Bohdan Triapitsyn
34d0ff7383
A diff is ordered by file path, which is almost never the order in which a change makes sense. This adds a Walkthrough surface that reorders it: the model groups related hunks into stops, explains what each group changes about behavior, and orders the stops so each builds on the last. It explains and orders; judging code stays with the existing Review action. Reviews uncommitted work (all, staged, unstaged), a branch against its base, or a pull request. Generation is always user-initiated — nothing runs on a timer, on a file change, or as a side effect of opening a panel. Invariants worth preserving: - Hunk identity is derived on the server and only there. Ids are content hashes, so an anchor that no longer resolves is proof the code it described changed, and staleness needs no heuristics. The client matches ids to ids and never recomputes them; two implementations would have to agree forever. - The digest is never truncated. A diff that does not fit the model's context is refused with an actionable reason, because a walkthrough written against half a diff reads as confident and is wrong. - Nothing disappears. Lockfiles and other generated output are excluded from the model's input by name — never by size — and everything no stop covers is listed at the end, so "have I seen all of it" stays answerable. - Cost is explicit. Results are content-addressed, so returning the working tree to an earlier state costs nothing; generation outlives its request, so a refresh detaches the client rather than discarding paid-for work, and only an explicit cancel stops it. Supporting changes to shared modules: - git: expose the existing getRangeDiff as GET /api/git listUntrackedPaths and getUntrackedDiffs. The latter resolve the repository once for a batch instead of per file, taking a panel ~340ms on an 80-file working tree. - small-model: structured output across four wire forma and abort signal, and an onOverflow policy so an oversized prompt fails loudly instead of being silently clipped. A provider remembered so the prompt-side fallback goes first next time. - models.dev metadata: surface structured_output as tri false blocks a model, a missing field does not, because the catalog omits it for roughly half of all models. Desktop and tablet only: VS Code serves Git through its these routes, and the mobile shell does not consume the surface registry. Docs: packages/docs walkthrough page in English and all eight locales.
127 lines
7.6 KiB
Markdown
127 lines
7.6 KiB
Markdown
# Small Model
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Server-side direct LLM calls that reuse the user's existing OpenCode provider
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logins (`~/.local/share/opencode/auth.json`). OpenCode uses a "small model"
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internally (titles, summaries) but does not expose it through the SDK or
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plugins — this module replicates that mechanism as an OpenChamber runtime API.
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## Security boundary
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Credentials never leave the server process. The client sends only a prompt;
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auth resolution, OAuth refresh, and provider dispatch all happen server-side.
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Routes live under `/api/*` and are gated by the ui-auth middleware like every
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other runtime API.
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## Files
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- `index.js` — orchestration: `generateSmallModelText()` / `describeSmallModel()`.
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- `resolve.js` — model selection, mirroring OpenCode's `getSmallModel` chain:
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0. OpenChamber's own settings override (Settings → Sessions → Small Model):
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when `smallModelUseDefault` is `false`, `smallModelOverride`
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(`provider/model`) outranks everything below. Sanitized in
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`settings-helpers.js` (server), `persistence.ts` (client), and
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`bridge-settings-runtime.ts` (VS Code).
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1. `small_model` from the merged OpenCode config layers (`provider/model`).
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2. Family-priority scan (`gemini-flash` → `gpt-nano` → `claude-haiku`)
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**within the session's provider first** (`preferredProviderID`, like
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OpenCode resolves within the current provider), then over the other
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providers with a usable auth entry, newest `release_date` first.
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3. GitHub Copilot hidden utility models (`gpt-*-nano/mini`) — these never
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appear in the catalog, so they participate as the `gpt-nano` family entry
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and as a final utility fallback.
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4. Last resort: the session's own model (`preferredModelID`) when no small
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model resolves anywhere — costlier, but always valid.
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- Input clamp: the prompt is measured against the resolved model's catalog
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`limit.context` (minus an output reserve, ~4 chars/token estimate;
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conservative default when the model is not in the catalog). `onOverflow`
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decides what an oversized prompt means:
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- `truncate` (default) clips the tail and reports `inputTruncated: true`.
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Correct for callers that degrade gracefully (summaries, commit messages).
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- `error` throws a `413` with `code: 'context-too-small'` plus
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`requiredChars`/`availableChars`. Correct for callers whose output would be
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quietly wrong on a clipped input, so they can ask the user for a roomier
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model instead of returning confident nonsense.
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- Structured output: pass `responseSchema` (a JSON Schema) to get
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schema-shaped JSON back as `text`. Wire support differs per format —
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`response_format: {type: 'json_schema'}` for OpenAI-compatible chat,
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`text.format` for the Responses API, a forced single tool call for the
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Anthropic messages API, and `generationConfig.responseSchema` for Google
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(whose OpenAPI-flavored dialect drops unknown JSON Schema keywords). The
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ChatGPT-plan codex backend has no equivalent and rejects a schema request
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with `code: 'structured-output-unsupported'` rather than silently returning
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prose.
