Kit Langton
fc3a1bfd34
Adds the parallel `runNative()` path inside `session/llm.ts` so a narrow slice of sessions can flow through `@opencode-ai/llm` instead of the AI SDK `streamText`. Behavior is gated and shipped off by default; only callers that opt in see any difference. The full migration plan (audit gap #4) is parallel-path-with-flag, prove parity test-by-test, flip default last. This commit is phase 1: get the wire-up in place behind a flag with one protocol so we can see whether the design holds before committing to the full migration. Wire-up summary: - New flag `OPENCODE_EXPERIMENTAL_LLM_NATIVE` (also enabled by the umbrella `OPENCODE_EXPERIMENTAL`). Off by default. - The session-LLM `live` layer now consumes `RequestExecutor.Service`, and the `defaultLayer` provides `RequestExecutor.defaultLayer` so a Node fetch HTTP client backs every native stream. - `runNative(input)` returns `Stream<Event> | undefined`. `undefined` means "fall through to AI SDK." It returns a real stream only when every gate passes: the flag is set, the caller populated `input.nativeMessages` (the bridge needs typed `MessageV2.WithParts`, not the AI SDK `messages` array), the session has zero tools (Phase 2 will lift this), and the bridge routes the model to a protocol in `NATIVE_PROTOCOLS`. - `NATIVE_PROTOCOLS` is a single-entry set today: `anthropic-messages`. Other adapters are imported and registered with the client so the Phase 2 expansion is a one-line edit, not an architecture change. - Stream wiring: client.stream(req) -> Stream.flatMap(event -> fromIterable(map.map(event))) -> Stream.concat(suspended fromIterable(map.flush())) -> Stream.provideService( RequestExecutor.Service, executor). The flush stream is built lazily with `Stream.unwrap(Effect.sync(...))` so it observes the mapper final state after every upstream event has been mapped. - The mapper (`LLMNativeEvents.mapper`) emits AI-SDK-shaped session events from `LLMEvent` so downstream consumers see one shape. What this does NOT do (deferred to later phases): - No tool support on the native path (skipped, falls through). - No parity harness yet; Phase 2 builds it. - No production traffic; flag is off by default and no production caller populates `nativeMessages`. - No reasoning/cache/multi-modal coverage. Anthropic supports reasoning and cache via existing patches, so those start working as soon as a caller routes a real session through. Verification: opencode typecheck clean, bridge tests still green (33/0/0 across llm-native.test.ts + llm-bridge.test.ts); LLM package tests green (123/0/0).
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Installation
# YOLO
curl -fsSL https://opencode.ai/install | bash
# Package managers
npm i -g opencode-ai@latest # or bun/pnpm/yarn
scoop install opencode # Windows
choco install opencode # Windows
brew install anomalyco/tap/opencode # macOS and Linux (recommended, always up to date)
brew install opencode # macOS and Linux (official brew formula, updated less)
sudo pacman -S opencode # Arch Linux (Stable)
paru -S opencode-bin # Arch Linux (Latest from AUR)
mise use -g opencode # Any OS
nix run nixpkgs#opencode # or github:anomalyco/opencode for latest dev branch
Tip
Remove versions older than 0.1.x before installing.
Desktop App (BETA)
OpenCode is also available as a desktop application. Download directly from the releases page or opencode.ai/download.
| Platform | Download |
|---|---|
| macOS (Apple Silicon) | opencode-desktop-darwin-aarch64.dmg |
| macOS (Intel) | opencode-desktop-darwin-x64.dmg |
| Windows | opencode-desktop-windows-x64.exe |
| Linux | .deb, .rpm, or AppImage |
# macOS (Homebrew)
brew install --cask opencode-desktop
# Windows (Scoop)
scoop bucket add extras; scoop install extras/opencode-desktop
Installation Directory
The install script respects the following priority order for the installation path:
$OPENCODE_INSTALL_DIR- Custom installation directory$XDG_BIN_DIR- XDG Base Directory Specification compliant path$HOME/bin- Standard user binary directory (if it exists or can be created)$HOME/.opencode/bin- Default fallback
# Examples
OPENCODE_INSTALL_DIR=/usr/local/bin curl -fsSL https://opencode.ai/install | bash
XDG_BIN_DIR=$HOME/.local/bin curl -fsSL https://opencode.ai/install | bash
Agents
OpenCode includes two built-in agents you can switch between with the Tab key.
- build - Default, full-access agent for development work
- plan - Read-only agent for analysis and code exploration
- Denies file edits by default
- Asks permission before running bash commands
- Ideal for exploring unfamiliar codebases or planning changes
Also included is a general subagent for complex searches and multistep tasks.
This is used internally and can be invoked using @general in messages.
Learn more about agents.
Documentation
For more info on how to configure OpenCode, head over to our docs.
Contributing
If you're interested in contributing to OpenCode, please read our contributing docs before submitting a pull request.
Building on OpenCode
If you are working on a project that's related to OpenCode and is using "opencode" as part of its name, for example "opencode-dashboard" or "opencode-mobile", please add a note to your README to clarify that it is not built by the OpenCode team and is not affiliated with us in any way.
FAQ
How is this different from Claude Code?
It's very similar to Claude Code in terms of capability. Here are the key differences:
- 100% open source
- Not coupled to any provider. Although we recommend the models we provide through OpenCode Zen, OpenCode can be used with Claude, OpenAI, Google, or even local models. As models evolve, the gaps between them will close and pricing will drop, so being provider-agnostic is important.
- Out-of-the-box LSP support
- A focus on TUI. OpenCode is built by neovim users and the creators of terminal.shop; we are going to push the limits of what's possible in the terminal.
- A client/server architecture. This, for example, can allow OpenCode to run on your computer while you drive it remotely from a mobile app, meaning that the TUI frontend is just one of the possible clients.