supplier+deploy/mainnet: LLM_BACKEND=openai via ChatMock proxy
Adds a Codex/ChatGPT backend path for the supplier alongside the
existing Ollama one. The mainnet supplier is repointed at a localhost
ChatMock proxy (RayBytes/ChatMock, pinned :v1.35) that authenticates
against a ChatGPT Pro subscription via OAuth.
- supplier/src/openai.ts: HTTP client for OpenAI-compatible
/v1/chat/completions. Same return shape as ollama.callOllama so
jobRunner can branch cleanly.
- supplier/src/jobRunner.ts: branch on config.llmBackend.
- supplier/src/config.ts: LLM_BACKEND ("ollama" default | "openai"),
OPENAI_BASE_URL, OPENAI_TIMEOUT_MS (default 180_000 — GPT first-token
latency).
- supplier/src/cli/gen-keypair.ts: standalone Ed25519 keypair generator
+ bech32 address derivation. Used to bootstrap a fresh supplier
wallet without round-tripping through tx:post-advert --dry-run.
- deploy/mainnet/docker-compose.chatmock.yml: long-running chatmock
serve + one-shot --profile login flow.
- deploy/mainnet/docker-compose.supplier.yml: rewritten for openai
backend; Traefik routes at mp-suppliers-gpt.vector.apexfusion.org so
the unsuffixed slot stays free for a future supplier with a
different backend.
- tests/unit/supplier-openai.test.ts: unit coverage for callOpenAi.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
david
235
tests/unit/supplier-openai.test.ts
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235
tests/unit/supplier-openai.test.ts
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/**
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* supplier-openai.test.ts — unit tests for supplier/src/openai.ts.
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*
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* Mirrors supplier-ollama.test.ts. All tests mock global.fetch — no real
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* ChatMock / OpenAI process required.
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*
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* Covers:
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* - Request shape: POST to ${baseUrl}/v1/chat/completions, body has model+messages+stream:false
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* - Happy path: parses /v1/chat/completions response, measures wallclock_ms locally
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* - Error: 5xx → OpenAiError reason "openai_failure"
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* - Error: timeout → OpenAiError reason "openai_timeout"
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* - Error: missing choices[0].message.content → OpenAiError reason "openai_malformed"
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*/
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import { describe, it, expect, vi, beforeEach, afterEach } from "vitest";
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import { callOpenAi, OpenAiError } from "../../supplier/src/openai.js";
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const BASE_URL = "http://localhost:8000";
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const MODEL = "gpt-5.4";
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const MESSAGES = [{ role: "user" as const, content: "Hello" }];
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const TIMEOUT_MS = 5_000;
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// ─── Helpers ──────────────────────────────────────────────────────────────────
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function makeFetchOk(body: unknown) {
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return vi.fn().mockResolvedValue({
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ok: true,
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status: 200,
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json: async () => body,
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});
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}
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function makeFetchError(status: number) {
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return vi.fn().mockResolvedValue({
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ok: false,
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status,
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json: async () => ({ error: "server error" }),
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text: async () => "server error",
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});
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}
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function makeOpenAiResponse(content: string, promptTokens = 10, completionTokens = 40) {
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return {
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id: "chatcmpl-test",
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object: "chat.completion",
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model: MODEL,
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choices: [
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{
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index: 0,
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message: { role: "assistant", content },
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finish_reason: "stop",
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},
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],
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usage: {
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prompt_tokens: promptTokens,
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completion_tokens: completionTokens,
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total_tokens: promptTokens + completionTokens,
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},
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};
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}
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// ─── Request shape ─────────────────────────────────────────────────────────
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describe("callOpenAi() — request shape", () => {
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beforeEach(() => {
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vi.stubGlobal("fetch", makeFetchOk(makeOpenAiResponse("Hi there")));
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});
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afterEach(() => {
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vi.restoreAllMocks();
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});
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it("sends POST to ${baseUrl}/v1/chat/completions", async () => {
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await callOpenAi({ baseUrl: BASE_URL, model: MODEL, messages: MESSAGES, timeoutMs: TIMEOUT_MS });
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const [url] = (global.fetch as ReturnType<typeof vi.fn>).mock.calls[0] as [string, RequestInit];
