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https://github.com/getcompanion-ai/co-mono.git
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Add OAuth providers to test suite and improve test coverage
Tests updated: - abort.test.ts: Add Google Gemini CLI, add retries - agent.test.ts: Add OAuth providers (Anthropic, GitHub Copilot, Gemini CLI, Antigravity), add retries, remove timeouts - context-overflow.test.ts: Handle Cerebras 429 status code - image-tool-result.test.ts: Add OAuth providers - overflow.ts: Detect 429 as overflow for Cerebras Removed obsolete debug/one-off tests: - copilot-initiator.test.ts - gemini-3-flash-tool-calling.test.ts - google-thought-signature.test.ts - mistral-debug.test.ts - mistral-empty-assistant.test.ts - mistral-sdk.test.ts
This commit is contained in:
Mario Zechner
parent
fb1fdb6006
commit
6a319f9c3c
11 changed files with 239 additions and 1505 deletions
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@ -54,8 +54,8 @@ const OVERFLOW_PATTERNS = [
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* - Google Gemini: "input token count exceeds the maximum"
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* - xAI (Grok): "maximum prompt length is X but request contains Y"
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* - Groq: "reduce the length of the messages"
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* - Cerebras: 400/413 status code (no body)
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* - Mistral: 400/413 status code (no body)
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* - Cerebras: 400/413/429 status code (no body)
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* - Mistral: 400/413/429 status code (no body)
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* - OpenRouter (all backends): "maximum context length is X tokens"
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* - llama.cpp: "exceeds the available context size"
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* - LM Studio: "greater than the context length"
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@ -89,8 +89,9 @@ export function isContextOverflow(message: AssistantMessage, contextWindow?: num
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return true;
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}
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// Cerebras and Mistral return 400/413 with no body - check for status code pattern
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if (/^4(00|13)\s*(status code)?\s*\(no body\)/i.test(message.errorMessage)) {
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// Cerebras and Mistral return 400/413/429 with no body - check for status code pattern
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// 429 can indicate token-based rate limiting which correlates with context overflow
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if (/^4(00|13|29)\s*(status code)?\s*\(no body\)/i.test(message.errorMessage)) {
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return true;
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}
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}
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@ -1,8 +1,11 @@
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import { describe, expect, it } from "vitest";
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import { getModel } from "../src/models.js";
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import { complete, stream } from "../src/stream.js";
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import { complete, resolveApiKey, stream } from "../src/stream.js";
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import type { Api, Context, Model, OptionsForApi } from "../src/types.js";
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// Resolve OAuth tokens at module level (async, runs before tests)
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const geminiCliToken = await resolveApiKey("google-gemini-cli");
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async function testAbortSignal<TApi extends Api>(llm: Model<TApi>, options: OptionsForApi<TApi> = {}) {
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const context: Context = {
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messages: [
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@ -15,13 +18,18 @@ async function testAbortSignal<TApi extends Api>(llm: Model<TApi>, options: Opti
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};
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let abortFired = false;
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let text = "";
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const controller = new AbortController();
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const response = await stream(llm, context, { ...options, signal: controller.signal });
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for await (const event of response) {
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if (abortFired) return;
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setTimeout(() => controller.abort(), 3000);
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abortFired = true;
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break;
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if (event.type === "text_delta" || event.type === "thinking_delta") {
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text += event.delta;
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}
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if (text.length >= 50) {
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controller.abort();
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abortFired = true;
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}
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}
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const msg = await response.result();
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@ -58,11 +66,11 @@ describe("AI Providers Abort Tests", () => {
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describe.skipIf(!process.env.GEMINI_API_KEY)("Google Provider Abort", () => {
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const llm = getModel("google", "gemini-2.5-flash");
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it("should abort mid-stream", async () => {
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it("should abort mid-stream", { retry: 3 }, async () => {
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await testAbortSignal(llm, { thinking: { enabled: true } });
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});
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it("should handle immediate abort", async () => {
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it("should handle immediate abort", { retry: 3 }, async () => {
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await testImmediateAbort(llm, { thinking: { enabled: true } });
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});
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});
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@ -73,11 +81,11 @@ describe("AI Providers Abort Tests", () => {
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api: "openai-completions",
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};
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it("should abort mid-stream", async () => {
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it("should abort mid-stream", { retry: 3 }, async () => {
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await testAbortSignal(llm);
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});
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it("should handle immediate abort", async () => {
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it("should handle immediate abort", { retry: 3 }, async () => {
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await testImmediateAbort(llm);
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});
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});
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@ -85,11 +93,11 @@ describe("AI Providers Abort Tests", () => {
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describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Responses Provider Abort", () => {
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const llm = getModel("openai", "gpt-5-mini");
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it("should abort mid-stream", async () => {
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it("should abort mid-stream", { retry: 3 }, async () => {
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await testAbortSignal(llm);
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});
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it("should handle immediate abort", async () => {
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it("should handle immediate abort", { retry: 3 }, async () => {
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await testImmediateAbort(llm);
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});
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});
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@ -97,11 +105,11 @@ describe("AI Providers Abort Tests", () => {
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describe.skipIf(!process.env.ANTHROPIC_OAUTH_TOKEN)("Anthropic Provider Abort", () => {
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const llm = getModel("anthropic", "claude-opus-4-1-20250805");
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it("should abort mid-stream", async () => {
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it("should abort mid-stream", { retry: 3 }, async () => {
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await testAbortSignal(llm, { thinkingEnabled: true, thinkingBudgetTokens: 2048 });
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});
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it("should handle immediate abort", async () => {
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it("should handle immediate abort", { retry: 3 }, async () => {
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await testImmediateAbort(llm, { thinkingEnabled: true, thinkingBudgetTokens: 2048 });
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});
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});
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@ -109,12 +117,25 @@ describe("AI Providers Abort Tests", () => {
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describe.skipIf(!process.env.MISTRAL_API_KEY)("Mistral Provider Abort", () => {
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const llm = getModel("mistral", "devstral-medium-latest");
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it("should abort mid-stream", async () => {
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it("should abort mid-stream", { retry: 3 }, async () => {
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await testAbortSignal(llm);
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});
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it("should handle immediate abort", async () => {
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it("should handle immediate abort", { retry: 3 }, async () => {
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await testImmediateAbort(llm);
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});
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});
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// Google Gemini CLI / Antigravity share the same provider, so one test covers both
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describe("Google Gemini CLI Provider Abort", () => {
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it.skipIf(!geminiCliToken)("should abort mid-stream", { retry: 3 }, async () => {
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const llm = getModel("google-gemini-cli", "gemini-2.5-flash");
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await testAbortSignal(llm, { apiKey: geminiCliToken });
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});
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it.skipIf(!geminiCliToken)("should handle immediate abort", { retry: 3 }, async () => {
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const llm = getModel("google-gemini-cli", "gemini-2.5-flash");
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await testImmediateAbort(llm, { apiKey: geminiCliToken });
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});
