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Author SHA1 Message Date
Dax Raad 80865407e0 refactor(sdk): remove local legacy package
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2026-07-26 02:47:43 -04:00
Dax Raad 28f4284bd7 fix(www): canonicalize production routes 2026-07-26 02:39:12 -04:00
Aiden Cline 7affee529b fix(core): harden grep search behavior (#38922) 2026-07-25 23:23:53 -05:00
Aiden Cline 79c7e9446e fix(core): clarify custom question answers (#38919) 2026-07-25 23:00:26 -05:00
Shoubhit Dash efb629a33a feat(core): add pluggable web search (#35558)
Co-authored-by: Dax Raad <d@ironbay.co>
2026-07-26 03:55:05 +00:00
Dax Raad 2ddc91a0e8 fix(tui): show shell working directory in prompt 2026-07-25 23:42:53 -04:00
Dax Raad c7871e14d4 fix(www): remove deployment environment gate 2026-07-25 21:21:57 -04:00
Dax Raad 9840f63b12 chore(www): simplify worker routes 2026-07-25 21:17:25 -04:00
Dax Raad 56a9c0150a fix(www): mark deploy script as module 2026-07-25 21:17:25 -04:00
Dax Raad 203a0613b8 feat(www): migrate docs to Blume 2026-07-25 21:17:25 -04:00
Aiden Cline 7d8f1bdab3 tweak(core): simplify skill tool description (#38900) 2026-07-25 17:09:20 -05:00
Aiden Cline 9eea5bc925 fix(core): tweak glob tool description/parameters (#38899) 2026-07-25 16:52:36 -05:00
Aiden Cline f753103e82 fix(core): reject file glob roots (#38890) 2026-07-25 14:43:18 -05:00
Aiden Cline 1e35d33ecb fix(codemode): search nested namespaces (#38887) 2026-07-25 14:17:49 -05:00
Aiden Cline c5bf4edb10 fix(ai): preserve response message phases (#38777) 2026-07-25 14:06:00 -05:00
Aiden Cline cce8bb0e1c fix(core): clarify empty Code Mode guidance (#38883) 2026-07-25 13:20:16 -05:00
Dax Raad 02c66c5fc1 docs(core): fix OpenCode skill links 2026-07-25 14:08:29 -04:00
Aiden Cline 33390cc457 fix(core): keep execute tool cache stable (#38783) 2026-07-25 13:01:05 -05:00
Kit Langton b2afb35527 refactor(core): settle steps lock-free by joining tool fibers first (#38743) 2026-07-25 13:43:17 -04:00
opencode-agent[bot] 828148909d fix(tui): preserve workspace while reconnecting (#38788)
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2026-07-25 03:48:42 +00:00
opencode-agent[bot] 454145fe65 fix(tui): preserve workspace while reconnecting (#38788) 2026-07-25 02:22:47 +00:00
Aiden Cline 1291dc1f11 fix(core): clarify code mode tool boundary (#38785) 2026-07-24 20:49:55 -05:00
Aiden Cline c7d7f61146 fix(ai): preserve Anthropic usage metadata (#38751) 2026-07-24 16:23:51 -05:00
Aiden Cline 13b6845e7e fix(core): scope MCP execute guidance to Code Mode (#38753) 2026-07-24 16:02:57 -05:00
Aiden Cline d1d97014b4 refactor(core): move static Code Mode guidance (#38746) 2026-07-24 14:46:59 -05:00
Aiden Cline b31747124b fix(core): stream Code Mode tool progress (#38718) 2026-07-24 14:46:46 -05:00
Aiden Cline 49bec25ae5 fix(ai): align Anthropic stream handling (#38733) 2026-07-24 14:23:35 -05:00
Aiden Cline d66d0cb904 fix(core): clarify Code Mode tool availability (#38745) 2026-07-24 13:44:59 -05:00
Kit Langton 3193f3aa95 fix(tui): flag likely cache busts accurately (#38727) 2026-07-24 18:35:13 +00:00
Aiden Cline ee5460a152 fix(codemode): report interrupted tool calls (#38741) 2026-07-24 13:32:54 -05:00
Kit Langton b09a066fb5 fix(ai): report OpenAI cache writes (#38735) 2026-07-24 18:26:30 +00:00
Aiden Cline 423fad730c fix(core): authorize external glob paths (#38714) 2026-07-24 13:24:23 -05:00
Kit Langton 5ae2d6d3f6 refactor(core): settle declined tool calls durably with typed reasons (#38734) 2026-07-24 18:18:02 +00:00
Kit Langton 993f046dd9 fix(ai): layer prompt cache breakpoints (#38725) 2026-07-24 18:02:35 +00:00
opencode-agent[bot] 9b640cf97d test(core): remove flaky npm install test (#38729)
Co-authored-by: Aiden Cline <rekram1-node@users.noreply.github.com>
2026-07-24 12:33:28 -05:00
Kit Langton 2200d100d0 refactor(core): name the unsettled-tool sweep scope and untangle hosted settlement (#38724) 2026-07-24 13:32:14 -04:00
Kit Langton 68ef893818 fix(core): start all suspended sessions promptly (#38720) 2026-07-24 16:58:50 +00:00
Kit Langton 7ab3dd04ad refactor(core): unify tool fiber bookkeeping into one owned structure (#38719) 2026-07-24 16:55:43 +00:00
Aiden Cline 4f201f87a9 fix(ai): align Bedrock stream handling (#38712) 2026-07-24 11:15:23 -05:00
Kit Langton 5aa276c117 refactor(core): mint assistant message identity before the step runs (#38717) 2026-07-24 16:11:31 +00:00
Aiden Cline 4605308be2 feat(core): render CodeMode catalog deltas from structured snapshots (#38183) 2026-07-24 10:20:26 -05:00
Aiden Cline c64d813347 fix(core): report truncated glob results (#38631) 2026-07-24 10:17:37 -05:00
Kit Langton 6e4a972bb9 refactor(core): clean up callModel readability (#38706) 2026-07-24 11:17:20 -04:00
Kit Langton 835149e42b refactor(core): select small model without sorting (#38707) 2026-07-24 11:08:57 -04:00
Kit Langton 0f3c30118c refactor(core): simplify session runner loop and pending input scopes (#38602) 2026-07-24 14:27:23 +00:00
Shoubhit Dash 35d31d8ec1 refactor(ai): remove dead LLM exports (#38700) 2026-07-24 14:19:07 +00:00
Shoubhit Dash 0374d29232 refactor(ai): colocate provider options (#38698) 2026-07-24 19:08:36 +05:30
Shoubhit Dash d90da82be2 refactor(ai): normalize provider option parsing (#38695) 2026-07-24 19:02:02 +05:30
Shoubhit Dash c06186a9d9 fix(ai): forward Anthropic provider options (#38694) 2026-07-24 18:50:20 +05:30
Shoubhit Dash c5680a206e refactor(ai): make OpenAI Responses extend Open Responses (#38681) 2026-07-24 18:36:35 +05:30
Simon Klee edaee143d9 mini: reserve headroom before showing usage (#38659) 2026-07-24 11:23:53 +02:00
Simon Klee 4184149b90 mini: monochrome rendered markdown only (#38656) 2026-07-24 11:14:48 +02:00
Simon Klee 00f063b381 mini: pack statusline by content width (#38646) 2026-07-24 10:54:30 +02:00
Aiden Cline ea010ab3a4 feat(ai): round-trip Bedrock redacted reasoning (#38623)
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2026-07-24 01:06:58 -05:00
Aiden Cline 65c5c7e3f6 feat(ai): round-trip Anthropic redacted thinking blocks (#38614) 2026-07-24 00:42:44 -05:00
opencode-agent[bot] ee69a91f26 docs: add ideal pseudocode skill (#38611)
Co-authored-by: Aiden Cline <rekram1-node@users.noreply.github.com>
2026-07-23 23:02:44 -05:00
Kit Langton 7456598cde fix(core): share one tool snapshot per request (#38596) 2026-07-24 02:54:22 +00:00
Kit Langton c228fc4886 fix(core): stabilize tool definition ordering (#38590) 2026-07-23 21:30:06 -04:00
Kit Langton bb3f4cc3c7 fix(codemode): stabilize catalog ordering (#38588) 2026-07-23 20:56:18 -04:00
Aiden Cline 8d9727be9f fix(core): improve patch errors (#38369) 2026-07-23 18:59:29 -05:00
Aiden Cline 6401eeaea0 feat(ai): preserve raw finish reasons (#38423) 2026-07-23 18:16:11 -05:00
Kit Langton e7ecee5df2 fix(core): isolate tool hook outcomes (#38571) 2026-07-23 17:40:42 -04:00
opencode-agent[bot] 02f2725154 chore: merge dev into v2 (#38563)
Co-authored-by: Aiden Cline <rekram1-node@users.noreply.github.com>
Co-authored-by: opencode-agent[bot] <219766164+opencode-agent[bot]@users.noreply.github.com>
Co-authored-by: Dax Raad <d@ironbay.co>
Co-authored-by: Dax <mail@thdxr.com>
Co-authored-by: opencode-agent[bot] <opencode-agent[bot]@users.noreply.github.com>
Co-authored-by: Aiden Cline <63023139+rekram1-node@users.noreply.github.com>
Co-authored-by: Nabs <nabil@instafork.com>
Co-authored-by: usrnk1 <7547651+usrnk1@users.noreply.github.com>
Co-authored-by: Brendan Allan <14191578+Brendonovich@users.noreply.github.com>
Co-authored-by: Aarav Sareen <96787824+arvsrn@users.noreply.github.com>
Co-authored-by: Brendan Allan <git@brendonovich.dev>
Co-authored-by: Victor Navarro <vn4varro@gmail.com>
Co-authored-by: Vladimir Glafirov <vglafirov@gitlab.com>
Co-authored-by: AidenGeunGeun <eastlandwyvern@gmail.com>
Co-authored-by: Mark <geraint0923@users.noreply.github.com>
Co-authored-by: Aiden Cline <aidenpcline@gmail.com>
Co-authored-by: Adam <2363879+adamdotdevin@users.noreply.github.com>
Co-authored-by: opencode <opencode@sst.dev>
Co-authored-by: Luke Parker <10430890+Hona@users.noreply.github.com>
Co-authored-by: David Hill <1879069+iamdavidhill@users.noreply.github.com>
Co-authored-by: Jay <air@live.ca>
Co-authored-by: Jay <53023+jayair@users.noreply.github.com>
Co-authored-by: BB84 <110078428+BB-84C@users.noreply.github.com>
Co-authored-by: Dustin Deus <deusdustin@gmail.com>
Co-authored-by: Frank <frank@anoma.ly>
Co-authored-by: Jack <jack@anoma.ly>
Co-authored-by: Sebastian <hasta84@gmail.com>
Co-authored-by: Jérôme Benoit <jerome.benoit@sap.com>
Co-authored-by: Test User <test@test.com>
Co-authored-by: Simon Klee <hello@simonklee.dk>
Co-authored-by: Rahul A Mistry <149420892+ProdigyRahul@users.noreply.github.com>
Co-authored-by: Qiping Li <liqiping1991@gmail.com>
Co-authored-by: liqiping <liqiping@msh.team>
Co-authored-by: OpeOginni <107570612+OpeOginni@users.noreply.github.com>
Co-authored-by: Matthias Reso <13337103+mreso@users.noreply.github.com>
Co-authored-by: tobwen <1864057+tobwen@users.noreply.github.com>
Co-authored-by: Daniel Polito <danielbpolito@gmail.com>
Co-authored-by: opencode <noreply@opencode.ai>
2026-07-23 16:20:37 -05:00
Kit Langton 79c1544072 refactor(tools): unify tool APIs and result handling (#38367) 2026-07-23 21:13:31 +00:00
Aiden Cline 8cac010bac fix(core): stop forcing toolChoice none on session.generate (#38557) 2026-07-23 14:12:23 -05:00
Aiden Cline 193f6be99c fix(ai): keep tools when Gemini tool choice is none (#38556) 2026-07-23 14:09:25 -05:00
opencode-agent[bot] 2a9f8e3a2c fix(tui): manage focus in devtools panels (#38555)
Co-authored-by: James Long <17031+jlongster@users.noreply.github.com>
2026-07-23 18:58:02 +00:00
Aiden Cline 2c814120c7 fix(ai): keep tools when Anthropic tool_choice is none (#38553) 2026-07-23 13:52:20 -05:00
opencode-agent[bot] 18fccac6ff fix(tui): preserve first message in new sessions (#38542)
Co-authored-by: Kit Langton <kit.langton@gmail.com>
Co-authored-by: James Long <17031+jlongster@users.noreply.github.com>
2026-07-23 13:59:51 -04:00
opencode-agent[bot] 360e7b412d feat(tui): expose debug settings (#38546)
Co-authored-by: James Long <longster@gmail.com>
2026-07-23 13:37:16 -04:00
opencode-agent[bot] ad596fb42b chore(core): upgrade fff to 0.10.1 (#38545)
Co-authored-by: Aiden Cline <rekram1-node@users.noreply.github.com>
2026-07-23 12:34:24 -05:00
opencode-agent[bot] 74e92f73e0 refactor(ai): remove unused response format (#38540)
Co-authored-by: Aiden Cline <rekram1-node@users.noreply.github.com>
2026-07-23 12:32:33 -05:00
458 changed files with 52302 additions and 89653 deletions
-7
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@@ -1,7 +0,0 @@
---
"@opencode-ai/client": patch
"@opencode-ai/protocol": patch
"@opencode-ai/cli": patch
---
Expose background-service lifecycle status, preserve one process-held owner through startup and failure, reconnect TUIs without activating replacement, and stop exact service instances gracefully.
-5
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@@ -1,5 +0,0 @@
---
"@opencode-ai/cli": patch
---
Expose a TUI plugin slot at the top of the session view.
-7
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@@ -1,7 +0,0 @@
---
"@opencode-ai/client": patch
"@opencode-ai/plugin": patch
"@opencode-ai/protocol": patch
---
Expose transient, read-only session generation through the HTTP API, generated clients, and V2 plugin session context.
-5
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@@ -1,5 +0,0 @@
---
"@opencode-ai/cli": patch
---
Expose a TUI plugin slot above the session composer.
+37
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@@ -0,0 +1,37 @@
name: deploy-www
on:
push:
branches:
- dev
- v2
workflow_dispatch:
concurrency:
group: deploy-www-${{ github.ref_name }}
cancel-in-progress: false
permissions:
contents: read
jobs:
deploy:
if: github.repository == 'anomalyco/opencode' && (github.ref_name == 'dev' || github.ref_name == 'v2')
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@f43a0e5ff2bd294095638e18286ca9a3d1956744 # v3.6.0
- uses: ./.github/actions/setup-bun
- name: Build
working-directory: packages/www
run: bun run build
env:
BLUME_ENV: ${{ github.ref_name == 'v2' && 'production' || 'dev' }}
CLOUDFLARE_ENV: ${{ github.ref_name == 'v2' && 'production' || 'dev' }}
- name: Deploy
working-directory: packages/www
run: bun run deploy
env:
CLOUDFLARE_API_TOKEN: ${{ secrets.CLOUDFLARE_API_TOKEN }}
+1 -1
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@@ -99,7 +99,7 @@ jobs:
- name: Check generated documentation
if: runner.os == 'Linux'
working-directory: packages/docs
working-directory: packages/www
run: bun run check:generated
e2e:
@@ -0,0 +1,68 @@
---
name: ideal-pseudocode
description: Function-by-function refactoring loop driven by ideal pseudocode. Use when the user says "ideal pseudocode", asks to make a function read like its pseudocode, or wants a dense module cleaned up one function at a time.
---
# Ideal Pseudocode
Clean up one function at a time by writing the pseudocode it _should_ read as, naming every delta between that and the real code, and closing only the gaps the user approves.
## Loop
One function per round. Never touch code before the user picks a direction.
1. **Pick the target** with the user — usually the next function up or down the call chain from the last round.
2. **Read the current code** fresh from disk. It may have unsaved or parallel edits; ask before overwriting anything unexpected.
3. **Distill.** Write the function's ideal pseudocode in a `ts`-fenced code block — TypeScript-flavored for syntax highlighting, but pseudocode: comments over mechanics, one line per idea, every arm of a loop visible as an arm. For a dense or unfamiliar function, first show the _current_ structure as pseudocode, then the ideal.
4. **Name the deltas.** A numbered list; each delta is one concrete gap: control flow smuggled through combinators, a flag-typed parameter, colliding names, side-effect plumbing drowning a loop body, twin functions differing only by a filter. For each, give an honest cost/benefit and a decisive recommendation — including "leave it" when the density has reasons (state the reasons).
5. **Verify before proposing.** Any API the proposal builds on (a combinator, schedule, matcher) gets checked against the installed version's source, not memory.
6. **Get buy-in, then apply.** Minimal edits. Quarantine irreducible ugliness inside a small helper whose name is the pseudocode line it implements. Collapse shallow sibling functions into one deep function only when the distinguishing argument is a domain noun, not a behavior switch.
7. **Validate.** Typecheck and the focused test suites from the package directory; rerun timing-sensitive tests repeatedly. Flag any semantic change the restructure introduced, even when tests pass.
8. **Offer the next target** and stop.
## Style
- Keep each round tight: pseudocode block, deltas, recommendation, one question.
- State mutation belongs in one visible place (usually the loop tail), never spread across error channels or callback closures.
- Prefer early return and `if` chains for control flow; matchers are for producing values.
- Compare names against the question each caller is actually asking; rename toward the domain noun.
## Example round
Every round should read like this (abridged from a real one, on an Effect step-runner):
> `runStep` it is. The ideal pseudocode:
>
> ```ts
> // One logical step: one settled model call, however many attempts it takes.
> // An attempt can end without settling in two ways:
> // transient provider failure -> retry the same call, same assistant message
> // compaction rewrote history -> rebuild the request and call again
> function runStep(session, promotable, step) {
> while (true) {
> const result = callModel(session, promotable, step)
>
> if (result.completed) return result
>
> if (result.retryable) {
> wait(retrySchedule) // exhausted -> publish Step.Failed, fail drain
> promotable = none // never re-promote on a second attempt
> continue
> }
>
> // compaction restarted the step: fresh request from rewritten history
> promotable = none
> step = result.step
> }
> }
> ```
>
> Comparing against the real thing, three deltas:
>
> 1. **The retry arm doesn't live in the loop.** In the pseudocode, retry is just another loop arm. In the real code it's smuggled through the error channel: `Effect.tapError` mutating loop variables via `Effect.sync` closures, then `Effect.retryOrElse` re-running a suspended call. Four mutable variables mutated from three different places — the state flow is invisible unless you already know the trick.
> 2. **`recoverOverflow: typeof compaction.compact | undefined`** — a function-typed parameter used as a one-shot armed/disarmed flag. The callee already closes over `compaction`; a boolean says what it is.
> 3. **`assistantMessageID`** exists solely to resume the same durable message across retries — fine, but only legible once the retry arm is visible in the loop.
>
> The unifying move for (1): a schedule driver, so a retryable failure becomes a caught value handled in the loop body exactly like the compaction arm. One honest trade: it's more manual than the blessed combinator — but the manual version is the loop the combinator was hiding, and the loop already exists for restarts. Two restart mechanisms, one control structure.
>
> Want me to apply it — unified loop, simplified schedule input, boolean `recoverOverflow`?
-1
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@@ -1,4 +1,3 @@
- To regenerate the legacy JavaScript SDK, run `./packages/sdk/js/script/build.ts`.
- After changing the public Protocol or Server `HttpApi`, run `bun run generate` from `packages/client`. Do not edit `src/generated` or `src/generated-effect` directly.
- Keep runtime dependencies directed from Schema to Core and Protocol, then from Core and Protocol to Server. Client runtime code may depend on Schema and Protocol but never Core or Server; `sdk-next` composes Client, Core, and Server.
- Do not modify `packages/opencode` unless the user explicitly asks for V1 work. `packages/opencode` is the V1 implementation and is present for reference only. New implementation changes should land in the V2 package set: `packages/core`, `packages/cli`, `packages/server`, `packages/protocol`, `packages/schema`, and related generated client surfaces when required.
+1615 -1649
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@@ -8,7 +8,7 @@
"@aws-sdk/client-s3": "3.933.0",
"@opencode-ai/plugin": "workspace:*",
"@opencode-ai/script": "workspace:*",
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"@opencode-ai/www/@astrojs/cloudflare/@cloudflare/vite-plugin/wrangler/esbuild/@esbuild/linux-x64": ["@esbuild/linux-x64@0.28.1", "", { "os": "linux", "cpu": "x64" }, "sha512-u/anNYF2mmVOEDwLtnQ1wOr3EZ9sTNGLWrsYGYwHWzGA3Si84IOkHXlbWTD1NB+9/1lcnweYKO54uhxZydNzfA=="],
"@opencode-ai/www/@astrojs/cloudflare/@cloudflare/vite-plugin/wrangler/esbuild/@esbuild/netbsd-arm64": ["@esbuild/netbsd-arm64@0.28.1", "", { "os": "none", "cpu": "arm64" }, "sha512-oks0DYbLwWMmaakTsCb+zL4E+aHRVLom9IJZOAthMQEPiQmydXHkziYEsGYRx0uNV/IjEKGAV941JzH02pflqw=="],
"@opencode-ai/www/@astrojs/cloudflare/@cloudflare/vite-plugin/wrangler/esbuild/@esbuild/netbsd-x64": ["@esbuild/netbsd-x64@0.28.1", "", { "os": "none", "cpu": "x64" }, "sha512-aeL6lAnN89Hz43Mlh1G8ARasbuoYvSITDEx0tHh5b7jJnHcssqgjy9Yx430GDpmCa6OyrKoS0aNRjKundRizGg=="],
"@opencode-ai/www/@astrojs/cloudflare/@cloudflare/vite-plugin/wrangler/esbuild/@esbuild/openbsd-arm64": ["@esbuild/openbsd-arm64@0.28.1", "", { "os": "openbsd", "cpu": "arm64" }, "sha512-MEFJe5C3R8pwXdZ5Y21oo6m7ePiS0d9pWucn99O/wvyJZChoIQKrQDxKrGeW8F5+T0okTHesAmDeiHDTIq0V/Q=="],
"@opencode-ai/www/@astrojs/cloudflare/@cloudflare/vite-plugin/wrangler/esbuild/@esbuild/openbsd-x64": ["@esbuild/openbsd-x64@0.28.1", "", { "os": "openbsd", "cpu": "x64" }, "sha512-i/ZLIOafE0Z8cI/XANJAixoJL/uRAoS2xOA3rb0xN+KK0K177cMAsQYkzHtBrtMXAKuAc7HGgcWiZ/sRC1Nxgw=="],
"@opencode-ai/www/@astrojs/cloudflare/@cloudflare/vite-plugin/wrangler/esbuild/@esbuild/openharmony-arm64": ["@esbuild/openharmony-arm64@0.28.1", "", { "os": "none", "cpu": "arm64" }, "sha512-ge+Z7EXFNt2BO1oAMsVpiQ8EwndV9i1xXerAeTIK7AtPs3bKFXQM7nlRxDSIUIMeueR1CNXxqztLzdNeReKBJg=="],
"@opencode-ai/www/@astrojs/cloudflare/@cloudflare/vite-plugin/wrangler/esbuild/@esbuild/sunos-x64": ["@esbuild/sunos-x64@0.28.1", "", { "os": "sunos", "cpu": "x64" }, "sha512-BEjgtECkL3vY+SaSQ6nzVfiALUeFxpawyp8Jmf5PtYhf1Ug40N1h/hxlhts+f1FvSvarEigdxS3BlSMI2PJLcQ=="],
"@opencode-ai/www/@astrojs/cloudflare/@cloudflare/vite-plugin/wrangler/esbuild/@esbuild/win32-arm64": ["@esbuild/win32-arm64@0.28.1", "", { "os": "win32", "cpu": "arm64" }, "sha512-lCv9eK/H6ZJWbE7bh2nw54CZ9M2nupBxJcTsdk/QQnWkdSjKGuxmmH8/GWrlT1eMmZfn4dGcCjRte397WqfQXA=="],
"@opencode-ai/www/@astrojs/cloudflare/@cloudflare/vite-plugin/wrangler/esbuild/@esbuild/win32-ia32": ["@esbuild/win32-ia32@0.28.1", "", { "os": "win32", "cpu": "ia32" }, "sha512-zvb/mB2bSCoJOpoCBgYKKpX6YM6mJBlBUVUtVj41DlZJVEB6/0CKlRYxP5wWl1C1ILiCoAU5wZZ4q1P3qeS6Eg=="],
"@opencode-ai/www/@astrojs/cloudflare/@cloudflare/vite-plugin/wrangler/esbuild/@esbuild/win32-x64": ["@esbuild/win32-x64@0.28.1", "", { "os": "win32", "cpu": "x64" }, "sha512-bm4Mowrv+GXMlpWX++EcXw/iLyd1o3+bJkC2DkWXYVvgZCqD/bSj9ctZeAMC3cIxgjRVR2Dufaiu4YPxr5gW1A=="],
"@opencode-ai/www/wrangler/miniflare/sharp/@img/sharp-wasm32/@emnapi/runtime": ["@emnapi/runtime@1.11.2", "", { "dependencies": { "tslib": "^2.4.0" } }, "sha512-kyOl3X0DuTiT1h2ft8r2fYO8JYtU9a9Xis/zBSiGArNaagCOWx90N1k2wxp18czFDH+OgcWGb5ZP/XMt3dcyPA=="],
@@ -9290,5 +9254,7 @@
"rimraf/glob/jackspeak/@isaacs/cliui/wrap-ansi/ansi-styles": ["ansi-styles@6.2.3", "", {}, "sha512-4Dj6M28JB+oAH8kFkTLUo+a2jwOFkuqb3yucU0CANcRRUbxS0cP0nZYCGjcc3BNXwRIsUVmDGgzawme7zvJHvg=="],
"temp/rimraf/glob/minimatch/brace-expansion/balanced-match": ["balanced-match@1.0.2", "", {}, "sha512-3oSeUO0TMV67hN1AmbXsK4yaqU7tjiHlbxRDZOpH0KW9+CeX4bRAaX0Anxt0tx2MrpRpWwQaPwIlISEJhYU5Pw=="],
"@opencode-ai/www/@astrojs/cloudflare/@cloudflare/vite-plugin/miniflare/sharp/@img/sharp-wasm32/@emnapi/runtime": ["@emnapi/runtime@1.11.2", "", { "dependencies": { "tslib": "^2.4.0" } }, "sha512-kyOl3X0DuTiT1h2ft8r2fYO8JYtU9a9Xis/zBSiGArNaagCOWx90N1k2wxp18czFDH+OgcWGb5ZP/XMt3dcyPA=="],
}
}
+1 -1
View File
@@ -2,7 +2,7 @@
exact = true
# Only install newly resolved package versions published at least 3 days ago.
minimumReleaseAge = 259200
minimumReleaseAgeExcludes = ["@ai-sdk/amazon-bedrock", "@ai-sdk/anthropic", "@opentui/core", "@opentui/core-darwin-arm64", "@opentui/core-darwin-x64", "@opentui/core-linux-arm64", "@opentui/core-linux-arm64-musl", "@opentui/core-linux-x64", "@opentui/core-linux-x64-musl", "@opentui/core-win32-arm64", "@opentui/core-win32-x64", "@opentui/keymap", "@opentui/solid", "opentui-spinner", "gitlab-ai-provider", "opencode-gitlab-auth", "@ff-labs/fff-node", "@ff-labs/fff-bun", "@ff-labs/fff-bin-darwin-arm64", "@ff-labs/fff-bin-darwin-x64", "@ff-labs/fff-bin-linux-arm64-gnu", "@ff-labs/fff-bin-linux-arm64-musl", "@ff-labs/fff-bin-linux-x64-gnu", "@ff-labs/fff-bin-linux-x64-musl", "@ff-labs/fff-bin-win32-arm64", "@ff-labs/fff-bin-win32-x64", "@pierre/diffs", "@pierre/theming", "app-builder-lib", "dmg-builder", "electron-builder", "electron-publish"]
minimumReleaseAgeExcludes = ["@ai-sdk/amazon-bedrock", "@ai-sdk/anthropic", "@opencode-ai/sdk", "@opentui/core", "@opentui/core-darwin-arm64", "@opentui/core-darwin-x64", "@opentui/core-linux-arm64", "@opentui/core-linux-arm64-musl", "@opentui/core-linux-x64", "@opentui/core-linux-x64-musl", "@opentui/core-win32-arm64", "@opentui/core-win32-x64", "@opentui/keymap", "@opentui/solid", "opentui-spinner", "gitlab-ai-provider", "opencode-gitlab-auth", "@ff-labs/fff-node", "@ff-labs/fff-bun", "@ff-labs/fff-bin-darwin-arm64", "@ff-labs/fff-bin-darwin-x64", "@ff-labs/fff-bin-linux-arm64-gnu", "@ff-labs/fff-bin-linux-arm64-musl", "@ff-labs/fff-bin-linux-x64-gnu", "@ff-labs/fff-bin-linux-x64-musl", "@ff-labs/fff-bin-win32-arm64", "@ff-labs/fff-bin-win32-x64", "@pierre/diffs", "@pierre/theming", "app-builder-lib", "dmg-builder", "electron-builder", "electron-publish"]
[test]
root = "./do-not-run-tests-from-root"
+1 -1
View File
@@ -15,6 +15,6 @@
"@actions/github": "6.0.1",
"@octokit/graphql": "9.0.1",
"@octokit/rest": "catalog:",
"@opencode-ai/sdk": "workspace:*"
"@opencode-ai/sdk": "1.18.5"
}
}
+4 -4
View File
@@ -1,8 +1,8 @@
{
"nodeModules": {
"x86_64-linux": "sha256-qt11SKmOjq0KU542QFbs+u7YyJicn4drCcwCdg325yk=",
"aarch64-linux": "sha256-z68doReXTrWS7HeiAjc0btIjAsvzeZZ7hXAlHr0c77Q=",
"aarch64-darwin": "sha256-PILYH1Pi8XBvSkuZ+1sNnUTao5kba+m5Z8iJKx6YXPo=",
"x86_64-darwin": "sha256-KpcJzP4m0SUavu/WaSffgzOxrHq8ljdy0GOzs9p16lo="
"x86_64-linux": "sha256-0kcwV34P2C3yKg2eG9W2nW+OedrSBb+1TdpuUeYtauY=",
"aarch64-linux": "sha256-yHVygApQchAB34wrtFR4GU0CkmZOlLsl3wsp15u0xzs=",
"aarch64-darwin": "sha256-DyalcwyK2Wn5R6249keFcNVECbgtjYNjscOFqTi88FI=",
"x86_64-darwin": "sha256-BkGw0GWN9W9q+/g4FYR0MqxUuFP80BPoERO+ypz/arQ="
}
}
+2 -3
View File
@@ -33,7 +33,6 @@
"packages/*",
"packages/console/*",
"packages/stats/*",
"packages/sdk/js",
"packages/slack"
],
"catalog": {
@@ -124,7 +123,7 @@
"@aws-sdk/client-s3": "3.933.0",
"@opencode-ai/plugin": "workspace:*",
"@opencode-ai/script": "workspace:*",
"@opencode-ai/sdk": "workspace:*",
"@opencode-ai/sdk": "1.18.5",
"heap-snapshot-toolkit": "1.1.3",
"typescript": "catalog:"
},
@@ -155,12 +154,12 @@
"@types/node": "catalog:"
},
"patchedDependencies": {
"@ff-labs/fff-bun@0.9.3": "patches/@ff-labs%2Ffff-bun@0.9.3.patch",
"@npmcli/agent@4.0.2": "patches/@npmcli%2Fagent@4.0.2.patch",
"@silvia-odwyer/photon-node@0.3.4": "patches/@silvia-odwyer%2Fphoton-node@0.3.4.patch",
"@standard-community/standard-openapi@0.2.9": "patches/@standard-community%2Fstandard-openapi@0.2.9.patch",
"solid-js@1.9.10": "patches/solid-js@1.9.10.patch",
"@ai-sdk/xai@3.0.102": "patches/@ai-sdk%2Fxai@3.0.102.patch",
"@ai-sdk/mistral@3.0.51": "patches/@ai-sdk%2Fmistral@3.0.51.patch",
"gcp-metadata@8.1.2": "patches/gcp-metadata@8.1.2.patch",
"pacote@21.5.0": "patches/pacote@21.5.0.patch",
"@ai-sdk/google@3.0.73": "patches/@ai-sdk%2Fgoogle@3.0.73.patch",
+6 -5
View File
@@ -54,7 +54,7 @@ Filter or narrow `LLMEvent` streams with `LLMEvent.is.*` (camelCase guards, e.g.
A route is the registered, runnable composition of four orthogonal pieces:
- **`Protocol`** (`src/route/protocol.ts`) — semantic API contract. Owns request body construction (`body.from`), the body schema (`body.schema`), the streaming-event schema (`stream.event`), and the event-to-`LLMEvent` state machine (`stream.step`). `Route.make(...)` validates and JSON-encodes the body from `body.schema` and decodes frames with `stream.event`. Examples: `OpenAIChat.protocol`, `OpenAIResponses.protocol`, `AnthropicMessages.protocol`, `Gemini.protocol`, `BedrockConverse.protocol`.
- **`Protocol`** (`src/route/protocol.ts`) — semantic API contract. Owns request body construction (`body.from`), the body schema (`body.schema`), the streaming-event schema (`stream.event`), and the event-to-`LLMEvent` state machine (`stream.step`). `Route.make(...)` validates and JSON-encodes the body from `body.schema` and decodes frames with `stream.event`. Examples: `OpenAIChat.protocol`, `OpenResponses.protocol`, `OpenAIResponses.protocol`, `AnthropicMessages.protocol`, `Gemini.protocol`, `BedrockConverse.protocol`.
- **`Endpoint`** (`src/route/endpoint.ts`) — URL construction. The host, path, and route query live on the endpoint. `Endpoint.path("/chat/completions", { baseURL })` is the common case; pass a function for paths that embed the model id or a body field (e.g. `Endpoint.path(({ body }) => `/model/${body.modelId}/converse-stream`)`).
- **`Auth`** (`src/route/auth.ts`) — per-request transport authentication. Provider facades configure credentials onto the route before model selection, usually via `Auth.bearer(apiKey)` or `Auth.header(name, apiKey)`. Routes that need per-request signing (Bedrock SigV4, future Vertex IAM, Azure AAD) implement `Auth` as a function that signs the body and merges signed headers into the result.
- **`Framing`** (`src/route/framing.ts`) — bytes → frames. SSE (`Framing.sse`) is shared; Bedrock keeps its AWS event-stream framing as a typed `Framing<object>` value alongside its protocol.
@@ -158,13 +158,14 @@ packages/ai/src/
protocols/
shared.ts ProviderShared toolkit used inside protocol impls
openai-chat.ts protocol + route (compose OpenAIChat.protocol)
openai-responses.ts
open-responses.ts provider-neutral Responses protocol baseline
openai-responses.ts OpenAI tools/events/transports composed over OpenResponses
anthropic-messages.ts
gemini.ts
bedrock-converse.ts
bedrock-event-stream.ts framing for AWS event-stream binary frames
openai-compatible-chat.ts route that reuses OpenAIChat.protocol, no canonical URL
openai-compatible-responses.ts route that reuses OpenAIResponses.protocol, no canonical URL
openai-compatible-responses.ts deployment adapter that reuses OpenResponses.protocol, no canonical URL
utils/ per-protocol helpers (auth, cache, media, tool-stream, ...)
providers/
openai-compatible.ts generic Chat helper + family model helpers
@@ -175,7 +176,7 @@ packages/ai/src/
tool-runtime.ts narrow one-call typed tool dispatcher
```
The dependency arrow points down: `providers/*.ts` files import protocol routes and auth-option utilities; protocol modules import `endpoint`, `auth`, `framing`, and transport pieces. Protocols do not import provider facades. Lower-level modules know nothing about provider catalog metadata.
The dependency arrow points down: `providers/*.ts` files import protocol routes and auth-option utilities; protocol modules import `endpoint`, `auth`, `framing`, and transport pieces. Protocols do not import provider facades. Lower-level modules know nothing about provider catalog metadata. `OpenAIResponses` composes the provider-neutral `OpenResponses` protocol; the baseline never imports the OpenAI extension.
### Shared protocol helpers
@@ -240,7 +241,7 @@ const get_weather = tool({
const tools = { get_weather, get_time, ... }
const events = yield* LLM.stream(
LLM.updateRequest(request, { tools: Tool.toDefinitions(tools) }),
LLMRequest.update(request, { tools: Tool.toDefinitions(tools) }),
).pipe(Stream.runCollect)
const call = Array.from(events).find(LLMEvent.is.toolCall)
+3 -2
View File
@@ -315,7 +315,8 @@ const longer = {
}
```
There is no `LLM.updateRequest(...)` helper and no request Schema class.
There is no `LLM.updateRequest(...)` helper. The current Schema-backed implementation
uses `LLMRequest.update(...)` when canonical request data must be derived.
### Conversation history
@@ -436,7 +437,7 @@ const call = Array.from(events).find(LLMEvent.is.toolCall)
if (call && !call.providerExecuted) {
const dispatched = yield * ToolRuntime.dispatch(tools, call)
const followUp = LLM.updateRequest(request, {
const followUp = LLMRequest.update(request, {
messages: [...request.messages, Message.assistant([call]), Message.tool({ ...call, result: dispatched.result })],
})
// Caller must invoke the provider again and repeat the loop.
+7 -5
View File
@@ -207,7 +207,9 @@ Prompt caching is **on by default**. Every `LLMRequest` resolves to `cache: "aut
### Auto placement
`"auto"` places three breakpoints — last tool definition, last system part, latest user message. The last-user-message boundary is the load-bearing detail: in a tool-use loop, a single user turn expands into many assistant/tool round-trips, all sharing that prefix. Caching at that boundary lets every intra-turn API call hit.
`"auto"` places up to four breakpoints — the last tool definition, the first system part, the last system part when distinct, and the final message boundary. These expose successively larger reusable prefixes for tools, the base agent, project instructions, and the active conversation. The rolling final-message boundary is the load-bearing detail in tool loops: it advances on every request so the previous cache entry stays within Anthropic's 20-block lookback.
Tools precede every system and conversation block in the provider prefix, so tool definitions must remain byte-stable and deterministically ordered for downstream breakpoints to remain reusable.
The math justifies the default: Anthropic's 5-minute cache write is 1.25× base, read is 0.1×, so a single reuse within 5 minutes already wins. One-shot completions below the per-model minimum-cacheable-token threshold silently no-op on the wire, so the worst case is harmless.
@@ -235,7 +237,7 @@ cache: {
### Manual hints
Inline `CacheHint` on any text / system / tool / tool-result part overrides automatic placement. The auto policy preserves manual hints; it only fills gaps.
Inline `CacheHint` on any text / system / tool / tool-result part overrides automatic placement. The auto policy preserves manual hints, counts them against Anthropic and Bedrock's four-breakpoint limit, and only fills the remaining slots.
```ts
LLM.request({
@@ -251,8 +253,8 @@ LLM.request({
| Protocol | `cache: "auto"` |
| ----------------------- | ------------------------------------------------------------------------- |
| Anthropic Messages | emits up to 3 `cache_control` markers (4-breakpoint cap enforced) |
| Bedrock Converse | emits up to 3 `cachePoint` blocks (4-breakpoint cap enforced) |
| Anthropic Messages | emits up to 4 `cache_control` markers (4-breakpoint cap enforced) |
| Bedrock Converse | emits up to 4 `cachePoint` blocks (4-breakpoint cap enforced) |
| OpenAI Chat / Responses | no-op (implicit caching above 1024 tokens) |
| Gemini | no-op (implicit caching on 2.5+; explicit `CachedContent` is out-of-band) |
@@ -300,7 +302,7 @@ OpenAI Chat and OpenAI Responses are separate semantic entrypoints:
- `@opencode-ai/ai/providers/google-vertex/responses`
- `@opencode-ai/ai/providers/google-vertex/messages`
Responses HTTP versus WebSocket is a scoped `transport` setting on the OpenAI Responses entrypoint, not another entrypoint. Azure follows the same Chat/Responses split at `providers/azure/chat` and `providers/azure/responses`. Generic OpenAI-compatible Chat remains at `providers/openai-compatible`; compatible Responses is separate at `providers/openai-compatible/responses`. Generic Anthropic Messages-compatible providers use `providers/anthropic-compatible`, which the named Anthropic provider composes. Google Gemini and Amazon Bedrock expose their single native API through their existing provider paths.
Responses HTTP versus WebSocket is a scoped `transport` setting on the OpenAI Responses entrypoint, not another entrypoint. Azure follows the same Chat/Responses split at `providers/azure/chat` and `providers/azure/responses`. Generic OpenAI-compatible Chat remains at `providers/openai-compatible`; the Responses adapter at `providers/openai-compatible/responses` uses the provider-neutral Open Responses protocol. OpenAI Responses extends that baseline with OpenAI tools, event variants, metadata, defaults, and transports. Generic Anthropic Messages-compatible providers use `providers/anthropic-compatible`, which the named Anthropic provider composes. Google Gemini and Amazon Bedrock expose their single native API through their existing provider paths.
Vertex Gemini, Vertex Chat, Vertex Responses, and Vertex Messages are separate API entrypoints. All accept `project`, `location`, and an optional `accessToken`; when no explicit token or auth override is supplied they lazily use Google Application Default Credentials. Vertex Gemini instead selects express mode when `apiKey` or `GOOGLE_VERTEX_API_KEY` is present. Vertex Chat targets MaaS models through the OpenAI-compatible Chat Completions endpoint, while Vertex Responses targets Grok models and defaults `store` to `false` as required by Vertex. `providers/google-vertex` remains the default alias for `providers/google-vertex/gemini`.
+24 -24
View File
@@ -1,6 +1,6 @@
# LLM Provider Parity Status
Last reviewed: 2026-07-17
Last reviewed: 2026-07-24
This file tracks the gap between the native `@opencode-ai/ai` package and the AI SDK provider packages that opencode still depends on for many catalog/runtime paths.
@@ -13,26 +13,26 @@ This file tracks the gap between the native `@opencode-ai/ai` package and the AI
## Current Implementation Snapshot
| Native slice | Source | Current state | Main gaps |
| ---------------------------------- | ---------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| OpenAI Chat | `src/protocols/openai-chat.ts`, `src/providers/openai.ts` | Usable. Streams text, reasoning deltas, tool calls, usage, images, and common generation controls. | No typed structured-output / `response_format` path. Limited typed OpenAI option surface compared with SDK escape hatches. |
| OpenAI Responses HTTP | `src/protocols/openai-responses.ts`, `src/providers/openai.ts` | Usable. Supports hosted-tool event surfacing, reasoning replay metadata, GPT-5 defaults, and cache usage. | No explicit `previous_response_id` path. Typed options cover only a subset of Responses fields. Structured output is still mostly synthetic-tool based. |
| OpenAI Responses WebSocket | `src/protocols/openai-responses.ts`, `src/route/transport/websocket.ts` | Present as `OpenAI.responsesWebSocket(...)`. | Runner/catalog support explicitly must not downgrade WebSocket routes; broader runtime selection is not complete. |
| OpenAI-compatible Chat | `src/protocols/openai-compatible-chat.ts`, `src/providers/openai-compatible.ts` | Usable for generic Chat and several profiles: Baseten, Cerebras, DeepInfra, DeepSeek, Fireworks, Groq, TogetherAI. | Family quirks are mostly endpoint defaults, not full typed behavior. |
| OpenAI-compatible Responses | `src/protocols/openai-compatible-responses.ts`, `src/providers/openai-compatible-responses.ts` | Usable for deployments that implement the OpenAI Responses wire protocol. | No named family profiles or recorded deployment coverage yet. |
| Anthropic-compatible Messages | `src/protocols/anthropic-messages.ts`, `src/providers/anthropic-compatible.ts` | Usable for deployments that implement the Anthropic Messages wire protocol. Named Anthropic composes this base; MiniMax M3 has recorded text and tool-loop coverage. | No named compatible family profiles yet. |
| Anthropic Messages | `src/protocols/anthropic-messages.ts`, `src/providers/anthropic.ts` | Usable. Supports tools, thinking, cache control, images, server-hosted tool events, and usage. | Provider option surface is small. Beta/header handling, metadata, and newer Messages fields need a typed parity pass. |
| Gemini Developer API | `src/protocols/gemini.ts`, `src/providers/google.ts` | Usable for Google API key flow. Supports text, images, tools, thinking signatures, and cache usage. | This is not Vertex. Typed provider options are narrow; many Gemini request fields currently require raw `http.body` overlays. |
| Vertex Gemini | `src/protocols/gemini.ts`, `src/providers/google-vertex.ts` | Usable through API-key express mode, explicit OAuth tokens, or ADC with project/location endpoint derivation, including tuned `endpoints/...` deployments. | Core runner/catalog mapping and recorded provider coverage are missing. |
| Vertex Chat | `src/protocols/openai-chat.ts`, `src/providers/google-vertex-chat.ts` | Usable for MaaS models through OpenAI-compatible Chat Completions with explicit OAuth tokens or ADC and project/location endpoint derivation. | Core runner/catalog mapping and recorded provider coverage are missing; MaaS family-specific request parity needs review. |
| Vertex Responses | `src/protocols/openai-responses.ts`, `src/providers/google-vertex-responses.ts` | Usable for Grok models through OpenAI-compatible Responses with explicit OAuth tokens or ADC, project/location endpoint derivation, and storage disabled by default. | Core runner/catalog mapping and recorded provider coverage are missing; stateful continuation is not supported by Vertex. |
| Vertex Messages | `src/protocols/anthropic-messages.ts`, `src/providers/google-vertex-messages.ts` | Usable through explicit OAuth tokens or ADC, including global, regional, and `eu`/`us` multi-region endpoints. | Core runner/catalog mapping and recorded provider coverage are missing; Vertex-specific hosted-tool parity needs review. |
| Bedrock Converse | `src/protocols/bedrock-converse.ts`, `src/providers/amazon-bedrock.ts` | Partial but real. Supports AWS event-stream framing, SigV4 with supplied credentials, bearer auth, tools, reasoning signatures, media, cache points, and recorded tests. | Native facade does not mirror the AI SDK plugin's default AWS credential chain/profile behavior. Runner/catalog mapping is missing. Guardrails, inference profiles, region-specific model ID fixes, and model-specific request fields need a parity pass. |
| Azure OpenAI | `src/providers/azure.ts` using OpenAI Chat/Responses protocols | Partial. Supports resource/base URL setup, API key auth, API version query, Chat, and Responses selectors. | Core runner does not map `@ai-sdk/azure` to this native facade. AAD/token auth and Azure-specific endpoint variants need review. |
| Cloudflare AI Gateway / Workers AI | `src/providers/cloudflare.ts` | Present via OpenAI-compatible Chat routes. | Useful but not part of the critical AI SDK replacement set yet. Needs per-product recorded coverage before relying on it broadly. |
| OpenRouter | `src/providers/openrouter.ts` | Present with OpenRouter-specific usage/reasoning/prompt-cache options over Chat. | Responses-style OpenRouter support is absent. |
| xAI | `src/providers/xai.ts` | Present with Responses and Chat selectors. | Needs package-parity review against the AI SDK xAI provider. |
| GitHub Copilot | `src/providers/github-copilot.ts` | Present as explicit-base-URL OpenAI Chat/Responses facade. | Runtime/catalog integration remains specialized and should stay separate from public OpenAI-compatible defaults. |
| Native slice | Source | Current state | Main gaps |
| ---------------------------------- | --------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| OpenAI Chat | `src/protocols/openai-chat.ts`, `src/providers/openai.ts` | Usable. Streams text, reasoning deltas, tool calls, usage, images, and common generation controls. | No typed structured-output / `response_format` path. Limited typed OpenAI option surface compared with SDK escape hatches. |
| OpenAI Responses HTTP | `src/protocols/open-responses.ts`, `src/protocols/openai-responses.ts`, `src/providers/openai.ts` | Usable. Extends the Open Responses baseline with hosted-tool event surfacing, reasoning replay metadata, GPT-5 defaults, and cache usage. | No explicit `previous_response_id` path. Typed options cover only a subset of Responses fields. Structured output is still mostly synthetic-tool based. |
| OpenAI Responses WebSocket | `src/protocols/openai-responses.ts`, `src/route/transport/websocket.ts` | Present as `OpenAI.responsesWebSocket(...)`. | Runner/catalog support explicitly must not downgrade WebSocket routes; broader runtime selection is not complete. |
| OpenAI-compatible Chat | `src/protocols/openai-compatible-chat.ts`, `src/providers/openai-compatible.ts` | Usable for generic Chat and several profiles: Baseten, Cerebras, DeepInfra, DeepSeek, Fireworks, Groq, TogetherAI. | Family quirks are mostly endpoint defaults, not full typed behavior. |
| Open Responses-compatible | `src/protocols/open-responses.ts`, `src/protocols/openai-compatible-responses.ts`, `src/providers/openai-compatible-responses.ts` | Usable for deployments that implement the provider-neutral Open Responses protocol. The deployment adapter does not inherit OpenAI tools, events, metadata, or defaults. | No named family profiles or recorded deployment coverage yet. |
| Anthropic-compatible Messages | `src/protocols/anthropic-messages.ts`, `src/providers/anthropic-compatible.ts` | Usable for deployments that implement the Anthropic Messages wire protocol. Named Anthropic composes this base; MiniMax M3 has recorded text and tool-loop coverage. | No named compatible family profiles yet. |
| Anthropic Messages | `src/protocols/anthropic-messages.ts`, `src/providers/anthropic.ts` | Usable. Supports tools, thinking, cache control, images, server-hosted tool events, and usage. | Provider option surface is small. Beta/header handling, metadata, and newer Messages fields need a typed parity pass. |
| Gemini Developer API | `src/protocols/gemini.ts`, `src/providers/google.ts` | Usable for Google API key flow. Supports text, images, tools, thinking signatures, and cache usage. | This is not Vertex. Typed provider options are narrow; many Gemini request fields currently require raw `http.body` overlays. |
| Vertex Gemini | `src/protocols/gemini.ts`, `src/providers/google-vertex.ts` | Usable through API-key express mode, explicit OAuth tokens, or ADC with project/location endpoint derivation, including tuned `endpoints/...` deployments. | Core runner/catalog mapping and recorded provider coverage are missing. |
| Vertex Chat | `src/protocols/openai-chat.ts`, `src/providers/google-vertex-chat.ts` | Usable for MaaS models through OpenAI-compatible Chat Completions with explicit OAuth tokens or ADC and project/location endpoint derivation. | Core runner/catalog mapping and recorded provider coverage are missing; MaaS family-specific request parity needs review. |
| Vertex Responses | `src/protocols/open-responses.ts`, `src/providers/google-vertex-responses.ts` | Usable for Grok models through Open Responses with explicit OAuth tokens or ADC, project/location endpoint derivation, and an explicit `store: false` Vertex default. | Core runner/catalog mapping and recorded provider coverage are missing; stateful continuation is not supported by Vertex. |
| Vertex Messages | `src/protocols/anthropic-messages.ts`, `src/providers/google-vertex-messages.ts` | Usable through explicit OAuth tokens or ADC, including global, regional, and `eu`/`us` multi-region endpoints. | Core runner/catalog mapping and recorded provider coverage are missing; Vertex-specific hosted-tool parity needs review. |
| Bedrock Converse | `src/protocols/bedrock-converse.ts`, `src/providers/amazon-bedrock.ts` | Partial but real. Supports AWS event-stream framing, SigV4 with supplied credentials, bearer auth, tools, reasoning signatures, media, cache points, and recorded tests. | Native facade does not mirror the AI SDK plugin's default AWS credential chain/profile behavior. Runner/catalog mapping is missing. Guardrails, inference profiles, region-specific model ID fixes, and model-specific request fields need a parity pass. |
| Azure OpenAI | `src/providers/azure.ts` using OpenAI Chat/Responses protocols | Partial. Supports resource/base URL setup, API key auth, API version query, Chat, and Responses selectors. | Core runner does not map `@ai-sdk/azure` to this native facade. AAD/token auth and Azure-specific endpoint variants need review. |
| Cloudflare AI Gateway / Workers AI | `src/providers/cloudflare.ts` | Present via OpenAI-compatible Chat routes. | Useful but not part of the critical AI SDK replacement set yet. Needs per-product recorded coverage before relying on it broadly. |
| OpenRouter | `src/providers/openrouter.ts` | Present with OpenRouter-specific usage/reasoning/prompt-cache options over Chat. | Responses-style OpenRouter support is absent. |
| xAI | `src/providers/xai.ts` | Present with Responses and Chat selectors. | Needs package-parity review against the AI SDK xAI provider. |
| GitHub Copilot | `src/providers/github-copilot.ts` | Present as explicit-base-URL OpenAI Chat/Responses facade. | Runtime/catalog integration remains specialized and should stay separate from public OpenAI-compatible defaults. |
## V2 Runner Status
@@ -65,7 +65,7 @@ Other `aisdk:` packages, including Google Vertex, Azure, and Bedrock, currently
## Highest-Risk Gaps
1. Runner support is narrower than the LLM package. The package has native provider facades for Google, Azure, and Bedrock, but the V2 Session runner only maps OpenAI, Anthropic, and explicit OpenAI-compatible Chat from `aisdk` catalog metadata.
