(t, *test.wantGPU, *opts.MainGPU)
}
})
}
}
func TestUseMmapFormatParams(t *testing.T) {
tr := true
fa := false
@@ -232,6 +277,12 @@ func TestUseMmapFormatParams(t *testing.T) {
}
}
func TestMainGPUFormatParams(t *testing.T) {
resp, err := FormatParams(map[string][]string{"main_gpu": {"0"}})
require.NoError(t, err)
assert.Equal(t, int64(0), resp["main_gpu"])
}
func TestMessage_UnmarshalJSON(t *testing.T) {
tests := []struct {
input string
@@ -495,6 +546,11 @@ func TestThinking_UnmarshalJSON(t *testing.T) {
input: `{ "think": "low" }`,
expectedThinking: &ThinkValue{Value: "low"},
},
{
name: "string_max",
input: `{ "think": "max" }`,
expectedThinking: &ThinkValue{Value: "max"},
},
{
name: "invalid_string",
input: `{ "think": "invalid" }`,
+3 -3
View File
@@ -75,9 +75,9 @@ The `-dev` flag enables:
CI builds with Xcode 14.1 for OS compatibility prior to v13. If you want to manually build v11+ support, you can download the older Xcode [here](https://developer.apple.com/services-account/download?path=/Developer_Tools/Xcode_14.1/Xcode_14.1.xip), extract, then `mv ./Xcode.app /Applications/Xcode_14.1.0.app` then activate with:
```
export CGO_CFLAGS=-mmacosx-version-min=12.0
export CGO_CXXFLAGS=-mmacosx-version-min=12.0
export CGO_LDFLAGS=-mmacosx-version-min=12.0
export CGO_CFLAGS="-O3 -mmacosx-version-min=12.0"
export CGO_CXXFLAGS="-O3 -mmacosx-version-min=12.0"
export CGO_LDFLAGS="-mmacosx-version-min=12.0"
export SDKROOT=/Applications/Xcode_14.1.0.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX.sdk
export DEVELOPER_DIR=/Applications/Xcode_14.1.0.app/Contents/Developer
```
+33 -6
View File
@@ -35,6 +35,7 @@ import (
var (
wv = &Webview{}
uiServerPort int
appStore *store.Store
)
var debug = strings.EqualFold(os.Getenv("OLLAMA_DEBUG"), "true") || os.Getenv("OLLAMA_DEBUG") == "1"
@@ -156,10 +157,6 @@ func main() {
}
}
if u := os.Getenv("OLLAMA_UPDATE_URL"); u != "" {
updater.UpdateCheckURLBase = u
}
// Detect if this is a first start after an upgrade, in
// which case we need to do some cleanup
var skipMove bool
@@ -208,6 +205,7 @@ func main() {
uiServerPort = port
st := &store.Store{}
appStore = st
// Enable CORS in development mode
if devMode {
@@ -253,6 +251,8 @@ func main() {
done <- osrv.Run(octx)
}()
upd := &updater.Updater{Store: st}
uiServer := ui.Server{
Token: token,
Restart: func() {
@@ -267,6 +267,10 @@ func main() {
ToolRegistry: toolRegistry,
Dev: devMode,
Logger: slog.Default(),
Updater: upd,
UpdateAvailableFunc: func() {
UpdateAvailable("")
},
}
srv := &http.Server{
@@ -284,8 +288,20 @@ func main() {
slog.Debug("background desktop server done")
}()
updater := &updater.Updater{Store: st}
updater.StartBackgroundUpdaterChecker(ctx, UpdateAvailable)
upd.StartBackgroundUpdaterChecker(ctx, UpdateAvailable)
// Check for pending updates on startup (show tray notification if update is ready)
if updater.IsUpdatePending() {
// On Windows, the tray is initialized in osRun(). Calling UpdateAvailable
// before that would dereference a nil tray callback.
// TODO: refactor so the update check runs after platform init on all platforms.
if runtime.GOOS == "windows" {
slog.Debug("update pending on startup, deferring tray notification until tray initialization")
} else {
slog.Debug("update pending on startup, showing tray notification")
UpdateAvailable("")
}
}
hasCompletedFirstRun, err := st.HasCompletedFirstRun()
if err != nil {
@@ -348,6 +364,17 @@ func startHiddenTasks() {
// CLI triggered app startup use-case
slog.Info("deferring pending update for fast startup")
} else {
// Check if auto-update is enabled before automatically upgrading
settings, err := appStore.Settings()
if err != nil {
slog.Warn("failed to load settings for upgrade check", "error", err)
} else if !settings.AutoUpdateEnabled {
slog.Info("auto-update disabled, skipping automatic upgrade at startup")
// Still show tray notification so user knows update is ready
UpdateAvailable("")
return
}
if err := updater.DoUpgradeAtStartup(); err != nil {
slog.Info("unable to perform upgrade at startup", "error", err)
// Make sure the restart to upgrade menu shows so we can attempt an interactive upgrade to get authorization
+19
View File
@@ -14,6 +14,7 @@ extern NSString *SystemWidePath;
@interface AppDelegate () <NSWindowDelegate, WKNavigationDelegate, WKUIDelegate>
@property(strong, nonatomic) NSStatusItem *statusItem;
@property(assign, nonatomic) BOOL updateAvailable;
@property(assign, nonatomic) BOOL systemShutdownInProgress;
@end
@implementation AppDelegate
@@ -40,6 +41,13 @@ bool firstTimeRun,startHidden; // Set in run before initialization
}
- (void)applicationDidFinishLaunching:(NSNotification *)aNotification {
// Register for system shutdown/restart notification so we can allow termination
[[[NSWorkspace sharedWorkspace] notificationCenter]
addObserver:self
selector:@selector(systemWillPowerOff:)
name:NSWorkspaceWillPowerOffNotification
object:nil];
// if we're in development mode, set the app icon
NSString *bundlePath = [[NSBundle mainBundle] bundlePath];
if (![bundlePath hasSuffix:@".app"]) {
@@ -278,7 +286,18 @@ bool firstTimeRun,startHidden; // Set in run before initialization
[NSApp activateIgnoringOtherApps:YES];
}
- (void)systemWillPowerOff:(NSNotification *)notification {
// Set flag so applicationShouldTerminate: knows to allow termination.
// The system will call applicationShouldTerminate: after posting this notification.
self.systemShutdownInProgress = YES;
}
- (NSApplicationTerminateReply)applicationShouldTerminate:(NSApplication *)sender {
// Allow termination if the system is shutting down or restarting
if (self.systemShutdownInProgress) {
return NSTerminateNow;
}
// Otherwise just hide the app (for Cmd+Q, close button, etc.)
[NSApp hide:nil];
[NSApp setActivationPolicy:NSApplicationActivationPolicyAccessory];
return NSTerminateCancel;
+12
View File
@@ -154,6 +154,10 @@ func handleURLSchemeRequest(urlScheme string) {
}
func UpdateAvailable(ver string) error {
if app.t == nil {
slog.Debug("tray not yet initialized, skipping update notification")
return nil
}
return app.t.UpdateAvailable(ver)
}
@@ -165,6 +169,14 @@ func osRun(shutdown func(), hasCompletedFirstRun, startHidden bool) {
log.Fatalf("Failed to start: %s", err)
}
// Check for pending updates now that the tray is initialized.
// The platform-independent check in app.go fires before osRun,
// when app.t is still nil, so we must re-check here.
if updater.IsUpdatePending() {
slog.Debug("update pending on startup, showing tray notification")
UpdateAvailable("")
}
signals := make(chan os.Signal, 1)
signal.Notify(signals, syscall.SIGINT, syscall.SIGTERM)
+4 -49
View File
@@ -90,9 +90,8 @@ DialogFontSize=12
[Files]
#if FileExists("..\dist\windows-ollama-app-amd64.exe")
Source: "..\dist\windows-ollama-app-amd64.exe"; DestDir: "{app}"; DestName: "{#MyAppExeName}" ;Check: not IsArm64(); Flags: ignoreversion 64bit; BeforeInstall: TaskKill('{#MyAppExeName}')
Source: "..\dist\windows-amd64\vc_redist.x64.exe"; DestDir: "{tmp}"; Check: not IsArm64() and vc_redist_needed(); Flags: deleteafterinstall
Source: "..\dist\windows-amd64\ollama.exe"; DestDir: "{app}"; Check: not IsArm64(); Flags: ignoreversion 64bit; BeforeInstall: TaskKill('ollama.exe')
Source: "..\dist\windows-amd64\lib\ollama\*"; DestDir: "{app}\lib\ollama\"; Check: not IsArm64(); Flags: ignoreversion 64bit recursesubdirs
Source: "..\dist\windows-amd64\lib\ollama\*"; Excludes: "\mlx_*\*"; DestDir: "{app}\lib\ollama\"; Check: not IsArm64(); Flags: ignoreversion 64bit recursesubdirs
#endif
; For local development, rely on binary compatibility at runtime since we can't cross compile
@@ -103,9 +102,11 @@ Source: "..\dist\windows-ollama-app-amd64.exe"; DestDir: "{app}"; DestName: "{#M
#endif
#if FileExists("..\dist\windows-arm64\ollama.exe")
Source: "..\dist\windows-arm64\vc_redist.arm64.exe"; DestDir: "{tmp}"; Check: IsArm64() and vc_redist_needed(); Flags: deleteafterinstall
Source: "..\dist\windows-arm64\ollama.exe"; DestDir: "{app}"; Check: IsArm64(); Flags: ignoreversion 64bit; BeforeInstall: TaskKill('ollama.exe')
#endif
#if DirExists("..\dist\windows-arm64\lib\ollama")
Source: "..\dist\windows-arm64\lib\ollama\*"; DestDir: "{app}\lib\ollama\"; Check: IsArm64(); Flags: ignoreversion 64bit recursesubdirs
#endif
Source: ".\assets\app.ico"; DestDir: "{app}"; Flags: ignoreversion
@@ -118,12 +119,6 @@ Name: "{userprograms}\{#MyAppName}"; Filename: "{app}\{#MyAppExeName}"; IconFile
Type: files; Name: "{%LOCALAPPDATA}\Ollama\updates"
[Run]
#if DirExists("..\dist\windows-arm64")
Filename: "{tmp}\vc_redist.arm64.exe"; Parameters: "/install /passive /norestart"; Check: IsArm64() and vc_redist_needed(); StatusMsg: "Installing VC++ Redistributables..."; Flags: waituntilterminated
#endif
#if DirExists("..\dist\windows-amd64")
Filename: "{tmp}\vc_redist.x64.exe"; Parameters: "/install /passive /norestart"; Check: not IsArm64() and vc_redist_needed(); StatusMsg: "Installing VC++ Redistributables..."; Flags: waituntilterminated
#endif
Filename: "{cmd}"; Parameters: "/C set PATH={app};%PATH% & ""{app}\{#MyAppExeName}"""; Flags: postinstall nowait runhidden
[UninstallRun]
@@ -184,46 +179,6 @@ begin
Result := Pos(';' + ExpandConstant(Param) + ';', ';' + OrigPath + ';') = 0;
end;
{ --- VC Runtime libraries discovery code - Only install vc_redist if it isn't already installed ----- }
const VCRTL_MIN_V1 = 14;
const VCRTL_MIN_V2 = 40;
const VCRTL_MIN_V3 = 33807;
const VCRTL_MIN_V4 = 0;
// check if the minimum required vc redist is installed (by looking the registry)
function vc_redist_needed (): Boolean;
var
sRegKey: string;
v1: Cardinal;
v2: Cardinal;
v3: Cardinal;
v4: Cardinal;
begin
if (IsArm64()) then begin
sRegKey := 'SOFTWARE\WOW6432Node\Microsoft\VisualStudio\14.0\VC\Runtimes\arm64';
end else begin
sRegKey := 'SOFTWARE\Microsoft\VisualStudio\14.0\VC\Runtimes\x64';
end;
if (RegQueryDWordValue (HKEY_LOCAL_MACHINE, sRegKey, 'Major', v1) and
RegQueryDWordValue (HKEY_LOCAL_MACHINE, sRegKey, 'Minor', v2) and
RegQueryDWordValue (HKEY_LOCAL_MACHINE, sRegKey, 'Bld', v3) and
RegQueryDWordValue (HKEY_LOCAL_MACHINE, sRegKey, 'RBld', v4)) then
begin
Log ('VC Redist version: ' + IntToStr (v1) +
'.' + IntToStr (v2) + '.' + IntToStr (v3) +
'.' + IntToStr (v4));
{ Version info was found. Return true if later or equal to our
minimal required version RTL_MIN_Vx }
Result := not (
(v1 > VCRTL_MIN_V1) or ((v1 = VCRTL_MIN_V1) and
((v2 > VCRTL_MIN_V2) or ((v2 = VCRTL_MIN_V2) and
((v3 > VCRTL_MIN_V3) or ((v3 = VCRTL_MIN_V3) and
(v4 >= VCRTL_MIN_V4)))))));
end
else
Result := TRUE;
end;
function GetDirSize(Path: String): Int64;
var
FindRec: TFindRec;
+64 -10
View File
@@ -41,6 +41,11 @@ type InferenceCompute struct {
VRAM string
}
type InferenceInfo struct {
Computes []InferenceCompute
DefaultContextLength int
}
func New(s *store.Store, devMode bool) *Server {
p := resolvePath("ollama")
return &Server{store: s, bin: p, dev: devMode}
@@ -78,6 +83,29 @@ func resolvePath(name string) string {
return name
}
func ollamaServeArgs(args []string) bool {
if len(args) < 2 {
return false
}
switch strings.Trim(filepath.Base(args[0]), `"`) {
case "ollama", "ollama.exe":
default:
return false
}
for _, rawArg := range args[1:] {
arg := strings.Trim(rawArg, `"`)
if strings.HasPrefix(arg, "-") {
continue
}
return arg == "serve" || arg == "start"
}
return false
}
// cleanup checks the pid file for a running ollama process
// and shuts it down gracefully if it is running
func cleanup() error {
@@ -205,6 +233,11 @@ func (s *Server) cmd(ctx context.Context) (*exec.Cmd, error) {
return nil, err
}
cloudDisabled, err := s.store.CloudDisabled()
if err != nil {
return nil, err
}
cmd := commandContext(ctx, s.bin, "serve")
cmd.Stdout, cmd.Stderr = s.log, s.log
@@ -230,6 +263,11 @@ func (s *Server) cmd(ctx context.Context) (*exec.Cmd, error) {
if settings.ContextLength > 0 {
env["OLLAMA_CONTEXT_LENGTH"] = strconv.Itoa(settings.ContextLength)
}
if cloudDisabled {
env["OLLAMA_NO_CLOUD"] = "1"
} else {
env["OLLAMA_NO_CLOUD"] = "0"
}
cmd.Env = []string{}
for k, v := range env {
cmd.Env = append(cmd.Env, k+"="+v)
@@ -262,9 +300,12 @@ func openRotatingLog() (io.WriteCloser, error) {
// Attempt to retrieve inference compute information from the server
// log. Set ctx to timeout to control how long to wait for the logs to appear
func GetInferenceComputer(ctx context.Context) ([]InferenceCompute, error) {
inference := []InferenceCompute{}
marker := regexp.MustCompile(`inference compute.*library=`)
func GetInferenceInfo(ctx context.Context) (*InferenceInfo, error) {
info := &InferenceInfo{}
computeMarker := regexp.MustCompile(`inference compute.*library=`)
defaultCtxMarker := regexp.MustCompile(`vram-based default context`)
defaultCtxRegex := regexp.MustCompile(`default_num_ctx=(\d+)`)
q := `inference compute.*%s=["]([^"]*)["]`
nq := `inference compute.*%s=(\S+)\s`
type regex struct {
@@ -330,8 +371,8 @@ func GetInferenceComputer(ctx context.Context) ([]InferenceCompute, error) {
scanner := bufio.NewScanner(file)
for scanner.Scan() {
line := scanner.Text()
match := marker.FindStringSubmatch(line)
if len(match) > 0 {
// Check for inference compute lines
if computeMarker.MatchString(line) {
ic := InferenceCompute{
Library: get("library", line),
Variant: get("variant", line),
@@ -342,12 +383,25 @@ func GetInferenceComputer(ctx context.Context) ([]InferenceCompute, error) {
}
slog.Info("Matched", "inference compute", ic)
inference = append(inference, ic)
} else {
// Break out on first non matching line after we start matching
if len(inference) > 0 {
return inference, nil
info.Computes = append(info.Computes, ic)
continue
}
// Check for default context length line
if defaultCtxMarker.MatchString(line) {
match := defaultCtxRegex.FindStringSubmatch(line)
if len(match) > 1 {
numCtx, err := strconv.Atoi(match[1])
if err == nil {
info.DefaultContextLength = numCtx
slog.Info("Matched default context length", "default_num_ctx", numCtx)
}
}
return info, nil
}
// If we've found compute info but hit a non-matching line, return what we have
// This handles older server versions that don't log the default context line
if len(info.Computes) > 0 {
return info, nil
}
}
time.Sleep(100 * time.Millisecond)
+166 -15
View File
@@ -111,7 +111,7 @@ func TestServerCmd(t *testing.T) {
for _, want := range tt.want {
found := false
for _, env := range cmd.Env {
if strings.Contains(env, want) {
if strings.HasPrefix(env, want) {
found = true
break
}
@@ -123,7 +123,7 @@ func TestServerCmd(t *testing.T) {
for _, dont := range tt.dont {
for _, env := range cmd.Env {
if strings.Contains(env, dont) {
if strings.HasPrefix(env, dont) {
t.Errorf("unexpected environment variable: %s", env)
}
}
@@ -136,44 +136,176 @@ func TestServerCmd(t *testing.T) {
}
}
func TestGetInferenceComputer(t *testing.T) {
func TestServerCmdCloudSettingEnv(t *testing.T) {
tests := []struct {
name string
envValue string
configContent string
want string
}{
{
name: "default cloud enabled",
want: "OLLAMA_NO_CLOUD=0",
},
{
name: "env disables cloud",
envValue: "1",
want: "OLLAMA_NO_CLOUD=1",
},
{
name: "config disables cloud",
configContent: `{"disable_ollama_cloud": true}`,
want: "OLLAMA_NO_CLOUD=1",
},
{
name: "invalid env disables cloud",
envValue: "invalid",
want: "OLLAMA_NO_CLOUD=1",
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
tmpHome := t.TempDir()
t.Setenv("HOME", tmpHome)
t.Setenv("USERPROFILE", tmpHome)
t.Setenv("OLLAMA_NO_CLOUD", tt.envValue)
if tt.configContent != "" {
configDir := filepath.Join(tmpHome, ".ollama")
if err := os.MkdirAll(configDir, 0o755); err != nil {
t.Fatalf("mkdir config dir: %v", err)
}
configPath := filepath.Join(configDir, "server.json")
if err := os.WriteFile(configPath, []byte(tt.configContent), 0o644); err != nil {
t.Fatalf("write config: %v", err)
}
}
st := &store.Store{DBPath: filepath.Join(t.TempDir(), "db.sqlite")}
defer st.Close()
s := &Server{store: st}
cmd, err := s.cmd(t.Context())
if err != nil {
t.Fatalf("s.cmd() error = %v", err)
}
found := false
for _, env := range cmd.Env {
if env == tt.want {
found = true
break
}
}
if !found {
t.Fatalf("expected environment variable %q in command env", tt.want)
}
})
}
}
func TestOllamaServeArgs(t *testing.T) {
tests := []struct {
name string
log string
exp []InferenceCompute
args []string
want bool
}{
{
name: "system ollama serve",
args: []string{"ollama", "serve"},
want: true,
},
{
name: "relative path ollama serve",
args: []string{"./ollama", "serve"},
want: true,
},
{
name: "serve after other flags",
args: []string{"./ollama", "--verbose", "serve"},
want: true,
},
{
name: "start alias",
args: []string{"ollama", "start"},
want: true,
},
{
name: "launch command",
args: []string{"ollama", "launch", "opencode"},
want: false,
},
{
name: "run command with model named serve",
args: []string{"ollama", "run", "serve"},
want: false,
},
{
name: "launch command with serve in passthrough args",
args: []string{"ollama", "launch", "codex", "--", "-p", "serve"},
want: false,
},
{
name: "different executable",
args: []string{"go", "run", "serve"},
want: false,
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
if got := ollamaServeArgs(tt.args); got != tt.want {
t.Fatalf("ollamaServeArgs(%v) = %v, want %v", tt.args, got, tt.want)
}
})
}
}
func TestGetInferenceInfo(t *testing.T) {
tests := []struct {
name string
log string
expComputes []InferenceCompute
expDefaultCtxLen int
}{
{
name: "metal",
log: `time=2025-06-30T09:23:07.374-07:00 level=DEBUG source=sched.go:108 msg="starting llm scheduler"
time=2025-06-30T09:23:07.416-07:00 level=INFO source=types.go:130 msg="inference compute" id=0 library=metal variant="" compute="" driver=0.0 name="" total="96.0 GiB" available="96.0 GiB"
time=2025-06-30T09:23:07.417-07:00 level=INFO source=routes.go:1721 msg="vram-based default context" total_vram="96.0 GiB" default_num_ctx=262144
time=2025-06-30T09:25:56.197-07:00 level=DEBUG source=ggml.go:155 msg="key not found" key=general.alignment default=32
`,
exp: []InferenceCompute{{
expComputes: []InferenceCompute{{
Library: "metal",
Driver: "0.0",
VRAM: "96.0 GiB",
}},
expDefaultCtxLen: 262144,
},
{
name: "cpu",
log: `time=2025-07-01T17:59:51.470Z level=INFO source=gpu.go:377 msg="no compatible GPUs were discovered"
time=2025-07-01T17:59:51.470Z level=INFO source=types.go:130 msg="inference compute" id=0 library=cpu variant="" compute="" driver=0.0 name="" total="31.3 GiB" available="30.4 GiB"
time=2025-07-01T17:59:51.471Z level=INFO source=routes.go:1721 msg="vram-based default context" total_vram="31.3 GiB" default_num_ctx=32768
[GIN] 2025/07/01 - 18:00:09 | 200 | 50.263µs | 100.126.204.152 | HEAD "/"
`,
exp: []InferenceCompute{{
expComputes: []InferenceCompute{{
Library: "cpu",
Driver: "0.0",
VRAM: "31.3 GiB",
}},
expDefaultCtxLen: 32768,
},
{
name: "cuda1",
log: `time=2025-07-01T19:33:43.162Z level=DEBUG source=amd_linux.go:419 msg="amdgpu driver not detected /sys/module/amdgpu"
releasing cuda driver library
time=2025-07-01T19:33:43.162Z level=INFO source=types.go:130 msg="inference compute" id=GPU-452cac9f-6960-839c-4fb3-0cec83699196 library=cuda variant=v12 compute=6.1 driver=12.7 name="NVIDIA GeForce GT 1030" total="3.9 GiB" available="3.9 GiB"
time=2025-07-01T19:33:43.163Z level=INFO source=routes.go:1721 msg="vram-based default context" total_vram="3.9 GiB" default_num_ctx=4096
[GIN] 2025/07/01 - 18:00:09 | 200 | 50.263µs | 100.126.204.152 | HEAD "/"
`,
exp: []InferenceCompute{{
expComputes: []InferenceCompute{{
Library: "cuda",
Variant: "v12",
Compute: "6.1",
@@ -181,6 +313,7 @@ time=2025-07-01T19:33:43.162Z level=INFO source=types.go:130 msg="inference comp
Name: "NVIDIA GeForce GT 1030",
VRAM: "3.9 GiB",
}},
expDefaultCtxLen: 4096,
},
{
name: "frank",
@@ -188,9 +321,10 @@ time=2025-07-01T19:33:43.162Z level=INFO source=types.go:130 msg="inference comp
releasing cuda driver library
time=2025-07-01T19:36:13.315Z level=INFO source=types.go:130 msg="inference compute" id=GPU-d6de3398-9932-6902-11ec-fee8e424c8a2 library=cuda variant=v12 compute=7.5 driver=12.8 name="NVIDIA GeForce RTX 2080 Ti" total="10.6 GiB" available="10.4 GiB"
time=2025-07-01T19:36:13.315Z level=INFO source=types.go:130 msg="inference compute" id=GPU-9abb57639fa80c50 library=rocm variant="" compute=gfx1030 driver=6.3 name=1002:73bf total="16.0 GiB" available="1.3 GiB"
time=2025-07-01T19:36:13.316Z level=INFO source=routes.go:1721 msg="vram-based default context" total_vram="26.6 GiB" default_num_ctx=32768
[GIN] 2025/07/01 - 18:00:09 | 200 | 50.263µs | 100.126.204.152 | HEAD "/"
`,
exp: []InferenceCompute{
expComputes: []InferenceCompute{
{
Library: "cuda",
Variant: "v12",
@@ -207,6 +341,20 @@ time=2025-07-01T19:33:43.162Z level=INFO source=types.go:130 msg="inference comp
VRAM: "16.0 GiB",
},
},
expDefaultCtxLen: 32768,
},
{
name: "missing_default_context",
log: `time=2025-06-30T09:23:07.374-07:00 level=DEBUG source=sched.go:108 msg="starting llm scheduler"
time=2025-06-30T09:23:07.416-07:00 level=INFO source=types.go:130 msg="inference compute" id=0 library=metal variant="" compute="" driver=0.0 name="" total="96.0 GiB" available="96.0 GiB"
time=2025-06-30T09:25:56.197-07:00 level=DEBUG source=ggml.go:155 msg="key not found" key=general.alignment default=32
`,
expComputes: []InferenceCompute{{
Library: "metal",
Driver: "0.0",
VRAM: "96.0 GiB",
}},
expDefaultCtxLen: 0, // No default context line, should return 0
},
}
for _, tt := range tests {
@@ -219,18 +367,21 @@ time=2025-07-01T19:33:43.162Z level=INFO source=types.go:130 msg="inference comp
}
ctx, cancel := context.WithTimeout(t.Context(), 10*time.Millisecond)
defer cancel()
ics, err := GetInferenceComputer(ctx)
info, err := GetInferenceInfo(ctx)
if err != nil {
t.Fatalf(" failed to get inference compute: %v", err)
t.Fatalf("failed to get inference info: %v", err)
}
if !reflect.DeepEqual(ics, tt.exp) {
t.Fatalf("got:\n%#v\nwant:\n%#v", ics, tt.exp)
if !reflect.DeepEqual(info.Computes, tt.expComputes) {
t.Fatalf("computes mismatch\ngot:\n%#v\nwant:\n%#v", info.Computes, tt.expComputes)
}
if info.DefaultContextLength != tt.expDefaultCtxLen {
t.Fatalf("default context length mismatch: got %d, want %d", info.DefaultContextLength, tt.expDefaultCtxLen)
}
})
}
}
func TestGetInferenceComputerTimeout(t *testing.T) {
func TestGetInferenceInfoTimeout(t *testing.T) {
ctx, cancel := context.WithTimeout(t.Context(), 10*time.Millisecond)
defer cancel()
tmpDir := t.TempDir()
@@ -239,7 +390,7 @@ func TestGetInferenceComputerTimeout(t *testing.T) {
if err != nil {
t.Fatalf("failed to write log file %s: %s", serverLogPath, err)
}
_, err = GetInferenceComputer(ctx)
_, err = GetInferenceInfo(ctx)
if err == nil {
t.Fatal("expected timeout")
}
+14 -1
View File
@@ -46,7 +46,17 @@ func terminated(pid int) (bool, error) {
return false, nil
}
// reapServers kills all ollama processes except our own
func ollamaServeProcess(pid int) bool {
output, err := exec.Command("ps", "-p", strconv.Itoa(pid), "-o", "args=").Output()
if err != nil {
slog.Debug("failed to inspect ollama process", "pid", pid, "err", err)
return false
}
return ollamaServeArgs(strings.Fields(strings.TrimSpace(string(output))))
}
// reapServers kills external ollama serve processes except our own.
func reapServers() error {
// Get our own PID to avoid killing ourselves
currentPID := os.Getpid()
@@ -82,6 +92,9 @@ func reapServers() error {
if pid == currentPID {
continue
}
if !ollamaServeProcess(pid) {
continue
}
proc, err := os.FindProcess(pid)
if err != nil {
+26 -1
View File
@@ -101,7 +101,29 @@ func terminated(pid int) (bool, error) {
return true, nil
}
// reapServers kills all ollama processes except our own
func ollamaServeProcess(pid int) bool {
cmd := exec.Command("wmic", "process", "where", fmt.Sprintf("ProcessId=%d", pid), "get", "CommandLine", "/value")
cmd.SysProcAttr = &syscall.SysProcAttr{HideWindow: true}
output, err := cmd.Output()
if err != nil {
slog.Debug("failed to inspect ollama process", "pid", pid, "err", err)
return false
}
for _, line := range strings.Split(string(output), "\n") {
line = strings.TrimSpace(line)
commandLine, ok := strings.CutPrefix(line, "CommandLine=")
if !ok {
continue
}
return ollamaServeArgs(strings.Fields(strings.ToLower(commandLine)))
}
return false
}
// reapServers kills external ollama serve processes except our own.
func reapServers() error {
// Get current process ID to avoid killing ourselves
currentPID := os.Getpid()
@@ -138,6 +160,9 @@ func reapServers() error {
if pid == currentPID {
continue
}
if !ollamaServeProcess(pid) {
continue
}
cmd := exec.Command("taskkill", "/F", "/PID", pidStr)
if err := cmd.Run(); err != nil {
+128
View File
@@ -0,0 +1,128 @@
//go:build windows || darwin
package store
import (
"encoding/json"
"errors"
"fmt"
"os"
"path/filepath"
"github.com/ollama/ollama/envconfig"
)
const serverConfigFilename = "server.json"
type serverConfig struct {
DisableOllamaCloud bool `json:"disable_ollama_cloud,omitempty"`
}
// CloudDisabled returns whether cloud features should be disabled.
// The source of truth is: OLLAMA_NO_CLOUD OR ~/.ollama/server.json:disable_ollama_cloud.
func (s *Store) CloudDisabled() (bool, error) {
disabled, _, err := s.CloudStatus()
return disabled, err
}
// CloudStatus returns whether cloud is disabled and the source of that decision.
