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cold-audit catch from 2026-05-23
Batched 4 small P3 mechanical cleanups per Iron Rule 11 IDR cleanup-batch
convention (all P3, all small, no semantic feature changes beyond defensive
validation).
Changes (7 files):
1. lib/ir/ir-to-openai.mjs (+30 / -3) — Finding 8 defensive validator:
- Added OPENAI_FINISH_REASON_ENUM Set with the 6 spec-allowed values
(stop / length / tool_calls / content_filter / function_call / null)
- Added normalizeFinishReason(value) helper that returns value unchanged
if in enum, else 'stop'
- Routed both irChunkToOpenAISSE (streaming path) and
irResponseToOpenAINonStream (non-stream path) through the helper
- Bonus tightening (in-scope, same finish_reason concept):
irResponseToOpenAINonStream's gate changed from `if (chunk.finish_reason)`
(truthy check) to `if (chunk.finish_reason !== undefined)` so an
explicit null (valid spec value meaning "still in progress") is no
longer silently dropped by the truthy guard
- Note: undefined → null collapse via `?? null` is unreachable in the
current codebase (all provider plugins explicitly set finish_reason
on stop chunks); defensive only against a future plugin that omits
the field — documented inline
2. .github/workflows/alignment.yml (-16) — Finding 14 dead CI cleanup:
- Removed `setup.mjs` from path triggers (push + pull_request) — the
file does not exist in the repo
- Removed the dead `KNOWN_PROVIDERS=(...)` bash array from job 1 and
its comment block — no later step iterated over it, so the array
was abandoned
- LEFT untouched: the Node.js inline KNOWN_PROVIDERS array in the
models-registry validation job — that one is actively consumed by
the schema validation script
3. lib/providers/anthropic.mjs / codex.mjs / mistral.mjs (3 × 1 line) —
Finding 15: removed unused `PROVIDER_ERROR_CODES` from import lines.
Each line went from `import { ProviderError, PROVIDER_ERROR_CODES } from
'./base.mjs';` to `import { ProviderError } from './base.mjs';`. The
constant remains exported from base.mjs (its declaration site, where
it IS used for validation).
4. server.mjs (1 line) — D17 reviewer's observation: removed unused
`getProviderForModel` from the import line. The function is only
called by lib/fallback/engine.mjs which imports it directly from
lib/providers/index.mjs. server.mjs's import was dead (the routing
SPOT lives in engine.mjs after D17 — server.mjs uses buildDefaultChain
exclusively).
5. test-features.mjs (+44) — Suite 3 (irChunkToOpenAISSE format) extended
with 4 new finish_reason normalization tests:
- Test 1: non-spec streaming finish_reason ('timeout', 'overloaded',
'cancelled') → mapped to 'stop'
- Test 2: spec-enum streaming finish_reason (all 6 incl. null) preserved
- Test 3: non-spec non-stream finish_reason → mapped to 'stop'
- Test 4: spec-enum non-stream finish_reason preserved (null
intentionally omitted — documented inline)
Tests: 324 → 328 (+4). All pass on Node 20.
Pre-commit fold-ins (per evidence-first checkpoint #4):
- **D19 reviewer suggestion #1**: added inline comment to
normalizeFinishReason explaining the unreachable `undefined → null`
branch (defensive only, no current plugin omits the field). Cheap
future-reader clarity.
- **D19 reviewer suggestion #2**: added inline comment to Test 4
explaining why null is intentionally omitted from the spec-enum list
(non-stream `!== undefined` gate enters with null and overwrites
default 'stop' to null — semantically odd but spec-valid).
Reviewer suggestion #3 (consider stricter `undefined → 'stop'` on
streaming-stop path vs `null → null` on delta path) explicitly marked
out of scope by reviewer — would require call-site context awareness;
filed mentally as potential future work, not tracked as an issue
since no current path triggers it.
Authority:
- ALIGNMENT.md Rule 2(b) — only spec-defined fields in OpenAI responses
- OpenAI Chat Completions spec finish_reason enum
https://platform.openai.com/docs/api-reference/chat/object#finish_reason
- CC 开发铁律 v1.6 § 10.x — Cold Audit Findings 8 / 14 / 15
Reviewer (Iron Rule v1.6 § 10.x Mode A, fresh-context opus, independent
of drafter): APPROVE. Verified the unreachable `undefined → null` branch
claim by grep-checking all 3 provider plugins (none emit undefined);
verified the two KNOWN_PROVIDERS arrays were correctly distinguished
(only the dead bash one removed); ran npm test independently to confirm
328/328.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
202 lines
6.8 KiB
JavaScript
202 lines
6.8 KiB
JavaScript
/**
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* lib/ir/ir-to-openai.mjs — IR v1.0 → OpenAI Chat Completions response translation
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*
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* Authority: ADR 0003 § "Translation direction model" (symmetric)
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* Entry-surface authority: OpenAI Chat Completions API response shape
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* https://platform.openai.com/docs/api-reference/chat/object
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* https://platform.openai.com/docs/api-reference/chat/streaming
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*
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* Produces OpenAI-shaped responses from IR response chunks so that the
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* entry surface (server.mjs) can emit them to clients without knowing
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* which provider generated them.
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*/
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import { randomBytes } from 'node:crypto';
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// ── finish_reason enum guard ───────────────────────────────────────────────
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/**
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* OpenAI-spec finish_reason enum (including null).
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* Ref: https://platform.openai.com/docs/api-reference/chat/object#finish_reason
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*/
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const OPENAI_FINISH_REASON_ENUM = new Set([
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'stop', 'length', 'tool_calls', 'content_filter', 'function_call', null,
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]);
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/**
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* Maps a raw finish_reason value to an OpenAI-spec enum member.
