a8b50f5109
---ci---
project: ci
phase: 6
milestone: v0.9
status: complete
artifacts:
tags: [v0.9.0]
decisions:
- id: D-047
decision: v0.9 theme = Distribution & Expansion
rationale: npm publish + OpenAI/Anthropic backends + agent flesh + parallel execution
confidence: 0.92
- id: D-049
decision: Feature milestone — patch tags v0.8.1-v0.8.6 then v0.9.0
rationale: OpenAI backend, agent flesh, npm publish all feat
confidence: 0.95
- id: D-059
decision: Rename OllamaBaseBackend to LLMBaseBackend + thin OllamaBaseBackend subclass
rationale: 15 of 17 methods backend-agnostic
confidence: 0.92
- id: D-060
decision: OpenAI/Anthropic backends use native fetch() not SDK packages
rationale: No dependency bloat; fetch native in Node 18+
confidence: 0.85
- id: D-066
decision: Concurrency limiter internal (no p-limit dependency)
rationale: 15 lines; avoids dependency for trivial feature
confidence: 0.90
- id: D-067
decision: Promise.allSettled for review agents at orchestrator lines 373-400
rationale: Current sequential loop replaced with parallel execution
confidence: 0.88
requirements:
covered: [PUBLISH-01, PUBLISH-02, PUBLISH-03, PUBLISH-04, OPENAI-01, OPENAI-02, OPENAI-03, OPENAI-04, OPENAI-05, FLESH-01, FLESH-02, FLESH-03, FLESH-04, FLESH-05, ANTHROPIC-01, ANTHROPIC-02, FLESH-06, FLESH-07, NPM-01, NPM-02, PARALLEL-01, PARALLEL-02, PARALLEL-03, INTEG-01, INTEG-02, INTEG-03, INTEG-04, INTEG-05]
---/ci---
6 phases, 28 tasks, 4077 net lines added, 57 test suites, 527 tests, zero stub agents
279 lines
8.8 KiB
TypeScript
279 lines
8.8 KiB
TypeScript
import { OpenAIBackend } from "../backends/openai.js";
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import { ChatCompletionResponse } from "../backends/llm-base.js";
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describe("OpenAIBackend", () => {
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const originalFetch = globalThis.fetch;
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let fetchCalls: Array<{ url: string; headers: Record<string, string>; body: string }>;
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beforeEach(() => {
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fetchCalls = [];
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});
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afterEach(() => {
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globalThis.fetch = originalFetch;
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delete process.env.TEST_OPENAI_KEY;
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delete process.env.TEST_OPENAI_KEY_EMPTY;
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});
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function mockFetch(response: ChatCompletionResponse, status = 200): void {
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globalThis.fetch = ((url: string, init: RequestInit) => {
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fetchCalls.push({
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url,
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headers: (init.headers as Record<string, string>) || {},
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body: init.body as string,
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});
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return Promise.resolve({
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ok: status >= 200 && status < 300,
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status,
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text: () => Promise.resolve(JSON.stringify(response)),
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json: () => Promise.resolve(response),
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} as Response);
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}) as typeof fetch;
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}
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describe("isAvailable", () => {
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it("returns true when API key is present", async () => {
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process.env.TEST_OPENAI_KEY = "sk-test-key-123";
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const backend = new OpenAIBackend({
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base_url: "https://api.openai.com/v1",
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api_key_env: "TEST_OPENAI_KEY",
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model: "gpt-4o",
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model_profile: "quality",
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});
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expect(await backend.isAvailable()).toBe(true);
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});
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it("returns false when API key is absent", async () => {
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const backend = new OpenAIBackend({
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base_url: "https://api.openai.com/v1",
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api_key_env: "NONEXISTENT_OPENAI_KEY_VAR_99999",
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model: "gpt-4o",
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model_profile: "quality",
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});
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expect(await backend.isAvailable()).toBe(false);
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});
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it("returns false when API key is empty string", async () => {
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process.env.TEST_OPENAI_KEY_EMPTY = "";
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const backend = new OpenAIBackend({
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base_url: "https://api.openai.com/v1",
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api_key_env: "TEST_OPENAI_KEY_EMPTY",
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model: "gpt-4o",
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model_profile: "quality",
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});
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expect(await backend.isAvailable()).toBe(false);
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});
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});
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describe("resolveModel", () => {
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it("returns config.model when set", async () => {
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process.env.TEST_OPENAI_KEY = "sk-test";
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mockFetch({
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choices: [{ message: { content: '{"success": true, "output": "done"}' } }],
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usage: { prompt_tokens: 10, completion_tokens: 20, total_tokens: 30 },
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});
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const backend = new OpenAIBackend({
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base_url: "https://api.openai.com/v1",
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api_key_env: "TEST_OPENAI_KEY",
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model: "gpt-4o-mini",
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model_profile: "speed",
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});
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const request = {
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persona: "executor" as const,
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workflow: "execute",
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task: "test",
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context: {
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project_path: "/tmp",
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phase: 1,
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stage: "execute" as const,
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specification: "",
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config_path: "",
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},
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autonomy: "full" as const,
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};
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await backend.execute(request);
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const body = JSON.parse(fetchCalls[0].body);
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expect(body.model).toBe("gpt-4o-mini");
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});
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it("defaults to gpt-4o when model not specified", async () => {
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process.env.TEST_OPENAI_KEY = "sk-test";
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mockFetch({
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choices: [{ message: { content: '{"success": true, "output": "done"}' } }],
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usage: { prompt_tokens: 10, completion_tokens: 20, total_tokens: 30 },
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});
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const backend = new OpenAIBackend({
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base_url: "https://api.openai.com/v1",
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api_key_env: "TEST_OPENAI_KEY",
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model: "",
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model_profile: "quality",
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});
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const request = {
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persona: "executor" as const,
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workflow: "execute",
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task: "test",
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context: {
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project_path: "/tmp",
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phase: 1,
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stage: "execute" as const,
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specification: "",
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config_path: "",
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},
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autonomy: "full" as const,
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};
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await backend.execute(request);
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const body = JSON.parse(fetchCalls[0].body);
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expect(body.model).toBe("gpt-4o");