2. OpenAI-compatible Responses is available as a separate package entrypoint, but the V2 runner still maps `@ai-sdk/openai-compatible` to Chat only. Catalog selection must become API-aware before Responses deployments can use it.
2. The Open Responses adapter is available through a separate package entrypoint, but the V2 runner still maps `@ai-sdk/openai-compatible` to Chat only. Catalog selection must become API-aware before Responses deployments can use it.
3. Bedrock native auth is not AI SDK parity. The AI SDK plugin uses the default AWS provider chain, profile, container credentials, and Bedrock bearer token env behavior. Native Bedrock currently expects explicit credentials or bearer auth on the facade.
4. Vertex Gemini, Vertex Chat, Vertex Responses, and Vertex Messages now have native package entrypoints, but the core runner does not map catalog metadata to them yet and recorded provider coverage is still missing.
5. Azure is only a provider facade, not a full runtime replacement. Native Azure exists, but the catalog runner does not select it, and token auth/resource variants need review.
@@ -83,13 +83,13 @@ These are implementation/API slices, not separate npm packages.
| OpenAI Chat | `@opencode-ai/ai/providers/openai/chat` | OpenAI `/chat/completions` semantics. |
| OpenAI Responses | `@opencode-ai/ai/providers/openai/responses` | OpenAI `/responses` semantics with HTTP/WebSocket selected through settings. |
| OpenAI-compatible Chat | `@opencode-ai/ai/providers/openai-compatible` | Generic OpenAI-compatible `/chat/completions`. |
| OpenAI-compatible Responses | `@opencode-ai/ai/providers/openai-compatible/responses` | Generic OpenAI-compatible `/responses`. |
| Open Responses-compatible | `@opencode-ai/ai/providers/openai-compatible/responses` | Generic provider-neutral `/responses`. |
| Anthropic-compatible Messages | `@opencode-ai/ai/providers/anthropic-compatible` | Generic Anthropic-compatible `/messages`. |
| Anthropic Messages | `@opencode-ai/ai/providers/anthropic` | Anthropic Messages API. |
| Gemini Developer API | `@opencode-ai/ai/providers/google` | Google AI Studio Gemini API. |
| Vertex Gemini | `@opencode-ai/ai/providers/google-vertex/gemini` | Vertex Gemini API; `providers/google-vertex` is the default alias. |
| Vertex Chat | `@opencode-ai/ai/providers/google-vertex/chat` | Vertex OpenAI-compatible Chat Completions for MaaS models. |
| Vertex Responses | `@opencode-ai/ai/providers/google-vertex/responses` | Vertex OpenAI-compatible Responses for Grok models. |
| Vertex Responses | `@opencode-ai/ai/providers/google-vertex/responses` | Vertex Open Responses for Grok models. |
| Vertex Messages | `@opencode-ai/ai/providers/google-vertex/messages` | Vertex-hosted Anthropic Messages API. |
| Bedrock Converse | `@opencode-ai/ai/providers/amazon-bedrock` | AWS Bedrock Converse API. |
| Bedrock Mantle | Missing | AWS Bedrock Mantle OpenAI-compatible APIs. |
+7 -4
View File
@@ -1,5 +1,5 @@
import { Config, Effect, Formatter, Layer, Schema, Stream } from "effect"
import { LLM, LLMClient, Message, ProviderID, Tool, ToolRuntime } from "@opencode-ai/ai"
import { LLM, LLMClient, LLMRequest, Message, ProviderID, Tool, ToolRuntime } from "@opencode-ai/ai"
import { Route, Auth, Endpoint, Framing, Protocol, RequestExecutor, WebSocketExecutor } from "@opencode-ai/ai/route"
import { OpenAI } from "@opencode-ai/ai/providers"
@@ -78,7 +78,10 @@ const streamText = LLM.stream(request).pipe(
Stream.tap((event) =>
Effect.sync(() => {
if (event.type === "text-delta") process.stdout.write(`\ntext: ${event.text}`)
if (event.type === "finish") process.stdout.write(`\nfinish: ${event.reason}\n`)
if (event.type === "finish")
process.stdout.write(
`\nfinish: ${event.reason.normalized}${event.reason.raw ? ` (${event.reason.raw})` : ""}\n`,
)
}),
),
Stream.runDrain,
@@ -113,7 +116,7 @@ const streamWithTools = Effect.gen(function* () {
// A durable agent would persist these messages before starting another
// raw model turn. This tutorial keeps the boundary visible instead.
const followUp = LLM.updateRequest(request, {
const followUp = LLMRequest.update(request, {
messages: [
...request.messages,
Message.assistant([event]),
@@ -194,7 +197,7 @@ const FakeProtocol = Protocol.make<FakeBody, string, string, void>({
event: Schema.String,
initial: () => undefined,
step: (_, frame) => Effect.succeed([undefined, [{ type: "text-delta", id: "text-0", text: frame }]] as const),
onHalt: () => [{ type: "finish", reason: "stop" }],
onHalt: () => [{ type: "finish", reason: { normalized: "stop" } }],
},
})
+61 -25
View File
@@ -2,32 +2,31 @@
// the policy designates. Runs once at compile time, before the per-protocol
// body builder, so the existing inline-hint lowering path handles the rest.
//
// The default `"auto"` shape places one breakpoint at the last tool definition,
// one at the last system part, and one at the latest user message. This
// matches what production agent harnesses (LangChain's caching middleware,
// kern-ai's 10x cost-reduction playbook) converge on for tool-use loops: the
// latest user message stays put while a single turn explodes into many
// assistant/tool round-trips, so caching at that boundary lets every
// intra-turn API call hit the prefix.
// The default `"auto"` shape places breakpoints at the last tool definition,
// the first and last distinct system parts, and the conversation tail. This
// exposes reusable tool, base-agent, project, and session prefixes while
// advancing the tail after each tool result keeps the previous cache entry
// within Anthropic's 20-block lookback during long agent turns.
//
// Manual `cache: CacheHint` placements on individual parts are preserved
// this function only fills gaps the caller left empty.
// Manual `cache: CacheHint` placements on individual parts are preserved and
// count against the four-breakpoint budget; auto only fills remaining slots.
import { CacheHint, type CachePolicy, type CachePolicyObject } from "./schema/options"
import { LLMRequest, Message, ToolDefinition, type ContentPart } from "./schema/messages"
const AUTO: CachePolicyObject = {
tools: true,
system: true,
messages: "latest-user-message",
messages: { tail: 1 },
}
const NONE: CachePolicyObject = {}
const BREAKPOINT_CAP = 4
// Resolution rules:
// - undefined → "auto" — caching is on by default. The math favors it:
// Anthropic 5m-cache write is 1.25x base, read is 0.1x,
// so a single reuse within 5 minutes already wins.
// - "auto" → tools + system + latest user msg.
// - "auto" → tools + first/last system + final message boundary.
// - "none" → no auto placement; manual `CacheHint`s still flow.
// - object form → exactly what the caller asked for.
const resolve = (policy: CachePolicy | undefined): CachePolicyObject => {
@@ -44,18 +43,32 @@ const RESPECTS_INLINE_HINTS = new Set(["anthropic-messages", "bedrock-converse"]
const makeHint = (ttlSeconds: number | undefined): CacheHint =>
ttlSeconds !== undefined ? new CacheHint({ type: "ephemeral", ttlSeconds }) : new CacheHint({ type: "ephemeral" })
const markLastTool = (tools: ReadonlyArray<ToolDefinition>, hint: CacheHint): ReadonlyArray<ToolDefinition> => {
interface Budget {
remaining: number
}
const markLastTool = (
tools: ReadonlyArray<ToolDefinition>,
hint: CacheHint,
budget: Budget,
): ReadonlyArray<ToolDefinition> => {
if (tools.length === 0) return tools
const last = tools.length - 1
if (tools[last]!.cache) return tools
if (tools[last]!.cache || budget.remaining === 0) return tools
budget.remaining -= 1
return tools.map((tool, i) => (i === last ? new ToolDefinition({ ...tool, cache: hint }) : tool))
}
const markLastSystem = (system: LLMRequest["system"], hint: CacheHint): LLMRequest["system"] => {
const markSystemBoundaries = (system: LLMRequest["system"], hint: CacheHint, budget: Budget): LLMRequest["system"] => {
if (system.length === 0) return system
const last = system.length - 1
if (system[last]!.cache) return system
return system.map((part, i) => (i === last ? { ...part, cache: hint } : part))
let changed = false
const next = system.map((part, index) => {
if ((index !== 0 && index !== system.length - 1) || part.cache || budget.remaining === 0) return part
budget.remaining -= 1
changed = true
return { ...part, cache: hint }
})
return changed ? next : system
}
const lastIndexOfRole = (messages: ReadonlyArray<Message>, role: Message["role"]): number =>
@@ -64,14 +77,20 @@ const lastIndexOfRole = (messages: ReadonlyArray<Message>, role: Message["role"]
// Mark the last text part of `messages[index]`. If no text part exists, mark
// the last content part regardless of type — that's the breakpoint position
// in tool-result-only messages too.
const markMessageAt = (messages: ReadonlyArray<Message>, index: number, hint: CacheHint): ReadonlyArray<Message> => {
const markMessageAt = (
messages: ReadonlyArray<Message>,
index: number,
hint: CacheHint,
budget: Budget,
): ReadonlyArray<Message> => {
if (index < 0 || index >= messages.length) return messages
const target = messages[index]!
if (target.content.length === 0) return messages
const lastTextIndex = target.content.findLastIndex((part) => part.type === "text")
const markAt = lastTextIndex >= 0 ? lastTextIndex : target.content.length - 1
const existing = target.content[markAt]!
if ("cache" in existing && existing.cache) return messages
if (("cache" in existing && existing.cache) || budget.remaining === 0) return messages
budget.remaining -= 1
const nextContent = target.content.map((part, i) => (i === markAt ? ({ ...part, cache: hint } as ContentPart) : part))
const next = new Message({ ...target, content: nextContent })
// Single pass over `messages`, substituting the one updated entry. Long
@@ -86,25 +105,42 @@ const markMessages = (
messages: ReadonlyArray<Message>,
strategy: NonNullable<CachePolicyObject["messages"]>,
hint: CacheHint,
budget: Budget,
): ReadonlyArray<Message> => {
if (messages.length === 0) return messages
if (strategy === "latest-user-message") return markMessageAt(messages, lastIndexOfRole(messages, "user"), hint)
if (strategy === "latest-assistant") return markMessageAt(messages, lastIndexOfRole(messages, "assistant"), hint)
if (strategy === "latest-user-message")
return markMessageAt(messages, lastIndexOfRole(messages, "user"), hint, budget)
if (strategy === "latest-assistant")
return markMessageAt(messages, lastIndexOfRole(messages, "assistant"), hint, budget)
const start = Math.max(0, messages.length - strategy.tail)
let next = messages
for (let i = start; i < messages.length; i++) next = markMessageAt(next, i, hint)
for (let i = start; i < messages.length; i++) next = markMessageAt(next, i, hint, budget)
return next
}
const countHints = (request: LLMRequest) =>
request.tools.reduce((count, tool) => count + (tool.cache === undefined ? 0 : 1), 0) +
request.system.reduce((count, part) => count + (part.cache === undefined ? 0 : 1), 0) +
request.messages.reduce(
(count, message) =>
count +
message.content.reduce(
(contentCount, part) => contentCount + ("cache" in part && part.cache !== undefined ? 1 : 0),
0,
),
0,
)
export const applyCachePolicy = (request: LLMRequest): LLMRequest => {
if (!RESPECTS_INLINE_HINTS.has(request.model.route.id)) return request
const policy = resolve(request.cache)
if (!policy.tools && !policy.system && !policy.messages) return request
const hint = makeHint(policy.ttlSeconds)
const tools = policy.tools ? markLastTool(request.tools, hint) : request.tools
const system = policy.system ? markLastSystem(request.system, hint) : request.system
const messages = policy.messages ? markMessages(request.messages, policy.messages, hint) : request.messages
const budget = { remaining: Math.max(0, BREAKPOINT_CAP - countHints(request)) }
const tools = policy.tools ? markLastTool(request.tools, hint, budget) : request.tools
const system = policy.system ? markSystemBoundaries(request.system, hint, budget) : request.system
const messages = policy.messages ? markMessages(request.messages, policy.messages, hint, budget) : request.messages
if (tools === request.tools && system === request.system && messages === request.messages) return request
return LLMRequest.update(request, { tools, system, messages })
+3 -21
View File
@@ -9,24 +9,13 @@ import {
LLMRequest,
LLMResponse,
Message,
type ModelInput as SchemaModelInput,
SystemPart,
ToolChoice,
ToolDefinition,
type ContentPart,
ToolResultPart,
} from "./schema"
import { make as makeTool, toDefinitions, type ToolSchema } from "./tool"
export type ModelInput = SchemaModelInput
export type MessageInput = Message.Input
export type ToolChoiceInput = ToolChoice.Input
export type ToolChoiceMode = ToolChoice.Mode
export type ToolResultInput = Parameters<typeof ToolResultPart.make>[0]
/** Input accepted by `LLM.request`, normalized into the canonical `LLMRequest` class. */
export type RequestInput = Omit<
ConstructorParameters<typeof LLMRequest>[0],
@@ -34,9 +23,9 @@ export type RequestInput = Omit<
> & {
readonly system?: string | SystemPart | ReadonlyArray<SystemPart>
readonly prompt?: string | ContentPart | ReadonlyArray<ContentPart>
readonly messages?: ReadonlyArray<Message | MessageInput>
readonly messages?: ReadonlyArray<Message | Message.Input>
readonly tools?: ReadonlyArray<ToolDefinition.Input>
readonly toolChoice?: ToolChoiceInput
readonly toolChoice?: ToolChoice.Input
readonly generation?: GenerationOptions.Input
readonly providerOptions?: ConstructorParameters<typeof LLMRequest>[0]["providerOptions"]
readonly http?: HttpOptions.Input
@@ -46,10 +35,6 @@ export const generate = LLMClient.generate
export const stream = LLMClient.stream
export const requestInput = (input: LLMRequest): RequestInput => ({
...LLMRequest.input(input),
})
export const request = (input: RequestInput) => {
const {
system: requestSystem,
@@ -74,14 +59,11 @@ export const request = (input: RequestInput) => {
})
}
export const updateRequest = (input: LLMRequest, patch: Partial<RequestInput>) =>
request({ ...requestInput(input), ...patch })
const GENERATE_OBJECT_TOOL_NAME = "generate_object"
const GENERATE_OBJECT_TOOL_DESCRIPTION = "Return the structured result by calling this tool."
type GenerateObjectBase = Omit<RequestInput, "tools" | "toolChoice" | "responseFormat">
type GenerateObjectBase = Omit<RequestInput, "tools" | "toolChoice">
export class GenerateObjectResponse<T> {
constructor(
+203 -66
View File
@@ -7,12 +7,15 @@ import { Protocol } from "../route/protocol"
import {
LLMError,
LLMEvent,
mergeJsonRecords,
Usage,
type CacheHint,
type FinishReasonDetails,
type FinishReason,
type JsonSchema,
type LLMRequest,
type MediaPart,
type ProviderOptions,
type ProviderMetadata,
type ToolCallPart,
type ToolDefinition,
@@ -31,6 +34,29 @@ const MEDIA_MIMES = new Set<string>([...ProviderShared.IMAGE_MIMES, ...ProviderS
export const DEFAULT_BASE_URL = "https://api.anthropic.com/v1"
export const PATH = "/messages"
export type ThinkingInput =
| {
readonly type: "adaptive"
readonly display?: "summarized" | "omitted"
}
| {
readonly type: "disabled"
}
| ({ readonly type: "enabled" } & (
| { readonly budgetTokens: number; readonly budget_tokens?: number }
| { readonly budgetTokens?: number; readonly budget_tokens: number }
))
export interface OptionsInput {
readonly [key: string]: unknown
readonly thinking?: ThinkingInput
readonly effort?: string
}
export type ProviderOptionsInput = ProviderOptions & {
readonly anthropic?: OptionsInput
}
// =============================================================================
// Request Body Schema
// =============================================================================
@@ -75,6 +101,15 @@ const AnthropicThinkingBlock = Schema.Struct({
cache_control: Schema.optional(AnthropicCacheControl),
})
// Safety-filtered thinking arrives as an opaque encrypted `data` payload with
// no visible text. It must round-trip verbatim so multi-turn thinking + tool
// use conversations keep their reasoning continuity.
const AnthropicRedactedThinkingBlock = Schema.Struct({
type: Schema.tag("redacted_thinking"),
data: Schema.String,
cache_control: Schema.optional(AnthropicCacheControl),
})
const AnthropicToolUseBlock = Schema.Struct({
type: Schema.tag("tool_use"),
id: Schema.String,
@@ -136,6 +171,7 @@ type AnthropicUserBlock = Schema.Schema.Type<typeof AnthropicUserBlock>
const AnthropicAssistantBlock = Schema.Union([
AnthropicTextBlock,
AnthropicThinkingBlock,
AnthropicRedactedThinkingBlock,
AnthropicToolUseBlock,
AnthropicServerToolUseBlock,
AnthropicServerToolResultBlock,
@@ -159,7 +195,7 @@ const AnthropicTool = Schema.Struct({
type AnthropicTool = Schema.Schema.Type<typeof AnthropicTool>
const AnthropicToolChoice = Schema.Union([
Schema.Struct({ type: Schema.Literals(["auto", "any"]) }),
Schema.Struct({ type: Schema.Literals(["auto", "any", "none"]) }),
Schema.Struct({ type: Schema.tag("tool"), name: Schema.String }),
])
@@ -199,12 +235,27 @@ const AnthropicBodyFields = {
export const AnthropicMessagesBody = Schema.Struct(AnthropicBodyFields)
export type AnthropicMessagesBody = Schema.Schema.Type<typeof AnthropicMessagesBody>
const AnthropicUsage = Schema.Struct({
input_tokens: Schema.optional(Schema.Number),
output_tokens: Schema.optional(Schema.Number),
cache_creation_input_tokens: optionalNull(Schema.Number),
cache_read_input_tokens: optionalNull(Schema.Number),
})
const AnthropicUsage = Schema.StructWithRest(
Schema.Struct({
input_tokens: Schema.optional(Schema.Number),
output_tokens: Schema.optional(Schema.Number),
cache_creation_input_tokens: optionalNull(Schema.Number),
cache_read_input_tokens: optionalNull(Schema.Number),
server_tool_use: optionalNull(
Schema.StructWithRest(
Schema.Struct({ web_search_requests: Schema.optional(Schema.Number) }),
[Schema.Record(Schema.String, Schema.Unknown)],
),
),
output_tokens_details: optionalNull(
Schema.StructWithRest(
Schema.Struct({ thinking_tokens: Schema.optional(Schema.Number) }),
[Schema.Record(Schema.String, Schema.Unknown)],
),
),
}),
[Schema.Record(Schema.String, Schema.Unknown)],
)
type AnthropicUsage = Schema.Schema.Type<typeof AnthropicUsage>
const AnthropicStreamBlock = Schema.Struct({
@@ -214,6 +265,9 @@ const AnthropicStreamBlock = Schema.Struct({
text: Schema.optional(Schema.String),
thinking: Schema.optional(Schema.String),
signature: Schema.optional(Schema.String),
// redacted_thinking blocks arrive whole in content_block_start with the
// encrypted payload in `data`; there is no streaming delta sequence.
data: Schema.optional(Schema.String),
input: Schema.optional(Schema.Unknown),
// *_tool_result blocks arrive whole as content_block_start (no streaming
// delta) with the structured payload in `content` and the originating
@@ -251,7 +305,12 @@ type AnthropicEvent = Schema.Schema.Type<typeof AnthropicEvent>
interface ParserState {
readonly tools: ToolStream.State<number>
readonly reasoningSignatures: Readonly<Record<number, string>>
readonly usage?: Usage
readonly pendingFinish?: {
readonly reason: FinishReasonDetails
readonly providerMetadata?: ProviderMetadata
}
readonly lifecycle: Lifecycle.State
}
@@ -287,6 +346,12 @@ const signatureFromMetadata = (metadata: ProviderMetadata | undefined): string |
return typeof anthropic.signature === "string" ? anthropic.signature : undefined
}
const redactedDataFromMetadata = (metadata: ProviderMetadata | undefined): string | undefined => {
const anthropic = metadata?.anthropic
if (!ProviderShared.isRecord(anthropic)) return undefined
return typeof anthropic.redactedData === "string" ? anthropic.redactedData : undefined
}
const lowerTool = (breakpoints: Cache.Breakpoints, tool: ToolDefinition, inputSchema: JsonSchema): AnthropicTool => ({
name: tool.name,
description: tool.description,
@@ -297,7 +362,7 @@ const lowerTool = (breakpoints: Cache.Breakpoints, tool: ToolDefinition, inputSc
const lowerToolChoice = (toolChoice: NonNullable<LLMRequest["toolChoice"]>) =>
ProviderShared.matchToolChoice("Anthropic Messages", toolChoice, {
auto: () => ({ type: "auto" as const }),
none: () => undefined,
none: () => ({ type: "none" as const }),
required: () => ({ type: "any" as const }),
tool: (name) => ({ type: "tool" as const, name }),
})
@@ -330,7 +395,10 @@ const lowerServerToolResult = Effect.fn("AnthropicMessages.lowerServerToolResult
const wireType = serverToolResultType(part.name)
if (!wireType)
return yield* invalid(`Anthropic Messages does not know how to round-trip server tool result for ${part.name}`)
return { type: wireType, tool_use_id: part.id, content: part.result.value } satisfies AnthropicServerToolResultBlock
// Prefer the provider-owned replay payload; fall back to the result value for
// histories constructed directly from provider events.
const payload = part.providerMetadata?.anthropic?.["result"] ?? part.result.value
return { type: wireType, tool_use_id: part.id, content: payload } satisfies AnthropicServerToolResultBlock
})
const lowerMedia = Effect.fn("AnthropicMessages.lowerMedia")(function* (part: MediaPart) {
@@ -469,11 +537,16 @@ const lowerMessages = Effect.fn("AnthropicMessages.lowerMessages")(function* (
continue
}
if (part.type === "reasoning") {
content.push({
type: "thinking",
thinking: part.text,
signature: part.encrypted ?? signatureFromMetadata(part.providerMetadata),
})
// Mirrors Vercel's @ai-sdk/anthropic: a signature marks visible
// thinking; only signature-less parts carrying redactedData
// round-trip as opaque redacted_thinking blocks.
const signature = part.encrypted ?? signatureFromMetadata(part.providerMetadata)
const redactedData = redactedDataFromMetadata(part.providerMetadata)
if (signature === undefined && redactedData !== undefined) {
content.push({ type: "redacted_thinking", data: redactedData })
continue
}
content.push({ type: "thinking", thinking: part.text, signature })
continue
}
if (part.type === "tool-call") {
@@ -510,39 +583,39 @@ const lowerMessages = Effect.fn("AnthropicMessages.lowerMessages")(function* (
return messages
})
const anthropicOptions = (request: LLMRequest) => request.providerOptions?.anthropic
const resolveOptions = Effect.fn("AnthropicMessages.resolveOptions")(function* (request: LLMRequest) {
const input = request.providerOptions?.anthropic
return {
thinking: yield* resolveThinking(input?.thinking),
effort: typeof input?.effort === "string" ? input.effort : undefined,
}
})
const lowerThinking = Effect.fn("AnthropicMessages.lowerThinking")(function* (request: LLMRequest) {
const thinking = anthropicOptions(request)?.thinking
if (!ProviderShared.isRecord(thinking)) return undefined
if (thinking.type === "adaptive") {
const resolveThinking = Effect.fn("AnthropicMessages.resolveThinking")(function* (input: unknown) {
if (!ProviderShared.isRecord(input)) return undefined
if (input.type === "adaptive") {
const display =
thinking.display === "summarized"
input.display === "summarized"
? ("summarized" as const)
: thinking.display === "omitted"
: input.display === "omitted"
? ("omitted" as const)
: undefined
return { type: "adaptive" as const, ...(display === undefined ? {} : { display }) }
}
if (thinking.type === "disabled") return { type: "disabled" as const }
if (thinking.type !== "enabled") return undefined
if (input.type === "disabled") return { type: "disabled" as const }
if (input.type !== "enabled") return undefined
const budget =
typeof thinking.budgetTokens === "number"
? thinking.budgetTokens
: typeof thinking.budget_tokens === "number"
? thinking.budget_tokens
typeof input.budgetTokens === "number"
? input.budgetTokens
: typeof input.budget_tokens === "number"
? input.budget_tokens
: undefined
if (budget === undefined) return yield* invalid("Anthropic thinking provider option requires budgetTokens")
if (budget === undefined)
return yield* ProviderShared.invalidRequest("Anthropic thinking provider option requires budgetTokens")
return { type: "enabled" as const, budget_tokens: budget }
})
const outputConfig = (request: LLMRequest) => {
const effort = anthropicOptions(request)?.effort
return typeof effort === "string" ? { effort } : undefined
}
const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (request: LLMRequest) {
const toolChoice = request.toolChoice ? yield* lowerToolChoice(request.toolChoice) : undefined
const generation = request.generation
const toolSchemaCompatibility = request.model.compatibility?.toolSchema
const outputLimit = request.model.defaults?.limits?.output ?? request.model.route.defaults.limits?.output ?? 4096
@@ -551,7 +624,7 @@ const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (reques
// over-mark we keep their tool hints and shed the message-tail ones first.
const breakpoints = Cache.newBreakpoints(ANTHROPIC_BREAKPOINT_CAP)
const tools =
request.tools.length === 0 || request.toolChoice?.type === "none"
request.tools.length === 0
? undefined
: request.tools.map((tool) =>
lowerTool(
@@ -560,6 +633,8 @@ const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (reques
ToolSchemaProjection.modelCompatibility(tool.inputSchema, toolSchemaCompatibility),
),
)
// Anthropic rejects tool_choice when tools are absent; "none" is only meaningful with tools present.
const toolChoice = tools === undefined || !request.toolChoice ? undefined : yield* lowerToolChoice(request.toolChoice)
const system =
request.system.length === 0
? undefined
@@ -574,6 +649,7 @@ const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (reques
`Anthropic Messages: dropped ${breakpoints.dropped} cache breakpoint(s); the API allows at most ${ANTHROPIC_BREAKPOINT_CAP} per request.`,
)
}
const options = yield* resolveOptions(request)
return {
model: request.model.id,
system,
@@ -586,8 +662,8 @@ const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (reques
top_p: generation?.topP,
top_k: generation?.topK,
stop_sequences: generation?.stop,
thinking: yield* lowerThinking(request),
output_config: outputConfig(request),
thinking: options.thinking,
output_config: options.effort === undefined ? undefined : { effort: options.effort },
}
})
@@ -596,7 +672,7 @@ const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (reques
// =============================================================================
const mapFinishReason = (reason: string | null | undefined): FinishReason => {
if (reason === "end_turn" || reason === "stop_sequence" || reason === "pause_turn") return "stop"
if (reason === "max_tokens") return "length"
if (reason === "max_tokens" || reason === "model_context_window_exceeded") return "length"
if (reason === "tool_use") return "tool-calls"
if (reason === "refusal") return "content-filter"
return "unknown"
@@ -606,9 +682,8 @@ const mapFinishReason = (reason: string | null | undefined): FinishReason => {
// `input_tokens` is the *non-cached* count per the Messages API docs, with
// cache reads and writes as separate fields. We sum them to derive the
// inclusive `inputTokens` the rest of the contract expects. Extended
// thinking tokens are *not* broken out by Anthropic — they're billed as
// part of `output_tokens`, so `reasoningTokens` stays `undefined` and
// `outputTokens` carries the combined total.
// thinking tokens are included in `output_tokens`; newer responses also
// expose that subset through `output_tokens_details.thinking_tokens`.
const mapUsage = (usage: AnthropicUsage | undefined): Usage | undefined => {
if (!usage) return undefined
const nonCached = usage.input_tokens
@@ -621,6 +696,7 @@ const mapUsage = (usage: AnthropicUsage | undefined): Usage | undefined => {
nonCachedInputTokens: nonCached,
cacheReadInputTokens: cacheRead,
cacheWriteInputTokens: cacheWrite,
reasoningTokens: usage.output_tokens_details?.thinking_tokens,
totalTokens: ProviderShared.totalTokens(inputTokens, usage.output_tokens, undefined),
providerMetadata: { anthropic: usage },
})
@@ -639,18 +715,18 @@ const mergeUsage = (left: Usage | undefined, right: Usage | undefined) => {
const cacheWriteInputTokens = right.cacheWriteInputTokens ?? left.cacheWriteInputTokens
const inputTokens = ProviderShared.sumTokens(nonCachedInputTokens, cacheReadInputTokens, cacheWriteInputTokens)
const outputTokens = right.outputTokens ?? left.outputTokens
const reasoningTokens = right.reasoningTokens ?? left.reasoningTokens
return new Usage({
inputTokens,
outputTokens,
nonCachedInputTokens,
cacheReadInputTokens,
cacheWriteInputTokens,
reasoningTokens,
totalTokens: ProviderShared.totalTokens(inputTokens, outputTokens, undefined),
providerMetadata: {
anthropic: {
...left.providerMetadata?.["anthropic"],
...right.providerMetadata?.["anthropic"],
},
anthropic:
mergeJsonRecords(left.providerMetadata?.["anthropic"], right.providerMetadata?.["anthropic"]) ?? {},
},
})
}
@@ -680,7 +756,9 @@ const serverToolResultEvent = (block: NonNullable<AnthropicEvent["content_block"
name: SERVER_TOOL_RESULT_NAMES[block.type],
result: isError ? { type: "error", value: block.content } : { type: "json", value: block.content },
providerExecuted: true,
providerMetadata: anthropicMetadata({ blockType: block.type }),
// The complete payload is irreducible provider replay state: subsequent
// stateless requests must round-trip the typed result block verbatim.
providerMetadata: anthropicMetadata({ blockType: block.type, result: block.content }),
})
}
@@ -707,6 +785,10 @@ const onContentBlockStart = (state: ParserState, event: AnthropicEvent): StepRes
tools: ToolStream.start(state.tools, event.index, {
id: block.id ?? String(event.index),
name: block.name ?? "",
input:
block.input !== undefined && (!ProviderShared.isRecord(block.input) || Object.keys(block.input).length > 0)
? ProviderShared.encodeJson(block.input)
: undefined,
providerExecuted: block.type === "server_tool_use",
}),
},
@@ -721,20 +803,50 @@ const onContentBlockStart = (state: ParserState, event: AnthropicEvent): StepRes
]
}
if (block.type === "text" && block.text) {
if (block.type === "text" && block.text !== undefined) {
const events: LLMEvent[] = []
const id = `text-${event.index ?? 0}`
const lifecycle = Lifecycle.textStart(state.lifecycle, events, id)
return [
{ ...state, lifecycle: Lifecycle.textDelta(state.lifecycle, events, `text-${event.index ?? 0}`, block.text) },
{ ...state, lifecycle: block.text ? Lifecycle.textDelta(lifecycle, events, id, block.text) : lifecycle },
events,
]
}
if (block.type === "thinking" && block.thinking) {
if (block.type === "thinking" && block.thinking !== undefined) {
const events: LLMEvent[] = []
const id = `reasoning-${event.index ?? 0}`
const providerMetadata = block.signature === undefined ? undefined : anthropicMetadata({ signature: block.signature })
const lifecycle = Lifecycle.reasoningStart(state.lifecycle, events, id, providerMetadata)
return [
{
...state,
lifecycle: block.thinking
? Lifecycle.reasoningDelta(lifecycle, events, id, block.thinking, providerMetadata)
: lifecycle,
reasoningSignatures:
event.index === undefined || block.signature === undefined
? state.reasoningSignatures
: { ...state.reasoningSignatures, [event.index]: block.signature },
},
events,
]
}
// Redacted thinking surfaces as an empty reasoning part carrying the opaque
// payload as `redactedData` metadata (same model as Vercel's
// @ai-sdk/anthropic). The existing content_block_stop closes the part.
if (block.type === "redacted_thinking" && block.data !== undefined) {
const events: LLMEvent[] = []
return [
{
...state,
lifecycle: Lifecycle.reasoningDelta(state.lifecycle, events, `reasoning-${event.index ?? 0}`, block.thinking),
lifecycle: Lifecycle.reasoningStart(
state.lifecycle,
events,
`reasoning-${event.index ?? 0}`,
anthropicMetadata({ redactedData: block.data }),
),
},
events,
]
@@ -772,18 +884,13 @@ const onContentBlockDelta = Effect.fn("AnthropicMessages.onContentBlockDelta")(f
}
if (delta?.type === "signature_delta" && delta.signature) {
const events: LLMEvent[] = []
const index = event.index ?? 0
return [
{
...state,
lifecycle: Lifecycle.reasoningEnd(
state.lifecycle,
events,
`reasoning-${event.index ?? 0}`,
anthropicMetadata({ signature: delta.signature }),
),
reasoningSignatures: { ...state.reasoningSignatures, [index]: delta.signature },
},
events,
NO_EVENTS,
] satisfies StepResult
}
@@ -814,28 +921,53 @@ const onContentBlockStop = Effect.fn("AnthropicMessages.onContentBlockStop")(fun
const result = yield* ToolStream.finish(ADAPTER, state.tools, event.index)
const events: LLMEvent[] = []
const resultEvents = result.events ?? []
const signature = state.reasoningSignatures[event.index]
const lifecycle = resultEvents.length
? Lifecycle.stepStart(state.lifecycle, events)
: Lifecycle.reasoningEnd(
Lifecycle.textEnd(state.lifecycle, events, `text-${event.index}`),
events,
`reasoning-${event.index}`,
signature === undefined ? undefined : anthropicMetadata({ signature }),
)
events.push(...resultEvents)
return [{ ...state, lifecycle, tools: result.tools }, events] satisfies StepResult
const reasoningSignatures = { ...state.reasoningSignatures }
delete reasoningSignatures[event.index]
return [{ ...state, lifecycle, tools: result.tools, reasoningSignatures }, events] satisfies StepResult
})
const onMessageDelta = (state: ParserState, event: AnthropicEvent): StepResult => {
const usage = mergeUsage(state.usage, mapUsage(event.usage))
return [
{
...state,
usage,
pendingFinish: {
reason: {
normalized: mapFinishReason(event.delta?.stop_reason),
raw: event.delta?.stop_reason ?? undefined,
},
providerMetadata:
event.delta?.stop_sequence === null || event.delta?.stop_sequence === undefined
? undefined
: anthropicMetadata({ stopSequence: event.delta.stop_sequence }),
},
},
NO_EVENTS,
]
}
const onMessageStop = (state: ParserState): StepResult => {
const events: LLMEvent[] = []
const lifecycle = Lifecycle.finish(state.lifecycle, events, {
reason: mapFinishReason(event.delta?.stop_reason),
usage,
providerMetadata: event.delta?.stop_sequence
? anthropicMetadata({ stopSequence: event.delta.stop_sequence })
: undefined,
reason: state.pendingFinish?.reason ?? {
normalized: "unknown",
raw: undefined,
},
usage: state.usage,
providerMetadata: state.pendingFinish?.providerMetadata,
})
return [{ ...state, lifecycle, usage }, events]
return [{ ...state, lifecycle }, events]
}
// Prefix `error.type` so overloads, rate limits, and quota errors are visible
@@ -860,6 +992,7 @@ const step = (state: ParserState, event: AnthropicEvent) => {
if (event.type === "content_block_delta") return onContentBlockDelta(state, event)
if (event.type === "content_block_stop") return onContentBlockStop(state, event)
if (event.type === "message_delta") return Effect.succeed(onMessageDelta(state, event))
if (event.type === "message_stop") return Effect.succeed(onMessageStop(state))
if (event.type === "error") return onError(event)
return Effect.succeed<StepResult>([state, NO_EVENTS])
}
@@ -880,7 +1013,11 @@ export const protocol = Protocol.make({
},
stream: {
event: Protocol.jsonEvent(AnthropicEvent),
initial: () => ({ tools: ToolStream.empty<number>(), lifecycle: Lifecycle.initial() }),
initial: () => ({
tools: ToolStream.empty<number>(),
reasoningSignatures: {},
lifecycle: Lifecycle.initial(),
}),
step,
},
})
+90 -28
View File
@@ -8,6 +8,7 @@ import {
Usage,
type CacheHint,
type FinishReason,
type FinishReasonDetails,
type JsonSchema,
type LLMRequest,
type ModelToolSchemaCompatibility,
@@ -65,14 +66,15 @@ const BedrockToolResultBlock = Schema.Struct({
type BedrockToolResultBlock = Schema.Schema.Type<typeof BedrockToolResultBlock>
const BedrockReasoningBlock = Schema.Struct({
reasoningContent: Schema.Struct({
reasoningText: Schema.optional(
Schema.Struct({
reasoningContent: Schema.Union([
Schema.Struct({
reasoningText: Schema.Struct({
text: Schema.String,
signature: Schema.optional(Schema.String),
}),
),
}),
}),
Schema.Struct({ redactedContent: Schema.String }),
]),
})
const BedrockUserBlock = Schema.Union([
@@ -153,6 +155,12 @@ const BedrockUsageSchema = Schema.Struct({
})
type BedrockUsageSchema = Schema.Schema.Type<typeof BedrockUsageSchema>
const BedrockStreamException = Schema.Struct({
message: Schema.optional(Schema.String),
originalMessage: Schema.optional(Schema.String),
originalStatusCode: Schema.optional(Schema.Number),
})
// Streaming event shape — the AWS event stream wraps each JSON payload by its
// `:event-type` header (e.g. `messageStart`, `contentBlockDelta`). We
// reconstruct that wrapping in `decodeFrames` below so the event schema can
@@ -180,6 +188,11 @@ const BedrockEvent = Schema.Struct({
Schema.Struct({
text: Schema.optional(Schema.String),
signature: Schema.optional(Schema.String),
// Blob fields in Bedrock's JSON event stream are base64 strings.
redactedContent: Schema.optional(Schema.String),
// Vercel's Bedrock provider exposes the same delta under
// Anthropic's shorter `data` spelling.
data: Schema.optional(Schema.String),
}),
),
}),
@@ -199,11 +212,11 @@ const BedrockEvent = Schema.Struct({
metrics: Schema.optional(Schema.Unknown),
}),
),
internalServerException: Schema.optional(Schema.Struct({ message: Schema.String })),
modelStreamErrorException: Schema.optional(Schema.Struct({ message: Schema.String })),
validationException: Schema.optional(Schema.Struct({ message: Schema.String })),
throttlingException: Schema.optional(Schema.Struct({ message: Schema.String })),
serviceUnavailableException: Schema.optional(Schema.Struct({ message: Schema.String })),
internalServerException: Schema.optional(BedrockStreamException),
modelStreamErrorException: Schema.optional(BedrockStreamException),
validationException: Schema.optional(BedrockStreamException),
throttlingException: Schema.optional(BedrockStreamException),
serviceUnavailableException: Schema.optional(BedrockStreamException),
})
type BedrockEvent = Schema.Schema.Type<typeof BedrockEvent>
@@ -259,6 +272,13 @@ const reasoningSignature = (part: ReasoningPart) => {
)
}
const reasoningRedactedData = (part: ReasoningPart) => {
const bedrock = part.providerMetadata?.bedrock
return ProviderShared.isRecord(bedrock) && typeof bedrock.redactedData === "string"
? bedrock.redactedData
: undefined
}
const lowerToolCall = (part: ToolCallPart): BedrockToolUseBlock => ({
toolUse: {
toolUseId: part.id,
@@ -348,11 +368,13 @@ const lowerMessages = Effect.fn("BedrockConverse.lowerMessages")(function* (
continue
}
if (part.type === "reasoning") {
content.push({
reasoningContent: {
reasoningText: { text: part.text, signature: reasoningSignature(part) },
},
})
const signature = reasoningSignature(part)
const redactedData = reasoningRedactedData(part)
if (signature === undefined && redactedData !== undefined) {
content.push({ reasoningContent: { redactedContent: redactedData } })
continue
}
content.push({ reasoningContent: { reasoningText: { text: part.text, signature } } })
continue
}
if (part.type === "tool-call") {
@@ -392,8 +414,13 @@ const fromRequest = Effect.fn("BedrockConverse.fromRequest")(function* (request:
// tools → system → messages order to favour the highest-impact prefixes.
const breakpoints = BedrockCache.breakpoints()
const toolConfig =
request.tools.length > 0 && request.toolChoice?.type !== "none"
? { tools: lowerTools(request.model.compatibility?.toolSchema, breakpoints, request.tools), toolChoice }
request.tools.length > 0
? {
tools: lowerTools(request.model.compatibility?.toolSchema, breakpoints, request.tools),
// Converse has no native "none". Keep definitions stable for prompt
// caching and omit only the unsupported choice.
toolChoice,
}
: undefined
const system = request.system.length === 0 ? undefined : lowerSystem(breakpoints, request.system)
const messages = yield* lowerMessages(request, breakpoints)
@@ -430,9 +457,10 @@ const fromRequest = Effect.fn("BedrockConverse.fromRequest")(function* (request:
// =============================================================================
const mapFinishReason = (reason: string): FinishReason => {
if (reason === "end_turn" || reason === "stop_sequence") return "stop"
if (reason === "max_tokens") return "length"
if (reason === "max_tokens" || reason === "model_context_window_exceeded") return "length"
if (reason === "tool_use") return "tool-calls"
if (reason === "content_filtered" || reason === "guardrail_intervened") return "content-filter"
if (reason === "malformed_model_output" || reason === "malformed_tool_use") return "error"
return "unknown"
}
@@ -461,7 +489,7 @@ interface ParserState {
// Bedrock splits the finish into `messageStop` (carries `stopReason`) and
// `metadata` (carries usage). Hold the terminal event in state so `onHalt`
// can emit exactly one finish after both chunks have had a chance to arrive.
readonly pendingFinish: { readonly reason: FinishReason; readonly usage?: Usage } | undefined
readonly pendingFinish: { readonly reason: FinishReasonDetails; readonly usage?: Usage } | undefined
readonly hasToolCalls: boolean
readonly lifecycle: Lifecycle.State
readonly reasoningSignatures: Readonly<Record<number, string>>
@@ -512,12 +540,26 @@ const step = (state: ParserState, event: BedrockEvent) =>
const index = event.contentBlockDelta.contentBlockIndex
const reasoning = event.contentBlockDelta.delta.reasoningContent
const events: LLMEvent[] = []
const redactedData = reasoning.redactedContent ?? reasoning.data
const providerMetadata = reasoning.signature
? bedrockMetadata({ signature: reasoning.signature })
: redactedData !== undefined
? bedrockMetadata({ redactedData })
: undefined
const lifecycle =
reasoning.text !== undefined || providerMetadata !== undefined
? Lifecycle.reasoningDelta(
state.lifecycle,
events,
`reasoning-${index}`,
reasoning.text ?? "",
providerMetadata,
)
: state.lifecycle
return [
{
...state,
lifecycle: reasoning.text
? Lifecycle.reasoningDelta(state.lifecycle, events, `reasoning-${index}`, reasoning.text)
: state.lifecycle,
lifecycle,
reasoningSignatures: reasoning.signature
? { ...state.reasoningSignatures, [index]: reasoning.signature }
: state.reasoningSignatures,
@@ -578,15 +620,30 @@ const step = (state: ParserState, event: BedrockEvent) =>
return [
{
...state,
pendingFinish: { reason: mapFinishReason(event.messageStop.stopReason), usage: state.pendingFinish?.usage },
pendingFinish: {
reason: {
normalized: mapFinishReason(event.messageStop.stopReason),
raw: event.messageStop.stopReason,
},
usage: state.pendingFinish?.usage,
},
},
[],
] as const
}
if (event.metadata) {
const usage = mapUsage(event.metadata.usage)
return [{ ...state, pendingFinish: { reason: state.pendingFinish?.reason ?? "stop", usage } }, []] as const
const usage = mapUsage(event.metadata.usage) ?? state.pendingFinish?.usage
return [
{
...state,
pendingFinish: {
reason: state.pendingFinish?.reason ?? { normalized: "stop" },
usage,
},
},
[],
] as const
}
const exception = (
@@ -603,7 +660,7 @@ const step = (state: ParserState, event: BedrockEvent) =>
module: ADAPTER,
method: "stream",
reason: classifyProviderFailure({
message: exception[1]?.message ?? "Bedrock Converse stream error",
message: exception[1]?.message ?? exception[1]?.originalMessage ?? "Bedrock Converse stream error",
code: exception[0],
}),
})
@@ -619,8 +676,13 @@ const onHalt = (state: ParserState): ReadonlyArray<LLMEvent> =>
? (() => {
const events: LLMEvent[] = []
Lifecycle.finish(state.lifecycle, events, {
reason:
state.pendingFinish.reason === "stop" && state.hasToolCalls ? "tool-calls" : state.pendingFinish.reason,
reason: {
...state.pendingFinish.reason,
normalized:
state.pendingFinish.reason.normalized === "stop" && state.hasToolCalls
? "tool-calls"
: state.pendingFinish.reason.normalized,
},
usage: state.pendingFinish.usage,
})
return events
@@ -53,8 +53,22 @@ const consumeFrames = (route: string) => (state: FrameBufferState, chunk: Uint8A
})
cursor = { buffer: cursor.buffer, offset: cursor.offset + totalLength }
if (decoded.headers[":message-type"]?.value !== "event") continue
const eventType = decoded.headers[":event-type"]?.value
const messageType = decoded.headers[":message-type"]?.value
if (messageType === "error") {
const code = decoded.headers[":error-code"]?.value
const message = decoded.headers[":error-message"]?.value
return yield* ProviderShared.eventError(
route,
[code, message].filter((value): value is string => typeof value === "string").join(": ") ||
"Bedrock Converse event-stream error",
)
}
const eventType =
messageType === "event"
? decoded.headers[":event-type"]?.value
: messageType === "exception"
? decoded.headers[":exception-type"]?.value
: undefined
if (typeof eventType !== "string") continue
const payload = utf8.decode(decoded.body)
if (!payload) continue
+46 -15
View File
@@ -11,6 +11,7 @@ import {
type JsonSchema,
type LLMRequest,
type MediaPart,
type ProviderOptions,
type ProviderMetadata,
type TextPart,
type ToolCallPart,
@@ -26,6 +27,18 @@ const ADAPTER = "gemini"
const MEDIA_MIMES = new Set<string>(ProviderShared.MEDIA_MIMES)
export const DEFAULT_BASE_URL = "https://generativelanguage.googleapis.com/v1beta"
export interface OptionsInput {
readonly [key: string]: unknown
readonly thinkingConfig?: {
readonly thinkingBudget?: number
readonly includeThoughts?: boolean
}
}
export type ProviderOptionsInput = ProviderOptions & {
readonly gemini?: OptionsInput
}
// =============================================================================
// Request Body Schema
// =============================================================================
@@ -203,7 +216,9 @@ const thoughtSignature = (providerMetadata: ProviderMetadata | undefined) => {
const functionCallId = (providerMetadata: ProviderMetadata | undefined) => {
const google = providerMetadata?.google
return ProviderShared.isRecord(google) && typeof google.functionCallId === "string" ? google.functionCallId : undefined
return ProviderShared.isRecord(google) && typeof google.functionCallId === "string"
? google.functionCallId
: undefined
}
const lowerToolCall = (part: ToolCallPart) => ({
@@ -300,21 +315,22 @@ const lowerMessages = Effect.fn("Gemini.lowerMessages")(function* (request: LLMR
return contents
})
const geminiOptions = (request: LLMRequest) => request.providerOptions?.gemini
const thinkingConfig = (request: LLMRequest) => {
const value = geminiOptions(request)?.thinkingConfig
if (!ProviderShared.isRecord(value)) return undefined
const result = {
const resolveOptions = (request: LLMRequest) => {
const value = request.providerOptions?.gemini?.thinkingConfig
if (!ProviderShared.isRecord(value)) return {}
const thinkingConfig = {
thinkingBudget: typeof value.thinkingBudget === "number" ? value.thinkingBudget : undefined,
includeThoughts: typeof value.includeThoughts === "boolean" ? value.includeThoughts : undefined,
}
return Object.values(result).some((item) => item !== undefined) ? result : undefined
return {
thinkingConfig: Object.values(thinkingConfig).some((item) => item !== undefined) ? thinkingConfig : undefined,
}
}
const fromRequest = Effect.fn("Gemini.fromRequest")(function* (request: LLMRequest) {
const toolsEnabled = request.tools.length > 0 && request.toolChoice?.type !== "none"
const hasTools = request.tools.length > 0
const generation = request.generation
const options = resolveOptions(request)
const toolSchemaCompatibility = request.model.compatibility?.toolSchema
const generationConfig = {
maxOutputTokens: generation?.maxTokens,
@@ -322,14 +338,14 @@ const fromRequest = Effect.fn("Gemini.fromRequest")(function* (request: LLMReque
topP: generation?.topP,
topK: generation?.topK,
stopSequences: generation?.stop,
thinkingConfig: thinkingConfig(request),
thinkingConfig: options.thinkingConfig,
}
return {
contents: yield* lowerMessages(request),
systemInstruction:
request.system.length === 0 ? undefined : { parts: [{ text: ProviderShared.joinText(request.system) }] },
tools: toolsEnabled
tools: hasTools
? [
{
functionDeclarations: request.tools.map((tool) =>
@@ -338,7 +354,7 @@ const fromRequest = Effect.fn("Gemini.fromRequest")(function* (request: LLMReque
},
]
: undefined,
toolConfig: toolsEnabled && request.toolChoice ? yield* lowerToolConfig(request.toolChoice) : undefined,
toolConfig: hasTools && request.toolChoice ? yield* lowerToolConfig(request.toolChoice) : undefined,
generationConfig: Object.values(generationConfig).some((value) => value !== undefined)
? generationConfig
: undefined,
@@ -382,10 +398,22 @@ const mapFinishReason = (finishReason: string | undefined, hasToolCalls: boolean
finishReason === "SAFETY" ||
finishReason === "BLOCKLIST" ||
finishReason === "PROHIBITED_CONTENT" ||
finishReason === "SPII"
finishReason === "SPII" ||
finishReason === "MODEL_ARMOR" ||
finishReason === "IMAGE_PROHIBITED_CONTENT" ||
finishReason === "IMAGE_RECITATION" ||
finishReason === "LANGUAGE"
)
return "content-filter"
if (finishReason === "MALFORMED_FUNCTION_CALL") return "error"
if (
finishReason === "MALFORMED_FUNCTION_CALL" ||
finishReason === "UNEXPECTED_TOOL_CALL" ||
finishReason === "NO_IMAGE" ||
finishReason === "TOO_MANY_TOOL_CALLS" ||
finishReason === "MISSING_THOUGHT_SIGNATURE" ||
finishReason === "MALFORMED_RESPONSE"
)
return "error"
return "unknown"
}
@@ -402,7 +430,10 @@ const finish = (state: ParserState): ReadonlyArray<LLMEvent> =>
)
: state.lifecycle
Lifecycle.finish(lifecycle, events, {
reason: mapFinishReason(state.finishReason, state.hasToolCalls),
reason: {
normalized: mapFinishReason(state.finishReason, state.hasToolCalls),
raw: state.finishReason,
},
usage: state.usage,
})
return events
+1
View File
@@ -6,3 +6,4 @@ export * as OpenAIImages from "./openai-images"
export * as OpenAICompatibleChat from "./openai-compatible-chat"
export * as OpenAICompatibleResponses from "./openai-compatible-responses"
export * as OpenAIResponses from "./openai-responses"
export * as OpenResponses from "./open-responses"
+1070
View File
@@ -0,0 +1,1070 @@
import { Effect, Schema } from "effect"
import { HttpTransport } from "../route/transport"
import { Protocol } from "../route/protocol"
import {
LLMError,
LLMEvent,
Usage,
type FinishReason,
type JsonSchema,
type LLMRequest,
type MediaPart,
type ProviderMetadata,
type ReasoningPart,
type TextPart,
type ToolCallPart,
type ToolDefinition,
type ToolContent,
type ToolResultPart,
} from "../schema"
import { JsonObject, optionalArray, optionalNull, ProviderShared } from "./shared"
import { classifyProviderFailure } from "../provider-error"
import { OpenResponsesOptions } from "./utils/open-responses-options"
import { Lifecycle } from "./utils/lifecycle"
import { ToolSchemaProjection } from "./utils/tool-schema"
import { ToolStream } from "./utils/tool-stream"
const ADAPTER = "open-responses"
const NAME = "Open Responses"
const MEDIA_MIMES = new Set<string>([...ProviderShared.IMAGE_MIMES, ...ProviderShared.PDF_MIMES])
export const PATH = "/responses"
// =============================================================================
// Request Body Schema
// =============================================================================
const OpenResponsesInputText = Schema.Struct({
type: Schema.tag("input_text"),
text: Schema.String,
})
const OpenResponsesInputImage = Schema.Struct({
type: Schema.tag("input_image"),
image_url: Schema.String,
})
const OpenResponsesInputFile = Schema.Struct({
type: Schema.tag("input_file"),
filename: Schema.String,
file_data: Schema.String,
mime_type: Schema.optional(Schema.String),
})
const MediaInput = Schema.Union([OpenResponsesInputImage, OpenResponsesInputFile])
export type MediaInput = Schema.Schema.Type<typeof MediaInput>
const OpenResponsesInputContent = Schema.Union([OpenResponsesInputText, MediaInput])
const OpenResponsesOutputText = Schema.Struct({
type: Schema.tag("output_text"),
text: Schema.String,
})
export const MessagePhase = Schema.Literals(["commentary", "final_answer"])
type MessagePhase = Schema.Schema.Type<typeof MessagePhase>
const OpenResponsesReasoningSummaryText = Schema.Struct({
type: Schema.tag("summary_text"),
text: Schema.String,
})
const OpenResponsesReasoningItem = Schema.Struct({
type: Schema.tag("reasoning"),
id: Schema.optionalKey(Schema.String),
summary: Schema.Array(OpenResponsesReasoningSummaryText),
encrypted_content: optionalNull(Schema.String),
})
const OpenResponsesItemReference = Schema.Struct({
type: Schema.tag("item_reference"),
id: Schema.String,
})
// `function_call_output.output` accepts either a plain string or an ordered
// array of content items so tools can return images and files in addition to text.