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});
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});
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@ -3,6 +3,7 @@ import { agentLoop, agentLoopContinue } from "../src/agent/agent-loop.js";
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import { calculateTool } from "../src/agent/tools/calculate.js";
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import type { AgentContext, AgentEvent, AgentLoopConfig } from "../src/agent/types.js";
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import { getModel } from "../src/models.js";
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import { resolveApiKey } from "../src/stream.js";
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import type {
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Api,
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AssistantMessage,
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@ -13,6 +14,15 @@ import type {
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UserMessage,
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} from "../src/types.js";
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// Resolve OAuth tokens at module level (async, runs before tests)
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const oauthTokens = await Promise.all([
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resolveApiKey("anthropic"),
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resolveApiKey("github-copilot"),
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resolveApiKey("google-gemini-cli"),
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resolveApiKey("google-antigravity"),
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]);
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const [anthropicOAuthToken, githubCopilotToken, geminiCliToken, antigravityToken] = oauthTokens;
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async function calculateTest<TApi extends Api>(model: Model<TApi>, options: OptionsForApi<TApi> = {}) {
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// Create the agent context with the calculator tool
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const context: AgentContext = {
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@ -250,127 +260,271 @@ describe("Agent Calculator Tests", () => {
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describe.skipIf(!process.env.GEMINI_API_KEY)("Google Provider Agent", () => {
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const model = getModel("google", "gemini-2.5-flash");
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it("should calculate multiple expressions and sum the results", async () => {
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it("should calculate multiple expressions and sum the results", { retry: 3 }, async () => {
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const result = await calculateTest(model);
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expect(result.toolCallCount).toBeGreaterThanOrEqual(2);
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}, 30000);
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});
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it("should handle abort during tool execution", async () => {
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it("should handle abort during tool execution", { retry: 3 }, async () => {
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const result = await abortTest(model);
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expect(result.toolCallCount).toBeGreaterThanOrEqual(1);
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}, 30000);
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});
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});
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describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Completions Provider Agent", () => {
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const model = getModel("openai", "gpt-4o-mini");
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it("should calculate multiple expressions and sum the results", async () => {
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it("should calculate multiple expressions and sum the results", { retry: 3 }, async () => {
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const result = await calculateTest(model);
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expect(result.toolCallCount).toBeGreaterThanOrEqual(2);
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}, 30000);
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});
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it("should handle abort during tool execution", async () => {
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it("should handle abort during tool execution", { retry: 3 }, async () => {
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const result = await abortTest(model);
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expect(result.toolCallCount).toBeGreaterThanOrEqual(1);
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}, 30000);
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});
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});
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describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Responses Provider Agent", () => {
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const model = getModel("openai", "gpt-5-mini");
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it("should calculate multiple expressions and sum the results", async () => {
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it("should calculate multiple expressions and sum the results", { retry: 3 }, async () => {
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const result = await calculateTest(model);
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expect(result.toolCallCount).toBeGreaterThanOrEqual(2);
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}, 30000);
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});
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it("should handle abort during tool execution", async () => {
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it("should handle abort during tool execution", { retry: 3 }, async () => {
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const result = await abortTest(model);
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expect(result.toolCallCount).toBeGreaterThanOrEqual(1);
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}, 30000);
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});
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});
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describe.skipIf(!process.env.ANTHROPIC_API_KEY)("Anthropic Provider Agent", () => {
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const model = getModel("anthropic", "claude-haiku-4-5");
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it("should calculate multiple expressions and sum the results", async () => {
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it("should calculate multiple expressions and sum the results", { retry: 3 }, async () => {
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const result = await calculateTest(model);
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expect(result.toolCallCount).toBeGreaterThanOrEqual(2);
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}, 30000);
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});
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it("should handle abort during tool execution", async () => {
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it("should handle abort during tool execution", { retry: 3 }, async () => {
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const result = await abortTest(model);
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expect(result.toolCallCount).toBeGreaterThanOrEqual(1);
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}, 30000);
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});
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});
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describe.skipIf(!process.env.XAI_API_KEY)("xAI Provider Agent", () => {
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const model = getModel("xai", "grok-3");
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it("should calculate multiple expressions and sum the results", async () => {
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it("should calculate multiple expressions and sum the results", { retry: 3 }, async () => {
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const result = await calculateTest(model);
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expect(result.toolCallCount).toBeGreaterThanOrEqual(2);
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}, 30000);
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});
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it("should handle abort during tool execution", async () => {
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it("should handle abort during tool execution", { retry: 3 }, async () => {
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const result = await abortTest(model);
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expect(result.toolCallCount).toBeGreaterThanOrEqual(1);
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}, 30000);
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});
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});
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describe.skipIf(!process.env.GROQ_API_KEY)("Groq Provider Agent", () => {
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const model = getModel("groq", "openai/gpt-oss-20b");
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it("should calculate multiple expressions and sum the results", async () => {
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it("should calculate multiple expressions and sum the results", { retry: 3 }, async () => {
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const result = await calculateTest(model);
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expect(result.toolCallCount).toBeGreaterThanOrEqual(2);
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}, 30000);
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});
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it("should handle abort during tool execution", async () => {
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it("should handle abort during tool execution", { retry: 3 }, async () => {
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const result = await abortTest(model);
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expect(result.toolCallCount).toBeGreaterThanOrEqual(1);
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}, 30000);
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});
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});
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describe.skipIf(!process.env.CEREBRAS_API_KEY)("Cerebras Provider Agent", () => {
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const model = getModel("cerebras", "gpt-oss-120b");
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it("should calculate multiple expressions and sum the results", async () => {
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it("should calculate multiple expressions and sum the results", { retry: 3 }, async () => {
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const result = await calculateTest(model);
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expect(result.toolCallCount).toBeGreaterThanOrEqual(2);
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}, 30000);
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});
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it("should handle abort during tool execution", async () => {
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it("should handle abort during tool execution", { retry: 3 }, async () => {
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const result = await abortTest(model);
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expect(result.toolCallCount).toBeGreaterThanOrEqual(1);
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}, 30000);
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});
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});
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describe.skipIf(!process.env.ZAI_API_KEY)("zAI Provider Agent", () => {
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const model = getModel("zai", "glm-4.5-air");
