mirror of
https://github.com/luckyyzh/pi-agent-integrated.git
synced 2026-10-03 02:59:35 +00:00
feat: integrate Pi backend and Pi Web
This commit is contained in:
luckyyzh
@@ -0,0 +1,304 @@
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import { beforeEach, describe, expect, it, vi } from "vitest";
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import { getModel, streamSimple } from "../src/compat.ts";
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// Empty tools arrays must NOT be serialized as `tools: []` — some OpenAI-compatible
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// backends (e.g. DashScope / Aliyun Qwen via compatible-mode) reject the request with
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// `"[] is too short - 'tools'"` (HTTP 400) when `--no-tools` produces an empty array.
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// Regression for https://github.com/earendil-works/pi-mono/issues/<issue-number>
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const mockState = vi.hoisted(() => ({
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lastParams: undefined as unknown,
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lastClientOptions: undefined as unknown,
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}));
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vi.mock("openai", () => {
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class FakeOpenAI {
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constructor(options: unknown) {
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mockState.lastClientOptions = options;
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}
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chat = {
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completions: {
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create: (params: unknown) => {
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mockState.lastParams = params;
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const stream = {
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async *[Symbol.asyncIterator]() {
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yield {
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choices: [{ delta: {}, finish_reason: "stop" }],
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usage: {
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prompt_tokens: 1,
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completion_tokens: 1,
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prompt_tokens_details: { cached_tokens: 0 },
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completion_tokens_details: { reasoning_tokens: 0 },
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},
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};
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},
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};
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const promise = Promise.resolve(stream) as Promise<typeof stream> & {
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withResponse: () => Promise<{
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data: typeof stream;
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response: { status: number; headers: Headers };
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}>;
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};
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promise.withResponse = async () => ({
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data: stream,
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response: { status: 200, headers: new Headers() },
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});
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return promise;
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},
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},
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};
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}
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return { default: FakeOpenAI };
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});
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describe("openai-completions empty tools handling", () => {
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beforeEach(() => {
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mockState.lastParams = undefined;
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mockState.lastClientOptions = undefined;
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});
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it("omits tools field when context.tools is an empty array", async () => {
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const { compat: _compat, ...baseModel } = getModel("openai", "gpt-4o-mini")!;
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const model = { ...baseModel, api: "openai-completions" } as const;
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await streamSimple(
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model,
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{
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messages: [{ role: "user", content: "hi", timestamp: Date.now() }],
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tools: [],
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},
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{ apiKey: "test" },
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).result();
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const params = mockState.lastParams as { tools?: unknown };
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expect("tools" in (params as object)).toBe(false);
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});
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it("omits tools field when context.tools is undefined", async () => {
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const { compat: _compat, ...baseModel } = getModel("openai", "gpt-4o-mini")!;
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const model = { ...baseModel, api: "openai-completions" } as const;
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await streamSimple(
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model,
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{
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messages: [{ role: "user", content: "hi", timestamp: Date.now() }],
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},
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{ apiKey: "test" },
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).result();
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const params = mockState.lastParams as { tools?: unknown };
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expect("tools" in (params as object)).toBe(false);
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});
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it("sends default maxTokens", async () => {
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const { compat: _compat, ...baseModel } = getModel("openai", "gpt-4o-mini")!;
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const model = { ...baseModel, api: "openai-completions" } as const;
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await streamSimple(
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model,
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{
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messages: [{ role: "user", content: "hi", timestamp: Date.now() }],
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},
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{ apiKey: "test" },
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).result();
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const params = mockState.lastParams as { max_tokens?: number; max_completion_tokens?: number };
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expect(params.max_tokens).toBeUndefined();
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expect(params.max_completion_tokens).toBe(model.maxTokens);
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});
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it("sends explicit maxTokens", async () => {
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const { compat: _compat, ...baseModel } = getModel("openai", "gpt-4o-mini")!;
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const model = { ...baseModel, api: "openai-completions" } as const;
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await streamSimple(
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model,
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{
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messages: [{ role: "user", content: "hi", timestamp: Date.now() }],
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},
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{ apiKey: "test", maxTokens: 1234 },
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).result();
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const params = mockState.lastParams as { max_tokens?: number; max_completion_tokens?: number };
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expect(params.max_tokens).toBeUndefined();
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expect(params.max_completion_tokens).toBe(1234);
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});
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it("clamps default maxTokens to remaining context", async () => {
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const { compat: _compat, ...baseModel } = getModel("openai", "gpt-4o-mini")!;
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const model = { ...baseModel, api: "openai-completions", contextWindow: 10000, maxTokens: 8000 } as const;
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await streamSimple(
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model,
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{
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messages: [{ role: "user", content: "x".repeat(8000), timestamp: Date.now() }],
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},
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{ apiKey: "test" },
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).result();
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const params = mockState.lastParams as { max_tokens?: number; max_completion_tokens?: number };
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expect(params.max_tokens).toBeUndefined();
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expect(params.max_completion_tokens).toBe(3904);
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});
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it("clamps explicit maxTokens to remaining context", async () => {
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const { compat: _compat, ...baseModel } = getModel("openai", "gpt-4o-mini")!;
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const model = { ...baseModel, api: "openai-completions", contextWindow: 10000, maxTokens: 8000 } as const;
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await streamSimple(
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model,
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{
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messages: [{ role: "user", content: "x".repeat(8000), timestamp: Date.now() }],
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},
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{ apiKey: "test", maxTokens: 7000 },