// https://www.openresponses.org/reference
const OpenResponsesFunctionCallOutputContent = Schema.Union([
OpenResponsesInputText,
OpenResponsesInputImage,
OpenResponsesInputFile,
])
const OpenResponsesFunctionCallOutput = Schema.Union([
Schema.String,
Schema.Array(OpenResponsesFunctionCallOutputContent),
])
export const InputItem = Schema.Union([
Schema.Struct({ role: Schema.tag("system"), content: Schema.String }),
Schema.Struct({ role: Schema.tag("user"), content: Schema.Array(OpenResponsesInputContent) }),
Schema.Struct({
role: Schema.tag("assistant"),
content: Schema.Array(OpenResponsesOutputText),
phase: Schema.optionalKey(MessagePhase),
}),
OpenResponsesReasoningItem,
OpenResponsesItemReference,
Schema.Struct({
type: Schema.tag("function_call"),
call_id: Schema.String,
name: Schema.String,
arguments: Schema.String,
}),
Schema.Struct({
type: Schema.tag("function_call_output"),
call_id: Schema.String,
output: OpenResponsesFunctionCallOutput,
}),
])
type OpenResponsesInputItem = Schema.Schema.Type<typeof InputItem>
type LoweredInputItem =
| OpenResponsesInputItem
| {
readonly role: "assistant"
readonly content: ReadonlyArray<{ readonly type: "output_text"; readonly text: string }>
readonly phase?: MessagePhase | null
}
// Mutable counterpart of the schema reasoning item so `lowerMessages` can fold
// multiple streamed summary parts into the same item before flushing.
type OpenResponsesReasoningInput = {
type: "reasoning"
id: string
summary: Array<{ type: "summary_text"; text: string }>
encrypted_content?: string | null
}
type OpenResponsesReasoningReplay = Omit<OpenResponsesReasoningInput, "id">
export const Tool = Schema.Struct({
type: Schema.tag("function"),
name: Schema.String,
description: Schema.String,
parameters: JsonObject,
strict: Schema.optional(Schema.Boolean),
})
export const ToolChoice = Schema.Union([
Schema.Literals(["auto", "none", "required"]),
Schema.Struct({ type: Schema.tag("function"), name: Schema.String }),
])
// Fields shared between the HTTP body and the WebSocket `response.create`
// message. The HTTP body adds `stream: true`; the WebSocket message adds
// `type: "response.create"`. Defining the shared shape once keeps the two
// transports in sync without a destructure-and-strip dance.
export const coreFields = {
model: Schema.String,
input: Schema.Array(InputItem),
instructions: Schema.optional(Schema.String),
tools: optionalArray(Tool),
tool_choice: Schema.optional(ToolChoice),
store: Schema.optional(Schema.Boolean),
service_tier: Schema.optional(OpenResponsesOptions.ServiceTierSchema),
prompt_cache_key: Schema.optional(Schema.String),
include: optionalArray(OpenResponsesOptions.ResponseIncludableSchema),
reasoning: Schema.optional(
Schema.Struct({
effort: Schema.optional(OpenResponsesOptions.ReasoningEffort),
summary: Schema.optional(Schema.Literals(["auto", "concise", "detailed"])),
}),
),
text: Schema.optional(
Schema.Struct({
verbosity: Schema.optional(OpenResponsesOptions.TextVerbositySchema),
}),
),
max_output_tokens: Schema.optional(Schema.Number),
temperature: Schema.optional(Schema.Number),
top_p: Schema.optional(Schema.Number),
}
const OpenResponsesBody = Schema.Struct({
...coreFields,
stream: Schema.Literal(true),
})
export type OpenResponsesBody = Schema.Schema.Type<typeof OpenResponsesBody>
const OpenResponsesUsage = Schema.Struct({
input_tokens: Schema.optional(Schema.Number),
input_tokens_details: optionalNull(
Schema.Struct({
cached_tokens: Schema.optional(Schema.Number),
cache_write_tokens: Schema.optional(Schema.Number),
}),
),
output_tokens: Schema.optional(Schema.Number),
output_tokens_details: optionalNull(Schema.Struct({ reasoning_tokens: Schema.optional(Schema.Number) })),
total_tokens: Schema.optional(Schema.Number),
})
type OpenResponsesUsage = Schema.Schema.Type<typeof OpenResponsesUsage>
export const StreamItem = Schema.StructWithRest(
Schema.Struct({
type: Schema.String,
id: Schema.optional(Schema.String),
call_id: Schema.optional(Schema.String),
name: Schema.optional(Schema.String),
arguments: Schema.optional(Schema.String),
encrypted_content: optionalNull(Schema.String),
}),
[Schema.Record(Schema.String, Schema.Unknown)],
)
export type StreamItem = Schema.Schema.Type<typeof StreamItem>
// The Responses schema puts streaming error details at the top level and
// response failures under `response.error`. WebSocket failures use an
// event-level `error` envelope, so accept all three shapes here.
// https://www.openresponses.org/specification
const OpenResponsesErrorPayload = Schema.Struct({
code: optionalNull(Schema.String),
message: optionalNull(Schema.String),
param: optionalNull(Schema.String),
})
export const Event = Schema.StructWithRest(
Schema.Struct({
type: Schema.String,
delta: Schema.optional(Schema.String),
text: Schema.optional(Schema.String),
item_id: Schema.optional(Schema.String),
summary_index: Schema.optional(Schema.Number),
item: Schema.optional(StreamItem),
response: Schema.optional(
Schema.StructWithRest(
Schema.Struct({
id: Schema.optional(Schema.String),
service_tier: optionalNull(Schema.String),
incomplete_details: optionalNull(Schema.Struct({ reason: Schema.optional(Schema.String) })),
usage: optionalNull(OpenResponsesUsage),
error: optionalNull(OpenResponsesErrorPayload),
}),
[Schema.Record(Schema.String, Schema.Unknown)],
),
),
code: optionalNull(Schema.String),
message: Schema.optional(Schema.String),
param: optionalNull(Schema.String),
error: optionalNull(OpenResponsesErrorPayload),
}),
[Schema.Record(Schema.String, Schema.Unknown)],
)
export type Event = Schema.Schema.Type<typeof Event>
export interface Extension {
readonly id: string
readonly name: string
readonly lowerMedia?: (input: {
readonly part: MediaPart
readonly media: ProviderShared.ValidatedMedia
readonly request: LLMRequest
}) => MediaInput | undefined
readonly messagePhase?: (value: unknown) => MessagePhase | null | undefined
}
const BASE: Extension = { id: ADAPTER, name: NAME }
export interface ParserState {
readonly id: string
readonly name: string
readonly providerMetadataKey: string
readonly tools: ToolStream.State<string>
readonly hasFunctionCall: boolean
readonly lifecycle: Lifecycle.State
readonly messageItems: ReadonlySet<string>
readonly messagePhase: (value: unknown) => MessagePhase | null | undefined
readonly messagePhases: Readonly<Record<string, MessagePhase | null>>
readonly reasoningItems: Readonly<Record<string, ReasoningStreamItem>>
readonly store: boolean | undefined
}
type ReasoningSummaryStatus = "active" | "can-conclude" | "concluded"
interface ReasoningStreamItem {
readonly encryptedContent: string | null | undefined
// Keyed by the wire protocol's numeric `summary_index`. JS object keys coerce to
// strings, but typing the map as `Record<number, ...>` documents intent
// and matches the wire field.
readonly summaryParts: Readonly<Record<number, ReasoningSummaryStatus>>
}
// =============================================================================
// Request Lowering
// =============================================================================
export const lowerTool = Effect.fn("OpenResponses.lowerTool")(function* (
protocolName: string,
tool: ToolDefinition,
inputSchema: JsonSchema,
) {
if (tool.native !== undefined)
return yield* ProviderShared.invalidRequest(`${protocolName} does not support provider-native tool ${tool.name}`)
return {
type: "function" as const,
name: tool.name,
description: tool.description,
parameters: ToolSchemaProjection.responses(inputSchema),
// TODO: Read this from Responses tool options so direct LLM callers can opt into strict schemas.
strict: false,
}
})
export const lowerToolChoice = (protocolName: string, toolChoice: NonNullable<LLMRequest["toolChoice"]>) =>
ProviderShared.matchToolChoice(protocolName, toolChoice, {
auto: () => "auto" as const,
none: () => "none" as const,
required: () => "required" as const,
tool: (toolName) => ({ type: "function" as const, name: toolName }),
})
const lowerToolCall = (part: ToolCallPart): OpenResponsesInputItem => ({
type: "function_call",
call_id: part.id,
name: part.name,
arguments: ProviderShared.encodeJson(part.input),
})
const lowerReasoning = (part: ReasoningPart, providerMetadataKey: string): OpenResponsesReasoningInput | undefined => {
const metadata = part.providerMetadata?.[providerMetadataKey]
if (!ProviderShared.isRecord(metadata) || typeof metadata.itemId !== "string" || metadata.itemId.length === 0)
return undefined
const encryptedContent =
typeof metadata.reasoningEncryptedContent === "string" || metadata.reasoningEncryptedContent === null
? metadata.reasoningEncryptedContent
: undefined
return {
type: "reasoning",
id: metadata.itemId,
summary: part.text.length > 0 ? [{ type: "summary_text", text: part.text }] : [],
encrypted_content: encryptedContent,
}
}
const hostedToolItemID = (part: ToolResultPart, providerMetadataKey: string) => {
const metadata = part.providerMetadata?.[providerMetadataKey]
return ProviderShared.isRecord(metadata) && typeof metadata.itemId === "string" && metadata.itemId.length > 0
? metadata.itemId
: undefined
}
const lowerMedia = Effect.fn("OpenResponses.lowerMedia")(function* (
part: MediaPart,
request: LLMRequest,
extension: Extension,
) {
const media = yield* ProviderShared.validateMedia(extension.name, part, MEDIA_MIMES)
const extended = extension.lowerMedia?.({ part, media, request })
if (extended) return extended
if (media.mime === "application/pdf") {
return {
type: "input_file" as const,
filename: part.filename ?? "document.pdf",
file_data: media.dataUrl,
}
}
return { type: "input_image" as const, image_url: media.dataUrl }
})
const lowerUserContent = Effect.fn("OpenResponses.lowerUserContent")(function* (
part: LLMRequest["messages"][number]["content"][number],
request: LLMRequest,
extension: Extension,
) {
if (part.type === "text") return { type: "input_text" as const, text: part.text }
if (part.type === "media") return yield* lowerMedia(part, request, extension)
return yield* ProviderShared.unsupportedContent(extension.name, "user", ["text", "media"])
})
// Tool results may carry structured text, images, and files. Keep media as provider-native
// content instead of JSON-stringifying base64 into a prompt string.
const lowerToolResultContentItem = Effect.fn("OpenResponses.lowerToolResultContentItem")(function* (
item: ToolContent,
request: LLMRequest,
extension: Extension,
) {
if (item.type === "text") return { type: "input_text" as const, text: item.text }
return yield* lowerMedia(
{ type: "media", mediaType: item.mime, data: item.uri, filename: item.name },
request,
extension,
)
})
const lowerToolResultOutput = Effect.fn("OpenResponses.lowerToolResultOutput")(function* (
part: ToolResultPart,
request: LLMRequest,
extension: Extension,
) {
// Text/json/error results are encoded as a plain string for backward
// compatibility with existing cassettes and provider expectations.
if (part.result.type !== "content") return ProviderShared.toolResultText(part)
// Preserve the narrowed array element type when compiled through a consumer package.
const content: ReadonlyArray<ToolContent> = part.result.value
return yield* Effect.forEach(content, (item) => lowerToolResultContentItem(item, request, extension))
})
const lowerMessages = Effect.fn("OpenResponses.lowerMessages")(function* (request: LLMRequest, extension: Extension) {
const system: LoweredInputItem[] =
request.system.length === 0 ? [] : [{ role: "system", content: ProviderShared.joinText(request.system) }]
const input: LoweredInputItem[] = [...system]
const store = OpenResponsesOptions.resolve(request).store
const providerMetadataKey = request.model.route.providerMetadataKey ?? "openresponses"
for (const message of request.messages) {
if (message.role === "system") {
const part = yield* ProviderShared.wrappedSystemUpdate(extension.name, message)
const previous = input.at(-1)
if (previous && "role" in previous && previous.role === "user")
input[input.length - 1] = {
role: "user",
content: [...previous.content, { type: "input_text", text: part.text }],
}
else input.push({ role: "user", content: [{ type: "input_text", text: part.text }] })
continue
}
if (message.role === "user") {
input.push({
role: "user",
content: yield* Effect.forEach(message.content, (part) => lowerUserContent(part, request, extension)),
})
continue
}
if (message.role === "assistant") {
const content: TextPart[] = []
const reasoningItems: Record<string, OpenResponsesReasoningReplay> = {}
const reasoningReferences = new Set<string>()
const hostedToolReferences = new Set<string>()
const flushText = () => {
if (content.length === 0) return
const groups = content.reduce<Array<{ phase: MessagePhase | null | undefined; parts: TextPart[] }>>(
(groups, part) => {
const metadata = part.providerMetadata?.[providerMetadataKey]
const phase =
ProviderShared.isRecord(metadata)
? messagePhase(metadata.phase, extension)
: undefined
const group = groups.at(-1)
if (group && group.phase === phase) group.parts.push(part)
else groups.push({ phase, parts: [part] })
return groups
},
[],
)
input.push(
...groups.map((group) => ({
role: "assistant" as const,
content: group.parts.map((part) => ({ type: "output_text" as const, text: part.text })),
...(group.phase === undefined ? {} : { phase: group.phase }),
})),
)
content.splice(0, content.length)
}
for (const part of message.content) {
if (part.type === "text") {
content.push(part)
continue
}
if (part.type === "reasoning") {
flushText()
const reasoning = lowerReasoning(part, providerMetadataKey)
if (!reasoning) continue
if (store !== false) {
if (!reasoningReferences.has(reasoning.id)) input.push({ type: "item_reference", id: reasoning.id })
reasoningReferences.add(reasoning.id)
continue
}
const existing = reasoningItems[reasoning.id]
if (existing) {
existing.summary.push(...reasoning.summary)
if (typeof reasoning.encrypted_content === "string")
existing.encrypted_content = reasoning.encrypted_content
continue
}
const replay = {
type: reasoning.type,
summary: reasoning.summary,
encrypted_content: reasoning.encrypted_content,
}
reasoningItems[reasoning.id] = replay
input.push(replay)
continue
}
if (part.type === "tool-call") {
flushText()
if (part.providerExecuted === true) continue
input.push(lowerToolCall(part))
continue
}
if (part.type === "tool-result" && part.providerExecuted === true) {
flushText()
const itemID = hostedToolItemID(part, providerMetadataKey)
if (store !== false && itemID && !hostedToolReferences.has(itemID))
input.push({ type: "item_reference", id: itemID })
if (store === false && part.result.type === "content") {
const content: ReadonlyArray<ToolContent> = part.result.value
input.push({
role: "user",
content: yield* Effect.forEach(content, (item) => lowerToolResultContentItem(item, request, extension)),
})
}
if (itemID) hostedToolReferences.add(itemID)
continue
}
return yield* ProviderShared.unsupportedContent(extension.name, "assistant", [
"text",
"reasoning",
"tool-call",
"tool-result",
])
}
flushText()
continue
}
for (const part of message.content) {
if (!ProviderShared.supportsContent(part, ["tool-result"]))
return yield* ProviderShared.unsupportedContent(extension.name, "tool", ["tool-result"])
input.push({
type: "function_call_output",
call_id: part.id,
output: yield* lowerToolResultOutput(part, request, extension),
})
}
}
// With store:false, Responses APIs only accept previous reasoning items when the
// complete item has encrypted state. Summary blocks for one item may carry
// that state only on the last block, so filter after they have been joined.
return store === false
? input.filter(
(item) => !("type" in item) || item.type !== "reasoning" || typeof item.encrypted_content === "string",
)
: input
})
const lowerOptions = (request: LLMRequest) => {
const options = OpenResponsesOptions.resolve(request)
return {
...(options.instructions ? { instructions: options.instructions } : {}),
...(options.store !== undefined ? { store: options.store } : {}),
...(options.promptCacheKey ? { prompt_cache_key: options.promptCacheKey } : {}),
...(options.include ? { include: options.include } : {}),
...(options.reasoningEffort || options.reasoningSummary
? { reasoning: { effort: options.reasoningEffort, summary: options.reasoningSummary } }
: {}),
...(options.textVerbosity ? { text: { verbosity: options.textVerbosity } } : {}),
...(options.serviceTier ? { service_tier: options.serviceTier } : {}),
}
}
export const fromRequestWithExtension = Effect.fn("OpenResponses.fromRequestWithExtension")(function* (
request: LLMRequest,
extension: Extension,
) {
const generation = request.generation
const toolSchemaCompatibility = request.model.compatibility?.toolSchema
return {
model: request.model.id,
input: yield* lowerMessages(request, extension),
tools:
request.tools.length === 0
? undefined
: yield* Effect.forEach(request.tools, (tool) =>
lowerTool(
extension.name,
tool,
ToolSchemaProjection.modelCompatibility(tool.inputSchema, toolSchemaCompatibility),
),
),
tool_choice: request.toolChoice ? yield* lowerToolChoice(extension.name, request.toolChoice) : undefined,
stream: true as const,
max_output_tokens: generation?.maxTokens,
temperature: generation?.temperature,
top_p: generation?.topP,
...lowerOptions(request),
}
})
const decodeBody = ProviderShared.validateWith(Schema.decodeUnknownEffect(OpenResponsesBody))
export const fromRequest = Effect.fn("OpenResponses.fromRequest")(function* (request: LLMRequest) {
return yield* decodeBody(yield* fromRequestWithExtension(request, BASE))
})
// =============================================================================
// Stream Parsing
// =============================================================================
// Responses APIs report `input_tokens` (inclusive total) with a
// cached-read and cache-write subsets, and `output_tokens` (inclusive total)
// with a `reasoning_tokens` subset. Pass the totals through and derive the
// non-cached breakdown.
const mapUsage = (usage: OpenResponsesUsage | null | undefined, providerMetadataKey: string) => {
if (!usage) return undefined
const cached = usage.input_tokens_details?.cached_tokens
const cacheWrite = usage.input_tokens_details?.cache_write_tokens
const reasoning = usage.output_tokens_details?.reasoning_tokens
const nonCached = ProviderShared.subtractTokens(usage.input_tokens, ProviderShared.sumTokens(cached, cacheWrite))
return new Usage({
inputTokens: usage.input_tokens,
outputTokens: usage.output_tokens,
nonCachedInputTokens: nonCached,
cacheReadInputTokens: cached,
cacheWriteInputTokens: cacheWrite,
reasoningTokens: reasoning,
totalTokens: ProviderShared.totalTokens(usage.input_tokens, usage.output_tokens, usage.total_tokens),
providerMetadata: { [providerMetadataKey]: usage },
})
}
const mapFinishReason = (event: Event, hasFunctionCall: boolean): FinishReason => {
const reason = event.response?.incomplete_details?.reason
if (reason === undefined || reason === null) {
if (hasFunctionCall) return "tool-calls"
if (event.type === "response.incomplete") return "unknown"
return "stop"
}
if (reason === "max_output_tokens") return "length"
if (reason === "content_filter") return "content-filter"
return hasFunctionCall ? "tool-calls" : "unknown"
}
export const providerMetadata = (state: ParserState, metadata: Record<string, unknown>): ProviderMetadata => ({
[state.providerMetadataKey]: metadata,
})
const isReasoningItem = (item: StreamItem): item is StreamItem & { type: "reasoning"; id: string } =>
item.type === "reasoning" && typeof item.id === "string" && item.id.length > 0
export type StepResult = readonly [ParserState, ReadonlyArray<LLMEvent>]
const NO_EVENTS: StepResult["1"] = []
// `response.completed` / `response.incomplete` are clean finishes that emit a
// `finish` event; `response.failed` is a hard failure. All three end the stream,
// so keep this set aligned with `step` and the protocol's terminal predicate.
const TERMINAL_TYPES = new Set(["response.completed", "response.incomplete", "response.failed"])
export const terminal = (event: Event) => TERMINAL_TYPES.has(event.type)
const onOutputTextDelta = (state: ParserState, event: Event, id: string): StepResult => {
if (!event.delta) return [state, NO_EVENTS]
const events: LLMEvent[] = []
const phase = state.messagePhases[id]
const metadata = phase === undefined ? undefined : providerMetadata(state, { phase })
const lifecycle = Lifecycle.textStart(state.lifecycle, events, id, metadata)
return [
{ ...state, lifecycle: Lifecycle.textDelta(lifecycle, events, id, event.delta) },
events,
]
}
const onOutputTextDone = (state: ParserState, event: Event, id: string): StepResult => {
if (state.messageItems.has(id)) {
if (state.lifecycle.text.has(id) || event.text === undefined) return [state, NO_EVENTS]
return onOutputTextDelta(state, { ...event, delta: event.text }, id)
}
const events: LLMEvent[] = []
return [{ ...state, lifecycle: Lifecycle.textEnd(state.lifecycle, events, id) }, events]
}
export const onReasoningDelta = (state: ParserState, event: Event, itemID: string): StepResult => {
if (!event.delta) return [state, NO_EVENTS]
const events: LLMEvent[] = []
const id =
event.summary_index !== undefined || state.reasoningItems[itemID] ? `${itemID}:${event.summary_index ?? 0}` : itemID
return [
{
...state,
lifecycle: Lifecycle.reasoningDelta(state.lifecycle, events, id, event.delta),
},
events,
]
}
export const onReasoningDone = (state: ParserState, _event: Event): StepResult => [state, NO_EVENTS]
const reasoningMetadata = (state: ParserState, item: StreamItem & { id: string }) =>
providerMetadata(state, { itemId: item.id, reasoningEncryptedContent: item.encrypted_content ?? null })
// Responses APIs stream reasoning items in a stable order:
// `output_item.added` (reasoning) →
// `reasoning_summary_part.added` (index=0) →
// `reasoning_summary_text.delta` →
// `reasoning_summary_part.done` (index=0) →
// (repeat for index>0) →
// `output_item.done` (reasoning).
// The handlers below rely on this ordering: `onOutputItemAdded` seeds the
// per-item entry, `onReasoningSummaryPartAdded` for `summary_index === 0`
// short-circuits when the entry already exists, and higher-index handlers
// fold against the same entry. Behaviour for out-of-order events is
// best-effort, not guaranteed.
const onOutputItemAdded = (state: ParserState, event: Event): StepResult => {
const item = event.item
if (item?.type === "message" && item.id)
return [
{
...state,
messageItems: new Set([...state.messageItems, item.id]),
messagePhases: (() => {
const phase = state.messagePhase(item.phase)
return phase === undefined ? state.messagePhases : { ...state.messagePhases, [item.id]: phase }
})(),
},
NO_EVENTS,
]
if (item && isReasoningItem(item)) {
const events: LLMEvent[] = []
return [
{
...state,
lifecycle: Lifecycle.reasoningStart(state.lifecycle, events, `${item.id}:0`, reasoningMetadata(state, item)),
reasoningItems: {
...state.reasoningItems,
[item.id]: { encryptedContent: item.encrypted_content, summaryParts: { 0: "active" } },
},
},
events,
]
}
if (item?.type !== "function_call" || !item.id) return [state, NO_EVENTS]
const metadata = providerMetadata(state, { itemId: item.id })
const events: LLMEvent[] = []
const lifecycle = Lifecycle.stepStart(state.lifecycle, events)
return [
{
...state,
lifecycle,
tools: ToolStream.start(state.tools, item.id, {
id: item.call_id ?? item.id,
name: item.name ?? "",
input: item.arguments ?? "",
providerMetadata: metadata,
}),
},
[
...events,
LLMEvent.toolInputStart({ id: item.call_id ?? item.id, name: item.name ?? "", providerMetadata: metadata }),
],
]
}
const onReasoningSummaryPartAdded = (state: ParserState, event: Event): StepResult => {
if (!event.item_id || event.summary_index === undefined) return [state, NO_EVENTS]
const item = state.reasoningItems[event.item_id] ?? { encryptedContent: undefined, summaryParts: {} }
if (event.summary_index === 0) {
if (state.reasoningItems[event.item_id]) return [state, NO_EVENTS]
const events: LLMEvent[] = []
return [
{
...state,
lifecycle: Lifecycle.reasoningStart(
state.lifecycle,
events,
`${event.item_id}:0`,
providerMetadata(state, { itemId: event.item_id, reasoningEncryptedContent: null }),
),
reasoningItems: {
...state.reasoningItems,
[event.item_id]: { ...item, summaryParts: { 0: "active" } },
},
},
events,
]
}
const events: LLMEvent[] = []
const closed = Object.entries(item.summaryParts)
.filter((entry) => entry[1] === "can-conclude")
.reduce(
(lifecycle, entry) =>
Lifecycle.reasoningEnd(
lifecycle,
events,
`${event.item_id}:${entry[0]}`,
providerMetadata(state, { itemId: event.item_id }),
),
state.lifecycle,
)
return [
{
...state,
lifecycle: Lifecycle.reasoningStart(
closed,
events,
`${event.item_id}:${event.summary_index}`,
providerMetadata(state, { itemId: event.item_id, reasoningEncryptedContent: item.encryptedContent ?? null }),
),
reasoningItems: {
...state.reasoningItems,
[event.item_id]: {
...item,
summaryParts: {
...Object.fromEntries(
Object.entries(item.summaryParts).map((entry) =>
entry[1] === "can-conclude" ? [entry[0], "concluded" as const] : entry,
),
),
[event.summary_index]: "active",
},
},
},
},
events,
]
}
const onReasoningSummaryPartDone = (state: ParserState, event: Event): StepResult => {
if (!event.item_id || event.summary_index === undefined) return [state, NO_EVENTS]
const item = state.reasoningItems[event.item_id]
if (!item) return [state, NO_EVENTS]
const events: LLMEvent[] = []
return [
{
...state,
lifecycle:
state.store !== false
? Lifecycle.reasoningEnd(
state.lifecycle,
events,
`${event.item_id}:${event.summary_index}`,
providerMetadata(state, { itemId: event.item_id }),
)
: state.lifecycle,
reasoningItems: {
...state.reasoningItems,
[event.item_id]: {
...item,
summaryParts: {
...item.summaryParts,
[event.summary_index]: state.store !== false ? "concluded" : "can-conclude",
},
},
},
},
events,
]
}
const onFunctionCallArgumentsDelta = Effect.fn("OpenResponses.onFunctionCallArgumentsDelta")(function* (
state: ParserState,
event: Event,
) {
if (!event.item_id || !event.delta) return [state, NO_EVENTS] satisfies StepResult
const result = ToolStream.appendExisting(
state.id,
state.tools,
event.item_id,
event.delta,
`${state.name} tool argument delta is missing its tool call`,
)
if (ToolStream.isError(result)) return yield* result
const events: LLMEvent[] = []
const lifecycle = result.events.length ? Lifecycle.stepStart(state.lifecycle, events) : state.lifecycle
events.push(...result.events)
return [{ ...state, lifecycle, tools: result.tools }, events] satisfies StepResult
})
const onOutputItemDone = Effect.fn("OpenResponses.onOutputItemDone")(function* (state: ParserState, event: Event) {
const item = event.item
if (!item) return [state, NO_EVENTS] satisfies StepResult
if (item.type === "message" && item.id) {
const itemPhase = state.messagePhase(item.phase)
const phase = itemPhase === undefined ? state.messagePhases[item.id] : itemPhase
const events: LLMEvent[] = []
const messageItems = new Set(state.messageItems)
messageItems.delete(item.id)
const { [item.id]: _phase, ...messagePhases } = state.messagePhases
return [
{
...state,
lifecycle: Lifecycle.textEnd(
state.lifecycle,
events,
item.id,
phase === undefined ? undefined : providerMetadata(state, { phase }),
),
messageItems,
messagePhases,
},
events,
] satisfies StepResult
}
if (item.type === "function_call") {
if (!item.id || !item.call_id || !item.name) return [state, NO_EVENTS] satisfies StepResult
const tools = state.tools[item.id]
? state.tools
: ToolStream.start(state.tools, item.id, { id: item.call_id, name: item.name })
const result =
item.arguments === undefined
? yield* ToolStream.finish(state.id, tools, item.id)
: yield* ToolStream.finishWithInput(state.id, tools, item.id, item.arguments)
const events: LLMEvent[] = []
const resultEvents = result.events ?? []
const lifecycle = resultEvents.length ? Lifecycle.stepStart(state.lifecycle, events) : state.lifecycle
events.push(...resultEvents)
return [
{
...state,
lifecycle,
hasFunctionCall:
resultEvents.some((event) => LLMEvent.is.toolCall(event) || LLMEvent.is.toolInputError(event)) ||
state.hasFunctionCall,
tools: result.tools,
},
events,
] satisfies StepResult
}
if (isReasoningItem(item)) {
const events: LLMEvent[] = []
const metadata = reasoningMetadata(state, item)
const reasoningItem = state.reasoningItems[item.id]
if (reasoningItem) {
const lifecycle = Object.entries(reasoningItem.summaryParts)
.filter((entry) => entry[1] === "active" || entry[1] === "can-conclude")
.reduce(
(lifecycle, entry) => Lifecycle.reasoningEnd(lifecycle, events, `${item.id}:${entry[0]}`, metadata),
state.lifecycle,
)
const { [item.id]: _removed, ...reasoningItems } = state.reasoningItems
return [{ ...state, lifecycle, reasoningItems }, events] satisfies StepResult
}
if (!state.lifecycle.reasoning.has(item.id)) {
const lifecycle = Lifecycle.stepStart(state.lifecycle, events)
events.push(LLMEvent.reasoningStart({ id: item.id, providerMetadata: metadata }))
events.push(LLMEvent.reasoningEnd({ id: item.id, providerMetadata: metadata }))
return [{ ...state, lifecycle }, events] satisfies StepResult
}
return [
{ ...state, lifecycle: Lifecycle.reasoningEnd(state.lifecycle, events, item.id, metadata) },
events,
] satisfies StepResult
}
return [state, NO_EVENTS] satisfies StepResult
})
const onResponseFinish = (state: ParserState, event: Event): StepResult => {
const events: LLMEvent[] = []
const lifecycle = Lifecycle.finish(state.lifecycle, events, {
reason: {
normalized: mapFinishReason(event, state.hasFunctionCall),
raw: event.response?.incomplete_details?.reason,
},
usage: mapUsage(event.response?.usage, state.providerMetadataKey),
providerMetadata:
event.response?.id || event.response?.service_tier
? providerMetadata(state, {
responseId: event.response.id,
serviceTier: event.response.service_tier,
})
: undefined,
})
return [{ ...state, lifecycle }, events]
}
// Build a single human-readable message from whatever the provider supplied.
// When both code and message are present, prefix the code so consumers see
// the failure mode (e.g. `rate_limit_exceeded: Slow down`) instead of just
// the bare message — production rate limits and context-length failures used
// to be indistinguishable from generic stream drops.
const providerErrorMessage = (event: Event, fallback: string): string => {
const nested = event.error ?? event.response?.error ?? undefined
const message = event.message || nested?.message || undefined
const code = event.code || nested?.code || undefined
if (message && code) return `${code}: ${message}`
return message || code || fallback
}
const providerError = (state: ParserState, event: Event, fallback: string) => {
const code = event.code || event.error?.code || event.response?.error?.code || undefined
const message = providerErrorMessage(event, fallback)
return new LLMError({
module: state.id,
method: "stream",
reason: classifyProviderFailure({ message, code }),
})
}
export const step = (state: ParserState, event: Event) => {
if (event.type === "response.output_text.delta" || event.type === "response.output_text.done") {
if (!event.item_id) return ProviderShared.eventError(state.id, `${event.type} is missing item_id`)
return Effect.succeed(
event.type === "response.output_text.delta"
? onOutputTextDelta(state, event, event.item_id)
: onOutputTextDone(state, event, event.item_id),
)
}
if (event.type === "response.reasoning.delta" || event.type === "response.reasoning_summary_text.delta") {
if (!event.item_id) return ProviderShared.eventError(state.id, `${event.type} is missing item_id`)
return Effect.succeed(onReasoningDelta(state, event, event.item_id))
}
if (event.type === "response.reasoning.done" || event.type === "response.reasoning_summary_text.done") {
if (!event.item_id) return ProviderShared.eventError(state.id, `${event.type} is missing item_id`)
return Effect.succeed(onReasoningDone(state, event))
}
if (event.type === "response.reasoning_summary_part.added")
return event.item_id
? Effect.succeed(onReasoningSummaryPartAdded(state, event))
: ProviderShared.eventError(state.id, `${event.type} is missing item_id`)
if (event.type === "response.reasoning_summary_part.done")
return event.item_id
? Effect.succeed(onReasoningSummaryPartDone(state, event))
: ProviderShared.eventError(state.id, `${event.type} is missing item_id`)
if (event.type === "response.output_item.added") {
if (event.item?.type === "message" && !event.item.id)
return ProviderShared.eventError(state.id, `${event.type} message is missing id`)
return Effect.succeed(onOutputItemAdded(state, event))
}
if (event.type === "response.function_call_arguments.delta") return onFunctionCallArgumentsDelta(state, event)
if (event.type === "response.output_item.done") {
if (event.item?.type === "message" && !event.item.id)
return ProviderShared.eventError(state.id, `${event.type} message is missing id`)
return onOutputItemDone(state, event)
}
if (event.type === "response.completed" || event.type === "response.incomplete")
return Effect.succeed(onResponseFinish(state, event))
if (event.type === "response.failed") return providerError(state, event, `${state.name} response failed`)
if (event.type === "error") return providerError(state, event, `${state.name} stream error`)
return Effect.succeed<StepResult>([state, NO_EVENTS])
}
// =============================================================================
// Protocol
// =============================================================================
/**
* The provider-neutral Open Responses protocol. Provider-specific Responses
* implementations compose this baseline with their own tools and event variants.
*/
export const initial = (request: LLMRequest, extension: Extension = BASE): ParserState => ({
id: extension.id,
name: extension.name,
providerMetadataKey: request.model.route.providerMetadataKey ?? "openresponses",
hasFunctionCall: false,
tools: ToolStream.empty<string>(),
lifecycle: Lifecycle.initial(),
messageItems: new Set<string>(),
messagePhase: (value) => messagePhase(value, extension),
messagePhases: {},
reasoningItems: {},
store: OpenResponsesOptions.resolve(request).store,
})
const messagePhase = (value: unknown, extension: Extension): MessagePhase | null | undefined => {
if (value === "commentary" || value === "final_answer") return value
return extension.messagePhase?.(value)
}
export const protocol = Protocol.make({
id: ADAPTER,
body: {
schema: OpenResponsesBody,
from: fromRequest,
},
stream: {
event: Protocol.jsonEvent(Event),
initial,
step,
terminal,
},
})
export const httpTransport = HttpTransport.sseJson.with<OpenResponsesBody>()
export * as OpenResponses from "./open-responses"
+47 -16
View File
@@ -5,9 +5,11 @@ import { Endpoint } from "../route/endpoint"
import { HttpTransport } from "../route/transport"
import { Protocol } from "../route/protocol"
import {
LLMError,
LLMEvent,
Usage,
type FinishReason,
type FinishReasonDetails,
type JsonSchema,
type LLMRequest,
type MediaPart,
@@ -17,6 +19,7 @@ import {
type ToolDefinition,
type ToolContent,
} from "../schema"
import { classifyProviderFailure } from "../provider-error"
import { isRecord, JsonObject, optionalArray, optionalNull, ProviderShared } from "./shared"
import { OpenAIOptions } from "./utils/openai-options"
import { Lifecycle } from "./utils/lifecycle"
@@ -128,6 +131,7 @@ const OpenAIChatUsage = Schema.Struct({
prompt_tokens_details: optionalNull(
Schema.Struct({
cached_tokens: Schema.optional(Schema.Number),
cache_write_tokens: Schema.optional(Schema.Number),
}),
),
completion_tokens_details: optionalNull(
@@ -164,11 +168,18 @@ const OpenAIChatDelta = Schema.StructWithRest(
const OpenAIChatChoice = Schema.Struct({
delta: optionalNull(OpenAIChatDelta),
finish_reason: optionalNull(Schema.String),
native_finish_reason: optionalNull(Schema.String),
})
const OpenAIChatError = Schema.Struct({
code: optionalNull(Schema.Union([Schema.String, Schema.Number])),
message: Schema.String,
})
export const OpenAIChatEvent = Schema.Struct({
choices: Schema.Array(OpenAIChatChoice),
choices: optionalNull(Schema.Array(OpenAIChatChoice)),
usage: optionalNull(OpenAIChatUsage),
error: optionalNull(OpenAIChatError),
})
export type OpenAIChatEvent = Schema.Schema.Type<typeof OpenAIChatEvent>
type OpenAIChatRequestMessage = LLMRequest["messages"][number]
@@ -184,7 +195,7 @@ export interface ParserState {
readonly pendingTools: Partial<Record<number, PendingToolDelta>>
readonly toolCallEvents: ReadonlyArray<LLMEvent>
readonly usage?: Usage
readonly finishReason?: FinishReason
readonly finishReason?: FinishReasonDetails
readonly lifecycle: Lifecycle.State
readonly reasoningField?: string
readonly reasoningDetails: Array<unknown>
@@ -386,14 +397,13 @@ const lowerMessages = Effect.fn("OpenAIChat.lowerMessages")(function* (request:
return messages
})
const lowerOptions = Effect.fn("OpenAIChat.lowerOptions")(function* (request: LLMRequest) {
const store = OpenAIOptions.store(request)
const reasoningEffort = OpenAIOptions.reasoningEffort(request)
const lowerOptions = (request: LLMRequest) => {
const options = OpenAIOptions.resolve(request)
return {
...(store !== undefined ? { store } : {}),
...(reasoningEffort ? { reasoning_effort: reasoningEffort } : {}),
...(options.store !== undefined ? { store: options.store } : {}),
...(options.reasoningEffort ? { reasoning_effort: options.reasoningEffort } : {}),
}
})
}
const fromRequest = Effect.fn("OpenAIChat.fromRequest")(function* (request: LLMRequest) {
// `fromRequest` returns the provider body only. Endpoint, auth, framing,
@@ -424,7 +434,7 @@ const fromRequest = Effect.fn("OpenAIChat.fromRequest")(function* (request: LLMR
presence_penalty: generation?.presencePenalty,
seed: generation?.seed,
stop: generation?.stop,
...(yield* lowerOptions(request)),
...lowerOptions(request),
}
})
@@ -439,24 +449,27 @@ const mapFinishReason = (reason: string | null | undefined): FinishReason => {
if (reason === "length") return "length"
if (reason === "content_filter") return "content-filter"
if (reason === "function_call" || reason === "tool_calls") return "tool-calls"
if (reason === "error") return "error"
return "unknown"
}
// OpenAI Chat reports `prompt_tokens` (inclusive total) with a
// `cached_tokens` subset, and `completion_tokens` (inclusive total) with
// a `reasoning_tokens` subset. We pass the inclusive totals through and
// derive the non-cached breakdown so the `LLM.Usage` contract is
// cached-read and cache-write subsets, and `completion_tokens` (inclusive
// total) with a `reasoning_tokens` subset. We pass the inclusive totals
// through and derive the non-cached breakdown so the `LLM.Usage` contract is
// satisfied on both sides.
const mapUsage = (usage: OpenAIChatEvent["usage"]): Usage | undefined => {
if (!usage) return undefined
const cached = usage.prompt_tokens_details?.cached_tokens
const cacheWrite = usage.prompt_tokens_details?.cache_write_tokens
const reasoning = usage.completion_tokens_details?.reasoning_tokens
const nonCached = ProviderShared.subtractTokens(usage.prompt_tokens, cached)
const nonCached = ProviderShared.subtractTokens(usage.prompt_tokens, ProviderShared.sumTokens(cached, cacheWrite))
return new Usage({
inputTokens: usage.prompt_tokens,
outputTokens: usage.completion_tokens,
nonCachedInputTokens: nonCached,
cacheReadInputTokens: cached,
cacheWriteInputTokens: cacheWrite,
reasoningTokens: reasoning,
totalTokens: ProviderShared.totalTokens(usage.prompt_tokens, usage.completion_tokens, usage.total_tokens),
providerMetadata: { openai: usage },
@@ -532,10 +545,22 @@ const reasoningMetadata = (field: ParserState["reasoningField"], details?: Reado
const step = (state: ParserState, event: OpenAIChatEvent) =>
Effect.gen(function* () {
if (event.error)
return yield* new LLMError({
module: ADAPTER,
method: "stream",
reason: classifyProviderFailure({
message: event.error.message,
code: event.error.code === undefined || event.error.code === null ? undefined : String(event.error.code),
status: typeof event.error.code === "number" ? event.error.code : undefined,
}),
})
const events: LLMEvent[] = []
const usage = mapUsage(event.usage) ?? state.usage
const choice = event.choices[0]
const finishReason = choice?.finish_reason ? mapFinishReason(choice.finish_reason) : state.finishReason
const choice = event.choices?.[0]
const finishReason = choice?.finish_reason
? { normalized: mapFinishReason(choice.finish_reason), raw: choice.native_finish_reason ?? choice.finish_reason }
: state.finishReason
const delta = choice?.delta
const toolDeltas = delta?.tool_calls ?? []
let tools = state.tools
@@ -627,7 +652,13 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
const finishEvents = (state: ParserState): ReadonlyArray<LLMEvent> => {
const events: LLMEvent[] = []
const hasToolCalls = state.toolCallEvents.length > 0
const reason = state.finishReason === "stop" && hasToolCalls ? "tool-calls" : state.finishReason
const reason = state.finishReason
? {
...state.finishReason,
normalized:
state.finishReason.normalized === "stop" && hasToolCalls ? "tool-calls" : state.finishReason.normalized,
}
: undefined
const metadata = reasoningMetadata(
state.reasoningField,
state.reasoningDetailsObserved ? state.reasoningDetails : undefined,
@@ -1,23 +1,22 @@
import { Route, type RouteRoutedModelInput } from "../route/client"
import { Endpoint } from "../route/endpoint"
import { OpenAIResponses } from "./openai-responses"
import { OpenResponses } from "./open-responses"
const ADAPTER = "openai-compatible-responses"
export type OpenAICompatibleResponsesModelInput = RouteRoutedModelInput
/**
* Route for providers that expose an OpenAI Responses-compatible `/responses`
* endpoint. Provider helpers configure identity, endpoint, and auth before
* model selection while this route reuses the OpenAI Responses protocol.
* Deployment adapter for providers that expose an Open Responses-compatible
* `/responses` endpoint. Provider helpers configure identity, endpoint, and
* auth while the semantic protocol remains provider-neutral.
*/
export const route = Route.make({
id: ADAPTER,
providerMetadataKey: "openai",
protocol: OpenAIResponses.protocol,
endpoint: Endpoint.path(OpenAIResponses.PATH),
transport: OpenAIResponses.httpTransport,
defaults: { providerOptions: { openai: { store: false } } },
providerMetadataKey: "openresponses",
protocol: OpenResponses.protocol,
endpoint: Endpoint.path(OpenResponses.PATH),
transport: OpenResponses.httpTransport,
})
export * as OpenAICompatibleResponses from "./openai-compatible-responses"
+89 -916
View File
@@ -2,134 +2,20 @@ import { Effect, Encoding, Schema } from "effect"
import { Route } from "../route/client"
import { Auth } from "../route/auth"
import { Endpoint } from "../route/endpoint"
import { HttpTransport, WebSocketTransport } from "../route/transport"
import { Protocol } from "../route/protocol"
import {
LLMError,
LLMEvent,
Usage,
type FinishReason,
type JsonSchema,
type LLMRequest,
type MediaPart,
type ProviderMetadata,
type ReasoningPart,
type TextPart,
type ToolCallPart,
type ToolDefinition,
type ToolContent,
type ToolResultPart,
} from "../schema"
import { JsonObject, optionalArray, optionalNull, ProviderShared } from "./shared"
import { classifyProviderFailure } from "../provider-error"
import { OpenAIOptions } from "./utils/openai-options"
import { HttpTransport, WebSocketTransport } from "../route/transport"
import { LLMEvent, LLMRequest, type JsonSchema, type ToolDefinition } from "../schema"
import { OpenResponses } from "./open-responses"
import { optionalArray, ProviderShared } from "./shared"
import { Lifecycle } from "./utils/lifecycle"
import { ToolSchemaProjection } from "./utils/tool-schema"
import { ToolStream } from "./utils/tool-stream"
import { OpenAIImage } from "./utils/openai-image"
import { ToolSchemaProjection } from "./utils/tool-schema"
const ADAPTER = "openai-responses"
const MEDIA_MIMES = new Set<string>([...ProviderShared.IMAGE_MIMES, ...ProviderShared.PDF_MIMES])
const NAME = "OpenAI Responses"
export const DEFAULT_BASE_URL = "https://api.openai.com/v1"
export const PATH = "/responses"
export const PATH = OpenResponses.PATH
// =============================================================================
// Request Body Schema
// =============================================================================
const OpenAIResponsesInputText = Schema.Struct({
type: Schema.tag("input_text"),
text: Schema.String,
})
const OpenAIResponsesInputImage = Schema.Struct({
type: Schema.tag("input_image"),
image_url: Schema.String,
})
const OpenAIResponsesInputFile = Schema.Struct({
type: Schema.tag("input_file"),
filename: Schema.String,
file_data: Schema.String,
mime_type: Schema.optional(Schema.String),
})
const OpenAIResponsesInputContent = Schema.Union([
OpenAIResponsesInputText,
OpenAIResponsesInputImage,
OpenAIResponsesInputFile,
])
type OpenAIResponsesInputContent = Schema.Schema.Type<typeof OpenAIResponsesInputContent>
const OpenAIResponsesOutputText = Schema.Struct({
type: Schema.tag("output_text"),
text: Schema.String,
})
const OpenAIResponsesReasoningSummaryText = Schema.Struct({
type: Schema.tag("summary_text"),
text: Schema.String,
})
const OpenAIResponsesReasoningItem = Schema.Struct({
type: Schema.tag("reasoning"),
id: Schema.optionalKey(Schema.String),
summary: Schema.Array(OpenAIResponsesReasoningSummaryText),
encrypted_content: optionalNull(Schema.String),
})
const OpenAIResponsesItemReference = Schema.Struct({
type: Schema.tag("item_reference"),
id: Schema.String,
})
// `function_call_output.output` accepts either a plain string or an ordered
// array of content items so tools can return images and files in addition to text.