// Source is one of: "none", "env", "config", "both".
func (s *Store) CloudStatus() (bool, string, error) {
if err := s.ensureDB(); err != nil {
return false, "", err
}
configDisabled, err := readServerConfigCloudDisabled()
if err != nil {
return false, "", err
}
envDisabled := envconfig.NoCloudEnv()
return envDisabled || configDisabled, cloudStatusSource(envDisabled, configDisabled), nil
}
// SetCloudEnabled writes the cloud setting to ~/.ollama/server.json.
func (s *Store) SetCloudEnabled(enabled bool) error {
if err := s.ensureDB(); err != nil {
return err
}
return setCloudEnabled(enabled)
}
func setCloudEnabled(enabled bool) error {
configPath, err := serverConfigPath()
if err != nil {
return err
}
if err := os.MkdirAll(filepath.Dir(configPath), 0o755); err != nil {
return fmt.Errorf("create server config directory: %w", err)
}
configMap := map[string]any{}
if data, err := os.ReadFile(configPath); err == nil {
if err := json.Unmarshal(data, &configMap); err != nil {
// If the existing file is invalid JSON, overwrite with a fresh object.
configMap = map[string]any{}
}
} else if !errors.Is(err, os.ErrNotExist) {
return fmt.Errorf("read server config: %w", err)
}
configMap["disable_ollama_cloud"] = !enabled
data, err := json.MarshalIndent(configMap, "", " ")
if err != nil {
return fmt.Errorf("marshal server config: %w", err)
}
data = append(data, '\n')
if err := os.WriteFile(configPath, data, 0o644); err != nil {
return fmt.Errorf("write server config: %w", err)
}
return nil
}
func readServerConfigCloudDisabled() (bool, error) {
configPath, err := serverConfigPath()
if err != nil {
return false, err
}
data, err := os.ReadFile(configPath)
if err != nil {
if errors.Is(err, os.ErrNotExist) {
return false, nil
}
return false, fmt.Errorf("read server config: %w", err)
}
var cfg serverConfig
// Invalid or unexpected JSON should not block startup; treat as default.
if json.Unmarshal(data, &cfg) == nil {
return cfg.DisableOllamaCloud, nil
}
return false, nil
}
func serverConfigPath() (string, error) {
home, err := os.UserHomeDir()
if err != nil {
return "", fmt.Errorf("resolve home directory: %w", err)
}
return filepath.Join(home, ".ollama", serverConfigFilename), nil
}
func cloudStatusSource(envDisabled bool, configDisabled bool) string {
switch {
case envDisabled && configDisabled:
return "both"
case envDisabled:
return "env"
case configDisabled:
return "config"
default:
return "none"
}
}
+130
View File
@@ -0,0 +1,130 @@
//go:build windows || darwin
package store
import (
"encoding/json"
"os"
"path/filepath"
"testing"
)
func TestCloudDisabled(t *testing.T) {
tests := []struct {
name string
envValue string
configContent string
wantDisabled bool
wantSource string
}{
{
name: "default enabled",
wantDisabled: false,
wantSource: "none",
},
{
name: "env disables cloud",
envValue: "1",
wantDisabled: true,
wantSource: "env",
},
{
name: "config disables cloud",
configContent: `{"disable_ollama_cloud": true}`,
wantDisabled: true,
wantSource: "config",
},
{
name: "env and config",
envValue: "1",
configContent: `{"disable_ollama_cloud": false}`,
wantDisabled: true,
wantSource: "env",
},
{
name: "invalid config is ignored",
configContent: `{bad`,
wantDisabled: false,
wantSource: "none",
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
tmpHome := t.TempDir()
setTestHome(t, tmpHome)
t.Setenv("OLLAMA_NO_CLOUD", tt.envValue)
if tt.configContent != "" {
configDir := filepath.Join(tmpHome, ".ollama")
if err := os.MkdirAll(configDir, 0o755); err != nil {
t.Fatalf("mkdir config dir: %v", err)
}
configPath := filepath.Join(configDir, serverConfigFilename)
if err := os.WriteFile(configPath, []byte(tt.configContent), 0o644); err != nil {
t.Fatalf("write config: %v", err)
}
}
s := &Store{DBPath: filepath.Join(tmpHome, "db.sqlite")}
defer s.Close()
disabled, err := s.CloudDisabled()
if err != nil {
t.Fatalf("CloudDisabled() error = %v", err)
}
if disabled != tt.wantDisabled {
t.Fatalf("CloudDisabled() = %v, want %v", disabled, tt.wantDisabled)
}
statusDisabled, source, err := s.CloudStatus()
if err != nil {
t.Fatalf("CloudStatus() error = %v", err)
}
if statusDisabled != tt.wantDisabled {
t.Fatalf("CloudStatus() disabled = %v, want %v", statusDisabled, tt.wantDisabled)
}
if source != tt.wantSource {
t.Fatalf("CloudStatus() source = %v, want %v", source, tt.wantSource)
}
})
}
}
func TestSetCloudEnabled(t *testing.T) {
tmpHome := t.TempDir()
setTestHome(t, tmpHome)
configDir := filepath.Join(tmpHome, ".ollama")
if err := os.MkdirAll(configDir, 0o755); err != nil {
t.Fatalf("mkdir config dir: %v", err)
}
configPath := filepath.Join(configDir, serverConfigFilename)
if err := os.WriteFile(configPath, []byte(`{"another_key":"value","disable_ollama_cloud":true}`), 0o644); err != nil {
t.Fatalf("seed config: %v", err)
}
s := &Store{DBPath: filepath.Join(tmpHome, "db.sqlite")}
defer s.Close()
if err := s.SetCloudEnabled(true); err != nil {
t.Fatalf("SetCloudEnabled(true) error = %v", err)
}
data, err := os.ReadFile(configPath)
if err != nil {
t.Fatalf("read config: %v", err)
}
var got map[string]any
if err := json.Unmarshal(data, &got); err != nil {
t.Fatalf("unmarshal config: %v", err)
}
if got["disable_ollama_cloud"] != false {
t.Fatalf("disable_ollama_cloud = %v, want false", got["disable_ollama_cloud"])
}
if got["another_key"] != "value" {
t.Fatalf("another_key = %v, want value", got["another_key"])
}
}
+143 -18
View File
@@ -9,12 +9,12 @@ import (
"strings"
"time"
sqlite3 "github.com/mattn/go-sqlite3"
_ "github.com/mattn/go-sqlite3"
)
// currentSchemaVersion defines the current database schema version.
// Increment this when making schema changes that require migrations.
const currentSchemaVersion = 12
const currentSchemaVersion = 16
// database wraps the SQLite connection.
// SQLite handles its own locking for concurrent access:
@@ -73,7 +73,7 @@ func (db *database) init() error {
agent BOOLEAN NOT NULL DEFAULT 0,
tools BOOLEAN NOT NULL DEFAULT 0,
working_dir TEXT NOT NULL DEFAULT '',
context_length INTEGER NOT NULL DEFAULT 4096,
context_length INTEGER NOT NULL DEFAULT 0,
window_width INTEGER NOT NULL DEFAULT 0,
window_height INTEGER NOT NULL DEFAULT 0,
config_migrated BOOLEAN NOT NULL DEFAULT 0,
@@ -82,9 +82,12 @@ func (db *database) init() error {
websearch_enabled BOOLEAN NOT NULL DEFAULT 0,
selected_model TEXT NOT NULL DEFAULT '',
sidebar_open BOOLEAN NOT NULL DEFAULT 0,
last_home_view TEXT NOT NULL DEFAULT 'launch',
think_enabled BOOLEAN NOT NULL DEFAULT 0,
think_level TEXT NOT NULL DEFAULT '',
cloud_setting_migrated BOOLEAN NOT NULL DEFAULT 0,
remote TEXT NOT NULL DEFAULT '', -- deprecated
auto_update_enabled BOOLEAN NOT NULL DEFAULT 1,
schema_version INTEGER NOT NULL DEFAULT %d
);
@@ -244,6 +247,30 @@ func (db *database) migrate() error {
return fmt.Errorf("migrate v11 to v12: %w", err)
}
version = 12
case 12:
// add cloud_setting_migrated column to settings table
if err := db.migrateV12ToV13(); err != nil {
return fmt.Errorf("migrate v12 to v13: %w", err)
}
version = 13
case 13:
// change default context_length from 4096 to 0 (VRAM-based tiered defaults)
if err := db.migrateV13ToV14(); err != nil {
return fmt.Errorf("migrate v13 to v14: %w", err)
}
version = 14
case 14:
// add auto_update_enabled column to settings table
if err := db.migrateV14ToV15(); err != nil {
return fmt.Errorf("migrate v14 to v15: %w", err)
}
version = 15
case 15:
// add last_home_view column to settings table
if err := db.migrateV15ToV16(); err != nil {
return fmt.Errorf("migrate v15 to v16: %w", err)
}
version = 16
default:
// If we have a version we don't recognize, just set it to current
// This might happen during development
@@ -452,6 +479,67 @@ func (db *database) migrateV11ToV12() error {
return nil
}
// migrateV12ToV13 adds cloud_setting_migrated to settings.
func (db *database) migrateV12ToV13() error {
_, err := db.conn.Exec(`ALTER TABLE settings ADD COLUMN cloud_setting_migrated BOOLEAN NOT NULL DEFAULT 0`)
if err != nil && !duplicateColumnError(err) {
return fmt.Errorf("add cloud_setting_migrated column: %w", err)
}
_, err = db.conn.Exec(`UPDATE settings SET schema_version = 13`)
if err != nil {
return fmt.Errorf("update schema version: %w", err)
}
return nil
}
// migrateV13ToV14 changes the default context_length from 4096 to 0.
// When context_length is 0, the ollama server uses VRAM-based tiered defaults.
func (db *database) migrateV13ToV14() error {
_, err := db.conn.Exec(`UPDATE settings SET context_length = 0 WHERE context_length = 4096`)
if err != nil {
return fmt.Errorf("update context_length default: %w", err)
}
_, err = db.conn.Exec(`UPDATE settings SET schema_version = 14`)
if err != nil {
return fmt.Errorf("update schema version: %w", err)
}
return nil
}
// migrateV14ToV15 adds the auto_update_enabled column to the settings table
func (db *database) migrateV14ToV15() error {
_, err := db.conn.Exec(`ALTER TABLE settings ADD COLUMN auto_update_enabled BOOLEAN NOT NULL DEFAULT 1`)
if err != nil && !duplicateColumnError(err) {
return fmt.Errorf("add auto_update_enabled column: %w", err)
}
_, err = db.conn.Exec(`UPDATE settings SET schema_version = 15`)
if err != nil {
return fmt.Errorf("update schema version: %w", err)
}
return nil
}
// migrateV15ToV16 adds the last_home_view column to the settings table
func (db *database) migrateV15ToV16() error {
_, err := db.conn.Exec(`ALTER TABLE settings ADD COLUMN last_home_view TEXT NOT NULL DEFAULT 'launch'`)
if err != nil && !duplicateColumnError(err) {
return fmt.Errorf("add last_home_view column: %w", err)
}
_, err = db.conn.Exec(`UPDATE settings SET schema_version = 16`)
if err != nil {
return fmt.Errorf("update schema version: %w", err)
}
return nil
}
// cleanupOrphanedData removes orphaned records that may exist due to the foreign key bug
func (db *database) cleanupOrphanedData() error {
_, err := db.conn.Exec(`
@@ -482,19 +570,11 @@ func (db *database) cleanupOrphanedData() error {
}
func duplicateColumnError(err error) bool {
if sqlite3Err, ok := err.(sqlite3.Error); ok {
return sqlite3Err.Code == sqlite3.ErrError &&
strings.Contains(sqlite3Err.Error(), "duplicate column name")
}
return false
return err != nil && strings.Contains(err.Error(), "duplicate column name")
}
func columnNotExists(err error) bool {
if sqlite3Err, ok := err.(sqlite3.Error); ok {
return sqlite3Err.Code == sqlite3.ErrError &&
strings.Contains(sqlite3Err.Error(), "no such column")
}
return false
return err != nil && strings.Contains(err.Error(), "no such column")
}
func (db *database) getAllChats() ([]Chat, error) {
@@ -1108,9 +1188,9 @@ func (db *database) getSettings() (Settings, error) {
var s Settings
err := db.conn.QueryRow(`
SELECT expose, survey, browser, models, agent, tools, working_dir, context_length, airplane_mode, turbo_enabled, websearch_enabled, selected_model, sidebar_open, think_enabled, think_level
SELECT expose, survey, browser, models, agent, tools, working_dir, context_length, turbo_enabled, websearch_enabled, selected_model, sidebar_open, last_home_view, think_enabled, think_level, auto_update_enabled
FROM settings
`).Scan(&s.Expose, &s.Survey, &s.Browser, &s.Models, &s.Agent, &s.Tools, &s.WorkingDir, &s.ContextLength, &s.AirplaneMode, &s.TurboEnabled, &s.WebSearchEnabled, &s.SelectedModel, &s.SidebarOpen, &s.ThinkEnabled, &s.ThinkLevel)
`).Scan(&s.Expose, &s.Survey, &s.Browser, &s.Models, &s.Agent, &s.Tools, &s.WorkingDir, &s.ContextLength, &s.TurboEnabled, &s.WebSearchEnabled, &s.SelectedModel, &s.SidebarOpen, &s.LastHomeView, &s.ThinkEnabled, &s.ThinkLevel, &s.AutoUpdateEnabled)
if err != nil {
return Settings{}, fmt.Errorf("get settings: %w", err)
}
@@ -1119,16 +1199,61 @@ func (db *database) getSettings() (Settings, error) {
}
func (db *database) setSettings(s Settings) error {
lastHomeView := strings.ToLower(strings.TrimSpace(s.LastHomeView))
validLaunchView := map[string]struct{}{
"launch": {},
"openclaw": {},
"claude": {},
"hermes": {},
"codex": {},
"codex-app": {},
"copilot": {},
"opencode": {},
"droid": {},
"pi": {},
}
if lastHomeView != "chat" {
if _, ok := validLaunchView[lastHomeView]; !ok {
lastHomeView = "launch"
}
}
_, err := db.conn.Exec(`
UPDATE settings
SET expose = ?, survey = ?, browser = ?, models = ?, agent = ?, tools = ?, working_dir = ?, context_length = ?, airplane_mode = ?, turbo_enabled = ?, websearch_enabled = ?, selected_model = ?, sidebar_open = ?, think_enabled = ?, think_level = ?
`, s.Expose, s.Survey, s.Browser, s.Models, s.Agent, s.Tools, s.WorkingDir, s.ContextLength, s.AirplaneMode, s.TurboEnabled, s.WebSearchEnabled, s.SelectedModel, s.SidebarOpen, s.ThinkEnabled, s.ThinkLevel)
UPDATE settings
SET expose = ?, survey = ?, browser = ?, models = ?, agent = ?, tools = ?, working_dir = ?, context_length = ?, turbo_enabled = ?, websearch_enabled = ?, selected_model = ?, sidebar_open = ?, last_home_view = ?, think_enabled = ?, think_level = ?, auto_update_enabled = ?
`, s.Expose, s.Survey, s.Browser, s.Models, s.Agent, s.Tools, s.WorkingDir, s.ContextLength, s.TurboEnabled, s.WebSearchEnabled, s.SelectedModel, s.SidebarOpen, lastHomeView, s.ThinkEnabled, s.ThinkLevel, s.AutoUpdateEnabled)
if err != nil {
return fmt.Errorf("set settings: %w", err)
}
return nil
}
func (db *database) isCloudSettingMigrated() (bool, error) {
var migrated bool
err := db.conn.QueryRow("SELECT cloud_setting_migrated FROM settings").Scan(&migrated)
if err != nil {
return false, fmt.Errorf("get cloud setting migration status: %w", err)
}
return migrated, nil
}
func (db *database) setCloudSettingMigrated(migrated bool) error {
_, err := db.conn.Exec("UPDATE settings SET cloud_setting_migrated = ?", migrated)
if err != nil {
return fmt.Errorf("set cloud setting migration status: %w", err)
}
return nil
}
func (db *database) getAirplaneMode() (bool, error) {
var airplaneMode bool
err := db.conn.QueryRow("SELECT airplane_mode FROM settings").Scan(&airplaneMode)
if err != nil {
return false, fmt.Errorf("get airplane_mode: %w", err)
}
return airplaneMode, nil
}
func (db *database) getWindowSize() (int, int, error) {
var width, height int
err := db.conn.QueryRow("SELECT window_width, window_height FROM settings").Scan(&width, &height)
+76
View File
@@ -98,6 +98,82 @@ func TestSchemaMigrations(t *testing.T) {
})
}
func TestMigrationV13ToV14ContextLength(t *testing.T) {
tmpDir := t.TempDir()
dbPath := filepath.Join(tmpDir, "test.db")
db, err := newDatabase(dbPath)
if err != nil {
t.Fatalf("failed to create database: %v", err)
}
defer db.Close()
_, err = db.conn.Exec("UPDATE settings SET context_length = 4096, schema_version = 13")
if err != nil {
t.Fatalf("failed to seed v13 settings row: %v", err)
}
if err := db.migrate(); err != nil {
t.Fatalf("migration from v13 to v14 failed: %v", err)
}
var contextLength int
if err := db.conn.QueryRow("SELECT context_length FROM settings").Scan(&contextLength); err != nil {
t.Fatalf("failed to read context_length: %v", err)
}
if contextLength != 0 {
t.Fatalf("expected context_length to migrate to 0, got %d", contextLength)
}
version, err := db.getSchemaVersion()
if err != nil {
t.Fatalf("failed to get schema version: %v", err)
}
if version != currentSchemaVersion {
t.Fatalf("expected schema version %d, got %d", currentSchemaVersion, version)
}
}
func TestMigrationV15ToV16LastHomeViewDefaultsToLaunch(t *testing.T) {
tmpDir := t.TempDir()
dbPath := filepath.Join(tmpDir, "test.db")
db, err := newDatabase(dbPath)
if err != nil {
t.Fatalf("failed to create database: %v", err)
}
defer db.Close()
if _, err := db.conn.Exec(`
ALTER TABLE settings DROP COLUMN last_home_view;
UPDATE settings SET schema_version = 15;
`); err != nil {
t.Fatalf("failed to seed v15 settings row: %v", err)
}
if err := db.migrate(); err != nil {
t.Fatalf("migration from v15 to v16 failed: %v", err)
}
var lastHomeView string
if err := db.conn.QueryRow("SELECT last_home_view FROM settings").Scan(&lastHomeView); err != nil {
t.Fatalf("failed to read last_home_view: %v", err)
}
if lastHomeView != "launch" {
t.Fatalf("expected last_home_view to default to launch after migration, got %q", lastHomeView)
}
version, err := db.getSchemaVersion()
if err != nil {
t.Fatalf("failed to get schema version: %v", err)
}
if version != currentSchemaVersion {
t.Fatalf("expected schema version %d, got %d", currentSchemaVersion, version)
}
}
func TestChatDeletionWithCascade(t *testing.T) {
t.Run("chat deletion cascades to related messages", func(t *testing.T) {
tmpDir := t.TempDir()
+59
View File
@@ -127,6 +127,65 @@ func TestNoConfigToMigrate(t *testing.T) {
}
}
func TestCloudMigrationFromAirplaneMode(t *testing.T) {
tmpHome := t.TempDir()
setTestHome(t, tmpHome)
t.Setenv("OLLAMA_NO_CLOUD", "")
dbPath := filepath.Join(tmpHome, "db.sqlite")
db, err := newDatabase(dbPath)
if err != nil {
t.Fatalf("failed to create database: %v", err)
}
if _, err := db.conn.Exec("UPDATE settings SET airplane_mode = 1, cloud_setting_migrated = 0"); err != nil {
db.Close()
t.Fatalf("failed to seed airplane migration state: %v", err)
}
db.Close()
s := Store{DBPath: dbPath}
defer s.Close()
// Trigger DB initialization + one-time cloud migration.
if _, err := s.ID(); err != nil {
t.Fatalf("failed to initialize store: %v", err)
}
disabled, err := s.CloudDisabled()
if err != nil {
t.Fatalf("CloudDisabled() error: %v", err)
}
if !disabled {
t.Fatal("expected cloud to be disabled after migrating airplane_mode=true")
}
configPath := filepath.Join(tmpHome, ".ollama", serverConfigFilename)
data, err := os.ReadFile(configPath)
if err != nil {
t.Fatalf("failed to read migrated server config: %v", err)
}
var cfg map[string]any
if err := json.Unmarshal(data, &cfg); err != nil {
t.Fatalf("failed to parse migrated server config: %v", err)
}
if cfg["disable_ollama_cloud"] != true {
t.Fatalf("disable_ollama_cloud = %v, want true", cfg["disable_ollama_cloud"])
}
var airplaneMode, migrated bool
if err := s.db.conn.QueryRow("SELECT airplane_mode, cloud_setting_migrated FROM settings").Scan(&airplaneMode, &migrated); err != nil {
t.Fatalf("failed to read migration flags from DB: %v", err)
}
if !airplaneMode {
t.Fatal("expected legacy airplane_mode value to remain unchanged")
}
if !migrated {
t.Fatal("expected cloud_setting_migrated to be true")
}
}
const (
v1Schema = `
CREATE TABLE IF NOT EXISTS settings (
+44 -3
View File
@@ -149,9 +149,6 @@ type Settings struct {
// ContextLength specifies the context length for the ollama server (using OLLAMA_CONTEXT_LENGTH)
ContextLength int
// AirplaneMode when true, turns off Ollama Turbo features and only uses local models
AirplaneMode bool
// TurboEnabled indicates if Ollama Turbo features are enabled
TurboEnabled bool
@@ -169,6 +166,12 @@ type Settings struct {
// SidebarOpen indicates if the chat sidebar is open
SidebarOpen bool
// LastHomeView stores the preferred home route target ("chat" or integration name)
LastHomeView string
// AutoUpdateEnabled indicates if automatic updates should be downloaded
AutoUpdateEnabled bool
}
type Store struct {
@@ -259,6 +262,40 @@ func (s *Store) ensureDB() error {
}
}
// Run one-time migration from legacy airplane_mode behavior.
if err := s.migrateCloudSetting(database); err != nil {
return fmt.Errorf("migrate cloud setting: %w", err)
}
return nil
}
// migrateCloudSetting migrates legacy airplane_mode into server.json exactly once.
// After this, cloud state is sourced from server.json OR OLLAMA_NO_CLOUD.
func (s *Store) migrateCloudSetting(database *database) error {
migrated, err := database.isCloudSettingMigrated()
if err != nil {
return err
}
if migrated {
return nil
}
airplaneMode, err := database.getAirplaneMode()
if err != nil {
return err
}
if airplaneMode {
if err := setCloudEnabled(false); err != nil {
return fmt.Errorf("migrate airplane_mode to cloud disabled: %w", err)
}
}
if err := database.setCloudSettingMigrated(true); err != nil {
return err
}
return nil
}
@@ -355,6 +392,10 @@ func (s *Store) Settings() (Settings, error) {
}
}
if settings.LastHomeView == "" {
settings.LastHomeView = "launch"
}
return settings, nil
}
+56
View File
@@ -81,6 +81,62 @@ func TestStore(t *testing.T) {
}
})
t.Run("settings default home view is launch", func(t *testing.T) {
loaded, err := s.Settings()
if err != nil {
t.Fatal(err)
}
if loaded.LastHomeView != "launch" {
t.Fatalf("expected default LastHomeView to be launch, got %q", loaded.LastHomeView)
}
})
t.Run("settings empty home view falls back to launch", func(t *testing.T) {
if err := s.SetSettings(Settings{LastHomeView: ""}); err != nil {
t.Fatal(err)
}
loaded, err := s.Settings()
if err != nil {
t.Fatal(err)
}
if loaded.LastHomeView != "launch" {
t.Fatalf("expected empty LastHomeView to fall back to launch, got %q", loaded.LastHomeView)
}
})
t.Run("settings disabled home view falls back to launch", func(t *testing.T) {
if err := s.SetSettings(Settings{LastHomeView: "claude-desktop"}); err != nil {
t.Fatal(err)
}
loaded, err := s.Settings()
if err != nil {
t.Fatal(err)
}
if loaded.LastHomeView != "launch" {
t.Fatalf("expected disabled LastHomeView to fall back to launch, got %q", loaded.LastHomeView)
}
})
t.Run("settings codex app home view is accepted", func(t *testing.T) {
if err := s.SetSettings(Settings{LastHomeView: "codex-app"}); err != nil {
t.Fatal(err)
}
loaded, err := s.Settings()
if err != nil {
t.Fatal(err)
}
if loaded.LastHomeView != "codex-app" {
t.Fatalf("expected codex-app LastHomeView to be preserved, got %q", loaded.LastHomeView)
}
})
t.Run("window size", func(t *testing.T) {
if err := s.SetWindowSize(1024, 768); err != nil {
t.Fatal(err)
+11
View File
@@ -0,0 +1,11 @@
//go:build windows || darwin
package store
import "testing"
func setTestHome(t *testing.T, home string) {
t.Helper()
t.Setenv("HOME", home)
t.Setenv("USERPROFILE", home)
}
+1 -1
View File
@@ -13,7 +13,7 @@ CREATE TABLE IF NOT EXISTS settings (
agent BOOLEAN NOT NULL DEFAULT 0,
tools BOOLEAN NOT NULL DEFAULT 0,
working_dir TEXT NOT NULL DEFAULT '',
context_length INTEGER NOT NULL DEFAULT 4096,
context_length INTEGER NOT NULL DEFAULT 0,
window_width INTEGER NOT NULL DEFAULT 0,
window_height INTEGER NOT NULL DEFAULT 0,
config_migrated BOOLEAN NOT NULL DEFAULT 0,
+35
View File
@@ -0,0 +1,35 @@
//go:build windows || darwin
package tools
import (
"context"
"errors"
"github.com/ollama/ollama/api"
internalcloud "github.com/ollama/ollama/internal/cloud"
)
// ensureCloudEnabledForTool checks cloud policy from the connected Ollama server.
// If policy cannot be determined, this fails closed and blocks the operation.
func ensureCloudEnabledForTool(ctx context.Context, operation string) error {
// Reuse shared message formatting; policy evaluation is still done via
// the connected server's /api/status endpoint below.
