fix(open-sse): treat CommandCode in-stream error events as request failures
Upstream emits AI SDK v5 {"type":"error"} events inside an HTTP 200 stream.
The translator turned them into fake success content ([CommandCode error: ...]
+ finish_reason stop), so account/model fallback never fired and logs showed
Status: success.
- translator: error events now emit an OpenAI-shaped error chunk (chunk.error)
instead of content; parseSSEToOpenAIResponse already detects chunk?.error
- executor: peek the first events before committing the response; an early
error event returns 502 so fallback runs before any byte reaches the client
This commit is contained in:
@@ -1,6 +1,7 @@
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import { randomUUID } from "crypto";
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import { BaseExecutor } from "./base.js";
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import { PROVIDERS } from "../config/providers.js";
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import { HTTP_STATUS } from "../config/runtimeConfig.js";
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import { commandCodeToOpenAIResponse } from "../translator/response/commandcode-to-openai.js";
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import { SSE_DONE } from "../utils/sseConstants.js";
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@@ -14,81 +15,268 @@ import { SSE_DONE } from "../utils/sseConstants.js";
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* We translate each event to an OpenAI chat.completion.chunk and emit it as SSE so
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* both the streaming and non-streaming (forced SSE → JSON) downstream handlers in
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* 9router can consume it without further format translation.
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*
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* Terminal upstream failures arrive as `{"type":"error"}` events inside the HTTP
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* 200 stream, so a plain `response.ok` check cannot see them. We peek the first
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* events before committing the response (see peekForUpstreamError) so a stream
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* that starts with an error fails fast — the normal `!response.ok` path then
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* triggers account/model fallback instead of streaming fake success content.
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*/
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export class CommandCodeExecutor extends BaseExecutor {
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constructor() {
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super("commandcode", PROVIDERS.commandcode);
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}
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constructor() {
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super("commandcode", PROVIDERS.commandcode);
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}
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transformRequest(model, body, stream, credentials) {
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body.stream = true;
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return body;
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}
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transformRequest(model, body, stream, credentials) {
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body.stream = true;
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return body;
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}
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buildHeaders(credentials, stream = true) {
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const headers = {
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"Content-Type": "application/json",
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...(this.config.headers || {}),
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"x-session-id": randomUUID(),
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};
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buildHeaders(credentials, stream = true) {
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const headers = {
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"Content-Type": "application/json",
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...(this.config.headers || {}),
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"x-session-id": randomUUID(),
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};
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const token = credentials?.apiKey || credentials?.accessToken;
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if (token) headers["Authorization"] = `Bearer ${token}`;
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const token = credentials?.apiKey || credentials?.accessToken;
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if (token) headers["Authorization"] = `Bearer ${token}`;
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if (stream) headers["Accept"] = "text/event-stream";
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return headers;
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}
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if (stream) headers["Accept"] = "text/event-stream";
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return headers;
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}
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async execute(opts) {
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const result = await super.execute(opts);
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if (!result?.response?.ok || !result.response.body) return result;
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result.response = wrapNdjsonAsOpenAISse(result.response, opts.model);
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return result;
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}
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async execute(opts) {
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const result = await super.execute(opts);
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if (!result?.response?.ok || !result.response.body) return result;
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result.response = await peekForUpstreamError(result.response, opts.model, {
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signal: opts.signal,
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});
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return result;
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}
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}
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// How long to hold the response open while peeking the first upstream events.
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// An upstream error event ("Network connection lost") is emitted at stream
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// start, so the peek is fast; the bound just prevents a slow-started stream
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// from being held hostage. Env: COMMANDCODE_PEEK_TIMEOUT_MS.
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const PEEK_TIMEOUT_MS = (() => {
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const raw = process.env.COMMANDCODE_PEEK_TIMEOUT_MS;
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const n = raw ? parseInt(raw, 10) : NaN;
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return Number.isFinite(n) && n > 0 ? n : 10 * 1000;
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})();
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// Event types that count as "the stream has started producing". Everything
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// else (start, start-step, reasoning-start, text-start, ...) is metadata and
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// does not end the peek.
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const MEANINGFUL_EVENT_TYPES = new Set([
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"text-delta",
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"reasoning-delta",
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"tool-input-start",
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"tool-input-delta",
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"tool-input-end",
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"tool-call",
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"finish-step",
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"finish",
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]);
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function makeAbortError(reason) {
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const error = new Error(reason?.message || reason || "Request aborted");
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error.name = "AbortError";
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return error;
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}
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function tryParseEvent(line) {
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const trimmed = line.trim();
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if (!trimmed) return null;
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const json = trimmed.startsWith("data:") ? trimmed.slice(5).trim() : trimmed;
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if (!json || json === "[DONE]") return null;
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try {
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return JSON.parse(json);
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} catch {
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return null;
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}
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}
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function formatErrorValue(errVal) {
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const errStr =
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typeof errVal === "string"
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? errVal
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: typeof errVal?.message === "string"
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? errVal.message
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: JSON.stringify(errVal);
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const errType =
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typeof errVal === "string"
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? "upstream_error"
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: errVal?.type || "upstream_error";
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return { message: errStr, type: errType };
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}
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/**
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* Read the first upstream events before committing the response.
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*
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* - `{"type":"error"}` as the first meaningful event → return a 502 Response so
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* chatCore's `!response.ok` path parses the error and triggers fallback.