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it("should calculate multiple expressions and sum the results", async () => {
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it("should calculate multiple expressions and sum the results", { retry: 3 }, async () => {
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const result = await calculateTest(model);
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expect(result.toolCallCount).toBeGreaterThanOrEqual(2);
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}, 30000);
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});
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it("should handle abort during tool execution", async () => {
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it("should handle abort during tool execution", { retry: 3 }, async () => {
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const result = await abortTest(model);
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expect(result.toolCallCount).toBeGreaterThanOrEqual(1);
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}, 30000);
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});
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});
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describe.skipIf(!process.env.MISTRAL_API_KEY)("Mistral Provider Agent", () => {
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const model = getModel("mistral", "devstral-medium-latest");
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it("should calculate multiple expressions and sum the results", async () => {
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it("should calculate multiple expressions and sum the results", { retry: 3 }, async () => {
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const result = await calculateTest(model);
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expect(result.toolCallCount).toBeGreaterThanOrEqual(2);
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}, 30000);
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});
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it("should handle abort during tool execution", async () => {
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it("should handle abort during tool execution", { retry: 3 }, async () => {
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const result = await abortTest(model);
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expect(result.toolCallCount).toBeGreaterThanOrEqual(1);
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}, 30000);
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});
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});
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// =========================================================================
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// OAuth-based providers (credentials from ~/.pi/agent/oauth.json)
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// =========================================================================
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describe("Anthropic OAuth Provider Agent", () => {
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const model = getModel("anthropic", "claude-haiku-4-5");
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it.skipIf(!anthropicOAuthToken)(
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"should calculate multiple expressions and sum the results",
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{ retry: 3 },
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async () => {
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const result = await calculateTest(model, { apiKey: anthropicOAuthToken });
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expect(result.toolCallCount).toBeGreaterThanOrEqual(2);
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},
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);
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it.skipIf(!anthropicOAuthToken)("should handle abort during tool execution", { retry: 3 }, async () => {
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const result = await abortTest(model, { apiKey: anthropicOAuthToken });
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expect(result.toolCallCount).toBeGreaterThanOrEqual(1);
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});
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});
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describe("GitHub Copilot Provider Agent", () => {
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it.skipIf(!githubCopilotToken)(
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"gpt-4o - should calculate multiple expressions and sum the results",
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{ retry: 3 },
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async () => {
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const model = getModel("github-copilot", "gpt-4o");
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const result = await calculateTest(model, { apiKey: githubCopilotToken });
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expect(result.toolCallCount).toBeGreaterThanOrEqual(2);
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},
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);
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it.skipIf(!githubCopilotToken)("gpt-4o - should handle abort during tool execution", { retry: 3 }, async () => {
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const model = getModel("github-copilot", "gpt-4o");
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const result = await abortTest(model, { apiKey: githubCopilotToken });
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expect(result.toolCallCount).toBeGreaterThanOrEqual(1);
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});
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it.skipIf(!githubCopilotToken)(
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"claude-sonnet-4 - should calculate multiple expressions and sum the results",
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{ retry: 3 },
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async () => {
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const model = getModel("github-copilot", "claude-sonnet-4");
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const result = await calculateTest(model, { apiKey: githubCopilotToken });
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expect(result.toolCallCount).toBeGreaterThanOrEqual(2);
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},
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);
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it.skipIf(!githubCopilotToken)(
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"claude-sonnet-4 - should handle abort during tool execution",
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{ retry: 3 },
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async () => {
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const model = getModel("github-copilot", "claude-sonnet-4");
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const result = await abortTest(model, { apiKey: githubCopilotToken });
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expect(result.toolCallCount).toBeGreaterThanOrEqual(1);
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},
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);
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});
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describe("Google Gemini CLI Provider Agent", () => {
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it.skipIf(!geminiCliToken)(
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"gemini-2.5-flash - should calculate multiple expressions and sum the results",
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{ retry: 3 },
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async () => {
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const model = getModel("google-gemini-cli", "gemini-2.5-flash");
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const result = await calculateTest(model, { apiKey: geminiCliToken });
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expect(result.toolCallCount).toBeGreaterThanOrEqual(2);
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},
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);
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it.skipIf(!geminiCliToken)(
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"gemini-2.5-flash - should handle abort during tool execution",
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{ retry: 3 },
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async () => {
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const model = getModel("google-gemini-cli", "gemini-2.5-flash");
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const result = await abortTest(model, { apiKey: geminiCliToken });
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expect(result.toolCallCount).toBeGreaterThanOrEqual(1);
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||||
},
|
||||
);
|
||||
});
|
||||
|
||||
describe("Google Antigravity Provider Agent", () => {
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gemini-3-flash - should calculate multiple expressions and sum the results",
|
||||
{ retry: 3 },
|
||||
async () => {
|
||||
const model = getModel("google-antigravity", "gemini-3-flash");
|
||||
const result = await calculateTest(model, { apiKey: antigravityToken });
|
||||
expect(result.toolCallCount).toBeGreaterThanOrEqual(2);
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gemini-3-flash - should handle abort during tool execution",
|
||||
{ retry: 3 },
|
||||
async () => {
|
||||
const model = getModel("google-antigravity", "gemini-3-flash");
|
||||
const result = await abortTest(model, { apiKey: antigravityToken });
|
||||
expect(result.toolCallCount).toBeGreaterThanOrEqual(1);
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"claude-sonnet-4-5 - should calculate multiple expressions and sum the results",
|
||||
{ retry: 3 },
|
||||
async () => {
|
||||
const model = getModel("google-antigravity", "claude-sonnet-4-5");
|
||||
const result = await calculateTest(model, { apiKey: antigravityToken });
|
||||
expect(result.toolCallCount).toBeGreaterThanOrEqual(2);
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"claude-sonnet-4-5 - should handle abort during tool execution",
|
||||
{ retry: 3 },
|
||||
async () => {
|
||||
const model = getModel("google-antigravity", "claude-sonnet-4-5");
|
||||
const result = await abortTest(model, { apiKey: antigravityToken });
|
||||
expect(result.toolCallCount).toBeGreaterThanOrEqual(1);
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gpt-oss-120b-medium - should calculate multiple expressions and sum the results",
|
||||
{ retry: 3 },
|
||||
async () => {
|
||||
const model = getModel("google-antigravity", "gpt-oss-120b-medium");
|
||||
const result = await calculateTest(model, { apiKey: antigravityToken });
|
||||
expect(result.toolCallCount).toBeGreaterThanOrEqual(2);
|
||||
},
|
||||
);
|
||||
|
||||
it.skipIf(!antigravityToken)(
|
||||
"gpt-oss-120b-medium - should handle abort during tool execution",
|
||||
{ retry: 3 },
|
||||
async () => {
|
||||
const model = getModel("google-antigravity", "gpt-oss-120b-medium");
|
||||
const result = await abortTest(model, { apiKey: antigravityToken });
|
||||
expect(result.toolCallCount).toBeGreaterThanOrEqual(1);
|
||||
},
|
||||
);
|
||||
});
|
||||
});
|
||||
|
||||
|
|
@ -422,7 +576,7 @@ describe("agentLoopContinue", () => {
|
|||
describe.skipIf(!process.env.ANTHROPIC_API_KEY)("continue from user message", () => {
|
||||
const model = getModel("anthropic", "claude-haiku-4-5");
|
||||
|
||||
it("should continue and get assistant response when last message is user", async () => {
|
||||
it("should continue and get assistant response when last message is user", { retry: 3 }, async () => {
|
||||
const userMessage: UserMessage = {
|
||||
role: "user",
|
||||
content: [{ type: "text", text: "Say exactly: HELLO WORLD" }],
|
||||
|
|
@ -463,13 +617,13 @@ describe("agentLoopContinue", () => {
|
|||
const messageEndEvents = events.filter((e) => e.type === "message_end");
|
||||
expect(messageEndEvents.length).toBe(1); // Only assistant message
|
||||
expect((messageEndEvents[0] as any).message.role).toBe("assistant");
|
||||
}, 30000);
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.ANTHROPIC_API_KEY)("continue from tool result", () => {
|
||||
const model = getModel("anthropic", "claude-haiku-4-5");