disabledMessage := internalcloud.DisabledError(operation)
client, err := api.ClientFromEnvironment()
if err != nil {
return errors.New(disabledMessage + " (unable to verify server cloud policy)")
}
status, err := client.CloudStatusExperimental(ctx)
if err != nil {
return errors.New(disabledMessage + " (unable to verify server cloud policy)")
}
if status.Cloud.Disabled {
return errors.New(disabledMessage)
}
return nil
}
+73
View File
@@ -0,0 +1,73 @@
//go:build windows || darwin
package tools
import (
"context"
"net/http"
"net/http/httptest"
"strings"
"testing"
)
func TestEnsureCloudEnabledForTool(t *testing.T) {
const op = "web search is unavailable"
const disabledPrefix = "ollama cloud is disabled: web search is unavailable"
t.Run("enabled allows tool execution", func(t *testing.T) {
ts := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
if r.URL.Path != "/api/status" {
http.NotFound(w, r)
return
}
w.Header().Set("Content-Type", "application/json")
_, _ = w.Write([]byte(`{"cloud":{"disabled":false,"source":"none"}}`))
}))
t.Cleanup(ts.Close)
t.Setenv("OLLAMA_HOST", ts.URL)
if err := ensureCloudEnabledForTool(context.Background(), op); err != nil {
t.Fatalf("expected nil error, got %v", err)
}
})
t.Run("disabled blocks tool execution", func(t *testing.T) {
ts := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
if r.URL.Path != "/api/status" {
http.NotFound(w, r)
return
}
w.Header().Set("Content-Type", "application/json")
_, _ = w.Write([]byte(`{"cloud":{"disabled":true,"source":"config"}}`))
}))
t.Cleanup(ts.Close)
t.Setenv("OLLAMA_HOST", ts.URL)
err := ensureCloudEnabledForTool(context.Background(), op)
if err == nil {
t.Fatal("expected error, got nil")
}
if got := err.Error(); got != disabledPrefix {
t.Fatalf("unexpected error: %q", got)
}
})
t.Run("status unavailable fails closed", func(t *testing.T) {
ts := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
http.NotFound(w, r)
}))
t.Cleanup(ts.Close)
t.Setenv("OLLAMA_HOST", ts.URL)
err := ensureCloudEnabledForTool(context.Background(), op)
if err == nil {
t.Fatal("expected error, got nil")
}
if got := err.Error(); !strings.Contains(got, disabledPrefix) {
t.Fatalf("expected disabled prefix, got %q", got)
}
if got := err.Error(); !strings.Contains(got, "unable to verify server cloud policy") {
t.Fatalf("expected verification failure detail, got %q", got)
}
})
}
+4
View File
@@ -77,6 +77,10 @@ func (w *WebFetch) Execute(ctx context.Context, args map[string]any) (any, strin
}
func performWebFetch(ctx context.Context, targetURL string) (*FetchResponse, error) {
if err := ensureCloudEnabledForTool(ctx, "web fetch is unavailable"); err != nil {
return nil, err
}
reqBody := FetchRequest{URL: targetURL}
jsonBody, err := json.Marshal(reqBody)
if err != nil {
+4
View File
@@ -93,6 +93,10 @@ func (w *WebSearch) Execute(ctx context.Context, args map[string]any) (any, stri
}
func performWebSearch(ctx context.Context, query string, maxResults int) (*SearchResponse, error) {
if err := ensureCloudEnabledForTool(ctx, "web search is unavailable"); err != nil {
return nil, err
}
reqBody := SearchRequest{Query: query, MaxResults: maxResults}
jsonBody, err := json.Marshal(reqBody)
+8 -6
View File
@@ -289,10 +289,12 @@ export class InferenceCompute {
}
export class InferenceComputeResponse {
inferenceComputes: InferenceCompute[];
defaultContextLength: number;
constructor(source: any = {}) {
if ('string' === typeof source) source = JSON.parse(source);
this.inferenceComputes = this.convertValues(source["inferenceComputes"], InferenceCompute);
this.defaultContextLength = source["defaultContextLength"];
}
convertValues(a: any, classs: any, asMap: boolean = false): any {
@@ -406,13 +408,14 @@ export class Settings {
Tools: boolean;
WorkingDir: string;
ContextLength: number;
AirplaneMode: boolean;
TurboEnabled: boolean;
WebSearchEnabled: boolean;
ThinkEnabled: boolean;
ThinkLevel: string;
SelectedModel: string;
SidebarOpen: boolean;
LastHomeView: string;
AutoUpdateEnabled: boolean;
constructor(source: any = {}) {
if ('string' === typeof source) source = JSON.parse(source);
@@ -424,13 +427,14 @@ export class Settings {
this.Tools = source["Tools"];
this.WorkingDir = source["WorkingDir"];
this.ContextLength = source["ContextLength"];
this.AirplaneMode = source["AirplaneMode"];
this.TurboEnabled = source["TurboEnabled"];
this.WebSearchEnabled = source["WebSearchEnabled"];
this.ThinkEnabled = source["ThinkEnabled"];
this.ThinkLevel = source["ThinkLevel"];
this.SelectedModel = source["SelectedModel"];
this.SidebarOpen = source["SidebarOpen"];
this.LastHomeView = source["LastHomeView"];
this.AutoUpdateEnabled = source["AutoUpdateEnabled"];
}
}
export class SettingsResponse {
@@ -548,14 +552,12 @@ export class Error {
}
}
export class ModelUpstreamResponse {
digest?: string;
pushTime: number;
stale: boolean;
error?: string;
constructor(source: any = {}) {
if ('string' === typeof source) source = JSON.parse(source);
this.digest = source["digest"];
this.pushTime = source["pushTime"];
this.stale = source["stale"];
this.error = source["error"];
}
}
@@ -0,0 +1 @@
<svg height="1em" style="flex:none;line-height:1" viewBox="0 0 24 24" width="1em" xmlns="http://www.w3.org/2000/svg"><title>Claude Code</title><path clip-rule="evenodd" d="M20.998 10.949H24v3.102h-3v3.028h-1.487V20H18v-2.921h-1.487V20H15v-2.921H9V20H7.488v-2.921H6V20H4.487v-2.921H3V14.05H0V10.95h3V5h17.998v5.949zM6 10.949h1.488V8.102H6v2.847zm10.51 0H18V8.102h-1.49v2.847z" fill="#D97757" fill-rule="evenodd"></path></svg>

After

Width:  |  Height:  |  Size: 424 B

@@ -0,0 +1,7 @@
<?xml version="1.0" encoding="UTF-8"?>
<!-- Generated by Pixelmator Pro 3.6.17 -->
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<rect width="512" height="512" fill="#131010"></rect>
<path d="M320 224V352H192V224H320Z" fill="#5A5858"></path>
<path fill-rule="evenodd" clip-rule="evenodd" d="M384 416H128V96H384V416ZM320 160H192V352H320V160Z" fill="white"></path>
</svg><style>@media (prefers-color-scheme: light) { :root { filter: none; } }
@media (prefers-color-scheme: dark) { :root { filter: none; } }
</style></svg>

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@@ -0,0 +1,9 @@
<?xml version="1.0" encoding="UTF-8"?>
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 800 800">
<rect width="800" height="800" rx="160" fill="#fff"/>
<path fill="#000" fill-rule="evenodd" d="
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M282.65 282.65 V400 H400 V282.65 Z
"/>
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</svg>

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+9
View File
@@ -0,0 +1,9 @@
<?xml version="1.0" encoding="UTF-8"?>
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 800 800">
<rect width="800" height="800" rx="160" fill="#000"/>
<path fill="#fff" fill-rule="evenodd" d="
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M282.65 282.65 V400 H400 V282.65 Z
"/>
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</svg>

After

Width:  |  Height:  |  Size: 389 B

+76 -12
View File
@@ -4,7 +4,6 @@ import {
ChatEvent,
DownloadEvent,
ErrorEvent,
InferenceCompute,
InferenceComputeResponse,
ModelCapabilitiesResponse,
Model,
@@ -27,6 +26,12 @@ declare module "@/gotypes" {
Model.prototype.isCloud = function (): boolean {
return this.model.endsWith("cloud");
};
export type CloudStatusSource = "env" | "config" | "both" | "none";
export interface CloudStatusResponse {
disabled: boolean;
source: CloudStatusSource;
}
// Helper function to convert Uint8Array to base64
function uint8ArrayToBase64(uint8Array: Uint8Array): string {
const chunkSize = 0x8000; // 32KB chunks to avoid stack overflow
@@ -156,7 +161,7 @@ export async function getModels(query?: string): Promise<Model[]> {
// Add query if it's in the registry and not already in the list
if (!exactMatch) {
const result = await getModelUpstreamInfo(new Model({ model: query }));
const existsUpstream = !!result.digest && !result.error;
const existsUpstream = result.exists;
if (existsUpstream) {
filteredModels.push(new Model({ model: query }));
}
@@ -285,6 +290,28 @@ export async function updateSettings(settings: Settings): Promise<{
};
}
export async function updateCloudSetting(
enabled: boolean,
): Promise<CloudStatusResponse> {
const response = await fetch(`${API_BASE}/api/v1/cloud`, {
method: "POST",
headers: {
"Content-Type": "application/json",
},
body: JSON.stringify({ enabled }),
});
if (!response.ok) {
const error = await response.text();
throw new Error(error || "Failed to update cloud setting");
}
const data = await response.json();
return {
disabled: Boolean(data.disabled),
source: (data.source as CloudStatusSource) || "none",
};
}
export async function renameChat(chatId: string, title: string): Promise<void> {
const response = await fetch(`${API_BASE}/api/v1/chat/${chatId}/rename`, {
method: "PUT",
@@ -312,7 +339,7 @@ export async function deleteChat(chatId: string): Promise<void> {
// Get upstream information for model staleness checking
export async function getModelUpstreamInfo(
model: Model,
): Promise<{ digest?: string; pushTime: number; error?: string }> {
): Promise<{ stale: boolean; exists: boolean; error?: string }> {
try {
const response = await fetch(`${API_BASE}/api/v1/model/upstream`, {
method: "POST",
@@ -326,22 +353,22 @@ export async function getModelUpstreamInfo(
if (!response.ok) {
console.warn(
`Failed to check upstream digest for ${model.model}: ${response.status}`,
`Failed to check upstream for ${model.model}: ${response.status}`,
);
return { pushTime: 0 };
return { stale: false, exists: false };
}
const data = await response.json();
if (data.error) {
console.warn(`Upstream digest check: ${data.error}`);
return { error: data.error, pushTime: 0 };
console.warn(`Upstream check: ${data.error}`);
return { stale: false, exists: false, error: data.error };
}
return { digest: data.digest, pushTime: data.pushTime || 0 };
return { stale: !!data.stale, exists: true };
} catch (error) {
console.warn(`Error checking model staleness:`, error);
return { pushTime: 0 };
return { stale: false, exists: false };
}
}
@@ -379,7 +406,32 @@ export async function* pullModel(
}
}
export async function getInferenceCompute(): Promise<InferenceCompute[]> {
export interface ModelRecommendation {
model: string;
description: string;
context_length?: number;
max_output_tokens?: number;
vram_bytes?: number;
}
export interface ModelRecommendationsResponse {
recommendations: ModelRecommendation[];
}
export async function getModelRecommendations(): Promise<ModelRecommendation[]> {
const response = await fetch(
`${API_BASE}/api/experimental/model-recommendations`,
);
if (!response.ok) {
throw new Error(
`Failed to fetch model recommendations: ${response.statusText}`,
);
}
const data: ModelRecommendationsResponse = await response.json();
return data.recommendations || [];
}
export async function getInferenceCompute(): Promise<InferenceComputeResponse> {
const response = await fetch(`${API_BASE}/api/v1/inference-compute`);
if (!response.ok) {
throw new Error(
@@ -388,8 +440,7 @@ export async function getInferenceCompute(): Promise<InferenceCompute[]> {
}
const data = await response.json();
const inferenceComputeResponse = new InferenceComputeResponse(data);
return inferenceComputeResponse.inferenceComputes || [];
return new InferenceComputeResponse(data);
}
export async function fetchHealth(): Promise<boolean> {
@@ -414,3 +465,16 @@ export async function fetchHealth(): Promise<boolean> {
return false;
}
}
export async function getCloudStatus(): Promise<CloudStatusResponse | null> {
const response = await fetch(`${API_BASE}/api/v1/cloud`);
if (!response.ok) {
throw new Error(`Failed to fetch cloud status: ${response.status}`);
}
const data = await response.json();
return {
disabled: Boolean(data.disabled),
source: (data.source as CloudStatusSource) || "none",
};
}
+57 -28
View File
@@ -17,11 +17,15 @@ import {
} from "@/hooks/useChats";
import { useNavigate } from "@tanstack/react-router";
import { useSelectedModel } from "@/hooks/useSelectedModel";
import { useHasVisionCapability } from "@/hooks/useModelCapabilities";
import {
useHasVisionCapability,
useHasToolsCapability,
} from "@/hooks/useModelCapabilities";
import { useUser } from "@/hooks/useUser";
import { DisplayLogin } from "@/components/DisplayLogin";
import { ErrorEvent, Message } from "@/gotypes";
import { useSettings } from "@/hooks/useSettings";
import { useCloudStatus } from "@/hooks/useCloudStatus";
import { ThinkButton } from "./ThinkButton";
import { ErrorMessage } from "./ErrorMessage";
import { processFiles } from "@/utils/fileValidation";
@@ -141,19 +145,14 @@ function ChatForm({
const {
settings: {
webSearchEnabled,
airplaneMode,
thinkEnabled,
thinkLevel: settingsThinkLevel,
},
setSettings,
} = useSettings();
const { cloudDisabled } = useCloudStatus();
// current supported models for web search
const modelLower = selectedModel?.model.toLowerCase() || "";
const supportsWebSearch =
modelLower.startsWith("gpt-oss") ||
modelLower.startsWith("qwen3") ||
modelLower.startsWith("deepseek-v3");
const supportsWebSearch = useHasToolsCapability(selectedModel?.model);
// Use per-chat thinking level instead of global
const thinkLevel: ThinkingLevel =
settingsThinkLevel === "none" || !settingsThinkLevel
@@ -180,6 +179,12 @@ function ChatForm({
setSettings,
]);
useEffect(() => {
if (cloudDisabled && webSearchEnabled) {
setSettings({ WebSearchEnabled: false });
}
}, [cloudDisabled, webSearchEnabled, setSettings]);
const removeFile = (index: number) => {
setMessage((prev) => ({
...prev,
@@ -234,19 +239,19 @@ function ChatForm({
// Determine if login banner should be shown
const shouldShowLoginBanner =
!cloudDisabled &&
!isLoadingUser &&
!isAuthenticated &&
((webSearchEnabled && supportsWebSearch) ||
(selectedModel?.isCloud() && !airplaneMode));
((webSearchEnabled && supportsWebSearch) || selectedModel?.isCloud());
// Determine which feature to highlight in the banner
const getActiveFeatureForBanner = () => {
if (cloudDisabled) return null;
if (!isAuthenticated) {
if (loginPromptFeature) return loginPromptFeature;
if (webSearchEnabled && selectedModel?.isCloud() && !airplaneMode)
return "webSearch";
if (webSearchEnabled && selectedModel?.isCloud()) return "webSearch";
if (webSearchEnabled) return "webSearch";
if (selectedModel?.isCloud() && !airplaneMode) return "turbo";
if (selectedModel?.isCloud()) return "turbo";
}
return null;
};
@@ -269,11 +274,12 @@ function ChatForm({
useEffect(() => {
if (
isAuthenticated ||
(!webSearchEnabled && !!selectedModel?.isCloud() && !airplaneMode)
cloudDisabled ||
(!webSearchEnabled && !!selectedModel?.isCloud())
) {
setLoginPromptFeature(null);
}
}, [isAuthenticated, webSearchEnabled, selectedModel, airplaneMode]);
}, [isAuthenticated, webSearchEnabled, selectedModel, cloudDisabled]);
// When entering edit mode, populate the composition with existing data
useEffect(() => {
@@ -465,20 +471,27 @@ function ChatForm({
const handleSubmit = async () => {
if (!message.content.trim() || isStreaming || isDownloading) return;
if (cloudDisabled && selectedModel?.isCloud()) {
return;
}
// Check if cloud mode is enabled but user is not authenticated
if (shouldShowLoginBanner) {
return;
}
// Prepare attachments for submission
const attachmentsToSend: FileAttachment[] = message.attachments.map(
(att) => ({
// Prepare attachments for submission, excluding unsupported images
const attachmentsToSend: FileAttachment[] = message.attachments
.filter(
(att) => hasVisionCapability || !isImageFile(att.filename),
)
.map((att) => ({
filename: att.filename,
data: att.data || new Uint8Array(0), // Empty data for existing files
}),
);
}));
const useWebSearch = supportsWebSearch && webSearchEnabled && !airplaneMode;
const useWebSearch =
supportsWebSearch && webSearchEnabled && !cloudDisabled;
const useThink = modelSupportsThinkingLevels
? thinkLevel
: supportsThinkToggling
@@ -725,10 +738,17 @@ function ChatForm({
)}
{(message.attachments.length > 0 || message.fileErrors.length > 0) && (
<div className="flex gap-2 overflow-x-auto px-3 pt pb-3 w-full scrollbar-hide">
{message.attachments.map((attachment, index) => (
{message.attachments.map((attachment, index) => {
const isUnsupportedImage =
!hasVisionCapability && isImageFile(attachment.filename);
return (
<div
key={attachment.id}
className="group flex items-center gap-2 py-2 px-3 rounded-lg bg-neutral-50 dark:bg-neutral-700/50 hover:bg-neutral-100 dark:hover:bg-neutral-700 transition-colors flex-shrink-0"
className={`group flex items-center gap-2 py-2 px-3 rounded-lg transition-colors flex-shrink-0 ${
isUnsupportedImage
? "bg-red-50 dark:bg-red-900/20 border border-red-200 dark:border-red-800"
: "bg-neutral-50 dark:bg-neutral-700/50 hover:bg-neutral-100 dark:hover:bg-neutral-700"
}`}
>
{isImageFile(attachment.filename) ? (
<ImageThumbnail
@@ -753,9 +773,16 @@ function ChatForm({
/>
</svg>
)}
<span className="text-sm text-neutral-700 dark:text-neutral-300 max-w-[150px] truncate">
{attachment.filename}
</span>
<div className="flex flex-col min-w-0">
<span className={`text-sm max-w-36 truncate ${isUnsupportedImage ? "text-red-700 dark:text-red-300" : "text-neutral-700 dark:text-neutral-300"}`}>
{attachment.filename}
</span>
{isUnsupportedImage && (
<span className="text-xs text-red-600 dark:text-red-400 opacity-75">
This model does not support images
</span>
)}
</div>
<button
type="button"
onClick={() => removeFile(index)}
@@ -777,7 +804,8 @@ function ChatForm({
</svg>
</button>
</div>
))}
);
})}
{message.fileErrors.map((fileError, index) => (
<div
key={`error-${index}`}
@@ -899,7 +927,7 @@ function ChatForm({
)}
<WebSearchButton
ref={webSearchButtonRef}
isVisible={supportsWebSearch && airplaneMode === false}
isVisible={supportsWebSearch && cloudDisabled === false}
isActive={webSearchEnabled}
onToggle={() => {
if (!webSearchEnabled && !isAuthenticated) {
@@ -940,6 +968,7 @@ function ChatForm({
!isDownloading &&
(!message.content.trim() ||
shouldShowLoginBanner ||
(cloudDisabled && selectedModel?.isCloud()) ||
message.fileErrors.length > 0)
}
className={`flex items-center justify-center h-9 w-9 rounded-full disabled:cursor-default cursor-pointer bg-black text-white dark:bg-white dark:text-black disabled:opacity-10 focus:outline-none focus:ring-2 focus:ring-blue-500`}
+27 -11
View File
@@ -6,12 +6,13 @@ import { getChat } from "@/api";
import { Link } from "@/components/ui/link";
import { useState, useRef, useEffect, useCallback, useMemo } from "react";
import { ChatsResponse } from "@/gotypes";
import { CogIcon } from "@heroicons/react/24/outline";
import { CogIcon, RocketLaunchIcon } from "@heroicons/react/24/outline";
// there's a hidden debug feature to copy a chat's data to the clipboard by
// holding shift and clicking this many times within this many seconds
const DEBUG_SHIFT_CLICKS_REQUIRED = 5;
const DEBUG_SHIFT_CLICK_WINDOW_MS = 7000; // 7 seconds
const launchSidebarRequestedKey = "ollama.launchSidebarRequested";
interface ChatSidebarProps {
currentChatId?: string;
@@ -267,9 +268,8 @@ export function ChatSidebar({ currentChatId }: ChatSidebarProps) {
<Link
href="/c/new"
mask={{ to: "/" }}
className={`flex w-full items-center gap-3 rounded-lg px-2 py-2 text-left text-sm text-neutral-700 hover:bg-neutral-100 dark:hover:bg-neutral-800 dark:text-neutral-100 ${
currentChatId === "new" ? "bg-neutral-100 dark:bg-neutral-800" : ""
}`}
className={`flex w-full items-center gap-3 rounded-lg px-2 py-2 text-left text-sm text-neutral-700 hover:bg-neutral-100 dark:hover:bg-neutral-800 dark:text-neutral-100 ${currentChatId === "new" ? "bg-neutral-100 dark:bg-neutral-800" : ""
}`}
draggable={false}
>
<svg
@@ -283,6 +283,23 @@ export function ChatSidebar({ currentChatId }: ChatSidebarProps) {
</svg>
<span className="truncate">New Chat</span>
</Link>
<Link
to="/c/$chatId"
params={{ chatId: "launch" }}
onClick={() => {
if (currentChatId !== "launch") {
sessionStorage.setItem(launchSidebarRequestedKey, "1");
}
}}
className={`flex w-full items-center gap-3 rounded-lg px-2 py-2 text-left text-sm text-neutral-700 hover:bg-neutral-100 dark:hover:bg-neutral-800 dark:text-neutral-100 cursor-pointer ${currentChatId === "launch"
? "bg-neutral-100 dark:bg-neutral-800"
: ""
}`}
draggable={false}
>
<RocketLaunchIcon className="h-5 w-5 stroke-current" />
<span className="truncate">Launch</span>
</Link>
{isWindows && (
<Link
href="/settings"
@@ -304,19 +321,18 @@ export function ChatSidebar({ currentChatId }: ChatSidebarProps) {
{group.chats.map((chat) => (
<div
key={chat.id}
className={`allow-context-menu flex items-center relative text-sm text-neutral-800 dark:text-neutral-400 rounded-lg hover:bg-neutral-100 dark:hover:bg-neutral-800 ${
chat.id === currentChatId
? "bg-neutral-100 text-black dark:bg-neutral-800"
: ""
}`}
className={`allow-context-menu flex items-center relative text-sm text-neutral-800 dark:text-neutral-400 rounded-lg hover:bg-neutral-100 dark:hover:bg-neutral-800 ${chat.id === currentChatId
? "bg-neutral-100 text-black dark:bg-neutral-800"
: ""
}`}
onMouseEnter={() => handleMouseEnter(chat.id)}
onContextMenu={(e) =>
handleContextMenu(
e,
chat.id,
chat.title ||
chat.userExcerpt ||
chat.createdAt.toLocaleString(),
chat.userExcerpt ||
chat.createdAt.toLocaleString(),
)
}
>
+4
View File
@@ -10,6 +10,7 @@ interface CopyButtonProps {
showLabels?: boolean;
className?: string;
title?: string;
onCopy?: () => void;
}
const CopyButton: React.FC<CopyButtonProps> = ({
@@ -20,6 +21,7 @@ const CopyButton: React.FC<CopyButtonProps> = ({
showLabels = false,
className = "",
title = "",
onCopy,
}) => {
const [isCopied, setIsCopied] = useState(false);
@@ -48,12 +50,14 @@ const CopyButton: React.FC<CopyButtonProps> = ({
}
setIsCopied(true);
onCopy?.();
setTimeout(() => setIsCopied(false), 2000);
} catch (error) {
console.error("Clipboard API failed, falling back to plain text", error);
try {
await navigator.clipboard.writeText(content);
setIsCopied(true);
onCopy?.();
setTimeout(() => setIsCopied(false), 2000);
} catch (fallbackError) {
console.error("Fallback copy also failed:", fallbackError);
@@ -0,0 +1,158 @@
import { useSettings } from "@/hooks/useSettings";
import CopyButton from "@/components/CopyButton";
interface LaunchCommand {
id: string;
name: string;
command: string;
description: string;
icon: string;
darkIcon?: string;
iconClassName?: string;
borderless?: boolean;
}
const LAUNCH_COMMANDS: LaunchCommand[] = [
{
id: "claude",
name: "Claude Code",
command: "ollama launch claude",
description: "Anthropic's coding tool with subagents",
icon: "/launch-icons/claude-code.svg",
iconClassName: "h-7 w-7",
},
{
id: "codex-app",
name: "Codex App",
command: "ollama launch codex-app",
description: "An AI agent you can delegate real work to, by OpenAI",
icon: "/launch-icons/codex-app.png",
iconClassName: "h-full w-full",
},
{
id: "hermes",
name: "Hermes Agent",
command: "ollama launch hermes",
description: "Self-improving AI agent built by Nous Research",
icon: "/launch-icons/hermes-agent.svg",
iconClassName: "h-7 w-7",
},
{
id: "openclaw",
name: "OpenClaw",
command: "ollama launch openclaw",
description: "Personal AI with 100+ skills",
icon: "/launch-icons/openclaw.svg",
},
{
id: "opencode",
name: "OpenCode",
command: "ollama launch opencode",
description: "Anomaly's open-source coding agent",
icon: "/launch-icons/opencode.svg",
iconClassName: "h-7 w-7 rounded",
},
{
id: "codex",
name: "Codex",
command: "ollama launch codex",
description: "OpenAI's open-source coding agent",
icon: "/launch-icons/codex.svg",
darkIcon: "/launch-icons/codex-dark.svg",
iconClassName: "h-7 w-7",
},
{
id: "copilot",
name: "Copilot CLI",
command: "ollama launch copilot",
description: "GitHub's AI coding agent for the terminal",
icon: "/launch-icons/copilot.svg",
darkIcon: "/launch-icons/copilot-dark.svg",
iconClassName: "h-7 w-7",
},
{
id: "droid",
name: "Droid",
command: "ollama launch droid",
description: "Factory's coding agent across terminal and IDEs",
icon: "/launch-icons/droid.svg",
},
{
id: "pi",
name: "Pi",
command: "ollama launch pi",
description: "Minimal AI agent toolkit with plugin support",
icon: "/launch-icons/pi.svg",
darkIcon: "/launch-icons/pi-dark.svg",
iconClassName: "h-7 w-7",
},
];
export default function LaunchCommands() {
const isWindows = navigator.platform.toLowerCase().includes("win");
const { setSettings } = useSettings();
const renderCommandCard = (item: LaunchCommand) => (
<div key={item.command} className="w-full text-left">
<div className="flex items-start gap-4 sm:gap-5">
<div
aria-hidden="true"
className={`flex h-10 w-10 shrink-0 items-center justify-center rounded-lg overflow-hidden ${item.borderless ? "" : "border border-neutral-200 bg-white dark:border-neutral-700 dark:bg-neutral-900"}`}
>
{item.darkIcon ? (
<picture>
<source srcSet={item.darkIcon} media="(prefers-color-scheme: dark)" />
<img src={item.icon} alt="" className={`${item.iconClassName ?? "h-8 w-8"} rounded-sm`} />
</picture>
) : (
<img src={item.icon} alt="" className={item.borderless ? "h-full w-full rounded-xl" : `${item.iconClassName ?? "h-8 w-8"} rounded-sm`} />
)}
</div>
<div className="min-w-0 flex-1">
<span className="text-sm font-medium text-neutral-900 dark:text-neutral-100">
{item.name}
</span>
<p className="mt-0.5 text-xs text-neutral-500 dark:text-neutral-400">
{item.description}
</p>
<div className="mt-2 flex items-center gap-2 rounded-xl border-neutral-200 dark:border-neutral-700 bg-neutral-50 dark:bg-neutral-800 px-3 py-2">
<code className="min-w-0 flex-1 truncate text-xs text-neutral-600 dark:text-neutral-300">
{item.command}
</code>
<CopyButton
content={item.command}
size="md"
title="Copy command to clipboard"
className="text-neutral-500 dark:text-neutral-400 hover:text-neutral-700 dark:hover:text-neutral-200 hover:bg-neutral-200/60 dark:hover:bg-neutral-700/70"
onCopy={() => {
setSettings({ LastHomeView: item.id }).catch(() => { });
}}
/>
</div>
</div>
</div>
</div>
);
return (
<main className="flex h-screen w-full flex-col relative">
<section
className={`flex-1 overflow-y-auto overscroll-contain relative min-h-0 ${isWindows ? "xl:pt-4" : "xl:pt-8"}`}
>
<div className="max-w-[730px] mx-auto w-full px-4 pt-4 pb-20 sm:px-6 sm:pt-6 sm:pb-24 lg:px-8 lg:pt-8 lg:pb-28">
<h1 className="text-xl font-semibold text-neutral-900 dark:text-neutral-100">
Launch
</h1>
<p className="mt-1 text-sm text-neutral-500 dark:text-neutral-400">
Copy a command and run it in your terminal.
</p>
<div className="mt-6 grid gap-7">
{LAUNCH_COMMANDS.map(renderCommandCard)}
</div>
</div>
</section>
</main>
);
}
+2 -2
View File
@@ -536,7 +536,7 @@ function ToolCallDisplay({
let args: Record<string, unknown> | null = null;
try {
args = JSON.parse(toolCall.function.arguments) as Record<string, unknown>;
} catch (e) {
} catch {
args = null;
}
const query = args && typeof args.query === "string" ? args.query : "";
@@ -562,7 +562,7 @@ function ToolCallDisplay({
let args: Record<string, unknown> | null = null;
try {
args = JSON.parse(toolCall.function.arguments) as Record<string, unknown>;
} catch (e) {
} catch {
args = null;
}
const url = args && typeof args.url === "string" ? args.url : "";
+1 -1
View File
@@ -73,7 +73,7 @@ export default function MessageList({
? String(args.url).trim()
: "";
if (candidate) lastQuery = candidate;
} catch {}
} catch { /* ignored */ }
}
}
}
+7 -24
View File
@@ -8,7 +8,7 @@ import {
} from "react";
import { Model } from "@/gotypes";
import { useSelectedModel } from "@/hooks/useSelectedModel";
import { useSettings } from "@/hooks/useSettings";
import { useCloudStatus } from "@/hooks/useCloudStatus";
import { useQueryClient } from "@tanstack/react-query";
import { getModelUpstreamInfo } from "@/api";
import { ArrowDownTrayIcon } from "@heroicons/react/24/outline";
@@ -34,7 +34,7 @@ export const ModelPicker = forwardRef<
chatId,
searchQuery,
);
const { settings } = useSettings();
const { cloudDisabled } = useCloudStatus();
const dropdownRef = useRef<HTMLDivElement>(null);
const searchInputRef = useRef<HTMLInputElement>(null);
const queryClient = useQueryClient();
@@ -61,24 +61,7 @@ export const ModelPicker = forwardRef<
try {
const upstreamInfo = await getModelUpstreamInfo(model);
// Compare local digest with upstream digest
let isStale =
model.digest &&
upstreamInfo.digest &&
model.digest !== upstreamInfo.digest;
// If the model has a modified time and upstream has a push time,
// check if the model was modified after the push time - if so, it's not stale
if (isStale && model.modified_at && upstreamInfo.pushTime > 0) {
const modifiedAtTime =
new Date(model.modified_at as string | number | Date).getTime() /
1000;
if (modifiedAtTime > upstreamInfo.pushTime) {
isStale = false;
}
}
if (isStale) {
if (upstreamInfo.stale) {
const currentStaleModels =
queryClient.getQueryData<Map<string, boolean>>(["staleModels"]) ||
new Map();
@@ -219,7 +202,7 @@ export const ModelPicker = forwardRef<
models={models}
selectedModel={selectedModel}
onModelSelect={handleModelSelect}
airplaneMode={settings.airplaneMode}
cloudDisabled={cloudDisabled}
isOpen={isOpen}
/>
</div>
@@ -233,13 +216,13 @@ export const ModelList = forwardRef(function ModelList(
models,
selectedModel,
onModelSelect,
airplaneMode,
cloudDisabled,
isOpen,
}: {
models: Model[];
selectedModel: Model | null;
onModelSelect: (model: Model) => void;
airplaneMode: boolean;
cloudDisabled: boolean;
isOpen: boolean;
},
ref,
@@ -348,7 +331,7 @@ export const ModelList = forwardRef(function ModelList(
</svg>
)}
{model.digest === undefined &&
(airplaneMode || !model.isCloud()) && (
(cloudDisabled || !model.isCloud()) && (
<ArrowDownTrayIcon
className="h-4 w-4 text-neutral-500 dark:text-neutral-400"
strokeWidth={1.75}
+133 -39
View File
@@ -11,15 +11,24 @@ import {
FolderIcon,
BoltIcon,
WrenchIcon,
CloudIcon,
XMarkIcon,
CogIcon,
ArrowLeftIcon,
ArrowDownTrayIcon,
} from "@heroicons/react/20/solid";
import { Settings as SettingsType } from "@/gotypes";
import { useNavigate } from "@tanstack/react-router";
import { useUser } from "@/hooks/useUser";
import { useCloudStatus } from "@/hooks/useCloudStatus";
import { useQuery, useMutation, useQueryClient } from "@tanstack/react-query";
import { getSettings, updateSettings } from "@/api";
import {
getSettings,
type CloudStatusResponse,
updateCloudSetting,
updateSettings,
getInferenceCompute,
} from "@/api";
function AnimatedDots() {
return (
@@ -53,6 +62,11 @@ export default function Settings() {
const [connectionError, setConnectionError] = useState<string | null>(null);
const [pollingInterval, setPollingInterval] = useState<number | null>(null);
const navigate = useNavigate();
const {
cloudDisabled,
cloudStatus,
isLoading: cloudStatusLoading,
} = useCloudStatus();
const {
data: settingsData,
@@ -65,6 +79,13 @@ export default function Settings() {
const settings = settingsData?.settings || null;
const { data: inferenceComputeResponse } = useQuery({
queryKey: ["inferenceCompute"],
queryFn: getInferenceCompute,
});
const defaultContextLength = inferenceComputeResponse?.defaultContextLength;
const updateSettingsMutation = useMutation({
mutationFn: updateSettings,
onSuccess: () => {
@@ -74,6 +95,50 @@ export default function Settings() {
},
});
const updateCloudMutation = useMutation({
mutationFn: (enabled: boolean) => updateCloudSetting(enabled),
onMutate: async (enabled: boolean) => {
await queryClient.cancelQueries({ queryKey: ["cloudStatus"] });
const previous = queryClient.getQueryData<CloudStatusResponse | null>([
"cloudStatus",
]);
const envForcesDisabled =
previous?.source === "env" || previous?.source === "both";
queryClient.setQueryData<CloudStatusResponse | null>(
["cloudStatus"],
previous
? {
...previous,
disabled: !enabled || envForcesDisabled,
}
: {
disabled: !enabled,
source: "config",
},
);
return { previous };
},
onError: (_error, _enabled, context) => {
if (context?.previous !== undefined) {
queryClient.setQueryData(["cloudStatus"], context.previous);
}
},
onSuccess: (status) => {
queryClient.setQueryData<CloudStatusResponse | null>(
["cloudStatus"],
status,
);
queryClient.invalidateQueries({ queryKey: ["models"] });
queryClient.invalidateQueries({ queryKey: ["cloudStatus"] });
setShowSaved(true);
setTimeout(() => setShowSaved(false), 1500);
},
});
useEffect(() => {
refetchUser();
}, []); // eslint-disable-line react-hooks/exhaustive-deps
@@ -148,13 +213,18 @@ export default function Settings() {
Models: "",
Agent: false,
Tools: false,
ContextLength: 4096,
AirplaneMode: false,
ContextLength: 0,
AutoUpdateEnabled: true,
});
updateSettingsMutation.mutate(defaultSettings);
}
};
const cloudOverriddenByEnv =
cloudStatus?.source === "env" || cloudStatus?.source === "both";
const cloudToggleDisabled =
cloudStatusLoading || updateCloudMutation.isPending || cloudOverriddenByEnv;
const handleConnectOllamaAccount = async () => {
setConnectionError(null);
@@ -203,6 +273,10 @@ export default function Settings() {
}
const isWindows = navigator.platform.toLowerCase().includes("win");
const handleCloseSettings = () => {
const chatId = settings.LastHomeView === "chat" ? "new" : "launch";
navigate({ to: "/c/$chatId", params: { chatId } });
};
return (
<main className="flex h-screen w-full flex-col select-none dark:bg-neutral-900">
@@ -216,7 +290,7 @@ export default function Settings() {
>
{isWindows && (
<button
onClick={() => navigate({ to: "/" })}
onClick={handleCloseSettings}
className="hover:bg-neutral-100 mr-3 dark:hover:bg-neutral-800 rounded-full p-1.5"
>
<ArrowLeftIcon className="w-5 h-5 dark:text-white" />
@@ -226,7 +300,7 @@ export default function Settings() {
</h1>
{!isWindows && (
<button
onClick={() => navigate({ to: "/" })}
onClick={handleCloseSettings}
className="p-1 hover:bg-neutral-100 mr-3 dark:hover:bg-neutral-800 rounded-full"
>
<XMarkIcon className="w-6 h-6 dark:text-white" />
@@ -237,7 +311,7 @@ export default function Settings() {
<div className="space-y-4 max-w-2xl mx-auto">
{/* Connect Ollama Account */}
<div className="overflow-hidden rounded-xl bg-white dark:bg-neutral-800">
<div className="p-4 border-b border-neutral-200 dark:border-neutral-800">
<div className="p-4">
<Field>
{isLoading ? (
// Loading skeleton, this will only happen if the app started recently
@@ -344,6 +418,57 @@ export default function Settings() {
{/* Local Configuration */}
<div className="relative overflow-hidden rounded-xl bg-white dark:bg-neutral-800">
<div className="space-y-4 p-4">
<Field>
<div className="flex items-start justify-between gap-4">
<div className="flex items-start space-x-3 flex-1">
<CloudIcon className="mt-1 h-5 w-5 flex-shrink-0 text-black dark:text-neutral-100" />
<div>
<Label>Cloud</Label>
<Description>
{cloudOverriddenByEnv
? "The OLLAMA_NO_CLOUD environment variable is currently forcing cloud off."
: "Enable cloud models and web search."}
</Description>
</div>
</div>
<div className="flex-shrink-0">
<Switch
checked={!cloudDisabled}
disabled={cloudToggleDisabled}
onChange={(checked) => {
if (cloudOverriddenByEnv) {
return;
}
updateCloudMutation.mutate(checked);
}}
/>
</div>
</div>
</Field>
{/* Auto Update */}
<Field>
<div className="flex items-start justify-between gap-4">
<div className="flex items-start space-x-3 flex-1">
<ArrowDownTrayIcon className="mt-1 h-5 w-5 flex-shrink-0 text-black dark:text-neutral-100" />
<div>
<Label>Auto-download updates</Label>
<Description>
{settings.AutoUpdateEnabled
? "Automatically download updates when available."
: "Updates will not be downloaded automatically."}
</Description>
</div>
</div>
<div className="flex-shrink-0">
<Switch
checked={settings.AutoUpdateEnabled}
onChange={(checked) => handleChange("AutoUpdateEnabled", checked)}
/>
</div>
</div>
</Field>
{/* Expose Ollama */}
<Field>
<div className="flex items-start justify-between gap-4">
@@ -419,13 +544,11 @@ export default function Settings() {
</Description>
<div className="mt-3">
<Slider
value={(() => {
// Otherwise use the settings value
return settings.ContextLength || 4096;
})()}
value={settings.ContextLength || defaultContextLength || 0}
onChange={(value) => {
handleChange("ContextLength", value);
}}
disabled={!defaultContextLength}
options={[
{ value: 4096, label: "4k" },
{ value: 8192, label: "8k" },
@@ -440,35 +563,6 @@ export default function Settings() {
</div>
</div>
</Field>
{/* Airplane Mode */}
<Field>
<div className="flex items-start justify-between gap-4">
<div className="flex items-start space-x-3 flex-1">
<svg
className="mt-1 h-5 w-5 flex-shrink-0 text-black dark:text-neutral-100"
viewBox="0 0 21.5508 17.9033"
fill="currentColor"
>
<path d="M21.5508 8.94727C21.542 7.91895 20.1445 7.17188 18.4658 7.17188L14.9238 7.17188C14.4316 7.17188 14.2471 7.09277 13.957 6.75879L8.05078 0.316406C7.86621 0.105469 7.6377 0 7.37402 0L6.35449 0C6.12598 0 5.99414 0.202148 6.1084 0.448242L9.14941 7.17188L4.68457 7.68164L3.09375 4.76367C2.97949 4.54395 2.78613 4.44727 2.49609 4.44727L2.11816 4.44727C1.88965 4.44727 1.74023 4.59668 1.74023 4.8252L1.74023 13.0693C1.74023 13.2979 1.88965 13.4385 2.11816 13.4385L2.49609 13.4385C2.78613 13.4385 2.97949 13.3418 3.09375 13.1309L4.68457 10.2129L9.14941 10.7227L6.1084 17.4463C5.99414 17.6836 6.12598 17.8945 6.35449 17.8945L7.37402 17.8945C7.6377 17.8945 7.86621 17.7803 8.05078 17.5781L13.957 11.127C14.2471 10.8018 14.4316 10.7227 14.9238 10.7227L18.4658 10.7227C20.1445 10.7227 21.542 9.9668 21.5508 8.94727Z" />
</svg>
<div>
<Label>Airplane mode</Label>
<Description>
Airplane mode keeps data local, disabling cloud models
and web search.