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* - Otherwise → re-emit the buffered bytes + the rest of the stream through the
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* normal NDJSON → OpenAI SSE wrapper and return it untouched in spirit.
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*
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* Bounded by `timeoutMs` (default PEEK_TIMEOUT_MS): if no meaningful event
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* arrives in time, or the request signal aborts, we commit whatever we have and
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* let the regular stream pipeline (stall detection, abort handling) take over.
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*/
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export async function peekForUpstreamError(
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originalResponse,
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model,
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{ signal = null, timeoutMs = PEEK_TIMEOUT_MS } = {},
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) {
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const reader = originalResponse.body.getReader();
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const decoder = new TextDecoder();
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const encoder = new TextEncoder();
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const abortController = new AbortController();
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const forwardAbort = () => abortController.abort(signal?.reason);
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if (signal?.aborted) abortController.abort(signal?.reason);
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else if (signal)
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signal.addEventListener("abort", forwardAbort, { once: true });
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let peeked = "";
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let errorEvent = null;
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let committed = false;
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const readWithTimeout = (ms) => {
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if (abortController.signal.aborted) {
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return Promise.reject(makeAbortError(abortController.signal.reason));
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}
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const timeoutPromise = new Promise((_, reject) => {
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const t = setTimeout(() => reject(new Error("peek timeout")), ms);
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t.unref?.();
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});
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const abortPromise = new Promise((_, reject) => {
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abortController.signal.addEventListener(
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"abort",
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() => reject(makeAbortError(abortController.signal.reason)),
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{ once: true },
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);
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});
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return Promise.race([reader.read(), timeoutPromise, abortPromise]);
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};
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try {
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const deadline = Date.now() + timeoutMs;
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while (!errorEvent && !committed && Date.now() < deadline) {
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const { done, value } = await readWithTimeout(
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Math.max(deadline - Date.now(), 1),
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);
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if (done) break;
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peeked += decoder.decode(value, { stream: true });
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const lines = peeked.split("\n");
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// The last segment may be a partial line — only parse complete ones.
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for (const line of lines.slice(0, -1)) {
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const event = tryParseEvent(line);
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if (!event?.type) continue;
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if (event.type === "error") {
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errorEvent = event;
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break;
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}
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if (MEANINGFUL_EVENT_TYPES.has(event.type)) {
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committed = true;
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break;
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}
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}
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}
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} catch {
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// timeout / abort / read failure during the peek → commit whatever we have;
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// the downstream stream pipeline (stall detection, abort handling) takes over.
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}
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// Flush any partial multi-byte UTF-8 sequence held by the decoder so the
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// re-encoded peeked bytes round-trip losslessly.
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peeked += decoder.decode();
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if (signal) signal.removeEventListener("abort", forwardAbort);
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if (errorEvent) {
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await reader.cancel("commandcode early error detected").catch(() => {});
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const { message, type } = formatErrorValue(
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errorEvent.error ?? errorEvent.message ?? "unknown",
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);
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return new Response(JSON.stringify({ error: { message, type } }), {
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status: HTTP_STATUS.BAD_GATEWAY,
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statusText: message.slice(0, 200),
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headers: { "Content-Type": "application/json" },
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});
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}
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const remaining = new ReadableStream({
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start(controller) {
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(async () => {
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try {
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if (peeked) controller.enqueue(encoder.encode(peeked));
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while (true) {
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const { done, value } = await reader.read();
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if (done) break;
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controller.enqueue(value);
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}
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controller.close();
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} catch (err) {
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controller.error(err);
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}
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})();
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},
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cancel() {
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reader.cancel("commandcode stream cancelled").catch(() => {});
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},
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});
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const combined = new Response(remaining, {
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status: originalResponse.status,
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statusText: originalResponse.statusText,
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headers: originalResponse.headers,
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});
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return wrapNdjsonAsOpenAISse(combined, model);
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}
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function wrapNdjsonAsOpenAISse(originalResponse, model) {
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const decoder = new TextDecoder();
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const encoder = new TextEncoder();
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let buffer = "";
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const state = { model };
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const decoder = new TextDecoder();
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const encoder = new TextEncoder();
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let buffer = "";
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const state = { model };
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const emitChunks = (chunks, controller) => {
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if (!chunks) return;
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const list = Array.isArray(chunks) ? chunks : [chunks];
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for (const c of list) {
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if (c == null) continue;
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controller.enqueue(encoder.encode(`data: ${JSON.stringify(c)}\n\n`));
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}
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};
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const emitChunks = (chunks, controller) => {
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if (!chunks) return;
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const list = Array.isArray(chunks) ? chunks : [chunks];
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for (const c of list) {
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if (c == null) continue;
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controller.enqueue(encoder.encode(`data: ${JSON.stringify(c)}\n\n`));
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}
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};
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const transform = new TransformStream({
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transform(chunk, controller) {
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buffer += decoder.decode(chunk, { stream: true });
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const lines = buffer.split("\n");
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buffer = lines.pop() || "";
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for (const line of lines) {
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const trimmed = line.trim();
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if (!trimmed) continue;
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// Translate AI SDK v5 NDJSON line to one or more OpenAI chunks
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emitChunks(commandCodeToOpenAIResponse(trimmed, state), controller);