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expect(url).toBe(`${BASE_URL}/v1/chat/completions`);
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});
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it("sends POST method", async () => {
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await callOpenAi({ baseUrl: BASE_URL, model: MODEL, messages: MESSAGES, timeoutMs: TIMEOUT_MS });
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const [, init] = (global.fetch as ReturnType<typeof vi.fn>).mock.calls[0] as [string, RequestInit];
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expect(init.method?.toUpperCase()).toBe("POST");
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});
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it("request body contains model", async () => {
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await callOpenAi({ baseUrl: BASE_URL, model: MODEL, messages: MESSAGES, timeoutMs: TIMEOUT_MS });
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const [, init] = (global.fetch as ReturnType<typeof vi.fn>).mock.calls[0] as [string, RequestInit];
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const body = JSON.parse(init.body as string);
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expect(body.model).toBe(MODEL);
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});
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it("request body contains messages", async () => {
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await callOpenAi({ baseUrl: BASE_URL, model: MODEL, messages: MESSAGES, timeoutMs: TIMEOUT_MS });
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const [, init] = (global.fetch as ReturnType<typeof vi.fn>).mock.calls[0] as [string, RequestInit];
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const body = JSON.parse(init.body as string);
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expect(body.messages).toEqual(MESSAGES);
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});
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it("request body has stream: false", async () => {
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await callOpenAi({ baseUrl: BASE_URL, model: MODEL, messages: MESSAGES, timeoutMs: TIMEOUT_MS });
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const [, init] = (global.fetch as ReturnType<typeof vi.fn>).mock.calls[0] as [string, RequestInit];
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const body = JSON.parse(init.body as string);
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expect(body.stream).toBe(false);
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});
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});
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// ─── Happy path ─────────────────────────────────────────────────────────────
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describe("callOpenAi() — happy path", () => {
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afterEach(() => {
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vi.restoreAllMocks();
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});
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it("returns content from choices[0].message.content", async () => {
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vi.stubGlobal("fetch", makeFetchOk(makeOpenAiResponse("Paris is the capital of France.")));
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const result = await callOpenAi({ baseUrl: BASE_URL, model: MODEL, messages: MESSAGES, timeoutMs: TIMEOUT_MS });
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expect(result.content).toBe("Paris is the capital of France.");
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});
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it("returns prompt_tokens from usage.prompt_tokens", async () => {
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vi.stubGlobal("fetch", makeFetchOk(makeOpenAiResponse("answer", 15, 40)));
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const result = await callOpenAi({ baseUrl: BASE_URL, model: MODEL, messages: MESSAGES, timeoutMs: TIMEOUT_MS });
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expect(result.prompt_tokens).toBe(15);
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});
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it("returns completion_tokens from usage.completion_tokens", async () => {
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vi.stubGlobal("fetch", makeFetchOk(makeOpenAiResponse("answer", 15, 40)));
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const result = await callOpenAi({ baseUrl: BASE_URL, model: MODEL, messages: MESSAGES, timeoutMs: TIMEOUT_MS });
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expect(result.completion_tokens).toBe(40);
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});
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it("wallclock_ms is measured locally (non-negative finite integer)", async () => {
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vi.stubGlobal("fetch", makeFetchOk(makeOpenAiResponse("answer")));
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const result = await callOpenAi({ baseUrl: BASE_URL, model: MODEL, messages: MESSAGES, timeoutMs: TIMEOUT_MS });
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expect(Number.isFinite(result.wallclock_ms)).toBe(true);
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expect(result.wallclock_ms).toBeGreaterThanOrEqual(0);
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});
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it("falls back to 0 token counts when usage block is absent", async () => {
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const body = makeOpenAiResponse("answer");
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delete (body as { usage?: unknown }).usage;
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vi.stubGlobal("fetch", makeFetchOk(body));
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const result = await callOpenAi({ baseUrl: BASE_URL, model: MODEL, messages: MESSAGES, timeoutMs: TIMEOUT_MS });
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expect(result.prompt_tokens).toBe(0);
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expect(result.completion_tokens).toBe(0);
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});
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});
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// ─── Error: 5xx response ────────────────────────────────────────────────────
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describe("callOpenAi() — openai_failure (non-2xx)", () => {
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afterEach(() => {
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vi.restoreAllMocks();
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});
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it("throws OpenAiError with reason openai_failure on 500", async () => {