// https://platform.openai.com/docs/api-reference/responses/object
const OpenAIResponsesFunctionCallOutputContent = Schema.Union([
OpenAIResponsesInputText,
OpenAIResponsesInputImage,
OpenAIResponsesInputFile,
])
const OpenAIResponsesFunctionCallOutput = Schema.Union([
Schema.String,
Schema.Array(OpenAIResponsesFunctionCallOutputContent),
])
const OpenAIResponsesInputItem = Schema.Union([
Schema.Struct({ role: Schema.tag("system"), content: Schema.String }),
Schema.Struct({ role: Schema.tag("user"), content: Schema.Array(OpenAIResponsesInputContent) }),
Schema.Struct({ role: Schema.tag("assistant"), content: Schema.Array(OpenAIResponsesOutputText) }),
OpenAIResponsesReasoningItem,
OpenAIResponsesItemReference,
Schema.Struct({
type: Schema.tag("function_call"),
call_id: Schema.String,
name: Schema.String,
arguments: Schema.String,
}),
Schema.Struct({
type: Schema.tag("function_call_output"),
call_id: Schema.String,
output: OpenAIResponsesFunctionCallOutput,
}),
])
type OpenAIResponsesInputItem = Schema.Schema.Type<typeof OpenAIResponsesInputItem>
// Mutable counterpart of the schema reasoning item so `lowerMessages` can fold
// multiple streamed summary parts into the same item before flushing.
type OpenAIResponsesReasoningInput = {
type: "reasoning"
id: string
summary: Array<{ type: "summary_text"; text: string }>
encrypted_content?: string | null
}
type OpenAIResponsesReasoningReplay = Omit<OpenAIResponsesReasoningInput, "id">
const OpenAIResponsesTool = Schema.Struct({
type: Schema.tag("function"),
name: Schema.String,
description: Schema.String,
parameters: JsonObject,
strict: Schema.optional(Schema.Boolean),
})
const OpenAIResponsesImageGenerationTool = Schema.Struct({
type: Schema.tag("image_generation"),
action: Schema.optional(Schema.Literals(["auto", "generate", "edit"])),
@@ -141,43 +27,28 @@ const OpenAIResponsesImageGenerationTool = Schema.Struct({
quality: Schema.optional(Schema.Literals(["auto", "low", "medium", "high"])),
size: Schema.optional(OpenAIImage.Size),
})
const OpenAIResponsesTools = Schema.Union([OpenAIResponsesTool, OpenAIResponsesImageGenerationTool])
type OpenAIResponsesTool = Schema.Schema.Type<typeof OpenAIResponsesTools>
const OpenAIResponsesTools = Schema.Union([OpenResponses.Tool, OpenAIResponsesImageGenerationTool])
const OpenAIResponsesToolChoice = Schema.Union([
Schema.Literals(["auto", "none", "required"]),
Schema.Struct({ type: Schema.tag("function"), name: Schema.String }),
OpenResponses.ToolChoice,
Schema.Struct({ type: Schema.tag("image_generation") }),
])
// Fields shared between the HTTP body and the WebSocket `response.create`
// message. The HTTP body adds `stream: true`; the WebSocket message adds
// `type: "response.create"`. Defining the shared shape once keeps the two
// transports in sync without a destructure-and-strip dance.
const OpenAIResponsesInputItem = Schema.Union([
Schema.Struct({
role: Schema.tag("assistant"),
content: Schema.Array(Schema.Struct({ type: Schema.tag("output_text"), text: Schema.String })),
phase: Schema.optionalKey(Schema.NullOr(OpenResponses.MessagePhase)),
}),
OpenResponses.InputItem,
])
const OpenAIResponsesCoreFields = {
model: Schema.String,
...OpenResponses.coreFields,
input: Schema.Array(OpenAIResponsesInputItem),
instructions: Schema.optional(Schema.String),
tools: optionalArray(OpenAIResponsesTools),
tool_choice: Schema.optional(OpenAIResponsesToolChoice),
store: Schema.optional(Schema.Boolean),
service_tier: Schema.optional(OpenAIOptions.OpenAIServiceTier),
prompt_cache_key: Schema.optional(Schema.String),
include: optionalArray(OpenAIOptions.OpenAIResponseIncludable),
reasoning: Schema.optional(
Schema.Struct({
effort: Schema.optional(OpenAIOptions.OpenAIReasoningEffort),
summary: Schema.optional(Schema.Literal("auto")),
}),
),
text: Schema.optional(
Schema.Struct({
verbosity: Schema.optional(OpenAIOptions.OpenAITextVerbosity),
}),
),
max_output_tokens: Schema.optional(Schema.Number),
temperature: Schema.optional(Schema.Number),
top_p: Schema.optional(Schema.Number),
}
const OpenAIResponsesBody = Schema.Struct({
@@ -196,100 +67,21 @@ const OpenAIResponsesWebSocketMessage = Schema.StructWithRest(
type OpenAIResponsesWebSocketMessage = Schema.Schema.Type<typeof OpenAIResponsesWebSocketMessage>
const encodeWebSocketMessage = Schema.encodeSync(Schema.fromJsonString(OpenAIResponsesWebSocketMessage))
const OpenAIResponsesUsage = Schema.Struct({
input_tokens: Schema.optional(Schema.Number),
input_tokens_details: optionalNull(Schema.Struct({ cached_tokens: Schema.optional(Schema.Number) })),
output_tokens: Schema.optional(Schema.Number),
output_tokens_details: optionalNull(Schema.Struct({ reasoning_tokens: Schema.optional(Schema.Number) })),
total_tokens: Schema.optional(Schema.Number),
})
type OpenAIResponsesUsage = Schema.Schema.Type<typeof OpenAIResponsesUsage>
const extension = {
id: ADAPTER,
name: NAME,
messagePhase: (value: unknown) => (value === null ? null : undefined),
lowerMedia: ({ part, media, request }) => {
if (request.model.provider !== "xai" || media.mime !== "application/pdf") return undefined
return {
type: "input_file",
filename: part.filename ?? "document.pdf",
file_data: media.base64,
mime_type: media.mime,
}
},
} satisfies OpenResponses.Extension
const OpenAIResponsesStreamItem = Schema.Struct({
type: Schema.String,
id: Schema.optional(Schema.String),
call_id: Schema.optional(Schema.String),
name: Schema.optional(Schema.String),
arguments: Schema.optional(Schema.String),
// Hosted (provider-executed) tool fields. Each hosted tool item carries its
// own subset of these — we capture them generically so we can surface the
// call's typed input portion and round-trip the full result payload without
// hand-rolling a per-tool schema.
status: Schema.optional(Schema.String),
action: Schema.optional(Schema.Unknown),
queries: Schema.optional(Schema.Unknown),
results: Schema.optional(Schema.Unknown),
code: Schema.optional(Schema.String),
container_id: Schema.optional(Schema.String),
outputs: Schema.optional(Schema.Unknown),
server_label: Schema.optional(Schema.String),
output: Schema.optional(Schema.Unknown),
result: Schema.optional(Schema.String),
output_format: Schema.optional(Schema.Literals(["png", "jpeg", "webp"])),
error: Schema.optional(Schema.Unknown),
encrypted_content: optionalNull(Schema.String),
})
type OpenAIResponsesStreamItem = Schema.Schema.Type<typeof OpenAIResponsesStreamItem>
// The Responses schema puts streaming error details at the top level and
// response failures under `response.error`. The official SDK also recognizes
// an event-level HTTP-style `error` envelope, so accept all three shapes here.
// https://github.com/openai/openai-openapi/blob/5162af98d3147432c14680df789e8e12d4891e6b/openapi.yaml#L67234-L67382
// https://github.com/openai/openai-node/blob/61539248cbe04665de68a71e6fd878127ae4db87/src/core/streaming.ts#L58-L85
const OpenAIResponsesErrorPayload = Schema.Struct({
code: optionalNull(Schema.String),
message: optionalNull(Schema.String),
param: optionalNull(Schema.String),
})
const OpenAIResponsesEvent = Schema.Struct({
type: Schema.String,
delta: Schema.optional(Schema.String),
item_id: Schema.optional(Schema.String),
summary_index: Schema.optional(Schema.Number),
item: Schema.optional(OpenAIResponsesStreamItem),
response: Schema.optional(
Schema.StructWithRest(
Schema.Struct({
id: Schema.optional(Schema.String),
service_tier: optionalNull(Schema.String),
incomplete_details: optionalNull(Schema.Struct({ reason: Schema.optional(Schema.String) })),
usage: optionalNull(OpenAIResponsesUsage),
error: optionalNull(OpenAIResponsesErrorPayload),
}),
[Schema.Record(Schema.String, Schema.Unknown)],
),
),
code: optionalNull(Schema.String),
message: Schema.optional(Schema.String),
param: optionalNull(Schema.String),
error: optionalNull(OpenAIResponsesErrorPayload),
})
type OpenAIResponsesEvent = Schema.Schema.Type<typeof OpenAIResponsesEvent>
interface ParserState {
readonly tools: ToolStream.State<string>
readonly hasFunctionCall: boolean
readonly lifecycle: Lifecycle.State
readonly reasoningItems: Readonly<Record<string, ReasoningStreamItem>>
readonly store: boolean | undefined
}
type ReasoningSummaryStatus = "active" | "can-conclude" | "concluded"
interface ReasoningStreamItem {
readonly encryptedContent: string | null | undefined
// Keyed by OpenAI's numeric `summary_index`. JS object keys coerce to
// strings, but typing the map as `Record<number, ...>` documents intent
// and matches the wire field.
readonly summaryParts: Readonly<Record<number, ReasoningSummaryStatus>>
}
const invalid = ProviderShared.invalidRequest
// =============================================================================
// Request Lowering
// =============================================================================
const nativeImageToolInput = (tool: ToolDefinition) => {
const native = tool.native?.openai
return ProviderShared.isRecord(native) && native.type === "image_generation" ? native : undefined
@@ -304,20 +96,13 @@ const lowerTool = Effect.fn("OpenAIResponses.lowerTool")(function* (tool: ToolDe
const native = nativeImageToolInput(tool)
if (native !== undefined) {
if (Schema.is(OpenAIResponsesImageGenerationTool)(native)) return native
return yield* invalid("OpenAI Responses image generation tool options are invalid")
}
return {
type: "function" as const,
name: tool.name,
description: tool.description,
parameters: ToolSchemaProjection.openAI(inputSchema),
// TODO: Read this from OpenAI-specific tool options so direct LLM callers can opt into strict schemas.
strict: false,
return yield* ProviderShared.invalidRequest("OpenAI Responses image generation tool options are invalid")
}
return yield* OpenResponses.lowerTool(NAME, tool, inputSchema)
})
const lowerToolChoice = (toolChoice: NonNullable<LLMRequest["toolChoice"]>, tools: ReadonlyArray<ToolDefinition>) =>
ProviderShared.matchToolChoice("OpenAI Responses", toolChoice, {
ProviderShared.matchToolChoice(NAME, toolChoice, {
auto: () => "auto" as const,
none: () => "none" as const,
required: () => "required" as const,
@@ -327,241 +112,14 @@ const lowerToolChoice = (toolChoice: NonNullable<LLMRequest["toolChoice"]>, tool
: { type: "function" as const, name },
})
const lowerToolCall = (part: ToolCallPart): OpenAIResponsesInputItem => ({
type: "function_call",
call_id: part.id,
name: part.name,
arguments: ProviderShared.encodeJson(part.input),
})
const lowerReasoning = (part: ReasoningPart): OpenAIResponsesReasoningInput | undefined => {
const openai = part.providerMetadata?.openai
if (!ProviderShared.isRecord(openai) || typeof openai.itemId !== "string" || openai.itemId.length === 0)
return undefined
const encryptedContent =
typeof openai.reasoningEncryptedContent === "string"
? openai.reasoningEncryptedContent
: openai.reasoningEncryptedContent === null
? null
: undefined
return {
type: "reasoning",
id: openai.itemId,
summary: part.text.length > 0 ? [{ type: "summary_text", text: part.text }] : [],
encrypted_content: encryptedContent,
}
}
const hostedToolItemID = (part: ToolResultPart) => {
const openai = part.providerMetadata?.openai
return ProviderShared.isRecord(openai) && typeof openai.itemId === "string" && openai.itemId.length > 0
? openai.itemId
: undefined
}
const lowerMedia = Effect.fn("OpenAIResponses.lowerMedia")(function* (part: MediaPart, provider: string) {
const media = yield* ProviderShared.validateMedia("OpenAI Responses", part, MEDIA_MIMES)
if (media.mime === "application/pdf") {
// xAI models inline bytes and MIME separately; OpenAI uses a data URL in file_data.
if (provider === "xai")
return {
type: "input_file" as const,
filename: part.filename ?? "document.pdf",
file_data: media.base64,
mime_type: media.mime,
}
return {
type: "input_file" as const,
filename: part.filename ?? "document.pdf",
file_data: media.dataUrl,
}
}
return { type: "input_image" as const, image_url: media.dataUrl }
})
const lowerUserContent = Effect.fn("OpenAIResponses.lowerUserContent")(function* (
part: LLMRequest["messages"][number]["content"][number],
provider: string,
) {
if (part.type === "text") return { type: "input_text" as const, text: part.text }
if (part.type === "media") return yield* lowerMedia(part, provider)
return yield* ProviderShared.unsupportedContent("OpenAI Responses", "user", ["text", "media"])
})
// Tool results may carry structured text, images, and files. Keep media as provider-native
// content instead of JSON-stringifying base64 into a prompt string.
const lowerToolResultContentItem = Effect.fn("OpenAIResponses.lowerToolResultContentItem")(function* (
item: ToolContent,
provider: string,
) {
if (item.type === "text") return { type: "input_text" as const, text: item.text }
return yield* lowerMedia(
{ type: "media", mediaType: item.mime, data: item.uri, filename: item.name },
provider,
)
})
const lowerToolResultOutput = Effect.fn("OpenAIResponses.lowerToolResultOutput")(function* (
part: ToolResultPart,
provider: string,
) {
// Text/json/error results are encoded as a plain string for backward
// compatibility with existing cassettes and provider expectations.
if (part.result.type !== "content") return ProviderShared.toolResultText(part)
// Preserve the narrowed array element type when compiled through a consumer package.
const content: ReadonlyArray<ToolContent> = part.result.value
return yield* Effect.forEach(content, (item) => lowerToolResultContentItem(item, provider))
})
const lowerMessages = Effect.fn("OpenAIResponses.lowerMessages")(function* (request: LLMRequest) {
const system: OpenAIResponsesInputItem[] =
request.system.length === 0 ? [] : [{ role: "system", content: ProviderShared.joinText(request.system) }]
const input: OpenAIResponsesInputItem[] = [...system]
const store = OpenAIOptions.store(request)
for (const message of request.messages) {
if (message.role === "system") {
const part = yield* ProviderShared.wrappedSystemUpdate("OpenAI Responses", message)
const previous = input.at(-1)
if (previous && "role" in previous && previous.role === "user")
input[input.length - 1] = {
role: "user",
content: [...previous.content, { type: "input_text", text: part.text }],
}
else input.push({ role: "user", content: [{ type: "input_text", text: part.text }] })
continue
}
if (message.role === "user") {
input.push({
role: "user",
content: yield* Effect.forEach(message.content, (part) => lowerUserContent(part, request.model.provider)),
})
continue
}
if (message.role === "assistant") {
const content: TextPart[] = []
const reasoningItems: Record<string, OpenAIResponsesReasoningReplay> = {}
const reasoningReferences = new Set<string>()
const hostedToolReferences = new Set<string>()
const flushText = () => {
if (content.length === 0) return
input.push({ role: "assistant", content: content.map((part) => ({ type: "output_text", text: part.text })) })
content.splice(0, content.length)
}
for (const part of message.content) {
if (part.type === "text") {
content.push(part)
continue
}
if (part.type === "reasoning") {
flushText()
const reasoning = lowerReasoning(part)
if (!reasoning) continue
if (store !== false) {
if (!reasoningReferences.has(reasoning.id)) input.push({ type: "item_reference", id: reasoning.id })
reasoningReferences.add(reasoning.id)
continue
}
const existing = reasoningItems[reasoning.id]
if (existing) {
existing.summary.push(...reasoning.summary)
if (typeof reasoning.encrypted_content === "string")
existing.encrypted_content = reasoning.encrypted_content
continue
}
const replay = {
type: reasoning.type,
summary: reasoning.summary,
encrypted_content: reasoning.encrypted_content,
}
reasoningItems[reasoning.id] = replay
input.push(replay)
continue
}
if (part.type === "tool-call") {
flushText()
if (part.providerExecuted === true) continue
input.push(lowerToolCall(part))
continue
}
if (part.type === "tool-result" && part.providerExecuted === true) {
flushText()
const itemID = hostedToolItemID(part)
if (store !== false && itemID && !hostedToolReferences.has(itemID))
input.push({ type: "item_reference", id: itemID })
if (store === false && part.name === "image_generation" && part.result.type === "content") {
const content: ReadonlyArray<ToolContent> = part.result.value
input.push({
role: "user",
content: yield* Effect.forEach(content, (item) =>
lowerToolResultContentItem(item, request.model.provider),
),
})
}
if (itemID) hostedToolReferences.add(itemID)
continue
}
return yield* ProviderShared.unsupportedContent("OpenAI Responses", "assistant", [
"text",
"reasoning",
"tool-call",
"tool-result",
])
}
flushText()
continue
}
for (const part of message.content) {
if (!ProviderShared.supportsContent(part, ["tool-result"]))
return yield* ProviderShared.unsupportedContent("OpenAI Responses", "tool", ["tool-result"])
input.push({
type: "function_call_output",
call_id: part.id,
output: yield* lowerToolResultOutput(part, request.model.provider),
})
}
}
// With store:false, OpenAI only accepts previous reasoning items when the
// complete item has encrypted state. Summary blocks for one item may carry
// that state only on the last block, so filter after they have been joined.
return store === false
? input.filter(
(item) => !("type" in item) || item.type !== "reasoning" || typeof item.encrypted_content === "string",
)
: input
})
const lowerOptions = Effect.fn("OpenAIResponses.lowerOptions")(function* (request: LLMRequest) {
const store = OpenAIOptions.store(request)
const promptCacheKey = OpenAIOptions.promptCacheKey(request)
const effort = OpenAIOptions.reasoningEffort(request)
const summary = OpenAIOptions.reasoningSummary(request)
const include = OpenAIOptions.include(request)
const verbosity = OpenAIOptions.textVerbosity(request)
const instructions = OpenAIOptions.instructions(request)
const serviceTier = OpenAIOptions.serviceTier(request)
return {
...(instructions ? { instructions } : {}),
...(store !== undefined ? { store } : {}),
...(promptCacheKey ? { prompt_cache_key: promptCacheKey } : {}),
...(include ? { include } : {}),
...(effort || summary ? { reasoning: { effort, summary } } : {}),
...(verbosity ? { text: { verbosity } } : {}),
...(serviceTier ? { service_tier: serviceTier } : {}),
}
})
const fromRequest = Effect.fn("OpenAIResponses.fromRequest")(function* (request: LLMRequest) {
const generation = request.generation
const options = yield* lowerOptions(request)
const body = yield* OpenResponses.fromRequestWithExtension(
LLMRequest.update(request, { tools: [], toolChoice: undefined }),
extension,
)
const toolSchemaCompatibility = request.model.compatibility?.toolSchema
return {
model: request.model.id,
input: yield* lowerMessages(request),
...body,
tools:
request.tools.length === 0
? undefined
@@ -569,58 +127,25 @@ const fromRequest = Effect.fn("OpenAIResponses.fromRequest")(function* (request:
lowerTool(tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, toolSchemaCompatibility)),
),
tool_choice: request.toolChoice ? yield* lowerToolChoice(request.toolChoice, request.tools) : undefined,
stream: true as const,
max_output_tokens: generation?.maxTokens,
temperature: generation?.temperature,
top_p: generation?.topP,
...options,
}
} satisfies OpenAIResponsesBody
})
// =============================================================================
// Stream Parsing
// =============================================================================
// OpenAI Responses reports `input_tokens` (inclusive total) with a
// `cached_tokens` subset, and `output_tokens` (inclusive total) with a
// `reasoning_tokens` subset. Pass the totals through and derive the
// non-cached breakdown.
const mapUsage = (usage: OpenAIResponsesUsage | null | undefined) => {
if (!usage) return undefined
const cached = usage.input_tokens_details?.cached_tokens
const reasoning = usage.output_tokens_details?.reasoning_tokens
const nonCached = ProviderShared.subtractTokens(usage.input_tokens, cached)
return new Usage({
inputTokens: usage.input_tokens,
outputTokens: usage.output_tokens,
nonCachedInputTokens: nonCached,
cacheReadInputTokens: cached,
reasoningTokens: reasoning,
totalTokens: ProviderShared.totalTokens(usage.input_tokens, usage.output_tokens, usage.total_tokens),
providerMetadata: { openai: usage },
})
type HostedToolData = OpenResponses.StreamItem & {
readonly id: string
readonly status?: string
readonly action?: unknown
readonly queries?: unknown
readonly results?: unknown
readonly code?: string
readonly container_id?: string
readonly outputs?: unknown
readonly server_label?: string
readonly output?: unknown
readonly result?: string
readonly output_format?: "png" | "jpeg" | "webp"
readonly error?: unknown
}
const mapFinishReason = (event: OpenAIResponsesEvent, hasFunctionCall: boolean): FinishReason => {
const reason = event.response?.incomplete_details?.reason
if (reason === undefined || reason === null)
return hasFunctionCall ? "tool-calls" : event.type === "response.incomplete" ? "unknown" : "stop"
if (reason === "max_output_tokens") return "length"
if (reason === "content_filter") return "content-filter"
return hasFunctionCall ? "tool-calls" : "unknown"
}
const openaiMetadata = (metadata: Record<string, unknown>): ProviderMetadata => ({ openai: metadata })
// Hosted tool items (provider-executed) ship their typed input + status +
// result fields all in one item. We expose them as a `tool-call` +
// `tool-result` pair so consumers can treat them uniformly with client tools,
// only differentiated by `providerExecuted: true`.
//
// One record per OpenAI Responses item type that represents a hosted
// (provider-executed) tool call: the common name we surface, plus an `input`
// extractor that picks the fields the model actually populated for that tool.
// Falling back to `{}` when an entry isn't fully typed keeps unknown tools
// observable without rolling a per-tool schema.
const HOSTED_TOOLS = {
web_search_call: { name: "web_search", input: (item) => item.action ?? {} },
web_search_preview_call: { name: "web_search_preview", input: (item) => item.action ?? {} },
@@ -636,38 +161,28 @@ const HOSTED_TOOLS = {
input: (item) => ({ server_label: item.server_label, name: item.name, arguments: item.arguments }),
},
local_shell_call: { name: "local_shell", input: (item) => item.action ?? {} },
} as const satisfies Record<
string,
{ readonly name: string; readonly input: (item: OpenAIResponsesStreamItem) => unknown }
>
} as const satisfies Record<string, { readonly name: string; readonly input: (item: HostedToolData) => unknown }>
type HostedToolType = keyof typeof HOSTED_TOOLS
type HostedToolItem = HostedToolData & { readonly type: HostedToolType }
const isHostedToolItem = (
item: OpenAIResponsesStreamItem,
): item is OpenAIResponsesStreamItem & { type: HostedToolType; id: string } =>
const isHostedToolItem = (item: OpenResponses.StreamItem): item is HostedToolItem =>
item.type in HOSTED_TOOLS && typeof item.id === "string" && item.id.length > 0
const isReasoningItem = (
item: OpenAIResponsesStreamItem,
): item is OpenAIResponsesStreamItem & { type: "reasoning"; id: string } =>
item.type === "reasoning" && typeof item.id === "string" && item.id.length > 0
// Round-trip the full item as the structured result so consumers can extract
// outputs / sources / status without re-decoding.
const hostedToolResult = Effect.fn("OpenAIResponses.hostedToolResult")(function* (item: OpenAIResponsesStreamItem) {
const isError = typeof item.error !== "undefined" && item.error !== null
const hostedToolResult = Effect.fn("OpenAIResponses.hostedToolResult")(function* (item: HostedToolItem) {
const isError = item.error !== undefined && item.error !== null
if (item.type === "image_generation_call" && item.result) {
yield* Effect.fromResult(Encoding.decodeBase64(item.result)).pipe(
Effect.mapError(() => ProviderShared.eventError(ADAPTER, "OpenAI Responses returned invalid image base64")),
)
const format = item.output_format ?? "png"
return {
type: "content" as const,
value: [
{
type: "file" as const,
uri: `data:image/${item.output_format ?? "png"};base64,${item.result}`,
mime: `image/${item.output_format ?? "png"}`,
uri: `data:image/${format};base64,${item.result}`,
mime: `image/${format}`,
},
],
}
@@ -675,12 +190,15 @@ const hostedToolResult = Effect.fn("OpenAIResponses.hostedToolResult")(function*
return isError ? { type: "error" as const, value: item.error } : { type: "json" as const, value: item }
})
const hostedToolEvents = Effect.fn("OpenAIResponses.hostedToolEvents")(function* (
item: OpenAIResponsesStreamItem & { type: HostedToolType; id: string },
const onHostedToolDone = Effect.fn("OpenAIResponses.onHostedToolDone")(function* (
state: OpenResponses.ParserState,
item: HostedToolItem,
) {
const tool = HOSTED_TOOLS[item.type]
const providerMetadata = openaiMetadata({ itemId: item.id })
return [
const providerMetadata = OpenResponses.providerMetadata(state, { itemId: item.id })
const events: LLMEvent[] = []
const lifecycle = Lifecycle.stepStart(state.lifecycle, events)
events.push(
LLMEvent.toolCall({
id: item.id,
name: tool.name,
@@ -695,363 +213,24 @@ const hostedToolEvents = Effect.fn("OpenAIResponses.hostedToolEvents")(function*
providerExecuted: true,
providerMetadata,
}),
]
)
return [{ ...state, lifecycle }, events] satisfies OpenResponses.StepResult
})
type StepResult = readonly [ParserState, ReadonlyArray<LLMEvent>]
const NO_EVENTS: StepResult["1"] = []
// `response.completed` / `response.incomplete` are clean finishes that emit a
// `finish` event; `response.failed` is a hard failure. All three end the stream,
// so keep this set aligned with `step` and the protocol's terminal predicate.
const TERMINAL_TYPES = new Set(["response.completed", "response.incomplete", "response.failed"])
const onOutputTextDelta = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {
if (!event.delta) return [state, NO_EVENTS]
const events: LLMEvent[] = []
return [
{ ...state, lifecycle: Lifecycle.textDelta(state.lifecycle, events, event.item_id ?? "text-0", event.delta) },
events,
]
const step = (state: OpenResponses.ParserState, event: OpenResponses.Event) => {
if (event.type === "response.reasoning_text.delta" || event.type === "response.reasoning_summary.delta")
return event.item_id
? Effect.succeed(OpenResponses.onReasoningDelta(state, event, event.item_id))
: ProviderShared.eventError(ADAPTER, `${event.type} is missing item_id`)
if (event.type === "response.reasoning_text.done" || event.type === "response.reasoning_summary.done")
return event.item_id
? Effect.succeed(OpenResponses.onReasoningDone(state, event))
: ProviderShared.eventError(ADAPTER, `${event.type} is missing item_id`)
if (event.type === "response.output_item.done" && event.item && isHostedToolItem(event.item))
return onHostedToolDone(state, event.item)
return OpenResponses.step(state, event)
}
const onOutputTextDone = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {
const events: LLMEvent[] = []
return [{ ...state, lifecycle: Lifecycle.textEnd(state.lifecycle, events, event.item_id ?? "text-0") }, events]
}
const onReasoningDelta = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {
if (!event.delta) return [state, NO_EVENTS]
const events: LLMEvent[] = []
const itemID = event.item_id ?? "reasoning-0"
const id =
event.summary_index !== undefined || state.reasoningItems[itemID] ? `${itemID}:${event.summary_index ?? 0}` : itemID
return [
{
...state,
lifecycle: Lifecycle.reasoningDelta(state.lifecycle, events, id, event.delta),
},
events,
]
}
const onReasoningDone = (state: ParserState, _event: OpenAIResponsesEvent): StepResult => [state, NO_EVENTS]
const reasoningMetadata = (item: OpenAIResponsesStreamItem & { id: string }) =>
openaiMetadata({ itemId: item.id, reasoningEncryptedContent: item.encrypted_content ?? null })
// OpenAI Responses streams reasoning items in a stable order:
// `output_item.added` (reasoning) →
// `reasoning_summary_part.added` (index=0) →
// `reasoning_summary_text.delta` →
// `reasoning_summary_part.done` (index=0) →
// (repeat for index>0) →
// `output_item.done` (reasoning).
// The handlers below rely on this ordering: `onOutputItemAdded` seeds the
// per-item entry, `onReasoningSummaryPartAdded` for `summary_index === 0`
// short-circuits when the entry already exists, and higher-index handlers
// fold against the same entry. Behaviour for out-of-order events is
// best-effort, not guaranteed.
const onOutputItemAdded = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {
const item = event.item
if (item && isReasoningItem(item)) {
const events: LLMEvent[] = []
return [
{
...state,
lifecycle: Lifecycle.reasoningStart(state.lifecycle, events, `${item.id}:0`, reasoningMetadata(item)),
reasoningItems: {
...state.reasoningItems,
[item.id]: { encryptedContent: item.encrypted_content, summaryParts: { 0: "active" } },
},
},
events,
]
}
if (item?.type !== "function_call" || !item.id) return [state, NO_EVENTS]
const providerMetadata = openaiMetadata({ itemId: item.id })
const events: LLMEvent[] = []
const lifecycle = Lifecycle.stepStart(state.lifecycle, events)
return [
{
...state,
lifecycle,
hasFunctionCall: state.hasFunctionCall,
tools: ToolStream.start(state.tools, item.id, {
id: item.call_id ?? item.id,
name: item.name ?? "",
input: item.arguments ?? "",
providerMetadata,
}),
},
[...events, LLMEvent.toolInputStart({ id: item.call_id ?? item.id, name: item.name ?? "", providerMetadata })],
]
}
const onReasoningSummaryPartAdded = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {
if (!event.item_id || event.summary_index === undefined) return [state, NO_EVENTS]
const item = state.reasoningItems[event.item_id] ?? { encryptedContent: undefined, summaryParts: {} }
if (event.summary_index === 0) {
if (state.reasoningItems[event.item_id]) return [state, NO_EVENTS]
const events: LLMEvent[] = []
return [
{
...state,
lifecycle: Lifecycle.reasoningStart(
state.lifecycle,
events,
`${event.item_id}:0`,
openaiMetadata({ itemId: event.item_id, reasoningEncryptedContent: null }),
),
reasoningItems: {
...state.reasoningItems,
[event.item_id]: { ...item, summaryParts: { 0: "active" } },
},
},
events,
]
}
const events: LLMEvent[] = []
const closed = Object.entries(item.summaryParts)
.filter((entry) => entry[1] === "can-conclude")
.reduce(
(lifecycle, entry) =>
Lifecycle.reasoningEnd(
lifecycle,
events,
`${event.item_id}:${entry[0]}`,
openaiMetadata({ itemId: event.item_id }),
),
state.lifecycle,
)
return [
{
...state,
lifecycle: Lifecycle.reasoningStart(
closed,
events,
`${event.item_id}:${event.summary_index}`,
openaiMetadata({ itemId: event.item_id, reasoningEncryptedContent: item.encryptedContent ?? null }),
),
reasoningItems: {
...state.reasoningItems,
[event.item_id]: {
...item,
summaryParts: {
...Object.fromEntries(
Object.entries(item.summaryParts).map((entry) =>
entry[1] === "can-conclude" ? [entry[0], "concluded" as const] : entry,
),
),
[event.summary_index]: "active",
},
},
},
},
events,
]
}
const onReasoningSummaryPartDone = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {
if (!event.item_id || event.summary_index === undefined) return [state, NO_EVENTS]
const item = state.reasoningItems[event.item_id]
if (!item) return [state, NO_EVENTS]
const events: LLMEvent[] = []
return [
{
...state,
lifecycle:
state.store !== false
? Lifecycle.reasoningEnd(
state.lifecycle,
events,
`${event.item_id}:${event.summary_index}`,
openaiMetadata({ itemId: event.item_id }),
)
: state.lifecycle,
reasoningItems: {
...state.reasoningItems,
[event.item_id]: {
...item,
summaryParts: {
...item.summaryParts,
[event.summary_index]: state.store !== false ? "concluded" : "can-conclude",
},
},
},
},
events,
]
}
const onFunctionCallArgumentsDelta = Effect.fn("OpenAIResponses.onFunctionCallArgumentsDelta")(function* (
state: ParserState,
event: OpenAIResponsesEvent,
) {
if (!event.item_id || !event.delta) return [state, NO_EVENTS] satisfies StepResult
const result = ToolStream.appendExisting(
ADAPTER,
state.tools,
event.item_id,
event.delta,
"OpenAI Responses tool argument delta is missing its tool call",
)
if (ToolStream.isError(result)) return yield* result
const events: LLMEvent[] = []
const lifecycle = result.events.length ? Lifecycle.stepStart(state.lifecycle, events) : state.lifecycle
events.push(...result.events)
return [{ ...state, lifecycle, tools: result.tools }, events] satisfies StepResult
})
const onOutputItemDone = Effect.fn("OpenAIResponses.onOutputItemDone")(function* (
state: ParserState,
event: OpenAIResponsesEvent,
) {
const item = event.item
if (!item) return [state, NO_EVENTS] satisfies StepResult
if (item.type === "message" && item.id) return onOutputTextDone(state, { ...event, item_id: item.id })
if (item.type === "function_call") {
if (!item.id || !item.call_id || !item.name) return [state, NO_EVENTS] satisfies StepResult
const tools = state.tools[item.id]
? state.tools
: ToolStream.start(state.tools, item.id, { id: item.call_id, name: item.name })
const result =
item.arguments === undefined
? yield* ToolStream.finish(ADAPTER, tools, item.id)
: yield* ToolStream.finishWithInput(ADAPTER, tools, item.id, item.arguments)
const events: LLMEvent[] = []
const resultEvents = result.events ?? []
const lifecycle = resultEvents.length ? Lifecycle.stepStart(state.lifecycle, events) : state.lifecycle
events.push(...resultEvents)
return [
{
...state,
lifecycle,
hasFunctionCall:
resultEvents.some((event) => LLMEvent.is.toolCall(event) || LLMEvent.is.toolInputError(event)) ||
state.hasFunctionCall,
tools: result.tools,
},
events,
] satisfies StepResult
}
if (isHostedToolItem(item)) {
const events: LLMEvent[] = []
const lifecycle = Lifecycle.stepStart(state.lifecycle, events)
events.push(...(yield* hostedToolEvents(item)))
return [{ ...state, lifecycle }, events] satisfies StepResult
}
if (isReasoningItem(item)) {
const events: LLMEvent[] = []
const providerMetadata = reasoningMetadata(item)
const reasoningItem = state.reasoningItems[item.id]
if (reasoningItem) {
const lifecycle = Object.entries(reasoningItem.summaryParts)
.filter((entry) => entry[1] === "active" || entry[1] === "can-conclude")
.reduce(
(lifecycle, entry) => Lifecycle.reasoningEnd(lifecycle, events, `${item.id}:${entry[0]}`, providerMetadata),
state.lifecycle,
)
const { [item.id]: _removed, ...reasoningItems } = state.reasoningItems
return [{ ...state, lifecycle, reasoningItems }, events] satisfies StepResult
}
if (!state.lifecycle.reasoning.has(item.id)) {
const lifecycle = Lifecycle.stepStart(state.lifecycle, events)
events.push(LLMEvent.reasoningStart({ id: item.id, providerMetadata }))
events.push(LLMEvent.reasoningEnd({ id: item.id, providerMetadata }))
return [{ ...state, lifecycle }, events] satisfies StepResult
}
return [
{ ...state, lifecycle: Lifecycle.reasoningEnd(state.lifecycle, events, item.id, providerMetadata) },
events,
] satisfies StepResult
}
return [state, NO_EVENTS] satisfies StepResult
})
const onResponseFinish = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {
const events: LLMEvent[] = []
const lifecycle = Lifecycle.finish(state.lifecycle, events, {
reason: mapFinishReason(event, state.hasFunctionCall),
usage: mapUsage(event.response?.usage),
providerMetadata:
event.response?.id || event.response?.service_tier
? openaiMetadata({
responseId: event.response.id,
serviceTier: event.response.service_tier,
})
: undefined,
})
return [{ ...state, lifecycle }, events]
}
// Build a single human-readable message from whatever the provider supplied.
// When both code and message are present, prefix the code so consumers see
// the failure mode (e.g. `rate_limit_exceeded: Slow down`) instead of just
// the bare message — production rate limits and context-length failures used
// to be indistinguishable from generic stream drops.
const providerErrorMessage = (event: OpenAIResponsesEvent, fallback: string): string => {
const nested = event.error ?? event.response?.error ?? undefined
const message = event.message || nested?.message || undefined
const code = event.code || nested?.code || undefined
if (message && code) return `${code}: ${message}`
return message || code || fallback
}
const providerError = (event: OpenAIResponsesEvent, fallback: string) => {
const code = event.code || event.error?.code || event.response?.error?.code || undefined
const message = providerErrorMessage(event, fallback)
return new LLMError({
module: ADAPTER,
method: "stream",
reason: classifyProviderFailure({ message, code }),
})
}
const step = (state: ParserState, event: OpenAIResponsesEvent) => {
if (event.type === "response.output_text.delta") return Effect.succeed(onOutputTextDelta(state, event))
if (event.type === "response.output_text.done") return Effect.succeed(onOutputTextDone(state, event))
if (
event.type === "response.reasoning_text.delta" ||
event.type === "response.reasoning_summary.delta" ||
event.type === "response.reasoning_summary_text.delta"
)
return Effect.succeed(onReasoningDelta(state, event))
if (
event.type === "response.reasoning_text.done" ||
event.type === "response.reasoning_summary.done" ||
event.type === "response.reasoning_summary_text.done"
)
return Effect.succeed(onReasoningDone(state, event))
if (event.type === "response.reasoning_summary_part.added")
return Effect.succeed(onReasoningSummaryPartAdded(state, event))
if (event.type === "response.reasoning_summary_part.done")
return Effect.succeed(onReasoningSummaryPartDone(state, event))
if (event.type === "response.output_item.added") return Effect.succeed(onOutputItemAdded(state, event))
if (event.type === "response.function_call_arguments.delta") return onFunctionCallArgumentsDelta(state, event)
if (event.type === "response.output_item.done") return onOutputItemDone(state, event)
if (event.type === "response.completed" || event.type === "response.incomplete")
return Effect.succeed(onResponseFinish(state, event))
if (event.type === "response.failed") return providerError(event, "OpenAI Responses response failed")
if (event.type === "error") return providerError(event, "OpenAI Responses stream error")
return Effect.succeed<StepResult>([state, NO_EVENTS])
}
// =============================================================================
// Protocol And OpenAI Route
// =============================================================================
/**
* The OpenAI Responses protocol — request body construction, body schema, and
* the streaming-event state machine. Used by native OpenAI and (once
* registered) Azure OpenAI Responses.
*/
export const protocol = Protocol.make({
id: ADAPTER,
body: {
@@ -1059,16 +238,10 @@ export const protocol = Protocol.make({
from: fromRequest,
},
stream: {
event: Protocol.jsonEvent(OpenAIResponsesEvent),
initial: (request) => ({
hasFunctionCall: false,
tools: ToolStream.empty<string>(),
lifecycle: Lifecycle.initial(),
reasoningItems: {},
store: OpenAIOptions.store(request),
}),
event: OpenResponses.protocol.stream.event,
initial: (request) => OpenResponses.initial(request, extension),
step,
terminal: (event) => TERMINAL_TYPES.has(event.type),
terminal: OpenResponses.terminal,
},
})
+11 -8
View File
@@ -1,4 +1,4 @@
import { LLMEvent, type FinishReason, type ProviderMetadata, type Usage } from "../../schema"
import { LLMEvent, type FinishReasonDetails, type ProviderMetadata, type Usage } from "../../schema"
export interface State {
readonly stepStarted: boolean
@@ -14,16 +14,19 @@ export const stepStart = (state: State, events: LLMEvent[]): State => {
return { ...state, stepStarted: true }
}
export const textDelta = (state: State, events: LLMEvent[], id: string, text: string): State => {
export const textStart = (state: State, events: LLMEvent[], id: string, providerMetadata?: ProviderMetadata): State => {
if (state.text.has(id)) return state
const stepped = stepStart(state, events)
if (stepped.text.has(id)) {
events.push(LLMEvent.textDelta({ id, text }))
return stepped
}
events.push(LLMEvent.textStart({ id }), LLMEvent.textDelta({ id, text }))
events.push(LLMEvent.textStart({ id, providerMetadata }))
return { ...stepped, text: new Set([...stepped.text, id]) }
}
export const textDelta = (state: State, events: LLMEvent[], id: string, text: string): State => {
const started = textStart(state, events, id)
events.push(LLMEvent.textDelta({ id, text }))
return started
}
export const reasoningStart = (
state: State,
events: LLMEvent[],
@@ -81,7 +84,7 @@ export const finish = (
state: State,
events: LLMEvent[],
input: {
readonly reason: FinishReason
readonly reason: FinishReasonDetails
readonly usage?: Usage
readonly providerMetadata?: ProviderMetadata
},
@@ -0,0 +1,65 @@
import { Schema } from "effect"
import { TextVerbosity, type LLMRequest } from "../../schema"
export const ResponseIncludables = [
"file_search_call.results",
"web_search_call.results",
"web_search_call.action.sources",
"message.input_image.image_url",
"computer_call_output.output.image_url",
"code_interpreter_call.outputs",
"reasoning.encrypted_content",
"message.output_text.logprobs",
] as const
export type ResponseIncludable = (typeof ResponseIncludables)[number]
export const ServiceTiers = ["auto", "default", "flex", "priority"] as const
export type ServiceTier = (typeof ServiceTiers)[number]
const TEXT_VERBOSITY = new Set<string>(["low", "medium", "high"])
const INCLUDABLES = new Set<string>(ResponseIncludables)
const SERVICE_TIERS = new Set<string>(ServiceTiers)
const isTextVerbosity = (value: unknown): value is Schema.Schema.Type<typeof TextVerbosity> =>
typeof value === "string" && TEXT_VERBOSITY.has(value)
const isServiceTier = (value: unknown): value is ServiceTier => typeof value === "string" && SERVICE_TIERS.has(value)
export const ReasoningEffort = Schema.String
export const TextVerbositySchema = TextVerbosity
export const ResponseIncludableSchema = Schema.Literals(ResponseIncludables)
export const ServiceTierSchema = Schema.Literals(ServiceTiers)
export interface Resolved {
readonly instructions?: string
readonly store?: boolean
readonly promptCacheKey?: string
readonly reasoningEffort?: string
readonly reasoningSummary?: "auto" | "concise" | "detailed"
readonly include?: ReadonlyArray<ResponseIncludable>
readonly textVerbosity?: Schema.Schema.Type<typeof TextVerbosity>
readonly serviceTier?: ServiceTier
}
export const resolve = (request: LLMRequest): Resolved => {
const input = request.providerOptions?.[request.model.route.providerMetadataKey ?? "openresponses"]
const include = Array.isArray(input?.include)
? input.include.filter((entry): entry is ResponseIncludable => INCLUDABLES.has(entry))
: []
const reasoningSummary = input?.reasoningSummary
return {
instructions: typeof input?.instructions === "string" ? input.instructions : undefined,
store: typeof input?.store === "boolean" ? input.store : undefined,
promptCacheKey: typeof input?.promptCacheKey === "string" ? input.promptCacheKey : undefined,
reasoningEffort: typeof input?.reasoningEffort === "string" ? input.reasoningEffort : undefined,
reasoningSummary:
reasoningSummary === "auto" || reasoningSummary === "concise" || reasoningSummary === "detailed"
? reasoningSummary
: undefined,
include: include.length > 0 ? include : undefined,
textVerbosity: isTextVerbosity(input?.textVerbosity) ? input.textVerbosity : undefined,
serviceTier: isServiceTier(input?.serviceTier) ? input.serviceTier : undefined,
}
}
export * as OpenResponsesOptions from "./open-responses-options"
@@ -1,85 +1,23 @@
import { Schema } from "effect"
import type { LLMRequest, TextVerbosity as TextVerbosityValue } from "../../schema"
import { ReasoningEfforts, TextVerbosity } from "../../schema"
import { ReasoningEfforts } from "../../schema"
import { OpenResponsesOptions } from "./open-responses-options"
export const OpenAIReasoningEfforts = ReasoningEfforts
export type OpenAIReasoningEffort = string
// Mirrors OpenAI's `ResponseIncludable` union from the official SDK. Keep this
// in lockstep with `openai-node/src/resources/responses/responses.ts`.
export const OpenAIResponseIncludables = [
"file_search_call.results",
"web_search_call.results",
"web_search_call.action.sources",
"message.input_image.image_url",
"computer_call_output.output.image_url",
"code_interpreter_call.outputs",
"reasoning.encrypted_content",
"message.output_text.logprobs",
] as const
export type OpenAIResponseIncludable = (typeof OpenAIResponseIncludables)[number]
export const OpenAIServiceTiers = ["auto", "default", "flex", "priority"] as const
export type OpenAIServiceTier = (typeof OpenAIServiceTiers)[number]
export const OpenAIResponseIncludables = OpenResponsesOptions.ResponseIncludables
export type OpenAIResponseIncludable = OpenResponsesOptions.ResponseIncludable
export const OpenAIServiceTiers = OpenResponsesOptions.ServiceTiers
export type OpenAIServiceTier = OpenResponsesOptions.ServiceTier
const TEXT_VERBOSITY = new Set<string>(["low", "medium", "high"])
const INCLUDABLES = new Set<string>(OpenAIResponseIncludables)
const SERVICE_TIERS = new Set<string>(OpenAIServiceTiers)
export const OpenAIReasoningEffort = Schema.String
export const OpenAITextVerbosity = TextVerbosity
export const OpenAIResponseIncludable = Schema.Literals(OpenAIResponseIncludables)
export const OpenAIServiceTier = Schema.Literals(OpenAIServiceTiers)
export const OpenAIReasoningEffort = OpenResponsesOptions.ReasoningEffort
export const OpenAITextVerbosity = OpenResponsesOptions.TextVerbositySchema
export const OpenAIResponseIncludable = OpenResponsesOptions.ResponseIncludableSchema
export const OpenAIServiceTier = OpenResponsesOptions.ServiceTierSchema
export const isReasoningEffort = (effort: unknown): effort is OpenAIReasoningEffort => typeof effort === "string"
const isTextVerbosity = (value: unknown): value is TextVerbosityValue =>
typeof value === "string" && TEXT_VERBOSITY.has(value)
const options = (request: LLMRequest) => request.providerOptions?.openai
export const store = (request: LLMRequest): boolean | undefined => {
const value = options(request)?.store
return typeof value === "boolean" ? value : undefined
}
export const reasoningEffort = (request: LLMRequest): string | undefined => {
const value = options(request)?.reasoningEffort
return typeof value === "string" ? value : undefined
}
export const reasoningSummary = (request: LLMRequest): "auto" | undefined =>
options(request)?.reasoningSummary === "auto" ? "auto" : undefined
// Resolve the OpenAI Responses `include` field. Filters out unknown
// includable values defensively so a typo in upstream config drops the
// invalid entry instead of poisoning the wire body. An empty array (either
// passed directly or produced by filtering) is treated as "no include" and
// returns undefined so the request body omits the field entirely.
export const include = (request: LLMRequest): ReadonlyArray<OpenAIResponseIncludable> | undefined => {
const value = options(request)?.include
if (!Array.isArray(value)) return undefined
const filtered = value.filter((entry): entry is OpenAIResponseIncludable => INCLUDABLES.has(entry))
return filtered.length > 0 ? filtered : undefined
}
export const promptCacheKey = (request: LLMRequest) => {
const value = options(request)?.promptCacheKey
return typeof value === "string" ? value : undefined
}
export const textVerbosity = (request: LLMRequest) => {
const value = options(request)?.textVerbosity
return isTextVerbosity(value) ? value : undefined
}
export const serviceTier = (request: LLMRequest) => {
const value = options(request)?.serviceTier
return typeof value === "string" && SERVICE_TIERS.has(value) ? (value as OpenAIServiceTier) : undefined
}
export const instructions = (request: LLMRequest) => {
const value = options(request)?.instructions
return typeof value === "string" ? value : undefined
}
export const resolve = OpenResponsesOptions.resolve
export * as OpenAIOptions from "./openai-options"
@@ -63,6 +63,8 @@ const openAI = (schema: JsonSchema): JsonSchema => {
return isRecord(normalized) ? normalized : { type: "object" }
}
const responses = openAI
const gemini = (schema: JsonSchema): JsonSchema => GeminiToolSchema.convert(schema) ?? {}
const modelCompatibility = (
@@ -83,4 +85,5 @@ export const ToolSchemaProjection = {
modelCompatibility,
moonshot,
openAI,
responses,
} as const
@@ -5,12 +5,17 @@ import type { ProviderAuthOption } from "../route/auth-options"
import type { RouteDefaultsInput } from "../route/client"
import { ProviderID, type ModelID } from "../schema"
export type AnthropicOptionsInput = AnthropicMessages.OptionsInput
export type AnthropicProviderOptionsInput = AnthropicMessages.ProviderOptionsInput
export type AnthropicThinkingInput = AnthropicMessages.ThinkingInput
export const id = ProviderID.make("anthropic-compatible")
export type Config = RouteDefaultsInput &
ProviderAuthOption<"optional"> & {
readonly provider?: string
readonly baseURL: string
readonly providerOptions?: AnthropicMessages.ProviderOptionsInput
}
export type Settings = ProviderPackage.Settings &
@@ -20,6 +25,7 @@ export type Settings = ProviderPackage.Settings &
) & {
readonly baseURL: string
readonly provider?: string
readonly providerOptions?: AnthropicMessages.ProviderOptionsInput
}
export const routes = [AnthropicMessages.route]
@@ -61,6 +67,7 @@ export const model: ProviderPackage.Definition<Settings>["model"] = (modelID, se
http: settings.body === undefined ? undefined : { body: { ...settings.body } },
limits: settings.limits,
provider: settings.provider,
providerOptions: settings.providerOptions,
}).model(modelID)
}
+11 -1
View File
@@ -6,11 +6,19 @@ import { ProviderID, type ModelID } from "../schema"
import { AnthropicMessages } from "../protocols/anthropic-messages"
import { AnthropicCompatible } from "./anthropic-compatible"
export type AnthropicOptionsInput = AnthropicMessages.OptionsInput
export type AnthropicProviderOptionsInput = AnthropicMessages.ProviderOptionsInput
export type AnthropicThinkingInput = AnthropicMessages.ThinkingInput
export const id = ProviderID.make("anthropic")
export const routes = [AnthropicMessages.route]
export type Config = RouteDefaultsInput & ProviderAuthOption<"optional"> & { readonly baseURL?: string }
export type Config = RouteDefaultsInput &
ProviderAuthOption<"optional"> & {
readonly baseURL?: string
readonly providerOptions?: AnthropicMessages.ProviderOptionsInput
}
export type Settings = ProviderPackage.Settings &
(
@@ -18,6 +26,7 @@ export type Settings = ProviderPackage.Settings &
| { readonly apiKey?: never; readonly authToken?: string }
) & {
readonly baseURL?: string
readonly providerOptions?: AnthropicMessages.ProviderOptionsInput
}
const auth = (options: ProviderAuthOption<"optional">) => {
@@ -52,5 +61,6 @@ export const model: ProviderPackage.Definition<Settings>["model"] = (modelID, se
headers: settings.headers === undefined ? undefined : { ...settings.headers },
http: settings.body === undefined ? undefined : { body: { ...settings.body } },
limits: settings.limits,
providerOptions: settings.providerOptions,
}).model(modelID)
}
@@ -6,9 +6,13 @@ import { Route, type RouteDefaultsInput } from "../route/client"
import { Endpoint } from "../route/endpoint"
import { Framing } from "../route/framing"
import { Protocol } from "../route/protocol"
import { ProviderID, type ModelID, type ProviderOptions } from "../schema"
import { ProviderID, type ModelID } from "../schema"
import { GoogleVertexShared } from "./google-vertex-shared"
export type AnthropicOptionsInput = AnthropicMessages.OptionsInput
export type AnthropicProviderOptionsInput = AnthropicMessages.ProviderOptionsInput
export type AnthropicThinkingInput = AnthropicMessages.ThinkingInput
const VERSION = "vertex-2023-10-16" as const
// models.dev uses this provider id even though the API contract is Anthropic Messages.