</Description>
</div>
</div>
<div className="flex-shrink-0">
<Switch
checked={settings.AirplaneMode}
onChange={(checked) =>
handleChange("AirplaneMode", checked)
}
/>
</div>
</div>
</Field>
</div>
</div>
+1 -1
View File
@@ -65,7 +65,7 @@ export const BadgeButton = forwardRef(function BadgeButton(
),
ref: React.ForwardedRef<HTMLElement>,
) {
let classes = clsx(
const classes = clsx(
className,
"group relative inline-flex rounded-md focus:not-data-focus:outline-hidden data-focus:outline-2 data-focus:outline-offset-2 data-focus:outline-blue-500",
);
+1 -1
View File
@@ -171,7 +171,7 @@ export const Button = forwardRef(function Button(
{ color, outline, plain, className, children, ...props }: ButtonProps,
ref: React.ForwardedRef<HTMLElement>,
) {
let classes = clsx(
const classes = clsx(
className,
styles.base,
outline
+8 -4
View File
@@ -6,10 +6,11 @@ export interface SliderProps {
value?: number;
onChange?: (value: number) => void;
className?: string;
disabled?: boolean;
}
const Slider = React.forwardRef<HTMLDivElement, SliderProps>(
({ label, options, value = 0, onChange }, ref) => {
({ label, options, value = 0, onChange, disabled = false }, ref) => {
const [selectedValue, setSelectedValue] = React.useState(value);
const [isDragging, setIsDragging] = React.useState(false);
const containerRef = React.useRef<HTMLDivElement>(null);
@@ -20,6 +21,7 @@ const Slider = React.forwardRef<HTMLDivElement, SliderProps>(
}, [value]);
const handleClick = (optionValue: number) => {
if (disabled) return;
setSelectedValue(optionValue);
onChange?.(optionValue);
};
@@ -39,6 +41,7 @@ const Slider = React.forwardRef<HTMLDivElement, SliderProps>(
};
const handleMouseDown = (e: React.MouseEvent) => {
if (disabled) return;
setIsDragging(true);
e.preventDefault();
};
@@ -77,7 +80,7 @@ const Slider = React.forwardRef<HTMLDivElement, SliderProps>(
}
return (
<div className="space-y-2" ref={ref}>
<div className={`space-y-2 ${disabled ? "opacity-50" : ""}`} ref={ref}>
{label && <label className="text-sm font-medium">{label}</label>}
<div className="relative">
<div className="absolute top-[9px] left-2 right-2 h-1 bg-neutral-200 dark:bg-neutral-700 pointer-events-none rounded-full" />
@@ -88,10 +91,11 @@ const Slider = React.forwardRef<HTMLDivElement, SliderProps>(
<button
onClick={() => handleClick(option.value)}
onMouseDown={handleMouseDown}
className="relative px-3 py-6 -mx-3 -my-6 z-10 cursor-pointer"
disabled={disabled}
className={`relative px-3 py-6 -mx-3 -my-6 z-10 ${disabled ? "cursor-not-allowed" : "cursor-pointer"}`}
>
<div className="relative w-5 h-5 flex items-center justify-center">
{selectedValue === option.value && (
{selectedValue === option.value && !disabled && (
<div className="w-4 h-4 bg-white dark:bg-white border border-neutral-400 dark:border-neutral-500 rounded-full cursor-grab active:cursor-grabbing" />
)}
</div>
+8 -10
View File
@@ -6,8 +6,8 @@ import { useSelectedModel } from "./useSelectedModel";
import { createQueryBatcher } from "./useQueryBatcher";
import { useRefetchModels } from "./useModels";
import { useStreamingContext } from "@/contexts/StreamingContext";
import { useSettings } from "./useSettings";
import { getModelCapabilities } from "@/api";
import { useCloudStatus } from "./useCloudStatus";
export const useChats = () => {
return useQuery({
@@ -116,11 +116,9 @@ export const useIsModelStale = (modelName: string) => {
export const useShouldShowStaleDisplay = (model: Model | null) => {
const isStale = useIsModelStale(model?.model || "");
const { data: dismissedModels } = useDismissedStaleModels();
const {
settings: { airplaneMode },
} = useSettings();
const { cloudDisabled } = useCloudStatus();
if (model?.isCloud() && !airplaneMode) {
if (model?.isCloud() && !cloudDisabled) {
return false;
}
@@ -383,7 +381,7 @@ export const useSendMessage = (chatId: string) => {
role: "assistant",
content: "",
thinking: "",
model: effectiveModel,
model: effectiveModel.model,
}),
);
lastMessage = newMessages[newMessages.length - 1];
@@ -435,7 +433,7 @@ export const useSendMessage = (chatId: string) => {
role: "assistant",
content: "",
thinking: "",
model: effectiveModel,
model: effectiveModel.model,
}),
);
lastMessage = newMessages[newMessages.length - 1];
@@ -522,7 +520,7 @@ export const useSendMessage = (chatId: string) => {
thinkingTimeStart:
lastMessage.thinkingTimeStart || event.thinkingTimeStart,
thinkingTimeEnd: event.thinkingTimeEnd,
model: selectedModel,
model: selectedModel.model,
});
newMessages[newMessages.length - 1] = updatedMessage;
} else {
@@ -535,7 +533,7 @@ export const useSendMessage = (chatId: string) => {
tool_calls: event.toolCalls,
thinkingTimeStart: event.thinkingTimeStart,
thinkingTimeEnd: event.thinkingTimeEnd,
model: selectedModel,
model: selectedModel.model,
}),
);
}
@@ -701,7 +699,7 @@ export const useSendMessage = (chatId: string) => {
queryClient.setQueryData(["chat", newId], {
chat: new Chat({
id: newId,
model: effectiveModel,
model: effectiveModel.model,
messages: [
new Message({
role: "user",
+20
View File
@@ -0,0 +1,20 @@
import { useQuery } from "@tanstack/react-query";
import { getCloudStatus, type CloudStatusResponse } from "@/api";
export function useCloudStatus() {
const cloudQuery = useQuery<CloudStatusResponse | null>({
queryKey: ["cloudStatus"],
queryFn: getCloudStatus,
retry: false,
staleTime: 60 * 1000,
});
return {
cloudStatus: cloudQuery.data,
cloudDisabled: cloudQuery.data?.disabled ?? false,
isKnown: cloudQuery.data !== null && cloudQuery.data !== undefined,
isLoading: cloudQuery.isLoading,
isError: cloudQuery.isError,
error: cloudQuery.error,
};
}
+13
View File
@@ -0,0 +1,13 @@
import { useQuery } from "@tanstack/react-query";
import { getModelRecommendations } from "@/api";
import type { ModelRecommendation } from "@/api";
export function useFeaturedModels() {
return useQuery<ModelRecommendation[], Error>({
queryKey: ["modelRecommendations"],
queryFn: getModelRecommendations,
staleTime: 5 * 60 * 1000,
gcTime: 30 * 60 * 1000,
refetchOnWindowFocus: false,
});
}
@@ -20,3 +20,8 @@ export function useHasVisionCapability(modelName: string | undefined) {
const { data: capabilitiesResponse } = useModelCapabilities(modelName);
return capabilitiesResponse?.capabilities?.includes("vision") ?? false;
}
export function useHasToolsCapability(modelName: string | undefined) {
const { data: capabilitiesResponse } = useModelCapabilities(modelName);
return capabilitiesResponse?.capabilities?.includes("tools") ?? false;
}
+37 -26
View File
@@ -1,51 +1,49 @@
import { useQuery } from "@tanstack/react-query";
import { Model } from "@/gotypes";
import { getModels } from "@/api";
import { mergeModels } from "@/utils/mergeModels";
import { useSettings } from "./useSettings";
import { useMemo } from "react";
import { useCloudStatus } from "./useCloudStatus";
import { useFeaturedModels } from "./useFeaturedModels";
export function useModels(searchQuery = "") {
const { settings } = useSettings();
const { cloudDisabled } = useCloudStatus();
const { data: recommendations, isLoading: recommendationsLoading } =
useFeaturedModels();
const localQuery = useQuery<Model[], Error>({
queryKey: ["models", searchQuery],
queryFn: () => getModels(searchQuery),
gcTime: 10 * 60 * 1000, // Keep in cache for 10 minutes
gcTime: 10 * 60 * 1000,
retry: 10,
// exponential backoff, starting at 100ms and capping at 5s
retryDelay: (attemptIndex) => Math.min(100 * 2 ** attemptIndex, 5000),
refetchOnWindowFocus: true,
refetchInterval: 30 * 1000, // Refetch every 30 seconds to keep models updated
refetchInterval: 30 * 1000,
refetchIntervalInBackground: true,
});
const allModels = useMemo(() => {
const models = mergeModels(localQuery.data || [], settings.airplaneMode);
const local = localQuery.data || [];
const featured = (recommendations || []).map((r) => r.model);
const featuredSet = new Set(featured);
if (searchQuery && searchQuery.trim()) {
const query = searchQuery.toLowerCase().trim();
const filteredModels = models.filter((model) =>
model.model.toLowerCase().includes(query),
);
// Recommended models first (using the local copy when downloaded),
// then everything else from /api/tags in tags order.
const recommended = featured.map(
(name) =>
local.find((m) => m.model === name) || new Model({ model: name }),
);
const rest = local.filter((m) => !featuredSet.has(m.model));
const merged = [...recommended, ...rest];
const seen = new Set<string>();
return filteredModels.filter((model) => {
const currentModel = model.model.toLowerCase();
if (seen.has(currentModel)) {
return false;
}
seen.add(currentModel);
return true;
});
}
return models;
}, [localQuery.data, searchQuery, settings.airplaneMode]);
const visible = cloudDisabled
? merged.filter((m) => !m.isCloud())
: merged;
return filterBySearch(visible, searchQuery);
}, [localQuery.data, searchQuery, cloudDisabled, recommendations]);
return {
...localQuery,
data: allModels,
isLoading: localQuery.isLoading,
isLoading: localQuery.isLoading || recommendationsLoading,
};
}
@@ -53,3 +51,16 @@ export function useRefetchModels() {
const { refetch } = useModels();
return refetch;
}
function filterBySearch(models: Model[], query: string): Model[] {
const q = query.trim().toLowerCase();
if (!q) return models;
const seen = new Set<string>();
return models.filter((m) => {
const name = m.model.toLowerCase();
if (!name.includes(q) || seen.has(name)) return false;
seen.add(name);
return true;
});
}
+28 -16
View File
@@ -4,9 +4,9 @@ import { useModels } from "./useModels";
import { useChat } from "./useChats";
import { useSettings } from "./useSettings.ts";
import { Model } from "@/gotypes";
import { FEATURED_MODELS } from "@/utils/mergeModels";
import { getTotalVRAM } from "@/utils/vram.ts";
import { getInferenceCompute } from "@/api";
import { useCloudStatus } from "./useCloudStatus";
export function recommendDefaultModel(totalVRAM: number): string {
const vram = Math.max(0, Number(totalVRAM) || 0);
@@ -22,16 +22,19 @@ export function recommendDefaultModel(totalVRAM: number): string {
export function useSelectedModel(currentChatId?: string, searchQuery?: string) {
const { settings, setSettings } = useSettings();
const { data: models = [], isLoading } = useModels(searchQuery || "");
const { cloudDisabled } = useCloudStatus();
const { data: chatData, isLoading: isChatLoading } = useChat(
currentChatId && currentChatId !== "new" ? currentChatId : "",
);
const { data: inferenceComputes = [] } = useQuery({
queryKey: ["inference-compute"],
const { data: inferenceComputeResponse } = useQuery({
queryKey: ["inferenceCompute"],
queryFn: getInferenceCompute,
enabled: !settings.selectedModel, // Only fetch if no model is selected
});
const inferenceComputes = inferenceComputeResponse?.inferenceComputes || [];
const totalVRAM = useMemo(
() => getTotalVRAM(inferenceComputes),
[inferenceComputes],
@@ -46,12 +49,11 @@ export function useSelectedModel(currentChatId?: string, searchQuery?: string) {
const restoredChatRef = useRef<string | null>(null);
const selectedModel: Model | null = useMemo(() => {
// if airplane mode is on and selected model ends with cloud,
// switch to recommended default model
if (settings.airplaneMode && settings.selectedModel?.endsWith("cloud")) {
// If cloud is disabled and selected model ends with cloud, switch to a local default.
if (cloudDisabled && settings.selectedModel?.endsWith("cloud")) {
return (
models.find((m) => m.model === recommendedModel) ||
models.find((m) => m.isCloud) ||
models.find((m) => !m.isCloud()) ||
models.find((m) => m.digest === undefined || m.digest === "") ||
models[0] ||
null
@@ -68,7 +70,7 @@ export function useSelectedModel(currentChatId?: string, searchQuery?: string) {
"qwen3-coder:480b",
];
const shouldMigrate =
!settings.airplaneMode &&
!cloudDisabled &&
settings.turboEnabled &&
baseModelsToMigrate.includes(settings.selectedModel);
@@ -89,20 +91,23 @@ export function useSelectedModel(currentChatId?: string, searchQuery?: string) {
(settings.selectedModel &&
new Model({
model: settings.selectedModel,
cloud: FEATURED_MODELS.some(
(f) => f.endsWith("cloud") && f === settings.selectedModel,
),
cloud: settings.selectedModel.endsWith("cloud"),
ollama_host: false,
})) ||
null
);
}, [models, settings.selectedModel, settings.airplaneMode, recommendedModel]);
}, [
models,
settings.selectedModel,
cloudDisabled,
recommendedModel,
]);
useEffect(() => {
if (!selectedModel) return;
if (
settings.airplaneMode &&
cloudDisabled &&
settings.selectedModel?.endsWith("cloud") &&
selectedModel.model !== settings.selectedModel
) {
@@ -110,13 +115,17 @@ export function useSelectedModel(currentChatId?: string, searchQuery?: string) {
}
if (
!settings.airplaneMode &&
!cloudDisabled &&
settings.turboEnabled &&
selectedModel.model !== settings.selectedModel
) {
setSettings({ SelectedModel: selectedModel.model, TurboEnabled: false });
}
}, [selectedModel, settings.airplaneMode, settings.selectedModel]);
}, [
selectedModel,
cloudDisabled,
settings.selectedModel,
]);
// Set model from chat history when chat data loads
useEffect(() => {
@@ -169,7 +178,9 @@ export function useSelectedModel(currentChatId?: string, searchQuery?: string) {
const defaultModel =
models.find((m) => m.model === recommendedModel) ||
models.find((m) => m.isCloud()) ||
(cloudDisabled
? models.find((m) => !m.isCloud())
: models.find((m) => m.isCloud())) ||
models.find((m) => m.digest === undefined || m.digest === "") ||
models[0];
@@ -181,6 +192,7 @@ export function useSelectedModel(currentChatId?: string, searchQuery?: string) {
inferenceComputes.length,
models.length,
settings.selectedModel,
cloudDisabled,
]);
// Add the selected model to the models list if it's not already there
+3 -2
View File
@@ -9,7 +9,7 @@ interface SettingsState {
webSearchEnabled: boolean;
selectedModel: string;
sidebarOpen: boolean;
airplaneMode: boolean;
lastHomeView: string;
thinkEnabled: boolean;
thinkLevel: string;
}
@@ -22,6 +22,7 @@ type SettingsUpdate = Partial<{
ThinkLevel: string;
SelectedModel: string;
SidebarOpen: boolean;
LastHomeView: string;
}>;
export function useSettings() {
@@ -51,7 +52,7 @@ export function useSettings() {
thinkLevel: settingsData?.settings?.ThinkLevel ?? "none",
selectedModel: settingsData?.settings?.SelectedModel ?? "",
sidebarOpen: settingsData?.settings?.SidebarOpen ?? false,
airplaneMode: settingsData?.settings?.AirplaneMode ?? false,
lastHomeView: settingsData?.settings?.LastHomeView ?? "launch",
}),
[settingsData?.settings],
);
+3
View File
@@ -2,6 +2,7 @@ import type { QueryClient } from "@tanstack/react-query";
import { createRootRouteWithContext, Outlet } from "@tanstack/react-router";
import { getSettings } from "@/api";
import { useQuery } from "@tanstack/react-query";
import { useCloudStatus } from "@/hooks/useCloudStatus";
function RootComponent() {
// This hook ensures settings are fetched on app startup
@@ -9,6 +10,8 @@ function RootComponent() {
queryKey: ["settings"],
queryFn: getSettings,
});
// Fetch cloud status on startup (best-effort)
useCloudStatus();
return (
<div>
+94 -4
View File
@@ -4,12 +4,37 @@ import Chat from "@/components/Chat";
import { getChat } from "@/api";
import { SidebarLayout } from "@/components/layout/layout";
import { ChatSidebar } from "@/components/ChatSidebar";
import LaunchCommands from "@/components/LaunchCommands";
import { useEffect, useRef } from "react";
import { useSettings } from "@/hooks/useSettings";
const launchSidebarRequestedKey = "ollama.launchSidebarRequested";
const launchSidebarSeenKey = "ollama.launchSidebarSeen";
const fallbackSessionState = new Map<string, string>();
function getSessionState() {
if (typeof sessionStorage !== "undefined") {
return sessionStorage;
}
return {
getItem(key: string) {
return fallbackSessionState.get(key) ?? null;
},
setItem(key: string, value: string) {
fallbackSessionState.set(key, value);
},
removeItem(key: string) {
fallbackSessionState.delete(key);
},
};
}
export const Route = createFileRoute("/c/$chatId")({
component: RouteComponent,
loader: async ({ context, params }) => {
// Skip loading for "new" chat
if (params.chatId !== "new") {
// Skip loading for special non-chat views
if (params.chatId !== "new" && params.chatId !== "launch") {
context.queryClient.ensureQueryData({
queryKey: ["chat", params.chatId],
queryFn: () => getChat(params.chatId),
@@ -21,13 +46,70 @@ export const Route = createFileRoute("/c/$chatId")({
function RouteComponent() {
const { chatId } = Route.useParams();
const { settingsData, setSettings } = useSettings();
const previousChatIdRef = useRef<string | null>(null);
// Always call hooks at the top level - use a flag to skip data when chatId is "new"
// Always call hooks at the top level - use a flag to skip data when chatId is a special view
const {
data: chatData,
isLoading: chatLoading,
error: chatError,
} = useChat(chatId === "new" ? "" : chatId);
} = useChat(chatId === "new" || chatId === "launch" ? "" : chatId);
useEffect(() => {
if (!settingsData) {
return;
}
const previousChatId = previousChatIdRef.current;
previousChatIdRef.current = chatId;
if (chatId === "launch") {
const sessionState = getSessionState();
const shouldOpenSidebar =
previousChatId !== "launch" &&
(() => {
if (sessionState.getItem(launchSidebarRequestedKey) === "1") {
sessionState.removeItem(launchSidebarRequestedKey);
sessionState.setItem(launchSidebarSeenKey, "1");
return true;
}
if (sessionState.getItem(launchSidebarSeenKey) !== "1") {
sessionState.setItem(launchSidebarSeenKey, "1");
return true;
}
return false;
})();
const updates: { LastHomeView?: string; SidebarOpen?: boolean } = {};
if (settingsData.LastHomeView !== "launch") {
updates.LastHomeView = "launch";
}
if (shouldOpenSidebar && !settingsData.SidebarOpen) {
updates.SidebarOpen = true;
}
if (Object.keys(updates).length === 0) {
return;
}
setSettings(updates).catch(() => {
// Best effort persistence for home view preference.
});
return;
}
if (settingsData.LastHomeView === "chat") {
return;
}
setSettings({ LastHomeView: "chat" }).catch(() => {
// Best effort persistence for home view preference.
});
}, [chatId, settingsData, setSettings]);
// Handle "new" chat case - just use Chat component which handles everything
if (chatId === "new") {
@@ -38,6 +120,14 @@ function RouteComponent() {
);
}
if (chatId === "launch") {
return (
<SidebarLayout sidebar={<ChatSidebar currentChatId={chatId} />}>
<LaunchCommands />
</SidebarLayout>
);
}
// Handle existing chat case
if (chatLoading) {
return (
+10 -2
View File
@@ -1,10 +1,18 @@
import { createFileRoute, redirect } from "@tanstack/react-router";
import { getSettings } from "@/api";
export const Route = createFileRoute("/")({
beforeLoad: () => {
beforeLoad: async ({ context }) => {
const settingsData = await context.queryClient.ensureQueryData({
queryKey: ["settings"],
queryFn: getSettings,
});
const chatId =
settingsData?.settings?.LastHomeView === "chat" ? "new" : "launch";
throw redirect({
to: "/c/$chatId",
params: { chatId: "new" },
params: { chatId },
mask: {
to: "/",
},
+57
View File
@@ -0,0 +1,57 @@
import { describe, expect, it, vi, beforeEach } from "vitest";
import { copyTextToClipboard } from "./clipboard";
describe("copyTextToClipboard", () => {
beforeEach(() => {
vi.restoreAllMocks();
});
it("copies via Clipboard API when available", async () => {
const writeText = vi.fn().mockResolvedValue(undefined);
vi.stubGlobal("navigator", {
clipboard: {
writeText,
},
});
const copied = await copyTextToClipboard("ollama launch claude");
expect(copied).toBe(true);
expect(writeText).toHaveBeenCalledWith("ollama launch claude");
});
it("falls back to execCommand when Clipboard API fails", async () => {
const writeText = vi.fn().mockRejectedValue(new Error("not allowed"));
vi.stubGlobal("navigator", {
clipboard: {
writeText,
},
});
const textarea = {
value: "",
setAttribute: vi.fn(),
style: {} as Record<string, string>,
focus: vi.fn(),
select: vi.fn(),
};
const appendChild = vi.fn();
const removeChild = vi.fn();
const execCommand = vi.fn().mockReturnValue(true);
vi.stubGlobal("document", {
createElement: vi.fn().mockReturnValue(textarea),
body: {
appendChild,
removeChild,
},
execCommand,
});
const copied = await copyTextToClipboard("ollama launch openclaw");
expect(copied).toBe(true);
expect(execCommand).toHaveBeenCalledWith("copy");
expect(appendChild).toHaveBeenCalled();
expect(removeChild).toHaveBeenCalled();
});
});
+30
View File
@@ -0,0 +1,30 @@
export async function copyTextToClipboard(text: string): Promise<boolean> {
try {
await navigator.clipboard.writeText(text);
return true;
} catch (clipboardError) {
console.error(
"Clipboard API failed, falling back to execCommand",
clipboardError,
);
}
try {
const textarea = document.createElement("textarea");
textarea.value = text;
textarea.setAttribute("readonly", "true");
textarea.style.position = "fixed";
textarea.style.left = "-9999px";
textarea.style.opacity = "0";
document.body.appendChild(textarea);
textarea.focus();
textarea.select();
const copied = document.execCommand("copy");
document.body.removeChild(textarea);
return copied;
} catch (fallbackError) {
console.error("Fallback copy failed", fallbackError);
return false;
}
}
+5 -3
View File
@@ -29,13 +29,15 @@ describe("fileValidation", () => {
expect(result.valid).toBe(true);
});
it("should reject WebP images when vision capability is disabled", () => {
it("should accept images regardless of vision capability", () => {
// Vision capability check is handled at the UI layer (ChatForm),
// not at validation time, so users can switch models without
// needing to re-upload files.