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* Non-spec values (e.g. 'timeout', 'overloaded') are silently normalized to
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* 'stop' so that OLP never emits a spec-violating finish_reason to clients.
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*
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* @param {string|null|undefined} value
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* @returns {string|null}
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*/
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function normalizeFinishReason(value) {
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// Note: `value ?? null` collapses undefined → null (which IS a valid spec
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// value meaning "still in progress"). All current provider plugins explicitly
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// set finish_reason on stop chunks (anthropic defaults to 'stop'; codex /
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// mistral always set a value), so the undefined branch is unreachable in the
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// current codebase — defensive only against a future plugin that omits the
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// field.
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const v = value ?? null;
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if (OPENAI_FINISH_REASON_ENUM.has(v)) return v;
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return 'stop';
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}
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// ── ID generation ─────────────────────────────────────────────────────────
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/**
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* Generates a random chat-completion request ID.
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* OpenAI format: chatcmpl-<alphanumeric>
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* @returns {string}
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*/
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export function generateRequestId() {
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return `chatcmpl-${randomBytes(12).toString('base64url')}`;
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}
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// ── Streaming translation ─────────────────────────────────────────────────
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/**
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* Converts a single IRResponseChunk to an OpenAI SSE event string.
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*
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* Per OpenAI streaming spec, each chunk is a `chat.completion.chunk` object
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* with a `choices[0].delta` field.
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*
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* @param {import('./types.mjs').IRResponseChunk} irChunk
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* @param {string} requestId - from generateRequestId()
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* @param {string} model - the model string from the IR request
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* @returns {string} SSE line in the form `data: {...}\n\n`
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*/
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export function irChunkToOpenAISSE(irChunk, requestId, model) {
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const created = Math.floor(Date.now() / 1000);
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if (irChunk.type === 'stop') {
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const chunk = {
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id: requestId,
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object: 'chat.completion.chunk',
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created,
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model,
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choices: [{
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index: 0,
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delta: {},
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finish_reason: normalizeFinishReason(irChunk.finish_reason),
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}],
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};
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// Include usage if the provider surfaced token counts on the final chunk
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if (irChunk.usage) {
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chunk.usage = irChunk.usage;
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}
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return `data: ${JSON.stringify(chunk)}\n\n`;
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}
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// Note: type === 'error' is intentionally not handled here.
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// Error chunks are converted to thrown ProviderError in server.mjs before
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// they reach this translator (see collectAllChunks and the real-streaming
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// error path). Per ALIGNMENT.md Rule 2 (b), adding a top-level `error`
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// field on chat.completion.chunk objects is a spec violation — OpenAI errors
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// surface via HTTP 4xx/5xx with {error: {...}} body, not in-band SSE fields.
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// If an error chunk somehow reaches here it falls through to the delta path
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// which is a no-op (no content/role/tool_calls), producing an empty delta.
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// type === 'delta'
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const delta = {};
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if (irChunk.role !== undefined) {
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delta.role = irChunk.role;
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}
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if (typeof irChunk.content === 'string' && irChunk.content !== '') {
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delta.content = irChunk.content;
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} else if (irChunk.content === '') {
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// Empty string delta is valid — pass through (first chunk often role-only + empty content)
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delta.content = '';
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}
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if (Array.isArray(irChunk.tool_calls) && irChunk.tool_calls.length > 0) {
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delta.tool_calls = irChunk.tool_calls;
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}
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const chunk = {
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id: requestId,
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object: 'chat.completion.chunk',
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created,
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model,
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choices: [{
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index: 0,
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delta,
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finish_reason: null,
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}],
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};
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return `data: ${JSON.stringify(chunk)}\n\n`;
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}
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/** SSE stream terminator per OpenAI spec */
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export const SSE_DONE = 'data: [DONE]\n\n';
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// ── Non-streaming translation ─────────────────────────────────────────────
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/**
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* Assembles a non-streaming OpenAI chat.completion object from an array of
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* IR response chunks (all chunks already collected from the provider).
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*
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* @param {import('./types.mjs').IRResponseChunk[]} irChunks
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* @param {string} requestId
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* @param {string} model
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* @returns {object} OpenAI chat.completion object
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*/
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export function irResponseToOpenAINonStream(irChunks, requestId, model) {
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let content = '';
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let finish_reason = 'stop';
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let usage = null;
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const tool_calls = [];
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for (const chunk of irChunks) {
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if (chunk.type === 'delta') {
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if (typeof chunk.content === 'string') {
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content += chunk.content;
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}
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if (Array.isArray(chunk.tool_calls)) {
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tool_calls.push(...chunk.tool_calls);
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}
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} else if (chunk.type === 'stop') {
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if (chunk.finish_reason !== undefined) {
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finish_reason = normalizeFinishReason(chunk.finish_reason);
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}
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if (chunk.usage) {
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usage = chunk.usage;
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}
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}
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// Note: type === 'error' is intentionally not handled here.
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// Error chunks are converted to thrown ProviderError in server.mjs
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// (collectAllChunks) before this function is ever called. Adding a
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// top-level `error` field on chat.completion objects violates
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// ALIGNMENT.md Rule 2 (b) — OpenAI errors surface via HTTP 4xx/5xx
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// with {error: {...}} body, not as invented response fields.
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}
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const message = {
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role: 'assistant',
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content: content || null,
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};
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if (tool_calls.length > 0) {
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message.tool_calls = tool_calls;
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if (!content) message.content = null;
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}
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const response = {
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id: requestId,
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object: 'chat.completion',
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created: Math.floor(Date.now() / 1000),
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model,
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choices: [{
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index: 0,
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message,
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finish_reason,
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}],
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};
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if (usage) {
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response.usage = usage;
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}
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return response;
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}
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