@@ -19,6 +23,7 @@ export type Config = RouteDefaultsInput &
readonly baseURL?: string
readonly location?: string
readonly project?: string
readonly providerOptions?: AnthropicMessages.ProviderOptionsInput
}
export interface Settings extends ProviderPackage.Settings {
@@ -27,7 +32,7 @@ export interface Settings extends ProviderPackage.Settings {
readonly baseURL?: string
readonly location?: string
readonly project?: string
readonly providerOptions?: ProviderOptions
readonly providerOptions?: AnthropicMessages.ProviderOptionsInput
}
const route = Route.make({
@@ -25,6 +25,7 @@ export interface Settings extends ProviderPackage.Settings {
const route = OpenAICompatibleResponses.route.with({
id: "google-vertex-responses",
provider: id,
providerOptions: { openresponses: { store: false } },
})
export const routes = [route]
+6 -2
View File
@@ -4,9 +4,12 @@ import { Auth } from "../route/auth"
import { Route, type RouteDefaultsInput } from "../route/client"
import { Endpoint } from "../route/endpoint"
import { Framing } from "../route/framing"
import { ProviderID, type ModelID, type ProviderOptions } from "../schema"
import { ProviderID, type ModelID } from "../schema"
import { GoogleVertexShared } from "./google-vertex-shared"
export type GeminiOptionsInput = Gemini.OptionsInput
export type GeminiProviderOptionsInput = Gemini.ProviderOptionsInput
export const id = ProviderID.make("google-vertex")
export type Config = RouteDefaultsInput &
@@ -14,6 +17,7 @@ export type Config = RouteDefaultsInput &
readonly baseURL?: string
readonly location?: string
readonly project?: string
readonly providerOptions?: Gemini.ProviderOptionsInput
}
export type Settings = ProviderPackage.Settings &
@@ -24,7 +28,7 @@ export type Settings = ProviderPackage.Settings &
readonly baseURL?: string
readonly location?: string
readonly project?: string
readonly providerOptions?: ProviderOptions
readonly providerOptions?: Gemini.ProviderOptionsInput
}
const route = Route.make({
+5 -2
View File
@@ -2,11 +2,13 @@ import type { RouteDefaultsInput } from "../route/client"
import { Auth } from "../route/auth"
import type { ProviderAuthOption } from "../route/auth-options"
import type { ProviderPackage } from "../provider-package"
import { HttpOptions, ProviderID, mergeHttpOptions, type ModelID, type ProviderOptions } from "../schema"
import { HttpOptions, ProviderID, mergeHttpOptions, type ModelID } from "../schema"
import { Gemini } from "../protocols/gemini"
import { GoogleImages } from "../protocols/google-images"
export type { GoogleImageOptions } from "../protocols/google-images"
export type GeminiOptionsInput = Gemini.OptionsInput
export type GeminiProviderOptionsInput = Gemini.ProviderOptionsInput
export const id = ProviderID.make("google")
@@ -15,12 +17,13 @@ export const routes = [Gemini.route]
export type Config = RouteDefaultsInput &
ProviderAuthOption<"optional"> & {
readonly baseURL?: string
readonly providerOptions?: Gemini.ProviderOptionsInput
}
export interface Settings extends ProviderPackage.Settings {
readonly apiKey?: string
readonly baseURL?: string
readonly providerOptions?: ProviderOptions
readonly providerOptions?: Gemini.ProviderOptionsInput
}
const auth = (options: ProviderAuthOption<"optional">) => {
@@ -0,0 +1,20 @@
import type { ResponseIncludable, ServiceTier } from "../protocols/utils/open-responses-options"
import type { ProviderOptions, ReasoningEffort, TextVerbosity } from "../schema"
export interface OpenResponsesOptionsInput {
readonly [key: string]: unknown
readonly instructions?: string
readonly store?: boolean
readonly promptCacheKey?: string
readonly reasoningEffort?: ReasoningEffort
readonly reasoningSummary?: "auto" | "concise" | "detailed"
readonly include?: ReadonlyArray<ResponseIncludable>
readonly textVerbosity?: TextVerbosity
readonly serviceTier?: ServiceTier
}
export type OpenResponsesProviderOptionsInput = ProviderOptions & {
readonly openresponses?: OpenResponsesOptionsInput
}
export * as OpenResponsesProviderOptions from "./open-responses-options"
@@ -3,7 +3,9 @@ import { OpenAICompatibleResponses } from "../protocols/openai-compatible-respon
import { AuthOptions, type ProviderAuthOption } from "../route/auth-options"
import type { RouteDefaultsInput } from "../route/client"
import { ProviderID, type ModelID } from "../schema"
import type { OpenAIProviderOptionsInput } from "./openai-options"
import type { OpenResponsesProviderOptionsInput } from "./open-responses-options"
export type { OpenResponsesOptionsInput, OpenResponsesProviderOptionsInput } from "./open-responses-options"
export const id = ProviderID.make("openai-compatible")
@@ -11,13 +13,14 @@ export type Config = RouteDefaultsInput &
ProviderAuthOption<"optional"> & {
readonly provider?: string
readonly baseURL: string
readonly providerOptions?: OpenResponsesProviderOptionsInput
}
export interface Settings extends ProviderPackage.Settings {
readonly apiKey?: string
readonly baseURL: string
readonly provider?: string
readonly providerOptions?: OpenAIProviderOptionsInput
readonly providerOptions?: OpenResponsesProviderOptionsInput
}
export const routes = [OpenAICompatibleResponses.route]
+3 -15
View File
@@ -1,22 +1,10 @@
import type { ProviderOptions, ReasoningEffort, TextVerbosity } from "../schema"
import type { ProviderOptions } from "../schema"
import { mergeProviderOptions } from "../schema"
import type { OpenAIResponseIncludable, OpenAIServiceTier } from "../protocols/utils/openai-options"
import type { OpenResponsesOptionsInput } from "./open-responses-options"
export type { OpenAIResponseIncludable, OpenAIServiceTier } from "../protocols/utils/openai-options"
export interface OpenAIOptionsInput {
readonly [key: string]: unknown
readonly store?: boolean
readonly promptCacheKey?: string
readonly reasoningEffort?: ReasoningEffort
readonly reasoningSummary?: "auto"
// OpenAI Responses `include` wire field. Mirrors the official SDK's
// `ResponseIncludable[]` union exactly so AI SDK callers and direct
// native-SDK callers share one shape and no translation is required.
readonly include?: ReadonlyArray<OpenAIResponseIncludable>
readonly textVerbosity?: TextVerbosity
readonly serviceTier?: OpenAIServiceTier
}
export type OpenAIOptionsInput = OpenResponsesOptionsInput
export type OpenAIProviderOptionsInput = ProviderOptions & {
readonly openai?: OpenAIOptionsInput
+2 -1
View File
@@ -12,7 +12,8 @@ import type { LLMError, LLMEvent, LLMRequest, ProtocolID } from "../schema"
* Examples:
*
* - `OpenAIChat.protocol` — chat completions style
* - `OpenAIResponses.protocol` — responses API
* - `OpenResponses.protocol` — provider-neutral Responses API baseline
* - `OpenAIResponses.protocol` — OpenAI extensions to that baseline
* - `AnthropicMessages.protocol` — messages API with content blocks
* - `Gemini.protocol` — generateContent
* - `BedrockConverse.protocol` — Converse with binary event-stream framing
+14 -8
View File
@@ -40,9 +40,9 @@ import { ProviderFailureClassification } from "./errors"
* - Anthropic and Bedrock report the input breakdown natively: Anthropic's
* `input_tokens` and Bedrock's `inputTokens` are non-cached only. Their
* mappers sum the breakdown to derive the inclusive `inputTokens`.
* Anthropic does *not* break extended-thinking out of `output_tokens`, so
* `reasoningTokens` is `undefined` and `outputTokens` carries the
* combined total — a documented limitation of the Anthropic API.
* Anthropic's `outputTokens` includes extended thinking. Newer responses
* expose that subset as `output_tokens_details.thinking_tokens`, which maps
* to `reasoningTokens`; older responses leave it undefined.
*
* `providerMetadata` always carries the provider's raw usage payload —
* keyed by provider name (`{ openai: ... }`, `{ anthropic: ... }`, etc.)
@@ -191,10 +191,16 @@ export const ToolError = Schema.Struct({
}).annotate({ identifier: "LLM.Event.ToolError" })
export type ToolError = Schema.Schema.Type<typeof ToolError>
export const FinishReasonDetails = Schema.Struct({
normalized: FinishReason,
raw: Schema.optional(Schema.String),
}).annotate({ identifier: "LLM.FinishReasonDetails" })
export type FinishReasonDetails = Schema.Schema.Type<typeof FinishReasonDetails>
export const StepFinish = Schema.Struct({
type: Schema.tag("step-finish"),
index: Schema.Number,
reason: FinishReason,
reason: FinishReasonDetails,
usage: Schema.optional(Usage),
providerMetadata: Schema.optional(ProviderMetadata),
}).annotate({ identifier: "LLM.Event.StepFinish" })
@@ -202,7 +208,7 @@ export type StepFinish = Schema.Schema.Type<typeof StepFinish>
export const Finish = Schema.Struct({
type: Schema.tag("finish"),
reason: FinishReason,
reason: FinishReasonDetails,
usage: Schema.optional(Usage),
providerMetadata: Schema.optional(ProviderMetadata),
}).annotate({ identifier: "LLM.Event.Finish" })
@@ -365,7 +371,7 @@ interface ResponseState {
readonly events: ReadonlyArray<LLMEvent>
readonly message: Message
readonly usage?: Usage
readonly finishReason?: FinishReason
readonly finishReason?: FinishReasonDetails
readonly textParts: Readonly<Record<string, ContentAssembly>>
readonly reasoningParts: Readonly<Record<string, ContentAssembly>>
readonly toolInputs: Readonly<Record<string, ToolInputAssembly>>
@@ -393,7 +399,7 @@ const appendEvent = (state: ResponseState, event: LLMEvent): ResponseState => {
return {
...state,
events,
finishReason: state.finishReason ?? "error",
finishReason: state.finishReason ?? { normalized: "error" },
}
}
return {
@@ -580,7 +586,7 @@ export class LLMResponse extends Schema.Class<LLMResponse>("LLM.Response")({
message: Message,
events: Schema.Array(LLMEvent),
usage: Schema.optional(Usage),
finishReason: FinishReason,
finishReason: FinishReasonDetails,
}) {
/** Concatenated assistant text assembled from streamed `text-delta` events. */
get text() {
-9
View File
@@ -261,13 +261,6 @@ export namespace ToolChoice {
}
}
export const ResponseFormat = Schema.Union([
Schema.Struct({ type: Schema.Literal("text") }),
Schema.Struct({ type: Schema.Literal("json"), schema: JsonSchema }),
Schema.Struct({ type: Schema.Literal("tool"), tool: ToolDefinition }),
]).pipe(Schema.toTaggedUnion("type"))
export type ResponseFormat = Schema.Schema.Type<typeof ResponseFormat>
export class LLMRequest extends Schema.Class<LLMRequest>("LLM.Request")({
id: Schema.optional(Schema.String),
model: ModelSchema,
@@ -278,7 +271,6 @@ export class LLMRequest extends Schema.Class<LLMRequest>("LLM.Request")({
generation: Schema.optional(GenerationOptions),
providerOptions: Schema.optional(ProviderOptions),
http: Schema.optional(HttpOptions),
responseFormat: Schema.optional(ResponseFormat),
cache: Schema.optional(CachePolicy),
metadata: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),
}) {}
@@ -296,7 +288,6 @@ export namespace LLMRequest {
generation: request.generation,
providerOptions: request.providerOptions,
http: request.http,
responseFormat: request.responseFormat,
cache: request.cache,
metadata: request.metadata,
})
+5 -5
View File
@@ -251,11 +251,11 @@ export class CacheHint extends Schema.Class<CacheHint>("LLM.CacheHint")({
// Auto-placement policy for prompt caching. The protocol-neutral lowering step
// reads this and injects `CacheHint`s at the configured boundaries; the
// per-protocol body builders then translate those hints into wire markers as
// usual. `"auto"` is the recommended default for agent loops — it places one
// breakpoint at the last tool definition, one at the last system part, and one
// at the latest user message. The combination of provider invalidation
// hierarchy (tools → system → messages) and Anthropic/Bedrock's 20-block
// lookback means three trailing breakpoints reliably cover the static prefix.
// usual. `"auto"` is the recommended default for agent loops — it places
// breakpoints at the last tool definition, the first and last distinct system
// parts, and the conversation tail. The rolling message breakpoint keeps a
// prior cache entry within Anthropic/Bedrock's 20-block lookback during long
// tool loops.
//
// Pass `"none"` to opt out entirely (the legacy behavior). Pass the granular
// object form to override individual choices.
+4 -4
View File
@@ -1,6 +1,6 @@
import { describe, expect } from "bun:test"
import { Effect, Schema, Stream } from "effect"
import { LLM, LLMResponse } from "../src"
import { LLM, LLMRequest, LLMResponse } from "../src"
import { Route, Endpoint, LLMClient, Protocol, type FramingDef } from "../src/route"
import { Model } from "../src/schema"
import { testEffect } from "./lib/effect"
@@ -40,7 +40,7 @@ const fakeFraming: FramingDef<FakeEvent> = {
const raiseEvent = (event: FakeEvent): import("../src/schema").LLMEvent =>
event.type === "finish"
? { type: "finish", reason: event.reason }
? { type: "finish", reason: { normalized: event.reason } }
: { type: "text-delta", id: "text-0", text: event.text }
const fakeProtocol = Protocol.make<FakeBody, FakeEvent, FakeEvent, void>({
@@ -141,7 +141,7 @@ describe("llm route", () => {
Effect.gen(function* () {
const llm = yield* LLMClient.Service
const prepared = yield* llm.prepare(
LLM.updateRequest(request, { model: updateModel(request.model, { route: configuredGemini }) }),
LLMRequest.update(request, { model: updateModel(request.model, { route: configuredGemini }) }),
)
expect(prepared.route).toBe("gemini-fake")
@@ -174,7 +174,7 @@ describe("llm route", () => {
})
const prepared = yield* (yield* LLMClient.Service).prepare(
LLM.updateRequest(request, { model: updateModel(request.model, { route: duplicate }) }),
LLMRequest.update(request, { model: updateModel(request.model, { route: duplicate }) }),
)
expect(prepared.body).toEqual({ body: "late-default" })
+26 -2
View File
@@ -137,15 +137,26 @@ Azure.configure({ apiKey: "azure-key", resourceName: "resource" }).chat("deploym
Azure.configure({ resourceName: "resource", apiKey: "azure-key", auth: Auth.header("api-key", "override") })
Anthropic.configure({ apiKey: "anthropic-key" }).model("claude-haiku")
Anthropic.configure({
apiKey: "anthropic-key",
providerOptions: {
anthropic: { thinking: { type: "enabled", budgetTokens: 1_024 }, effort: "high" },
},
}).model("claude-haiku")
// @ts-expect-error Anthropic model selectors only accept model ids.
Anthropic.configure({ apiKey: "anthropic-key" }).model("claude-haiku", {})
// @ts-expect-error Anthropic package settings accept only one auth source.
Anthropic.model("claude-sonnet-4-6", { apiKey: "anthropic-key", authToken: "anthropic-token" })
// @ts-expect-error Enabled Anthropic thinking requires a token budget.
Anthropic.configure({ providerOptions: { anthropic: { thinking: { type: "enabled" } } } })
// @ts-expect-error Anthropic thinking budgets must be numbers.
Anthropic.configure({ providerOptions: { anthropic: { thinking: { type: "enabled", budgetTokens: "large" } } } })
AnthropicCompatible.configure({
apiKey: "messages-key",
baseURL: "https://messages.example.com/v1",
provider: "example",
providerOptions: { anthropic: { thinking: { type: "disabled" } } },
}).model("compatible-model")
// @ts-expect-error Anthropic-compatible providers require a base URL.
AnthropicCompatible.configure({ apiKey: "messages-key" })
@@ -159,10 +170,19 @@ AnthropicCompatible.model("compatible-model", {
})
Google.configure({ apiKey: "google-key" }).model("gemini-2.5-flash")
Google.configure({
apiKey: "google-key",
providerOptions: { gemini: { thinkingConfig: { thinkingBudget: 0, includeThoughts: false } } },
}).model("gemini-2.5-flash")
// @ts-expect-error Google model selectors only accept model ids.
Google.configure({ apiKey: "google-key" }).model("gemini-2.5-flash", {})
// @ts-expect-error Gemini thinking budgets must be numbers.
Google.configure({ providerOptions: { gemini: { thinkingConfig: { thinkingBudget: "large" } } } })
GoogleVertex.configure({ apiKey: "vertex-key" }).model("gemini-3.5-flash")
GoogleVertex.configure({
apiKey: "vertex-key",
providerOptions: { gemini: { thinkingConfig: { thinkingBudget: 1_024 } } },
}).model("gemini-3.5-flash")
GoogleVertex.configure({ accessToken: "vertex-token", project: "project" }).model("gemini-3.5-flash")
GoogleVertex.configure({ auth: Auth.bearer("vertex-token"), project: "project" }).model("gemini-3.5-flash")
// @ts-expect-error Vertex Gemini model selectors only accept model ids.
@@ -208,7 +228,11 @@ GoogleVertexResponses.configure({
project: "project",
})
GoogleVertexMessages.configure({ accessToken: "vertex-token", project: "project" }).model("claude-sonnet-4-6")
GoogleVertexMessages.configure({
accessToken: "vertex-token",
project: "project",
providerOptions: { anthropic: { thinking: { type: "adaptive", display: "omitted" }, effort: "low" } },
}).model("claude-sonnet-4-6")
// @ts-expect-error Vertex Messages package settings do not accept API keys.
GoogleVertexMessages.model("claude-sonnet-4-6", { apiKey: "vertex-key", project: "project" })
GoogleVertexMessages.configure({ auth: Auth.bearer("vertex-token"), project: "project" }).model("claude-sonnet-4-6")
+68 -8
View File
@@ -39,8 +39,8 @@ describe("applyCachePolicy", () => {
}),
)
// No explicit cache field → auto policy fires → last system part + latest
// user message both get cache_control markers.
// A single system block is both the first and last boundary, so the auto
// policy deduplicates it and still marks the conversation tail.
expect(prepared.body).toMatchObject({
system: [{ type: "text", text: "You are concise.", cache_control: { type: "ephemeral" } }],
messages: [{ role: "user", content: [{ type: "text", text: "hi", cache_control: { type: "ephemeral" } }] }],
@@ -48,12 +48,15 @@ describe("applyCachePolicy", () => {
}),
)
it.effect("'auto' marks the last tool, last system part, and latest user message on Anthropic", () =>
it.effect("'auto' marks the last tool, first and last system parts, and final message boundary on Anthropic", () =>
Effect.gen(function* () {
const prepared = yield* LLMClient.prepare(
LLM.request({
model: anthropicModel,
system: "Sys A",
system: [
{ type: "text", text: "Base agent" },
{ type: "text", text: "Project instructions" },
],
tools: [{ name: "t1", description: "t1", inputSchema: { type: "object", properties: {} } }],
messages: [
Message.user("first user"),
@@ -66,7 +69,10 @@ describe("applyCachePolicy", () => {
expect(prepared.body).toMatchObject({
tools: [{ name: "t1", cache_control: { type: "ephemeral" } }],
system: [{ type: "text", text: "Sys A", cache_control: { type: "ephemeral" } }],
system: [
{ type: "text", text: "Base agent", cache_control: { type: "ephemeral" } },
{ type: "text", text: "Project instructions", cache_control: { type: "ephemeral" } },
],
messages: [
{ role: "user", content: [{ type: "text", text: "first user" }] },
{ role: "assistant", content: [{ type: "text", text: "assistant reply" }] },
@@ -120,7 +126,10 @@ describe("applyCachePolicy", () => {
const prepared = yield* LLMClient.prepare(
LLM.request({
model: bedrockModel,
system: "Sys",
system: [
{ type: "text", text: "Base agent" },
{ type: "text", text: "Project instructions" },
],
tools: [{ name: "t1", description: "t1", inputSchema: { type: "object", properties: {} } }],
messages: [Message.user("first user"), Message.assistant("reply"), Message.user("latest user")],
cache: "auto",
@@ -131,7 +140,12 @@ describe("applyCachePolicy", () => {
toolConfig: {
tools: [{ toolSpec: { name: "t1" } }, { cachePoint: { type: "default" } }],
},
system: [{ text: "Sys" }, { cachePoint: { type: "default" } }],
system: [
{ text: "Base agent" },
{ cachePoint: { type: "default" } },
{ text: "Project instructions" },
{ cachePoint: { type: "default" } },
],
messages: [
{ role: "user", content: [{ text: "first user" }] },
{ role: "assistant", content: [{ text: "reply" }] },
@@ -193,9 +207,55 @@ describe("applyCachePolicy", () => {
}),
)
const body = prepared.body as { system: Array<{ text: string; cache_control?: unknown }> }
const body = prepared.body as {
system: Array<{ text: string; cache_control?: unknown }>
messages: Array<{ content: Array<{ cache_control?: unknown }> }>
}
expect(body.system[0]?.cache_control).toEqual({ type: "ephemeral", ttl: "1h" })
expect(body.system[1]?.cache_control).toEqual({ type: "ephemeral" })
expect(body.messages[0]?.content[0]?.cache_control).toEqual({ type: "ephemeral" })
}),
)
it.effect("auto policy stays within the four-breakpoint cap when preserving manual hints", () =>
Effect.gen(function* () {
const request = LLM.request({
model: anthropicModel,
system: [
{ type: "text", text: "Base agent" },
{
type: "text",
text: "Manual context",
cache: new CacheHint({ type: "ephemeral", ttlSeconds: 3600 }),
},
{ type: "text", text: "Project instructions" },
],
tools: [{ name: "t1", description: "t1", inputSchema: { type: "object", properties: {} } }],
prompt: "hi",
cache: "auto",
})
const applied = applyCachePolicy(request)
expect(applied.tools[0]?.cache).toBeDefined()
expect(applied.system.map((part) => part.cache !== undefined)).toEqual([true, true, true])
const tail = applied.messages[0]!.content[0]!
expect("cache" in tail ? tail.cache : undefined).toBeUndefined()
expect(applyCachePolicy(applied)).toBe(applied)
const prepared = yield* LLMClient.prepare(request)
const body = prepared.body as {
tools: Array<{ cache_control?: unknown }>
system: Array<{ cache_control?: unknown }>
messages: Array<{ content: Array<{ cache_control?: unknown }> }>
}
const marked = [
...body.tools.map((tool) => tool.cache_control),
...body.system.map((part) => part.cache_control),
...body.messages.flatMap((message) => message.content.map((part) => part.cache_control)),
].filter((cache) => cache !== undefined)
expect(marked).toHaveLength(4)
expect(body.system[1]?.cache_control).toEqual({ type: "ephemeral", ttl: "1h" })
expect(body.messages[0]?.content[0]?.cache_control).toBeUndefined()
}),
)
+9 -1
View File
@@ -11,7 +11,13 @@ import {
XAI,
} from "@opencode-ai/ai/providers"
import * as GitHubCopilot from "@opencode-ai/ai/providers/github-copilot"
import { OpenAIChat, OpenAICompatibleChat, OpenAICompatibleResponses, OpenAIResponses } from "@opencode-ai/ai/protocols"
import {
OpenAIChat,
OpenAICompatibleChat,
OpenAICompatibleResponses,
OpenAIResponses,
OpenResponses,
} from "@opencode-ai/ai/protocols"
import * as AnthropicMessages from "@opencode-ai/ai/protocols/anthropic-messages"
describe("public exports", () => {
@@ -74,7 +80,9 @@ describe("public exports", () => {
test("protocol barrels expose supported low-level routes", () => {
expect(OpenAIChat.route.id).toBe("openai-chat")
expect(OpenAICompatibleChat.route.id).toBe("openai-compatible-chat")
expect(OpenResponses.protocol.id).toBe("open-responses")
expect(OpenAICompatibleResponses.route.id).toBe("openai-compatible-responses")
expect(OpenAICompatibleResponses.route.protocol).toBe("open-responses")
expect(OpenAIResponses.route.id).toBe("openai-responses")
expect(OpenAIResponses.webSocketRoute.id).toBe("openai-responses-websocket")
expect(AnthropicMessages.route.id).toBe("anthropic-messages")
File diff suppressed because one or more lines are too long
+1 -1
View File
@@ -83,7 +83,7 @@ const indexStep = (event: LLMEvent, index: number): LLMEvent => {
const stepState = (events: ReadonlyArray<LLMEvent>) => {
const assistantContent: ContentPart[] = []
const toolCalls: ToolCallPart[] = []
let reason: Extract<LLMEvent, { type: "finish" }>["reason"] = "unknown"
let reason: Extract<LLMEvent, { type: "finish" }>["reason"] = { normalized: "unknown" }
let usage: Usage | undefined
let providerMetadata: ProviderMetadata | undefined
+13 -4
View File
@@ -2,7 +2,16 @@ import { describe, expect, test } from "bun:test"
import { CacheHint, LLM, LLMResponse } from "../src"
import * as OpenAIChat from "../src/protocols/openai-chat"
import * as OpenAIResponses from "../src/protocols/openai-responses"
import { LLMRequest, Message, Model, ToolCallPart, ToolChoice, ToolDefinition, ToolResultPart } from "../src/schema"
import {
GenerationOptions,
LLMRequest,
Message,
Model,
ToolCallPart,
ToolChoice,
ToolDefinition,
ToolResultPart,
} from "../src/schema"
const chatRoute = OpenAIChat.route
const responsesRoute = OpenAIResponses.route
@@ -31,8 +40,8 @@ describe("llm constructors", () => {
model: Model.make({ id: "fake-model", provider: "fake", route: chatRoute }),
prompt: "Say hello.",
})
const updated = LLM.updateRequest(base, {
generation: { maxTokens: 20 },
const updated = LLMRequest.update(base, {
generation: GenerationOptions.make({ maxTokens: 20 }),
messages: [...base.messages, Message.assistant("Hi.")],
})
@@ -191,7 +200,7 @@ describe("llm constructors", () => {
LLMResponse.text({
events: [
{ type: "text-delta", id: "text-0", text: "hi" },
{ type: "finish", reason: "stop" },
{ type: "finish", reason: { normalized: "stop" } },
],
}),
).toBe("hi")
+18 -4
View File
@@ -59,7 +59,7 @@ describe("provider package entrypoints", () => {
headers: { "x-application": "opencode" },
body: { service_tier: "priority" },
limits: { context: 200_000, output: 64_000 },
providerOptions: { openai: { reasoningEffort: "low", store: true } },
providerOptions: { openresponses: { reasoningEffort: "low", store: true } },
})
expect(String(selected.provider)).toBe("example")
@@ -72,7 +72,7 @@ describe("provider package entrypoints", () => {
expect(selected.route.defaults.http?.body).toEqual({ service_tier: "priority" })
expect(selected.route.defaults.limits).toEqual({ context: 200_000, output: 64_000 })
expect(selected.route.defaults.providerOptions).toEqual({
openai: { reasoningEffort: "low", store: true },
openresponses: { reasoningEffort: "low", store: true },
})
})
@@ -85,6 +85,7 @@ describe("provider package entrypoints", () => {
headers: { "x-application": "opencode" },
body: { metadata: { user_id: "user_1" } },
limits: { context: 200_000, output: 64_000 },
providerOptions: { anthropic: { effort: "low" } },
})
expect(String(selected.provider)).toBe("example")
@@ -96,6 +97,19 @@ describe("provider package entrypoints", () => {
expect(selected.route.defaults.headers).toEqual({ "x-application": "opencode" })
expect(selected.route.defaults.http?.body).toEqual({ metadata: { user_id: "user_1" } })
expect(selected.route.defaults.limits).toEqual({ context: 200_000, output: 64_000 })
expect(selected.route.defaults.providerOptions).toEqual({ anthropic: { effort: "low" } })
})
test("maps Anthropic provider options onto the executable model", async () => {
const Anthropic = await import("@opencode-ai/ai/providers/anthropic")
const selected = Anthropic.model("claude-sonnet-4-6", {
apiKey: "fixture",
providerOptions: { anthropic: { thinking: { type: "adaptive" } } },
})
expect(selected.route.defaults.providerOptions).toEqual({
anthropic: { thinking: { type: "adaptive" } },
})
})
test("requires an Anthropic-compatible base URL at runtime", async () => {
@@ -235,12 +249,12 @@ describe("provider package entrypoints", () => {
path: "/chat/completions",
})
expect(responses.route.id).toBe("google-vertex-responses")
expect(responses.route.protocol).toBe("openai-responses")
expect(responses.route.protocol).toBe("open-responses")
expect(responses.route.endpoint).toMatchObject({
baseURL: "https://aiplatform.googleapis.com/v1/projects/vertex-project/locations/global/endpoints/openapi",
path: "/responses",
})
expect(responses.route.defaults.providerOptions).toEqual({ openai: { store: false } })
expect(responses.route.defaults.providerOptions).toEqual({ openresponses: { store: false } })
})
test("rejects conflicting Vertex auth settings at runtime", async () => {
@@ -1,6 +1,6 @@
import { describe, expect } from "bun:test"
import { Effect } from "effect"
import { CacheHint, LLM } from "../../src"
import { CacheHint, LLM, LLMRequest, Message, ToolCallPart, ToolDefinition } from "../../src"
import { LLMClient } from "../../src/route"
import * as Anthropic from "../../src/providers/anthropic"
import { LARGE_CACHEABLE_SYSTEM } from "../recorded-scenarios"
@@ -24,6 +24,39 @@ const cacheRequest = LLM.request({
generation: { maxTokens: 16, temperature: 0 },
})
const lookup = ToolDefinition.make({
name: "lookup",
description: "Look up a fixture value.",
inputSchema: {
type: "object",
properties: { index: { type: "number" } },
required: ["index"],
additionalProperties: false,
},
})
const longToolTurn = [
Message.user("Run the fixture lookups."),
...Array.from({ length: 11 }, (_, index) => {
const id = `lookup_${index}`
return [
Message.assistant(ToolCallPart.make({ id, name: lookup.name, input: { index } })),
Message.tool({
id,
name: lookup.name,
result: `Fixture result ${index}. `.repeat(80),
}),
]
}).flat(),
]
const longToolTurnRequest = LLM.request({
id: "recorded_anthropic_cache_long_tool_turn",
model,
system: LARGE_CACHEABLE_SYSTEM,
messages: longToolTurn,
tools: [lookup],
generation: { maxTokens: 16, temperature: 0 },
})
const recorded = recordedTests({
prefix: "anthropic-messages-cache",
provider: "anthropic",
@@ -50,4 +83,28 @@ describe("Anthropic Messages cache recorded", () => {
expect(second.usage?.cacheReadInputTokens ?? 0).toBeGreaterThan(0)
}),
)
recorded.effect.with("keeps a long tool turn inside the cache lookback", { tags: ["cache", "tool"] }, () =>
Effect.gen(function* () {
const first = yield* LLMClient.generate(longToolTurnRequest)
const firstRead = first.usage?.cacheReadInputTokens ?? 0
const firstWrite = first.usage?.cacheWriteInputTokens ?? 0
const firstCached = firstRead + firstWrite
// The prefix may already be warm when recording, so either a read or a
// write establishes that Anthropic recognized the cache boundary.
expect(firstCached).toBeGreaterThan(0)
const second = yield* LLMClient.generate(
LLMRequest.update(longToolTurnRequest, {
messages: [
...longToolTurn,
Message.assistant("The fixture lookups are complete."),
Message.user("Reply exactly: OK"),
],
}),
)
expect(second.usage?.cacheReadInputTokens ?? 0).toBeGreaterThanOrEqual(firstCached)
expect(second.usage?.cacheWriteInputTokens ?? 0).toBeLessThan(firstCached)
}),
)
})
@@ -1,7 +1,7 @@
import { describe, expect } from "bun:test"
import { Effect } from "effect"
import { HttpClientRequest } from "effect/unstable/http"
import { CacheHint, LLM, LLMError, Message, ToolCallPart, Usage } from "../../src"
import { CacheHint, LLM, LLMError, LLMRequest, Message, ToolCallPart, ToolDefinition, Usage } from "../../src"
import { Auth, LLMClient } from "../../src/route"
import * as AnthropicMessages from "../../src/protocols/anthropic-messages"
import { continuationRequest, nativeAnthropicMessagesContinuation } from "../continuation-scenarios"
@@ -60,7 +60,7 @@ describe("Anthropic Messages route", () => {
it.effect("lowers adaptive thinking settings with effort", () =>
Effect.gen(function* () {
const prepared = yield* LLMClient.prepare<AnthropicMessages.AnthropicMessagesBody>(
LLM.updateRequest(request, {
LLMRequest.update(request, {
providerOptions: {
anthropic: { thinking: { type: "adaptive", display: "summarized" }, effort: "low" },
},
@@ -74,6 +74,42 @@ describe("Anthropic Messages route", () => {
}),
)
it.effect("normalizes enabled and disabled thinking settings", () =>
Effect.gen(function* () {
const enabled = yield* LLMClient.prepare<AnthropicMessages.AnthropicMessagesBody>(
LLMRequest.update(request, {
providerOptions: { anthropic: { thinking: { type: "enabled", budgetTokens: 1_024 } } },
}),
)
const legacy = yield* LLMClient.prepare<AnthropicMessages.AnthropicMessagesBody>(
LLMRequest.update(request, {
providerOptions: { anthropic: { thinking: { type: "enabled", budget_tokens: 2_048 } } },
}),
)
const disabled = yield* LLMClient.prepare<AnthropicMessages.AnthropicMessagesBody>(
LLMRequest.update(request, {
providerOptions: { anthropic: { thinking: { type: "disabled" } } },
}),
)
expect(enabled.body.thinking).toEqual({ type: "enabled", budget_tokens: 1_024 })
expect(legacy.body.thinking).toEqual({ type: "enabled", budget_tokens: 2_048 })
expect(disabled.body.thinking).toEqual({ type: "disabled" })
}),
)
it.effect("rejects enabled thinking without a budget", () =>
Effect.gen(function* () {
const error = yield* LLMClient.prepare(
LLMRequest.update(request, {
providerOptions: { anthropic: { thinking: { type: "enabled" } } },
}),
).pipe(Effect.flip)
expect(error.message).toContain("Anthropic thinking provider option requires budgetTokens")
}),
)
it.effect("lowers chronological system updates natively for Claude Opus 4.8 with cache hints", () =>
Effect.gen(function* () {
const prepared = yield* LLMClient.prepare<AnthropicMessages.AnthropicMessagesBody>(
@@ -235,6 +271,34 @@ describe("Anthropic Messages route", () => {
}),
)
it.effect("keeps tools and sends tool_choice none", () =>
Effect.gen(function* () {
const prepared = yield* LLMClient.prepare<AnthropicMessages.AnthropicMessagesBody>(
LLM.request({
id: "req_tool_choice_none",
model,
tools: [{ name: "lookup", description: "Look things up", inputSchema: { type: "object", properties: {} } }],
messages: [
Message.user("What is the weather?"),
Message.assistant([ToolCallPart.make({ id: "call_1", name: "lookup", input: { query: "weather" } })]),
Message.tool({ id: "call_1", name: "lookup", result: { forecast: "sunny" } }),
],
toolChoice: "none",
cache: "none",
}),
)
expect(prepared.body.tools).toEqual([
{
name: "lookup",
description: "Look things up",
input_schema: { type: "object", properties: {} },
},
])
expect(prepared.body.tool_choice).toEqual({ type: "none" })
}),
)
// Regression: read tool results must stay structured so base64 media data is
// not JSON-stringified into `tool_result.content`.
it.effect("lowers media tool-result content as structured blocks", () =>
@@ -381,6 +445,34 @@ describe("Anthropic Messages route", () => {
}),
)
it.effect("round-trips redacted thinking as redacted_thinking blocks", () =>
Effect.gen(function* () {
const prepared = yield* LLMClient.prepare(
LLM.request({
model,
messages: [
Message.assistant([
{ type: "reasoning", text: "", providerMetadata: { anthropic: { redactedData: "opaque_1" } } },
{ type: "reasoning", text: "visible", providerMetadata: { anthropic: { signature: "sig_1" } } },
]),
],
}),
)
expect(prepared.body).toMatchObject({
messages: [
{
role: "assistant",
content: [
{ type: "redacted_thinking", data: "opaque_1" },
{ type: "thinking", thinking: "visible", signature: "sig_1" },
],
},
],
})
}),
)
it.effect("parses text, reasoning, and usage stream fixtures", () =>
Effect.gen(function* () {
const body = sseEvents(
@@ -414,18 +506,351 @@ describe("Anthropic Messages route", () => {
expect(response.events.find((event) => event.type === "reasoning-end")).toMatchObject({
providerMetadata: { anthropic: { signature: "sig_1" } },
})
expect(response.events.find((event) => event.type === "reasoning-delta" && event.text === "")).toBeUndefined()
expect(response.message.content).toEqual([
{ type: "text", text: "Hello!" },
{ type: "reasoning", text: "thinking", providerMetadata: { anthropic: { signature: "sig_1" } } },
])
expect(response.events.at(-1)).toMatchObject({
type: "finish",
reason: "stop",
reason: { normalized: "stop", raw: "end_turn" },
providerMetadata: { anthropic: { stopSequence: "\n\nHuman:" } },
})
}),
)
it.effect("requires message_stop before completing a streamed message", () =>
Effect.gen(function* () {
const error = yield* LLMClient.generate(request).pipe(
Effect.provide(
fixedResponse(
sseEvents(
{ type: "message_start", message: { usage: { input_tokens: 5 } } },
{ type: "content_block_start", index: 0, content_block: { type: "text", text: "" } },
{ type: "content_block_delta", index: 0, delta: { type: "text_delta", text: "Hello" } },
{ type: "content_block_stop", index: 0 },
{ type: "message_delta", delta: { stop_reason: "end_turn" }, usage: { output_tokens: 1 } },
),
),
),
Effect.flip,
)
expect(error.reason).toMatchObject({
_tag: "InvalidProviderOutput",
message: "Provider stream ended without a terminal finish event",
})
}),
)
it.effect("maps thinking tokens and preserves unknown Anthropic usage fields", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(request).pipe(
Effect.provide(
fixedResponse(
sseEvents(
{
type: "message_start",
message: {
usage: {
input_tokens: 5,
cache_read_input_tokens: 2,
service_tier: "standard",
cache_creation: { ephemeral_5m_input_tokens: 1 },
server_tool_use: { web_search_requests: 1, start_counter: 2 },
output_tokens_details: { thinking_tokens: 3, start_detail: "preserved" },
},
},
},
{
type: "message_delta",
delta: { stop_reason: "end_turn" },
usage: {
output_tokens: 8,
server_tool_use: { web_search_requests: 2, terminal_counter: 3 },
output_tokens_details: { terminal_detail: "preserved" },
future_terminal: { requests: 4 },
},
},
{ type: "message_stop" },
),
),
),
)
expect(response.usage).toMatchObject({
inputTokens: 7,
outputTokens: 8,
reasoningTokens: 3,
totalTokens: 15,
providerMetadata: {
anthropic: {
input_tokens: 5,
cache_read_input_tokens: 2,
service_tier: "standard",
cache_creation: { ephemeral_5m_input_tokens: 1 },
server_tool_use: { web_search_requests: 2, start_counter: 2, terminal_counter: 3 },
output_tokens: 8,
output_tokens_details: {
thinking_tokens: 3,
start_detail: "preserved",
terminal_detail: "preserved",
},
future_terminal: { requests: 4 },
},
},
})
}),
)
it.effect("round-trips omitted thinking carried only by a signature delta", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(request).pipe(
Effect.provide(
fixedResponse(
sseEvents(
{ type: "message_start", message: { usage: { input_tokens: 5 } } },
{
type: "content_block_start",
index: 0,
content_block: { type: "thinking", thinking: "", signature: "" },
},
{ type: "content_block_delta", index: 0, delta: { type: "signature_delta", signature: "sig_1" } },
{ type: "content_block_stop", index: 0 },
{ type: "message_delta", delta: { stop_reason: "end_turn" }, usage: { output_tokens: 1 } },
{ type: "message_stop" },
),
),
),
)
expect(response.message.content).toEqual([
{ type: "reasoning", text: "", providerMetadata: { anthropic: { signature: "sig_1" } } },
])
const prepared = yield* LLMClient.prepare<AnthropicMessages.AnthropicMessagesBody>(
LLM.request({ model, messages: [response.message], cache: "none" }),
)
expect(prepared.body.messages).toEqual([
{ role: "assistant", content: [{ type: "thinking", thinking: "", signature: "sig_1" }] },
])
}),
)
it.effect("retains a thinking signature supplied in content_block_start", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(request).pipe(
Effect.provide(
fixedResponse(
sseEvents(
{ type: "message_start", message: { usage: { input_tokens: 5 } } },
{
type: "content_block_start",
index: 0,
content_block: { type: "thinking", thinking: "", signature: "sig_1" },
},
{ type: "content_block_stop", index: 0 },
{ type: "message_delta", delta: { stop_reason: "end_turn" }, usage: { output_tokens: 1 } },
{ type: "message_stop" },
),
),
),
)
expect(response.message.content).toEqual([
{ type: "reasoning", text: "", providerMetadata: { anthropic: { signature: "sig_1" } } },
])
expect(response.events.find((event) => event.type === "reasoning-end")).toMatchObject({
providerMetadata: { anthropic: { signature: "sig_1" } },
})
}),
)
it.effect("retains complete tool input from content_block_start", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(request).pipe(
Effect.provide(
fixedResponse(
sseEvents(
{ type: "message_start", message: { usage: { input_tokens: 5 } } },
{
type: "content_block_start",
index: 0,
content_block: { type: "tool_use", id: "call_1", name: "lookup", input: { query: "weather" } },
},
{ type: "content_block_stop", index: 0 },
{ type: "message_delta", delta: { stop_reason: "tool_use" }, usage: { output_tokens: 1 } },
{ type: "message_stop" },
),
),
),
)
expect(response.toolCalls).toMatchObject([
{ id: "call_1", name: "lookup", input: { query: "weather" } },
])
}),
)
it.effect("retains empty text blocks", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(request).pipe(
Effect.provide(
fixedResponse(
sseEvents(
{ type: "message_start", message: { usage: { input_tokens: 5 } } },
{ type: "content_block_start", index: 0, content_block: { type: "text", text: "" } },
{ type: "content_block_stop", index: 0 },
{ type: "message_delta", delta: { stop_reason: "end_turn" }, usage: { output_tokens: 1 } },
{ type: "message_stop" },
),
),
),
)
expect(response.message.content).toEqual([{ type: "text", text: "" }])
}),
)
it.effect("parses redacted thinking into empty reasoning with redactedData metadata", () =>
Effect.gen(function* () {
const body = sseEvents(
{ type: "message_start", message: { usage: { input_tokens: 5 } } },
{ type: "content_block_start", index: 0, content_block: { type: "redacted_thinking", data: "opaque_1" } },
{ type: "content_block_stop", index: 0 },
{ type: "content_block_start", index: 1, content_block: { type: "text", text: "" } },
{ type: "content_block_delta", index: 1, delta: { type: "text_delta", text: "Hello" } },
{ type: "content_block_stop", index: 1 },
{ type: "message_delta", delta: { stop_reason: "end_turn" }, usage: { output_tokens: 2 } },
{ type: "message_stop" },
)
const response = yield* LLMClient.generate(request).pipe(Effect.provide(fixedResponse(body)))
expect(response.events.find((event) => event.type === "reasoning-start")).toMatchObject({
providerMetadata: { anthropic: { redactedData: "opaque_1" } },
})
expect(response.message.content).toEqual([
{ type: "reasoning", text: "", providerMetadata: { anthropic: { redactedData: "opaque_1" } } },
{ type: "text", text: "Hello" },
])
}),
)
it.effect("round-trips streamed redacted thinking with tool use into a continuation request", () =>
Effect.gen(function* () {
// Anthropic types `redacted_thinking.data` as an opaque string. Its
// contents are provider-owned and must be replayed without inspection.
const redactedData = "cmVkYWN0ZWQtdGhpbmtpbmc="
const response = yield* LLMClient.generate(
LLMRequest.update(request, {
tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
}),
).pipe(
Effect.provide(
fixedResponse(
sseEvents(
{ type: "message_start", message: { usage: { input_tokens: 5 } } },
{
type: "content_block_start",
index: 0,
content_block: { type: "redacted_thinking", data: redactedData },
},
{ type: "content_block_stop", index: 0 },
{
type: "content_block_start",
index: 1,
content_block: { type: "tool_use", id: "call_1", name: "lookup" },
},
{
type: "content_block_delta",
index: 1,
delta: { type: "input_json_delta", partial_json: '{"query":"weather"}' },
},
{ type: "content_block_stop", index: 1 },
{ type: "message_delta", delta: { stop_reason: "tool_use" }, usage: { output_tokens: 1 } },
{ type: "message_stop" },
),
),
),
)
const prepared = yield* LLMClient.prepare<AnthropicMessages.AnthropicMessagesBody>(
LLM.request({
model,
messages: [
Message.user("Say hello."),
response.message,
Message.tool({ id: "call_1", name: "lookup", result: "sunny", resultType: "text" }),
],
tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
cache: "none",
}),
)
expect(prepared.body.messages).toEqual([
{ role: "user", content: [{ type: "text", text: "Say hello." }] },
{
role: "assistant",
content: [
{ type: "redacted_thinking", data: redactedData },
{ type: "tool_use", id: "call_1", name: "lookup", input: { query: "weather" } },
],
},
{
role: "user",
content: [
{
type: "tool_result",
tool_use_id: "call_1",
content: "sunny",
is_error: undefined,
cache_control: undefined,
},
],
},
])
}),
)
it.effect("maps context-window truncation to length", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(request).pipe(
Effect.provide(
fixedResponse(
sseEvents(
{ type: "message_start", message: { usage: { input_tokens: 5 } } },
{
type: "message_delta",
delta: { stop_reason: "model_context_window_exceeded" },
usage: { output_tokens: 1 },
},
{ type: "message_stop" },
),
),
),
)
expect(response.finishReason).toEqual({ normalized: "length", raw: "model_context_window_exceeded" })
}),
)
it.effect("preserves pause_turn while normalizing it to stop", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(request).pipe(
Effect.provide(
fixedResponse(
sseEvents(
{ type: "message_start", message: { usage: { input_tokens: 5 } } },
{ type: "message_delta", delta: { stop_reason: "pause_turn" }, usage: { output_tokens: 1 } },
{ type: "message_stop" },
),
),
),
)
expect(response.finishReason).toEqual({ normalized: "stop", raw: "pause_turn" })
}),
)
it.effect("assembles streamed tool call input", () =>
Effect.gen(function* () {
const body = sseEvents(
@@ -435,10 +860,11 @@ describe("Anthropic Messages route", () => {
{ type: "content_block_delta", index: 0, delta: { type: "input_json_delta", partial_json: ':"weather"}' } },
{ type: "content_block_stop", index: 0 },
{ type: "message_delta", delta: { stop_reason: "tool_use" }, usage: { output_tokens: 1 } },
{ type: "message_stop" },
)
const response = yield* LLMClient.generate(
LLM.updateRequest(request, {
tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
LLMRequest.update(request, {
tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
}),
).pipe(Effect.provide(fixedResponse(body)))
const usage = new Usage({
@@ -475,10 +901,16 @@ describe("Anthropic Messages route", () => {
providerExecuted: undefined,
providerMetadata: undefined,
},
{ type: "step-finish", index: 0, reason: "tool-calls", usage, providerMetadata: undefined },
{
type: "step-finish",
index: 0,
reason: { normalized: "tool-calls", raw: "tool_use" },
usage,
providerMetadata: undefined,
},
{
type: "finish",
reason: "tool-calls",
reason: { normalized: "tool-calls", raw: "tool_use" },
providerMetadata: undefined,
usage,
},
@@ -614,10 +1046,13 @@ describe("Anthropic Messages route", () => {
{ type: "content_block_delta", index: 2, delta: { type: "text_delta", text: "Found it." } },
{ type: "content_block_stop", index: 2 },
{ type: "message_delta", delta: { stop_reason: "end_turn" }, usage: { output_tokens: 8 } },
{ type: "message_stop" },
)
const response = yield* LLMClient.generate(
LLM.updateRequest(request, {
tools: [{ name: "web_search", description: "Web search", inputSchema: { type: "object" } }],
LLMRequest.update(request, {
tools: [
ToolDefinition.make({ name: "web_search", description: "Web search", inputSchema: { type: "object" } }),
],
}),
).pipe(Effect.provide(fixedResponse(body)))
@@ -636,10 +1071,20 @@ describe("Anthropic Messages route", () => {
name: "web_search",
result: { type: "json", value: [{ type: "web_search_result", url: "https://example.com", title: "Example" }] },
providerExecuted: true,
providerMetadata: { anthropic: { blockType: "web_search_tool_result" } },
// The complete payload rides in provider metadata as irreducible replay
// state for later stateless requests.
providerMetadata: {
anthropic: {
blockType: "web_search_tool_result",
result: [{ type: "web_search_result", url: "https://example.com", title: "Example" }],
},
},
})
expect(response.text).toBe("Found it.")