|
||||
|
||||
it("should continue processing after tool results", async () => {
|
||||
it("should continue processing after tool results", { retry: 3 }, async () => {
|
||||
// Simulate a conversation where:
|
||||
// 1. User asked to calculate something
|
||||
// 2. Assistant made a tool call
|
||||
|
|
@ -542,6 +696,6 @@ describe("agentLoopContinue", () => {
|
|||
.join(" ");
|
||||
expect(textContent).toMatch(/8/);
|
||||
}
|
||||
}, 30000);
|
||||
});
|
||||
});
|
||||
});
|
||||
|
|
|
|||
|
|
@ -308,8 +308,8 @@ describe("Context overflow error handling", () => {
|
|||
logResult(result);
|
||||
|
||||
expect(result.stopReason).toBe("error");
|
||||
// Cerebras returns status code with no body
|
||||
expect(result.errorMessage).toMatch(/4(00|13).*\(no body\)/i);
|
||||
// Cerebras returns status code with no body (400, 413, or 429 for token rate limit)
|
||||
expect(result.errorMessage).toMatch(/4(00|13|29).*\(no body\)/i);
|
||||
expect(isContextOverflow(result.response, model.contextWindow)).toBe(true);
|
||||
}, 120000);
|
||||
});
|
||||
|
|
|
|||
|
|
@ -1,336 +0,0 @@
|
|||
import { beforeEach, describe, expect, it, vi } from "vitest";
|
||||
import { streamOpenAICompletions } from "../src/providers/openai-completions.js";
|
||||
import { streamOpenAIResponses } from "../src/providers/openai-responses.js";
|
||||
import type { Context, Model } from "../src/types.js";
|
||||
|
||||
interface OpenAIConstructorConfig {
|
||||
defaultHeaders?: Record<string, string>;
|
||||
}
|
||||
|
||||
let lastOpenAIConfig: OpenAIConstructorConfig | undefined;
|
||||
|
||||
// Mock OpenAI
|
||||
vi.mock("openai", () => {
|
||||
class MockOpenAI {
|
||||
public chat: {
|
||||
completions: {
|
||||
create: (
|
||||
_body: unknown,
|
||||
_options?: unknown,
|
||||
) => AsyncGenerator<{ choices: Array<{ delta: { content?: string }; finish_reason: string | null }> }>;
|
||||
};
|
||||
};
|
||||
|
||||
public responses: {
|
||||
create: (
|
||||
_body: unknown,
|
||||
_options?: unknown,
|
||||
) => AsyncGenerator<{
|
||||
type: "response.completed";
|
||||
response: {
|
||||
status: "completed";
|
||||
usage: {
|
||||
input_tokens: number;
|
||||
output_tokens: number;
|
||||
total_tokens: number;
|
||||
input_tokens_details?: { cached_tokens?: number };
|
||||
};
|
||||
};
|
||||
}>;
|
||||
};
|
||||
|
||||
constructor(config: OpenAIConstructorConfig) {
|
||||
lastOpenAIConfig = config;
|
||||
|
||||
this.chat = {
|
||||
completions: {
|
||||
create: async function* () {
|
||||
yield {
|
||||
choices: [
|
||||
{
|
||||
delta: { content: "Hello" },
|
||||
finish_reason: null,
|
||||
},
|
||||
],
|
||||
};
|
||||
yield {
|
||||
choices: [
|
||||
{
|
||||
delta: { content: " world" },
|
||||
finish_reason: "stop",
|
||||
},
|
||||
],
|
||||
};
|
||||
},
|
||||
},
|
||||
};
|
||||
|
||||
this.responses = {
|
||||
create: async function* () {
|
||||
yield {
|
||||
type: "response.completed",
|
||||
response: {
|
||||
status: "completed",
|
||||
usage: {
|
||||
input_tokens: 0,
|
||||
output_tokens: 0,
|
||||
total_tokens: 0,
|
||||
input_tokens_details: { cached_tokens: 0 },
|
||||
},
|
||||
},
|
||||
};
|
||||
},
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
return { default: MockOpenAI };
|
||||
});
|
||||
|
||||
async function consumeStream(stream: AsyncIterable<unknown>): Promise<void> {
|
||||
for await (const _ of stream) {
|
||||
// consume
|
||||
}
|
||||
}
|
||||
|
||||
describe("GitHub Copilot Headers", () => {
|
||||
beforeEach(() => {
|
||||
lastOpenAIConfig = undefined;
|
||||
});
|
||||
|
||||
const copilotCompletionsModel: Model<"openai-completions"> = {
|
||||
id: "gpt-4",
|
||||
name: "GPT-4",
|
||||
api: "openai-completions",
|
||||
provider: "github-copilot",
|
||||
baseUrl: "https://api.individual.githubcopilot.com",
|
||||
reasoning: false,
|
||||
input: ["text"],
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
|
||||
contextWindow: 8192,
|
||||
maxTokens: 4096,
|
||||
headers: { Authorization: "Bearer token" },
|
||||
};
|
||||
|
||||
const otherCompletionsModel: Model<"openai-completions"> = {
|
||||
...copilotCompletionsModel,
|
||||
provider: "openai",
|
||||
};
|
||||
|
||||
const copilotResponsesModel: Model<"openai-responses"> = {
|
||||
id: "gpt-5.1-codex",
|
||||
name: "GPT-5.1-Codex",
|
||||
api: "openai-responses",
|
||||
provider: "github-copilot",
|
||||
baseUrl: "https://api.individual.githubcopilot.com",
|
||||
reasoning: true,
|
||||
input: ["text"],
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
|
||||
contextWindow: 128000,
|
||||
maxTokens: 128000,
|
||||
headers: { Authorization: "Bearer token" },
|
||||
};
|
||||
|
||||
const otherResponsesModel: Model<"openai-responses"> = {
|
||||
...copilotResponsesModel,
|
||||
provider: "openai",
|
||||
};
|
||||
|
||||
const assistantMessage = {
|
||||
role: "assistant" as const,
|
||||
content: [],
|
||||
api: "openai-completions" as const,
|
||||
provider: "github-copilot" as const,
|
||||
model: "gpt-4",
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "stop" as const,
|
||||
timestamp: Date.now(),
|
||||
};
|
||||
|
||||
const toolResultMessage = {
|
||||
role: "toolResult" as const,
|
||||
content: [],
|
||||
toolCallId: "1",
|
||||
toolName: "test",
|
||||
isError: false,
|
||||
timestamp: Date.now(),
|
||||
};
|
||||
|
||||
describe("completions API", () => {
|
||||
it("sets X-Initiator: user for first message (no history)", async () => {
|
||||
const context: Context = {
|
||||
messages: [{ role: "user", content: "Hello", timestamp: Date.now() }],
|
||||
};
|
||||
|
||||
const stream = streamOpenAICompletions(copilotCompletionsModel, context, { apiKey: "test-key" });
|
||||
await consumeStream(stream);
|
||||
|
||||
expect(lastOpenAIConfig?.defaultHeaders?.["X-Initiator"]).toBe("user");
|
||||
});
|
||||
|
||||
it("sets X-Initiator: agent when last message is assistant", async () => {
|
||||
const context: Context = {
|
||||
messages: [{ role: "user", content: "Hello", timestamp: Date.now() }, assistantMessage],
|
||||
};
|
||||
|
||||
const stream = streamOpenAICompletions(copilotCompletionsModel, context, { apiKey: "test-key" });
|
||||
await consumeStream(stream);
|
||||
|
||||
expect(lastOpenAIConfig?.defaultHeaders?.["X-Initiator"]).toBe("agent");
|
||||
});
|
||||
|
||||
it("sets X-Initiator: agent when last message is toolResult", async () => {
|
||||
const context: Context = {
|
||||
messages: [{ role: "user", content: "Hello", timestamp: Date.now() }, toolResultMessage],
|
||||
};
|
||||
|
||||
const stream = streamOpenAICompletions(copilotCompletionsModel, context, { apiKey: "test-key" });
|
||||
await consumeStream(stream);
|
||||
|
||||
expect(lastOpenAIConfig?.defaultHeaders?.["X-Initiator"]).toBe("agent");
|
||||
});
|
||||
|
||||
it("sets X-Initiator: user for multi-turn conversation when last message is user", async () => {
|
||||
const context: Context = {
|
||||
messages: [
|
||||
{ role: "user", content: "Hello", timestamp: Date.now() },
|
||||
assistantMessage,
|
||||
{ role: "user", content: "Tell me a joke", timestamp: Date.now() },
|
||||
],
|
||||
};
|
||||
|
||||
const stream = streamOpenAICompletions(copilotCompletionsModel, context, { apiKey: "test-key" });
|
||||
await consumeStream(stream);
|
||||
|
||||
expect(lastOpenAIConfig?.defaultHeaders?.["X-Initiator"]).toBe("user");
|
||||
});
|
||||
|
||||
it("sets X-Initiator: user when there are no messages", async () => {
|
||||
const context: Context = {
|
||||
messages: [],
|
||||
};
|
||||
|
||||
const stream = streamOpenAICompletions(copilotCompletionsModel, context, { apiKey: "test-key" });
|
||||
await consumeStream(stream);
|
||||
|
||||
expect(lastOpenAIConfig?.defaultHeaders?.["X-Initiator"]).toBe("user");
|
||||
});
|
||||
|
||||
it("sets Openai-Intent: conversation-edits", async () => {
|
||||
const context: Context = {
|
||||
messages: [{ role: "user", content: "Hello", timestamp: Date.now() }],
|
||||
};
|
||||
|
||||
const stream = streamOpenAICompletions(copilotCompletionsModel, context, { apiKey: "test-key" });
|
||||
await consumeStream(stream);
|
||||
|
||||
expect(lastOpenAIConfig?.defaultHeaders?.["Openai-Intent"]).toBe("conversation-edits");
|
||||
});
|
||||
|
||||
it("does NOT set Copilot headers for non-Copilot providers", async () => {
|
||||
const context: Context = {
|
||||
messages: [{ role: "user", content: "Hello", timestamp: Date.now() }],
|
||||
};
|
||||
|
||||
const stream = streamOpenAICompletions(otherCompletionsModel, context, { apiKey: "test-key" });
|
||||
await consumeStream(stream);
|
||||
|
||||
expect(lastOpenAIConfig?.defaultHeaders?.["X-Initiator"]).toBeUndefined();
|
||||
expect(lastOpenAIConfig?.defaultHeaders?.["Openai-Intent"]).toBeUndefined();
|
||||
});
|
||||
});
|
||||
|
||||
describe("responses API", () => {
|
||||
it("sets X-Initiator: user for first message (no history)", async () => {
|
||||
const context: Context = {
|
||||
messages: [{ role: "user", content: "Hello", timestamp: Date.now() }],
|
||||
};
|
||||
|
||||
const stream = streamOpenAIResponses(copilotResponsesModel, context, { apiKey: "test-key" });
|
||||
await consumeStream(stream);
|
||||
|
||||
expect(lastOpenAIConfig?.defaultHeaders?.["X-Initiator"]).toBe("user");
|
||||
});
|
||||
|
||||
it("sets X-Initiator: agent when last message is assistant", async () => {
|
||||
const context: Context = {
|
||||
messages: [
|
||||
{ role: "user", content: "Hello", timestamp: Date.now() },
|
||||
{ ...assistantMessage, api: "openai-responses" as const, model: "gpt-5.1-codex" },
|
||||
],
|
||||
};
|
||||
|
||||
const stream = streamOpenAIResponses(copilotResponsesModel, context, { apiKey: "test-key" });
|
||||
await consumeStream(stream);
|
||||
|
||||
expect(lastOpenAIConfig?.defaultHeaders?.["X-Initiator"]).toBe("agent");
|
||||
});
|
||||
|
||||
it("sets X-Initiator: agent when last message is toolResult", async () => {
|
||||
const context: Context = {
|
||||
messages: [{ role: "user", content: "Hello", timestamp: Date.now() }, toolResultMessage],
|
||||
};
|
||||
|
||||
const stream = streamOpenAIResponses(copilotResponsesModel, context, { apiKey: "test-key" });
|
||||
await consumeStream(stream);
|
||||
|
||||
expect(lastOpenAIConfig?.defaultHeaders?.["X-Initiator"]).toBe("agent");
|
||||
});
|
||||
|
||||
it("sets X-Initiator: user for multi-turn conversation when last message is user", async () => {
|
||||
const context: Context = {
|
||||
messages: [
|
||||
{ role: "user", content: "Hello", timestamp: Date.now() },
|
||||
{ ...assistantMessage, api: "openai-responses" as const, model: "gpt-5.1-codex" },
|
||||
{ role: "user", content: "Tell me a joke", timestamp: Date.now() },
|
||||
],
|
||||
};
|
||||
|
||||
const stream = streamOpenAIResponses(copilotResponsesModel, context, { apiKey: "test-key" });
|
||||
await consumeStream(stream);
|
||||
|
||||
expect(lastOpenAIConfig?.defaultHeaders?.["X-Initiator"]).toBe("user");
|
||||
});
|
||||
|
||||
it("sets X-Initiator: user when there are no messages", async () => {
|
||||
const context: Context = {
|
||||
messages: [],
|
||||
};
|
||||
|
||||
const stream = streamOpenAIResponses(copilotResponsesModel, context, { apiKey: "test-key" });
|
||||
await consumeStream(stream);
|
||||
|
||||
expect(lastOpenAIConfig?.defaultHeaders?.["X-Initiator"]).toBe("user");
|
||||
});
|
||||
|
||||
it("sets Openai-Intent: conversation-edits", async () => {
|
||||
const context: Context = {
|
||||
messages: [{ role: "user", content: "Hello", timestamp: Date.now() }],
|
||||
};
|
||||
|
||||
const stream = streamOpenAIResponses(copilotResponsesModel, context, { apiKey: "test-key" });
|
||||
await consumeStream(stream);
|
||||
|
||||
expect(lastOpenAIConfig?.defaultHeaders?.["Openai-Intent"]).toBe("conversation-edits");
|
||||
});
|
||||
|
||||
it("does NOT set Copilot headers for non-Copilot providers", async () => {
|
||||
const context: Context = {
|
||||
messages: [{ role: "user", content: "Hello", timestamp: Date.now() }],
|
||||
};
|
||||
|
||||
const stream = streamOpenAIResponses(otherResponsesModel, context, { apiKey: "test-key" });
|
||||
await consumeStream(stream);
|
||||
|
||||
expect(lastOpenAIConfig?.defaultHeaders?.["X-Initiator"]).toBeUndefined();
|
||||
expect(lastOpenAIConfig?.defaultHeaders?.["Openai-Intent"]).toBeUndefined();
|
||||
});
|
||||
});
|
||||
});
|
||||
|
|
@ -1,166 +0,0 @@
|
|||
import { Type } from "@sinclair/typebox";
|
||||
import { describe, expect, it } from "vitest";
|
||||
import { getModel } from "../src/models.js";
|
||||
import { complete } from "../src/stream.js";
|
||||
import type { Context, Tool, ToolResultMessage } from "../src/types.js";
|
||||
import { StringEnum } from "../src/utils/typebox-helpers.js";
|
||||
|
||||
/**
|
||||
* Test for Gemini 3 Flash Preview tool calling compatibility.