const file = createMockFile("test.webp", 1024, "image/webp");
const result = validateFile(file, {
hasVisionCapability: false,
});
expect(result.valid).toBe(false);
expect(result.error).toBe("This model does not support images");
expect(result.valid).toBe(true);
});
it("should accept PNG images when vision capability is enabled", () => {
-5
View File
@@ -63,7 +63,6 @@ export function validateFile(
const {
maxFileSize = 10,
allowedExtensions = [...TEXT_FILE_EXTENSIONS, ...IMAGE_EXTENSIONS],
hasVisionCapability = false,
customValidator,
} = options;
@@ -83,10 +82,6 @@ export function validateFile(
return { valid: false, error: "File type not supported" };
}
if (IMAGE_EXTENSIONS.includes(fileExtension) && !hasVisionCapability) {
return { valid: false, error: "This model does not support images" };
}
// File size validation
if (file.size > MAX_FILE_SIZE) {
return { valid: false, error: "File too large" };
-128
View File
@@ -1,128 +0,0 @@
import { describe, it, expect } from "vitest";
import { Model } from "@/gotypes";
import { mergeModels, FEATURED_MODELS } from "@/utils/mergeModels";
import "@/api";
describe("Model merging logic", () => {
it("should handle cloud models with -cloud suffix", () => {
const localModels: Model[] = [
new Model({ model: "gpt-oss:120b-cloud" }),
new Model({ model: "llama3:latest" }),
new Model({ model: "mistral:latest" }),
];
const merged = mergeModels(localModels);
// First verify cloud models are first and in FEATURED_MODELS order
const cloudModels = FEATURED_MODELS.filter((m: string) =>
m.endsWith("cloud"),
);
for (let i = 0; i < cloudModels.length; i++) {
expect(merged[i].model).toBe(cloudModels[i]);
expect(merged[i].isCloud()).toBe(true);
}
// Then verify non-cloud featured models are next and in FEATURED_MODELS order
const nonCloudFeatured = FEATURED_MODELS.filter(
(m: string) => !m.endsWith("cloud"),
);
for (let i = 0; i < nonCloudFeatured.length; i++) {
const model = merged[i + cloudModels.length];
expect(model.model).toBe(nonCloudFeatured[i]);
expect(model.isCloud()).toBe(false);
}
// Verify local models are preserved and come after featured models
const featuredCount = FEATURED_MODELS.length;
expect(merged[featuredCount].model).toBe("llama3:latest");
expect(merged[featuredCount + 1].model).toBe("mistral:latest");
// Length should be exactly featured models plus our local models
expect(merged.length).toBe(FEATURED_MODELS.length + 2);
});
it("should hide cloud models in airplane mode", () => {
const localModels: Model[] = [
new Model({ model: "gpt-oss:120b-cloud" }),
new Model({ model: "llama3:latest" }),
new Model({ model: "mistral:latest" }),
];
const merged = mergeModels(localModels, true); // airplane mode = true
// No cloud models should be present
const cloudModels = merged.filter((m) => m.isCloud());
expect(cloudModels.length).toBe(0);
// Should have non-cloud featured models
const nonCloudFeatured = FEATURED_MODELS.filter(
(m) => !m.endsWith("cloud"),
);
for (let i = 0; i < nonCloudFeatured.length; i++) {
const model = merged[i];
expect(model.model).toBe(nonCloudFeatured[i]);
expect(model.isCloud()).toBe(false);
}
// Local models should be preserved
const featuredCount = nonCloudFeatured.length;
expect(merged[featuredCount].model).toBe("llama3:latest");
expect(merged[featuredCount + 1].model).toBe("mistral:latest");
});
it("should handle empty input", () => {
const merged = mergeModels([]);
// First verify cloud models are first and in FEATURED_MODELS order
const cloudModels = FEATURED_MODELS.filter((m) => m.endsWith("cloud"));
for (let i = 0; i < cloudModels.length; i++) {
expect(merged[i].model).toBe(cloudModels[i]);
expect(merged[i].isCloud()).toBe(true);
}
// Then verify non-cloud featured models are next and in FEATURED_MODELS order
const nonCloudFeatured = FEATURED_MODELS.filter(
(m) => !m.endsWith("cloud"),
);
for (let i = 0; i < nonCloudFeatured.length; i++) {
const model = merged[i + cloudModels.length];
expect(model.model).toBe(nonCloudFeatured[i]);
expect(model.isCloud()).toBe(false);
}
// Length should be exactly FEATURED_MODELS length
expect(merged.length).toBe(FEATURED_MODELS.length);
});
it("should sort models correctly", () => {
const localModels: Model[] = [
new Model({ model: "zephyr:latest" }),
new Model({ model: "alpha:latest" }),
new Model({ model: "gpt-oss:120b-cloud" }),
];
const merged = mergeModels(localModels);
// First verify cloud models are first and in FEATURED_MODELS order
const cloudModels = FEATURED_MODELS.filter((m) => m.endsWith("cloud"));
for (let i = 0; i < cloudModels.length; i++) {
expect(merged[i].model).toBe(cloudModels[i]);
expect(merged[i].isCloud()).toBe(true);
}
// Then verify non-cloud featured models are next and in FEATURED_MODELS order
const nonCloudFeatured = FEATURED_MODELS.filter(
(m) => !m.endsWith("cloud"),
);
for (let i = 0; i < nonCloudFeatured.length; i++) {
const model = merged[i + cloudModels.length];
expect(model.model).toBe(nonCloudFeatured[i]);
expect(model.isCloud()).toBe(false);
}
// Non-featured local models should be at the end in alphabetical order
const featuredCount = FEATURED_MODELS.length;
expect(merged[featuredCount].model).toBe("alpha:latest");
expect(merged[featuredCount + 1].model).toBe("zephyr:latest");
});
});
-101
View File
@@ -1,101 +0,0 @@
import { Model } from "@/gotypes";
// Featured models list (in priority order)
export const FEATURED_MODELS = [
"gpt-oss:120b-cloud",
"gpt-oss:20b-cloud",
"deepseek-v3.1:671b-cloud",
"qwen3-coder:480b-cloud",
"qwen3-vl:235b-cloud",
"minimax-m2:cloud",
"glm-4.6:cloud",
"gpt-oss:120b",
"gpt-oss:20b",
"gemma3:27b",
"gemma3:12b",
"gemma3:4b",
"gemma3:1b",
"deepseek-r1:8b",
"qwen3-coder:30b",
"qwen3-vl:30b",
"qwen3-vl:8b",
"qwen3-vl:4b",
"qwen3:30b",
"qwen3:8b",
"qwen3:4b",
];
function alphabeticalSort(a: Model, b: Model): number {
return a.model.toLowerCase().localeCompare(b.model.toLowerCase());
}
//Merges models, sorting cloud models first, then other models
export function mergeModels(
localModels: Model[],
airplaneMode: boolean = false,
): Model[] {
const allModels = (localModels || []).map((model) => model);
// 1. Get cloud models from local models and featured list
const cloudModels = [...allModels.filter((m) => m.isCloud())];
// Add any cloud models from FEATURED_MODELS that aren't in local models
FEATURED_MODELS.filter((f) => f.endsWith("cloud")).forEach((cloudModel) => {
if (!cloudModels.some((m) => m.model === cloudModel)) {
cloudModels.push(new Model({ model: cloudModel }));
}
});
// 2. Get other featured models (non-cloud)
const featuredModels = FEATURED_MODELS.filter(
(f) => !f.endsWith("cloud"),
).map((model) => {
// Check if this model exists in local models
const localMatch = allModels.find(
(m) => m.model.toLowerCase() === model.toLowerCase(),
);
if (localMatch) return localMatch;
return new Model({
model,
});
});
// 3. Get remaining local models that aren't featured and aren't cloud models
const remainingModels = allModels.filter(
(model) =>
!model.isCloud() &&
!FEATURED_MODELS.some(
(f) => f.toLowerCase() === model.model.toLowerCase(),
),
);
cloudModels.sort((a, b) => {
const aIndex = FEATURED_MODELS.indexOf(a.model);
const bIndex = FEATURED_MODELS.indexOf(b.model);
// If both are featured, sort by their position in FEATURED_MODELS
if (aIndex !== -1 && bIndex !== -1) {
return aIndex - bIndex;
}
// If only one is featured, featured model comes first
if (aIndex !== -1 && bIndex === -1) return -1;
if (aIndex === -1 && bIndex !== -1) return 1;
// If neither is featured, sort alphabetically
return a.model.toLowerCase().localeCompare(b.model.toLowerCase());
});
featuredModels.sort(
(a, b) =>
FEATURED_MODELS.indexOf(a.model) - FEATURED_MODELS.indexOf(b.model),
);
remainingModels.sort(alphabeticalSort);
return airplaneMode
? [...featuredModels, ...remainingModels]
: [...cloudModels, ...featuredModels, ...remainingModels];
}
+4 -4
View File
@@ -45,7 +45,8 @@ type InferenceCompute struct {
}
type InferenceComputeResponse struct {
InferenceComputes []InferenceCompute `json:"inferenceComputes"`
InferenceComputes []InferenceCompute `json:"inferenceComputes"`
DefaultContextLength int `json:"defaultContextLength"`
}
type ModelCapabilitiesResponse struct {
@@ -132,9 +133,8 @@ type Error struct {
}
type ModelUpstreamResponse struct {
Digest string `json:"digest,omitempty"`
PushTime int64 `json:"pushTime"`
Error string `json:"error,omitempty"`
Stale bool `json:"stale"`
Error string `json:"error,omitempty"`
}
// Serializable data for the browser state
+98 -36
View File
@@ -28,9 +28,11 @@ import (
"github.com/ollama/ollama/app/tools"
"github.com/ollama/ollama/app/types/not"
"github.com/ollama/ollama/app/ui/responses"
"github.com/ollama/ollama/app/updater"
"github.com/ollama/ollama/app/version"
ollamaAuth "github.com/ollama/ollama/auth"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/manifest"
"github.com/ollama/ollama/types/model"
_ "github.com/tkrajina/typescriptify-golang-structs/typescriptify"
)
@@ -106,6 +108,10 @@ type Server struct {
// Dev is true if the server is running in development mode
Dev bool
// Updater for checking and downloading updates
Updater *updater.Updater
UpdateAvailableFunc func()
}
func (s *Server) log() *slog.Logger {
@@ -150,7 +156,7 @@ func (s *Server) ollamaProxy() http.Handler {
return
}
target := envconfig.Host()
target := envconfig.ConnectableHost()
s.log().Info("configuring ollama proxy", "target", target.String())
newProxy := httputil.NewSingleHostReverseProxy(target)
@@ -188,7 +194,7 @@ func (s *Server) Handler() http.Handler {
if CORS() {
w.Header().Set("Access-Control-Allow-Origin", "*")
w.Header().Set("Access-Control-Allow-Methods", "GET, POST, PUT, DELETE, OPTIONS")
w.Header().Set("Access-Control-Allow-Headers", "Content-Type, Authorization, X-Requested-With")
w.Header().Set("Access-Control-Allow-Headers", "Content-Type, Authorization, User-Agent, Accept, X-Requested-With")
w.Header().Set("Access-Control-Allow-Credentials", "true")
// Handle preflight requests
@@ -284,15 +290,19 @@ func (s *Server) Handler() http.Handler {
mux.Handle("POST /api/v1/model/upstream", handle(s.modelUpstream))
mux.Handle("GET /api/v1/settings", handle(s.getSettings))
mux.Handle("POST /api/v1/settings", handle(s.settings))
mux.Handle("GET /api/v1/cloud", handle(s.getCloudSetting))
mux.Handle("POST /api/v1/cloud", handle(s.cloudSetting))
// Ollama proxy endpoints
ollamaProxy := s.ollamaProxy()
mux.Handle("GET /api/tags", ollamaProxy)
mux.Handle("POST /api/show", ollamaProxy)
mux.Handle("GET /api/version", ollamaProxy)
mux.Handle("GET /api/status", ollamaProxy)
mux.Handle("HEAD /api/version", ollamaProxy)
mux.Handle("POST /api/me", ollamaProxy)
mux.Handle("POST /api/signout", ollamaProxy)
mux.Handle("GET /api/experimental/model-recommendations", ollamaProxy)
// React app - catch all non-API routes and serve the React app
mux.Handle("GET /", s.appHandler())
@@ -310,7 +320,7 @@ func (s *Server) handleError(w http.ResponseWriter, e error) {
if CORS() {
w.Header().Set("Access-Control-Allow-Origin", "*")
w.Header().Set("Access-Control-Allow-Methods", "GET, POST, PUT, DELETE, OPTIONS")
w.Header().Set("Access-Control-Allow-Headers", "Content-Type, Authorization, X-Requested-With")
w.Header().Set("Access-Control-Allow-Headers", "Content-Type, Authorization, User-Agent, Accept, X-Requested-With")
w.Header().Set("Access-Control-Allow-Credentials", "true")
}
@@ -333,8 +343,18 @@ func (t *userAgentTransport) RoundTrip(req *http.Request) (*http.Response, error
// httpClient returns an HTTP client that automatically adds the User-Agent header
func (s *Server) httpClient() *http.Client {
return userAgentHTTPClient(10 * time.Second)
}
// inferenceClient uses almost the same HTTP client, but without a timeout so
// long requests aren't truncated
func (s *Server) inferenceClient() *api.Client {
return api.NewClient(envconfig.Host(), userAgentHTTPClient(0))
}
func userAgentHTTPClient(timeout time.Duration) *http.Client {
return &http.Client{
Timeout: 10 * time.Second,
Timeout: timeout,
Transport: &userAgentTransport{
base: http.DefaultTransport,
},
@@ -712,11 +732,7 @@ func (s *Server) chat(w http.ResponseWriter, r *http.Request) error {
_, cancelLoading := context.WithCancel(ctx)
loading := false
c, err := api.ClientFromEnvironment()
if err != nil {
cancelLoading()
return err
}
c := s.inferenceClient()
// Check if the model exists locally by trying to show it
// TODO (jmorganca): skip this round trip and instead just act
@@ -826,8 +842,9 @@ func (s *Server) chat(w http.ResponseWriter, r *http.Request) error {
if !hasAttachments {
WebSearchEnabled := req.WebSearch != nil && *req.WebSearch
hasToolsCapability := slices.Contains(details.Capabilities, model.CapabilityTools)
if WebSearchEnabled {
if WebSearchEnabled && hasToolsCapability {
if supportsBrowserTools(req.Model) {
browserState, ok := s.browserState(chat)
if !ok {
@@ -837,7 +854,7 @@ func (s *Server) chat(w http.ResponseWriter, r *http.Request) error {
registry.Register(tools.NewBrowserSearch(browser))
registry.Register(tools.NewBrowserOpen(browser))
registry.Register(tools.NewBrowserFind(browser))
} else if supportsWebSearchTools(req.Model) {
} else {
registry.Register(&tools.WebSearch{})
registry.Register(&tools.WebFetch{})
}
@@ -1417,11 +1434,6 @@ func (s *Server) getSettings(w http.ResponseWriter, r *http.Request) error {
settings.Models = envconfig.Models()
}
// set default context length if not set
if settings.ContextLength == 0 {
settings.ContextLength = 4096
}
// Include current runtime settings
settings.Agent = s.Agent
settings.Tools = s.Tools
@@ -1448,6 +1460,24 @@ func (s *Server) settings(w http.ResponseWriter, r *http.Request) error {
return fmt.Errorf("failed to save settings: %w", err)
}
// Handle auto-update toggle changes
if old.AutoUpdateEnabled != settings.AutoUpdateEnabled {
if !settings.AutoUpdateEnabled {
// Auto-update disabled: cancel any ongoing download
if s.Updater != nil {
s.Updater.CancelOngoingDownload()
}
} else {
// Auto-update re-enabled: show notification if update is already staged, or trigger immediate check
if (updater.IsUpdatePending() || updater.UpdateDownloaded) && s.UpdateAvailableFunc != nil {
s.UpdateAvailableFunc()
} else if s.Updater != nil {
// Trigger the background checker to run immediately
s.Updater.TriggerImmediateCheck()
}
}
}
if old.ContextLength != settings.ContextLength ||
old.Models != settings.Models ||
old.Expose != settings.Expose {
@@ -1460,17 +1490,51 @@ func (s *Server) settings(w http.ResponseWriter, r *http.Request) error {
})
}
func (s *Server) cloudSetting(w http.ResponseWriter, r *http.Request) error {
var req struct {
Enabled bool `json:"enabled"`
}
if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
return fmt.Errorf("invalid request body: %w", err)
}
if err := s.Store.SetCloudEnabled(req.Enabled); err != nil {
return fmt.Errorf("failed to persist cloud setting: %w", err)
}
s.Restart()
return s.writeCloudStatus(w)
}
func (s *Server) getCloudSetting(w http.ResponseWriter, r *http.Request) error {
return s.writeCloudStatus(w)
}
func (s *Server) writeCloudStatus(w http.ResponseWriter) error {
disabled, source, err := s.Store.CloudStatus()
if err != nil {
return fmt.Errorf("failed to load cloud status: %w", err)
}
w.Header().Set("Content-Type", "application/json")
return json.NewEncoder(w).Encode(map[string]any{
"disabled": disabled,
"source": source,
})
}
func (s *Server) getInferenceCompute(w http.ResponseWriter, r *http.Request) error {
ctx, cancel := context.WithTimeout(r.Context(), 500*time.Millisecond)
defer cancel()
serverInferenceComputes, err := server.GetInferenceComputer(ctx)
info, err := server.GetInferenceInfo(ctx)
if err != nil {
s.log().Error("failed to get inference compute", "error", err)
return fmt.Errorf("failed to get inference compute: %w", err)
s.log().Error("failed to get inference info", "error", err)
return fmt.Errorf("failed to get inference info: %w", err)
}
inferenceComputes := make([]responses.InferenceCompute, len(serverInferenceComputes))
for i, ic := range serverInferenceComputes {
inferenceComputes := make([]responses.InferenceCompute, len(info.Computes))
for i, ic := range info.Computes {
inferenceComputes[i] = responses.InferenceCompute{
Library: ic.Library,
Variant: ic.Variant,
@@ -1482,7 +1546,8 @@ func (s *Server) getInferenceCompute(w http.ResponseWriter, r *http.Request) err
}
response := responses.InferenceComputeResponse{
InferenceComputes: inferenceComputes,
InferenceComputes: inferenceComputes,
DefaultContextLength: info.DefaultContextLength,
}
w.Header().Set("Content-Type", "application/json")
@@ -1515,9 +1580,18 @@ func (s *Server) modelUpstream(w http.ResponseWriter, r *http.Request) error {
return json.NewEncoder(w).Encode(response)
}
n := model.ParseName(req.Model)
stale := true
if m, err := manifest.ParseNamedManifest(n); err == nil {
if m.Digest() == digest {
stale = false
} else if pushTime > 0 && m.FileInfo().ModTime().Unix() >= pushTime {
stale = false
}
}
response := responses.ModelUpstreamResponse{
Digest: digest,
PushTime: pushTime,
Stale: stale,
}
w.Header().Set("Content-Type", "application/json")
@@ -1615,18 +1689,6 @@ func supportsBrowserTools(model string) bool {
return strings.HasPrefix(strings.ToLower(model), "gpt-oss")
}
// Web search tools are simpler, providing only basic web search and fetch capabilities (e.g., "web_search", "web_fetch") without simulating a browser. Currently only qwen3 and deepseek-v3 support web search tools.
func supportsWebSearchTools(model string) bool {
model = strings.ToLower(model)
prefixes := []string{"qwen3", "deepseek-v3"}
for _, p := range prefixes {
if strings.HasPrefix(model, p) {
return true
}
}
return false
}
// buildChatRequest converts store.Chat to api.ChatRequest
func (s *Server) buildChatRequest(chat *store.Chat, model string, think any, availableTools []map[string]any) (*api.ChatRequest, error) {
var msgs []api.Message
+419
View File
@@ -4,6 +4,7 @@ package ui
import (
"bytes"
"context"
"encoding/json"
"io"
"net/http"
@@ -11,9 +12,12 @@ import (
"path/filepath"
"runtime"
"strings"
"sync/atomic"
"testing"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/app/store"
"github.com/ollama/ollama/app/updater"
)
func TestHandlePostApiSettings(t *testing.T) {
@@ -115,6 +119,107 @@ func TestHandlePostApiSettings(t *testing.T) {
}
}
func TestHandlePostApiCloudSetting(t *testing.T) {
tmpHome := t.TempDir()
t.Setenv("HOME", tmpHome)
t.Setenv("OLLAMA_NO_CLOUD", "")
testStore := &store.Store{
DBPath: filepath.Join(t.TempDir(), "db.sqlite"),
}
defer testStore.Close()
restartCount := 0
server := &Server{
Store: testStore,
Restart: func() {
restartCount++
},
}
for _, tc := range []struct {
name string
body string
wantEnabled bool
}{
{name: "disable cloud", body: `{"enabled": false}`, wantEnabled: false},
{name: "enable cloud", body: `{"enabled": true}`, wantEnabled: true},
} {
t.Run(tc.name, func(t *testing.T) {
req := httptest.NewRequest("POST", "/api/v1/cloud", bytes.NewBufferString(tc.body))
req.Header.Set("Content-Type", "application/json")
rr := httptest.NewRecorder()
if err := server.cloudSetting(rr, req); err != nil {
t.Fatalf("cloudSetting() error = %v", err)
}
if rr.Code != http.StatusOK {
t.Fatalf("cloudSetting() status = %d, want %d", rr.Code, http.StatusOK)
}
var got map[string]any
if err := json.Unmarshal(rr.Body.Bytes(), &got); err != nil {
t.Fatalf("cloudSetting() invalid response JSON: %v", err)
}
if got["disabled"] != !tc.wantEnabled {
t.Fatalf("response disabled = %v, want %v", got["disabled"], !tc.wantEnabled)
}
disabled, err := testStore.CloudDisabled()
if err != nil {
t.Fatalf("CloudDisabled() error = %v", err)
}
if gotEnabled := !disabled; gotEnabled != tc.wantEnabled {
t.Fatalf("cloud enabled = %v, want %v", gotEnabled, tc.wantEnabled)
}
})
}
if restartCount != 2 {
t.Fatalf("Restart called %d times, want 2", restartCount)
}
}
func TestHandleGetApiCloudSetting(t *testing.T) {
tmpHome := t.TempDir()
t.Setenv("HOME", tmpHome)
t.Setenv("OLLAMA_NO_CLOUD", "")
testStore := &store.Store{
DBPath: filepath.Join(t.TempDir(), "db.sqlite"),
}
defer testStore.Close()
if err := testStore.SetCloudEnabled(false); err != nil {
t.Fatalf("SetCloudEnabled(false) error = %v", err)
}
server := &Server{
Store: testStore,
Restart: func() {},
}
req := httptest.NewRequest("GET", "/api/v1/cloud", nil)
rr := httptest.NewRecorder()
if err := server.getCloudSetting(rr, req); err != nil {
t.Fatalf("getCloudSetting() error = %v", err)
}
if rr.Code != http.StatusOK {
t.Fatalf("getCloudSetting() status = %d, want %d", rr.Code, http.StatusOK)
}
var got map[string]any
if err := json.Unmarshal(rr.Body.Bytes(), &got); err != nil {
t.Fatalf("getCloudSetting() invalid response JSON: %v", err)
}
if got["disabled"] != true {
t.Fatalf("response disabled = %v, want true", got["disabled"])
}
if got["source"] != "config" {
t.Fatalf("response source = %v, want config", got["source"])
}
}
func TestAuthenticationMiddleware(t *testing.T) {
tests := []struct {
name string
@@ -421,3 +526,317 @@ func TestUserAgentTransport(t *testing.T) {
t.Logf("User-Agent transport successfully set: %s", receivedUA)
}
func TestInferenceClientUsesUserAgent(t *testing.T) {
var gotUserAgent atomic.Value
ts := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
gotUserAgent.Store(r.Header.Get("User-Agent"))
w.Header().Set("Content-Type", "application/json")
w.Write([]byte(`{}`))
}))
defer ts.Close()
t.Setenv("OLLAMA_HOST", ts.URL)
server := &Server{}
client := server.inferenceClient()
_, err := client.Show(context.Background(), &api.ShowRequest{Model: "test"})
if err != nil {
t.Fatalf("show request failed: %v", err)
}
receivedUA, _ := gotUserAgent.Load().(string)
expectedUA := userAgent()
if receivedUA != expectedUA {
t.Errorf("User-Agent mismatch\nExpected: %s\nReceived: %s", expectedUA, receivedUA)
}
}
func TestSupportsBrowserTools(t *testing.T) {
tests := []struct {
model string
want bool
}{
{"gpt-oss", true},
{"gpt-oss-latest", true},
{"GPT-OSS", true},
{"Gpt-Oss-v2", true},
{"qwen3", false},
{"deepseek-v3", false},
{"llama3.3", false},
{"", false},
}
for _, tt := range tests {
t.Run(tt.model, func(t *testing.T) {
if got := supportsBrowserTools(tt.model); got != tt.want {
t.Errorf("supportsBrowserTools(%q) = %v, want %v", tt.model, got, tt.want)
}
})
}
}
func TestWebSearchToolRegistration(t *testing.T) {
// Validates that the capability-gating logic in chat() correctly
// decides which tools to register based on model capabilities and
// the web search flag.
tests := []struct {
name string
webSearchEnabled bool
hasToolsCap bool
model string
wantBrowser bool // expects browser tools (gpt-oss)
wantWebSearch bool // expects basic web search/fetch tools
wantNone bool // expects no tools registered
}{
{
name: "web search enabled with tools capability - browser model",
webSearchEnabled: true,
hasToolsCap: true,
model: "gpt-oss-latest",
wantBrowser: true,
},
{
name: "web search enabled with tools capability - non-browser model",
webSearchEnabled: true,
hasToolsCap: true,
model: "qwen3",
wantWebSearch: true,
},
{
name: "web search enabled without tools capability",
webSearchEnabled: true,
hasToolsCap: false,
model: "llama3.3",
wantNone: true,
},
{
name: "web search disabled with tools capability",
webSearchEnabled: false,
hasToolsCap: true,
model: "qwen3",
wantNone: true,
},
{
name: "web search disabled without tools capability",
webSearchEnabled: false,
hasToolsCap: false,
model: "llama3.3",
wantNone: true,
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
// Replicate the decision logic from chat() handler
gotBrowser := false
gotWebSearch := false
if tt.webSearchEnabled && tt.hasToolsCap {
if supportsBrowserTools(tt.model) {
gotBrowser = true
} else {
gotWebSearch = true
}
}
if tt.wantBrowser && !gotBrowser {
t.Error("expected browser tools to be registered")
}
if tt.wantWebSearch && !gotWebSearch {
t.Error("expected web search tools to be registered")
}
if tt.wantNone && (gotBrowser || gotWebSearch) {
t.Error("expected no tools to be registered")
}
if !tt.wantBrowser && gotBrowser {
t.Error("unexpected browser tools registered")
}
if !tt.wantWebSearch && gotWebSearch {
t.Error("unexpected web search tools registered")
}
})
}
}
func TestSettingsToggleAutoUpdateOff_CancelsDownload(t *testing.T) {
testStore := &store.Store{
DBPath: filepath.Join(t.TempDir(), "db.sqlite"),
}
defer testStore.Close()
// Start with auto-update enabled
settings, err := testStore.Settings()
if err != nil {
t.Fatal(err)
}
settings.AutoUpdateEnabled = true
if err := testStore.SetSettings(settings); err != nil {
t.Fatal(err)
}
upd := &updater.Updater{Store: &store.Store{
DBPath: filepath.Join(t.TempDir(), "db2.sqlite"),
}}
defer upd.Store.Close()
// We can't easily mock CancelOngoingDownload, but we can verify
// the full settings handler flow works without error
server := &Server{
Store: testStore,
Restart: func() {},
Updater: upd,
}
// Disable auto-update via settings API
settings.AutoUpdateEnabled = false
body, err := json.Marshal(settings)
if err != nil {
t.Fatal(err)
}
req := httptest.NewRequest("POST", "/api/v1/settings", bytes.NewReader(body))
req.Header.Set("Content-Type", "application/json")
rr := httptest.NewRecorder()
if err := server.settings(rr, req); err != nil {
t.Fatalf("settings() error = %v", err)
}
if rr.Code != http.StatusOK {
t.Fatalf("settings() status = %d, want %d", rr.Code, http.StatusOK)
}
// Verify settings were saved with auto-update disabled
saved, err := testStore.Settings()
if err != nil {
t.Fatal(err)
}
if saved.AutoUpdateEnabled {
t.Fatal("expected AutoUpdateEnabled to be false after toggle off")
}
}
func TestSettingsToggleAutoUpdateOn_WithPendingUpdate_ShowsNotification(t *testing.T) {
testStore := &store.Store{
DBPath: filepath.Join(t.TempDir(), "db.sqlite"),
}
defer testStore.Close()
// Start with auto-update disabled
settings, err := testStore.Settings()
if err != nil {
t.Fatal(err)
}
settings.AutoUpdateEnabled = false
if err := testStore.SetSettings(settings); err != nil {
t.Fatal(err)
}
// Simulate that an update was previously downloaded
oldVal := updater.UpdateDownloaded
updater.UpdateDownloaded = true
defer func() { updater.UpdateDownloaded = oldVal }()
var notificationCalled atomic.Bool
server := &Server{
Store: testStore,
Restart: func() {},
UpdateAvailableFunc: func() {
notificationCalled.Store(true)
},
}
// Re-enable auto-update via settings API
settings.AutoUpdateEnabled = true
body, err := json.Marshal(settings)
if err != nil {
t.Fatal(err)
}
req := httptest.NewRequest("POST", "/api/v1/settings", bytes.NewReader(body))
req.Header.Set("Content-Type", "application/json")
rr := httptest.NewRecorder()
if err := server.settings(rr, req); err != nil {
t.Fatalf("settings() error = %v", err)
}
if rr.Code != http.StatusOK {
t.Fatalf("settings() status = %d, want %d", rr.Code, http.StatusOK)
}
if !notificationCalled.Load() {
t.Fatal("expected UpdateAvailableFunc to be called when re-enabling with a downloaded update")
}
}
func TestSettingsToggleAutoUpdateOn_NoPendingUpdate_TriggersCheck(t *testing.T) {
testStore := &store.Store{
DBPath: filepath.Join(t.TempDir(), "db.sqlite"),
}
defer testStore.Close()
// Start with auto-update disabled
settings, err := testStore.Settings()
if err != nil {
t.Fatal(err)
}
settings.AutoUpdateEnabled = false
if err := testStore.SetSettings(settings); err != nil {
t.Fatal(err)
}
// Ensure no pending update - clear both the downloaded flag and the stage dir
oldVal := updater.UpdateDownloaded
updater.UpdateDownloaded = false
defer func() { updater.UpdateDownloaded = oldVal }()
oldStageDir := updater.UpdateStageDir
updater.UpdateStageDir = t.TempDir() // empty dir means IsUpdatePending() returns false
defer func() { updater.UpdateStageDir = oldStageDir }()
upd := &updater.Updater{Store: &store.Store{
DBPath: filepath.Join(t.TempDir(), "db2.sqlite"),
}}
defer upd.Store.Close()
// Initialize the checkNow channel by starting (and immediately stopping) the checker
// so TriggerImmediateCheck doesn't panic on nil channel
ctx, cancel := context.WithCancel(t.Context())
upd.StartBackgroundUpdaterChecker(ctx, func(string) error { return nil })
defer cancel()
var notificationCalled atomic.Bool
server := &Server{
Store: testStore,
Restart: func() {},
Updater: upd,
UpdateAvailableFunc: func() {
notificationCalled.Store(true)
},
}
// Re-enable auto-update via settings API
settings.AutoUpdateEnabled = true
body, err := json.Marshal(settings)
if err != nil {
t.Fatal(err)
}
req := httptest.NewRequest("POST", "/api/v1/settings", bytes.NewReader(body))
req.Header.Set("Content-Type", "application/json")
rr := httptest.NewRecorder()
if err := server.settings(rr, req); err != nil {
t.Fatalf("settings() error = %v", err)
}
if rr.Code != http.StatusOK {
t.Fatalf("settings() status = %d, want %d", rr.Code, http.StatusOK)
}
// UpdateAvailableFunc should NOT be called since there's no pending update
if notificationCalled.Load() {
t.Fatal("UpdateAvailableFunc should not be called when there is no pending update")
}
}
+159 -33
View File
@@ -5,6 +5,8 @@ package updater
import (
"context"
"crypto/rand"
"crypto/sha256"
"encoding/hex"
"encoding/json"
"errors"
"fmt"
@@ -19,6 +21,7 @@ import (
"runtime"
"strconv"
"strings"
"sync"
"time"
"github.com/ollama/ollama/app/store"
@@ -58,7 +61,8 @@ func (u *Updater) checkForUpdate(ctx context.Context) (bool, UpdateResponse) {
query := requestURL.Query()
query.Add("os", runtime.GOOS)
query.Add("arch", runtime.GOARCH)
query.Add("version", version.Version)
currentVersion := version.Version
query.Add("version", currentVersion)
query.Add("ts", strconv.FormatInt(time.Now().Unix(), 10))
// The original macOS app used to use the device ID
@@ -131,15 +135,27 @@ func (u *Updater) checkForUpdate(ctx context.Context) (bool, UpdateResponse) {
}
func (u *Updater) DownloadNewRelease(ctx context.Context, updateResp UpdateResponse) error {
// Create a cancellable context for this download
downloadCtx, cancel := context.WithCancel(ctx)
u.cancelDownloadLock.Lock()
u.cancelDownload = cancel
u.cancelDownloadLock.Unlock()
defer func() {
u.cancelDownloadLock.Lock()
u.cancelDownload = nil
u.cancelDownloadLock.Unlock()
cancel()
}()
// Do a head first to check etag info
req, err := http.NewRequestWithContext(ctx, http.MethodHead, updateResp.UpdateURL, nil)
req, err := http.NewRequestWithContext(downloadCtx, http.MethodHead, updateResp.UpdateURL, nil)