expect(response.events.at(-1)).toMatchObject({ type: "finish", reason: "stop" })
expect(response.events.at(-1)).toMatchObject({
type: "finish",
reason: { normalized: "stop", raw: "end_turn" },
})
}),
)
@@ -665,10 +1110,13 @@ describe("Anthropic Messages route", () => {
},
{ type: "content_block_stop", index: 1 },
{ type: "message_delta", delta: { stop_reason: "end_turn" }, usage: { output_tokens: 1 } },
{ type: "message_stop" },
)
const response = yield* LLMClient.generate(
LLM.updateRequest(request, {
tools: [{ name: "web_search", description: "Web search", inputSchema: { type: "object" } }],
LLMRequest.update(request, {
tools: [
ToolDefinition.make({ name: "web_search", description: "Web search", inputSchema: { type: "object" } }),
],
}),
).pipe(Effect.provide(fixedResponse(body)))
@@ -784,7 +1232,10 @@ describe("Anthropic Messages route", () => {
content: [
{ type: "text", text: "What is in this image?" },
{ type: "image", source: { type: "base64", media_type: "image/png", data: "AAECAw==" } },
{ type: "document", source: { type: "base64", media_type: "application/pdf", data: "JVBERi0xLjQ=" } },
{
type: "document",
source: { type: "base64", media_type: "application/pdf", data: "JVBERi0xLjQ=" },
},
],
},
],
@@ -2,7 +2,16 @@ import { EventStreamCodec } from "@smithy/eventstream-codec"
import { fromUtf8, toUtf8 } from "@smithy/util-utf8"
import { describe, expect } from "bun:test"
import { Effect } from "effect"
import { CacheHint, LLM, Message, ToolCallPart, ToolChoice } from "../../src"
import {
CacheHint,
GenerationOptions,
LLM,
LLMRequest,
Message,
ToolCallPart,
ToolChoice,
ToolDefinition,
} from "../../src"
import { LLMClient } from "../../src/route"
import { AmazonBedrock } from "../../src/providers"
import * as BedrockConverse from "../../src/protocols/bedrock-converse"
@@ -34,6 +43,26 @@ const eventFrame = (type: string, payload: object) =>
body: utf8Encoder.encode(JSON.stringify(payload)),
})
const exceptionFrame = (type: string, payload: object) =>
codec.encode({
headers: {
":message-type": { type: "string", value: "exception" },
":exception-type": { type: "string", value: type },
":content-type": { type: "string", value: "application/json" },
},
body: utf8Encoder.encode(JSON.stringify(payload)),
})
const errorFrame = (code: string, message: string) =>
codec.encode({
headers: {
":message-type": { type: "string", value: "error" },
":error-code": { type: "string", value: code },
":error-message": { type: "string", value: message },
},
body: new Uint8Array(),
})
const concat = (frames: ReadonlyArray<Uint8Array>) => {
const total = frames.reduce((sum, frame) => sum + frame.length, 0)
const out = new Uint8Array(total)
@@ -86,7 +115,9 @@ describe("Bedrock Converse route", () => {
it.effect("passes topK through additionalModelRequestFields as top_k", () =>
Effect.gen(function* () {
const prepared = yield* LLMClient.prepare<BedrockConverse.BedrockConverseBody>(
LLM.updateRequest(baseRequest, { generation: { maxTokens: 64, temperature: 0, topK: 40 } }),
LLMRequest.update(baseRequest, {
generation: GenerationOptions.make({ maxTokens: 64, temperature: 0, topK: 40 }),
}),
)
// Converse's inferenceConfig has no topK; Anthropic/Nova read it from
@@ -123,13 +154,13 @@ describe("Bedrock Converse route", () => {
it.effect("prepares tool config with toolSpec and toolChoice", () =>
Effect.gen(function* () {
const prepared = yield* LLMClient.prepare(
LLM.updateRequest(baseRequest, {
LLMRequest.update(baseRequest, {
tools: [
{
ToolDefinition.make({
name: "lookup",
description: "Lookup data",
inputSchema: { type: "object", properties: { query: { type: "string" } }, required: ["query"] },
},
}),
],
toolChoice: ToolChoice.make({ type: "required" }),
}),
@@ -154,6 +185,36 @@ describe("Bedrock Converse route", () => {
}),
)
it.effect("keeps tools and omits the unsupported choice when tool choice is none", () =>
Effect.gen(function* () {
const prepared = yield* LLMClient.prepare(
LLMRequest.update(baseRequest, {
tools: [
ToolDefinition.make({
name: "lookup",
description: "Lookup data",
inputSchema: { type: "object", properties: { query: { type: "string" } } },
}),
],
toolChoice: ToolChoice.make({ type: "none" }),
}),
)
expect(prepared.body.toolConfig).toMatchObject({
tools: [
{
toolSpec: {
name: "lookup",
description: "Lookup data",
inputSchema: { json: { type: "object", properties: { query: { type: "string" } } } },
},
},
],
})
expect(prepared.body.toolConfig?.toolChoice).toBeUndefined()
}),
)
it.effect("lowers assistant tool-call + tool-result message history", () =>
Effect.gen(function* () {
const prepared = yield* LLMClient.prepare(
@@ -260,7 +321,10 @@ describe("Bedrock Converse route", () => {
// `metadata` (carries usage). We consolidate them into a single
// terminal `finish` event with both.
expect(finishes).toHaveLength(1)
expect(finishes[0]).toMatchObject({ type: "finish", reason: "stop" })
expect(finishes[0]).toMatchObject({
type: "finish",
reason: { normalized: "stop", raw: "end_turn" },
})
expect(response.usage).toMatchObject({
inputTokens: 5,
outputTokens: 2,
@@ -269,6 +333,23 @@ describe("Bedrock Converse route", () => {
}),
)
it.effect("maps truncation and malformed output stop reasons", () =>
Effect.gen(function* () {
const reasons = [
["model_context_window_exceeded", "length"],
["malformed_model_output", "error"],
["malformed_tool_use", "error"],
] as const
for (const [raw, normalized] of reasons) {
const response = yield* LLMClient.generate(baseRequest).pipe(
Effect.provide(fixedBytes(eventStreamBody(["messageStop", { stopReason: raw }]))),
)
expect(response.finishReason).toEqual({ normalized, raw })
}
}),
)
it.effect("adds cache reads and writes to Bedrock input usage", () =>
Effect.gen(function* () {
const body = eventStreamBody(
@@ -302,6 +383,19 @@ describe("Bedrock Converse route", () => {
}),
)
it.effect("preserves usage across later metadata events without usage", () =>
Effect.gen(function* () {
const body = eventStreamBody(
["messageStop", { stopReason: "end_turn" }],
["metadata", { usage: { inputTokens: 5, outputTokens: 2, totalTokens: 7 } }],
["metadata", { metrics: { latencyMs: 100 } }],
)
const response = yield* LLMClient.generate(baseRequest).pipe(Effect.provide(fixedBytes(body)))
expect(response.usage).toMatchObject({ inputTokens: 5, outputTokens: 2, totalTokens: 7 })
}),
)
it.effect("assembles streamed tool call input", () =>
Effect.gen(function* () {
const body = eventStreamBody(
@@ -319,8 +413,8 @@ describe("Bedrock Converse route", () => {
["messageStop", { stopReason: "tool_use" }],
)
const response = yield* LLMClient.generate(
LLM.updateRequest(baseRequest, {
tools: [{ name: "lookup", description: "Lookup", inputSchema: { type: "object" } }],
LLMRequest.update(baseRequest, {
tools: [ToolDefinition.make({ name: "lookup", description: "Lookup", inputSchema: { type: "object" } })],
}),
).pipe(Effect.provide(fixedBytes(body)))
@@ -332,7 +426,10 @@ describe("Bedrock Converse route", () => {
{ type: "tool-input-delta", id: "tool_1", name: "lookup", text: '{"query"' },
{ type: "tool-input-delta", id: "tool_1", name: "lookup", text: ':"weather"}' },
])
expect(response.events.at(-1)).toMatchObject({ type: "finish", reason: "tool-calls" })
expect(response.events.at(-1)).toMatchObject({
type: "finish",
reason: { normalized: "tool-calls", raw: "tool_use" },
})
}),
)
@@ -358,7 +455,7 @@ describe("Bedrock Converse route", () => {
name: "lookup",
raw: '{"query":"partial',
})
expect(response.finishReason).toBe("tool-calls")
expect(response.finishReason).toEqual({ normalized: "tool-calls", raw: "end_turn" })
}),
)
@@ -414,12 +511,170 @@ describe("Bedrock Converse route", () => {
}),
)
it.effect("classifies throttlingException as a rate limit", () =>
it.effect("preserves reasoning signatures when contentBlockStop is missing", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(baseRequest).pipe(
Effect.provide(
fixedBytes(
eventStreamBody(
["messageStart", { role: "assistant" }],
[
"contentBlockDelta",
{ contentBlockIndex: 0, delta: { reasoningContent: { text: "Let me think." } } },
],
[
"contentBlockDelta",
{ contentBlockIndex: 0, delta: { reasoningContent: { signature: "sig_1" } } },
],
["messageStop", { stopReason: "end_turn" }],
),
),
),
)
expect(response.events.find((event) => event.type === "reasoning-delta" && event.text === "")).toEqual({
type: "reasoning-delta",
id: "reasoning-0",
text: "",
providerMetadata: { bedrock: { signature: "sig_1" } },
})
expect(response.message.content).toEqual([
{
type: "reasoning",
text: "Let me think.",
providerMetadata: { bedrock: { signature: "sig_1" } },
},
])
const prepared = yield* LLMClient.prepare<BedrockConverse.BedrockConverseBody>(
LLM.request({ model, messages: [response.message], cache: "none" }),
)
expect(prepared.body.messages).toEqual([
{
role: "assistant",
content: [{ reasoningContent: { reasoningText: { text: "Let me think.", signature: "sig_1" } } }],
},
])
}),
)
it.effect("preserves signature-only reasoning blocks", () =>
Effect.gen(function* () {
const body = eventStreamBody(
["messageStart", { role: "assistant" }],
["throttlingException", { message: "Slow down" }],
[
"contentBlockDelta",
{ contentBlockIndex: 0, delta: { reasoningContent: { signature: "sig_1" } } },
],
["contentBlockStop", { contentBlockIndex: 0 }],
["messageStop", { stopReason: "end_turn" }],
)
const response = yield* LLMClient.generate(baseRequest).pipe(Effect.provide(fixedBytes(body)))
expect(response.message.content).toEqual([
{ type: "reasoning", text: "", providerMetadata: { bedrock: { signature: "sig_1" } } },
])
}),
)
it.effect("accepts Vercel-compatible redacted reasoning data deltas", () =>
Effect.gen(function* () {
const redactedData = "cmVkYWN0ZWQtdGhpbmtpbmc="
const body = eventStreamBody(
["messageStart", { role: "assistant" }],
["contentBlockDelta", { contentBlockIndex: 0, delta: { reasoningContent: { data: redactedData } } }],
["contentBlockStop", { contentBlockIndex: 0 }],
["messageStop", { stopReason: "end_turn" }],
)
const response = yield* LLMClient.generate(baseRequest).pipe(Effect.provide(fixedBytes(body)))
expect(response.events.find((event) => event.type === "reasoning-delta" && event.text === "")).toEqual({
type: "reasoning-delta",
id: "reasoning-0",
text: "",
providerMetadata: { bedrock: { redactedData } },
})
expect(response.message.content).toEqual([
{ type: "reasoning", text: "", providerMetadata: { bedrock: { redactedData } } },
])
}),
)
it.effect("round-trips streamed redacted reasoning with tool use into a continuation request", () =>
Effect.gen(function* () {
// Bedrock represents redactedContent blobs as base64 strings on its JSON
// wire. The provider owns the payload and requires byte-exact replay.
const redactedData = "cmVkYWN0ZWQtdGhpbmtpbmc="
const response = yield* LLMClient.generate(
LLMRequest.update(baseRequest, {
tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
}),
).pipe(
Effect.provide(
fixedBytes(
eventStreamBody(
["messageStart", { role: "assistant" }],
[
"contentBlockDelta",
{ contentBlockIndex: 0, delta: { reasoningContent: { redactedContent: redactedData } } },
],
["contentBlockStop", { contentBlockIndex: 0 }],
[
"contentBlockStart",
{
contentBlockIndex: 1,
start: { toolUse: { toolUseId: "tool_1", name: "lookup" } },
},
],
["contentBlockDelta", { contentBlockIndex: 1, delta: { toolUse: { input: '{"query":"weather"}' } } }],
["contentBlockStop", { contentBlockIndex: 1 }],
["messageStop", { stopReason: "tool_use" }],
),
),
),
)
expect(response.events.find((event) => event.type === "reasoning-delta" && event.text === "")).toEqual({
type: "reasoning-delta",
id: "reasoning-0",
text: "",
providerMetadata: { bedrock: { redactedData } },
})
const prepared = yield* LLMClient.prepare<BedrockConverse.BedrockConverseBody>(
LLM.request({
model,
messages: [
Message.user("Say hello."),
response.message,
Message.tool({ id: "tool_1", name: "lookup", result: "sunny", resultType: "text" }),
],
tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
cache: "none",
}),
)
expect(prepared.body.messages).toEqual([
{ role: "user", content: [{ text: "Say hello." }] },
{
role: "assistant",
content: [
{ reasoningContent: { redactedContent: redactedData } },
{ toolUse: { toolUseId: "tool_1", name: "lookup", input: { query: "weather" } } },
],
},
{
role: "user",
content: [{ toolResult: { toolUseId: "tool_1", content: [{ text: "sunny" }], status: "success" } }],
},
])
}),
)
it.effect("classifies throttlingException as a rate limit", () =>
Effect.gen(function* () {
const body = concat([
eventFrame("messageStart", { role: "assistant" }),
exceptionFrame("throttlingException", { message: "Slow down" }),
])
const error = yield* LLMClient.generate(baseRequest).pipe(Effect.provide(fixedBytes(body)), Effect.flip)
expect(error.reason).toMatchObject({ _tag: "RateLimit", message: "Slow down" })
@@ -430,7 +685,7 @@ describe("Bedrock Converse route", () => {
Effect.gen(function* () {
const error = yield* LLMClient.generate(baseRequest).pipe(
Effect.provide(
fixedBytes(eventStreamBody(["validationException", { message: "Input is too long for requested model" }])),
fixedBytes(exceptionFrame("validationException", { message: "Input is too long for requested model" })),
),
Effect.flip,
)
@@ -443,12 +698,44 @@ describe("Bedrock Converse route", () => {
}),
)
it.effect("uses originalMessage from model stream exception frames", () =>
Effect.gen(function* () {
const error = yield* LLMClient.generate(baseRequest).pipe(
Effect.provide(
fixedBytes(
exceptionFrame("modelStreamErrorException", {
originalMessage: "Upstream model failed",
originalStatusCode: 500,
}),
),
),
Effect.flip,
)
expect(error.reason).toMatchObject({ _tag: "ProviderInternal", message: "Upstream model failed" })
}),
)
it.effect("fails unmodeled AWS event-stream errors", () =>
Effect.gen(function* () {
const error = yield* LLMClient.generate(baseRequest).pipe(
Effect.provide(fixedBytes(errorFrame("BadStream", "Stream failed"))),
Effect.flip,
)
expect(error.reason).toMatchObject({
_tag: "InvalidProviderOutput",
message: "BadStream: Stream failed",
})
}),
)
it.effect("rejects requests with no auth path", () =>
Effect.gen(function* () {
const unsignedModel = AmazonBedrock.configure({
baseURL: "https://bedrock-runtime.test",
}).model("anthropic.claude-3-5-sonnet-20240620-v1:0")
const error = yield* LLMClient.generate(LLM.updateRequest(baseRequest, { model: unsignedModel })).pipe(
const error = yield* LLMClient.generate(LLMRequest.update(baseRequest, { model: unsignedModel })).pipe(
Effect.provide(fixedBytes(eventStreamBody(["messageStop", { stopReason: "end_turn" }]))),
Effect.flip,
)
@@ -467,7 +754,7 @@ describe("Bedrock Converse route", () => {
secretAccessKey: "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
},
}).model("anthropic.claude-3-5-sonnet-20240620-v1:0")
const prepared = yield* LLMClient.prepare(LLM.updateRequest(baseRequest, { model: signed }))
const prepared = yield* LLMClient.prepare(LLMRequest.update(baseRequest, { model: signed }))
expect(prepared.route).toBe("bedrock-converse")
expect(prepared.model).toBe(signed)
@@ -652,6 +939,7 @@ describe("Bedrock Converse route", () => {
const prepared = yield* LLMClient.prepare<BedrockConverse.BedrockConverseBody>(
LLM.request({
model,
cache: "none",
messages: [
Message.assistant([ToolCallPart.make({ id: "call_1", name: "read", input: { path: "report.pdf" } })]),
Message.tool({
+88 -18
View File
@@ -1,6 +1,6 @@
import { describe, expect } from "bun:test"
import { Effect } from "effect"
import { LLM, LLMError, Message, ToolCallPart, Usage } from "../../src"
import { LLM, LLMError, LLMRequest, Message, ToolCallPart, ToolDefinition, Usage } from "../../src"
import { Auth, LLMClient } from "../../src/route"
import * as Gemini from "../../src/protocols/gemini"
import { ProviderShared } from "../../src/protocols/shared"
@@ -36,6 +36,27 @@ describe("Gemini route", () => {
}),
)
it.effect("normalizes Gemini thinking options", () =>
Effect.gen(function* () {
const prepared = yield* LLMClient.prepare<Gemini.GeminiBody>(
LLMRequest.update(request, {
providerOptions: { gemini: { thinkingConfig: { thinkingBudget: 0, includeThoughts: false } } },
}),
)
const filtered = yield* LLMClient.prepare<Gemini.GeminiBody>(
LLMRequest.update(request, {
providerOptions: { gemini: { thinkingConfig: { thinkingBudget: "invalid", includeThoughts: false } } },
}),
)
expect(prepared.body.generationConfig?.thinkingConfig).toEqual({
thinkingBudget: 0,
includeThoughts: false,
})
expect(filtered.body.generationConfig?.thinkingConfig).toEqual({ includeThoughts: false })
}),
)
it.effect("lowers chronological system updates to wrapped user text in order", () =>
Effect.gen(function* () {
const prepared = yield* LLMClient.prepare<Gemini.GeminiBody>(
@@ -233,20 +254,22 @@ describe("Gemini route", () => {
}),
)
it.effect("omits tools when tool choice is none", () =>
it.effect("keeps tools and sends function calling mode NONE", () =>
Effect.gen(function* () {
const prepared = yield* LLMClient.prepare(
LLM.request({
id: "req_no_tools",
id: "req_tool_choice_none",
model,
prompt: "Say hello.",
tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
toolChoice: { type: "none" },
}),
)
expect(prepared.body).toEqual({
expect(prepared.body).toMatchObject({
contents: [{ role: "user", parts: [{ text: "Say hello." }] }],
tools: [{ functionDeclarations: [{ name: "lookup", description: "Lookup data" }] }],
toolConfig: { functionCallingConfig: { mode: "NONE" } },
})
}),
)
@@ -371,10 +394,16 @@ describe("Gemini route", () => {
{ type: "text-delta", id: "text-0", text: "Hello" },
{ type: "text-delta", id: "text-0", text: "!" },
{ type: "text-end", id: "text-0" },
{ type: "step-finish", index: 0, reason: "stop", usage, providerMetadata: undefined },
{
type: "step-finish",
index: 0,
reason: { normalized: "stop", raw: "STOP" },
usage,
providerMetadata: undefined,
},
{
type: "finish",
reason: "stop",
reason: { normalized: "stop", raw: "STOP" },
usage,
},
])
@@ -402,8 +431,8 @@ describe("Gemini route", () => {
],
})
const response = yield* LLMClient.generate(
LLM.updateRequest(request, {
tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
LLMRequest.update(request, {
tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
}),
).pipe(Effect.provide(fixedResponse(body)))
const reasoning = response.events.find((event) => event.type === "reasoning-start")
@@ -493,8 +522,8 @@ describe("Gemini route", () => {
usageMetadata: { promptTokenCount: 5, candidatesTokenCount: 1 },
})
const response = yield* LLMClient.generate(
LLM.updateRequest(request, {
tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
LLMRequest.update(request, {
tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
}),
).pipe(Effect.provide(fixedResponse(body)))
const usage = new Usage({
@@ -527,10 +556,16 @@ describe("Gemini route", () => {
providerExecuted: undefined,
providerMetadata: undefined,
},
{ type: "step-finish", index: 0, reason: "tool-calls", usage, providerMetadata: undefined },
{
type: "step-finish",
index: 0,
reason: { normalized: "tool-calls", raw: "STOP" },
usage,
providerMetadata: undefined,
},
{
type: "finish",
reason: "tool-calls",
reason: { normalized: "tool-calls", raw: "STOP" },
usage,
},
])
@@ -554,8 +589,8 @@ describe("Gemini route", () => {
],
})
const response = yield* LLMClient.generate(
LLM.updateRequest(request, {
tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
LLMRequest.update(request, {
tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
}),
).pipe(Effect.provide(fixedResponse(body)))
@@ -569,7 +604,10 @@ describe("Gemini route", () => {
},
{ type: "tool-call", id: "tool_1", name: "lookup", input: { query: "news" } },
])
expect(response.events.at(-1)).toMatchObject({ type: "finish", reason: "tool-calls" })
expect(response.events.at(-1)).toMatchObject({
type: "finish",
reason: { normalized: "tool-calls", raw: "STOP" },
})
}),
)
@@ -589,9 +627,41 @@ describe("Gemini route", () => {
)
expect(length.events.map((event) => event.type)).toEqual(["step-start", "step-finish", "finish"])
expect(length.events.at(-1)).toMatchObject({ type: "finish", reason: "length" })
expect(length.events.at(-1)).toMatchObject({
type: "finish",
reason: { normalized: "length", raw: "MAX_TOKENS" },
})
expect(filtered.events.map((event) => event.type)).toEqual(["step-start", "step-finish", "finish"])
expect(filtered.events.at(-1)).toMatchObject({ type: "finish", reason: "content-filter" })
expect(filtered.events.at(-1)).toMatchObject({
type: "finish",
reason: { normalized: "content-filter", raw: "SAFETY" },
})
}),
)
it.effect("maps current blocking and invalid-output finish reasons", () =>
Effect.gen(function* () {
const reasons = [
["MODEL_ARMOR", "content-filter"],
["IMAGE_PROHIBITED_CONTENT", "content-filter"],
["IMAGE_RECITATION", "content-filter"],
["LANGUAGE", "content-filter"],
["UNEXPECTED_TOOL_CALL", "error"],
["NO_IMAGE", "error"],
["IMAGE_OTHER", "unknown"],
["TOO_MANY_TOOL_CALLS", "error"],
["MISSING_THOUGHT_SIGNATURE", "error"],
["MALFORMED_RESPONSE", "error"],
] as const
for (const [raw, normalized] of reasons) {
const response = yield* LLMClient.generate(request).pipe(
Effect.provide(
fixedResponse(sseEvents({ candidates: [{ content: { role: "model", parts: [] }, finishReason: raw }] })),
),
)
expect(response.finishReason).toEqual({ normalized, raw })
}
}),
)
+51 -29
View File
@@ -1,7 +1,18 @@
import { describe, expect } from "bun:test"
import { Effect, Schema, Stream } from "effect"
import { HttpClientRequest } from "effect/unstable/http"
import { LLM, LLMError, LLMEvent, Message, Model, ToolCallPart, Usage } from "../../src"
import {
HttpOptions,
LLM,
LLMError,
LLMEvent,
LLMRequest,
Message,
Model,
ToolCallPart,
ToolDefinition,
Usage,
} from "../../src"
import * as Azure from "../../src/providers/azure"
import * as OpenAI from "../../src/providers/openai"
import * as OpenAIChat from "../../src/protocols/openai-chat"
@@ -162,7 +173,7 @@ describe("OpenAI Chat route", () => {
it.effect("adds native query params to the Chat Completions URL", () =>
LLMClient.generate(
LLM.updateRequest(request, {
LLMRequest.update(request, {
model: Model.update(model, { route: model.route.with({ endpoint: { query: { "api-version": "v1" } } }) }),
}),
).pipe(
@@ -182,7 +193,7 @@ describe("OpenAI Chat route", () => {
it.effect("uses Azure api-key header for static OpenAI Chat keys", () =>
LLMClient.generate(
LLM.updateRequest(request, {
LLMRequest.update(request, {
model: Azure.configure({
baseURL: "https://opencode-test.openai.azure.com/openai/v1/",
apiKey: "azure-key",
@@ -208,15 +219,15 @@ describe("OpenAI Chat route", () => {
it.effect("applies serializable HTTP overlays after payload lowering", () =>
LLMClient.generate(
LLM.updateRequest(request, {
LLMRequest.update(request, {
model: model.route
.with({ auth: Auth.bearer("fresh-key"), headers: { authorization: "Bearer stale" } })
.model({ id: model.id }),
http: {
http: HttpOptions.make({
body: { metadata: { source: "test" } },
headers: { authorization: "Bearer request", "x-custom": "yes" },
query: { debug: "1" },
},
}),
}),
).pipe(
Effect.provide(
@@ -539,7 +550,7 @@ describe("OpenAI Chat route", () => {
prompt_tokens: 5,
completion_tokens: 2,
total_tokens: 7,
prompt_tokens_details: { cached_tokens: 1 },
prompt_tokens_details: { cached_tokens: 1, cache_write_tokens: 2 },
completion_tokens_details: { reasoning_tokens: 0 },
}),
)
@@ -547,8 +558,9 @@ describe("OpenAI Chat route", () => {
const usage = new Usage({
inputTokens: 5,
outputTokens: 2,
nonCachedInputTokens: 4,
nonCachedInputTokens: 2,
cacheReadInputTokens: 1,
cacheWriteInputTokens: 2,
reasoningTokens: 0,
totalTokens: 7,
providerMetadata: {
@@ -556,7 +568,7 @@ describe("OpenAI Chat route", () => {
prompt_tokens: 5,
completion_tokens: 2,
total_tokens: 7,
prompt_tokens_details: { cached_tokens: 1 },
prompt_tokens_details: { cached_tokens: 1, cache_write_tokens: 2 },
completion_tokens_details: { reasoning_tokens: 0 },
},
},
@@ -569,10 +581,16 @@ describe("OpenAI Chat route", () => {
{ type: "text-delta", id: "text-0", text: "Hello" },
{ type: "text-delta", id: "text-0", text: "!" },
{ type: "text-end", id: "text-0" },
{ type: "step-finish", index: 0, reason: "stop", usage, providerMetadata: undefined },
{
type: "step-finish",
index: 0,
reason: { normalized: "stop", raw: "stop" },
usage,
providerMetadata: undefined,
},
{
type: "finish",
reason: "stop",
reason: { normalized: "stop", raw: "stop" },
usage,
},
])
@@ -612,7 +630,7 @@ describe("OpenAI Chat route", () => {
it.effect("parses and replays a configured custom reasoning field", () =>
Effect.gen(function* () {
const custom = Model.update(model, { compatibility: { reasoningField: "vendor_reasoning" } })
const response = yield* LLMClient.generate(LLM.updateRequest(request, { model: custom })).pipe(
const response = yield* LLMClient.generate(LLMRequest.update(request, { model: custom })).pipe(
Effect.provide(
fixedResponse(
sseEvents(
@@ -632,9 +650,7 @@ describe("OpenAI Chat route", () => {
const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
LLM.request({ model: custom, messages: [response.message] }),
)
expect(replay.body.messages).toEqual([
{ role: "assistant", content: "Hello", vendor_reasoning: "thinking" },
])
expect(replay.body.messages).toEqual([{ role: "assistant", content: "Hello", vendor_reasoning: "thinking" }])
}),
)
@@ -645,8 +661,8 @@ describe("OpenAI Chat route", () => {
{ type: "reasoning.encrypted", data: "opaque", format: "anthropic-claude-v1", index: 1 },
]
const response = yield* LLMClient.generate(
LLM.updateRequest(request, {
tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
LLMRequest.update(request, {
tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
}),
).pipe(
Effect.provide(
@@ -1018,8 +1034,8 @@ describe("OpenAI Chat route", () => {
deltaChunk({}, "tool_calls"),
)
const response = yield* LLMClient.generate(
LLM.updateRequest(request, {
tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
LLMRequest.update(request, {
tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
}),
).pipe(Effect.provide(fixedResponse(body)))
@@ -1037,8 +1053,14 @@ describe("OpenAI Chat route", () => {
providerExecuted: undefined,
providerMetadata: undefined,
},
{ type: "step-finish", index: 0, reason: "tool-calls", usage: undefined, providerMetadata: undefined },
{ type: "finish", reason: "tool-calls", usage: undefined },
{
type: "step-finish",
index: 0,
reason: { normalized: "tool-calls", raw: "tool_calls" },
usage: undefined,
providerMetadata: undefined,
},
{ type: "finish", reason: { normalized: "tool-calls", raw: "tool_calls" }, usage: undefined },
])
}),
)
@@ -1055,8 +1077,8 @@ describe("OpenAI Chat route", () => {
deltaChunk({}, "tool_calls"),
)
const response = yield* LLMClient.generate(
LLM.updateRequest(request, {
tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
LLMRequest.update(request, {
tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
}),
).pipe(Effect.provide(fixedResponse(body)))
@@ -1077,8 +1099,8 @@ describe("OpenAI Chat route", () => {
deltaChunk({}, "tool_calls"),
)
const response = yield* LLMClient.generate(
LLM.updateRequest(request, {
tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
LLMRequest.update(request, {
tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
}),
).pipe(Effect.provide(fixedResponse(body)))
@@ -1095,8 +1117,8 @@ describe("OpenAI Chat route", () => {
deltaChunk({}, "tool_calls"),
)
const error = yield* LLMClient.generate(
LLM.updateRequest(request, {
tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
LLMRequest.update(request, {
tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
}),
).pipe(Effect.provide(fixedResponse(body)), Effect.flip)
@@ -1113,8 +1135,8 @@ describe("OpenAI Chat route", () => {
}),
deltaChunk({ tool_calls: [{ index: 0, function: { arguments: ':"weather"}' } }] }),
)
const input = LLM.updateRequest(request, {
tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
const input = LLMRequest.update(request, {
tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
})
const events: LLMEvent[] = []
const streamError = yield* LLMClient.stream(input).pipe(
@@ -1,7 +1,7 @@
import { describe, expect } from "bun:test"
import { Effect, Schema } from "effect"
import { HttpClientRequest } from "effect/unstable/http"
import { LLM, Message, ToolCallPart } from "../../src"
import { LLM, LLMRequest, Message, ToolCallPart, ToolChoice, ToolDefinition } from "../../src"
import { Auth, LLMClient } from "../../src/route"
import * as OpenAICompatible from "../../src/providers/openai-compatible"
import * as OpenAICompatibleChat from "../../src/protocols/openai-compatible-chat"
@@ -53,9 +53,9 @@ describe("OpenAI-compatible Chat route", () => {
it.effect("prepares generic Chat target", () =>
Effect.gen(function* () {
const prepared = yield* LLMClient.prepare(
LLM.updateRequest(request, {
tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
toolChoice: { type: "required" },
LLMRequest.update(request, {
tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
toolChoice: ToolChoice.make({ type: "required" }),
}),
)
@@ -232,7 +232,10 @@ describe("OpenAI-compatible Chat route", () => {
expect(response.text).toBe("Hello!")
expect(response.usage).toMatchObject({ inputTokens: 5, outputTokens: 2, totalTokens: 7 })
expect(response.events.at(-1)).toMatchObject({ type: "finish", reason: "stop" })
expect(response.events.at(-1)).toMatchObject({
type: "finish",
reason: { normalized: "stop", raw: "stop" },
})
}),
)
})
@@ -1,17 +1,22 @@
import { describe, expect } from "bun:test"
import { Effect } from "effect"
import { LLM } from "../../src"
import { LLM, LLMEvent, Message } from "../../src"
import { configure } from "../../src/providers/openai-compatible-responses"
import { OpenAI } from "../../src/providers"
import { OpenResponses } from "../../src/protocols/open-responses"
import { OpenAICompatibleResponses } from "../../src/protocols/openai-compatible-responses"
import { OpenAIResponses } from "../../src/protocols/openai-responses"
import { LLMClient } from "../../src/route"
import { it } from "../lib/effect"
import { fixedResponse } from "../lib/http"
import { sseEvents } from "../lib/sse"
describe("OpenAI-compatible Responses route", () => {
it.effect("reuses the OpenAI Responses protocol for a configured deployment", () =>
describe("Open Responses-compatible route", () => {
it.effect("uses the Open Responses baseline for a configured deployment", () =>
Effect.gen(function* () {
expect(OpenAICompatibleResponses.route.body).toBe(OpenAIResponses.protocol.body)
expect(OpenAICompatibleResponses.route.transport).toBe(OpenAIResponses.httpTransport)
expect(OpenAICompatibleResponses.route.body).toBe(OpenResponses.protocol.body)
expect(OpenAICompatibleResponses.route.transport).toBe(OpenResponses.httpTransport)
expect(OpenAICompatibleResponses.route.body).not.toBe(OpenAIResponses.protocol.body)
const model = configure({
apiKey: "test-key",
@@ -27,7 +32,7 @@ describe("OpenAI-compatible Responses route", () => {
)
expect(prepared.route).toBe("openai-compatible-responses")
expect(prepared.protocol).toBe("openai-responses")
expect(prepared.protocol).toBe("open-responses")
expect(prepared.model).toMatchObject({
id: "example-model",
provider: "example",
@@ -45,9 +50,92 @@ describe("OpenAI-compatible Responses route", () => {
{ role: "system", content: "You are concise." },
{ role: "user", content: [{ type: "input_text", text: "Say hello." }] },
],
store: false,
stream: true,
})
}),
)
it.effect("rejects OpenAI-native tools", () =>
Effect.gen(function* () {
const model = configure({
apiKey: "test-key",
baseURL: "https://responses.example.test/v1",
}).model("example-model")
const error = yield* LLMClient.prepare(
LLM.request({ model, prompt: "Draw.", tools: [OpenAI.imageGeneration()] }),
).pipe(Effect.flip)
expect(error.reason._tag).toBe("InvalidRequest")
expect(error.message).toContain("Open Responses does not support provider-native tool image_generation")
}),
)
it.effect("omits OpenAI-only nullable phases from the Open Responses baseline", () =>
Effect.gen(function* () {
const model = configure({
apiKey: "test-key",
baseURL: "https://responses.example.test/v1",
}).model("example-model")
const prepared = yield* LLMClient.prepare(
LLM.request({
model,
messages: [
Message.assistant({
type: "text",
text: "Unclassified.",
providerMetadata: { openresponses: { phase: null } },
}),
],
}),
)
expect(prepared.body).toMatchObject({
input: [{ role: "assistant", content: [{ type: "output_text", text: "Unclassified." }] }],
})
}),
)
it.effect("reads standard options from the Open Responses namespace", () =>
Effect.gen(function* () {
const model = configure({
apiKey: "test-key",
baseURL: "https://responses.example.test/v1",
providerOptions: { openresponses: { reasoningEffort: "low", store: true } },
}).model("example-model")
const prepared = yield* LLMClient.prepare(LLM.request({ model, prompt: "Think." }))
expect(prepared.body).toMatchObject({
reasoning: { effort: "low" },
store: true,
})
}),
)
it.effect("does not interpret OpenAI hosted-tool items", () =>
Effect.gen(function* () {
const model = configure({
apiKey: "test-key",
baseURL: "https://responses.example.test/v1",
provider: "example",
}).model("example-model")
const response = yield* LLMClient.generate(LLM.request({ model, prompt: "Search." })).pipe(
Effect.provide(
fixedResponse(
sseEvents(
{
type: "response.output_item.done",
item: { type: "web_search_call", id: "ws_1", status: "completed", action: { query: "news" } },
},
{ type: "response.completed", response: { id: "resp_1" } },
),
),
),
)
expect(response.toolCalls).toEqual([])
expect(response.events.find(LLMEvent.is.finish)).toMatchObject({
providerMetadata: { openresponses: { responseId: "resp_1" } },
})
}),
)
})
@@ -1,7 +1,18 @@
import { describe, expect } from "bun:test"
import { ConfigProvider, Effect, Layer, Stream } from "effect"
import { Headers, HttpClientRequest } from "effect/unstable/http"
import { LLM, LLMError, LLMEvent, Message, Model, ToolCallPart, ToolResultPart, Usage } from "../../src"
import {
LLM,
LLMError,
LLMEvent,
LLMRequest,
Message,
Model,
ToolCallPart,
ToolDefinition,
ToolResultPart,
Usage,
} from "../../src"
import { Auth, LLMClient, RequestExecutor, WebSocketExecutor } from "../../src/route"
import * as Azure from "../../src/providers/azure"
import * as OpenAI from "../../src/providers/openai"
@@ -96,7 +107,7 @@ describe("OpenAI Responses route", () => {
it.effect("lowers semantic service tier options", () =>
Effect.gen(function* () {
const input = LLM.updateRequest(request, { providerOptions: { openai: { serviceTier: "priority" } } })
const input = LLMRequest.update(request, { providerOptions: { openai: { serviceTier: "priority" } } })
expect(input.providerOptions).toEqual({ openai: { serviceTier: "priority" } })
const prepared = yield* LLMClient.prepare(input)
@@ -108,7 +119,7 @@ describe("OpenAI Responses route", () => {
it.effect("passes through custom OpenAI reasoning effort strings", () =>
Effect.gen(function* () {
const prepared = yield* LLMClient.prepare<OpenAIResponses.OpenAIResponsesBody>(
LLM.updateRequest(request, { providerOptions: { openai: { reasoningEffort: "experimental" } } }),
LLMRequest.update(request, { providerOptions: { openai: { reasoningEffort: "experimental" } } }),
)
expect(prepared.body.reasoning).toEqual({ effort: "experimental" })
@@ -118,7 +129,7 @@ describe("OpenAI Responses route", () => {
it.effect("omits unsupported semantic service tiers", () =>
Effect.gen(function* () {
const prepared = yield* LLMClient.prepare(
LLM.updateRequest(request, { providerOptions: { openai: { serviceTier: "unsupported" } } }),
LLMRequest.update(request, { providerOptions: { openai: { serviceTier: "unsupported" } } }),
)
expect(prepared.body).not.toHaveProperty("service_tier")
@@ -128,9 +139,9 @@ describe("OpenAI Responses route", () => {
it.effect("flattens top-level object unions in function schemas", () =>
Effect.gen(function* () {
const prepared = yield* LLMClient.prepare<OpenAIResponses.OpenAIResponsesBody>(
LLM.updateRequest(request, {
LLMRequest.update(request, {
tools: [
{
ToolDefinition.make({
name: "read",
description: "Read a path or resource.",
inputSchema: {
@@ -152,7 +163,7 @@ describe("OpenAI Responses route", () => {
},
],
},
},
}),
],
}),
)
@@ -207,7 +218,7 @@ describe("OpenAI Responses route", () => {
it.effect("prepares OpenAI Responses WebSocket target", () =>
Effect.gen(function* () {
const prepared = yield* LLMClient.prepare(
LLM.updateRequest(request, {
LLMRequest.update(request, {
model: OpenAIResponses.webSocketRoute
.with({ endpoint: { baseURL: "https://api.openai.test/v1/" }, auth: Auth.bearer("test") })
.model({ id: "gpt-4.1-mini" }),
@@ -291,7 +302,7 @@ describe("OpenAI Responses route", () => {
it.effect("adds native query params to the Responses URL", () =>
Effect.gen(function* () {
yield* LLMClient.generate(
LLM.updateRequest(request, {
LLMRequest.update(request, {
model: Model.update(model, { route: model.route.with({ endpoint: { query: { "api-version": "v1" } } }) }),
}),
).pipe(
@@ -313,7 +324,7 @@ describe("OpenAI Responses route", () => {
it.effect("uses Azure api-key header for static OpenAI Responses keys", () =>
Effect.gen(function* () {
yield* LLMClient.generate(
LLM.updateRequest(request, {
LLMRequest.update(request, {
model: Azure.configure({
baseURL: "https://opencode-test.openai.azure.com/openai/v1/",
apiKey: "azure-key",
@@ -340,7 +351,7 @@ describe("OpenAI Responses route", () => {
it.effect("loads OpenAI default auth from Effect Config", () =>
LLMClient.generate(
LLM.updateRequest(request, {
LLMRequest.update(request, {
model: OpenAI.configure({ baseURL: "https://api.openai.test/v1/" }).responses("gpt-4.1-mini"),
}),
).pipe(
@@ -361,7 +372,7 @@ describe("OpenAI Responses route", () => {
it.effect("lets explicit auth override OpenAI default API key auth", () =>
LLMClient.generate(
LLM.updateRequest(request, {
LLMRequest.update(request, {
model: OpenAI.configure({
baseURL: "https://api.openai.test/v1/",
auth: Auth.bearer("oauth-token"),
@@ -821,7 +832,7 @@ describe("OpenAI Responses route", () => {
input_tokens: 5,
output_tokens: 2,
total_tokens: 7,
input_tokens_details: { cached_tokens: 1 },
input_tokens_details: { cached_tokens: 1, cache_write_tokens: 2 },
output_tokens_details: { reasoning_tokens: 0 },
},
},
@@ -831,8 +842,9 @@ describe("OpenAI Responses route", () => {
const usage = new Usage({
inputTokens: 5,
outputTokens: 2,
nonCachedInputTokens: 4,
nonCachedInputTokens: 2,
cacheReadInputTokens: 1,
cacheWriteInputTokens: 2,
reasoningTokens: 0,
totalTokens: 7,
providerMetadata: {
@@ -840,7 +852,7 @@ describe("OpenAI Responses route", () => {
input_tokens: 5,
output_tokens: 2,
total_tokens: 7,
input_tokens_details: { cached_tokens: 1 },
input_tokens_details: { cached_tokens: 1, cache_write_tokens: 2 },
output_tokens_details: { reasoning_tokens: 0 },
},
},
@@ -856,13 +868,13 @@ describe("OpenAI Responses route", () => {
{
type: "step-finish",
index: 0,
reason: "stop",
reason: { normalized: "stop", raw: undefined },
providerMetadata: { openai: { responseId: "resp_1", serviceTier: "default" } },
usage,
},
{
type: "finish",
reason: "stop",
reason: { normalized: "stop", raw: undefined },
providerMetadata: { openai: { responseId: "resp_1", serviceTier: "default" } },
usage,
},
@@ -870,6 +882,121 @@ describe("OpenAI Responses route", () => {
}),
)
it.effect("preserves and replays assistant message phases", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(request).pipe(
Effect.provide(
fixedResponse(
sseEvents(
{
type: "response.output_item.added",
item: { type: "message", id: "msg_commentary" },
},
{ type: "response.output_text.delta", item_id: "msg_commentary", delta: "Checking." },
{ type: "response.output_text.done", item_id: "msg_commentary" },
{
type: "response.output_item.done",
item: { type: "message", id: "msg_commentary", phase: "commentary" },
},
{
type: "response.output_item.added",
item: { type: "message", id: "msg_final", phase: "final_answer" },
},
{ type: "response.output_text.done", item_id: "msg_final", text: "Finished." },
{
type: "response.output_item.done",
item: { type: "message", id: "msg_final", phase: "final_answer" },
},
{ type: "response.output_item.added", item: { type: "message", id: "msg_null", phase: null } },
{ type: "response.output_text.delta", item_id: "msg_null", delta: "Unclassified." },
{ type: "response.output_item.done", item: { type: "message", id: "msg_null", phase: null } },
{ type: "response.completed", response: { id: "resp_1" } },
),
),
),
)
expect(response.message.content).toEqual([
{
type: "text",
text: "Checking.",
providerMetadata: { openai: { phase: "commentary" } },
},
{
type: "text",
text: "Finished.",
providerMetadata: { openai: { phase: "final_answer" } },
},
{
type: "text",
text: "Unclassified.",
providerMetadata: { openai: { phase: null } },
},
])
const prepared = yield* LLMClient.prepare<OpenAIResponses.OpenAIResponsesBody>(
LLM.request({ model, messages: [response.message] }),
)
expect(prepared.body.input).toEqual([
{
role: "assistant",
content: [{ type: "output_text", text: "Checking." }],
phase: "commentary",
},
{
role: "assistant",
content: [{ type: "output_text", text: "Finished." }],
phase: "final_answer",
},
{
role: "assistant",
content: [{ type: "output_text", text: "Unclassified." }],
phase: null,
},
])
}),
)
it.effect("rejects output text events without the spec-required item id", () =>
Effect.gen(function* () {
const error = yield* LLMClient.generate(request).pipe(
Effect.provide(
fixedResponse(
sseEvents(
{ type: "response.output_text.delta", delta: "orphaned" },
{ type: "response.completed", response: { id: "resp_1" } },
),
),
),
Effect.flip,
)
expect(error.reason._tag).toBe("InvalidProviderOutput")
expect(error.message).toContain("response.output_text.delta is missing item_id")
}),
)
it.effect("rejects reasoning events without the spec-required item id", () =>
Effect.gen(function* () {
const events = [
{ type: "response.reasoning_summary_part.added", summary_index: 0 },
{ type: "response.reasoning_summary_part.done", summary_index: 0 },
{ type: "response.reasoning_text.done" },
]
for (const event of events) {
const error = yield* LLMClient.generate(request).pipe(
Effect.provide(
fixedResponse(sseEvents(event, { type: "response.completed", response: { id: "resp_1" } })),
),
Effect.flip,
)
expect(error.reason._tag).toBe("InvalidProviderOutput")
expect(error.message).toContain(`${event.type} is missing item_id`)
}
}),
)
it.effect("maps incomplete response reasons", () =>
Effect.gen(function* () {
const generate = (incompleteDetails: object) =>
@@ -887,11 +1014,13 @@ describe("OpenAI Responses route", () => {
const length = yield* generate({ reason: "max_output_tokens" })
const contentFilter = yield* generate({ reason: "content_filter" })
const unknown = yield* generate({})
const custom = yield* generate({ reason: "provider_limit" })
expect([length.finishReason, contentFilter.finishReason, unknown.finishReason]).toEqual([
"length",
"content-filter",
"unknown",
expect([length.finishReason, contentFilter.finishReason, unknown.finishReason, custom.finishReason]).toEqual([
{ normalized: "length", raw: "max_output_tokens" },
{ normalized: "content-filter", raw: "content_filter" },
{ normalized: "unknown", raw: undefined },
{ normalized: "unknown", raw: "provider_limit" },
])
}),
)
@@ -946,8 +1075,8 @@ describe("OpenAI Responses route", () => {
{ type: "text-delta", id: "msg_1", text: "Hello" },
{ type: "reasoning-end", id: "rs_1" },
{ type: "text-end", id: "msg_1" },
{ type: "step-finish", index: 0, reason: "stop" },
{ type: "finish", reason: "stop" },
{ type: "step-finish", index: 0, reason: { normalized: "stop", raw: undefined } },
{ type: "finish", reason: { normalized: "stop", raw: undefined } },
])
expect(response.events.filter((event) => event.type === "finish")).toHaveLength(1)
expect(response.message.content).toEqual([
@@ -992,7 +1121,7 @@ describe("OpenAI Responses route", () => {
it.effect("streams each reasoning summary part as a separate block", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(
LLM.updateRequest(request, { providerOptions: { openai: { store: false } } }),
LLMRequest.update(request, { providerOptions: { openai: { store: false } } }),
).pipe(
Effect.provide(
fixedResponse(
@@ -1038,8 +1167,8 @@ describe("OpenAI Responses route", () => {
id: "rs_1:1",
providerMetadata: { openai: { itemId: "rs_1", reasoningEncryptedContent: "encrypted-state" } },
},
{ type: "step-finish", index: 0, reason: "stop" },
{ type: "finish", reason: "stop" },
{ type: "step-finish", index: 0, reason: { normalized: "stop", raw: undefined } },
{ type: "finish", reason: { normalized: "stop", raw: undefined } },
])
}),
)
@@ -1047,7 +1176,7 @@ describe("OpenAI Responses route", () => {
it.effect("closes reasoning summary parts when storage is not disabled", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(
LLM.updateRequest(request, { providerOptions: { openai: { store: true } } }),
LLMRequest.update(request, { providerOptions: { openai: { store: true } } }),
).pipe(
Effect.provide(
fixedResponse(
@@ -1374,8 +1503,8 @@ describe("OpenAI Responses route", () => {
{ type: "response.completed", response: { usage: { input_tokens: 5, output_tokens: 1 } } },
)
const response = yield* LLMClient.generate(
LLM.updateRequest(request, {
tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
LLMRequest.update(request, {
tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
}),
).pipe(Effect.provide(fixedResponse(body)))
const usage = new Usage({
@@ -1422,10 +1551,16 @@ describe("OpenAI Responses route", () => {
providerExecuted: undefined,
providerMetadata: { openai: { itemId: "item_1" } },
},
{ type: "step-finish", index: 0, reason: "tool-calls", usage, providerMetadata: undefined },
{
type: "step-finish",
index: 0,
reason: { normalized: "tool-calls", raw: undefined },
usage,
providerMetadata: undefined,
},
{
type: "finish",
reason: "tool-calls",
reason: { normalized: "tool-calls", raw: undefined },
providerMetadata: undefined,
usage,
},
@@ -1454,8 +1589,8 @@ describe("OpenAI Responses route", () => {
{ type: "response.completed", response: { usage: { input_tokens: 5, output_tokens: 1 } } },
)
const response = yield* LLMClient.generate(
LLM.updateRequest(request, {
tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
LLMRequest.update(request, {
tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
}),
).pipe(Effect.provide(fixedResponse(body)))
@@ -1465,7 +1600,7 @@ describe("OpenAI Responses route", () => {
name: "lookup",
raw: '{"query":"partial',
})
expect(response.finishReason).toBe("tool-calls")
expect(response.finishReason.normalized).toBe("tool-calls")
expect(response.events.some(LLMEvent.is.toolCall)).toBeFalse()
}),
)
@@ -1492,7 +1627,7 @@ describe("OpenAI Responses route", () => {
name: "lookup",
raw: '{"query":"partial',
})
expect(response.finishReason).toBe("tool-calls")
expect(response.finishReason.normalized).toBe("tool-calls")
}),
)
@@ -4,6 +4,8 @@ import { LLM, Message } from "../../src"
import { LLMClient } from "../../src/route"
import * as OpenRouter from "../../src/providers/openrouter"
import { it } from "../lib/effect"
import { fixedResponse } from "../lib/http"
import { sseEvents } from "../lib/sse"
describe("OpenRouter", () => {
it.effect("prepares OpenRouter models through the OpenAI-compatible Chat route", () =>
@@ -54,6 +56,42 @@ describe("OpenRouter", () => {
}),
)
it.effect("preserves the upstream provider finish reason", () =>
Effect.gen(function* () {
const model = OpenRouter.configure({ apiKey: "test-key" }).model("anthropic/claude-sonnet-4.6")
const response = yield* LLMClient.generate(LLM.request({ model, prompt: "Say hello." })).pipe(
Effect.provide(
fixedResponse(
sseEvents({
choices: [{ delta: { content: "Hello" }, finish_reason: "stop", native_finish_reason: "end_turn" }],
}),
),
),
)
expect(response.finishReason).toEqual({ normalized: "stop", raw: "end_turn" })
}),
)
it.effect("fails on a mid-stream provider error", () =>
Effect.gen(function* () {
const model = OpenRouter.configure({ apiKey: "test-key" }).model("openai/gpt-4o-mini")
const error = yield* LLMClient.generate(LLM.request({ model, prompt: "Say hello." })).pipe(
Effect.provide(
fixedResponse(
sseEvents({
error: { code: 502, message: "Provider disconnected" },
}),
),
),
Effect.flip,
)
expect(error.reason).toMatchObject({ _tag: "ProviderInternal" })
expect(error.message).toContain("Provider disconnected")
}),
)
it.effect("preserves manually supplied reasoning details", () =>
Effect.gen(function* () {
const details = [
@@ -106,7 +106,7 @@ const readPdfRuntime = Tool.make({
})
const expectCode = (response: LLMResponse) => {
expect(response.finishReason).toBe("stop")
expect(response.finishReason.normalized).toBe("stop")
expect(response.text.toUpperCase()).toContain(CODE)
}
@@ -166,7 +166,7 @@ describe("PDF recorded", () => {
tools: { read_pdf: readPdfRuntime },
}).pipe(Stream.runCollect),
)
expect(events.at(-1)).toMatchObject({ type: "finish", reason: "stop" })
expect(events.at(-1)).toMatchObject({ type: "finish", reason: { normalized: "stop" } })
expect(LLMResponse.text({ events }).toUpperCase()).toContain(CODE)
return
}
+8 -10
View File
@@ -3,6 +3,7 @@ import { Effect, Schema } from "effect"
import {
LLM,
LLMEvent,
LLMRequest,
LLMResponse,
Message,
ToolRuntime,
@@ -11,7 +12,6 @@ import {
toDefinitions,
type ContentPart,
type FinishReason,
type LLMRequest,
type Model,
} from "../src"
import { LLMClient } from "../src/route"