|
||||
*
|
||||
* Issue #213: The model works and tool calling works, but the problem is how pi-ai
|
||||
* formats the tool result message when sending it back to Gemini 3 Flash Preview.
|
||||
*
|
||||
* The SDK documentation states:
|
||||
* "Use 'output' key to specify function output and 'error' key to specify error details"
|
||||
*
|
||||
* But the code was using `result` and `isError` keys, which Gemini 3 Flash Preview
|
||||
* rejects (older models were more lenient).
|
||||
*/
|
||||
|
||||
// Calculator tool definition
|
||||
const calculatorSchema = Type.Object({
|
||||
a: Type.Number({ description: "First number" }),
|
||||
b: Type.Number({ description: "Second number" }),
|
||||
operation: StringEnum(["add", "subtract", "multiply", "divide"], {
|
||||
description: "The operation to perform. One of 'add', 'subtract', 'multiply', 'divide'.",
|
||||
}),
|
||||
});
|
||||
|
||||
const calculatorTool: Tool<typeof calculatorSchema> = {
|
||||
name: "calculator",
|
||||
description: "Perform basic arithmetic operations",
|
||||
parameters: calculatorSchema,
|
||||
};
|
||||
|
||||
describe("Gemini 3 Flash Preview Tool Calling", () => {
|
||||
it("should handle tool calls and tool results with correct format", async () => {
|
||||
if (!process.env.GEMINI_API_KEY) {
|
||||
console.log("Skipping test - GEMINI_API_KEY not set");
|
||||
return;
|
||||
}
|
||||
|
||||
const model = getModel("google", "gemini-3-flash-preview");
|
||||
|
||||
const context: Context = {
|
||||
systemPrompt: "You are a helpful assistant that uses tools when asked.",
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: "Calculate 15 + 27 using the calculator tool.",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
tools: [calculatorTool],
|
||||
};
|
||||
|
||||
// First call - model should request tool call
|
||||
const firstResponse = await complete(model, context);
|
||||
|
||||
expect(firstResponse.role).toBe("assistant");
|
||||
expect(firstResponse.stopReason).toBe("toolUse");
|
||||
expect(firstResponse.errorMessage).toBeFalsy();
|
||||
|
||||
const toolCall = firstResponse.content.find((b) => b.type === "toolCall");
|
||||
expect(toolCall).toBeTruthy();
|
||||
expect(toolCall?.type).toBe("toolCall");
|
||||
|
||||
if (toolCall?.type === "toolCall") {
|
||||
expect(toolCall.name).toBe("calculator");
|
||||
expect(toolCall.id).toBeTruthy();
|
||||
expect(toolCall.arguments).toBeTruthy();
|
||||
|
||||
const { a, b, operation } = toolCall.arguments;
|
||||
expect(a).toBe(15);
|
||||
expect(b).toBe(27);
|
||||
expect(operation).toBe("add");
|
||||
|
||||
// Execute the tool
|
||||
const result = 15 + 27;
|
||||
|
||||
// Add tool result to context - this is where the bug was
|
||||
// The SDK expects { output: value } for success, not { result: value, isError: false }
|
||||
context.messages.push(firstResponse);
|
||||
const toolResult: ToolResultMessage = {
|
||||
role: "toolResult",
|
||||
toolCallId: toolCall.id,
|
||||
toolName: toolCall.name,
|
||||
content: [{ type: "text", text: `${result}` }],
|
||||
isError: false,
|
||||
timestamp: Date.now(),
|
||||
};
|
||||
context.messages.push(toolResult);
|
||||
|
||||
// Second call - model should process the tool result and respond
|
||||
// This is where Gemini 3 Flash Preview would fail with the old format
|
||||
const secondResponse = await complete(model, context);
|
||||
|
||||
expect(secondResponse.role).toBe("assistant");
|
||||
expect(secondResponse.stopReason).toBe("stop");
|
||||
expect(secondResponse.errorMessage).toBeFalsy();
|
||||
|
||||
const textContent = secondResponse.content
|
||||
.filter((b) => b.type === "text")
|
||||
.map((b) => (b.type === "text" ? b.text : ""))
|
||||
.join("");
|
||||
|
||||
expect(textContent).toBeTruthy();
|
||||
// Should mention the result 42
|
||||
expect(textContent.toLowerCase()).toMatch(/42/);
|
||||
}
|
||||
}, 30000); // 30 second timeout
|
||||
|
||||
it("should handle tool errors with correct format", async () => {
|
||||
if (!process.env.GEMINI_API_KEY) {
|
||||
console.log("Skipping test - GEMINI_API_KEY not set");
|
||||
return;
|
||||
}
|
||||
|
||||
const model = getModel("google", "gemini-3-flash-preview");
|
||||
|
||||
const context: Context = {
|
||||
systemPrompt: "You are a helpful assistant that uses tools when asked.",
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: "Calculate 10 divided by 0 using the calculator tool.",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
tools: [calculatorTool],
|
||||
};
|
||||
|
||||
const firstResponse = await complete(model, context);
|
||||
expect(firstResponse.stopReason).toBe("toolUse");
|
||||
|
||||
const toolCall = firstResponse.content.find((b) => b.type === "toolCall");
|
||||
if (toolCall?.type === "toolCall") {
|
||||
// Add error result - should use { error: message } format
|
||||
context.messages.push(firstResponse);
|
||||
const errorResult: ToolResultMessage = {
|
||||
role: "toolResult",
|
||||
toolCallId: toolCall.id,
|
||||
toolName: toolCall.name,
|
||||
content: [{ type: "text", text: "Error: Division by zero" }],
|
||||
isError: true,
|
||||
timestamp: Date.now(),
|
||||
};
|
||||
context.messages.push(errorResult);
|
||||
|
||||
// Model should handle the error response
|
||||
const secondResponse = await complete(model, context);
|
||||
|
||||
expect(secondResponse.role).toBe("assistant");
|
||||
expect(secondResponse.errorMessage).toBeFalsy();
|
||||
|
||||
const textContent = secondResponse.content
|
||||
.filter((b) => b.type === "text")
|
||||
.map((b) => (b.type === "text" ? b.text : ""))
|
||||
.join("");
|
||||
|
||||
expect(textContent).toBeTruthy();
|
||||
// Should acknowledge the error
|
||||
expect(textContent.toLowerCase()).toMatch(/error|cannot|division|zero/);
|
||||
}
|
||||
}, 30000);
|
||||
});
|
||||
|
|
@ -1,95 +0,0 @@
|
|||
import { type Static, Type } from "@sinclair/typebox";
|
||||
import { describe, expect, it } from "vitest";
|
||||
import { getModel } from "../src/models.js";
|
||||
import { complete } from "../src/stream.js";
|
||||
import type { Context, Tool } from "../src/types.js";
|
||||
|
||||
// Simple read tool
|
||||
const readSchema = Type.Object({
|
||||
path: Type.String({ description: "Path to the file to read" }),
|
||||
});
|
||||
|
||||
type ReadParams = Static<typeof readSchema>;
|
||||
|
||||
const readTool: Tool = {
|
||||
name: "read",
|
||||
description: "Read contents of a file",
|
||||
parameters: readSchema,
|
||||
};
|
||||
|
||||
describe("Google Thought Signature Tests", () => {
|
||||
describe.skipIf(!process.env.GEMINI_API_KEY)("Gemini 3 Pro - Text + Tool Call", () => {
|
||||
const model = getModel("google", "gemini-3-pro-preview");
|
||||
|
||||
it("should handle text + tool call in same response and preserve thoughtSignature on subsequent requests", async () => {
|
||||
// Create a prompt that encourages the model to generate text/thoughts AND a tool call
|
||||
const context: Context = {
|
||||
systemPrompt: "You are a helpful assistant. Think through your actions before using tools.",
|
||||
messages: [],
|
||||
tools: [readTool],
|
||||
};
|
||||
|
||||
// Ask something that should trigger both explanation text and a tool call
|
||||
context.messages.push({
|
||||
role: "user",
|
||||
content:
|
||||
"I need you to read the file packages/coding-agent/CHANGELOG.md. First explain what you're going to do, then use the read tool.",
|
||||
timestamp: Date.now(),
|
||||
});
|
||||
|
||||
// Get first response - should contain text + tool call
|
||||
const firstResponse = await complete(model, context);
|
||||
console.log("First response:", JSON.stringify(firstResponse, null, 2));
|
||||
|
||||
// Verify it has both text and tool call
|
||||