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}
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},
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flush(controller) {
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const trimmed = buffer.trim();
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if (trimmed) {
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emitChunks(commandCodeToOpenAIResponse(trimmed, state), controller);
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}
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controller.enqueue(encoder.encode(SSE_DONE));
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},
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});
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const transform = new TransformStream({
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transform(chunk, controller) {
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buffer += decoder.decode(chunk, { stream: true });
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const lines = buffer.split("\n");
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buffer = lines.pop() || "";
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for (const line of lines) {
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const trimmed = line.trim();
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if (!trimmed) continue;
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// Translate AI SDK v5 NDJSON line to one or more OpenAI chunks
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emitChunks(commandCodeToOpenAIResponse(trimmed, state), controller);
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}
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},
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flush(controller) {
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const trimmed = buffer.trim();
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if (trimmed) {
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emitChunks(commandCodeToOpenAIResponse(trimmed, state), controller);
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}
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controller.enqueue(encoder.encode(SSE_DONE));
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},
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});
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const newBody = originalResponse.body.pipeThrough(transform);
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return new Response(newBody, {
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status: originalResponse.status,
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statusText: originalResponse.statusText,
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headers: originalResponse.headers,
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});
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const newBody = originalResponse.body.pipeThrough(transform);
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return new Response(newBody, {
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status: originalResponse.status,
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statusText: originalResponse.statusText,
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headers: originalResponse.headers,
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});
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}
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export default CommandCodeExecutor;
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@@ -25,160 +25,198 @@ import { fallbackToolCallId } from "../concerns/toolCall.js";
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import { toOpenAIFinish } from "../concerns/finishReason.js";
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function ensureState(state, model) {
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if (!state.responseId) {
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state.responseId = `chatcmpl-${Date.now()}`;
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state.created = Math.floor(Date.now() / 1000);
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state.model = state.model || model || "commandcode";
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state.chunkIndex = 0;
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state.toolIndex = 0;
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state.toolIndexById = new Map();
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state.openTools = new Set();
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state.openText = false;
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state.finishReason = null;
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state.usage = null;
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}
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if (!state.responseId) {
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state.responseId = `chatcmpl-${Date.now()}`;
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state.created = Math.floor(Date.now() / 1000);
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state.model = state.model || model || "commandcode";
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state.chunkIndex = 0;
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state.toolIndex = 0;
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state.toolIndexById = new Map();
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state.openTools = new Set();
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state.openText = false;
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state.finishReason = null;
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state.usage = null;
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}
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}
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function makeChunk(state, delta, finishReason = null) {
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return buildChunk(
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{ id: state.responseId, created: state.created, model: state.model },
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delta,
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finishReason
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);
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return buildChunk(
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{ id: state.responseId, created: state.created, model: state.model },
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delta,
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finishReason,
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);
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}
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const mapFinishReason = (reason) => toOpenAIFinish(reason, "commandcode");
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export function commandCodeToOpenAIResponse(chunk, state) {
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if (!chunk) return null;
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if (!chunk) return null;
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// Already-OpenAI chunk: pass through
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if (chunk && typeof chunk === "object" && chunk.object === "chat.completion.chunk") {
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return chunk;
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}
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// Already-OpenAI chunk: pass through
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if (
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chunk &&
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typeof chunk === "object" &&
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chunk.object === "chat.completion.chunk"
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) {
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return chunk;
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}
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// Parse string lines coming out of upstream
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let event = chunk;
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if (typeof chunk === "string") {
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const line = chunk.trim();
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if (!line) return null;
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// Tolerate raw "data: {...}" framing if the upstream wrapper inserts it
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const json = line.startsWith("data:") ? line.slice(5).trim() : line;
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if (!json || json === "[DONE]") return null;
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try {
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event = JSON.parse(json);
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} catch {
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return null;
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}
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}
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// Parse string lines coming out of upstream
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let event = chunk;
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if (typeof chunk === "string") {
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const line = chunk.trim();
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if (!line) return null;
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// Tolerate raw "data: {...}" framing if the upstream wrapper inserts it
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const json = line.startsWith("data:") ? line.slice(5).trim() : line;
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if (!json || json === "[DONE]") return null;
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try {
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event = JSON.parse(json);
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} catch {
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return null;
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}
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}
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if (!event || typeof event !== "object" || !event.type) return null;
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if (!event || typeof event !== "object" || !event.type) return null;
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ensureState(state, event.model);
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const out = [];
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ensureState(state, event.model);
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const out = [];
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switch (event.type) {
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case "text-delta": {
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const text = event.text || event.delta || "";
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if (!text) break;
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const delta = state.chunkIndex === 0 ? { role: ROLE.ASSISTANT, content: text } : { content: text };
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state.chunkIndex++;
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state.openText = true;
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out.push(makeChunk(state, delta));
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break;
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}
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case "reasoning-delta": {
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const text = event.text || "";
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if (!text) break;
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// Map reasoning to OpenAI "reasoning_content" field (used by deepseek-reasoner-style clients).