@@ -91,7 +91,7 @@ const restroomImage = () =>
export const runWeatherToolLoop = (request: LLMRequest) =>
Effect.gen(function* () {
const tools = { [weatherToolName]: weatherRuntimeTool }
let next = LLM.updateRequest(request, { tools: toDefinitions(tools) })
let next = LLMRequest.update(request, { tools: toDefinitions(tools) })
const events: LLMEvent[] = []
for (let step = 0; step < 10; step++) {
@@ -108,7 +108,7 @@ export const runWeatherToolLoop = (request: LLMRequest) =>
ToolRuntime.dispatch(tools, call).pipe(Effect.map((result) => [call, result] as const)),
)
events.push(...dispatched.flatMap(([, result]) => result.events))
next = LLM.updateRequest(next, {
next = LLMRequest.update(next, {
messages: [
...next.messages,
Message.assistant(assistantContent(response.events)),
@@ -123,10 +123,8 @@ export const runWeatherToolLoop = (request: LLMRequest) =>
const assistantContent = (events: ReadonlyArray<LLMEvent>) =>
events.reduce(LLMResponse.reduce, LLMResponse.empty()).message.content
export const expectFinish = (
events: ReadonlyArray<LLMEvent>,
reason: Extract<LLMEvent, { readonly type: "finish" }>["reason"],
) => expect(events.at(-1)).toMatchObject({ type: "finish", reason })
export const expectFinish = (events: ReadonlyArray<LLMEvent>, reason: FinishReason) =>
expect(events.at(-1)).toMatchObject({ type: "finish", reason: { normalized: reason } })
export const expectWeatherToolCall = (response: LLMResponse) =>
expect(response.toolCalls).toMatchObject([
@@ -136,10 +134,10 @@ export const expectWeatherToolCall = (response: LLMResponse) =>
export const expectWeatherToolLoop = (events: ReadonlyArray<LLMEvent>) => {
const finishes = events.filter(LLMEvent.is.finish)
expect(finishes).toHaveLength(1)
expect(finishes[0]?.reason).toBe("stop")
expect(finishes[0]?.reason.normalized).toBe("stop")
const stepFinishes = events.filter(LLMEvent.is.stepFinish)
expect(stepFinishes.map((event) => event.reason)).toEqual(["tool-calls", "stop"])
expect(stepFinishes.map((event) => event.reason.normalized)).toEqual(["tool-calls", "stop"])
const toolCalls = events.filter(LLMEvent.is.toolCall)
expect(toolCalls).toHaveLength(1)
@@ -503,7 +501,7 @@ export const eventSummary = (events: ReadonlyArray<LLMEvent>) => {
continue
}
if (event.type === "finish") {
summary.push({ type: "finish", reason: event.reason, usage: usageSummary(event.usage) })
summary.push({ type: "finish", reason: event.reason.normalized, usage: usageSummary(event.usage) })
}
}
return summary.map((item) => Object.fromEntries(Object.entries(item).filter((entry) => entry[1] !== undefined)))
+15 -7
View File
@@ -14,11 +14,11 @@ describe("LLMResponse reducer", () => {
LLMEvent.reasoningEnd({ id: "r1", providerMetadata: { anthropic: { signature: "sig" } } }),
LLMEvent.textDelta({ id: "t1", text: "Answer" }),
LLMEvent.textEnd({ id: "t1" }),
LLMEvent.finish({ reason: "stop", usage: { outputTokens: 5 } }),
LLMEvent.finish({ reason: { normalized: "stop" }, usage: { outputTokens: 5 } }),
]
const response = LLMResponse.fromEvents(events)
expect(response?.finishReason).toBe("stop")
expect(response?.finishReason).toEqual({ normalized: "stop" })
expect(response?.usage).toMatchObject({ outputTokens: 5 })
expect(response?.events).toEqual(events)
expect(response?.events.map((event) => event.type)).toEqual([
@@ -62,18 +62,26 @@ describe("LLMResponse reducer", () => {
test("uses terminal usage when present and keeps prior usage when finish omits it", () => {
const withFinishUsage = LLMResponse.fromEvents([
LLMEvent.stepFinish({ index: 0, reason: "stop", usage: { inputTokens: 3 } }),
LLMEvent.finish({ reason: "stop", usage: { outputTokens: 2 } }),
LLMEvent.stepFinish({ index: 0, reason: { normalized: "stop" }, usage: { inputTokens: 3 } }),
LLMEvent.finish({ reason: { normalized: "stop" }, usage: { outputTokens: 2 } }),
])
const withoutFinishUsage = LLMResponse.fromEvents([
LLMEvent.stepFinish({ index: 0, reason: "stop", usage: { inputTokens: 3 } }),
LLMEvent.finish({ reason: "stop" }),
LLMEvent.stepFinish({ index: 0, reason: { normalized: "stop" }, usage: { inputTokens: 3 } }),
LLMEvent.finish({ reason: { normalized: "stop" } }),
])
expect(withFinishUsage?.usage).toMatchObject({ outputTokens: 2 })
expect(withoutFinishUsage?.usage).toMatchObject({ inputTokens: 3 })
})
test("preserves the raw finish reason", () => {
const response = LLMResponse.fromEvents([
LLMEvent.finish({ reason: { normalized: "unknown", raw: "provider_limit" } }),
])
expect(response?.finishReason).toEqual({ normalized: "unknown", raw: "provider_limit" })
})
test("assembles tool-call content only after the completed tool call event", () => {
const pending = reduce([
LLMEvent.toolInputStart({ id: "call_1", name: "lookup" }),
@@ -88,7 +96,7 @@ describe("LLMResponse reducer", () => {
LLMEvent.toolInputDelta({ id: "call_1", name: "lookup", text: ':"weather"}' }),
LLMEvent.toolInputEnd({ id: "call_1", name: "lookup" }),
LLMEvent.toolCall({ id: "call_1", name: "lookup", input: { query: "weather" } }),
LLMEvent.finish({ reason: "tool-calls" }),
LLMEvent.finish({ reason: { normalized: "tool-calls" } }),
])
expect(response?.message.content).toEqual([
+6 -2
View File
@@ -48,8 +48,12 @@ describe("llm schema", () => {
})
test("finish constructors accept usage input", () => {
expect(LLMEvent.stepFinish({ index: 0, reason: "stop", usage: { inputTokens: 1 } }).usage).toBeInstanceOf(Usage)
expect(LLMEvent.finish({ reason: "stop", usage: { outputTokens: 2 } }).usage).toBeInstanceOf(Usage)
expect(
LLMEvent.stepFinish({ index: 0, reason: { normalized: "stop" }, usage: { inputTokens: 1 } }).usage,
).toBeInstanceOf(Usage)
expect(LLMEvent.finish({ reason: { normalized: "stop" }, usage: { outputTokens: 2 } }).usage).toBeInstanceOf(
Usage,
)
})
test("content part tagged union exposes guards", () => {
+5 -2
View File
@@ -539,6 +539,7 @@ describe("LLMClient tools", () => {
},
{ type: "content_block_stop", index: 1 },
{ type: "message_delta", delta: { stop_reason: "tool_use" }, usage: { output_tokens: 5 } },
{ type: "message_stop" },
)
: sseEvents(
{ type: "message_start", message: { usage: { input_tokens: 5 } } },
@@ -546,6 +547,7 @@ describe("LLMClient tools", () => {
{ type: "content_block_delta", index: 0, delta: { type: "text_delta", text: "Done." } },
{ type: "content_block_stop", index: 0 },
{ type: "message_delta", delta: { stop_reason: "end_turn" }, usage: { output_tokens: 1 } },
{ type: "message_stop" },
),
{ headers: { "content-type": "text/event-stream" } },
)
@@ -553,7 +555,7 @@ describe("LLMClient tools", () => {
)
yield* TestToolRuntime.runTools({
request: LLM.updateRequest(baseRequest, {
request: LLMRequest.update(baseRequest, {
model: AnthropicMessages.route
.with({ auth: Auth.header("x-api-key", "test") })
.model({ id: "claude-sonnet-4-5" }),
@@ -801,6 +803,7 @@ describe("LLMClient tools", () => {
{ type: "content_block_delta", index: 2, delta: { type: "text_delta", text: "Done." } },
{ type: "content_block_stop", index: 2 },
{ type: "message_delta", delta: { stop_reason: "end_turn" }, usage: { output_tokens: 8 } },
{ type: "message_stop" },
),
{ headers: { "content-type": "text/event-stream" } },
)
@@ -808,7 +811,7 @@ describe("LLMClient tools", () => {
)
const events = Array.from(
yield* TestToolRuntime.runTools({
request: LLM.updateRequest(baseRequest, {
request: LLMRequest.update(baseRequest, {
model: AnthropicMessages.route
.with({ auth: Auth.header("x-api-key", "test") })
.model({ id: "claude-sonnet-4-5" }),
@@ -97,6 +97,7 @@ export async function setupTimeline(
locale?: string
deviceScaleFactor?: number
seedHistory?: boolean
protocol?: "v1" | "v2"
} = {},
) {
const sessions = input.sessions ?? [session()]
@@ -114,6 +115,7 @@ export async function setupTimeline(
retry: input.eventRetry ?? 20,
})
await mockOpenCodeServer(page, {
protocol: input.protocol,
directory,
project: project(),
provider: provider(),
@@ -89,8 +89,8 @@ test("reconnects after a stream error", async ({ page }) => {
expect((await timeline.transport.connections())[0]?.endedBy).toBe("error")
})
test("records event IDs and reconnect Last-Event-ID headers", async ({ page }) => {
const timeline = await setupTimeline(page, { eventRetry: 10 })
test("does not request replay when reconnecting the volatile V2 event stream", async ({ page }) => {
const timeline = await setupTimeline(page, { eventRetry: 10, protocol: "v2" })
const first = await timeline.transport.send(partUpdated(textPart("prt_transport_id", "event with id")), {
id: "timeline-event-7",
})
@@ -100,7 +100,7 @@ test("records event IDs and reconnect Last-Event-ID headers", async ({ page }) =
const connection = await timeline.transport.waitForConnection({ after: first.connectionID })
expect(first.eventID).toBe("timeline-event-7")
expect(connection.headers["last-event-id"]).toBe("timeline-event-7")
expect(connection.headers["last-event-id"]).toBeUndefined()
})
test("passes through non-event fetches", async ({ page }) => {
+276 -2
View File
@@ -4,6 +4,7 @@ const emptyList = new Set(["/skill", "/command", "/lsp", "/formatter", "/vcs/sta
const emptyObject = new Set(["/global/config", "/config", "/provider/auth", "/mcp", "/experimental/resource"])
export interface MockServerConfig {
protocol?: "v1" | "v2"
provider: unknown
directory: string
project: unknown
@@ -53,8 +54,20 @@ export async function mockOpenCodeServer(page: Page, config: MockServerConfig) {
if (url.port !== targetPort && url.port !== appPort) return route.fallback()
const path = url.pathname
if (path === "/global/event" || path === "/event") return sse(route, config.events?.(), config.eventRetry)
if (path === "/global/health") return json(route, { healthy: true })
if (path === "/global/event" || path === "/event" || path === "/api/event") {
const events = config.events?.()
return sse(
route,
path === "/api/event"
? [{ id: "evt_mock_connected", type: "server.connected", data: {} }, ...(events?.map(currentEvent) ?? [])]
: events,
config.eventRetry,
)
}
if (path === "/global/health")
return config.protocol === "v2" ? json(route, {}, undefined, 404) : json(route, { healthy: true })
if (path === "/api/health" && config.protocol === "v2")
return json(route, { healthy: true, version: "2.0.0", pid: 1 })
if (path === "/experimental/capabilities") return json(route, { backgroundSubagents: true })
if (path === "/permission")
return json(route, typeof config.permissions === "function" ? config.permissions() : (config.permissions ?? []))
@@ -83,10 +96,129 @@ export async function mockOpenCodeServer(page: Page, config: MockServerConfig) {
},
data: [],
})
if (path === "/api/agent")
return json(route, {
location: location(config),
data: [
{
id: "build",
name: "Build",
mode: "primary",
hidden: false,
request: { settings: {}, headers: {}, body: {} },
permissions: [],
},
],
})
if (path === "/api/command") return json(route, { location: location(config), data: [] })
if (path === "/api/mcp") return json(route, { location: location(config), data: [] })
if (path === "/api/mcp/resource")
return json(route, { location: location(config), data: { resources: [], templates: [] } })
const integration = path.match(/^\/api\/integration\/([^/]+)$/)?.[1]
if (integration && route.request().method() === "GET")
return json(route, {
location: location(config),
data: { id: integration, name: integration, methods: [{ type: "key", label: "API key" }], connections: [] },
})
if (/^\/api\/integration\/[^/]+\/connect\/key$/.test(path) && route.request().method() === "POST")
return route.fulfill({ status: 204, headers: { "access-control-allow-origin": "*" } })
if (path === "/api/project") return json(route, [config.project])
if (path === "/api/project/current")
return json(route, { id: (config.project as { id?: string }).id, directory: config.directory })
if (path.startsWith("/api/project/") && route.request().method() === "PATCH") return json(route, config.project)
if (path === "/api/path")
return json(route, {
state: config.directory,
config: config.directory,
worktree: config.directory,
directory: config.directory,
home: "C:/OpenCode",
})
if (path === "/api/permission/request")
return json(route, {
location: location(config),
data: (typeof config.permissions === "function" ? config.permissions() : (config.permissions ?? [])).map(
currentPermission,
),
})
if (path === "/api/question/request")
return json(route, {
location: location(config),
data: typeof config.questions === "function" ? config.questions() : (config.questions ?? []),
})
if (path === "/api/vcs")
return json(route, { location: location(config), data: { branch: "main", defaultBranch: "main" } })
if (path === "/api/vcs/status") return json(route, { location: location(config), data: [] })
if (path === "/api/vcs/diff") return json(route, { location: location(config), data: config.vcsDiff ?? [] })
if (path === "/api/pty/shells") return json(route, { location: location(config), data: [] })
if (/^\/api\/pty\/[^/]+\/connect-token$/.test(path))
return json(route, { location: location(config), data: { ticket: "e2e-ticket", expires_in: 60 } })
if (emptyObject.has(path)) return json(route, {})
if (emptyList.has(path)) return json(route, [])
if (path === "/api/session") {
const directory = url.searchParams.get("directory")
const parentID = url.searchParams.get("parentID")
const limit = Number(url.searchParams.get("limit") ?? 50)
const offset = Number(url.searchParams.get("cursor") ?? 0)
const sessions = config.sessions
.filter((session) => !directory || session.directory === directory)
.filter((session) => parentID !== "null" || session.parentID === undefined)
.filter((session) => {
const search = url.searchParams.get("search")?.toLowerCase()
return (
!search ||
String(session.title ?? "")
.toLowerCase()
.includes(search)
)
})
const ordered = url.searchParams.get("order") === "asc" ? sessions.toReversed() : sessions
const data = ordered.slice(offset, offset + limit)
const next = offset + limit < ordered.length ? String(offset + limit) : undefined
return json(route, {
data: data.map((session) => currentSession(session, config.directory)),
cursor: { next },
})
}
if (path === "/api/session/active") {
const statuses = (config.sessionStatus ?? {}) as Record<string, { type?: string }>
return json(route, {
data: Object.fromEntries(
Object.entries(statuses).flatMap(([id, status]) =>
status.type === "idle" ? [] : [[id, { type: "running" }]],
),
),
})
}
if (/^\/api\/session\/[^/]+\/shell$/.test(path) && route.request().method() === "POST") {
return route.fulfill({ status: 204, headers: { "access-control-allow-origin": "*" } })
}
if (/^\/api\/session\/[^/]+\/question\/[^/]+\/(reply|reject)$/.test(path) && route.request().method() === "POST") {
return route.fulfill({ status: 204, headers: { "access-control-allow-origin": "*" } })
}
if (/^\/api\/session\/[^/]+\/permission\/[^/]+\/reply$/.test(path) && route.request().method() === "POST") {
return route.fulfill({ status: 204, headers: { "access-control-allow-origin": "*" } })
}
if (
/^\/api\/session\/[^/]+\/(archive|rename|interrupt|revert\/clear|revert\/commit)$/.test(path) &&
route.request().method() === "POST"
) {
return route.fulfill({ status: 204, headers: { "access-control-allow-origin": "*" } })
}
if (/^\/api\/session\/[^/]+$/.test(path) && route.request().method() === "DELETE") {
return route.fulfill({ status: 204, headers: { "access-control-allow-origin": "*" } })
}
if (path in staticRoutes) return json(route, staticRoutes[path])
const currentSessionMatch = path.match(/^\/api\/session\/([^/]+)$/)
if (currentSessionMatch) {
const session = config.sessions.find((item) => item.id === currentSessionMatch[1])
if (!session) return json(route, { error: "Session not found" }, undefined, 404)
return json(route, {
data: currentSession(session, config.directory),
})
}
const sessionMatch = path.match(/^\/session\/([^/]+)$/)
if (sessionMatch) {
const session = config.sessions.find((s) => s.id === sessionMatch[1])
@@ -107,6 +239,24 @@ export async function mockOpenCodeServer(page: Page, config: MockServerConfig) {
if (/^\/session\/[^/]+\/(children|diff)$/.test(path)) return json(route, [])
const currentMessagesMatch = path.match(/^\/api\/session\/([^/]+)\/message$/)
if (currentMessagesMatch) {
const token = url.searchParams.get("cursor") ?? undefined
const before = token ? cursors.get(token) : undefined
if (token && !before) return json(route, { error: "Invalid cursor" }, undefined, 400)
config.onMessages?.({ sessionID: currentMessagesMatch[1], before, phase: "start" })
await config.beforeMessagesResponse?.({ sessionID: currentMessagesMatch[1]!, before })
if (config.messageDelay !== undefined) await new Promise((resolve) => setTimeout(resolve, config.messageDelay))
const pageData = config.pageMessages(currentMessagesMatch[1], Number(url.searchParams.get("limit") ?? 50), before)
config.onMessages?.({ sessionID: currentMessagesMatch[1], before, phase: "end" })
const cursor = pageData.cursor ? `cursor_${++nextCursor}` : undefined
if (cursor) cursors.set(cursor, pageData.cursor!)
return json(route, {
data: pageData.items.map(currentMessage).reverse(),
cursor: { next: cursor },
})
}
const messagesMatch = path.match(/^\/session\/([^/]+)\/message$/)
if (messagesMatch) {
const token = url.searchParams.get("before") ?? undefined
@@ -129,6 +279,115 @@ export async function mockOpenCodeServer(page: Page, config: MockServerConfig) {
})
}
function location(config: MockServerConfig) {
return {
directory: config.directory,
project: { id: (config.project as { id?: string }).id, directory: config.directory },
}
}
function currentPermission(value: unknown) {
const permission = value as Record<string, unknown>
if (permission.action) return permission
const tool = permission.tool as { messageID?: string; callID?: string } | undefined
return {
id: permission.id,
sessionID: permission.sessionID,
action: permission.permission,
resources: permission.patterns ?? [],
save: permission.always,
metadata: permission.metadata,
source:
tool?.messageID && tool.callID ? { type: "tool", messageID: tool.messageID, callID: tool.callID } : undefined,
}
}
export function currentSession(session: { id: string } & Record<string, unknown>, fallbackDirectory?: string) {
const time = session.time && typeof session.time === "object" ? session.time : {}
return {
id: session.id,
parentID: session.parentID,
projectID: session.projectID ?? "project",
agent: session.agent ?? "build",
model: session.model ?? { id: "mock-model", providerID: "mock-provider" },
cost: session.cost ?? 0,
tokens: session.tokens ?? { input: 0, output: 0, reasoning: 0, cache: { read: 0, write: 0 } },
time: {
created: "created" in time && typeof time.created === "number" ? time.created : 0,
updated: "updated" in time && typeof time.updated === "number" ? time.updated : 0,
...(session.time && typeof session.time === "object" && "archived" in session.time
? { archived: session.time.archived }
: {}),
},
title: session.title ?? session.id,
location: {
directory: typeof session.directory === "string" ? session.directory : fallbackDirectory,
...(typeof session.workspaceID === "string" ? { workspaceID: session.workspaceID } : {}),
},
subpath: session.path,
revert: session.revert,
}
}
function currentMessage(value: unknown) {
const item = value as {
info: Record<string, unknown> & { id: string; role: "user" | "assistant"; time: { created: number } }
parts: Array<Record<string, unknown> & { type: string }>
}
if (item.info.role === "user") {
return {
id: item.info.id,
type: "user",
time: item.info.time,
text: item.parts
.flatMap((part) => (part.type === "text" && typeof part.text === "string" ? [part.text] : []))
.join("\n"),
}
}
return {
id: item.info.id,
type: "assistant",
time: item.info.time,
agent: item.info.agent ?? "build",
model: { id: item.info.modelID ?? "model", providerID: item.info.providerID ?? "provider" },
cost: item.info.cost,
tokens: item.info.tokens,
error: item.info.error,
content: item.parts.flatMap<unknown>((part) => {
if (part.type === "text" || part.type === "reasoning") return [{ type: part.type, text: part.text ?? "" }]
if (part.type !== "tool") return []
const state = part.state as Record<string, unknown>
return [
{
type: "tool",
id: part.id,
name: part.tool,
time: state.time ?? { created: item.info.time.created },
state:
state.status === "pending"
? { status: "streaming", input: state.raw ?? JSON.stringify(state.input ?? {}) }
: state.status === "completed"
? {
status: "completed",
input: state.input ?? {},
structured: state.metadata ?? {},
content: [{ type: "text", text: state.output ?? "" }],
}
: state.status === "error"
? {
status: "error",
input: state.input ?? {},
structured: state.metadata ?? {},
content: [],
error: { type: "ToolError", message: state.error ?? "Tool failed" },
}
: { status: "running", input: state.input ?? {}, structured: state.metadata ?? {}, content: [] },
},
]
}),
}
}
function json(route: Route, body: unknown, headers?: Record<string, string>, status = 200) {
return route.fulfill({
status,
@@ -149,3 +408,18 @@ function sse(route: Route, events?: unknown[], retry?: number) {
body: `${retry === undefined ? "" : `retry: ${retry}\n\n`}${events?.map((event) => `data: ${JSON.stringify(event)}\n\n`).join("") || ": ok\n\n"}`,
})
}
function currentEvent(input: unknown) {
if (!input || typeof input !== "object" || !("payload" in input)) return input
const envelope = input as { directory?: string; payload?: unknown }
if (!envelope.payload || typeof envelope.payload !== "object") return input
const payload = envelope.payload as { id?: string; type?: string; properties?: unknown }
if (!payload.type) return input
return {
id: payload.id ?? `evt_mock_${Date.now()}`,
created: Date.now(),
type: payload.type,
data: payload.properties ?? {},
location: envelope.directory && envelope.directory !== "global" ? { directory: envelope.directory } : undefined,
}
}
+29 -9
View File
@@ -3,7 +3,7 @@ import type { Page } from "@playwright/test"
export type SseConnectionRecord = {
id: number
url: string
path: "/global/event" | "/event"
path: "/global/event" | "/event" | "/api/event"
headers: Record<string, string>
openedAt: number
endedAt?: number
@@ -93,6 +93,21 @@ export async function installSseTransport<T>(
eventOptions.retry === undefined ? "" : `retry: ${eventOptions.retry}\n`,
`data: ${JSON.stringify(payload)}\n\n`,
].join("")
const currentEvent = (input: unknown) => {
if (!input || typeof input !== "object" || !("payload" in input)) return input
const envelope = input as { directory?: string; payload?: unknown }
if (!envelope.payload || typeof envelope.payload !== "object") return input
const payload = envelope.payload as { id?: string; type?: string; properties?: unknown }
if (!payload.type) return input
return {
id: payload.id ?? `evt_mock_${Date.now()}`,
created: Date.now(),
type: payload.type,
data: payload.properties ?? {},
location:
envelope.directory && envelope.directory !== "global" ? { directory: envelope.directory } : undefined,
}
}
const acknowledge = (
connection: Connection,
bytes: number,
@@ -140,15 +155,13 @@ export async function installSseTransport<T>(
output.forEach((chunk) => connection.controller.enqueue(chunk))
return acknowledge(connection, input.bytes.length, output.length)
}
const encoded = input.deliveries.map((delivery) => ({
delivery,
bytes: encoder.encode(frame(delivery.payload, delivery.options)),
}))
const encoded = input.deliveries.map((delivery) => {
const payload = connection.path === "/api/event" ? currentEvent(delivery.payload) : delivery.payload
return { delivery, payload, bytes: encoder.encode(frame(payload, delivery.options)) }
})
encoded.forEach((item) => marker(item.delivery.options?.marker))
if (input.burst) {
const bytes = encoder.encode(
encoded.map((item) => frame(item.delivery.payload, item.delivery.options)).join(""),
)
const bytes = encoder.encode(encoded.map((item) => frame(item.payload, item.delivery.options)).join(""))
connection.controller.enqueue(bytes)
return encoded.map((item) => acknowledge(connection, item.bytes.byteLength, 1, item.delivery.options?.id))
}
@@ -161,7 +174,10 @@ export async function installSseTransport<T>(
const fetch = (input: RequestInfo | URL, init?: RequestInit) => {
const request = new Request(input, init)
const url = new URL(request.url)
if (url.origin !== server || (url.pathname !== "/global/event" && url.pathname !== "/event"))
if (
url.origin !== server ||
(url.pathname !== "/global/event" && url.pathname !== "/event" && url.pathname !== "/api/event")
)
return originalFetch(request)
const id = ++nextConnectionID
@@ -177,6 +193,10 @@ export async function installSseTransport<T>(
record.controller = controller
connections.push(record)
if (retry !== undefined) controller.enqueue(encoder.encode(`retry: ${retry}\n\n`))
if (url.pathname === "/api/event")
controller.enqueue(
encoder.encode(frame({ id: `evt_mock_connected_${id}`, type: "server.connected", data: {} })),
)
request.signal.addEventListener(
"abort",
() => {
+2 -1
View File
@@ -53,9 +53,10 @@
"@dnd-kit/helpers": "0.5.0",
"@dnd-kit/solid": "0.5.0",
"@kobalte/core": "catalog:",
"@opencode-ai/client": "file:vendor/opencode-ai-client-1.17.13.tgz",
"@opencode-ai/core": "workspace:*",
"@opencode-ai/schema": "workspace:*",
"@opencode-ai/sdk": "workspace:*",
"@opencode-ai/sdk": "1.18.5",
"@opencode-ai/session-ui": "workspace:*",
"@opencode-ai/ui": "workspace:*",
"@pierre/trees": "1.0.0-beta.4",
+37 -1
View File
@@ -1,5 +1,6 @@
import { describe, expect, test } from "bun:test"
import { coalesceServerEvents, enqueueServerEvent, resumeStreamAfterPageShow } from "./server-sdk"
import { adaptServerEvent, coalesceServerEvents, enqueueServerEvent, resumeStreamAfterPageShow } from "./server-sdk"
import type { OpenCodeEvent } from "@opencode-ai/client/promise"
import type { Event } from "@opencode-ai/sdk/v2/client"
describe("resumeStreamAfterPageShow", () => {
@@ -14,6 +15,23 @@ describe("resumeStreamAfterPageShow", () => {
})
})
describe("adaptServerEvent", () => {
test("preserves V2 events while adapting permission requests for existing consumers", () => {
const current = {
id: "evt_1",
created: 1,
type: "permission.v2.asked",
data: { id: "perm_1", sessionID: "ses_1", action: "read", resources: ["src/**"] },
} as OpenCodeEvent
expect(adaptServerEvent(current)).toMatchObject({
type: "permission.asked",
properties: { id: "perm_1", sessionID: "ses_1", permission: "read", patterns: ["src/**"] },
current,
})
})
})
describe("coalesceServerEvents", () => {
const delta = (value: string, field = "text", partID = "part") => ({
directory: "/repo",
@@ -34,6 +52,24 @@ describe("coalesceServerEvents", () => {
expect(result[0]?.payload).toMatchObject({ id: "second", properties: { delta: "hello world" } })
})
test("merges adjacent current text deltas", () => {
const current = (id: string, value: string) =>
adaptServerEvent({
id,
created: 1,
type: "session.text.delta",
location: { directory: "/repo" },
data: { sessionID: "ses", assistantMessageID: "msg", ordinal: 0, delta: value },
} as OpenCodeEvent)
const result = coalesceServerEvents([
{ directory: "/repo", payload: current("evt_1", "hello ") },
{ directory: "/repo", payload: current("evt_2", "world") },
])
expect(result).toHaveLength(1)
expect(result[0]?.payload.current).toMatchObject({ id: "evt_2", data: { delta: "hello world" } })
})
test("preserves event boundaries and distinct fields", () => {
const status = {
directory: "/repo",
+143 -51
View File
@@ -1,21 +1,60 @@
import type { OpenCodeEvent } from "@opencode-ai/client/promise"
import type { Event } from "@opencode-ai/sdk/v2/client"
import { createSimpleContext } from "@opencode-ai/ui/context"
import { createGlobalEmitter } from "@solid-primitives/event-bus"
import { makeEventListener } from "@solid-primitives/event-listener"
import { type Accessor, batch, createMemo, onCleanup, onMount } from "solid-js"
import { createSdkForServer } from "@/utils/server"
import { createApiForServer, createSdkForServer, type ServerApi } from "@/utils/server"
import { useLanguage } from "./language"
import { usePlatform } from "./platform"
import { ServerConnection, useServer } from "./server"
import { createRefCountMap } from "@/utils/refcount"
import { useGlobal } from "./global"
import { ServerScope } from "@/utils/server-scope"
import { detectServerProtocol, type ServerProtocol } from "@/utils/server-protocol"
import { createCompatibleApi, type CompatibleApi } from "@/utils/server-compat"
const isAbortError = (error: unknown) =>
error !== null && typeof error === "object" && "name" in error && error.name === "AbortError"
const isStreamClosed = (error: unknown, signal?: AbortSignal) => isAbortError(error) || signal?.aborted === true
type QueuedServerEvent = { directory: string; payload: Event }
export type ServerEvent = Event & { current?: OpenCodeEvent }
type QueuedServerEvent = { directory: string; payload: ServerEvent }
type CurrentDelta = Extract<
OpenCodeEvent,
{ type: "session.text.delta" | "session.reasoning.delta" | "session.tool.input.delta" | "session.compaction.delta" }
>
export function adaptServerEvent(event: OpenCodeEvent): ServerEvent {
if (event.type === "permission.v2.asked") {
return {
id: event.id,
type: "permission.asked",
properties: {
id: event.data.id,
sessionID: event.data.sessionID,
permission: event.data.action,
patterns: event.data.resources,
always: event.data.save ?? [],
metadata: event.data.metadata ?? {},
tool:
event.data.source?.type === "tool"
? { messageID: event.data.source.messageID, callID: event.data.source.callID }
: undefined,
},
current: event,
} as ServerEvent
}
if (event.type === "permission.v2.replied")
return { id: event.id, type: "permission.replied", properties: event.data, current: event } as ServerEvent
if (event.type === "question.v2.asked")
return { id: event.id, type: "question.asked", properties: event.data, current: event } as ServerEvent
if (event.type === "question.v2.replied")
return { id: event.id, type: "question.replied", properties: event.data, current: event } as ServerEvent
if (event.type === "question.v2.rejected")
return { id: event.id, type: "question.rejected", properties: event.data, current: event } as ServerEvent
return { id: event.id, type: event.type, properties: event.data, current: event } as ServerEvent
}
const coalescedKey = (event: QueuedServerEvent) => {
if (event.payload.type === "lsp.updated") return `lsp.updated:${event.directory}`
@@ -40,6 +79,34 @@ export function enqueueServerEvent(queue: QueuedServerEvent[], event: QueuedServ
export function coalesceServerEvents(events: QueuedServerEvent[]) {
const output: QueuedServerEvent[] = []
events.forEach((event) => {
const current = currentDelta(event.payload.current)
if (current) {
const previous = output[output.length - 1]
const prior = currentDelta(previous?.payload.current)
if (
previous &&
prior &&
previous.directory === event.directory &&
currentDeltaKey(prior) === currentDeltaKey(current)
) {
const fragment = currentDeltaFragment(prior) + currentDeltaFragment(current)
const data =
current.type === "session.compaction.delta"
? { ...current.data, text: fragment }
: { ...current.data, delta: fragment }
output[output.length - 1] = {
directory: event.directory,
payload: {
...event.payload,
properties: data,
current: { ...current, data } as CurrentDelta,
} as ServerEvent,
}
return
}
output.push(event)
return
}
if (event.payload.type !== "message.part.delta") {
output.push(event)
return
@@ -71,12 +138,52 @@ export function coalesceServerEvents(events: QueuedServerEvent[]) {
return output
}
function currentDelta(event: OpenCodeEvent | undefined): CurrentDelta | undefined {
if (
event?.type === "session.text.delta" ||
event?.type === "session.reasoning.delta" ||
event?.type === "session.tool.input.delta" ||
event?.type === "session.compaction.delta"
)
return event
}
function currentDeltaKey(event: CurrentDelta) {
if (event.type === "session.tool.input.delta")
return `${event.type}:${event.data.sessionID}:${event.data.assistantMessageID}:${event.data.callID}`
if (event.type === "session.compaction.delta") return `${event.type}:${event.data.sessionID}`
return `${event.type}:${event.data.sessionID}:${event.data.assistantMessageID}:${event.data.ordinal}`
}
function currentDeltaFragment(event: CurrentDelta) {
return event.type === "session.compaction.delta" ? event.data.text : event.data.delta
}
export function resumeStreamAfterPageShow(event: PageTransitionEvent, start: () => unknown) {
if (!event.persisted) return
start()
}
function createServerSdkContextBase(server: ServerConnection.Any, scope: ServerScope) {
type ServerEventEmitter = ReturnType<typeof createGlobalEmitter<{ [key: string]: ServerEvent }>>
type ServerSDKBase = {
server: ServerConnection.Any
scope: ServerScope
protocol: Promise<ServerProtocol>
url: string
client: ReturnType<typeof createSdkForServer>
api: CompatibleApi
currentApi: ServerApi
event: {
on: ServerEventEmitter["on"]
listen: ServerEventEmitter["listen"]
start: () => Promise<void> | undefined
}
createClient: (
opts: Omit<Parameters<typeof createSdkForServer>[0], "server" | "fetch">,
) => ReturnType<typeof createSdkForServer>
}
function createServerSdkContextBase(server: ServerConnection.Any, scope: ServerScope): ServerSDKBase {
const platform = usePlatform()
const abort = new AbortController()
@@ -91,13 +198,15 @@ function createServerSdkContextBase(server: ServerConnection.Any, scope: ServerS
}
})()
const eventApi = createApiForServer({ server: server.http, fetch: eventFetch })
const eventSdk = createSdkForServer({
signal: abort.signal,
fetch: eventFetch,
server: server.http,
})
const protocol = detectServerProtocol(server.http, platform.fetch ?? globalThis.fetch)
const emitter = createGlobalEmitter<{
[key: string]: Event
[key: string]: ServerEvent
}>()
type Queued = QueuedServerEvent
@@ -142,21 +251,6 @@ function createServerSdkContextBase(server: ServerConnection.Any, scope: ServerS
let run: Promise<void> | undefined
let started = false
let generation = 0
const HEARTBEAT_TIMEOUT_MS = 15_000
let lastEventAt = Date.now()
let heartbeat: ReturnType<typeof setTimeout> | undefined
const resetHeartbeat = () => {
lastEventAt = Date.now()
if (heartbeat) clearTimeout(heartbeat)
heartbeat = setTimeout(() => {
attempt?.abort()
}, HEARTBEAT_TIMEOUT_MS)
}
const clearHeartbeat = () => {
if (!heartbeat) return
clearTimeout(heartbeat)
heartbeat = undefined
}
const start = () => {
if (started) return run
@@ -168,35 +262,24 @@ function createServerSdkContextBase(server: ServerConnection.Any, scope: ServerS
// oxlint-disable-next-line no-unmodified-loop-condition -- `started` is set to false by stop() which also aborts; both flags are checked to allow graceful exit
while (!abort.signal.aborted && started && generation === active) {
attempt = new AbortController()
lastEventAt = Date.now()
const onAbort = () => {
attempt?.abort()
}
abort.signal.addEventListener("abort", onAbort)
try {
const events = await eventSdk.global.event({
signal: attempt.signal,
onSseError: (error) => {
if (isStreamClosed(error, attempt?.signal)) return
if (streamErrorLogged) return
streamErrorLogged = true
console.error("[global-sdk] event stream error", {
url: server.http.url,
fetch: eventFetch ? "platform" : "webview",
error,
})
},
})
const kind = await protocol
const events =
kind === "v1"
? (await eventSdk.global.event({ signal: attempt.signal })).stream
: eventApi.event.subscribe({ signal: attempt.signal })
let yielded = Date.now()
resetHeartbeat()
for await (const event of events.stream) {
resetHeartbeat()
for await (const event of events) {
streamErrorLogged = false
if (event.payload.type !== "sync") {
const directory = event.directory ?? "global"
const payload = event.payload as Event
if (enqueueServerEvent(queue, { directory, payload })) schedule()
}
const legacy = "payload" in event
if (legacy && event.payload.type === "sync") continue
const directory = legacy ? (event.directory ?? "global") : (event.location?.directory ?? "global")
const payload = legacy ? (event.payload as Event) : adaptServerEvent(event)
if (enqueueServerEvent(queue, { directory, payload })) schedule()
if (Date.now() - yielded < STREAM_YIELD_MS) continue
yielded = Date.now()
@@ -214,7 +297,6 @@ function createServerSdkContextBase(server: ServerConnection.Any, scope: ServerS
} finally {
abort.signal.removeEventListener("abort", onAbort)
attempt = undefined
clearHeartbeat()
}
if (abort.signal.aborted || !started || generation !== active) return
@@ -233,18 +315,11 @@ function createServerSdkContextBase(server: ServerConnection.Any, scope: ServerS
started = false
generation++
attempt?.abort()
clearHeartbeat()
}
onMount(() => {
makeEventListener(window, "pagehide", stop)
makeEventListener(window, "pageshow", (event) => resumeStreamAfterPageShow(event, start))
makeEventListener(document, "visibilitychange", () => {
if (document.visibilityState !== "visible") return
if (!started) return
if (Date.now() - lastEventAt < HEARTBEAT_TIMEOUT_MS) return
attempt?.abort()
})
})
onCleanup(() => {
@@ -258,12 +333,24 @@ function createServerSdkContextBase(server: ServerConnection.Any, scope: ServerS
fetch: platform.fetch,
throwOnError: true,
})
const currentApi: ServerApi = createApiForServer({ server: server.http, fetch: platform.fetch })
const legacy = (directory?: string) =>
createSdkForServer({
server: server.http,
fetch: platform.fetch,
throwOnError: true,
directory,
})
const api = createCompatibleApi({ protocol, current: currentApi, legacy })
return {
server,
scope,
protocol,
url: server.http.url,
client: sdk,
api,
currentApi,
event: {
on: emitter.on.bind(emitter),
listen: emitter.listen.bind(emitter),
@@ -279,7 +366,6 @@ function createServerSdkContextBase(server: ServerConnection.Any, scope: ServerS
}
}
type ServerSDKBase = ReturnType<typeof createServerSdkContextBase>
export type ServerSDK = ServerSDKBase & {
ensureDirSdkContext: (directory: string) => ReturnType<typeof createDirSdkContext>
}
@@ -309,7 +395,7 @@ export const { use: useServerSDK, provider: ServerSDKProvider } = createSimpleCo
})
type SDKEventMap = {
[key in Event["type"]]: Extract<Event, { type: key }>
[key in Event["type"]]: Extract<ServerEvent, { type: key }>
}
function createDirSdkContext(directory: string, serverSDK: ServerSDKBase) {
@@ -329,6 +415,12 @@ function createDirSdkContext(directory: string, serverSDK: ServerSDKBase) {
scope: serverSDK.scope,
directory,
client,
api: createCompatibleApi({
protocol: serverSDK.protocol,
current: serverSDK.currentApi,
legacy: (next) => serverSDK.createClient({ directory: next ?? directory, throwOnError: true }),
directory,
}),
event: emitter,
get url() {
return serverSDK.url
@@ -0,0 +1,113 @@
import { describe, expect, test } from "bun:test"
import { createApiForServer, createSdkForServer } from "./server"
import { createCompatibleApi } from "./server-compat"
function setup(protocol: "v1" | "v2" | Promise<"v1" | "v2">) {
const requests: Request[] = []
const fetcher = Object.assign(
async (input: string | URL | Request, init?: RequestInit) => {
const request = new Request(input, init)
requests.push(request)
if (request.method === "PATCH") {
return Response.json({
id: "ses_1",
slug: "ses_1",
projectID: "project",
directory: "/repo",
title: "Session",
version: "1",
time: { created: 1, updated: 1 },
})
}
if (request.method === "POST" && request.url.endsWith("/prompt_async"))
return new Response(undefined, { status: 204 })
if (request.method === "POST" && request.url.endsWith("/prompt")) {
return Response.json({
admittedSeq: 1,
id: "msg_1",
sessionID: "ses_1",
timeCreated: 1,
type: "user",
data: { text: "hello" },
delivery: "steer",
})
}
if (request.method === "GET") return Response.json([])
return new Response(undefined, { status: 204 })
},
{ preconnect: globalThis.fetch.preconnect },
)
const server = { url: "http://localhost:4096" }
const api = createCompatibleApi({
protocol: typeof protocol === "string" ? Promise.resolve(protocol) : protocol,
current: createApiForServer({ server, fetch: fetcher }),
legacy: (directory) => createSdkForServer({ server, fetch: fetcher, directory, throwOnError: true }),
directory: "/repo",
})
return { api, requests }
}
describe("createCompatibleApi", () => {
test("routes V1 archive through the legacy session update", async () => {
const { api, requests } = setup("v1")
await api.session.archive({ sessionID: "ses_1", directory: "/repo" })
const url = new URL(requests[0]!.url)
expect(url.pathname).toBe("/session/ses_1")
expect(requests[0]!.headers.get("x-opencode-directory")).toBe("%2Frepo")
expect(requests[0]!.method).toBe("PATCH")
expect(await requests[0]!.json()).toMatchObject({ time: { archived: expect.any(Number) } })
})
test("converts current prompts to the V1 prompt contract", async () => {
const { api, requests } = setup("v1")
await api.session.prompt({
sessionID: "ses_1",
id: "msg_1",
text: "hello",
agent: "build",
model: { providerID: "provider", modelID: "model" },
})
expect(new URL(requests[0]!.url).pathname).toBe("/session/ses_1/prompt_async")
expect(await requests[0]!.json()).toMatchObject({
messageID: "msg_1",
agent: "build",
model: { providerID: "provider", modelID: "model" },
parts: [{ type: "text", text: "hello" }],
})
})
test("keeps V2 session actions on the current API", async () => {
const { api, requests } = setup("v2")
await api.session.archive({ sessionID: "ses_1" })
expect(new URL(requests[0]!.url).pathname).toBe("/api/session/ses_1/archive")
expect(requests[0]!.method).toBe("POST")
})
test("resolves protocol detection once across implementation methods", async () => {
let detections = 0
const resolved = Promise.resolve<"v1" | "v2">("v2")
const protocol = new Proxy(resolved, {
get(target, property) {
if (property !== "then") return Reflect.get(target, property, target)
detections++
return target.then.bind(target)
},
})
const { api } = setup(protocol)
await api.session.archive({ sessionID: "ses_1" })
await api.session.list()
expect(detections).toBe(1)
})
test("uses the global V1 session search endpoint", async () => {
const { api, requests } = setup("v1")
await api.session.list({ parentID: null, search: "session", limit: 50 })
expect(new URL(requests[0]!.url).pathname).toBe("/experimental/session")
})
})
+495
View File
@@ -0,0 +1,495 @@
import type { ServerApi } from "./server"
import type { ServerProtocol } from "./server-protocol"
import type { OpencodeClient, Session } from "@opencode-ai/sdk/v2/client"
import type {
Project,
ProjectCurrent,
SessionApi,
SessionCommandInput,
SessionCommandOutput,
SessionCompactInput,
SessionCompactOutput,
SessionInfo,
SessionPromptInput,
SessionPromptOutput,
SessionShellInput,
SessionShellOutput,
} from "@opencode-ai/client/promise"
type LegacyClient = OpencodeClient
type LegacyFor = (directory?: string) => LegacyClient
type CompatibleSessionApi = Omit<
SessionApi,
"prompt" | "command" | "shell" | "compact" | "rename" | "archive" | "remove"
> & {
prompt: (input: SessionPromptInput & LegacyPrompt) => Promise<SessionPromptOutput>
command: (input: SessionCommandInput) => Promise<SessionCommandOutput>
shell: (input: SessionShellInput & LegacyPrompt) => Promise<SessionShellOutput>
compact: (input: SessionCompactInput & { model?: LegacyPrompt["model"] }) => Promise<SessionCompactOutput>
rename: (input: Parameters<SessionApi["rename"]>[0] & LegacyLocation) => ReturnType<SessionApi["rename"]>
archive: (input: Parameters<SessionApi["archive"]>[0] & LegacyLocation) => ReturnType<SessionApi["archive"]>
remove: (input: Parameters<SessionApi["remove"]>[0] & LegacyLocation) => ReturnType<SessionApi["remove"]>
}
export type CompatibleApi = Omit<ServerApi, "session"> & { readonly session: CompatibleSessionApi }
type LegacyPrompt = {
agent?: string
model?: { providerID: string; modelID: string }
variant?: string
}
type LegacyLocation = { directory?: string }
type CompatibleInput = {
protocol: Promise<ServerProtocol>
current: ServerApi
legacy: LegacyFor
directory?: string
}
function mime(uri: string) {
const match = /^data:([^;,]+)/.exec(uri)
return match?.[1] ?? "application/octet-stream"
}
function sessionInfo(session: Session): SessionInfo {
return {
id: session.id,
parentID: session.parentID,
projectID: session.projectID,
agent: session.agent,
model: session.model && {
id: session.model.id,
providerID: session.model.providerID,
variant: session.model.variant,
},
cost: session.cost ?? 0,
tokens: session.tokens ?? { input: 0, output: 0, reasoning: 0, cache: { read: 0, write: 0 } },
time: session.time,
title: session.title,
location: { directory: session.directory, workspaceID: session.workspaceID },
subpath: session.path,
revert: session.revert && {
messageID: session.revert.messageID,
partID: session.revert.partID,
snapshot: session.revert.snapshot,
},
}
}
export function createCompatibleApi(input: CompatibleInput): CompatibleApi {
const v1 = createV1Api(input)
return lazyApi(
input.protocol.then((protocol) => (protocol === "v1" ? v1 : input.current)),
input.current,
)
}
function lazyApi<T extends object>(implementation: Promise<T>, shape: T): T {
const cache = new Map<PropertyKey, unknown>()
return new Proxy(shape, {
get(target, property, receiver) {
const sample = Reflect.get(target, property, receiver)
if (typeof sample === "function") {
return (...args: unknown[]) =>
implementation.then((value) => {
const method = Reflect.get(value, property)
if (typeof method !== "function") throw new Error(`API method unavailable: ${String(property)}`)
return Reflect.apply(method, value, args)
})
}
if (sample === null || typeof sample !== "object") return sample
if (cache.has(property)) return cache.get(property)
const nested = lazyApi(
implementation.then((value) => {
const result = Reflect.get(value, property)
if (result === null || typeof result !== "object") {
throw new Error(`API namespace unavailable: ${String(property)}`)
}
return result
}),
sample,
)
cache.set(property, nested)
return nested
},
})
}
function createV1Api(input: CompatibleInput): CompatibleApi {
const directory = (location?: { directory?: string }) => location?.directory ?? input.directory
const legacy = (location?: { directory?: string }) => input.legacy(directory(location))
const located = <T>(data: T, value?: { directory?: string }) => ({
location: {
directory: directory(value) ?? "",
project: { id: "", directory: directory(value) ?? "" },
},
data,
})
return {
...input.current,
session: {
...input.current.session,
async list(
value?: Parameters<ServerApi["session"]["list"]>[0],
options?: Parameters<ServerApi["session"]["list"]>[1],
) {
if (!value?.directory && value?.search !== undefined) {
const result = await legacy().experimental.session.list(
{
roots: value.parentID === null ? true : undefined,
search: value.search,
limit: value.limit,
},
options,
)
return { data: (result.data ?? []).map(sessionInfo), cursor: {} }
}
const result = await legacy({ directory: value?.directory }).session.list({
directory: value?.directory,
roots: value?.parentID === null ? true : undefined,
search: value?.search,
limit: value?.limit,
})
return { data: (result.data ?? []).map(sessionInfo), cursor: {} }
},
async create(value?: Parameters<ServerApi["session"]["create"]>[0]) {
const result = await legacy(value?.location ?? undefined).session.create({
directory: directory(value?.location ?? undefined),
})
if (!result.data) throw new Error("Failed to create session")
return sessionInfo(result.data)
},
async get(value: Parameters<ServerApi["session"]["get"]>[0]) {
const result = await legacy().session.get(value)
if (!result.data) throw new Error(`Session not found: ${value.sessionID}`)
return sessionInfo(result.data)
},
async active() {
const result = await legacy().session.status()
return Object.fromEntries(
Object.entries(result.data ?? {}).flatMap(([sessionID, status]) =>
status.type === "idle" ? [] : [[sessionID, { type: "running" as const }]],
),
)
},
async rename(value: Parameters<ServerApi["session"]["rename"]>[0] & LegacyLocation) {
await legacy(value).session.update({ sessionID: value.sessionID, title: value.title })
},
async archive(value: Parameters<ServerApi["session"]["archive"]>[0] & LegacyLocation) {
await legacy(value).session.update({ sessionID: value.sessionID, time: { archived: Date.now() } })
},
async remove(value: Parameters<ServerApi["session"]["remove"]>[0] & LegacyLocation) {
await legacy(value).session.delete(value)
},
async fork(value: Parameters<ServerApi["session"]["fork"]>[0]) {
const result = await legacy().session.fork(value)
if (!result.data) throw new Error("Failed to fork session")
return sessionInfo(result.data)
},
async interrupt(value: Parameters<ServerApi["session"]["interrupt"]>[0]) {
await legacy().session.abort(value)
},
async prompt(value: SessionPromptInput & LegacyPrompt) {
await legacy().session.promptAsync({
sessionID: value.sessionID,
messageID: value.id ?? undefined,
agent: value.agent,
model: value.model,
variant: value.variant,
parts: [
{ type: "text", text: value.text },
...(value.files ?? []).map((file) => ({
type: "file" as const,
mime: mime(file.uri),
url: file.uri,
filename: file.name,
})),
...(value.agents ?? []).map((agent) => ({
type: "agent" as const,
name: agent.name,
source: agent.mention
? { value: agent.mention.text, start: agent.mention.start, end: agent.mention.end }
: undefined,
})),
],
})
return {
admittedSeq: 0,
id: value.id ?? "",
sessionID: value.sessionID,
timeCreated: Date.now(),
type: "user",
data: { text: value.text },
delivery: value.delivery ?? "steer",
}
},
async command(value: SessionCommandInput) {
await legacy().session.command({
sessionID: value.sessionID,
messageID: value.id ?? undefined,
command: value.command,