if err != nil {
return err
}
// In case of slow downloads, continue the update check in the background
bgctx, cancel := context.WithCancel(ctx)
defer cancel()
bgctx, bgcancel := context.WithCancel(downloadCtx)
defer bgcancel()
go func() {
for {
select {
@@ -155,27 +171,26 @@ func (u *Updater) DownloadNewRelease(ctx context.Context, updateResp UpdateRespo
if err != nil {
return fmt.Errorf("error checking update: %w", err)
}
resp.Body.Close()
if resp.StatusCode != http.StatusOK {
return fmt.Errorf("unexpected status attempting to download update %d", resp.StatusCode)
}
resp.Body.Close()
etag := strings.Trim(resp.Header.Get("etag"), "\"")
if etag == "" {
slog.Debug("no etag detected, falling back to filename based dedup")
etag = "_"
}
filename := Installer
_, params, err := mime.ParseMediaType(resp.Header.Get("content-disposition"))
if err == nil {
if err == nil && params["filename"] != "" {
filename = params["filename"]
}
stageFilename := filepath.Join(UpdateStageDir, etag, filename)
stageFilename, err := updateStagePath(UpdateStageDir, resp.Header.Get("etag"), filename)
if err != nil {
return err
}
// Check to see if we already have it downloaded
_, err = os.Stat(stageFilename)
if err == nil {
slog.Info("update already downloaded", "bundle", stageFilename)
UpdateDownloaded = true
return nil
}
@@ -187,13 +202,14 @@ func (u *Updater) DownloadNewRelease(ctx context.Context, updateResp UpdateRespo
return fmt.Errorf("error checking update: %w", err)
}
defer resp.Body.Close()
etag = strings.Trim(resp.Header.Get("etag"), "\"")
if etag == "" {
slog.Debug("no etag detected, falling back to filename based dedup") // TODO probably can get rid of this redundant log
etag = "_"
if resp.StatusCode != http.StatusOK {
return fmt.Errorf("unexpected status attempting to download update %d", resp.StatusCode)
}
stageFilename = filepath.Join(UpdateStageDir, etag, filename)
stageFilename, err = updateStagePath(UpdateStageDir, resp.Header.Get("etag"), filename)
if err != nil {
return err
}
_, err = os.Stat(filepath.Dir(stageFilename))
if errors.Is(err, os.ErrNotExist) {
@@ -210,10 +226,13 @@ func (u *Updater) DownloadNewRelease(ctx context.Context, updateResp UpdateRespo
if err != nil {
return fmt.Errorf("write payload %s: %w", stageFilename, err)
}
defer fp.Close()
if n, err := fp.Write(payload); err != nil || n != len(payload) {
_ = fp.Close()
return fmt.Errorf("write payload %s: %d vs %d -- %w", stageFilename, n, len(payload), err)
}
if err := fp.Close(); err != nil {
return fmt.Errorf("close payload %s: %w", stageFilename, err)
}
slog.Info("new update downloaded " + stageFilename)
if err := VerifyDownload(); err != nil {
@@ -224,6 +243,61 @@ func (u *Updater) DownloadNewRelease(ctx context.Context, updateResp UpdateRespo
return nil
}
func updateStagePath(stageDir, etag, filename string) (string, error) {
filename, err := safeUpdateFilename(filename)
if err != nil {
return "", err
}
stageDir, err = filepath.Abs(stageDir)
if err != nil {
return "", fmt.Errorf("resolve update stage dir: %w", err)
}
stageFilename := filepath.Join(stageDir, updateStageETagDir(etag), filename)
if err := ensurePathInDir(stageDir, stageFilename); err != nil {
return "", err
}
return stageFilename, nil
}
func safeUpdateFilename(filename string) (string, error) {
filename = strings.TrimSpace(filename)
if filename == "" {
return "", errors.New("missing update filename")
}
if filename == "." || filename == ".." ||
filepath.IsAbs(filename) || path.IsAbs(filename) ||
strings.ContainsAny(filename, `/\:`) ||
filepath.Base(filename) != filename || path.Base(filename) != filename {
return "", fmt.Errorf("unsafe update filename %q", filename)
}
return filename, nil
}
func updateStageETagDir(etag string) string {
etag = strings.Trim(strings.TrimSpace(etag), "\"")
if etag == "" {
slog.Debug("no etag detected, falling back to filename based dedup")
return "_"
}
sum := sha256.Sum256([]byte(etag))
return hex.EncodeToString(sum[:])
}
func ensurePathInDir(dir, name string) error {
rel, err := filepath.Rel(dir, name)
if err != nil {
return fmt.Errorf("resolve update staging path: %w", err)
}
if rel == ".." || strings.HasPrefix(rel, ".."+string(filepath.Separator)) || filepath.IsAbs(rel) {
return fmt.Errorf("update staging path escapes stage dir: %s", name)
}
return nil
}
func cleanupOldDownloads(stageDir string) {
files, err := os.ReadDir(stageDir)
if err != nil && errors.Is(err, os.ErrNotExist) {
@@ -244,33 +318,85 @@ func cleanupOldDownloads(stageDir string) {
}
type Updater struct {
Store *store.Store
Store *store.Store
cancelDownload context.CancelFunc
cancelDownloadLock sync.Mutex
checkNow chan struct{}
}
// CancelOngoingDownload cancels any currently running download
func (u *Updater) CancelOngoingDownload() {
u.cancelDownloadLock.Lock()
defer u.cancelDownloadLock.Unlock()
if u.cancelDownload != nil {
slog.Info("cancelling ongoing update download")
u.cancelDownload()
u.cancelDownload = nil
}
}
// TriggerImmediateCheck signals the background checker to check for updates immediately
func (u *Updater) TriggerImmediateCheck() {
if u.checkNow != nil {
select {
case u.checkNow <- struct{}{}:
default:
// Check already pending, no need to queue another
}
}
}
func (u *Updater) StartBackgroundUpdaterChecker(ctx context.Context, cb func(string) error) {
u.checkNow = make(chan struct{}, 1)
u.checkNow <- struct{}{} // Trigger first check after initial delay
go func() {
// Don't blast an update message immediately after startup
time.Sleep(UpdateCheckInitialDelay)
slog.Info("beginning update checker", "interval", UpdateCheckInterval)
ticker := time.NewTicker(UpdateCheckInterval)
defer ticker.Stop()
for {
available, resp := u.checkForUpdate(ctx)
if available {
err := u.DownloadNewRelease(ctx, resp)
if err != nil {
slog.Error(fmt.Sprintf("failed to download new release: %s", err))
} else {
err = cb(resp.UpdateVersion)
if err != nil {
slog.Warn(fmt.Sprintf("failed to register update available with tray: %s", err))
}
}
}
select {
case <-ctx.Done():
slog.Debug("stopping background update checker")
return
default:
time.Sleep(UpdateCheckInterval)
case <-u.checkNow:
// Immediate check triggered
case <-ticker.C:
// Regular interval check
}
// Always check for updates
available, resp := u.checkForUpdate(ctx)
if !available {
continue
}
// Update is available - check if auto-update is enabled for downloading
settings, err := u.Store.Settings()
if err != nil {
slog.Error("failed to load settings", "error", err)
continue
}
if !settings.AutoUpdateEnabled {
// Auto-update disabled - don't download, just log
slog.Debug("update available but auto-update disabled", "version", resp.UpdateVersion)
continue
}
// Auto-update is enabled - download
err = u.DownloadNewRelease(ctx, resp)
if err != nil {
slog.Error("failed to download new release", "error", err)
continue
}
// Download successful - show tray notification
err = cb(resp.UpdateVersion)
if err != nil {
slog.Warn("failed to register update available with tray", "error", err)
}
}
}()
+99 -51
View File
@@ -22,6 +22,15 @@ import (
"golang.org/x/sys/unix"
)
const updateArchiveRoot = "Ollama.app"
type bundleEntryScope int
const (
bundleEntryRelative bundleEntryScope = iota
bundleEntryWithArchiveRoot
)
var (
appBackupDir string
SystemWidePath = "/Applications/Ollama.app"
@@ -167,8 +176,12 @@ func DoUpgrade(interactive bool) error {
}
name := s[1]
if strings.HasSuffix(name, "/") {
d := filepath.Join(BundlePath, name)
err := os.MkdirAll(d, 0o755)
d, err := bundleEntryPath(BundlePath, name, bundleEntryRelative)
if err != nil {
anyFailures = true
return err
}
err = os.MkdirAll(d, 0o755)
if err != nil {
anyFailures = true
return fmt.Errorf("failed to mkdir %s: %w", d, err)
@@ -181,30 +194,14 @@ func DoUpgrade(interactive bool) error {
continue
}
src, err := f.Open()
destName, err := bundleEntryPath(BundlePath, name, bundleEntryRelative)
if err != nil {
anyFailures = true
return fmt.Errorf("failed to open bundle file %s: %w", name, err)
return err
}
destName := filepath.Join(BundlePath, name)
// Verify directory first
d := filepath.Dir(destName)
if _, err := os.Stat(d); err != nil {
err := os.MkdirAll(d, 0o755)
if err != nil {
anyFailures = true
return fmt.Errorf("failed to mkdir %s: %w", d, err)
}
}
destFile, err := os.OpenFile(destName, os.O_WRONLY|os.O_CREATE|os.O_TRUNC, 0o755)
if err != nil {
if err := extractBundleFile(f, destName, name); err != nil {
anyFailures = true
return fmt.Errorf("failed to open output file %s: %w", destName, err)
}
defer destFile.Close()
if _, err := io.Copy(destFile, src); err != nil {
anyFailures = true
return fmt.Errorf("failed to open extract file %s: %w", destName, err)
return err
}
}
for _, f := range links {
@@ -225,16 +222,24 @@ func DoUpgrade(interactive bool) error {
return err
}
link := string(buf)
if link[0] == '/' {
if link == "" {
anyFailures = true
return fmt.Errorf("bundle contains empty symlink %s", f.Name)
}
if filepath.IsAbs(link) {
anyFailures = true
return fmt.Errorf("bundle contains absolute symlink %s -> %s", f.Name, link)
}
// Don't allow links outside of Ollama.app
if strings.HasPrefix(filepath.Join(filepath.Dir(name), link), "..") {
if !validBundleLinkTarget(name, link, bundleEntryRelative) {
anyFailures = true
return fmt.Errorf("bundle contains link outside of contents %s -> %s", f.Name, link)
return fmt.Errorf("bundle contains invalid symlink %s -> %s", f.Name, link)
}
if err = os.Symlink(link, filepath.Join(BundlePath, name)); err != nil {
destName, err := bundleEntryPath(BundlePath, name, bundleEntryRelative)
if err != nil {
anyFailures = true
return err
}
if err = os.Symlink(link, destName); err != nil {
anyFailures = true
return err
}
@@ -282,8 +287,11 @@ func verifyDownload() error {
links := []*zip.File{}
for _, f := range r.File {
if strings.HasSuffix(f.Name, "/") {
d := filepath.Join(dir, f.Name)
err := os.MkdirAll(d, 0o755)
d, err := bundleEntryPath(dir, f.Name, bundleEntryWithArchiveRoot)
if err != nil {
return err
}
err = os.MkdirAll(d, 0o755)
if err != nil {
return fmt.Errorf("failed to mkdir %s: %w", d, err)
}
@@ -294,26 +302,12 @@ func verifyDownload() error {
links = append(links, f)
continue
}
src, err := f.Open()
destName, err := bundleEntryPath(dir, f.Name, bundleEntryWithArchiveRoot)
if err != nil {
return fmt.Errorf("failed to open bundle file %s: %w", f.Name, err)
return err
}
destName := filepath.Join(dir, f.Name)
// Verify directory first
d := filepath.Dir(destName)
if _, err := os.Stat(d); err != nil {
err := os.MkdirAll(d, 0o755)
if err != nil {
return fmt.Errorf("failed to mkdir %s: %w", d, err)
}
}
destFile, err := os.OpenFile(destName, os.O_WRONLY|os.O_CREATE|os.O_TRUNC, 0o755)
if err != nil {
return fmt.Errorf("failed to open output file %s: %w", destName, err)
}
defer destFile.Close()
if _, err := io.Copy(destFile, src); err != nil {
return fmt.Errorf("failed to open extract file %s: %w", destName, err)
if err := extractBundleFile(f, destName, f.Name); err != nil {
return err
}
}
for _, f := range links {
@@ -326,13 +320,20 @@ func verifyDownload() error {
return err
}
link := string(buf)
if link[0] == '/' {
if link == "" {
return fmt.Errorf("bundle contains empty symlink %s", f.Name)
}
if filepath.IsAbs(link) {
return fmt.Errorf("bundle contains absolute symlink %s -> %s", f.Name, link)
}
if strings.HasPrefix(filepath.Join(filepath.Dir(f.Name), link), "..") {
return fmt.Errorf("bundle contains link outside of contents %s -> %s", f.Name, link)
if !validBundleLinkTarget(f.Name, link, bundleEntryWithArchiveRoot) {
return fmt.Errorf("bundle contains invalid symlink %s -> %s", f.Name, link)
}
if err = os.Symlink(link, filepath.Join(dir, f.Name)); err != nil {
destName, err := bundleEntryPath(dir, f.Name, bundleEntryWithArchiveRoot)
if err != nil {
return err
}
if err = os.Symlink(link, destName); err != nil {
return err
}
}
@@ -343,6 +344,53 @@ func verifyDownload() error {
return nil
}
func bundleEntryPath(root, name string, scope bundleEntryScope) (string, error) {
cleanName := filepath.Clean(filepath.FromSlash(name))
if !filepath.IsLocal(cleanName) {
return "", fmt.Errorf("bundle contains invalid path: %s", name)
}
if scope == bundleEntryWithArchiveRoot && cleanName != updateArchiveRoot &&
!strings.HasPrefix(cleanName, updateArchiveRoot+string(os.PathSeparator)) {
return "", fmt.Errorf("bundle contains invalid path: %s", name)
}
return filepath.Join(root, cleanName), nil
}
func extractBundleFile(f *zip.File, destName, name string) error {
src, err := f.Open()
if err != nil {
return fmt.Errorf("failed to open bundle file %s: %w", name, err)
}
defer src.Close()
d := filepath.Dir(destName)
if _, err := os.Stat(d); err != nil {
if err := os.MkdirAll(d, 0o755); err != nil {
return fmt.Errorf("failed to mkdir %s: %w", d, err)
}
}
destFile, err := os.OpenFile(destName, os.O_WRONLY|os.O_CREATE|os.O_TRUNC, 0o755)
if err != nil {
return fmt.Errorf("failed to open output file %s: %w", destName, err)
}
defer destFile.Close()
if _, err := io.Copy(destFile, src); err != nil {
return fmt.Errorf("failed to open extract file %s: %w", destName, err)
}
return nil
}
func validBundleLinkTarget(name, link string, scope bundleEntryScope) bool {
cleanTarget := filepath.Clean(filepath.Join(filepath.Dir(filepath.FromSlash(name)), filepath.FromSlash(link)))
if !filepath.IsLocal(cleanTarget) {
return false
}
return scope == bundleEntryRelative || cleanTarget == updateArchiveRoot ||
strings.HasPrefix(cleanTarget, updateArchiveRoot+string(os.PathSeparator))
}
// If we detect an upgrade bundle, attempt to upgrade at startup
func DoUpgradeAtStartup() error {
bundle := getStagedUpdate()
+68 -3
View File
@@ -2,6 +2,7 @@ package updater
import (
"archive/zip"
"errors"
"io/fs"
"os"
"path/filepath"
@@ -146,6 +147,46 @@ func TestDoUpgrade(t *testing.T) {
}
}
func TestDoUpgradeRejectsInvalidBundlePath(t *testing.T) {
tmpDir := t.TempDir()
BundlePath = filepath.Join(tmpDir, "Ollama.app")
appBackupDir = filepath.Join(tmpDir, "backup")
UpdateStageDir = filepath.Join(tmpDir, "updates")
UpgradeMarkerFile = filepath.Join(tmpDir, "upgraded")
bundle := filepath.Join(UpdateStageDir, "foo", "ollama-darwin.zip")
invalidTarget := filepath.Join(tmpDir, "invalid-entry")
if err := os.MkdirAll(filepath.Join(BundlePath, "Contents", "MacOS"), 0o755); err != nil {
t.Fatal("failed to create empty dirs")
}
if err := os.WriteFile(filepath.Join(BundlePath, "Contents", "MacOS", "Ollama"), []byte("old app"), 0o755); err != nil {
t.Fatal("failed to create old app")
}
if err := os.MkdirAll(filepath.Dir(bundle), 0o755); err != nil {
t.Fatal("failed to create empty dirs")
}
if err := zipCreationHelper(bundle, []testPayload{{
Name: "Ollama.app/../invalid-entry",
Body: []byte("payload"),
}}); err != nil {
t.Fatal(err)
}
if err := DoUpgrade(false); err == nil {
t.Fatal("expected failure with invalid bundle path")
} else if !strings.Contains(err.Error(), "bundle contains invalid path") {
t.Fatalf("unexpected error with invalid bundle path: %s", err)
}
if _, err := os.Stat(invalidTarget); err == nil {
t.Fatalf("invalid bundle path wrote %s", invalidTarget)
} else if !errors.Is(err, os.ErrNotExist) {
t.Fatalf("unexpected stat error for %s: %s", invalidTarget, err)
}
if _, err := os.Stat(filepath.Join(BundlePath, "Contents", "MacOS", "Ollama")); err != nil {
t.Fatalf("old app was not restored: %s", err)
}
}
func TestDoUpgradeAtStartup(t *testing.T) {
tmpDir := t.TempDir()
BundlePath = filepath.Join(tmpDir, "Ollama.app")
@@ -203,7 +244,7 @@ func TestVerifyDownloadFailures(t *testing.T) {
in []testPayload
expected string
}{
{"breakout", []testPayload{
{"invalid symlink target", []testPayload{
{
Name: "Ollama.app/",
Body: []byte{},
@@ -212,15 +253,34 @@ func TestVerifyDownloadFailures(t *testing.T) {
Body: []byte("cli payload here"),
}, {
Name: "Ollama.app/Contents/MacOS/Ollama",
Body: []byte("../../../../breakout"),
Body: []byte("../../../../invalid-target"),
Mode: os.ModeSymlink,
},
}, "bundle contains link outside"},
}, "bundle contains invalid symlink"},
{"invalid archive symlink target", []testPayload{
{
Name: "Ollama.app/Contents/MacOS/Ollama",
Body: []byte("../../../invalid-target"),
Mode: os.ModeSymlink,
},
}, "bundle contains invalid symlink"},
{"absolute", []testPayload{{
Name: "Ollama.app/Contents/MacOS/Ollama",
Body: []byte("/etc/foo"),
Mode: os.ModeSymlink,
}}, "bundle contains absolute"},
{"invalid relative file", []testPayload{{
Name: "Ollama.app/../invalid-entry",
Body: []byte("payload"),
}}, "bundle contains invalid path"},
{"invalid relative directory", []testPayload{{
Name: "Ollama.app/../invalid-entry/",
Body: []byte{},
}}, "bundle contains invalid path"},
{"absolute file", []testPayload{{
Name: filepath.Join(tmpDir, "invalid-entry"),
Body: []byte("payload"),
}}, "bundle contains invalid path"},
{"missing", []testPayload{{
Name: "Ollama.app/Contents/MacOS/Ollama",
Body: []byte("../nothere"),
@@ -242,6 +302,11 @@ func TestVerifyDownloadFailures(t *testing.T) {
if err == nil || !strings.Contains(err.Error(), tt.expected) {
t.Fatalf("expected \"%s\" got %s", tt.expected, err)
}
if _, err := os.Stat(filepath.Join(tmpDir, "invalid-entry")); err == nil {
t.Fatal("invalid bundle path wrote unexpected file")
} else if !errors.Is(err, os.ErrNotExist) {
t.Fatalf("unexpected stat error for invalid file: %s", err)
}
})
}
}
+127
View File
@@ -0,0 +1,127 @@
//go:build (windows || darwin) && updater_live
package updater
import (
"context"
"os"
"path/filepath"
"runtime"
"strings"
"testing"
"time"
"github.com/ollama/ollama/app/store"
"github.com/ollama/ollama/app/version"
)
// TestLiveAppUpdate exercises the production update endpoint and downloads the
// current OS update artifact. It is intentionally excluded from normal test
// runs because it depends on ollama.com and downloads a release artifact.
//
// Run with:
//
// go test -tags updater_live -run TestLiveAppUpdate ./app/updater
func TestLiveAppUpdate(t *testing.T) {
const spoofedVersion = "0.20.0"
ctx, cancel := context.WithTimeout(context.Background(), 10*time.Minute)
defer cancel()
oldUpdateStageDir := UpdateStageDir
oldUpdateDownloaded := UpdateDownloaded
oldVerifyDownload := VerifyDownload
oldVersion := version.Version
defer func() {
UpdateStageDir = oldUpdateStageDir
UpdateDownloaded = oldUpdateDownloaded
VerifyDownload = oldVerifyDownload
version.Version = oldVersion
}()
version.Version = spoofedVersion
expectedFilename := ""
switch runtime.GOOS {
case "windows":
t.Setenv("LOCALAPPDATA", t.TempDir())
expectedFilename = "OllamaSetup.exe"
case "darwin":
expectedFilename = "Ollama-darwin.zip"
default:
t.Fatalf("unsupported updater live test OS %q", runtime.GOOS)
}
UpdateStageDir = filepath.Join(t.TempDir(), "updates")
UpdateDownloaded = false
verifyCalled := false
VerifyDownload = func() error {
verifyCalled = true
return verifyDownload()
}
updater := &Updater{Store: &store.Store{DBPath: filepath.Join(t.TempDir(), "db.sqlite")}}
defer updater.Store.Close()
available, updateResp := updater.checkForUpdate(ctx)
if !available {
t.Fatalf("expected production update check to offer an update for spoofed version %s", spoofedVersion)
}
if updateResp.UpdateURL == "" {
t.Fatal("production update response did not include a download URL")
}
t.Logf("production update version=%q url=%q", updateResp.UpdateVersion, updateResp.UpdateURL)
if err := updater.DownloadNewRelease(ctx, updateResp); err != nil {
t.Fatalf("download production update: %v", err)
}
staged := getStagedUpdate()
if staged == "" {
t.Fatal("production update was not staged")
}
t.Logf("staged production update at %s", staged)
assertPathInsideDir(t, UpdateStageDir, staged)
if filepath.Base(staged) != expectedFilename {
t.Fatalf("expected staged %s update filename to be %q, got %q", runtime.GOOS, expectedFilename, filepath.Base(staged))
}
expectedExt := filepath.Ext(expectedFilename)
if filepath.Ext(staged) != expectedExt {
t.Fatalf("expected staged %s update to be a %s artifact, got %s", runtime.GOOS, expectedExt, staged)
}
info, err := os.Stat(staged)
if err != nil {
t.Fatalf("stat staged update: %v", err)
}
if info.Size() == 0 {
t.Fatal("staged production update is empty")
}
if !verifyCalled {
t.Fatal("DownloadNewRelease did not call VerifyDownload")
}
t.Logf("production updater download path verified staged %s update", runtime.GOOS)
}
func assertPathInsideDir(t *testing.T, dir, name string) {
t.Helper()
dir, err := filepath.Abs(dir)
if err != nil {
t.Fatal(err)
}
name, err = filepath.Abs(name)
if err != nil {
t.Fatal(err)
}
rel, err := filepath.Rel(dir, name)
if err != nil {
t.Fatal(err)
}
if rel == ".." || strings.HasPrefix(rel, ".."+string(filepath.Separator)) || filepath.IsAbs(rel) {
t.Fatalf("staged update escaped update stage dir: %s", name)
}
}
+544 -3
View File
@@ -11,12 +11,62 @@ import (
"log/slog"
"net/http"
"net/http/httptest"
"os"
"path/filepath"
"strings"
"sync/atomic"
"testing"
"time"
"github.com/ollama/ollama/app/store"
)
func TestUpdateStagePathRejectsUnsafeFilename(t *testing.T) {
stageDir := t.TempDir()
for _, tt := range []struct {
name string
filename string
}{
{"empty", ""},
{"dot", "."},
{"dotdot", ".."},
{"posix_parent", "../OllamaSetup.exe"},
{"windows_parent", `..\OllamaSetup.exe`},
{"posix_absolute_tmp", "/tmp/OllamaSetup.exe"},
{"darwin_absolute_app", "/Applications/Ollama.app"},
{"darwin_bundle_path", "Ollama.app/Contents/MacOS/Ollama"},
{"darwin_user_download", "~/Downloads/Ollama-darwin.zip"},
{"windows_absolute", `C:\Users\Public\OllamaSetup.exe`},
{"colon", "Ollama:Setup.exe"},
} {
t.Run(tt.name, func(t *testing.T) {
if _, err := updateStagePath(stageDir, "etag", tt.filename); err == nil {
t.Fatal("expected unsafe filename to be rejected")
}
})
}
}
func TestUpdateStagePathHashesETag(t *testing.T) {
stageDir := t.TempDir()
stageFilename, err := updateStagePath(stageDir, `../escaped`, "OllamaSetup.exe")
if err != nil {
t.Fatal(err)
}
rel, err := filepath.Rel(stageDir, stageFilename)
if err != nil {
t.Fatal(err)
}
if rel == ".." || strings.HasPrefix(rel, ".."+string(filepath.Separator)) || filepath.IsAbs(rel) {
t.Fatalf("stage filename escaped stage dir: %s", stageFilename)
}
etagDir := filepath.Base(filepath.Dir(stageFilename))
if etagDir == ".." || etagDir == "escaped" || strings.ContainsAny(etagDir, `/\`) {
t.Fatalf("stage filename used raw etag path component: %s", stageFilename)
}
}
func TestIsNewReleaseAvailable(t *testing.T) {
slog.SetLogLoggerLevel(slog.LevelDebug)
var server *httptest.Server
@@ -33,7 +83,7 @@ func TestIsNewReleaseAvailable(t *testing.T) {
defer server.Close()
slog.Debug("server", "url", server.URL)
updater := &Updater{Store: &store.Store{}}
updater := &Updater{Store: &store.Store{DBPath: filepath.Join(t.TempDir(), "test.db")}}
defer updater.Store.Close() // Ensure database is closed
UpdateCheckURLBase = server.URL + "/update.json"
updatePresent, resp := updater.checkForUpdate(t.Context())
@@ -45,6 +95,223 @@ func TestIsNewReleaseAvailable(t *testing.T) {
}
}
func TestDownloadNewReleaseRejectsUnsafeHeaderFilename(t *testing.T) {
UpdateStageDir = t.TempDir()
oldInstaller := Installer
oldVerifyDownload := VerifyDownload
oldUpdateDownloaded := UpdateDownloaded
defer func() {
Installer = oldInstaller
VerifyDownload = oldVerifyDownload
UpdateDownloaded = oldUpdateDownloaded
}()
Installer = "OllamaSetup.exe"
UpdateDownloaded = false
VerifyDownload = func() error {
t.Fatal("verification should not run for rejected downloads")
return nil
}
var getAttempted atomic.Bool
server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
if r.Method == http.MethodHead {
w.Header().Set("ETag", `"safe"`)
w.Header().Set("Content-Disposition", `attachment; filename="../OllamaSetup.exe"`)
w.WriteHeader(http.StatusOK)
return
}
getAttempted.Store(true)
w.WriteHeader(http.StatusOK)
}))
defer server.Close()
updater := &Updater{}
err := updater.DownloadNewRelease(t.Context(), UpdateResponse{UpdateURL: server.URL + "/download"})
if err == nil || !strings.Contains(err.Error(), "unsafe update filename") {
t.Fatalf("expected unsafe filename error, got %v", err)
}
if getAttempted.Load() {
t.Fatal("download should not continue after unsafe filename")
}
if _, err := os.Stat(filepath.Join(filepath.Dir(UpdateStageDir), "OllamaSetup.exe")); err == nil {
t.Fatal("download escaped update stage dir")
}
}
func TestDownloadNewReleaseDoesNotUseRawETagAsPathComponent(t *testing.T) {
UpdateStageDir = t.TempDir()
oldInstaller := Installer
oldVerifyDownload := VerifyDownload
oldUpdateDownloaded := UpdateDownloaded
defer func() {
Installer = oldInstaller
VerifyDownload = oldVerifyDownload
UpdateDownloaded = oldUpdateDownloaded
}()
Installer = "OllamaSetup.exe"
UpdateDownloaded = false
VerifyDownload = func() error {
return nil
}
payload := []byte("payload")
server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
w.Header().Set("ETag", `"../escaped"`)
w.WriteHeader(http.StatusOK)
if r.Method == http.MethodGet {
_, _ = w.Write(payload)
}
}))
defer server.Close()
updater := &Updater{}
if err := updater.DownloadNewRelease(t.Context(), UpdateResponse{UpdateURL: server.URL + "/download"}); err != nil {
t.Fatal(err)
}
if _, err := os.Stat(filepath.Join(filepath.Dir(UpdateStageDir), "escaped", Installer)); err == nil {
t.Fatal("download escaped update stage dir via etag")
}
entries, err := os.ReadDir(UpdateStageDir)
if err != nil {
t.Fatal(err)
}
if len(entries) != 1 {
t.Fatalf("expected one staged update dir, got %d", len(entries))
}
stageFilename := filepath.Join(UpdateStageDir, entries[0].Name(), Installer)
got, err := os.ReadFile(stageFilename)
if err != nil {
t.Fatal(err)
}
if string(got) != string(payload) {
t.Fatalf("unexpected staged payload %q", got)
}
}
func TestBackgroundCheckerSkipsAlreadyStagedETagDownload(t *testing.T) {
UpdateStageDir = t.TempDir()
oldInstaller := Installer
oldVerifyDownload := VerifyDownload
oldUpdateDownloaded := UpdateDownloaded
oldUpdateCheckInitialDelay := UpdateCheckInitialDelay
oldUpdateCheckInterval := UpdateCheckInterval
oldUpdateCheckURLBase := UpdateCheckURLBase
defer func() {
Installer = oldInstaller
VerifyDownload = oldVerifyDownload
UpdateDownloaded = oldUpdateDownloaded
UpdateCheckInitialDelay = oldUpdateCheckInitialDelay
UpdateCheckInterval = oldUpdateCheckInterval
UpdateCheckURLBase = oldUpdateCheckURLBase
}()
Installer = "OllamaSetup.exe"
UpdateDownloaded = false
UpdateCheckInitialDelay = time.Millisecond
UpdateCheckInterval = 5 * time.Millisecond
var verifyCount atomic.Int32
VerifyDownload = func() error {
verifyCount.Add(1)
return nil
}
headETag := `"old-update"`
getETag := `"download-response-etag"`
payload := []byte("payload")
var headCount atomic.Int32
var getCount atomic.Int32
var server *httptest.Server
server = httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
switch r.URL.Path {
case "/update.json":
w.Write([]byte(
fmt.Sprintf(`{"version": "9.9.9", "url": "%s"}`,
server.URL+"/9.9.9/"+Installer)))
case "/9.9.9/" + Installer:
w.Header().Set("Content-Disposition", `attachment; filename="OllamaSetup.exe"`)
switch r.Method {
case http.MethodHead:
etag := headETag
if getCount.Load() > 0 {
etag = getETag
}
w.Header().Set("ETag", etag)
headCount.Add(1)
w.WriteHeader(http.StatusOK)
case http.MethodGet:
w.Header().Set("ETag", getETag)
getCount.Add(1)
w.WriteHeader(http.StatusOK)
_, _ = w.Write(payload)
default:
t.Errorf("unexpected request method %s", r.Method)
w.WriteHeader(http.StatusMethodNotAllowed)
}
default:
t.Errorf("unexpected request path %s", r.URL.Path)
w.WriteHeader(http.StatusNotFound)
}
}))
defer server.Close()
UpdateCheckURLBase = server.URL + "/update.json"
updater := &Updater{Store: &store.Store{DBPath: filepath.Join(t.TempDir(), "test.db")}}
defer updater.Store.Close()
settings, err := updater.Store.Settings()
if err != nil {
t.Fatal(err)
}
settings.AutoUpdateEnabled = true
if err := updater.Store.SetSettings(settings); err != nil {
t.Fatal(err)
}
ctx, cancel := context.WithCancel(t.Context())
defer cancel()
callbacks := make(chan string, 4)
updater.StartBackgroundUpdaterChecker(ctx, func(ver string) error {
callbacks <- ver
return nil
})
for range 2 {
select {
case <-callbacks:
case <-time.After(5 * time.Second):
t.Fatal("timed out waiting for repeated update checks")
}
}
cancel()
stageFilename, err := updateStagePath(UpdateStageDir, getETag, Installer)
if err != nil {
t.Fatal(err)
}
got, err := os.ReadFile(stageFilename)
if err != nil {
t.Fatal(err)
}
if string(got) != string(payload) {
t.Fatalf("unexpected staged payload %q", got)
}
if headCount.Load() < 2 {
t.Fatalf("HEAD count = %d, want at least 2", headCount.Load())
}
if getCount.Load() != 1 {
t.Fatalf("GET count = %d, want 1", getCount.Load())
}
if verifyCount.Load() != 1 {
t.Fatalf("verification count = %d, want 1", verifyCount.Load())
}
if !UpdateDownloaded {
t.Fatal("UpdateDownloaded should stay true for already staged update")
}
}
func TestBackgoundChecker(t *testing.T) {
UpdateStageDir = t.TempDir()
haveUpdate := false
@@ -84,8 +351,18 @@ func TestBackgoundChecker(t *testing.T) {
defer server.Close()
UpdateCheckURLBase = server.URL + "/update.json"
updater := &Updater{Store: &store.Store{}}
defer updater.Store.Close() // Ensure database is closed
updater := &Updater{Store: &store.Store{DBPath: filepath.Join(t.TempDir(), "test.db")}}
defer updater.Store.Close()
settings, err := updater.Store.Settings()
if err != nil {
t.Fatal(err)
}
settings.AutoUpdateEnabled = true
if err := updater.Store.SetSettings(settings); err != nil {
t.Fatal(err)
}
updater.StartBackgroundUpdaterChecker(ctx, cb)
select {
case <-stallTimer.C:
@@ -99,3 +376,267 @@ func TestBackgoundChecker(t *testing.T) {
}
}
}
func TestAutoUpdateDisabledSkipsDownload(t *testing.T) {
UpdateStageDir = t.TempDir()
var downloadAttempted atomic.Bool
done := make(chan struct{})
ctx, cancel := context.WithCancel(t.Context())
defer cancel()
UpdateCheckInitialDelay = 5 * time.Millisecond
UpdateCheckInterval = 5 * time.Millisecond
VerifyDownload = func() error {
return nil
}
var server *httptest.Server
server = httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
if r.URL.Path == "/update.json" {
w.Write([]byte(
fmt.Sprintf(`{"version": "9.9.9", "url": "%s"}`,
server.URL+"/9.9.9/"+Installer)))
} else if r.URL.Path == "/9.9.9/"+Installer {
downloadAttempted.Store(true)
buf := &bytes.Buffer{}
zw := zip.NewWriter(buf)
zw.Close()
io.Copy(w, buf)
}
}))
defer server.Close()