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const delta = reasoningDelta(text, state.chunkIndex === 0);
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state.chunkIndex++;
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out.push(makeChunk(state, delta));
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break;
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}
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case "tool-input-start": {
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const id = event.id || event.toolCallId || fallbackToolCallId(state.toolIndex);
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let idx = state.toolIndexById.get(id);
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if (idx == null) {
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idx = state.toolIndex++;
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state.toolIndexById.set(id, idx);
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}
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state.openTools.add(id);
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const delta = {
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...(state.chunkIndex === 0 ? { role: ROLE.ASSISTANT } : {}),
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tool_calls: [{
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index: idx,
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id,
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type: OPENAI_BLOCK.FUNCTION,
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function: { name: event.toolName || "", arguments: "" },
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}],
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};
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state.chunkIndex++;
|
||||
out.push(makeChunk(state, delta));
|
||||
break;
|
||||
}
|
||||
case "tool-input-delta": {
|
||||
const id = event.id || event.toolCallId;
|
||||
const idx = state.toolIndexById.get(id);
|
||||
if (idx == null) break;
|
||||
const delta = {
|
||||
tool_calls: [{
|
||||
index: idx,
|
||||
function: { arguments: event.delta || event.inputTextDelta || "" },
|
||||
}],
|
||||
};
|
||||
out.push(makeChunk(state, delta));
|
||||
break;
|
||||
}
|
||||
case "tool-call": {
|
||||
// Final consolidated tool call — only emit if we never saw tool-input-* deltas.
|
||||
const id = event.toolCallId;
|
||||
if (state.toolIndexById.has(id)) break;
|
||||
const idx = state.toolIndex++;
|
||||
state.toolIndexById.set(id, idx);
|
||||
const argsStr = typeof event.input === "string" ? event.input : JSON.stringify(event.input ?? {});
|
||||
const delta = {
|
||||
...(state.chunkIndex === 0 ? { role: ROLE.ASSISTANT } : {}),
|
||||
tool_calls: [{
|
||||
index: idx,
|
||||
id,
|
||||
type: OPENAI_BLOCK.FUNCTION,
|
||||
function: { name: event.toolName || "", arguments: argsStr },
|
||||
}],
|
||||
};
|
||||
state.chunkIndex++;
|
||||
out.push(makeChunk(state, delta));
|
||||
break;
|
||||
}
|
||||
case "finish-step": {
|
||||
state.finishReason = mapFinishReason(event.finishReason);
|
||||
if (event.usage) state.usage = event.usage;
|
||||
break;
|
||||
}
|
||||
case "finish": {
|
||||
const finishReason = state.finishReason || mapFinishReason(event.finishReason || "stop");
|
||||
const finalChunk = makeChunk(state, {}, finishReason);
|
||||
const totalUsage = event.totalUsage || state.usage;
|
||||
const usage = toOpenAIUsage(totalUsage, "commandcode");
|
||||
if (usage) finalChunk.usage = usage;
|
||||
out.push(finalChunk);
|
||||
break;
|
||||
}
|
||||
case "error": {
|
||||
state.finishReason = OPENAI_FINISH.STOP;
|
||||
const errVal = event.error ?? event.message ?? "unknown";
|
||||
const errStr = typeof errVal === "string" ? errVal : JSON.stringify(errVal);
|
||||
out.push(makeChunk(state, { content: `\n\n[CommandCode error: ${errStr}]` }));
|
||||
out.push(makeChunk(state, {}, OPENAI_FINISH.STOP));
|
||||
break;
|
||||
}
|
||||
// Silently ignore: start, start-step, reasoning-start, reasoning-end, text-start, text-end,
|
||||
// provider-metadata, message-metadata, etc. They carry no client-visible content.
|
||||
default:
|
||||
break;
|
||||
}
|
||||
switch (event.type) {
|
||||
case "text-delta": {
|
||||
const text = event.text || event.delta || "";
|
||||
if (!text) break;
|
||||
const delta =
|
||||
state.chunkIndex === 0
|
||||
? { role: ROLE.ASSISTANT, content: text }
|
||||
: { content: text };
|
||||
state.chunkIndex++;
|
||||
state.openText = true;
|
||||
out.push(makeChunk(state, delta));
|
||||
break;
|
||||
}
|
||||
case "reasoning-delta": {
|
||||
const text = event.text || "";
|
||||
if (!text) break;
|
||||
// Map reasoning to OpenAI "reasoning_content" field (used by deepseek-reasoner-style clients).
|
||||
const delta = reasoningDelta(text, state.chunkIndex === 0);
|
||||
state.chunkIndex++;
|
||||
out.push(makeChunk(state, delta));
|
||||
break;
|
||||
}
|
||||
case "tool-input-start": {
|
||||
const id =
|
||||
event.id || event.toolCallId || fallbackToolCallId(state.toolIndex);
|
||||
let idx = state.toolIndexById.get(id);
|
||||
if (idx == null) {
|
||||
idx = state.toolIndex++;
|
||||
state.toolIndexById.set(id, idx);
|
||||
}
|
||||
state.openTools.add(id);
|
||||
const delta = {
|
||||
...(state.chunkIndex === 0 ? { role: ROLE.ASSISTANT } : {}),
|
||||
tool_calls: [
|
||||
{
|
||||
index: idx,
|
||||
id,
|
||||
type: OPENAI_BLOCK.FUNCTION,
|
||||
function: { name: event.toolName || "", arguments: "" },
|
||||
},
|
||||
],
|
||||
};
|
||||
state.chunkIndex++;
|
||||
out.push(makeChunk(state, delta));
|
||||
break;
|
||||
}
|
||||
case "tool-input-delta": {
|
||||
const id = event.id || event.toolCallId;
|
||||
const idx = state.toolIndexById.get(id);
|
||||
if (idx == null) break;
|
||||
const delta = {
|
||||
tool_calls: [
|
||||
{
|
||||
index: idx,
|
||||
function: { arguments: event.delta || event.inputTextDelta || "" },
|
||||
},
|
||||
],
|
||||
};
|
||||
out.push(makeChunk(state, delta));
|
||||
break;
|
||||
}
|
||||
case "tool-call": {
|
||||
// Final consolidated tool call — only emit if we never saw tool-input-* deltas.