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).result();
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const params = mockState.lastParams as { max_tokens?: number; max_completion_tokens?: number };
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expect(params.max_tokens).toBeUndefined();
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expect(params.max_completion_tokens).toBe(3904);
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});
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it("uses conservative OpenAI-compatible fields for Cloudflare AI Gateway /compat models", async () => {
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process.env.CLOUDFLARE_API_KEY = "cf-token";
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process.env.CLOUDFLARE_ACCOUNT_ID = "account-id";
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process.env.CLOUDFLARE_GATEWAY_ID = "gateway-id";
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const model = getModel("cloudflare-ai-gateway", "workers-ai/@cf/moonshotai/kimi-k2.6")!;
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await streamSimple(
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model,
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{
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systemPrompt: "You are helpful.",
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messages: [{ role: "user", content: "hi", timestamp: Date.now() }],
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},
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{ maxTokens: 1234, reasoning: "high" },
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).result();
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const params = mockState.lastParams as {
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messages: Array<{ role: string }>;
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max_tokens?: number;
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max_completion_tokens?: number;
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reasoning_effort?: string;
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store?: boolean;
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};
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expect(params.messages[0].role).toBe("system");
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expect(params.max_tokens).toBe(1234);
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expect(params.max_completion_tokens).toBeUndefined();
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expect(params.reasoning_effort).toBeUndefined();
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expect(params.store).toBeUndefined();
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const clientOptions = mockState.lastClientOptions as {
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baseURL?: string;
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defaultHeaders?: Record<string, unknown>;
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};
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expect(clientOptions.baseURL).toBe("https://gateway.ai.cloudflare.com/v1/account-id/gateway-id/compat");
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expect(clientOptions.defaultHeaders?.Authorization).toBeNull();
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expect(clientOptions.defaultHeaders?.["cf-aig-authorization"]).toBe("Bearer cf-token");
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});
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it("resolves Cloudflare AI Gateway base URL through provider auth", async () => {
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process.env.CLOUDFLARE_API_KEY = "cf-token";
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process.env.CLOUDFLARE_ACCOUNT_ID = "account-id";
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process.env.CLOUDFLARE_GATEWAY_ID = "gateway-id";
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const model = getModel("cloudflare-ai-gateway", "workers-ai/@cf/moonshotai/kimi-k2.6")!;
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await streamSimple(model, {
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messages: [{ role: "user", content: "hi", timestamp: Date.now() }],
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}).result();
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const clientOptions = mockState.lastClientOptions as { baseURL?: string };
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expect(clientOptions.baseURL).toBe("https://gateway.ai.cloudflare.com/v1/account-id/gateway-id/compat");
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});
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it("preserves inline upstream Authorization for Cloudflare AI Gateway BYOK requests", async () => {
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process.env.CLOUDFLARE_API_KEY = "cf-token";
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process.env.CLOUDFLARE_ACCOUNT_ID = "account-id";
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process.env.CLOUDFLARE_GATEWAY_ID = "gateway-id";
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const model = getModel("cloudflare-ai-gateway", "gpt-5.1")!;
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await streamSimple(
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model,
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{
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messages: [{ role: "user", content: "hi", timestamp: Date.now() }],
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},
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{ headers: { Authorization: "Bearer upstream-token" } },
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).result();
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const clientOptions = mockState.lastClientOptions as { defaultHeaders?: Record<string, unknown> };
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expect(clientOptions.defaultHeaders?.Authorization).toBe("Bearer upstream-token");
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expect(clientOptions.defaultHeaders?.["cf-aig-authorization"]).toBe("Bearer cf-token");
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});
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it("sends session affinity headers for Workers AI through Cloudflare AI Gateway", async () => {
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process.env.CLOUDFLARE_API_KEY = "cf-token";
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process.env.CLOUDFLARE_ACCOUNT_ID = "account-id";
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process.env.CLOUDFLARE_GATEWAY_ID = "gateway-id";
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const workersModel = getModel("cloudflare-ai-gateway", "workers-ai/@cf/moonshotai/kimi-k2.6")!;
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await streamSimple(
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workersModel,
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{
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messages: [{ role: "user", content: "hi", timestamp: Date.now() }],
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},
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{ sessionId: "session-1" },
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).result();
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const clientOptions = mockState.lastClientOptions as { defaultHeaders?: Record<string, string> };
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expect(clientOptions.defaultHeaders?.session_id).toBe("session-1");
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expect(clientOptions.defaultHeaders?.["x-client-request-id"]).toBe("session-1");
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expect(clientOptions.defaultHeaders?.["x-session-affinity"]).toBe("session-1");
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});
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it("still emits tools: [] for Anthropic/LiteLLM proxy when conversation has tool history", async () => {
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const { compat: _compat, ...baseModel } = getModel("openai", "gpt-4o-mini")!;
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const model = { ...baseModel, api: "openai-completions" } as const;
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await streamSimple(
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model,
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{
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messages: [
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{ role: "user", content: "use the tool", timestamp: Date.now() },
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{
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role: "assistant",
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content: [
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{
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type: "toolCall",
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id: "t1",
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name: "noop",
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arguments: {},
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},
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],
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stopReason: "toolUse",
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usage: {
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input: 0,
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output: 0,
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cacheRead: 0,
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cacheWrite: 0,
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totalTokens: 0,
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cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
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},
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api: "openai-completions",
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provider: "openai",
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model: "gpt-4o-mini",
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timestamp: Date.now(),
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},
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{
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role: "toolResult",
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toolCallId: "t1",
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toolName: "noop",
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content: [{ type: "text", text: "done" }],
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isError: false,
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timestamp: Date.now(),
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},
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],
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tools: [],
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},
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{ apiKey: "test" },
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).result();
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const params = mockState.lastParams as { tools?: unknown[] };
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expect(Array.isArray(params.tools)).toBe(true);
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expect(params.tools).toEqual([]);
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});
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});
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