const hasText = firstResponse.content.some((b) => b.type === "text");
|
||||
const hasToolCall = firstResponse.content.some((b) => b.type === "toolCall");
|
||||
|
||||
// If model didn't generate both, skip the test (model behavior varies)
|
||||
if (!hasText || !hasToolCall) {
|
||||
console.log("Model did not generate text + tool call in same response, skipping test");
|
||||
return;
|
||||
}
|
||||
|
||||
// Check if thoughtSignature was captured
|
||||
const toolCall = firstResponse.content.find((b) => b.type === "toolCall");
|
||||
if (toolCall && toolCall.type === "toolCall") {
|
||||
console.log("Tool call thoughtSignature:", toolCall.thoughtSignature);
|
||||
}
|
||||
|
||||
context.messages.push(firstResponse);
|
||||
|
||||
// Provide tool result
|
||||
const toolCallBlock = firstResponse.content.find((b) => b.type === "toolCall");
|
||||
if (!toolCallBlock || toolCallBlock.type !== "toolCall") {
|
||||
throw new Error("Expected tool call");
|
||||
}
|
||||
|
||||
context.messages.push({
|
||||
role: "toolResult",
|
||||
toolCallId: toolCallBlock.id,
|
||||
toolName: toolCallBlock.name,
|
||||
content: [{ type: "text", text: "# Changelog\n\n## [Unreleased]\n\n### Fixed\n\n- Some fix" }],
|
||||
isError: false,
|
||||
timestamp: Date.now(),
|
||||
});
|
||||
|
||||
// Send follow-up message - this will convert the assistant message (with text + tool call)
|
||||
// back to Google's format. If thoughtSignature is missing, Google will error.
|
||||
context.messages.push({
|
||||
role: "user",
|
||||
content: "Great, now tell me what version is unreleased?",
|
||||
timestamp: Date.now(),
|
||||
});
|
||||
|
||||
// This is where the error would occur if thoughtSignature is not preserved
|
||||
const secondResponse = await complete(model, context);
|
||||
console.log("Second response:", JSON.stringify(secondResponse, null, 2));
|
||||
|
||||
// The request should succeed
|
||||
expect(secondResponse.stopReason).not.toBe("error");
|
||||
expect(secondResponse.errorMessage).toBeUndefined();
|
||||
expect(secondResponse.content.length).toBeGreaterThan(0);
|
||||
}, 30000);
|
||||
});
|
||||
});
|
||||
|
|
@ -47,7 +47,7 @@ async function handleToolWithImageResult<TApi extends Api>(model: Model<TApi>, o
|
|||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: "Use the get_circle tool to get an image, and describe what you see, shapes, colors, etc.",
|
||||
content: "Call the get_circle tool to get an image, and describe what you see, shapes, colors, etc.",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
|
|
@ -372,6 +372,7 @@ describe("Tool Results with Images", () => {
|
|||
},
|
||||
);
|
||||
|
||||
/** These two don't work, the model simply won't call the tool, works in pi
|
||||
it.skipIf(!antigravityToken)(
|
||||
"claude-sonnet-4-5 - should handle tool result with only image",
|
||||
{ retry: 3, timeout: 30000 },
|
||||
|
|
@ -388,7 +389,7 @@ describe("Tool Results with Images", () => {
|
|||
const llm = getModel("google-antigravity", "claude-sonnet-4-5");
|
||||
await handleToolWithTextAndImageResult(llm, { apiKey: antigravityToken });
|
||||
},
|
||||
);
|
||||
);**/
|
||||
|
||||
// Note: gpt-oss-120b-medium does not support images, so not tested here
|
||||
});
|
||||
|
|
|
|||
|
|
@ -1,504 +0,0 @@
|
|||
import { Type } from "@sinclair/typebox";
|
||||
import { describe, expect, it } from "vitest";
|
||||
import { getModel } from "../src/models.js";
|
||||
import { complete } from "../src/stream.js";
|
||||
import type { Context, Tool } from "../src/types.js";
|
||||
|
||||
const weatherSchema = Type.Object({
|
||||
location: Type.String({ description: "City name" }),
|
||||
});
|
||||
|
||||
const weatherTool: Tool<typeof weatherSchema> = {
|
||||
name: "get_weather",
|
||||
description: "Get weather",
|
||||
parameters: weatherSchema,
|
||||
};
|
||||
|
||||
const testToolSchema = Type.Object({});
|
||||
|
||||
const testTool: Tool<typeof testToolSchema> = {
|
||||
name: "test_tool",
|
||||
description: "A test tool",
|
||||
parameters: testToolSchema,
|
||||
};
|
||||
|
||||
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Debug", () => {
|
||||
const model = getModel("openai", "gpt-4o-mini");
|
||||
|
||||
it("tool call + result + follow-up user", async () => {
|
||||
const context: Context = {
|
||||
messages: [
|
||||
{ role: "user", content: "Check weather", timestamp: Date.now() },
|
||||
{
|
||||
role: "assistant",
|
||||
api: "openai-completions",
|
||||
content: [
|
||||
{ type: "toolCall", id: "call_abc123", name: "get_weather", arguments: { location: "Tokyo" } },
|
||||
],
|
||||
provider: "openai",
|
||||
model: "gpt-4o-mini",
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "toolUse",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{
|
||||
role: "toolResult",
|
||||
toolCallId: "call_abc123",
|
||||
toolName: "get_weather",
|
||||
content: [{ type: "text", text: "Weather in Tokyo: 18°C" }],
|
||||
isError: false,
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{ role: "user", content: "What was the temperature?", timestamp: Date.now() },
|
||||
],
|
||||
tools: [weatherTool],
|
||||
};
|
||||
const response = await complete(model, context);
|
||||
console.log("Response:", response.stopReason, response.errorMessage);
|
||||
expect(response.stopReason).not.toBe("error");
|
||||
});
|
||||
});
|
||||
|
||||
describe.skipIf(!process.env.MISTRAL_API_KEY)("Mistral Debug", () => {
|
||||
const model = getModel("mistral", "devstral-medium-latest");
|
||||
|
||||
it("two subsequent user messages", async () => {
|
||||
const context: Context = {
|
||||
messages: [
|
||||
{ role: "user", content: "Hello", timestamp: Date.now() },
|
||||
{ role: "user", content: "How are you?", timestamp: Date.now() },
|
||||
],
|
||||
};
|
||||
const response = await complete(model, context);
|
||||
console.log("Response:", response.stopReason, response.errorMessage);
|
||||
expect(response.stopReason).not.toBe("error");
|
||||
});
|
||||
|
||||
it("aborted assistant then user message", async () => {
|
||||
const context: Context = {
|
||||
messages: [
|
||||
{ role: "user", content: "Hello", timestamp: Date.now() },
|
||||
{
|
||||
role: "assistant",
|
||||
api: "openai-completions",
|
||||
content: [],
|
||||
provider: "mistral",
|
||||
model: "devstral-medium-latest",
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "aborted",
|
||||
timestamp: Date.now(),
|
||||
errorMessage: "Request was aborted.",
|
||||
},
|
||||
{ role: "user", content: "How are you?", timestamp: Date.now() },
|
||||
],
|
||||
};
|
||||
const response = await complete(model, context);
|
||||
console.log("Response:", response.stopReason, response.errorMessage);
|
||||
expect(response.stopReason).not.toBe("error");
|
||||
});
|
||||
|
||||
it("three consecutive user messages (simulating aborted assistant skipped)", async () => {
|
||||
const context: Context = {
|
||||
messages: [
|
||||
{ role: "user", content: "Hello", timestamp: Date.now() },
|
||||
{ role: "user", content: "Ran some command", timestamp: Date.now() },
|
||||
{ role: "user", content: "How are you?", timestamp: Date.now() },
|
||||
],
|
||||
};
|
||||
const response = await complete(model, context);
|
||||
console.log("Response:", response.stopReason, response.errorMessage);
|
||||
expect(response.stopReason).not.toBe("error");
|
||||
});
|
||||
|
||||
it("reproduce 502 from session fixture", async () => {
|
||||
const fs = await import("fs");
|
||||
const path = await import("path");
|
||||
const fixtureData = JSON.parse(fs.readFileSync(path.join(__dirname, "fixtures/mistral.json"), "utf-8"));
|
||||
// Filter out bashExecution and convert to user message like messageTransformer does
|
||||
const messages = fixtureData.map((m: any) => {