|
||||
const id = event.toolCallId;
|
||||
if (state.toolIndexById.has(id)) break;
|
||||
const idx = state.toolIndex++;
|
||||
state.toolIndexById.set(id, idx);
|
||||
const argsStr =
|
||||
typeof event.input === "string"
|
||||
? event.input
|
||||
: JSON.stringify(event.input ?? {});
|
||||
const delta = {
|
||||
...(state.chunkIndex === 0 ? { role: ROLE.ASSISTANT } : {}),
|
||||
tool_calls: [
|
||||
{
|
||||
index: idx,
|
||||
id,
|
||||
type: OPENAI_BLOCK.FUNCTION,
|
||||
function: { name: event.toolName || "", arguments: argsStr },
|
||||
},
|
||||
],
|
||||
};
|
||||
state.chunkIndex++;
|
||||
out.push(makeChunk(state, delta));
|
||||
break;
|
||||
}
|
||||
case "finish-step": {
|
||||
state.finishReason = mapFinishReason(event.finishReason);
|
||||
if (event.usage) state.usage = event.usage;
|
||||
break;
|
||||
}
|
||||
case "finish": {
|
||||
const finishReason =
|
||||
state.finishReason || mapFinishReason(event.finishReason || "stop");
|
||||
const finalChunk = makeChunk(state, {}, finishReason);
|
||||
const totalUsage = event.totalUsage || state.usage;
|
||||
const usage = toOpenAIUsage(totalUsage, "commandcode");
|
||||
if (usage) finalChunk.usage = usage;
|
||||
out.push(finalChunk);
|
||||
break;
|
||||
}
|
||||
case "error": {
|
||||
// Terminal upstream failure (AI SDK v5 error event) — NOT content. Emit an
|
||||
// OpenAI-shaped error chunk (chunk.error) so downstream — parseSSEToOpenAIResponse
|
||||
// for non-streaming, OpenAI SDK clients for streaming — treats the request as
|
||||
// failed instead of surfacing fake success content like "[CommandCode error: ...]".
|
||||
state.finishReason = OPENAI_FINISH.STOP;
|
||||
const errVal = event.error ?? event.message ?? "unknown";
|
||||
const errStr =
|
||||
typeof errVal === "string"
|
||||
? errVal
|
||||
: typeof errVal?.message === "string"
|
||||
? errVal.message
|
||||
: JSON.stringify(errVal);
|
||||
const errType =
|
||||
typeof errVal === "string"
|
||||
? "upstream_error"
|
||||
: errVal?.type || "upstream_error";
|
||||
const errChunk = makeChunk(state, {});
|
||||
errChunk.error = { message: errStr, type: errType };
|
||||
out.push(errChunk);
|
||||
out.push(makeChunk(state, {}, OPENAI_FINISH.STOP));
|
||||
break;
|
||||
}
|
||||
// Silently ignore: start, start-step, reasoning-start, reasoning-end, text-start, text-end,
|
||||
// provider-metadata, message-metadata, etc. They carry no client-visible content.
|
||||
default:
|
||||
break;
|
||||
}
|
||||
|
||||
return out.length ? out : null;
|
||||
return out.length ? out : null;
|
||||
}
|
||||
|
||||
register(FORMATS.COMMANDCODE, FORMATS.OPENAI, null, commandCodeToOpenAIResponse);
|
||||
register(
|
||||
FORMATS.COMMANDCODE,
|
||||
FORMATS.OPENAI,
|
||||
null,
|
||||
commandCodeToOpenAIResponse,
|
||||
);
|
||||
|
||||
101
tests/unit/commandcode-executor.test.js
Normal file
101
tests/unit/commandcode-executor.test.js
Normal file
@@ -0,0 +1,101 @@
|
||||
/**
|
||||
* Unit tests for the CommandCode executor early-error peek.
|
||||
*
|
||||
* The upstream emits AI SDK v5 NDJSON over an HTTP 200 stream, so a terminal
|
||||
* `{"type":"error"}` event is invisible to the normal `response.ok` success
|
||||
* check. `peekForUpstreamError` reads the first events before committing the
|
||||
* response: an error event → non-ok Response (fallback can kick in); otherwise
|
||||
* the buffered bytes are re-emitted and streaming proceeds as before.