UpdateCheckURLBase = server.URL + "/update.json"
updater := &Updater{Store: &store.Store{DBPath: filepath.Join(t.TempDir(), "test.db")}}
defer updater.Store.Close()
// Ensure auto-update is disabled
settings, err := updater.Store.Settings()
if err != nil {
t.Fatal(err)
}
settings.AutoUpdateEnabled = false
if err := updater.Store.SetSettings(settings); err != nil {
t.Fatal(err)
}
cb := func(ver string) error {
t.Fatal("callback should not be called when auto-update is disabled")
return nil
}
updater.StartBackgroundUpdaterChecker(ctx, cb)
// Wait enough time for multiple check cycles
time.Sleep(50 * time.Millisecond)
close(done)
if downloadAttempted.Load() {
t.Fatal("download should not be attempted when auto-update is disabled")
}
}
func TestAutoUpdateReenabledDownloadsUpdate(t *testing.T) {
UpdateStageDir = t.TempDir()
var downloadAttempted atomic.Bool
callbackCalled := make(chan struct{}, 1)
ctx, cancel := context.WithCancel(t.Context())
defer cancel()
UpdateCheckInitialDelay = 5 * time.Millisecond
UpdateCheckInterval = 5 * time.Millisecond
VerifyDownload = func() error {
return nil
}
var server *httptest.Server
server = httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
if r.URL.Path == "/update.json" {
w.Write([]byte(
fmt.Sprintf(`{"version": "9.9.9", "url": "%s"}`,
server.URL+"/9.9.9/"+Installer)))
} else if r.URL.Path == "/9.9.9/"+Installer {
downloadAttempted.Store(true)
buf := &bytes.Buffer{}
zw := zip.NewWriter(buf)
zw.Close()
io.Copy(w, buf)
}
}))
defer server.Close()
UpdateCheckURLBase = server.URL + "/update.json"
upd := &Updater{Store: &store.Store{DBPath: filepath.Join(t.TempDir(), "test.db")}}
defer upd.Store.Close()
// Start with auto-update disabled
settings, err := upd.Store.Settings()
if err != nil {
t.Fatal(err)
}
settings.AutoUpdateEnabled = false
if err := upd.Store.SetSettings(settings); err != nil {
t.Fatal(err)
}
cb := func(ver string) error {
select {
case callbackCalled <- struct{}{}:
default:
}
return nil
}
upd.StartBackgroundUpdaterChecker(ctx, cb)
// Wait for a few cycles with auto-update disabled - no download should happen
time.Sleep(50 * time.Millisecond)
if downloadAttempted.Load() {
t.Fatal("download should not happen while auto-update is disabled")
}
// Re-enable auto-update
settings.AutoUpdateEnabled = true
if err := upd.Store.SetSettings(settings); err != nil {
t.Fatal(err)
}
// Wait for the checker to pick it up and download
select {
case <-callbackCalled:
// Success: download happened and callback was called after re-enabling
if !downloadAttempted.Load() {
t.Fatal("expected download to be attempted after re-enabling")
}
case <-time.After(5 * time.Second):
t.Fatal("expected download and callback after re-enabling auto-update")
}
}
func TestCancelOngoingDownload(t *testing.T) {
UpdateStageDir = t.TempDir()
downloadStarted := make(chan struct{})
downloadCancelled := make(chan struct{})
ctx := t.Context()
VerifyDownload = func() error {
return nil
}
var server *httptest.Server
server = httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
if r.URL.Path == "/update.json" {
w.Write([]byte(
fmt.Sprintf(`{"version": "9.9.9", "url": "%s"}`,
server.URL+"/9.9.9/"+Installer)))
} else if r.URL.Path == "/9.9.9/"+Installer {
if r.Method == http.MethodHead {
w.Header().Set("Content-Length", "1000000")
w.WriteHeader(http.StatusOK)
return
}
// Signal that download has started
close(downloadStarted)
// Wait for cancellation or timeout
select {
case <-r.Context().Done():
close(downloadCancelled)
return
case <-time.After(5 * time.Second):
t.Error("download was not cancelled in time")
}
}
}))
defer server.Close()
UpdateCheckURLBase = server.URL + "/update.json"
updater := &Updater{Store: &store.Store{DBPath: filepath.Join(t.TempDir(), "test.db")}}
defer updater.Store.Close()
_, resp := updater.checkForUpdate(ctx)
// Start download in goroutine
go func() {
_ = updater.DownloadNewRelease(ctx, resp)
}()
// Wait for download to start
select {
case <-downloadStarted:
case <-time.After(2 * time.Second):
t.Fatal("download did not start in time")
}
// Cancel the download
updater.CancelOngoingDownload()
// Verify cancellation was received
select {
case <-downloadCancelled:
// Success
case <-time.After(2 * time.Second):
t.Fatal("download cancellation was not received by server")
}
}
func TestTriggerImmediateCheck(t *testing.T) {
UpdateStageDir = t.TempDir()
checkCount := atomic.Int32{}
checkDone := make(chan struct{}, 10)
ctx, cancel := context.WithCancel(t.Context())
defer cancel()
// Set a very long interval so only TriggerImmediateCheck causes checks
UpdateCheckInitialDelay = 1 * time.Millisecond
UpdateCheckInterval = 1 * time.Hour
VerifyDownload = func() error {
return nil
}
server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
if r.URL.Path == "/update.json" {
checkCount.Add(1)
select {
case checkDone <- struct{}{}:
default:
}
// Return no update available
w.WriteHeader(http.StatusNoContent)
}
}))
defer server.Close()
UpdateCheckURLBase = server.URL + "/update.json"
updater := &Updater{Store: &store.Store{DBPath: filepath.Join(t.TempDir(), "test.db")}}
defer updater.Store.Close()
cb := func(ver string) error {
return nil
}
updater.StartBackgroundUpdaterChecker(ctx, cb)
// Wait for the initial check that fires after the initial delay
select {
case <-checkDone:
case <-time.After(2 * time.Second):
t.Fatal("initial check did not happen")
}
initialCount := checkCount.Load()
// Trigger immediate check
updater.TriggerImmediateCheck()
// Wait for the triggered check
select {
case <-checkDone:
case <-time.After(2 * time.Second):
t.Fatal("triggered check did not happen")
}
finalCount := checkCount.Load()
if finalCount <= initialCount {
t.Fatalf("TriggerImmediateCheck did not cause additional check: initial=%d, final=%d", initialCount, finalCount)
}
}
+175
View File
@@ -1,6 +1,7 @@
package updater
import (
"crypto/x509"
"errors"
"fmt"
"log/slog"
@@ -18,6 +19,30 @@ import (
var runningInstaller string
var (
crypt32 = windows.NewLazySystemDLL("crypt32.dll")
procCryptMsgGetParam = crypt32.NewProc("CryptMsgGetParam")
procCryptMsgClose = crypt32.NewProc("CryptMsgClose")
)
const cmsgSignerInfoParam = 6
type cmsgSignerInfo struct {
Version uint32
Issuer windows.CertNameBlob
SerialNumber windows.CryptIntegerBlob
HashAlgorithm windows.CryptAlgorithmIdentifier
HashEncryptionAlgorithm windows.CryptAlgorithmIdentifier
EncryptedHash windows.CryptDataBlob
AuthAttrs cryptAttributes
UnauthAttrs cryptAttributes
}
type cryptAttributes struct {
Count uint32
Attributes unsafe.Pointer
}
type OSVERSIONINFOEXW struct {
dwOSVersionInfoSize uint32
dwMajorVersion uint32
@@ -99,6 +124,12 @@ func DoUpgrade(interactive bool) error {
return fmt.Errorf("failed to lookup downloads")
}
if err := VerifyDownload(); err != nil {
_ = os.Remove(bundle)
slog.Warn("verification failure", "bundle", bundle, "error", err)
return fmt.Errorf("staged update verification failed: %w", err)
}
// We move the installer to ensure we don't race with multiple apps starting in quick succession
if err := os.Rename(bundle, runningInstaller); err != nil {
return fmt.Errorf("unable to rename %s -> %s : %w", bundle, runningInstaller, err)
@@ -184,6 +215,150 @@ func DoPostUpgradeCleanup() error {
}
func verifyDownload() error {
bundle := getStagedUpdate()
if bundle == "" {
return fmt.Errorf("failed to lookup downloads")
}
slog.Debug("verifying update", "bundle", bundle)
if err := verifyWindowsInstallerSignature(bundle); err != nil {
return fmt.Errorf("signature verification failed: %w", err)
}
return nil
}
func verifyWindowsInstallerSignature(filename string) error {
filename16, err := windows.UTF16PtrFromString(filename)
if err != nil {
return err
}
data := &windows.WinTrustData{
Size: uint32(unsafe.Sizeof(windows.WinTrustData{})),
UIChoice: windows.WTD_UI_NONE,
RevocationChecks: windows.WTD_REVOKE_WHOLECHAIN,
UnionChoice: windows.WTD_CHOICE_FILE,
StateAction: windows.WTD_STATEACTION_VERIFY,
UIContext: windows.WTD_UICONTEXT_INSTALL,
FileOrCatalogOrBlobOrSgnrOrCert: unsafe.Pointer(&windows.WinTrustFileInfo{
Size: uint32(unsafe.Sizeof(windows.WinTrustFileInfo{})),
FilePath: filename16,
}),
}
verifyErr := windows.WinVerifyTrustEx(windows.InvalidHWND, &windows.WINTRUST_ACTION_GENERIC_VERIFY_V2, data)
data.StateAction = windows.WTD_STATEACTION_CLOSE
closeErr := windows.WinVerifyTrustEx(windows.InvalidHWND, &windows.WINTRUST_ACTION_GENERIC_VERIFY_V2, data)
if verifyErr != nil {
return verifyErr
}
if closeErr != nil {
return fmt.Errorf("close WinVerifyTrust state: %w", closeErr)
}
subject, err := windowsInstallerSignerSubject(filename)
if err != nil {
return err
}
slog.Debug("verified update signature", "subject", subject)
return nil
}
func windowsInstallerSignerSubject(filename string) (string, error) {
filename16, err := windows.UTF16PtrFromString(filename)
if err != nil {
return "", err
}
var certStore windows.Handle
var msg windows.Handle
if err := windows.CryptQueryObject(
windows.CERT_QUERY_OBJECT_FILE,
unsafe.Pointer(filename16),
windows.CERT_QUERY_CONTENT_FLAG_PKCS7_SIGNED_EMBED,
windows.CERT_QUERY_FORMAT_FLAG_BINARY,
0,
nil,
nil,
nil,
&certStore,
&msg,
nil,
); err != nil {
return "", err
}
defer windows.CertCloseStore(certStore, 0) //nolint:errcheck
defer cryptMsgClose(msg) //nolint:errcheck
var signerInfoSize uint32
if err := cryptMsgGetParam(msg, cmsgSignerInfoParam, 0, nil, &signerInfoSize); err != nil {
return "", err
}
if signerInfoSize == 0 {
return "", fmt.Errorf("missing signer info")
}
signerInfoBuf := make([]byte, signerInfoSize)
if err := cryptMsgGetParam(msg, cmsgSignerInfoParam, 0, unsafe.Pointer(&signerInfoBuf[0]), &signerInfoSize); err != nil {
return "", err
}
signerInfo := (*cmsgSignerInfo)(unsafe.Pointer(&signerInfoBuf[0]))
certInfo := windows.CertInfo{
Issuer: signerInfo.Issuer,
SerialNumber: signerInfo.SerialNumber,
}
cert, err := windows.CertFindCertificateInStore(
certStore,
windows.X509_ASN_ENCODING|windows.PKCS_7_ASN_ENCODING,
0,
windows.CERT_FIND_SUBJECT_CERT,
unsafe.Pointer(&certInfo),
nil,
)
if err != nil {
return "", err
}
defer windows.CertFreeCertificateContext(cert) //nolint:errcheck
parsed, err := x509.ParseCertificate(unsafe.Slice(cert.EncodedCert, cert.Length))
if err != nil {
return "", err
}
for _, org := range parsed.Subject.Organization {
if org == "Ollama Inc." {
return parsed.Subject.String(), nil
}
}
return "", fmt.Errorf("unexpected signer: %s", parsed.Subject.String())
}
func cryptMsgGetParam(msg windows.Handle, paramType, index uint32, data unsafe.Pointer, size *uint32) error {
r1, _, e1 := procCryptMsgGetParam.Call(
uintptr(msg),
uintptr(paramType),
uintptr(index),
uintptr(data),
uintptr(unsafe.Pointer(size)),
)
if r1 == 0 {
if e1 != syscall.Errno(0) {
return e1
}
return syscall.EINVAL
}
return nil
}
func cryptMsgClose(msg windows.Handle) error {
r1, _, e1 := procCryptMsgClose.Call(uintptr(msg))
if r1 == 0 {
if e1 != syscall.Errno(0) {
return e1
}
return syscall.EINVAL
}
return nil
}
+73 -1
View File
@@ -1,13 +1,85 @@
//go:build windows || darwin
//go:build windows
package updater
import (
"log/slog"
"os"
"path/filepath"
"strings"
"testing"
)
func TestVerifyDownloadRejectsUnsignedWindowsInstaller(t *testing.T) {
oldUpdateStageDir := UpdateStageDir
defer func() {
UpdateStageDir = oldUpdateStageDir
}()
t.Setenv("LOCALAPPDATA", t.TempDir())
UpdateStageDir = t.TempDir()
bundle := filepath.Join(UpdateStageDir, "etag", "OllamaSetup.exe")
if err := os.MkdirAll(filepath.Dir(bundle), 0o755); err != nil {
t.Fatal(err)
}
if err := os.WriteFile(bundle, []byte("not a signed installer"), 0o755); err != nil {
t.Fatal(err)
}
err := verifyDownload()
if err == nil || !strings.Contains(err.Error(), "signature verification failed") {
t.Fatalf("expected signature verification failure, got %v", err)
}
}
func TestDoUpgradeAtStartupRejectsUnsignedWindowsInstaller(t *testing.T) {
oldUpdateStageDir := UpdateStageDir
oldRunningInstaller := runningInstaller
oldUpgradeLogFile := UpgradeLogFile
oldUpgradeMarkerFile := UpgradeMarkerFile
oldVerifyDownload := VerifyDownload
defer func() {
UpdateStageDir = oldUpdateStageDir
runningInstaller = oldRunningInstaller
UpgradeLogFile = oldUpgradeLogFile
UpgradeMarkerFile = oldUpgradeMarkerFile
VerifyDownload = oldVerifyDownload
}()
t.Setenv("LOCALAPPDATA", t.TempDir())
UpdateStageDir = t.TempDir()
runDir := t.TempDir()
runningInstaller = filepath.Join(runDir, "OllamaSetup.exe")
UpgradeLogFile = filepath.Join(runDir, "upgrade.log")
UpgradeMarkerFile = filepath.Join(runDir, "upgraded")
VerifyDownload = verifyDownload
bundle := filepath.Join(UpdateStageDir, "etag", "OllamaSetup.exe")
if err := os.MkdirAll(filepath.Dir(bundle), 0o755); err != nil {
t.Fatal(err)
}
if err := os.WriteFile(bundle, []byte("not a signed installer"), 0o755); err != nil {
t.Fatal(err)
}
err := DoUpgradeAtStartup()
if err == nil || !strings.Contains(err.Error(), "signature verification failed") {
t.Fatalf("expected signature verification failure, got %v", err)
}
if _, err := os.Stat(runningInstaller); !os.IsNotExist(err) {
t.Fatalf("unsigned installer was moved before verification failed: %v", err)
}
if _, err := os.Stat(bundle); !os.IsNotExist(err) {
t.Fatalf("unsigned staged installer was not removed after verification failure: %v", err)
}
}
func TestIsInstallerRunning(t *testing.T) {
oldInstaller := Installer
defer func() {
Installer = oldInstaller
}()
slog.SetLogLoggerLevel(slog.LevelDebug)
Installer = "go.exe"
if !isInstallerRunning() {
-19
View File
@@ -369,25 +369,6 @@ func (t *winTray) addSeparatorMenuItem(menuItemId, parentId uint32) error {
return nil
}
// func (t *winTray) hideMenuItem(menuItemId, parentId uint32) error {
// const ERROR_SUCCESS syscall.Errno = 0
// t.muMenus.RLock()
// menu := uintptr(t.menus[parentId])
// t.muMenus.RUnlock()
// res, _, err := pRemoveMenu.Call(
// menu,
// uintptr(menuItemId),
// MF_BYCOMMAND,
// )
// if res == 0 && err.(syscall.Errno) != ERROR_SUCCESS {
// return err
// }
// t.delFromVisibleItems(parentId, menuItemId)
// return nil
// }
func (t *winTray) showMenu() error {
p := point{}
boolRet, _, err := pGetCursorPos.Call(uintptr(unsafe.Pointer(&p)))
-1
View File
@@ -51,7 +51,6 @@ const (
IMAGE_ICON = 1 // Loads an icon
LR_DEFAULTSIZE = 0x00000040 // Loads default-size icon for windows(SM_CXICON x SM_CYICON) if cx, cy are set to zero
LR_LOADFROMFILE = 0x00000010 // Loads the stand-alone image from the file
MF_BYCOMMAND = 0x00000000
MFS_DISABLED = 0x00000003
MFT_SEPARATOR = 0x00000800
MFT_STRING = 0x00000000
+692
View File
@@ -0,0 +1,692 @@
# Local Ollama superbuild targets.
#
# This file keeps the repository-root CMake project focused on orchestration:
# it builds a runnable local Ollama payload by delegating llama.cpp work to the
# llama/server CMake project and building the Go binary into a matching layout.
include(ExternalProject)
set(OLLAMA_LLAMA_BACKENDS "" CACHE STRING
"Semicolon-separated llama-server GPU backends to build: cuda_v12;cuda_v13;rocm_v7_1;rocm_v7_2;vulkan;cuda_jetpack5;cuda_jetpack6")
set(_ollama_mlx_backends_doc "Semicolon-separated MLX backends to build: cuda_v13;metal_v3;metal_v4")
set(OLLAMA_VERSION "0.0.0" CACHE STRING "Ollama version embedded in the local Go binary")
set(OLLAMA_PAYLOAD_INSTALL_PREFIX "${CMAKE_BINARY_DIR}" CACHE PATH
"Build-time staging prefix for nested Ollama native payloads")
string(REGEX REPLACE "^v" "" OLLAMA_VERSION "${OLLAMA_VERSION}")
set(OLLAMA_NATIVE_CONFIG_ARG)
if(CMAKE_CONFIGURATION_TYPES)
set(OLLAMA_NATIVE_CONFIG_ARG --config Release)
endif()
set(OLLAMA_NATIVE_EXTERNAL_OPTIONS)
if(CMAKE_VERSION VERSION_GREATER_EQUAL 3.28)
list(APPEND OLLAMA_NATIVE_EXTERNAL_OPTIONS BUILD_JOB_SERVER_AWARE TRUE)
endif()
function(ollama_check_metal_toolchain output_version)
find_program(_ollama_xcrun xcrun)
if(NOT _ollama_xcrun)
message(FATAL_ERROR
"MLX Metal requires Xcode command line tools. Install Xcode, run "
"`sudo xcode-select -s /Applications/Xcode.app/Contents/Developer`, "
"then install the Metal toolchain with "
"`xcodebuild -downloadComponent MetalToolchain`.")
endif()
execute_process(
COMMAND zsh "-c"
"echo \"__METAL_VERSION__\" | \"${_ollama_xcrun}\" -sdk macosx metal -E -x metal -P - 2>/dev/null | tail -1 | tr -d '\n'"
OUTPUT_VARIABLE _metal_version
RESULT_VARIABLE _metal_result)
if(NOT _metal_result EQUAL 0 OR NOT _metal_version MATCHES "^[0-9]+$")
message(FATAL_ERROR
"MLX Metal requires Xcode's Metal toolchain. Install Xcode, run "
"`sudo xcode-select -s /Applications/Xcode.app/Contents/Developer`, "
"then install the Metal toolchain with "
"`xcodebuild -downloadComponent MetalToolchain`.")
endif()
set(${output_version} "${_metal_version}" PARENT_SCOPE)
endfunction()
function(ollama_macos_major_version output)
execute_process(
COMMAND sw_vers -productVersion
OUTPUT_VARIABLE _macos_version
OUTPUT_STRIP_TRAILING_WHITESPACE
RESULT_VARIABLE _macos_result
ERROR_QUIET)
if(_macos_result EQUAL 0)
string(REGEX MATCH "^[0-9]+" _macos_major "${_macos_version}")
endif()
set(${output} "${_macos_major}" PARENT_SCOPE)
endfunction()
function(ollama_macos_sdk_major_version output)
execute_process(
COMMAND xcrun --sdk macosx --show-sdk-version
OUTPUT_VARIABLE _sdk_version
OUTPUT_STRIP_TRAILING_WHITESPACE
RESULT_VARIABLE _sdk_result
ERROR_QUIET)
if(_sdk_result EQUAL 0)
string(REGEX MATCH "^[0-9]+" _sdk_major "${_sdk_version}")
endif()
set(${output} "${_sdk_major}" PARENT_SCOPE)
endfunction()
function(ollama_default_mlx_backends output)
set(_backends "")
if(APPLE AND CMAKE_SYSTEM_PROCESSOR STREQUAL "arm64")
ollama_check_metal_toolchain(_metal_version)
ollama_macos_major_version(_macos_major)
ollama_macos_sdk_major_version(_sdk_major)
if(_macos_major AND _sdk_major AND _macos_major GREATER_EQUAL 26 AND _sdk_major GREATER_EQUAL 26)
set(_backends "metal_v4")
else()
set(_backends "metal_v3")
endif()
message(STATUS "Defaulting OLLAMA_MLX_BACKENDS=${_backends} for macOS arm64")
endif()
set(${output} "${_backends}" PARENT_SCOPE)
endfunction()
if(NOT DEFINED OLLAMA_MLX_BACKENDS)
ollama_default_mlx_backends(_ollama_default_mlx_backends)
set(OLLAMA_MLX_BACKENDS "${_ollama_default_mlx_backends}" CACHE STRING "${_ollama_mlx_backends_doc}")
else()
set(OLLAMA_MLX_BACKENDS "${OLLAMA_MLX_BACKENDS}" CACHE STRING "${_ollama_mlx_backends_doc}")
endif()
if(NOT OLLAMA_HAVE_LLAMA_SERVER)
if(OLLAMA_LLAMA_BACKENDS)
message(FATAL_ERROR "llama/server is required when OLLAMA_LLAMA_BACKENDS is set")
endif()
if(NOT OLLAMA_MLX_BACKENDS)
message(FATAL_ERROR "llama/server is required for local Ollama builds")
endif()
else()
file(READ "${CMAKE_SOURCE_DIR}/LLAMA_CPP_VERSION" OLLAMA_LLAMA_CPP_GIT_TAG)
string(STRIP "${OLLAMA_LLAMA_CPP_GIT_TAG}" OLLAMA_LLAMA_CPP_GIT_TAG)
include(${CMAKE_SOURCE_DIR}/llama/compat/compat.cmake)
if(DEFINED FETCHCONTENT_SOURCE_DIR_LLAMA_CPP AND NOT "${FETCHCONTENT_SOURCE_DIR_LLAMA_CPP}" STREQUAL "")
get_filename_component(OLLAMA_LLAMA_CPP_SOURCE_DIR
"${FETCHCONTENT_SOURCE_DIR_LLAMA_CPP}" ABSOLUTE BASE_DIR "${CMAKE_SOURCE_DIR}")
message(STATUS "Using llama.cpp source override: ${OLLAMA_LLAMA_CPP_SOURCE_DIR}")
add_custom_target(ollama-llama-cpp-source)
elseif(DEFINED ENV{OLLAMA_LLAMA_CPP_SOURCE})
get_filename_component(OLLAMA_LLAMA_CPP_SOURCE_DIR
"$ENV{OLLAMA_LLAMA_CPP_SOURCE}" ABSOLUTE BASE_DIR "${CMAKE_SOURCE_DIR}")
message(STATUS "Using local llama.cpp source: ${OLLAMA_LLAMA_CPP_SOURCE_DIR}")
add_custom_target(ollama-llama-cpp-source)
else()
set(OLLAMA_LLAMA_CPP_SOURCE_DIR "${CMAKE_BINARY_DIR}/_deps/llama_cpp-src")
ExternalProject_Add(ollama-llama-cpp-source
GIT_REPOSITORY "https://github.com/ggml-org/llama.cpp.git"
GIT_TAG ${OLLAMA_LLAMA_CPP_GIT_TAG}
GIT_SHALLOW TRUE
SOURCE_DIR ${OLLAMA_LLAMA_CPP_SOURCE_DIR}
CONFIGURE_COMMAND ""
BUILD_COMMAND ""
INSTALL_COMMAND ""
PATCH_COMMAND ${OLLAMA_LLAMA_CPP_COMPAT_PATCH_COMMAND}
USES_TERMINAL_DOWNLOAD TRUE
USES_TERMINAL_PATCH TRUE)
endif()
endif()
set(_mlx_source_targets)
if(OLLAMA_MLX_BACKENDS)
file(READ "${CMAKE_SOURCE_DIR}/MLX_VERSION" OLLAMA_MLX_GIT_TAG)
string(STRIP "${OLLAMA_MLX_GIT_TAG}" OLLAMA_MLX_GIT_TAG)
file(READ "${CMAKE_SOURCE_DIR}/MLX_C_VERSION" OLLAMA_MLX_C_GIT_TAG)
string(STRIP "${OLLAMA_MLX_C_GIT_TAG}" OLLAMA_MLX_C_GIT_TAG)
if(DEFINED FETCHCONTENT_SOURCE_DIR_MLX AND NOT "${FETCHCONTENT_SOURCE_DIR_MLX}" STREQUAL "")
get_filename_component(OLLAMA_MLX_SOURCE_DIR
"${FETCHCONTENT_SOURCE_DIR_MLX}" ABSOLUTE BASE_DIR "${CMAKE_SOURCE_DIR}")
message(STATUS "Using MLX source override: ${OLLAMA_MLX_SOURCE_DIR}")
elseif(DEFINED ENV{OLLAMA_MLX_SOURCE})
get_filename_component(OLLAMA_MLX_SOURCE_DIR
"$ENV{OLLAMA_MLX_SOURCE}" ABSOLUTE BASE_DIR "${CMAKE_SOURCE_DIR}")
message(STATUS "Using local MLX source: ${OLLAMA_MLX_SOURCE_DIR}")
else()
set(OLLAMA_MLX_SOURCE_DIR "${CMAKE_BINARY_DIR}/_deps/mlx-src")
ExternalProject_Add(ollama-mlx-source
GIT_REPOSITORY "https://github.com/ml-explore/mlx.git"
GIT_TAG ${OLLAMA_MLX_GIT_TAG}
# MLX uses commit hashes while we track closely; switch to shallow when MLX pins move to tags.
GIT_SHALLOW FALSE
SOURCE_DIR ${OLLAMA_MLX_SOURCE_DIR}
CONFIGURE_COMMAND ""
BUILD_COMMAND ""
INSTALL_COMMAND ""
USES_TERMINAL_DOWNLOAD TRUE)
list(APPEND _mlx_source_targets ollama-mlx-source)
endif()
if(DEFINED "FETCHCONTENT_SOURCE_DIR_MLX-C" AND NOT "${FETCHCONTENT_SOURCE_DIR_MLX-C}" STREQUAL "")
get_filename_component(OLLAMA_MLX_C_SOURCE_DIR
"${FETCHCONTENT_SOURCE_DIR_MLX-C}" ABSOLUTE BASE_DIR "${CMAKE_SOURCE_DIR}")
message(STATUS "Using MLX-C source override: ${OLLAMA_MLX_C_SOURCE_DIR}")
elseif(DEFINED ENV{OLLAMA_MLX_C_SOURCE})
get_filename_component(OLLAMA_MLX_C_SOURCE_DIR
"$ENV{OLLAMA_MLX_C_SOURCE}" ABSOLUTE BASE_DIR "${CMAKE_SOURCE_DIR}")
message(STATUS "Using local MLX-C source: ${OLLAMA_MLX_C_SOURCE_DIR}")
else()
set(OLLAMA_MLX_C_SOURCE_DIR "${CMAKE_BINARY_DIR}/_deps/mlx-c-src")
ExternalProject_Add(ollama-mlx-c-source
GIT_REPOSITORY "https://github.com/ml-explore/mlx-c.git"
GIT_TAG ${OLLAMA_MLX_C_GIT_TAG}
# MLX-C uses commit hashes while we track closely; switch to shallow when MLX-C pins move to tags.
GIT_SHALLOW FALSE
SOURCE_DIR ${OLLAMA_MLX_C_SOURCE_DIR}
CONFIGURE_COMMAND ""
BUILD_COMMAND ""
INSTALL_COMMAND ""
USES_TERMINAL_DOWNLOAD TRUE)
list(APPEND _mlx_source_targets ollama-mlx-c-source)
endif()
add_custom_target(ollama-mlx-sources DEPENDS ${_mlx_source_targets})
endif()
set(OLLAMA_NATIVE_BUILD_TOOL_COMMAND
${CMAKE_COMMAND} --build <BINARY_DIR>)
set(OLLAMA_NATIVE_BUILD_TARGET_ARG --target)
if(CMAKE_GENERATOR MATCHES "Makefiles")
set(OLLAMA_NATIVE_BUILD_TOOL_COMMAND
"$(MAKE)" -C <BINARY_DIR>)
set(OLLAMA_NATIVE_BUILD_TARGET_ARG)
endif()
function(ollama_escape_cmake_list input output)
string(REPLACE ";" "|" _escaped "${input}")
set(${output} "${_escaped}" PARENT_SCOPE)
endfunction()
function(ollama_collect_cache_args_with_prefix prefix output)
get_cmake_property(_cache_variables CACHE_VARIABLES)
list(SORT _cache_variables)
set(_args)
foreach(_var IN LISTS _cache_variables)
if(_var MATCHES "^${prefix}")
ollama_escape_cmake_list("${${_var}}" _value)
list(APPEND _args "-D${_var}=${_value}")
endif()
endforeach()
set(${output} "${_args}" PARENT_SCOPE)
endfunction()
function(ollama_append_cache_arg_if_set output name)
if(DEFINED ${name} AND NOT "${${name}}" STREQUAL "")
ollama_escape_cmake_list("${${name}}" _value)
set(${output} ${${output}} "-D${name}=${_value}" PARENT_SCOPE)
endif()
endfunction()
function(ollama_cache_arg_is_set name output)
if(DEFINED ${name} AND NOT "${${name}}" STREQUAL "")
set(${output} TRUE PARENT_SCOPE)
else()
set(${output} FALSE PARENT_SCOPE)
endif()
endfunction()
function(ollama_llama_cuda_preset backend output)
ollama_cache_arg_is_set(CMAKE_CUDA_ARCHITECTURES _has_cuda_arch)
if(_has_cuda_arch)
set(_preset "llama_${backend}_user_arch")
elseif(WIN32)
set(_preset "llama_${backend}_windows")
else()
set(_preset "llama_${backend}_linux")
endif()
set(${output} "${_preset}" PARENT_SCOPE)
endfunction()
function(ollama_mlx_cuda_preset output)
ollama_cache_arg_is_set(MLX_CUDA_ARCHITECTURES _has_mlx_arch)
ollama_cache_arg_is_set(CMAKE_CUDA_ARCHITECTURES _has_cuda_arch)
if(_has_mlx_arch OR _has_cuda_arch)
set(_preset "mlx_cuda_v13_user_arch")
elseif(WIN32)
set(_preset "mlx_cuda_v13_windows")
else()
set(_preset "mlx_cuda_v13_linux")
endif()
set(${output} "${_preset}" PARENT_SCOPE)
endfunction()
function(ollama_rocm_preset backend output)
ollama_cache_arg_is_set(AMDGPU_TARGETS _has_amdgpu_targets)
ollama_cache_arg_is_set(CMAKE_HIP_ARCHITECTURES _has_hip_arch)
if(_has_amdgpu_targets OR _has_hip_arch)
if(backend STREQUAL "rocm_v7_1" AND NOT WIN32)
message(FATAL_ERROR "OLLAMA_LLAMA_BACKENDS=rocm_v7_1 is only supported for Windows ROCm builds")
elseif(backend STREQUAL "rocm_v7_2" AND WIN32)
message(FATAL_ERROR "OLLAMA_LLAMA_BACKENDS=rocm_v7_2 is only supported for Linux ROCm builds")
endif()
elseif(backend STREQUAL "rocm_v7_1")
if(NOT WIN32)
message(FATAL_ERROR "OLLAMA_LLAMA_BACKENDS=rocm_v7_1 is only supported for Windows ROCm builds")
endif()
set(_preset "${backend}_windows")
elseif(backend STREQUAL "rocm_v7_2")
if(WIN32)
message(FATAL_ERROR "OLLAMA_LLAMA_BACKENDS=rocm_v7_2 is only supported for Linux ROCm builds")
endif()
set(_preset "${backend}_linux")
else()
message(FATAL_ERROR "Unknown ROCm backend '${backend}'")
endif()
if(_has_amdgpu_targets OR _has_hip_arch)
set(_preset "${backend}_user_arch")
endif()
set(${output} "${_preset}" PARENT_SCOPE)
endfunction()
function(ollama_add_llama_server_build name)
cmake_parse_arguments(ARG "" "PRESET;RUNNER_DIR" "TARGETS;CMAKE_ARGS" ${ARGN})
if(NOT ARG_TARGETS)
message(FATAL_ERROR "ollama_add_llama_server_build(${name}) requires TARGETS")
endif()
if(WIN32 AND name STREQUAL "vulkan")
# The Vulkan shader generator nests deeply enough to hit Windows MAX_PATH.
set(_build_dir ${CMAKE_BINARY_DIR}/ls-vk)
else()
set(_build_dir ${CMAKE_BINARY_DIR}/llama-server-${name})
endif()
ollama_collect_cache_args_with_prefix("GGML_" _ggml_cache_args)
ollama_collect_cache_args_with_prefix("LLAMA_" _llama_cache_args)
set(_cmake_args
-DCMAKE_BUILD_TYPE=${CMAKE_BUILD_TYPE}
-DCMAKE_INSTALL_PREFIX=${OLLAMA_PAYLOAD_INSTALL_PREFIX}
-DOLLAMA_LIB_DIR:STRING=${OLLAMA_LIB_DIR}
-DOLLAMA_RUNNER_DIR=${ARG_RUNNER_DIR}
-DFETCHCONTENT_SOURCE_DIR_LLAMA_CPP=${OLLAMA_LLAMA_CPP_SOURCE_DIR}
-DOLLAMA_LLAMA_CPP_SKIP_COMPAT_PATCH=ON
-DGGML_NATIVE=OFF
-DGGML_OPENMP=OFF
${ARG_CMAKE_ARGS}
${_ggml_cache_args}
${_llama_cache_args}
)
if(APPLE)
if(CMAKE_OSX_ARCHITECTURES)
list(APPEND _cmake_args
-DCMAKE_OSX_ARCHITECTURES=${CMAKE_OSX_ARCHITECTURES})
endif()
if(CMAKE_OSX_DEPLOYMENT_TARGET)
list(APPEND _cmake_args
-DCMAKE_OSX_DEPLOYMENT_TARGET=${CMAKE_OSX_DEPLOYMENT_TARGET})
endif()
endif()
set(_configure_command ${CMAKE_COMMAND}
-S ${CMAKE_SOURCE_DIR}/llama/server
-B <BINARY_DIR>
${_cmake_args})
if(ARG_PRESET)
set(_configure_command ${CMAKE_COMMAND}
-S ${CMAKE_SOURCE_DIR}/llama/server
--preset ${ARG_PRESET}
-B <BINARY_DIR>
${_cmake_args})
endif()
ExternalProject_Add(ollama-llama-server-${name}
SOURCE_DIR ${CMAKE_SOURCE_DIR}/llama/server
BINARY_DIR ${_build_dir}
CONFIGURE_COMMAND ${_configure_command}
BUILD_COMMAND ${OLLAMA_NATIVE_BUILD_TOOL_COMMAND}
${OLLAMA_NATIVE_CONFIG_ARG}
${OLLAMA_NATIVE_BUILD_TARGET_ARG} ${ARG_TARGETS}
INSTALL_COMMAND ${CMAKE_COMMAND} --install <BINARY_DIR>
${OLLAMA_NATIVE_CONFIG_ARG}
--component llama-server
DEPENDS ollama-llama-cpp-source
LIST_SEPARATOR |
# ExternalProject cannot reliably infer when nested FetchContent
# sources, compat patches, or forwarded GGML/LLAMA cache settings need
# a rebuild. Always entering the sub-build keeps direct `cmake --build`
# iteration correct; the nested generator still performs incremental
# compilation.
BUILD_ALWAYS TRUE
${OLLAMA_NATIVE_EXTERNAL_OPTIONS}
USES_TERMINAL_CONFIGURE TRUE
USES_TERMINAL_BUILD TRUE
USES_TERMINAL_INSTALL TRUE)
endfunction()
function(ollama_add_mlx_build name)
cmake_parse_arguments(ARG "" "PRESET;RUNNER_DIR" "CMAKE_ARGS" ${ARGN})
if(NOT ARG_RUNNER_DIR)
message(FATAL_ERROR "ollama_add_mlx_build(${name}) requires RUNNER_DIR")
endif()
set(_build_dir ${CMAKE_BINARY_DIR}/${ARG_RUNNER_DIR})
ollama_collect_cache_args_with_prefix("MLX_" _mlx_cache_args)
set(_cmake_args
-DCMAKE_BUILD_TYPE=${CMAKE_BUILD_TYPE}
-DCMAKE_INSTALL_PREFIX=${OLLAMA_PAYLOAD_INSTALL_PREFIX}
-DOLLAMA_LIB_DIR:STRING=${OLLAMA_LIB_DIR}
-DOLLAMA_RUNNER_DIR=${ARG_RUNNER_DIR}
-DOLLAMA_SOURCE_DIR=${CMAKE_SOURCE_DIR}
-DFETCHCONTENT_SOURCE_DIR_MLX=${OLLAMA_MLX_SOURCE_DIR}
-DFETCHCONTENT_SOURCE_DIR_MLX-C=${OLLAMA_MLX_C_SOURCE_DIR}
-DOLLAMA_MLX_GENERATE_WRAPPERS=OFF
${ARG_CMAKE_ARGS}
${_mlx_cache_args}
)
foreach(_arg IN ITEMS
BLAS_INCLUDE_DIRS
LAPACK_INCLUDE_DIRS
CUDAToolkit_ROOT
CUDNN_ROOT_DIR
CUDNN_INCLUDE_PATH
CUDNN_LIBRARY_PATH
CMAKE_CUDA_COMPILER
CMAKE_CUDA_HOST_COMPILER
CMAKE_INCLUDE_PATH
CMAKE_LIBRARY_PATH
CMAKE_PREFIX_PATH)
ollama_append_cache_arg_if_set(_cmake_args ${_arg})
endforeach()
if(APPLE)
if(CMAKE_OSX_ARCHITECTURES)
list(APPEND _cmake_args
-DCMAKE_OSX_ARCHITECTURES=${CMAKE_OSX_ARCHITECTURES})
endif()
endif()
set(_configure_command ${CMAKE_COMMAND}
-S ${CMAKE_SOURCE_DIR}/cmake/mlx
-B <BINARY_DIR>
${_cmake_args})
if(ARG_PRESET)
set(_configure_command ${CMAKE_COMMAND}
-S ${CMAKE_SOURCE_DIR}/cmake/mlx
--preset ${ARG_PRESET}
-B <BINARY_DIR>
${_cmake_args})
endif()
ExternalProject_Add(ollama-mlx-${name}
SOURCE_DIR ${CMAKE_SOURCE_DIR}/cmake/mlx
BINARY_DIR ${_build_dir}
CONFIGURE_COMMAND ${_configure_command}
BUILD_COMMAND ${OLLAMA_NATIVE_BUILD_TOOL_COMMAND}
${OLLAMA_NATIVE_CONFIG_ARG}
${OLLAMA_NATIVE_BUILD_TARGET_ARG} mlx
${OLLAMA_NATIVE_BUILD_TARGET_ARG} mlxc
INSTALL_COMMAND ${CMAKE_COMMAND} --install <BINARY_DIR>
${OLLAMA_NATIVE_CONFIG_ARG}
--component MLX
COMMAND ${CMAKE_COMMAND} --install <BINARY_DIR>
${OLLAMA_NATIVE_CONFIG_ARG}
--component MLX_VENDOR
DEPENDS ollama-mlx-sources
LIST_SEPARATOR |
BUILD_ALWAYS TRUE
${OLLAMA_NATIVE_EXTERNAL_OPTIONS}
USES_TERMINAL_CONFIGURE TRUE
USES_TERMINAL_BUILD TRUE
USES_TERMINAL_INSTALL TRUE)
endfunction()
find_program(GO_EXECUTABLE go)
if(OLLAMA_MLX_BACKENDS)
set(_mlx_c_headers_dir "${OLLAMA_MLX_C_SOURCE_DIR}/mlx/c")
set(_mlx_c_headers_dest "${CMAKE_SOURCE_DIR}/x/mlxrunner/mlx/include/mlx/c")
if(GO_EXECUTABLE AND (NOT APPLE OR CMAKE_SYSTEM_PROCESSOR STREQUAL CMAKE_HOST_SYSTEM_PROCESSOR))
add_custom_target(ollama-mlx-generate-wrappers
COMMAND ${CMAKE_COMMAND}
-DMLX_C_HEADERS_DIR=${_mlx_c_headers_dir}
-DMLX_C_HEADERS_DEST=${_mlx_c_headers_dest}
-P "${CMAKE_SOURCE_DIR}/cmake/vendor-mlx-c-headers.cmake"
COMMAND ${CMAKE_COMMAND} -E env
CC= CGO_CFLAGS= CGO_CXXFLAGS=
${GO_EXECUTABLE} generate ./x/...