arguments: value.arguments ?? "",
agent: value.agent ?? undefined,
model: value.model ? `${value.model.providerID}/${value.model.id}` : undefined,
variant: value.model?.variant,
parts: value.files?.map((file) => ({
type: "file" as const,
mime: mime(file.uri),
url: file.uri,
filename: file.name,
})),
})
return {
admittedSeq: 0,
id: value.id ?? "",
sessionID: value.sessionID,
timeCreated: Date.now(),
type: "user",
data: { text: `/${value.command} ${value.arguments ?? ""}`.trim() },
delivery: value.delivery ?? "steer",
}
},
async shell(value: SessionShellInput & LegacyPrompt) {
await legacy().session.shell({
sessionID: value.sessionID,
command: value.command,
agent: value.agent,
model: value.model,
})
},
compact: async (value: SessionCompactInput & { model?: LegacyPrompt["model"] }) => {
if (!value.model) throw new Error("A model is required to compact a V1 session")
await legacy().session.summarize({
sessionID: value.sessionID,
providerID: value.model.providerID,
modelID: value.model.modelID,
})
return {
admittedSeq: 0,
id: value.id ?? "",
sessionID: value.sessionID,
timeCreated: Date.now(),
type: "compaction",
}
},
revert: {
stage: async (value: Parameters<ServerApi["session"]["revert"]["stage"]>[0]) => {
await legacy().session.revert(value)
return { messageID: value.messageID }
},
clear: async (value: Parameters<ServerApi["session"]["revert"]["clear"]>[0]) => {
await legacy().session.unrevert(value)
},
commit: input.current.session.revert.commit,
},
},
project: {
...input.current.project,
async list() {
return ((await legacy().project.list()).data ?? []) as Project[]
},
async current(value?: Parameters<ServerApi["project"]["current"]>[0]) {
const result = await legacy(value?.location).project.current()
if (!result.data) throw new Error("Project not found")
return { id: result.data.id, directory: result.data.worktree } satisfies ProjectCurrent
},
async update(value: Parameters<ServerApi["project"]["update"]>[0]) {
const project = (await legacy().project.list()).data?.find((item) => item.id === value.projectID)
const result = await legacy({ directory: project?.worktree }).project.update({
...value,
directory: project?.worktree,
})
if (!result.data) throw new Error(`Project not found: ${value.projectID}`)
return result.data as Project
},
async directories(value: Parameters<ServerApi["project"]["directories"]>[0]) {
const result = await legacy(value.location).worktree.list()
return (result.data ?? []).map((item) => ({ directory: item }))
},
},
path: {
...input.current.path,
async get(value?: Parameters<ServerApi["path"]["get"]>[0]) {
const result = await legacy(value?.location).path.get()
if (!result.data) throw new Error("Path unavailable")
return result.data
},
},
vcs: {
...input.current.vcs,
async get(value?: Parameters<ServerApi["vcs"]["get"]>[0]) {
const result = await legacy(value?.location).vcs.get()
return located({ branch: result.data?.branch, defaultBranch: undefined }, value?.location)
},
async status(value?: Parameters<ServerApi["vcs"]["status"]>[0]) {
const result = await legacy(value?.location).vcs.status()
return located(result.data ?? [], value?.location)
},
async diff(value: Parameters<ServerApi["vcs"]["diff"]>[0]) {
const result = await legacy(value.location).vcs.diff({
mode: value.mode === "working" ? "git" : value.mode,
context: value.context,
})
return located(
(result.data ?? []).map((file) => ({
file: file.file,
patch: file.patch ?? "",
additions: file.additions,
deletions: file.deletions,
status: file.status ?? "modified",
})),
value.location,
)
},
},
file: {
...input.current.file,
async list(value?: Parameters<ServerApi["file"]["list"]>[0]) {
const result = await legacy(value?.location).file.list({ path: value?.path ?? "" })
return located(result.data ?? [], value?.location)
},
async find(value: Parameters<ServerApi["file"]["find"]>[0]) {
const result = await legacy(value.location).find.files({
query: value.query,
type: value.type,
limit: value.limit,
})
return located(
(result.data ?? []).map((path) => ({ path, type: value.type ?? "file" })),
value.location,
)
},
},
integration: {
...input.current.integration,
async get(value: Parameters<ServerApi["integration"]["get"]>[0]) {
const methods = ((await legacy(value.location).provider.auth()).data?.[value.integrationID] ?? []).map(
(method, index) =>
method.type === "api"
? { type: "key" as const, label: method.label }
: { type: "oauth" as const, id: String(index), label: method.label, prompts: method.prompts },
)
return located(
{
id: value.integrationID,
name: value.integrationID,
methods,
connections: [],
},
value.location,
)
},
connect: {
...input.current.integration.connect,
key: async (value: Parameters<ServerApi["integration"]["connect"]["key"]>[0]) => {
await legacy(value.location).auth.set({
providerID: value.integrationID,
auth: { type: "api", key: value.key },
})
},
},
oauth: {
...input.current.integration.oauth,
connect: async (value: Parameters<ServerApi["integration"]["oauth"]["connect"]>[0]) => {
const method = Number(value.methodID)
const result = await legacy(value.location).provider.oauth.authorize(
{ providerID: value.integrationID, method, inputs: value.inputs },
{ throwOnError: true },
)
if (!result.data) throw new Error("Failed to start OAuth authorization")
return located(
{
attemptID: `${value.integrationID}:${method}`,
url: result.data.url,
instructions: result.data.instructions,
mode: result.data.method,
time: { created: Date.now(), expires: Date.now() + 10 * 60 * 1000 },
},
value.location,
)
},
complete: async (value: Parameters<ServerApi["integration"]["oauth"]["complete"]>[0]) => {
const method = Number(value.attemptID.split(":").at(-1))
await legacy(value.location).provider.oauth.callback(
{ providerID: value.integrationID, method, code: value.code },
{ throwOnError: true },
)
},
status: async (value: Parameters<ServerApi["integration"]["oauth"]["status"]>[0]) => {
const method = Number(value.attemptID.split(":").at(-1))
await legacy(value.location).provider.oauth.callback(
{ providerID: value.integrationID, method },
{ throwOnError: true },
)
return located(
{ status: "complete" as const, time: { created: Date.now(), expires: Date.now() } },
value.location,
)
},
},
},
pty: {
...input.current.pty,
async shells(value?: Parameters<ServerApi["pty"]["shells"]>[0]) {
return located((await legacy(value?.location).pty.shells()).data ?? [], value?.location)
},
async list(value?: Parameters<ServerApi["pty"]["list"]>[0]) {
return located((await legacy(value?.location).pty.list()).data ?? [], value?.location)
},
async create(value?: Parameters<ServerApi["pty"]["create"]>[0]) {
const result = await legacy(value?.location).pty.create({
command: value?.command,
args: value?.args ? [...value.args] : undefined,
cwd: value?.cwd,
title: value?.title,
env: value?.env,
})
if (!result.data) throw new Error("Failed to create terminal")
return located(result.data, value?.location)
},
async get(value: Parameters<ServerApi["pty"]["get"]>[0]) {
const result = await legacy(value.location).pty.get({ ptyID: value.ptyID })
if (!result.data) throw new Error(`Terminal not found: ${value.ptyID}`)
return located(result.data, value.location)
},
async update(value: Parameters<ServerApi["pty"]["update"]>[0]) {
const result = await legacy(value.location).pty.update({
ptyID: value.ptyID,
title: value.title,
size: value.size,
})
if (!result.data) throw new Error(`Terminal not found: ${value.ptyID}`)
return located(result.data, value.location)
},
async remove(value: Parameters<ServerApi["pty"]["remove"]>[0]) {
await legacy(value.location).pty.remove({ ptyID: value.ptyID })
},
async connectToken(value: Parameters<ServerApi["pty"]["connectToken"]>[0]) {
const result = await legacy(value.location).pty.connectToken({ ptyID: value.ptyID })
if (!result.data) throw new Error(`Failed to connect terminal: ${value.ptyID}`)
return located(result.data, value.location)
},
},
permission: {
...input.current.permission,
async reply(value: Parameters<ServerApi["permission"]["reply"]>[0]) {
await legacy().permission.respond({
sessionID: value.sessionID,
permissionID: value.requestID,
response: value.reply,
})
},
},
question: {
...input.current.question,
async reply(value: Parameters<ServerApi["question"]["reply"]>[0]) {
await legacy().question.reply({
requestID: value.requestID,
answers: value.answers.map((answer) => [...answer]),
})
},
async reject(value: Parameters<ServerApi["question"]["reject"]>[0]) {
await legacy().question.reject({ requestID: value.requestID })
},
},
}
}
+34 -4
View File
@@ -14,15 +14,45 @@ function abortFromInput(input: RequestInfo | URL, init?: RequestInit) {
describe("checkServerHealth", () => {
test("returns healthy response with version", async () => {
const fetch = (async () =>
new Response(JSON.stringify({ healthy: true, version: "1.2.3" }), {
let request: URL | undefined
const fetch = (async (input: RequestInfo | URL) => {
request = input instanceof URL ? input : new URL(input instanceof Request ? input.url : input)
return new Response(JSON.stringify({ healthy: true, version: "1.2.3" }), {
status: 200,
headers: { "content-type": "application/json" },
})) as unknown as typeof globalThis.fetch
})
}) as unknown as typeof globalThis.fetch
const result = await checkServerHealth(server, fetch)
expect(result).toEqual({ healthy: true, version: "1.2.3" })
expect(request?.pathname).toBe("/api/health")
})
test("falls back to the V1 health endpoint", async () => {
const paths: string[] = []
const fetch = (async (input: RequestInfo | URL) => {
const url = input instanceof URL ? input : new URL(input instanceof Request ? input.url : input)
paths.push(url.pathname)
if (url.pathname === "/api/health") return new Response(undefined, { status: 404 })
return Response.json({ healthy: true, version: "1.18.4" })
}) as unknown as typeof globalThis.fetch
expect(await checkServerHealth(server, fetch)).toEqual({ healthy: true, version: "1.18.4" })
expect(paths).toEqual(["/api/health", "/global/health"])
})
test("falls back when the current health response is malformed", async () => {
const paths: string[] = []
const fetch = (async (input: RequestInfo | URL) => {
const url = input instanceof URL ? input : new URL(input instanceof Request ? input.url : input)
paths.push(url.pathname)
if (url.pathname === "/api/health") return Response.json({})
return Response.json({ healthy: true, version: "1.18.4" })
}) as unknown as typeof globalThis.fetch
expect(await checkServerHealth(server, fetch)).toEqual({ healthy: true, version: "1.18.4" })
expect(paths).toEqual(["/api/health", "/global/health"])
})
test("allows slow servers thirty seconds by default", async () => {
@@ -142,7 +172,7 @@ describe("checkServerHealth", () => {
retryDelayMs: 1,
})
expect(count).toBe(3)
expect(count).toBe(6)
expect(result).toEqual({ healthy: false })
})
})
+23 -5
View File
@@ -1,6 +1,7 @@
import { usePlatform } from "@/context/platform"
import { ServerConnection } from "@/context/server"
import { createSdkForServer } from "./server"
import { authTokenFromCredentials, createSdkForServer } from "./server"
import { ClientError, OpenCode } from "@opencode-ai/client"
import { Accessor, createEffect, onCleanup } from "solid-js"
import { createStore, reconcile } from "solid-js/store"
@@ -61,6 +62,7 @@ function wait(ms: number, signal?: AbortSignal) {
function retryable(error: unknown, signal?: AbortSignal) {
if (signal?.aborted) return false
if (error instanceof ClientError) return error.reason === "Transport"
if (!(error instanceof Error)) return false
if (error.name === "AbortError" || error.name === "TimeoutError") return false
if (error instanceof TypeError) return true
@@ -82,15 +84,31 @@ export async function checkServerHealth(
.then(() => attempt(count + 1))
.catch(() => ({ healthy: false }))
}
const attempt = (count: number): Promise<ServerHealth> =>
createSdkForServer({
server,
const attempt = async (count: number): Promise<ServerHealth> => {
const current = await OpenCode.make({
baseUrl: server.url,
fetch,
signal,
headers: server.password
? {
Authorization: `Basic ${authTokenFromCredentials({ username: server.username, password: server.password })}`,
}
: undefined,
})
.health.get({ signal })
.then((x) =>
typeof x.healthy === "boolean"
? { data: { healthy: x.healthy, version: x.version } }
: { error: new Error("Invalid health response") },
)
.catch((error) => ({ error }))
if ("data" in current && current.data) return current.data
if (signal?.aborted) return { healthy: false }
return createSdkForServer({ server, fetch, signal })
.global.health()
.then((x) => (x.error ? next(count, x.error) : { healthy: x.data?.healthy === true, version: x.data?.version }))
.catch((error) => next(count, error))
}
return attempt(0).finally(() => timeout?.clear?.())
}
@@ -0,0 +1,40 @@
import { describe, expect, test } from "bun:test"
import { detectServerProtocol } from "./server-protocol"
const server = { url: "http://localhost:4096" }
const json = (value: unknown, status = 200) =>
new Response(JSON.stringify(value), { status, headers: { "content-type": "application/json" } })
const mockFetch = (run: (input: string | URL | Request) => Promise<Response>) =>
Object.assign(run, { preconnect: globalThis.fetch.preconnect })
describe("detectServerProtocol", () => {
test("prefers the legacy health endpoint when both API generations exist", async () => {
const fetcher = mockFetch((input) => {
const path = new URL(input instanceof Request ? input.url : input).pathname
if (path === "/global/health") return Promise.resolve(json({ healthy: true, version: "1.18.4" }))
return Promise.resolve(json({ healthy: true, version: "2.0.0", pid: 123 }))
})
expect(await detectServerProtocol(server, fetcher)).toBe("v1")
})
test("recognizes V2 health by its process identifier", async () => {
const fetcher = mockFetch((input) => {
const path = new URL(input instanceof Request ? input.url : input).pathname
if (path === "/global/health") return Promise.resolve(json({}, 404))
return Promise.resolve(json({ healthy: true, version: "2.0.0", pid: 123 }))
})
expect(await detectServerProtocol(server, fetcher)).toBe("v2")
})
test("recognizes the transitional V1 API health response", async () => {
const fetcher = mockFetch((input) => {
const path = new URL(input instanceof Request ? input.url : input).pathname
if (path === "/global/health") return Promise.resolve(json({}, 404))
return Promise.resolve(json({ healthy: true }))
})
expect(await detectServerProtocol(server, fetcher)).toBe("v1")
})
})
+35
View File
@@ -0,0 +1,35 @@
import type { ServerConnection } from "@/context/server"
import { authTokenFromCredentials } from "./server"
export type ServerProtocol = "v1" | "v2"
function headers(server: ServerConnection.HttpBase) {
if (!server.password) return
return {
Authorization: `Basic ${authTokenFromCredentials({ username: server.username, password: server.password })}`,
}
}
async function probe(server: ServerConnection.HttpBase, fetch: typeof globalThis.fetch, path: string) {
const response = await fetch(new URL(path, server.url), {
headers: headers(server),
signal: AbortSignal.timeout(5_000),
})
if (!response.ok || !response.headers.get("content-type")?.includes("application/json")) return
const value: unknown = await response.json()
if (!value || typeof value !== "object") return
return value
}
export async function detectServerProtocol(
server: ServerConnection.HttpBase,
fetch: typeof globalThis.fetch,
): Promise<ServerProtocol> {
const legacy = await probe(server, fetch, "/global/health").catch(() => undefined)
if (legacy && "healthy" in legacy && legacy.healthy === true) return "v1"
const current = await probe(server, fetch, "/api/health").catch(() => undefined)
if (current && "pid" in current && typeof current.pid === "number") return "v2"
if (current && "healthy" in current && current.healthy === true) return "v1"
return "v2"
}
+21
View File
@@ -1,4 +1,5 @@
import { createOpencodeClient } from "@opencode-ai/sdk/v2/client"
import { OpenCode, type OpenCodeClient } from "@opencode-ai/client/promise"
import type { ServerConnection } from "@/context/server"
import { decode64 } from "@/utils/base64"
@@ -39,3 +40,23 @@ export function createSdkForServer({
baseUrl: server.url,
})
}
export function createApiForServer(input: {
server: ServerConnection.HttpBase
fetch?: typeof globalThis.fetch
}): OpenCodeClient {
return OpenCode.make({
baseUrl: input.server.url,
fetch: input.fetch,
headers: input.server.password
? {
Authorization: `Basic ${authTokenFromCredentials({
username: input.server.username,
password: input.server.password,
})}`,
}
: undefined,
})
}
export type ServerApi = OpenCodeClient
Binary file not shown.
+9 -14
View File
@@ -28,7 +28,7 @@ export type TurnControl = {
type ToolState = {
readonly name: string
input: ToolInput
structured: Record<string, unknown>
metadata: Record<string, unknown>
content: ToolContent
}
@@ -38,7 +38,7 @@ export type TurnStart =
| { readonly type: "compaction"; readonly id: string }
function emptyToolState(): ToolState {
return { name: "tool", input: {}, structured: {}, content: [] }
return { name: "tool", input: {}, metadata: {}, content: [] }
}
export async function streamTurn(input: {
@@ -120,7 +120,7 @@ export async function streamTurn(input: {
}
if (event.type === "session.tool.input.started") {
assistantMessageID = event.data.assistantMessageID
tools.set(event.data.callID, { name: event.data.name, input: {}, structured: {}, content: [] })
tools.set(event.data.callID, { name: event.data.name, input: {}, metadata: {}, content: [] })
await update({
sessionUpdate: "tool_call",
...pendingToolCall({
@@ -151,15 +151,13 @@ export async function streamTurn(input: {
if (event.type === "session.tool.progress") {
const current = tools.get(event.data.callID)
if (!current) continue
current.structured = event.data.structured
current.content = event.data.content
current.metadata = event.data.metadata
await update({
sessionUpdate: "tool_call_update",
...runningToolUpdate({
toolCallId: event.data.callID,
toolName: current.name,
state: { input: current.input },
content: current.content,
cwd: input.cwd,
}),
})
@@ -175,7 +173,7 @@ export async function streamTurn(input: {
cwd: input.cwd,
toolName: current.name,
toolInput: current.input,
structured: event.data.structured,
metadata: event.data.metadata ?? {},
}).catch(() => {})
await update({
sessionUpdate: "tool_call_update",
@@ -183,9 +181,8 @@ export async function streamTurn(input: {
toolCallId: event.data.callID,
toolName: current.name,
input: current.input,
structured: event.data.structured,
metadata: event.data.metadata,
content: event.data.content,
result: event.data.result,
}),
})
continue
@@ -199,7 +196,7 @@ export async function streamTurn(input: {
toolCallId: event.data.callID,
toolName: current.name,
input: current.input,
structured: event.data.metadata ?? current.structured,
metadata: event.data.metadata ?? current.metadata,
content: event.data.content ?? current.content,
error: event.data.error.message,
cwd: input.cwd,
@@ -342,9 +339,8 @@ async function replayMessage(
toolCallId: part.id,
toolName: part.name,
input: part.state.input,
structured: part.state.structured,
metadata: part.state.metadata,
content: part.state.content,
result: part.state.result,
}),
},
})
@@ -358,7 +354,6 @@ async function replayMessage(
toolCallId: part.id,
toolName: part.name,
state: { input: part.state.input },
content: part.state.content,
cwd,
}),
},
@@ -373,7 +368,7 @@ async function replayMessage(
toolCallId: part.id,
toolName: part.name,
input: part.state.input,
structured: part.state.structured,
metadata: part.state.metadata,
content: part.state.content,
error: part.state.error.message,
cwd,
+3 -3
View File
@@ -58,11 +58,11 @@ export async function syncEditedFiles(input: {
readonly cwd: string
readonly toolName: string
readonly toolInput: ToolInput
readonly structured: Readonly<Record<string, unknown>>
readonly metadata: Readonly<Record<string, unknown>>
}) {
if (!input.writeTextFile || !input.connection.writeTextFile || toToolKind(input.toolName) !== "edit") return
const files = Array.isArray(input.structured.files)
? input.structured.files.flatMap((file): string[] => {
const files = Array.isArray(input.metadata.files)
? input.metadata.files.flatMap((file): string[] => {
if (!file || typeof file !== "object") return []
const path = Reflect.get(file, "file")
return typeof path === "string" ? [path] : []
+13 -24
View File
@@ -1,5 +1,6 @@
import { isAbsolute, resolve } from "node:path"
import type { ToolCall, ToolCallContent, ToolCallLocation, ToolCallUpdate, ToolKind } from "@agentclientprotocol/sdk"
import { readDisplayText } from "@opencode-ai/tui/mini/tool"
export type ToolInput = Record<string, unknown>
export type ToolContent = ReadonlyArray<
@@ -100,11 +101,12 @@ export function completedToolUpdate(input: {
readonly toolName: string
readonly input: ToolInput
readonly content: ToolContent
readonly structured: Readonly<Record<string, unknown>>
readonly result?: unknown
readonly metadata?: Readonly<Record<string, unknown>>
}): ToolCallUpdate {
const normalized = toolContent(input.content)
const read = input.toolName.toLocaleLowerCase() === "read" ? readDisplayText(input.structured) : undefined
// Read's model content is a JSON page envelope; show the clean text instead.
const firstText = input.content.find((part) => part.type === "text")
const read = input.toolName.toLocaleLowerCase() === "read" && firstText ? readDisplayText(firstText.text) : undefined
const images = normalized.filter((part) => part.type === "content" && part.content.type === "image")
const primary =
read === undefined
@@ -128,8 +130,7 @@ export function completedToolUpdate(input: {
status: "completed",
content: [...primary, ...diff, ...images],
rawOutput: {
structured: input.structured,
...(input.result === undefined ? {} : { result: input.result }),
...(input.metadata === undefined ? {} : { metadata: input.metadata }),
},
}
}
@@ -138,8 +139,8 @@ export function errorToolUpdate(input: {
readonly toolCallId: string
readonly toolName: string
readonly input: ToolInput
readonly content: ToolContent
readonly structured: Readonly<Record<string, unknown>>
readonly content?: ToolContent
readonly metadata?: Readonly<Record<string, unknown>>
readonly error: string
readonly cwd?: string
}): ToolCallUpdate {
@@ -150,8 +151,11 @@ export function errorToolUpdate(input: {
title: toolTitle(input.toolName, input.input, undefined),
locations: toLocations(input.toolName, input.input, input.cwd),
rawInput: rawInput(input.toolName, input.input, input.cwd),
content: [...toolContent(input.content), { type: "content", content: { type: "text", text: input.error } }],
rawOutput: { structured: input.structured, error: input.error },
content: [...toolContent(input.content ?? []), { type: "content", content: { type: "text", text: input.error } }],
rawOutput: {
...(input.metadata === undefined ? {} : { metadata: input.metadata }),
error: input.error,
},
}
}
@@ -164,21 +168,6 @@ function toolContent(content: ToolContent): ToolCallContent[] {
})
}
function readDisplayText(structured: Readonly<Record<string, unknown>>) {
if (typeof structured.content === "string") {
if (structured.type === "text-page" || structured.encoding === "utf8") return structured.content
}
if (!Array.isArray(structured.entries)) return undefined
return structured.entries
.flatMap((entry): string[] => {
if (typeof entry === "string") return [entry]
if (!entry || typeof entry !== "object") return []
const path = Reflect.get(entry, "path")
return typeof path === "string" ? [path] : []
})
.join("\n")
}
function toolTitle(toolName: string, input: ToolInput, fallback: string | undefined) {
if (isShell(toolName)) return stringValue(input.command) ?? stringValue(input.cmd) ?? fallback ?? toolName
return fallback || toolName
@@ -10,6 +10,7 @@ import {
Reference,
Skill,
} from "@opencode-ai/plugin/v2"
import { Tool } from "@opencode-ai/plugin/v2/tool"
const key = Symbol.for("opencode.plugin.v2.promise")
;(globalThis as typeof globalThis & { [key]?: unknown })[key] = {
@@ -23,4 +24,5 @@ const key = Symbol.for("opencode.plugin.v2.promise")
Provider,
Reference,
Skill,
Tool,
}
+25 -23
View File
@@ -10,7 +10,7 @@ import type {
import { SessionMessage } from "@opencode-ai/schema/session-message"
import { EOL } from "node:os"
import { readFile } from "node:fs/promises"
import { toolOutputText, type MiniToolPart } from "@opencode-ai/tui/mini/tool"
import { nonEmptyToolContent, toolOutputText, type MiniToolPart } from "@opencode-ai/tui/mini/tool"
import { UI } from "./ui"
type Model = {
@@ -55,7 +55,7 @@ type ToolState = StartedPart & {
raw?: string
provider?: unknown
providerState?: SessionMessageAssistantTool["providerState"]
structured: Record<string, JsonValue>
metadata: Record<string, JsonValue>
content: LLMToolContent[]
}
@@ -306,7 +306,7 @@ export async function runNonInteractivePrompt(input: Input) {
assistantMessageID: event.data.assistantMessageID,
tool: event.data.name,
input: {},
structured: {},
metadata: {},
content: [],
})
continue
@@ -334,7 +334,7 @@ export async function runNonInteractivePrompt(input: Input) {
raw: current?.raw,
provider: { executed: event.data.executed, state: event.data.state },
providerState: event.data.state,
structured: {},
metadata: {},
content: [],
})
continue
@@ -342,8 +342,7 @@ export async function runNonInteractivePrompt(input: Input) {
if (event.type === "session.tool.progress") {
const current = tools.get(toolKey(event.data.assistantMessageID, event.data.callID))
if (current) {
current.structured = event.data.structured
current.content = event.data.content
current.metadata = event.data.metadata
}
continue
}
@@ -360,9 +359,8 @@ export async function runNonInteractivePrompt(input: Input) {
state: {
status: "completed",
input: current.input,
structured: event.data.structured,
metadata: event.data.metadata,
content: event.data.content,
result: event.data.result,
},
time: { created: current.timestamp, ran: current.timestamp, completed: time },
}
@@ -379,9 +377,8 @@ export async function runNonInteractivePrompt(input: Input) {
output: toolOutputText(current.tool, event.data.content),
title: current.tool,
metadata: {
structured: event.data.structured,
metadata: event.data.metadata,
content: event.data.content,
result: event.data.result,
providerCall: current.provider,
providerResult: { executed: event.data.executed, state: event.data.resultState },
rawInput: current.raw,
@@ -398,8 +395,8 @@ export async function runNonInteractivePrompt(input: Input) {
const key = toolKey(event.data.assistantMessageID, event.data.callID)
const current = tools.get(key) ?? fallbackTool(event)
const error = event.data.error.message
const structured = event.data.metadata ?? current.structured
const content = event.data.content ?? current.content
const metadata = event.data.metadata ?? current.metadata
const content = event.data.content ?? nonEmptyToolContent(current.content)
const tool: SessionMessageAssistantTool = {
type: "tool",
id: event.data.callID,
@@ -410,10 +407,9 @@ export async function runNonInteractivePrompt(input: Input) {
state: {
status: "error",
input: current.input,
structured,
metadata,
content,
error: event.data.error,
result: event.data.result,
},
time: { created: current.timestamp, ran: current.timestamp, completed: time },
}
@@ -429,7 +425,6 @@ export async function runNonInteractivePrompt(input: Input) {
input: current.input,
error,
metadata: {
result: event.data.result,
providerCall: current.provider,
providerResult: { executed: event.data.executed, state: event.data.resultState },
rawInput: current.raw,
@@ -441,15 +436,14 @@ export async function runNonInteractivePrompt(input: Input) {
renderedTools.add(key)
if (input.compatibility === "v1" && (permissionRejected || formCancelled)) continue
if (!emit("tool_use", time, { part })) {
if (toolOutputText(current.tool, content).trim())
if (content && toolOutputText(current.tool, content).trim())
await input.renderTool({
...tool,
state: {
status: "completed",
input: current.input,
structured,
metadata,
content,
result: event.data.result,
},
})
await input.renderToolError(tool)
@@ -597,14 +591,14 @@ export async function runNonInteractivePrompt(input: Input) {
input: item.state.input,
output: toolOutputText(item.name, item.state.content),
title: item.name,
metadata: { structured: item.state.structured, content: item.state.content, result: item.state.result },
metadata: { metadata: item.state.metadata, content: item.state.content },
time: { start: item.time.ran ?? item.time.created, end: item.time.completed ?? timestamp },
}
: {
status: "error",
input: item.state.input,
error: item.state.error.message,
metadata: { structured: item.state.structured, content: item.state.content, result: item.state.result },
metadata: { metadata: item.state.metadata, content: item.state.content },
time: { start: item.time.ran ?? item.time.created, end: item.time.completed ?? timestamp },
},
}
@@ -614,8 +608,16 @@ export async function runNonInteractivePrompt(input: Input) {
await input.renderTool(item)
continue
}
if (toolOutputText(item.name, item.state.content).trim()) {
await input.renderTool({ ...item, state: { ...item.state, status: "completed" } })
if (item.state.content && toolOutputText(item.name, item.state.content).trim()) {
await input.renderTool({
...item,
state: {
status: "completed",
input: item.state.input,
metadata: item.state.metadata,
content: item.state.content,
},
})
}
await input.renderToolError(item)
UI.error(item.state.error.message)
@@ -792,7 +794,7 @@ function fallbackTool(event: {
assistantMessageID: event.data.assistantMessageID,
tool: "tool",
input: {},
structured: {},
metadata: {},
content: [],
}
}
+11 -18
View File
@@ -218,8 +218,7 @@ describe("acp event behavior", () => {
sessionID: "ses_tools",
assistantMessageID: "msg_tools",
callID: "call_ok",
structured: { phase: 1 },
content: [{ type: "text", text: "working" }],
metadata: { phase: 1 },
}),
)
send(
@@ -227,9 +226,8 @@ describe("acp event behavior", () => {
sessionID: "ses_tools",
assistantMessageID: "msg_tools",
callID: "call_ok",
structured: { exit: 0 },
metadata: { exit: 0 },
content: [{ type: "text", text: "done" }],
result: { code: 0 },
executed: true,
}),
)
@@ -255,8 +253,7 @@ describe("acp event behavior", () => {
sessionID: "ses_tools",
assistantMessageID: "msg_tools",
callID: "call_fail",
structured: { bytes: 0 },
content: [{ type: "text", text: "opening" }],
metadata: { bytes: 0 },
}),
)
send(
@@ -313,12 +310,10 @@ describe("acp event behavior", () => {
locations: [{ path: resolve("/workspace", "sub") }],
rawInput: { command: "printf done", workdir: "sub" },
})
expect(updates[2]?.update).toMatchObject({
content: [{ type: "content", content: { type: "text", text: "working" } }],
})
expect(updates[2]?.update).not.toHaveProperty("content")
expect(updates[3]?.update).toMatchObject({
content: [{ type: "content", content: { type: "text", text: "done" } }],
rawOutput: { structured: { exit: 0 }, result: { code: 0 } },
rawOutput: { metadata: { exit: 0 } },
})
expect(updates[7]?.update).toMatchObject({
kind: "read",
@@ -327,7 +322,7 @@ describe("acp event behavior", () => {
{ type: "content", content: { type: "text", text: "opening" } },
{ type: "content", content: { type: "text", text: "not found" } },
],
rawOutput: { structured: { bytes: 0 }, error: "not found" },
rawOutput: { metadata: { bytes: 0 }, error: "not found" },
})
expect(response.stopReason).toBe("end_turn")
} finally {
@@ -379,7 +374,7 @@ describe("acp event behavior", () => {
{ type: "content", content: { type: "text", text: "done" } },
{ type: "content", content: { type: "image", mimeType: "image/png", data: "AAAA" } },
],
rawOutput: { structured: { exit: 0 }, result: { code: 0 } },
rawOutput: { metadata: { exit: 0 } },
})
expect(updates[8]?.update).toMatchObject({
toolCallId: "call_running",
@@ -618,12 +613,11 @@ function replayFixtureMessages(): SessionMessageInfo[] {
state: {
status: "completed",
input: { command: "printf done" },
structured: { exit: 0 },
metadata: { exit: 0 },
content: [
{ type: "text", text: "done" },
{ type: "file", uri: "data:image/png;base64,AAAA", mime: "image/png", name: "image.png" },
],
result: { code: 0 },
},
},
{
@@ -634,8 +628,7 @@ function replayFixtureMessages(): SessionMessageInfo[] {
state: {
status: "running",
input: { command: "pwd" },
structured: {},
content: [{ type: "text", text: "/workspace" }],
metadata: {},
},
},
{
@@ -646,7 +639,7 @@ function replayFixtureMessages(): SessionMessageInfo[] {
state: {
status: "error",
input: { filePath: "/workspace/missing.ts" },
structured: { bytes: 0 },
metadata: { bytes: 0 },
content: [{ type: "text", text: "partial" }],
error: { type: "tool.error", message: "failed hard" },
},
@@ -679,7 +672,7 @@ function replayToolMessage(id: string) {
state: {
status: "completed",
input: { command: "printf done" },
structured: { exit: 0 },
metadata: { exit: 0 },
content: [{ type: "text", text: "done" }],
},
},
@@ -28,7 +28,7 @@ describe("acp permission behavior", () => {
cwd: "/workspace",
toolName: "edit",
toolInput: { filePath: "/workspace/file.ts" },
structured: {},
metadata: {},
})
expect(writes).toEqual([])
@@ -193,7 +193,7 @@ describe("acp permission behavior", () => {
sessionID: "ses_edit",
assistantMessageID: "msg_edit",
callID: "call_edit",
structured: { files: [{ file: "file.ts" }], replacements: 1 },
metadata: { files: [{ file: "file.ts" }], replacements: 1 },
content: [{ type: "text", text: "edited" }],
executed: true,
}),
@@ -286,7 +286,7 @@ describe("acp permission behavior", () => {
sessionID: "ses_patch",
assistantMessageID: "msg_patch",
callID: "call_patch",
structured: { files: [{ file: "first.ts" }, { file: "second.ts" }] },
metadata: { files: [{ file: "first.ts" }, { file: "second.ts" }] },
content: [{ type: "text", text: "patched" }],
executed: true,
}),
+33 -30
View File
@@ -63,7 +63,7 @@ describe("acp tools", () => {
{ type: "file", mime: "image/png", name: "image.png", uri: `data:image/png;base64,${image}` },
{ type: "file", mime: "text/plain", name: "note.txt", uri: "data:text/plain;base64,bm90ZQ==" },
],
structured: {},
metadata: {},
}).content,
).toEqual([
{
@@ -93,7 +93,7 @@ describe("acp tools", () => {
content: "created",
},
content: [{ type: "text", text: "wrote /tmp/file.ts" }],
structured: {},
metadata: {},
}).content,
).toEqual([
{
@@ -103,20 +103,22 @@ describe("acp tools", () => {
])
})
test("uses clean structured read content instead of model-facing formatting", () => {
test("unwraps read's JSON page envelope instead of showing model-facing formatting", () => {
expect(
completedToolUpdate({
toolCallId: "tool-read",
toolName: "read",
input: { path: "/tmp/file.ts" },
content: [{ type: "text", text: "<content>1: first\n2: second</content>" }],
structured: {
type: "text-page",
content: "first\nsecond",
mime: "text/plain",
offset: 1,
truncated: false,
},
content: [
{
type: "text",
text: JSON.stringify(
{ type: "text-page", content: "first\nsecond", mime: "text/plain", offset: 1, truncated: false },
null,
2,
),
},
],
}).content,
).toEqual([{ type: "content", content: { type: "text", text: "first\nsecond" } }])
@@ -125,13 +127,17 @@ describe("acp tools", () => {
toolCallId: "tool-list",
toolName: "read",
input: { path: "/tmp" },
content: [],
structured: {
entries: [
{ path: "a.ts", type: "file" },
{ path: "src", type: "directory" },
],
},
content: [
{
type: "text",
text: JSON.stringify({
entries: [
{ path: "a.ts", type: "file" },
{ path: "src", type: "directory" },
],
}),
},
],
}).content,
).toEqual([{ type: "content", content: { type: "text", text: "a.ts\nsrc" } }])
})
@@ -171,7 +177,7 @@ describe("acp tools", () => {
newString: "after",
},
content: [{ type: "text", text: "Edit applied successfully." }],
structured: { output: "Edit applied successfully." },
metadata: { output: "Edit applied successfully." },
}),
).toEqual({
toolCallId: "tool-1",
@@ -189,7 +195,7 @@ describe("acp tools", () => {
},
],
rawOutput: {
structured: { output: "Edit applied successfully." },
metadata: { output: "Edit applied successfully." },
},
})
})
@@ -209,7 +215,7 @@ describe("acp tools", () => {
})
})
test("builds completed raw output with structured data and optional result", () => {
test("builds completed raw output with optional metadata", () => {
const attachments = [
{
type: "file",
@@ -225,12 +231,10 @@ describe("acp tools", () => {
toolName: "read",
input: {},
content: [],
structured: { output: "done", metadata: { exit: 0 }, attachments },
result: "done",
metadata: { output: "done", metadata: { exit: 0 }, attachments },
}).rawOutput,
).toEqual({
structured: { output: "done", metadata: { exit: 0 }, attachments },
result: "done",
metadata: { output: "done", metadata: { exit: 0 }, attachments },
})
expect(
@@ -239,9 +243,8 @@ describe("acp tools", () => {
toolName: "read",
input: {},
content: [],
structured: { output: "done" },
}).rawOutput,
).toEqual({ structured: { output: "done" } })
).toEqual({})
})
test("extracts image attachments only from data URLs", () => {
@@ -255,7 +258,7 @@ describe("acp tools", () => {
{ type: "file", mime: "image/png", uri: "https://example.com/image.png" },
{ type: "file", mime: "text/plain", uri: "data:text/plain;base64,BBBB" },
],
structured: {},
metadata: {},
}).content,
).toEqual([
{
@@ -272,7 +275,7 @@ describe("acp tools", () => {
toolName: "read",
input: { filePath: "/tmp/a" },
content: [{ type: "text", text: "partial output" }],
structured: { path: "/tmp/a" },
metadata: { path: "/tmp/a" },
error: "failed",
}),
).toEqual({
@@ -286,7 +289,7 @@ describe("acp tools", () => {
{ type: "content", content: { type: "text", text: "partial output" } },
{ type: "content", content: { type: "text", text: "failed" } },
],
rawOutput: { structured: { path: "/tmp/a" }, error: "failed" },
rawOutput: { metadata: { path: "/tmp/a" }, error: "failed" },
})
})
})
+6 -1
View File
@@ -23,7 +23,12 @@ describe("CLI frontend import boundaries", () => {
expect(Object.keys(run).sort()).toEqual(["runNonInteractive", "runV1Bridge"])
expect(Object.keys(mini).sort()).toEqual(["runMiniFrontend"])
expect(Object.keys(tool).sort()).toEqual(["toolInlineInfo", "toolOutputText"])
expect(Object.keys(tool).sort()).toEqual([
"nonEmptyToolContent",
"readDisplayText",
"toolInlineInfo",
"toolOutputText",
])
expect(Object.keys(cli.exports).filter((key) => key === "./mini" || key.startsWith("./mini/"))).toEqual([])
})
+11 -14
View File
@@ -134,15 +134,14 @@ function failedTool(inputID: string): V2Event[] {
sessionID: "ses_1",
assistantMessageID: "msg_failed_tool",
callID: "call_failed_tool",
structured: { checkpoint: 1 },
content: [{ type: "text", text: "partial output" }],
metadata: { checkpoint: 1 },
},
},
{
id: "evt_failed_tool_terminal",
created: 4,
type: "session.tool.failed",
durable: { aggregateID: "ses_1", seq: 4, version: 1 },
durable: { aggregateID: "ses_1", seq: 4, version: 2 },
data: {
sessionID: "ses_1",
assistantMessageID: "msg_failed_tool",
@@ -190,12 +189,12 @@ function successfulGrep(inputID: string): V2Event[] {
id: "evt_grep_success",
created: 3,
type: "session.tool.success",
durable: { aggregateID: "ses_1", seq: 3, version: 1 },
durable: { aggregateID: "ses_1", seq: 3, version: 2 },
data: {
sessionID: "ses_1",
assistantMessageID: "msg_grep",
callID: "call_grep",
structured: { matches: 2 },
metadata: { matches: 2 },
content: [{ type: "text", text }],
executed: false,
},
@@ -258,9 +257,7 @@ async function run(input: {
spyOn(sdk.session, "wait").mockImplementation(() => input.wait?.() ?? wait.promise)
spyOn(sdk.message, "list").mockImplementation(() =>
ok({
data: input.messages?.(promptID) ?? [
{ id: promptID, type: "user", text: "hello", time: { created: 1 } },
],
data: input.messages?.(promptID) ?? [{ id: promptID, type: "user", text: "hello", time: { created: 1 } }],
cursor: {},
}),
)
@@ -316,7 +313,7 @@ afterEach(() => {
})
describe("runNonInteractivePrompt", () => {
test("keeps formatted tool output and compact structured metadata in JSON", async () => {
test("keeps formatted tool output and compact tool metadata in JSON", async () => {
const output = await capture({ format: "json", turn: successfulGrep })
const events = output.stdout
.split("\n")
@@ -332,13 +329,13 @@ describe("runNonInteractivePrompt", () => {
status: "completed",
output: expect.stringContaining("Found 2 matches"),
metadata: {
structured: { matches: 2 },
metadata: { matches: 2 },
content: [{ type: "text", text: expect.stringContaining("/src/a.ts") }],
},
},
},
})
expect(events[0].part.state.metadata.structured).toEqual({ matches: 2 })
expect(events[0].part.state.metadata.metadata).toEqual({ matches: 2 })
expect(events[0].part.state.metadata.result).toBeUndefined()
})
@@ -534,7 +531,7 @@ describe("runNonInteractivePrompt", () => {
id: "call_failed_tool",
state: {
status: "completed",
structured: { checkpoint: 1 },
metadata: { checkpoint: 1 },
content: [{ type: "text", text: "partial output" }],
},
},
@@ -544,7 +541,7 @@ describe("runNonInteractivePrompt", () => {
id: "call_failed_tool",
state: {
status: "error",
structured: { checkpoint: 1 },
metadata: { checkpoint: 1 },
content: [{ type: "text", text: "partial output" }],
error: { message: "tool failed" },
},
@@ -574,7 +571,7 @@ describe("runNonInteractivePrompt", () => {
},
})
expect(events[0].part.state.output).toBeUndefined()
expect(events[0].part.state.metadata.structured).toBeUndefined()
expect(events[0].part.state.metadata.metadata).toBeUndefined()
expect(events[0].part.state.metadata.content).toBeUndefined()
expect(output.stderr).toBe("")
})
+8 -4
View File
@@ -75,6 +75,10 @@ export const define = sdk.Plugin.define`
const effectPluginModule = promisePluginModule
.replace("opencode.plugin.v2.promise", "opencode.plugin.v2.effect")
.replace("Promise plugin", "Effect plugin")
const promiseToolModule = `const sdk = globalThis[Symbol.for("opencode.plugin.v2.promise")]
if (!sdk) throw new Error("OpenCode Promise plugin SDK is unavailable")
export const Tool = sdk.Tool
export const make = sdk.Tool.make`
const effectToolModule = `const sdk = globalThis[Symbol.for("opencode.plugin.v2.effect")]
if (!sdk) throw new Error("OpenCode Effect plugin SDK is unavailable")
export const Tool = sdk.Tool
@@ -83,10 +87,8 @@ export const RegistrationError = sdk.Tool.RegistrationError
export const make = sdk.Tool.make
export const validateName = sdk.Tool.validateName
export const registrationEntries = sdk.Tool.registrationEntries
export const withPermission = sdk.Tool.withPermission
export const permission = sdk.Tool.permission
export const definition = sdk.Tool.definition
export const settle = sdk.Tool.settle`
export const validateNamespace = sdk.Tool.validateNamespace
export const toLLMDefinition = sdk.Tool.toLLMDefinition`
return `#!/usr/bin/env -S node ${nodeExecArgv.join(" ")}
import __cjs_mod__ from "node:module"
import { chmodSync as __ocChmod, existsSync as __ocExists, lstatSync as __ocLstat, mkdirSync as __ocMkdir, renameSync as __ocRename, rmSync as __ocRm, writeFileSync as __ocWrite } from "node:fs"
@@ -100,6 +102,7 @@ const require = __cjs_mod__.createRequire(import.meta.url)
const __ocPluginModules = ${JSON.stringify({
"@opencode-ai/plugin/v2": "opencode:plugin-v2",
"@opencode-ai/plugin/v2/plugin": "opencode:plugin-v2-plugin",
"@opencode-ai/plugin/v2/tool": "opencode:plugin-v2-tool",
"@opencode-ai/plugin/v2/effect": "opencode:plugin-v2-effect",
"@opencode-ai/plugin/v2/effect/plugin": "opencode:plugin-v2-effect-plugin",
"@opencode-ai/plugin/v2/effect/tool": "opencode:plugin-v2-effect-tool",
@@ -107,6 +110,7 @@ const __ocPluginModules = ${JSON.stringify({
const __ocPluginSources = ${JSON.stringify({
"opencode:plugin-v2": promiseModule,
"opencode:plugin-v2-plugin": promisePluginModule,
"opencode:plugin-v2-tool": promiseToolModule,
"opencode:plugin-v2-effect": effectModule,
"opencode:plugin-v2-effect-plugin": effectPluginModule,
"opencode:plugin-v2-effect-tool": effectToolModule,
+3 -1
View File
@@ -1,7 +1,9 @@
import type { ModelApi, ProviderApi } from "./api/api.js"
import type { ModelApi, ProviderApi, WebsearchApi } from "./api/api.js"
export type * from "./api/api.js"
export type WebSearchApi<E = never> = WebsearchApi<E>
export interface CatalogApi<E = never> {
readonly provider: ProviderApi<E>
readonly model: ModelApi<E>
+20
View File
@@ -1042,6 +1042,25 @@ export interface DebugApi<E = never> {
readonly location: { readonly list: DebugLocationListOperation<E>; readonly evict: DebugLocationEvictOperation<E> }
}
type Endpoint27_0Request = Parameters<RawClient["server.websearch"]["websearch.providers"]>[0]
export type Endpoint27_0Input = { readonly location?: Endpoint27_0Request["query"]["location"] }
export type Endpoint27_0Output = EffectValue<ReturnType<RawClient["server.websearch"]["websearch.providers"]>>
export type WebsearchProvidersOperation<E = never> = (input?: Endpoint27_0Input) => Effect.Effect<Endpoint27_0Output, E>
type Endpoint27_1Request = Parameters<RawClient["server.websearch"]["websearch.query"]>[0]
export type Endpoint27_1Input = {
readonly location?: Endpoint27_1Request["query"]["location"]
readonly query: Endpoint27_1Request["payload"]["query"]
readonly providerID?: Endpoint27_1Request["payload"]["providerID"]
}
export type Endpoint27_1Output = EffectValue<ReturnType<RawClient["server.websearch"]["websearch.query"]>>
export type WebsearchQueryOperation<E = never> = (input: Endpoint27_1Input) => Effect.Effect<Endpoint27_1Output, E>
export interface WebsearchApi<E = never> {
readonly providers: WebsearchProvidersOperation<E>
readonly query: WebsearchQueryOperation<E>
}
export interface AppApi<E = never> {
readonly health: HealthApi<E>
readonly server: ServerApi<E>
@@ -1070,4 +1089,5 @@ export interface AppApi<E = never> {
readonly projectCopy: ProjectCopyApi<E>
readonly vcs: VcsApi<E>
readonly debug: DebugApi<E>
readonly websearch: WebsearchApi<E>
}
@@ -1244,6 +1244,28 @@ const adaptGroup26 = (raw: RawClient["server.debug"]) => ({
location: { list: Endpoint26_0(raw), evict: Endpoint26_1(raw) },
})
type Endpoint27_0Request = Parameters<RawClient["server.websearch"]["websearch.providers"]>[0]
type Endpoint27_0Input = { readonly location?: Endpoint27_0Request["query"]["location"] }
const Endpoint27_0 = (raw: RawClient["server.websearch"]) => (input?: Endpoint27_0Input) =>
raw["websearch.providers"]({ query: { location: input?.["location"] } }).pipe(Effect.mapError(mapClientError))
type Endpoint27_1Request = Parameters<RawClient["server.websearch"]["websearch.query"]>[0]
type Endpoint27_1Input = {
readonly location?: Endpoint27_1Request["query"]["location"]
readonly query: Endpoint27_1Request["payload"]["query"]
readonly providerID?: Endpoint27_1Request["payload"]["providerID"]
}
const Endpoint27_1 = (raw: RawClient["server.websearch"]) => (input: Endpoint27_1Input) =>
raw["websearch.query"]({
query: { location: input["location"] },
payload: { query: input["query"], providerID: input["providerID"] },
}).pipe(Effect.mapError(mapClientError))
const adaptGroup27 = (raw: RawClient["server.websearch"]) => ({
providers: Endpoint27_0(raw),
query: Endpoint27_1(raw),
})
const adaptClient = (raw: RawClient) => ({
health: adaptGroup0(raw["server.health"]),
server: adaptGroup1(raw["server.server"]),
@@ -1272,6 +1294,7 @@ const adaptClient = (raw: RawClient) => ({
projectCopy: adaptGroup24(raw["server.projectCopy"]),
vcs: adaptGroup25(raw["server.vcs"]),
debug: adaptGroup26(raw["server.debug"]),
websearch: adaptGroup27(raw["server.websearch"]),
})
export const make = (options?: { readonly baseUrl?: URL | string }) =>
+2
View File
@@ -14,6 +14,7 @@ export type {
PluginApi,
ProviderApi,
ReferenceApi,
WebSearchApi,
SessionApi,
SkillApi,
} from "./api.js"
@@ -35,6 +36,7 @@ export { Provider } from "@opencode-ai/schema/provider"
export { Pty } from "@opencode-ai/schema/pty"
export { Question } from "@opencode-ai/schema/question"
export { Reference } from "@opencode-ai/schema/reference"
export { WebSearch } from "@opencode-ai/schema/websearch"
export { AbsolutePath, RelativePath } from "@opencode-ai/schema/schema"
export { Session } from "@opencode-ai/schema/session"
export { SessionPending } from "@opencode-ai/schema/session-pending"
+1
View File
@@ -8,6 +8,7 @@ export type ModelApi = Client["model"]
export type PluginApi = Client["plugin"]
export type ProviderApi = Client["provider"]
export type ReferenceApi = Client["reference"]
export type WebSearchApi = Client["websearch"]
export type SessionApi = Client["session"]
export type SkillApi = Client["skill"]
@@ -207,6 +207,10 @@ import type {
DebugLocationListOutput,
DebugLocationEvictInput,
DebugLocationEvictOutput,
WebsearchProvidersInput,
WebsearchProvidersOutput,
WebsearchQueryInput,
WebsearchQueryOutput,
} from "./types"
import { ClientError } from "./client-error"
@@ -1735,6 +1739,33 @@ export function make(options: ClientOptions) {
),
},
},
websearch: {
providers: (input?: WebsearchProvidersInput, requestOptions?: RequestOptions) =>
request<WebsearchProvidersOutput>(
{
method: "GET",
path: `/api/websearch/provider`,
query: { location: input?.["location"] },
successStatus: 200,
declaredStatuses: [503, 401, 400],
empty: false,
},
requestOptions,
),
query: (input: WebsearchQueryInput, requestOptions?: RequestOptions) =>
request<WebsearchQueryOutput>(
{
method: "POST",
path: `/api/websearch`,
query: { location: input["location"] },
body: { query: input["query"], providerID: input["providerID"] },
successStatus: 200,
declaredStatuses: [400, 503, 401],
empty: false,
},
requestOptions,
),
},
}
}

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