|
||||
*/
|
||||
import { describe, it, expect } from "vitest";
|
||||
import { peekForUpstreamError } from "../../open-sse/executors/commandcode.js";
|
||||
|
||||
const encoder = new TextEncoder();
|
||||
|
||||
function ndjsonResponse(lines) {
|
||||
const body = new ReadableStream({
|
||||
start(controller) {
|
||||
for (const line of lines) controller.enqueue(encoder.encode(line + "\n"));
|
||||
controller.close();
|
||||
},
|
||||
});
|
||||
return new Response(body, {
|
||||
status: 200,
|
||||
headers: { "content-type": "text/event-stream" },
|
||||
});
|
||||
}
|
||||
|
||||
describe("commandcode executor — early-error peek", () => {
|
||||
it("returns 502 when the first meaningful event is an error", async () => {
|
||||
const res = await peekForUpstreamError(
|
||||
ndjsonResponse([
|
||||
'{"type":"error","error":{"type":"server_error","message":"Network connection lost."}}',
|
||||
]),
|
||||
"model",
|
||||
);
|
||||
expect(res.status).toBe(502);
|
||||
const body = await res.json();
|
||||
expect(body.error.message).toBe("Network connection lost.");
|
||||
expect(body.error.type).toBe("server_error");
|
||||
});
|
||||
|
||||
it("detects an error event even when metadata events arrive first", async () => {
|
||||
const res = await peekForUpstreamError(
|
||||
ndjsonResponse([
|
||||
'{"type":"start"}',
|
||||
'{"type":"start-step"}',
|
||||
'{"type":"error","error":{"type":"server_error","message":"Network connection lost."}}',
|
||||
]),
|
||||
"model",
|
||||
);
|
||||
expect(res.status).toBe(502);
|
||||
const body = await res.json();
|
||||
expect(body.error.message).toContain("Network connection lost");
|
||||
});
|
||||
|
||||
it("commits and streams normally when the first meaningful event is content", async () => {
|
||||
const res = await peekForUpstreamError(
|
||||
ndjsonResponse([
|
||||
'{"type":"start"}',
|
||||
'{"type":"text-delta","text":"hi there"}',
|
||||
'{"type":"finish"}',
|
||||
]),
|
||||
"model",
|
||||
);
|
||||
expect(res.status).toBe(200);
|
||||
const text = await res.text();
|
||||
expect(text).toContain('"content":"hi there"');
|
||||
expect(text).not.toContain("[CommandCode error:");
|
||||
});
|
||||
|
||||
it("commits when the stream ends without any event", async () => {
|
||||
const res = await peekForUpstreamError(ndjsonResponse([]), "model");
|
||||
expect(res.status).toBe(200);
|
||||
await res.body.cancel();
|
||||
});
|
||||
|
||||
it("commits (does not hang) when no event arrives before the peek timeout", async () => {
|
||||
const stalled = new Response(new ReadableStream({ start() {} }), {
|
||||
status: 200,
|
||||
headers: { "content-type": "text/event-stream" },
|
||||
});
|
||||
const res = await peekForUpstreamError(stalled, "model", { timeoutMs: 50 });
|
||||
expect(res.status).toBe(200);
|
||||
await res.body.cancel();
|
||||
});
|
||||
|
||||
it("does not hang when the request signal aborts during the peek", async () => {
|
||||
const controller = new AbortController();
|
||||
const stalled = new Response(new ReadableStream({ start() {} }), {
|
||||
status: 200,
|
||||
headers: { "content-type": "text/event-stream" },
|
||||
});
|
||||
setTimeout(() => controller.abort(new Error("client gone")), 10);
|
||||
const res = await peekForUpstreamError(stalled, "model", {
|
||||
signal: controller.signal,
|
||||
timeoutMs: 2000,
|
||||
});
|
||||
expect(res.status).toBe(200);
|
||||
await res.body.cancel();
|
||||
});
|
||||
});
|
||||
@@ -12,116 +12,152 @@ import { describe, it, expect } from "vitest";
|
||||
import { commandCodeToOpenAIResponse } from "../../open-sse/translator/response/commandcode-to-openai.js";
|
||||
|
||||
function feed(events) {
|
||||
const state = {};
|
||||
const all = [];
|
||||
for (const e of events) {
|
||||
const out = commandCodeToOpenAIResponse(JSON.stringify(e), state);
|
||||
if (out) for (const c of out) all.push(c);
|
||||
}
|
||||
return { state, chunks: all };
|
||||
const state = {};
|
||||
const all = [];
|
||||
for (const e of events) {
|
||||
const out = commandCodeToOpenAIResponse(JSON.stringify(e), state);
|
||||
if (out) for (const c of out) all.push(c);
|
||||
}
|
||||
return { state, chunks: all };
|
||||
}
|
||||
|
||||
describe("commandcode-to-openai — text-delta", () => {
|
||||
it("emits assistant role on first delta then content-only", () => {
|
||||
const { chunks } = feed([
|
||||
{ type: "text-delta", text: "Hello" },
|
||||
{ type: "text-delta", text: " world" },
|
||||
]);
|
||||
expect(chunks[0].choices[0].delta.role).toBe("assistant");
|
||||
expect(chunks[0].choices[0].delta.content).toBe("Hello");
|
||||