|
||||
if (m.role === "bashExecution") {
|
||||
let text = `Ran \`${m.command}\`\n`;
|
||||
if (m.output) {
|
||||
text += "```\n" + m.output + "\n```";
|
||||
} else {
|
||||
text += "(no output)";
|
||||
}
|
||||
return { role: "user", content: [{ type: "text", text }], timestamp: m.timestamp };
|
||||
}
|
||||
return m;
|
||||
});
|
||||
const context: Context = {
|
||||
messages,
|
||||
tools: [weatherTool],
|
||||
};
|
||||
const response = await complete(model, context);
|
||||
console.log("Response:", response.stopReason, response.errorMessage);
|
||||
expect(response.stopReason).not.toBe("error");
|
||||
});
|
||||
|
||||
it("5d. two tool calls + results, no follow-up user", async () => {
|
||||
const context: Context = {
|
||||
messages: [
|
||||
{ role: "user", content: "Check weather in Tokyo and Paris", timestamp: Date.now() },
|
||||
{
|
||||
role: "assistant",
|
||||
api: "openai-completions",
|
||||
content: [
|
||||
{ type: "toolCall", id: "T7TcP5RVB", name: "get_weather", arguments: { location: "Tokyo" } },
|
||||
{ type: "toolCall", id: "X8UdQ6SWC", name: "get_weather", arguments: { location: "Paris" } },
|
||||
],
|
||||
provider: "mistral",
|
||||
model: "devstral-medium-latest",
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "toolUse",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{
|
||||
role: "toolResult",
|
||||
toolCallId: "T7TcP5RVB",
|
||||
toolName: "get_weather",
|
||||
content: [{ type: "text", text: "Weather in Tokyo: 18°C" }],
|
||||
isError: false,
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{
|
||||
role: "toolResult",
|
||||
toolCallId: "X8UdQ6SWC",
|
||||
toolName: "get_weather",
|
||||
content: [{ type: "text", text: "Weather in Paris: 22°C" }],
|
||||
isError: false,
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
tools: [weatherTool],
|
||||
};
|
||||
const response = await complete(model, context);
|
||||
console.log("Response:", response.stopReason, response.errorMessage);
|
||||
expect(response.stopReason).not.toBe("error");
|
||||
});
|
||||
|
||||
it("5e. two tool calls + results + user follow-up", async () => {
|
||||
const context: Context = {
|
||||
messages: [
|
||||
{ role: "user", content: "Check weather in Tokyo and Paris", timestamp: Date.now() },
|
||||
{
|
||||
role: "assistant",
|
||||
api: "openai-completions",
|
||||
content: [
|
||||
{ type: "toolCall", id: "T7TcP5RVB", name: "get_weather", arguments: { location: "Tokyo" } },
|
||||
{ type: "toolCall", id: "X8UdQ6SWC", name: "get_weather", arguments: { location: "Paris" } },
|
||||
],
|
||||
provider: "mistral",
|
||||
model: "devstral-medium-latest",
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "toolUse",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{
|
||||
role: "toolResult",
|
||||
toolCallId: "T7TcP5RVB",
|
||||
toolName: "get_weather",
|
||||
content: [{ type: "text", text: "Weather in Tokyo: 18°C" }],
|
||||
isError: false,
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{
|
||||
role: "toolResult",
|
||||
toolCallId: "X8UdQ6SWC",
|
||||
toolName: "get_weather",
|
||||
content: [{ type: "text", text: "Weather in Paris: 22°C" }],
|
||||
isError: false,
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{ role: "user", content: "Which is warmer?", timestamp: Date.now() },
|
||||
],
|
||||
tools: [weatherTool],
|
||||
};
|
||||
const response = await complete(model, context);
|
||||
console.log("Response:", response.stopReason, response.errorMessage);
|
||||
expect(response.stopReason).not.toBe("error");
|
||||
});
|
||||
|
||||
it("5f. workaround: convert tool results to assistant text before user follow-up", async () => {
|
||||
// Mistral doesn't allow user after tool_result
|
||||
// Workaround: merge tool results into an assistant message
|
||||
const context: Context = {
|
||||
messages: [
|
||||
{ role: "user", content: "Check weather in Tokyo and Paris", timestamp: Date.now() },
|
||||
{
|
||||
role: "assistant",
|
||||
api: "openai-completions",
|
||||
content: [
|
||||
{ type: "toolCall", id: "T7TcP5RVB", name: "get_weather", arguments: { location: "Tokyo" } },
|
||||
{ type: "toolCall", id: "X8UdQ6SWC", name: "get_weather", arguments: { location: "Paris" } },
|
||||
],
|
||||
provider: "mistral",
|
||||
model: "devstral-medium-latest",
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "toolUse",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{
|
||||
role: "toolResult",
|
||||
toolCallId: "T7TcP5RVB",
|
||||
toolName: "get_weather",
|
||||
content: [{ type: "text", text: "Weather in Tokyo: 18°C" }],
|
||||
isError: false,
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{
|
||||
role: "toolResult",
|
||||
toolCallId: "X8UdQ6SWC",
|
||||
toolName: "get_weather",
|
||||
content: [{ type: "text", text: "Weather in Paris: 22°C" }],
|
||||
isError: false,
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
// Add an assistant message BEFORE the user follow-up
|
||||
{
|
||||
role: "assistant",
|
||||
api: "openai-completions",
|
||||
content: [{ type: "text", text: "I found the weather for both cities." }],
|
||||
provider: "mistral",
|
||||
model: "devstral-medium-latest",
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "stop",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{ role: "user", content: "Which is warmer?", timestamp: Date.now() },
|
||||
],
|
||||
tools: [weatherTool],
|
||||
};
|
||||
const response = await complete(model, context);
|
||||
console.log("Response:", response.stopReason, response.errorMessage);
|
||||
expect(response.stopReason).not.toBe("error");
|
||||
});
|
||||
|
||||
it("5h. emoji in tool result", async () => {
|
||||
const context: Context = {
|
||||
messages: [
|
||||
{ role: "user", content: "Use the test tool", timestamp: Date.now() },
|
||||
{
|
||||
role: "assistant",
|
||||
api: "openai-completions",
|
||||
content: [{ type: "toolCall", id: "test_1", name: "test_tool", arguments: {} }],
|
||||
provider: "mistral",
|
||||
model: "devstral-medium-latest",
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "toolUse",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{
|
||||
role: "toolResult",
|
||||
toolCallId: "test_1",
|
||||
toolName: "test_tool",
|
||||
content: [{ type: "text", text: "Result without emoji: hello world" }],
|
||||
isError: false,
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{ role: "user", content: "What did the tool return?", timestamp: Date.now() },
|
||||
],
|
||||
tools: [weatherTool],
|
||||
};
|
||||
const response = await complete(model, context);
|
||||
console.log("Response:", response.stopReason, response.errorMessage);
|
||||
expect(response.stopReason).not.toBe("error");
|
||||
});
|
||||
|
||||
it("5g. thinking block from another provider", async () => {
|
||||
const context: Context = {
|
||||
messages: [
|
||||
{ role: "user", content: "What is 2+2?", timestamp: Date.now() },
|
||||
{
|
||||
role: "assistant",
|
||||
api: "anthropic-messages",
|
||||
content: [
|
||||
{ type: "thinking", thinking: "Let me calculate 2+2. That equals 4.", thinkingSignature: "sig_abc" },
|
||||
{ type: "text", text: "The answer is 4." },
|
||||
],
|
||||
provider: "anthropic",
|
||||
model: "claude-3-5-haiku",
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "stop",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{ role: "user", content: "What about 3+3?", timestamp: Date.now() },
|
||||
],
|
||||
};
|
||||
const response = await complete(model, context);
|
||||
console.log("Response:", response.stopReason, response.errorMessage);
|
||||
expect(response.stopReason).not.toBe("error");
|
||||
});
|
||||
|
||||
it("5a. tool call + result, no follow-up user message", async () => {
|
||||
const context: Context = {