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});
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});
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describe("callModel request format", () => {
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it("sends correct URL, Authorization header, and body structure", async () => {
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process.env.TEST_OPENAI_KEY = "sk-test-key-abc";
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const mockResponse: ChatCompletionResponse = {
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choices: [{ message: { content: '{"success": true, "output": "done"}' } }],
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usage: { prompt_tokens: 10, completion_tokens: 20, total_tokens: 30 },
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};
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mockFetch(mockResponse);
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const backend = new OpenAIBackend({
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base_url: "https://api.openai.com/v1",
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api_key_env: "TEST_OPENAI_KEY",
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model: "gpt-4o",
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model_profile: "quality",
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});
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const request = {
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persona: "executor" as const,
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workflow: "execute",
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task: "Do the thing",
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context: {
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project_path: "/tmp",
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phase: 1,
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stage: "execute" as const,
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specification: "",
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config_path: "",
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},
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autonomy: "full" as const,
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};
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await backend.execute(request);
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expect(fetchCalls.length).toBe(1);
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expect(fetchCalls[0].url).toBe("https://api.openai.com/v1/chat/completions");
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expect(fetchCalls[0].headers["Authorization"]).toBe("Bearer sk-test-key-abc");
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expect(fetchCalls[0].headers["Content-Type"]).toBe("application/json");
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const body = JSON.parse(fetchCalls[0].body);
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expect(body.model).toBe("gpt-4o");
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expect(body.stream).toBe(false);
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expect(Array.isArray(body.messages)).toBe(true);
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expect(body.messages.length).toBeGreaterThanOrEqual(2);
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expect(body.messages[0].role).toBe("system");
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expect(body.messages[1].role).toBe("user");
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expect(body.messages[1].content).toBe("Do the thing");
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expect(Array.isArray(body.tools)).toBe(true);
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});
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});
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describe("custom base_url override", () => {
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it("sends request to custom base_url", async () => {
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process.env.TEST_OPENAI_KEY = "sk-test";
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mockFetch({
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choices: [{ message: { content: '{"success": true, "output": "done"}' } }],
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usage: { prompt_tokens: 1, completion_tokens: 1, total_tokens: 2 },
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});
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const backend = new OpenAIBackend({
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base_url: "https://custom-proxy.example.com/api",
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api_key_env: "TEST_OPENAI_KEY",
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model: "gpt-4o",
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model_profile: "quality",
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});
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const request = {
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persona: "executor" as const,
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workflow: "execute",
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task: "test",
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context: {
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project_path: "/tmp",
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phase: 1,
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stage: "execute" as const,
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specification: "",
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config_path: "",
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},
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autonomy: "full" as const,
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};
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await backend.execute(request);
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expect(fetchCalls[0].url).toBe("https://custom-proxy.example.com/api/chat/completions");
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});
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});
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describe("organization header", () => {
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it("sends OpenAI-Organization header when config.organization is set", async () => {
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process.env.TEST_OPENAI_KEY = "sk-test";
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mockFetch({
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choices: [{ message: { content: '{"success": true, "output": "done"}' } }],
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usage: { prompt_tokens: 1, completion_tokens: 1, total_tokens: 2 },
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});
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const backend = new OpenAIBackend({
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base_url: "https://api.openai.com/v1",
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api_key_env: "TEST_OPENAI_KEY",
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model: "gpt-4o",
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model_profile: "quality",
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organization: "org-abc123",
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});
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const request = {
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persona: "executor" as const,
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workflow: "execute",
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task: "test",
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context: {
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project_path: "/tmp",
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phase: 1,
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stage: "execute" as const,
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specification: "",
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config_path: "",
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},
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autonomy: "full" as const,
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};
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await backend.execute(request);
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expect(fetchCalls[0].headers["OpenAI-Organization"]).toBe("org-abc123");
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});
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it("does not send OpenAI-Organization header when config.organization is not set", async () => {
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process.env.TEST_OPENAI_KEY = "sk-test";
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mockFetch({
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choices: [{ message: { content: '{"success": true, "output": "done"}' } }],
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usage: { prompt_tokens: 1, completion_tokens: 1, total_tokens: 2 },
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});
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const backend = new OpenAIBackend({
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base_url: "https://api.openai.com/v1",
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api_key_env: "TEST_OPENAI_KEY",
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model: "gpt-4o",
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model_profile: "quality",
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});
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const request = {
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persona: "executor" as const,
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workflow: "execute",
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task: "test",
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context: {
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project_path: "/tmp",
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phase: 1,
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stage: "execute" as const,
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specification: "",
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config_path: "",
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},
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autonomy: "full" as const,
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};
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await backend.execute(request);
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expect(fetchCalls[0].headers["OpenAI-Organization"]).toBeUndefined();
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});
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});
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}); |