expect(chunks[1].choices[0].delta.role).toBeUndefined();
|
||||
expect(chunks[1].choices[0].delta.content).toBe(" world");
|
||||
});
|
||||
it("emits assistant role on first delta then content-only", () => {
|
||||
const { chunks } = feed([
|
||||
{ type: "text-delta", text: "Hello" },
|
||||
{ type: "text-delta", text: " world" },
|
||||
]);
|
||||
expect(chunks[0].choices[0].delta.role).toBe("assistant");
|
||||
expect(chunks[0].choices[0].delta.content).toBe("Hello");
|
||||
expect(chunks[1].choices[0].delta.role).toBeUndefined();
|
||||
expect(chunks[1].choices[0].delta.content).toBe(" world");
|
||||
});
|
||||
});
|
||||
|
||||
describe("commandcode-to-openai — reasoning-delta", () => {
|
||||
it("maps reasoning-delta to reasoning_content delta", () => {
|
||||
const { chunks } = feed([
|
||||
{ type: "reasoning-delta", text: "thinking..." },
|
||||
]);
|
||||
expect(chunks[0].choices[0].delta.reasoning_content).toBe("thinking...");
|
||||
});
|
||||
it("maps reasoning-delta to reasoning_content delta", () => {
|
||||
const { chunks } = feed([{ type: "reasoning-delta", text: "thinking..." }]);
|
||||
expect(chunks[0].choices[0].delta.reasoning_content).toBe("thinking...");
|
||||
});
|
||||
});
|
||||
|
||||
describe("commandcode-to-openai — tool-input-* with id field (live schema)", () => {
|
||||
it("registers tool index using event.id (NOT toolCallId)", () => {
|
||||
const { chunks } = feed([
|
||||
{ type: "tool-input-start", id: "call_X", toolName: "Bash" },
|
||||
{ type: "tool-input-delta", id: "call_X", delta: "{\"cmd" },
|
||||
{ type: "tool-input-delta", id: "call_X", delta: "\":\"ls\"}" },
|
||||
]);
|
||||
it("registers tool index using event.id (NOT toolCallId)", () => {
|
||||
const { chunks } = feed([
|
||||
{ type: "tool-input-start", id: "call_X", toolName: "Bash" },
|
||||
{ type: "tool-input-delta", id: "call_X", delta: '{"cmd' },
|
||||
{ type: "tool-input-delta", id: "call_X", delta: '":"ls"}' },
|
||||
]);
|
||||
|
||||
// First chunk emits tool_calls with id
|
||||
const startChunk = chunks[0].choices[0].delta.tool_calls[0];
|
||||
expect(startChunk.id).toBe("call_X");
|
||||
expect(startChunk.function.name).toBe("Bash");
|
||||
// First chunk emits tool_calls with id
|
||||
const startChunk = chunks[0].choices[0].delta.tool_calls[0];
|
||||
expect(startChunk.id).toBe("call_X");
|
||||
expect(startChunk.function.name).toBe("Bash");
|
||||
|
||||
// Subsequent deltas accumulate arguments
|
||||
expect(chunks[1].choices[0].delta.tool_calls[0].function.arguments).toBe("{\"cmd");
|
||||
expect(chunks[2].choices[0].delta.tool_calls[0].function.arguments).toBe("\":\"ls\"}");
|
||||
});
|
||||
// Subsequent deltas accumulate arguments
|
||||
expect(chunks[1].choices[0].delta.tool_calls[0].function.arguments).toBe(
|
||||
'{"cmd',
|
||||
);
|
||||
expect(chunks[2].choices[0].delta.tool_calls[0].function.arguments).toBe(
|
||||
'":"ls"}',
|
||||
);
|
||||
});
|
||||
|
||||
it("ignores tool-input-delta when id is unknown (no prior start)", () => {
|
||||
const { chunks } = feed([
|
||||
{ type: "tool-input-delta", id: "unknown", delta: "x" },
|
||||
]);
|
||||
expect(chunks.length).toBe(0);
|
||||
});
|
||||
it("ignores tool-input-delta when id is unknown (no prior start)", () => {
|
||||
const { chunks } = feed([
|
||||
{ type: "tool-input-delta", id: "unknown", delta: "x" },
|
||||
]);
|
||||
expect(chunks.length).toBe(0);
|
||||
});
|
||||
});
|
||||
|
||||
describe("commandcode-to-openai — final tool-call event", () => {
|
||||
it("does NOT re-emit tool_calls when tool-input-* deltas already fired", () => {
|
||||
const { chunks } = feed([
|
||||
{ type: "tool-input-start", id: "call_Y", toolName: "Write" },
|
||||
{ type: "tool-input-delta", id: "call_Y", delta: "{\"file\":\"a\"}" },
|
||||
{ type: "tool-call", toolCallId: "call_Y", toolName: "Write", input: { file: "a" } },
|
||||
]);
|
||||
// Should be exactly 2 chunks (start + delta), no duplicate from final tool-call
|
||||
expect(chunks.length).toBe(2);
|
||||
});
|
||||
it("does NOT re-emit tool_calls when tool-input-* deltas already fired", () => {
|
||||
const { chunks } = feed([
|
||||
{ type: "tool-input-start", id: "call_Y", toolName: "Write" },
|
||||
{ type: "tool-input-delta", id: "call_Y", delta: '{"file":"a"}' },
|
||||
{
|
||||
type: "tool-call",
|
||||
toolCallId: "call_Y",
|
||||
toolName: "Write",
|
||||
input: { file: "a" },
|
||||
},
|
||||
]);
|
||||
// Should be exactly 2 chunks (start + delta), no duplicate from final tool-call
|
||||
expect(chunks.length).toBe(2);
|
||||
});
|
||||
|
||||
it("emits a consolidated tool_calls when only the final tool-call event arrives", () => {