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vi.stubGlobal("fetch", makeFetchError(500));
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await expect(
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callOpenAi({ baseUrl: BASE_URL, model: MODEL, messages: MESSAGES, timeoutMs: TIMEOUT_MS })
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).rejects.toMatchObject({ reason: "openai_failure" });
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});
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it("throws OpenAiError with reason openai_failure on 401 (Codex auth revoked)", async () => {
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vi.stubGlobal("fetch", makeFetchError(401));
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await expect(
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callOpenAi({ baseUrl: BASE_URL, model: MODEL, messages: MESSAGES, timeoutMs: TIMEOUT_MS })
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).rejects.toMatchObject({ reason: "openai_failure" });
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});
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it("throws OpenAiError (not generic Error) on non-2xx", async () => {
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vi.stubGlobal("fetch", makeFetchError(500));
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await expect(
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callOpenAi({ baseUrl: BASE_URL, model: MODEL, messages: MESSAGES, timeoutMs: TIMEOUT_MS })
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).rejects.toBeInstanceOf(OpenAiError);
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});
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});
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// ─── Error: timeout ─────────────────────────────────────────────────────────
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describe("callOpenAi() — openai_timeout", () => {
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afterEach(() => {
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vi.restoreAllMocks();
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});
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it("throws OpenAiError with reason openai_timeout when AbortSignal fires", async () => {
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const abortErr = new DOMException("The operation was aborted.", "AbortError");
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vi.stubGlobal("fetch", vi.fn().mockRejectedValue(abortErr));
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await expect(
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callOpenAi({ baseUrl: BASE_URL, model: MODEL, messages: MESSAGES, timeoutMs: 10 })
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).rejects.toMatchObject({ reason: "openai_timeout" });
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});
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});
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// ─── Error: malformed response ───────────────────────────────────────────────
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describe("callOpenAi() — openai_malformed", () => {
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afterEach(() => {
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vi.restoreAllMocks();
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});
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it("throws OpenAiError with reason openai_malformed when choices array is missing", async () => {
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vi.stubGlobal("fetch", makeFetchOk({ id: "x", object: "chat.completion", usage: { prompt_tokens: 0, completion_tokens: 0 } }));
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await expect(
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callOpenAi({ baseUrl: BASE_URL, model: MODEL, messages: MESSAGES, timeoutMs: TIMEOUT_MS })
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).rejects.toMatchObject({ reason: "openai_malformed" });
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});
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it("throws OpenAiError with reason openai_malformed when choices array is empty", async () => {
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vi.stubGlobal("fetch", makeFetchOk({ id: "x", object: "chat.completion", choices: [], usage: { prompt_tokens: 0, completion_tokens: 0 } }));
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await expect(
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callOpenAi({ baseUrl: BASE_URL, model: MODEL, messages: MESSAGES, timeoutMs: TIMEOUT_MS })
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).rejects.toMatchObject({ reason: "openai_malformed" });
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});
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it("throws OpenAiError with reason openai_malformed when choices[0].message is missing", async () => {
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vi.stubGlobal("fetch", makeFetchOk({ id: "x", object: "chat.completion", choices: [{ index: 0, finish_reason: "stop" }] }));
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await expect(
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callOpenAi({ baseUrl: BASE_URL, model: MODEL, messages: MESSAGES, timeoutMs: TIMEOUT_MS })
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).rejects.toMatchObject({ reason: "openai_malformed" });
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});
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it("throws OpenAiError with reason openai_malformed when content is null", async () => {
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vi.stubGlobal("fetch", makeFetchOk({ id: "x", object: "chat.completion", choices: [{ index: 0, message: { role: "assistant", content: null }, finish_reason: "stop" }] }));
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await expect(
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callOpenAi({ baseUrl: BASE_URL, model: MODEL, messages: MESSAGES, timeoutMs: TIMEOUT_MS })
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).rejects.toMatchObject({ reason: "openai_malformed" });
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});
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it("throws OpenAiError with reason openai_malformed when content is empty string", async () => {
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vi.stubGlobal("fetch", makeFetchOk(makeOpenAiResponse("")));
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await expect(
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callOpenAi({ baseUrl: BASE_URL, model: MODEL, messages: MESSAGES, timeoutMs: TIMEOUT_MS })
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).rejects.toMatchObject({ reason: "openai_malformed" });
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});
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});
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Reference in New Issue
Block a user