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- Output budget: `maxOutputTokens` is capped at the catalog's `limit.output` for
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the model, and the **same number** is reserved from the input allowance. The
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two must not drift — a caller that asks for a large answer while the reserve
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stays at the default overruns the context, and the failure looks like a
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truncation bug rather than a budgeting one. `describeSmallModel` takes
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`outputReserveTokens` so readiness checks agree with what generation will do.
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- Reasoning models can spend the entire output budget thinking and return
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nothing. That case (empty content with `finish_reason: 'length'`, or content
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empty while `reasoning_content` is populated) throws with
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`code: 'output-exhausted'` so callers can offer a different model instead of
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showing a transport error.
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- `timeoutMs` overrides the 60s default per call; `signal` lets a caller abort
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a request that is no longer wanted. Both apply to every wire format.
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- `describeSmallModel()` additionally reports `inputCharBudget`,
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`contextTokens`, `contextKnown`, and `structuredOutput`. The last is
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tri-state: `true`/`false` from the catalog, `null` when the catalog omits the
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field — which it does for roughly half of all models, aggregators and proxies
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especially. Callers must treat `null` as "try it", not "unsupported".
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- `call.js` — wire formats and per-provider auth, replicating OpenCode's
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plugin auth loaders:
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- **GitHub Copilot**: fetches the requested model's authenticated `/models`
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metadata from `https://api.githubcopilot.com` (or
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`copilot-api.<enterprise>`) and honors its advertised endpoint, preferring
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Anthropic-compatible `/v1/messages`, then OpenAI `/responses`, then
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`/chat/completions`. Models without `supported_endpoints` retain the legacy
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Chat Completions default; metadata, missing-model, and unsupported-endpoint
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failures are surfaced instead of guessing. The stored device-OAuth token is
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used as the bearer with no token exchange or expiry.
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- **OpenAI OAuth (ChatGPT plan)**: streaming Responses API on
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`https://chatgpt.com/backend-api/codex/responses` with
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`ChatGPT-Account-Id`; expired tokens are refreshed against
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`auth.openai.com` (single-flight) and written back to `auth.json`.
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- **Anthropic** (`type: api`): `/v1/messages` with `x-api-key`.
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- **Google** (`type: api`): `generateContent` with `x-goog-api-key`; Gemini 3
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uses `thinkingLevel` while older Flash models use `thinkingBudget: 0`.
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- Everything else: OpenAI-compatible `/chat/completions` against the
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provider's base URL, resolved from (1) `provider.<id>.options.baseURL`
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in the OpenCode config, (2) the hardcoded `https://api.openai.com/v1`
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endpoint, or (3) the provider's `api` field from the models.dev catalog.
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Configured API keys honor OpenCode's `{env:NAME}` and `{file:path}`
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substitutions; file contents and resolved credentials remain server-side.
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- `[small-model:diagnostic]` logs record provider/model, input character
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counts, output budget, thinking toggle, HTTP/finish status, and
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content/reasoning lengths without logging prompts, response text, or
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credentials. Goal audit parsing similarly emits
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`[session-goal:diagnostic]` structural verdict metadata.
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- `catalog.js` — models.dev catalog via the shared in-process cache
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(`../opencode/models-metadata.js`, also serving
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`/api/openchamber/models-metadata`).
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- `routes.js` — `GET /api/small-model` (resolution preview) and
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`POST /api/small-model/generate` (`{ prompt, system?, maxOutputTokens?,
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model?, directory? }` → `{ text, providerID, modelID, source }`).
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## Registration
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Mounted lazily from `feature-routes-runtime.js` (same pattern as quota): the
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module is imported on first request, not at server startup.
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## Known limitations
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- OpenCode's free models (`opencode/big-pickle`, `*-free`) work without a
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token only through OpenCode's own server — direct calls are rejected, and
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piggybacking on their subsidized infra is out of bounds by design. Every
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resolution step therefore requires a usable auth entry for the provider:
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a session on an unauthenticated `opencode` provider falls through to the
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global scan (or a clean 404 on a vanilla setup with no logins).
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- Anthropic OAuth (Claude Pro/Max) entries are not supported — OpenCode itself
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keeps those outside `auth.json` in this generation; only `type: api` keys
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work for Anthropic.
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- Amazon Bedrock, GitLab, Azure and other credential-chain providers are out
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of scope; they need more than a key/token (regions, resource names).
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- Responses from the codex backend are collected from the SSE stream; the
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endpoint itself is non-streaming by design (small utility calls).
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