|
||||
const { chunks } = feed([
|
||||
{ type: "tool-call", toolCallId: "call_Z", toolName: "Read", input: { path: "/x" } },
|
||||
]);
|
||||
expect(chunks.length).toBe(1);
|
||||
const tc = chunks[0].choices[0].delta.tool_calls[0];
|
||||
expect(tc.id).toBe("call_Z");
|
||||
expect(tc.function.name).toBe("Read");
|
||||
expect(tc.function.arguments).toBe(JSON.stringify({ path: "/x" }));
|
||||
});
|
||||
it("emits a consolidated tool_calls when only the final tool-call event arrives", () => {
|
||||
const { chunks } = feed([
|
||||
{
|
||||
type: "tool-call",
|
||||
toolCallId: "call_Z",
|
||||
toolName: "Read",
|
||||
input: { path: "/x" },
|
||||
},
|
||||
]);
|
||||
expect(chunks.length).toBe(1);
|
||||
const tc = chunks[0].choices[0].delta.tool_calls[0];
|
||||
expect(tc.id).toBe("call_Z");
|
||||
expect(tc.function.name).toBe("Read");
|
||||
expect(tc.function.arguments).toBe(JSON.stringify({ path: "/x" }));
|
||||
});
|
||||
});
|
||||
|
||||
describe("commandcode-to-openai — finish", () => {
|
||||
it("emits a final chunk with finish_reason=tool_calls when finishReason is tool-calls", () => {
|
||||
const { chunks } = feed([
|
||||
{ type: "tool-input-start", id: "call_F", toolName: "Bash" },
|
||||
{ type: "tool-input-delta", id: "call_F", delta: "{}" },
|
||||
{ type: "finish-step", finishReason: "tool-calls" },
|
||||
{ type: "finish" },
|
||||
]);
|
||||
const last = chunks[chunks.length - 1];
|
||||
expect(last.choices[0].finish_reason).toBe("tool_calls");
|
||||
});
|
||||
it("emits a final chunk with finish_reason=tool_calls when finishReason is tool-calls", () => {
|
||||
const { chunks } = feed([
|
||||
{ type: "tool-input-start", id: "call_F", toolName: "Bash" },
|
||||
{ type: "tool-input-delta", id: "call_F", delta: "{}" },
|
||||
{ type: "finish-step", finishReason: "tool-calls" },
|
||||
{ type: "finish" },
|
||||
]);
|
||||
const last = chunks[chunks.length - 1];
|
||||
expect(last.choices[0].finish_reason).toBe("tool_calls");
|
||||
});
|
||||
|
||||
it("includes usage on the final chunk when totalUsage provided", () => {
|
||||
const { chunks } = feed([
|
||||
{ type: "text-delta", text: "hi" },
|
||||
{ type: "finish-step", finishReason: "stop", usage: { inputTokens: 10, outputTokens: 5, totalTokens: 15 } },
|
||||
{ type: "finish", totalUsage: { inputTokens: 10, outputTokens: 5, totalTokens: 15 } },
|
||||
]);
|
||||
const last = chunks[chunks.length - 1];
|
||||
expect(last.usage).toEqual({ prompt_tokens: 10, completion_tokens: 5, total_tokens: 15 });
|
||||
});
|
||||
it("includes usage on the final chunk when totalUsage provided", () => {
|
||||
const { chunks } = feed([
|
||||
{ type: "text-delta", text: "hi" },
|
||||
{
|
||||
type: "finish-step",
|
||||
finishReason: "stop",
|
||||
usage: { inputTokens: 10, outputTokens: 5, totalTokens: 15 },
|
||||
},
|
||||
{
|
||||
type: "finish",
|
||||
totalUsage: { inputTokens: 10, outputTokens: 5, totalTokens: 15 },
|
||||
},
|
||||
]);
|
||||
const last = chunks[chunks.length - 1];
|
||||
expect(last.usage).toEqual({
|
||||
prompt_tokens: 10,
|
||||
completion_tokens: 5,
|
||||
total_tokens: 15,
|
||||
});
|
||||
});
|
||||
});
|
||||
|
||||
describe("commandcode-to-openai — error event", () => {
|
||||
it("stringifies object errors so client sees readable message", () => {
|
||||
const { chunks } = feed([
|
||||
{ type: "error", error: { type: "server_error", message: "Boom" } },
|
||||
]);
|
||||
const text = chunks[0].choices[0].delta.content;
|
||||
expect(text).toContain("Boom");
|
||||
expect(text).not.toContain("[object Object]");
|
||||
});
|
||||
it("emits an OpenAI-shaped error chunk instead of fake success content", () => {
|
||||
const { chunks } = feed([
|
||||
{ type: "error", error: { type: "server_error", message: "Boom" } },
|
||||
]);
|
||||
expect(chunks[0].error).toEqual({ message: "Boom", type: "server_error" });
|
||||
expect(chunks[0].choices[0].delta.content).toBeUndefined();
|
||||
expect(chunks[1].choices[0].finish_reason).toBe("stop");
|
||||
expect(JSON.stringify(chunks)).not.toContain("[CommandCode error:");
|
||||
});
|
||||
|
||||
it("keeps the stream terminal so clients do not hang waiting for more", () => {
|
||||
const { chunks } = feed([
|
||||
{ type: "start" },
|
||||
{
|
||||
type: "error",
|
||||
error: { type: "server_error", message: "Network connection lost." },
|
||||
},
|
||||
]);
|
||||
expect(chunks[0].error.message).toBe("Network connection lost.");
|
||||
expect(chunks[1].choices[0].finish_reason).toBe("stop");
|
||||
});
|
||||
});
|
||||
|
||||
Reference in New Issue
Block a user