WORKING_DIRECTORY ${CMAKE_SOURCE_DIR}
DEPENDS ollama-mlx-sources
COMMENT "Regenerating MLX Go wrappers"
VERBATIM)
else()
add_custom_target(ollama-mlx-generate-wrappers
COMMAND ${CMAKE_COMMAND} -E echo
"Cannot regenerate MLX wrappers while Go is unavailable or while cross-compiling"
COMMAND ${CMAKE_COMMAND} -E false
DEPENDS ollama-mlx-sources
VERBATIM)
endif()
endif()
if(OLLAMA_HAVE_LLAMA_SERVER)
if(NOT OLLAMA_GO_OUTPUT)
if(WIN32)
set(OLLAMA_GO_OUTPUT ${CMAKE_SOURCE_DIR}/ollama.exe)
else()
set(OLLAMA_GO_OUTPUT ${CMAKE_SOURCE_DIR}/ollama)
endif()
endif()
if(NOT IS_ABSOLUTE "${OLLAMA_GO_OUTPUT}")
set(OLLAMA_GO_OUTPUT "${CMAKE_SOURCE_DIR}/${OLLAMA_GO_OUTPUT}")
endif()
get_filename_component(OLLAMA_GO_OUTPUT "${OLLAMA_GO_OUTPUT}" ABSOLUTE)
set(OLLAMA_GO_OUTPUT "${OLLAMA_GO_OUTPUT}" CACHE FILEPATH "Output path for the local Ollama Go binary")
get_filename_component(OLLAMA_GO_OUTPUT_DIR "${OLLAMA_GO_OUTPUT}" DIRECTORY)
set(OLLAMA_GO_LDFLAGS
"-s -w -X=github.com/ollama/ollama/version.Version=${OLLAMA_VERSION} -X=github.com/ollama/ollama/server.mode=release")
if(GO_EXECUTABLE)
add_custom_target(ollama-go ALL
COMMAND ${CMAKE_COMMAND} -E make_directory "${OLLAMA_GO_OUTPUT_DIR}"
COMMAND ${CMAKE_COMMAND} -E env CGO_ENABLED=1
${GO_EXECUTABLE} build -trimpath -ldflags "${OLLAMA_GO_LDFLAGS}" -o "${OLLAMA_GO_OUTPUT}" .
WORKING_DIRECTORY ${CMAKE_SOURCE_DIR}
BYPRODUCTS ${OLLAMA_GO_OUTPUT}
COMMENT "Building Ollama Go binary"
VERBATIM)
else()
add_custom_target(ollama-go ALL
COMMAND ${CMAKE_COMMAND} -E echo
"Go executable not found. Install Go or set GO_EXECUTABLE to build the local Ollama binary."
COMMAND ${CMAKE_COMMAND} -E false
COMMENT "Building Ollama Go binary"
VERBATIM)
endif()
set(_cpu_args)
if(APPLE AND CMAKE_SYSTEM_PROCESSOR STREQUAL "arm64")
list(APPEND _cpu_args
-DBUILD_SHARED_LIBS=OFF
-DGGML_BACKEND_DL=OFF
-DGGML_METAL=ON
-DGGML_METAL_EMBED_LIBRARY=ON)
else()
list(APPEND _cpu_args
-DBUILD_SHARED_LIBS=ON
-DGGML_BACKEND_DL=ON
-DGGML_CPU_ALL_VARIANTS=ON)
if(WIN32)
list(APPEND _cpu_args -DGGML_OPENMP=ON)
endif()
if(APPLE)
list(APPEND _cpu_args -DGGML_METAL=OFF)
endif()
endif()
ollama_add_llama_server_build(local
RUNNER_DIR ""
TARGETS llama-server llama-quantize
CMAKE_ARGS ${_cpu_args})
add_custom_target(ollama-local ALL
DEPENDS ollama-go ollama-llama-server-local
COMMENT "Building local Ollama payload")
install(PROGRAMS "${OLLAMA_GO_OUTPUT}"
DESTINATION "${CMAKE_INSTALL_BINDIR}"
COMPONENT ollama-local)
endif()
set(_backend_targets)
if(OLLAMA_HAVE_LLAMA_SERVER)
foreach(_backend IN LISTS OLLAMA_LLAMA_BACKENDS)
if(_backend STREQUAL "cuda_v12")
ollama_llama_cuda_preset(${_backend} _cuda_preset)
set(_cuda_args)
ollama_append_cache_arg_if_set(_cuda_args CMAKE_CUDA_ARCHITECTURES)
ollama_append_cache_arg_if_set(_cuda_args CMAKE_CUDA_FLAGS)
ollama_add_llama_server_build(${_backend}
PRESET ${_cuda_preset}
RUNNER_DIR ${_backend}
TARGETS ggml-cuda
CMAKE_ARGS ${_cuda_args})
list(APPEND _backend_targets ollama-llama-server-${_backend})
elseif(_backend STREQUAL "cuda_v13")
ollama_llama_cuda_preset(${_backend} _cuda_preset)
set(_cuda_args)
ollama_append_cache_arg_if_set(_cuda_args CMAKE_CUDA_ARCHITECTURES)
ollama_append_cache_arg_if_set(_cuda_args CMAKE_CUDA_FLAGS)
ollama_add_llama_server_build(${_backend}
PRESET ${_cuda_preset}
RUNNER_DIR ${_backend}
TARGETS ggml-cuda
CMAKE_ARGS ${_cuda_args})
list(APPEND _backend_targets ollama-llama-server-${_backend})
elseif(_backend STREQUAL "rocm_v7_1" OR _backend STREQUAL "rocm_v7_2")
# ROCm 7.1 and 7.2 currently share build settings. Keep the backend
# names versioned so future packaging can install side-by-side ROCm
# payloads without changing the superbuild interface.
ollama_rocm_preset(${_backend} _rocm_preset)
set(_rocm_args
-DBUILD_SHARED_LIBS=ON
-DGGML_BACKEND_DL=ON
-DGGML_HIP=ON
-DCMAKE_HIP_PLATFORM=amd
-DOLLAMA_GPU_BACKEND=hip)
ollama_append_cache_arg_if_set(_rocm_args AMDGPU_TARGETS)
ollama_append_cache_arg_if_set(_rocm_args CMAKE_HIP_ARCHITECTURES)
ollama_append_cache_arg_if_set(_rocm_args CMAKE_HIP_FLAGS)
ollama_append_cache_arg_if_set(_rocm_args GGML_CUDA_NO_PEER_COPY)
ollama_append_cache_arg_if_set(_rocm_args CMAKE_PREFIX_PATH)
ollama_add_llama_server_build(${_backend}
PRESET ${_rocm_preset}
RUNNER_DIR ${_backend}
TARGETS ggml-hip
CMAKE_ARGS ${_rocm_args})
list(APPEND _backend_targets ollama-llama-server-${_backend})
elseif(_backend STREQUAL "vulkan")
ollama_add_llama_server_build(vulkan
RUNNER_DIR vulkan
TARGETS ggml-vulkan
CMAKE_ARGS
-DBUILD_SHARED_LIBS=ON
-DGGML_BACKEND_DL=ON
-DGGML_VULKAN=ON
-DOLLAMA_GPU_BACKEND=vulkan)
list(APPEND _backend_targets ollama-llama-server-vulkan)
elseif(_backend STREQUAL "cuda_jetpack5")
if(CMAKE_CUDA_ARCHITECTURES)
set(_cuda_preset llama_cuda_jetpack5_user_arch)
else()
set(_cuda_preset llama_cuda_jetpack5)
endif()
set(_cuda_args)
ollama_append_cache_arg_if_set(_cuda_args CMAKE_CUDA_ARCHITECTURES)
ollama_append_cache_arg_if_set(_cuda_args CMAKE_CUDA_FLAGS)
ollama_add_llama_server_build(${_backend}
PRESET ${_cuda_preset}
RUNNER_DIR ${_backend}
TARGETS ggml-cuda
CMAKE_ARGS ${_cuda_args})
list(APPEND _backend_targets ollama-llama-server-${_backend})
elseif(_backend STREQUAL "cuda_jetpack6")
if(CMAKE_CUDA_ARCHITECTURES)
set(_cuda_preset llama_cuda_jetpack6_user_arch)
else()
set(_cuda_preset llama_cuda_jetpack6)
endif()
set(_cuda_args)
ollama_append_cache_arg_if_set(_cuda_args CMAKE_CUDA_ARCHITECTURES)
ollama_append_cache_arg_if_set(_cuda_args CMAKE_CUDA_FLAGS)
ollama_add_llama_server_build(${_backend}
PRESET ${_cuda_preset}
RUNNER_DIR ${_backend}
TARGETS ggml-cuda
CMAKE_ARGS ${_cuda_args})
list(APPEND _backend_targets ollama-llama-server-${_backend})
else()
message(FATAL_ERROR
"Unknown OLLAMA_LLAMA_BACKENDS entry '${_backend}'")
endif()
endforeach()
endif()
if(_backend_targets)
add_custom_target(ollama-llama-server-backends ALL
DEPENDS ${_backend_targets}
COMMENT "Building llama-server GPU backends")
endif()
set(_mlx_targets)
foreach(_backend IN LISTS OLLAMA_MLX_BACKENDS)
if(_backend STREQUAL "cuda_v13")
ollama_mlx_cuda_preset(_mlx_cuda_preset)
set(_mlx_cuda_args)
ollama_append_cache_arg_if_set(_mlx_cuda_args CMAKE_CUDA_ARCHITECTURES)
ollama_append_cache_arg_if_set(_mlx_cuda_args MLX_CUDA_ARCHITECTURES)
ollama_append_cache_arg_if_set(_mlx_cuda_args CMAKE_CUDA_FLAGS)
ollama_add_mlx_build(cuda_v13
PRESET ${_mlx_cuda_preset}
RUNNER_DIR mlx_cuda_v13
CMAKE_ARGS ${_mlx_cuda_args})
list(APPEND _mlx_targets ollama-mlx-cuda_v13)
elseif(_backend STREQUAL "metal_v3")
if(NOT APPLE)
message(FATAL_ERROR "OLLAMA_MLX_BACKENDS=metal_v3 is only supported on macOS")
endif()
ollama_check_metal_toolchain(_metal_version)
ollama_add_mlx_build(metal_v3
PRESET mlx_metal_v3
RUNNER_DIR mlx_metal_v3)
list(APPEND _mlx_targets ollama-mlx-metal_v3)
elseif(_backend STREQUAL "metal_v4")
if(NOT APPLE)
message(FATAL_ERROR "OLLAMA_MLX_BACKENDS=metal_v4 is only supported on macOS")
endif()
ollama_check_metal_toolchain(_metal_version)
ollama_macos_sdk_major_version(_ollama_mlx_sdk_major)
if(_ollama_mlx_sdk_major AND _ollama_mlx_sdk_major GREATER_EQUAL 26)
ollama_add_mlx_build(metal_v4
PRESET mlx_metal_v4
RUNNER_DIR mlx_metal_v4)
list(APPEND _mlx_targets ollama-mlx-metal_v4)
else()
message(FATAL_ERROR
"OLLAMA_MLX_BACKENDS=metal_v4 requires the macOS 26 SDK. "
"Install a newer Xcode or use OLLAMA_MLX_BACKENDS=metal_v3.")
endif()
else()
message(FATAL_ERROR
"Unknown OLLAMA_MLX_BACKENDS entry '${_backend}'")
endif()
endforeach()
if(_mlx_targets)
add_custom_target(ollama-mlx-backends ALL
DEPENDS ${_mlx_targets}
COMMENT "Building MLX backends")
endif()
install(DIRECTORY "${OLLAMA_PAYLOAD_INSTALL_PREFIX}/${OLLAMA_LIB_DIR}/"
DESTINATION "${OLLAMA_LIB_DIR}"
COMPONENT ollama-local
USE_SOURCE_PERMISSIONS)
+235
View File
@@ -0,0 +1,235 @@
cmake_minimum_required(VERSION 3.24)
project(OllamaMLX C CXX)
include(CheckLanguage)
include(GNUInstallDirs)
find_package(Threads REQUIRED)
if(NOT CMAKE_CONFIGURATION_TYPES AND NOT CMAKE_BUILD_TYPE)
set(CMAKE_BUILD_TYPE Release CACHE STRING "Build type" FORCE)
endif()
if(NOT DEFINED BUILD_SHARED_LIBS)
set(BUILD_SHARED_LIBS ON)
endif()
set(CMAKE_CXX_STANDARD 17)
set(CMAKE_CXX_STANDARD_REQUIRED ON)
set(CMAKE_CXX_EXTENSIONS ON)
if(APPLE)
set(CMAKE_BUILD_RPATH "@loader_path")
set(CMAKE_INSTALL_RPATH "@loader_path")
set(CMAKE_BUILD_WITH_INSTALL_RPATH ON)
endif()
if(NOT DEFINED OLLAMA_SOURCE_DIR OR "${OLLAMA_SOURCE_DIR}" STREQUAL "")
get_filename_component(OLLAMA_SOURCE_DIR "${CMAKE_CURRENT_LIST_DIR}/../.." ABSOLUTE)
endif()
get_filename_component(OLLAMA_SOURCE_DIR "${OLLAMA_SOURCE_DIR}" ABSOLUTE BASE_DIR "${CMAKE_CURRENT_LIST_DIR}")
set(OLLAMA_SOURCE_DIR "${OLLAMA_SOURCE_DIR}" CACHE PATH "Ollama repository root")
set(OLLAMA_LIB_DIR "lib/ollama" CACHE STRING "Install destination for Ollama runtime payloads")
set(OLLAMA_RUNNER_DIR "" CACHE STRING "Ollama runtime payload subdirectory")
set(OLLAMA_BUILD_DIR ${CMAKE_BINARY_DIR}/lib/ollama)
set(OLLAMA_INSTALL_DIR ${OLLAMA_LIB_DIR}/${OLLAMA_RUNNER_DIR})
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${OLLAMA_BUILD_DIR})
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY_DEBUG ${OLLAMA_BUILD_DIR})
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY_RELEASE ${OLLAMA_BUILD_DIR})
set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${OLLAMA_BUILD_DIR})
set(CMAKE_LIBRARY_OUTPUT_DIRECTORY_DEBUG ${OLLAMA_BUILD_DIR})
set(CMAKE_LIBRARY_OUTPUT_DIRECTORY_RELEASE ${OLLAMA_BUILD_DIR})
if(MLX_CUDA_ARCHITECTURES OR CMAKE_CUDA_ARCHITECTURES)
check_language(CUDA)
endif()
option(OLLAMA_MLX_GENERATE_WRAPPERS "Regenerate MLX Go wrappers" OFF)
message(STATUS "Setting up MLX (this takes a while...)")
add_subdirectory(${OLLAMA_SOURCE_DIR}/x/imagegen/mlx ${CMAKE_BINARY_DIR}/x/imagegen/mlx)
# Find CUDA toolkit if MLX is built with CUDA support.
find_package(CUDAToolkit)
# Build list of directories for runtime dependency resolution.
set(MLX_RUNTIME_DIRS ${CUDAToolkit_BIN_DIR} ${CUDAToolkit_BIN_DIR}/x64 ${CUDAToolkit_LIBRARY_DIR})
# Add cuDNN bin paths for DLLs (Windows MLX CUDA builds).
# CUDNN_ROOT_DIR is the standard CMake variable for cuDNN location.
if(CUDNN_ROOT_DIR)
set(_cudnn_root "${CUDNN_ROOT_DIR}")
elseif(DEFINED ENV{CUDNN_ROOT_DIR})
set(_cudnn_root "$ENV{CUDNN_ROOT_DIR}")
endif()
if(_cudnn_root)
# cuDNN 9.x has versioned subdirectories under bin/ (e.g., bin/13.0/).
file(GLOB CUDNN_BIN_SUBDIRS "${_cudnn_root}/bin/*")
list(APPEND MLX_RUNTIME_DIRS ${CUDNN_BIN_SUBDIRS})
endif()
# Add build output directory and MLX dependency build directories.
list(APPEND MLX_RUNTIME_DIRS ${OLLAMA_BUILD_DIR})
# OpenBLAS DLL location (pre-built zip extracts into openblas-src/bin/).
list(APPEND MLX_RUNTIME_DIRS ${CMAKE_BINARY_DIR}/_deps/openblas-src/bin)
# NCCL: on Linux, if real NCCL is found, cmake bundles libnccl.so via the
# regex below. If NCCL is not found, MLX links a static stub (OBJECT lib)
# so there is no runtime dependency. This path covers the stub build dir
# for windows so we include the DLL in our dependencies.
list(APPEND MLX_RUNTIME_DIRS ${CMAKE_BINARY_DIR}/_deps/mlx-build/mlx/distributed/nccl/nccl_stub-prefix/src/nccl_stub-build/Release)
# Base regexes for runtime dependencies (cross-platform).
set(MLX_INCLUDE_REGEXES cublas cublasLt cudart cufft nvrtc nvrtc-builtins cudnn nccl openblas gfortran)
# On Windows, also include dl.dll (dlfcn-win32 POSIX emulation layer).
if(WIN32)
list(APPEND MLX_INCLUDE_REGEXES "^dl\\.dll$")
endif()
# Keep mlx/mlxc targets separate from runtime dependencies so --strip only
# applies to the binaries we build, not vendor DLLs/libs.
install(TARGETS mlx mlxc
RUNTIME_DEPENDENCY_SET mlx_runtime_deps
RUNTIME DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT MLX
LIBRARY DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT MLX
FRAMEWORK DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT MLX
)
install(RUNTIME_DEPENDENCY_SET mlx_runtime_deps
DIRECTORIES ${MLX_RUNTIME_DIRS}
PRE_INCLUDE_REGEXES ${MLX_INCLUDE_REGEXES}
PRE_EXCLUDE_REGEXES ".*"
RUNTIME DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT MLX_VENDOR
LIBRARY DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT MLX_VENDOR
)
if(TARGET jaccl)
install(TARGETS jaccl
RUNTIME DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT MLX
LIBRARY DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT MLX
FRAMEWORK DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT MLX
)
endif()
# Install the Metal library for macOS arm64 (must be colocated with the binary).
# Metal backend is only built for arm64, not x86_64.
if(APPLE AND CMAKE_SYSTEM_PROCESSOR STREQUAL "arm64")
install(FILES ${CMAKE_BINARY_DIR}/_deps/mlx-build/mlx/backend/metal/kernels/mlx.metallib
DESTINATION ${OLLAMA_INSTALL_DIR}
COMPONENT MLX)
endif()
# Install headers for NVRTC JIT compilation at runtime.
# MLX's own install rules use the default component so they get skipped by
# --component MLX. Headers are installed alongside libmlx in OLLAMA_INSTALL_DIR.
#
# Layout:
# ${OLLAMA_INSTALL_DIR}/include/cccl/{cuda,nv}/ - CCCL headers
# ${OLLAMA_INSTALL_DIR}/include/*.h - CUDA toolkit headers
#
# MLX's jit_module.cpp resolves CCCL via
# current_binary_dir()[.parent_path()] / "include" / "cccl"
# On Linux, MLX's jit_module.cpp resolves CCCL via
# current_binary_dir().parent_path() / "include" / "cccl", so we create a
# symlink from lib/ollama/include -> ${OLLAMA_RUNNER_DIR}/include.
# This will need refinement if we add multiple CUDA versions for MLX in the future.
# CUDA runtime headers are found via CUDA_PATH env var (set by mlxrunner).
if(EXISTS ${CMAKE_BINARY_DIR}/_deps/cccl-src/include/cuda)
install(DIRECTORY ${CMAKE_BINARY_DIR}/_deps/cccl-src/include/cuda
DESTINATION ${OLLAMA_INSTALL_DIR}/include/cccl
COMPONENT MLX)
install(DIRECTORY ${CMAKE_BINARY_DIR}/_deps/cccl-src/include/nv
DESTINATION ${OLLAMA_INSTALL_DIR}/include/cccl
COMPONENT MLX)
endif()
# Install minimal CUDA toolkit headers needed by MLX JIT kernels.
# These are the transitive closure of includes from mlx/backend/cuda/device/*.cuh.
# The Go mlxrunner sets CUDA_PATH to OLLAMA_INSTALL_DIR so MLX finds them at
# $CUDA_PATH/include/*.h via NVRTC --include-path.
if(CUDAToolkit_FOUND)
# CUDAToolkit_INCLUDE_DIRS may be a semicolon-separated list
# (e.g. ".../include;.../include/cccl"). Find the entry that
# contains the CUDA runtime headers we need.
set(_cuda_inc "")
foreach(_dir ${CUDAToolkit_INCLUDE_DIRS})
if(EXISTS "${_dir}/cuda_runtime_api.h")
set(_cuda_inc "${_dir}")
break()
endif()
endforeach()
if(NOT _cuda_inc)
message(WARNING "Could not find cuda_runtime_api.h in CUDAToolkit_INCLUDE_DIRS: ${CUDAToolkit_INCLUDE_DIRS}")
else()
set(_dst "${OLLAMA_INSTALL_DIR}/include")
set(_MLX_JIT_CUDA_HEADERS
builtin_types.h
cooperative_groups.h
cuda_bf16.h
cuda_bf16.hpp
cuda_device_runtime_api.h
cuda_fp16.h
cuda_fp16.hpp
cuda_fp8.h
cuda_fp8.hpp
cuda_runtime_api.h
device_types.h
driver_types.h
math_constants.h
surface_types.h
texture_types.h
vector_functions.h
vector_functions.hpp
vector_types.h
)
foreach(_hdr ${_MLX_JIT_CUDA_HEADERS})
install(FILES "${_cuda_inc}/${_hdr}"
DESTINATION ${_dst}
COMPONENT MLX)
endforeach()
# Subdirectory headers.
install(DIRECTORY "${_cuda_inc}/cooperative_groups"
DESTINATION ${_dst}
COMPONENT MLX
FILES_MATCHING PATTERN "*.h")
install(FILES "${_cuda_inc}/crt/host_defines.h"
DESTINATION "${_dst}/crt"
COMPONENT MLX)
if(NOT WIN32 AND NOT APPLE)
install(CODE "
set(_link \"${CMAKE_INSTALL_PREFIX}/${OLLAMA_LIB_DIR}/include\")
set(_target \"${OLLAMA_RUNNER_DIR}/include\")
if(NOT EXISTS \${_link})
execute_process(COMMAND \${CMAKE_COMMAND} -E create_symlink \${_target} \${_link})
endif()
" COMPONENT MLX)
endif()
endif()
endif()
# On Windows, explicitly install dl.dll (dlfcn-win32 POSIX dlopen emulation).
# RUNTIME_DEPENDENCIES auto-excludes it via POST_EXCLUDE_FILES_STRICT because
# dlfcn-win32 is a known CMake target with its own install rules (which install
# to the wrong destination). We must install it explicitly here.
if(WIN32)
install(FILES ${OLLAMA_BUILD_DIR}/dl.dll
DESTINATION ${OLLAMA_INSTALL_DIR}
COMPONENT MLX)
endif()
# Manually install CUDA runtime libraries that MLX loads via dlopen
# (not detected by RUNTIME_DEPENDENCIES since they aren't link-time deps).
if(CUDAToolkit_FOUND)
file(GLOB MLX_CUDA_LIBS
"${CUDAToolkit_LIBRARY_DIR}/libcudart.so*"
"${CUDAToolkit_LIBRARY_DIR}/libcublas.so*"
"${CUDAToolkit_LIBRARY_DIR}/libcublasLt.so*"
"${CUDAToolkit_LIBRARY_DIR}/libnvrtc.so*"
"${CUDAToolkit_LIBRARY_DIR}/libnvrtc-builtins.so*"
"${CUDAToolkit_LIBRARY_DIR}/libcufft.so*"
"${CUDAToolkit_LIBRARY_DIR}/libcudnn.so*")
if(MLX_CUDA_LIBS)
install(FILES ${MLX_CUDA_LIBS}
DESTINATION ${OLLAMA_INSTALL_DIR}
COMPONENT MLX_VENDOR)
endif()
endif()
+90
View File
@@ -0,0 +1,90 @@
{
"version": 3,
"configurePresets": [
{
"name": "default",
"binaryDir": "${sourceDir}/../../build/mlx",
"installDir": "${sourceDir}/../../dist",
"cacheVariables": {
"CMAKE_BUILD_TYPE": "Release",
"CMAKE_MSVC_RUNTIME_LIBRARY": "MultiThreaded",
"OLLAMA_SOURCE_DIR": "${sourceDir}/../.."
}
},
{
"name": "mlx_cuda_v13_base",
"hidden": true,
"inherits": [ "default" ],
"cacheVariables": {
"CMAKE_CUDA_FLAGS": "-t 2",
"OLLAMA_RUNNER_DIR": "mlx_cuda_v13"
}
},
{
"name": "mlx_cuda_v13_linux",
"inherits": [ "mlx_cuda_v13_base" ],
"binaryDir": "${sourceDir}/../../build/mlx_cuda_v13",
"cacheVariables": {
"MLX_CUDA_ARCHITECTURES": "75-virtual;80-virtual;86-virtual;89-virtual;90-virtual;90a-virtual;100-virtual;103-virtual;110-virtual;120-virtual;121-virtual"
}
},
{
"name": "mlx_cuda_v13_windows",
"inherits": [ "mlx_cuda_v13_base" ],
"binaryDir": "${sourceDir}/../../build/mlx_cuda_v13",
"cacheVariables": {
"MLX_CUDA_ARCHITECTURES": "75-virtual;80-virtual;86-virtual;89-virtual;90-virtual;90a-virtual;100-virtual;103-virtual;110-virtual;120-virtual;121-virtual"
}
},
{
"name": "mlx_cuda_v13_user_arch",
"inherits": [ "mlx_cuda_v13_base" ],
"binaryDir": "${sourceDir}/../../build/mlx_cuda_v13"
},
{
"name": "mlx_metal_v3",
"inherits": [ "default" ],
"binaryDir": "${sourceDir}/../../build/metal-v3",
"cacheVariables": {
"CMAKE_OSX_DEPLOYMENT_TARGET": "14.0",
"OLLAMA_RUNNER_DIR": "mlx_metal_v3"
}
},
{
"name": "mlx_metal_v4",
"inherits": [ "default" ],
"binaryDir": "${sourceDir}/../../build/metal-v4",
"cacheVariables": {
"CMAKE_OSX_DEPLOYMENT_TARGET": "26.0",
"OLLAMA_RUNNER_DIR": "mlx_metal_v4"
}
}
],
"buildPresets": [
{
"name": "mlx_cuda_v13_linux",
"configurePreset": "mlx_cuda_v13_linux",
"targets": [ "mlx", "mlxc" ]
},
{
"name": "mlx_cuda_v13_windows",
"configurePreset": "mlx_cuda_v13_windows",
"targets": [ "mlx", "mlxc" ]
},
{
"name": "mlx_cuda_v13_user_arch",
"configurePreset": "mlx_cuda_v13_user_arch",
"targets": [ "mlx", "mlxc" ]
},
{
"name": "mlx_metal_v3",
"configurePreset": "mlx_metal_v3",
"targets": [ "mlx", "mlxc" ]
},
{
"name": "mlx_metal_v4",
"configurePreset": "mlx_metal_v4",
"targets": [ "mlx", "mlxc" ]
}
]
}
+14
View File
@@ -0,0 +1,14 @@
if(NOT DEFINED MLX_C_HEADERS_DIR OR NOT IS_DIRECTORY "${MLX_C_HEADERS_DIR}")
message(FATAL_ERROR "MLX_C_HEADERS_DIR does not exist: ${MLX_C_HEADERS_DIR}")
endif()
if(NOT DEFINED MLX_C_HEADERS_DEST OR "${MLX_C_HEADERS_DEST}" STREQUAL "")
message(FATAL_ERROR "MLX_C_HEADERS_DEST is required")
endif()
file(GLOB _mlx_c_headers LIST_DIRECTORIES false "${MLX_C_HEADERS_DIR}/*.h")
if(NOT _mlx_c_headers)
message(FATAL_ERROR "No MLX-C headers found in ${MLX_C_HEADERS_DIR}")
endif()
file(MAKE_DIRECTORY "${MLX_C_HEADERS_DEST}")
file(COPY ${_mlx_c_headers} DESTINATION "${MLX_C_HEADERS_DEST}")

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