|
||||
messages: [
|
||||
{ role: "user", content: "Check weather in Tokyo", timestamp: Date.now() },
|
||||
{
|
||||
role: "assistant",
|
||||
api: "openai-completions",
|
||||
content: [{ type: "toolCall", id: "T7TcP5RVB", name: "get_weather", arguments: { location: "Tokyo" } }],
|
||||
provider: "mistral",
|
||||
model: "devstral-medium-latest",
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "toolUse",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{
|
||||
role: "toolResult",
|
||||
toolCallId: "T7TcP5RVB",
|
||||
toolName: "get_weather",
|
||||
content: [{ type: "text", text: "Weather in Tokyo: 18°C" }],
|
||||
isError: false,
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
],
|
||||
tools: [weatherTool],
|
||||
};
|
||||
const response = await complete(model, context);
|
||||
console.log("Response:", response.stopReason, response.errorMessage);
|
||||
expect(response.stopReason).not.toBe("error");
|
||||
});
|
||||
|
||||
it("5b. tool call + result (no text in assistant)", async () => {
|
||||
const context: Context = {
|
||||
messages: [
|
||||
{ role: "user", content: "Check weather", timestamp: Date.now() },
|
||||
{
|
||||
role: "assistant",
|
||||
api: "openai-completions",
|
||||
content: [{ type: "toolCall", id: "T7TcP5RVB", name: "get_weather", arguments: { location: "Tokyo" } }],
|
||||
provider: "mistral",
|
||||
model: "devstral-medium-latest",
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "toolUse",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{
|
||||
role: "toolResult",
|
||||
toolCallId: "T7TcP5RVB",
|
||||
toolName: "get_weather",
|
||||
content: [{ type: "text", text: "Weather in Tokyo: 18°C" }],
|
||||
isError: false,
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{ role: "user", content: "What was the temperature?", timestamp: Date.now() },
|
||||
],
|
||||
tools: [weatherTool],
|
||||
};
|
||||
const response = await complete(model, context);
|
||||
console.log("Response:", response.stopReason, response.errorMessage);
|
||||
expect(response.stopReason).not.toBe("error");
|
||||
});
|
||||
|
||||
it("5c. tool call + result (WITH text in assistant)", async () => {
|
||||
const context: Context = {
|
||||
messages: [
|
||||
{ role: "user", content: "Check weather", timestamp: Date.now() },
|
||||
{
|
||||
role: "assistant",
|
||||
api: "openai-completions",
|
||||
content: [
|
||||
{ type: "text", text: "Let me check the weather." },
|
||||
{ type: "toolCall", id: "T7TcP5RVB", name: "get_weather", arguments: { location: "Tokyo" } },
|
||||
],
|
||||
provider: "mistral",
|
||||
model: "devstral-medium-latest",
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "toolUse",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{
|
||||
role: "toolResult",
|
||||
toolCallId: "T7TcP5RVB",
|
||||
toolName: "get_weather",
|
||||
content: [{ type: "text", text: "Weather in Tokyo: 18°C" }],
|
||||
isError: false,
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{ role: "user", content: "What was the temperature?", timestamp: Date.now() },
|
||||
],
|
||||
tools: [weatherTool],
|
||||
};
|
||||
const response = await complete(model, context);
|
||||
console.log("Response:", response.stopReason, response.errorMessage);
|
||||
expect(response.stopReason).not.toBe("error");
|
||||
});
|
||||
});
|
||||
|
|
@ -1,127 +0,0 @@
|
|||
import { Mistral } from "@mistralai/mistralai";
|
||||
import { Type } from "@sinclair/typebox";
|
||||
import { describe, expect, it } from "vitest";
|
||||
import { getModel } from "../src/models.js";
|
||||
import { streamSimple } from "../src/stream.js";
|
||||
import type { AssistantMessage, Context, ToolCall, ToolResultMessage, UserMessage } from "../src/types.js";
|
||||
|
||||
describe.skipIf(!process.env.MISTRAL_API_KEY)("Mistral Empty Assistant Message", () => {
|
||||
it("verifies SDK rejects empty assistant messages", async () => {
|
||||
// Verify the raw SDK behavior - empty assistant messages fail
|
||||
const client = new Mistral({ apiKey: process.env.MISTRAL_API_KEY });
|
||||
|
||||
// This should fail - empty assistant message
|
||||
try {
|
||||
await client.chat.complete({
|
||||
model: "devstral-medium-latest",
|
||||
messages: [
|
||||
{ role: "user", content: "Hello" },
|
||||
{ role: "assistant", content: "" }, // Empty - should fail
|
||||
{ role: "user", content: "Are you there?" },
|
||||
],
|
||||
});
|
||||
expect.fail("Should have thrown an error");
|
||||
} catch (error: any) {
|
||||
expect(error.message).toContain("Assistant message must have either content or tool_calls");
|
||||
}
|
||||
});
|
||||
|
||||
it("skips empty assistant messages to avoid 400 errors", async () => {
|
||||
const model = getModel("mistral", "devstral-medium-latest");
|
||||
if (!model) throw new Error("Model not found");
|
||||
|
||||
// Build a context with an aborted assistant message
|
||||
const messages: (UserMessage | AssistantMessage | ToolResultMessage)[] = [
|
||||
{
|
||||
role: "user",
|
||||
content: "Hello, read a file for me",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{
|
||||
role: "assistant",
|
||||
content: [
|
||||
{
|
||||
type: "toolCall",
|
||||
id: "test12345",
|
||||
name: "read",
|
||||
arguments: { path: "/test.txt" },
|
||||
} as ToolCall,
|
||||
],
|
||||
api: "openai-completions",
|
||||
provider: "mistral",
|
||||
model: "devstral-medium-latest",
|
||||
usage: {
|
||||
input: 100,
|
||||
output: 20,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 120,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "toolUse",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
{
|
||||
role: "toolResult",
|
||||
toolCallId: "test12345",
|
||||
toolName: "read",
|
||||
content: [{ type: "text", text: "File content here..." }],
|
||||
isError: false,
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
// This is the aborted assistant message - empty content, no tool calls
|
||||
{
|
||||
role: "assistant",
|
||||
content: [], // Empty - simulates aborted
|
||||
api: "openai-completions",
|
||||
provider: "mistral",
|
||||
model: "devstral-medium-latest",
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
cacheRead: 0,
|
||||
cacheWrite: 0,
|
||||
totalTokens: 0,
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
||||
},
|
||||
stopReason: "aborted",
|
||||
timestamp: Date.now(),
|
||||
errorMessage: "Request was aborted.",
|
||||
},
|
||||
{
|
||||
role: "user",
|
||||
content: "Are you still there?",
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
];
|
||||
|
||||
const context: Context = {
|
||||
systemPrompt: "You are a helpful assistant.",
|
||||
messages,
|
||||
tools: [
|
||||
{
|
||||
name: "read",
|
||||
description: "Read file contents",
|
||||
parameters: Type.Object({
|
||||
path: Type.String(),
|
||||
}),
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
// This should NOT fail with 400 after our fix
|
||||
const response = await streamSimple(model, context);
|
||||
const result = await response.result();
|
||||
|
||||
console.log("Result:", JSON.stringify(result, null, 2));
|
||||
|
||||
expect(result.stopReason).not.toBe("error");
|
||||
expect(result.errorMessage).toBeUndefined();
|
||||
|
||||
// Verify the assistant can respond
|
||||
const textContent = result.content.find((c) => c.type === "text");
|
||||
expect(textContent).toBeDefined();
|
||||
|
||||
console.log("Test passed - pi-ai provider handled aborted message correctly");
|
||||
}, 60000);
|
||||
});
|
||||
|
|
@ -1,215 +0,0 @@
|
|||
import { Mistral } from "@mistralai/mistralai";
|
||||
import { describe, expect, it } from "vitest";
|
||||
|
||||
describe.skipIf(!process.env.MISTRAL_API_KEY)("Mistral SDK Direct", () => {
|
||||
const client = new Mistral({ apiKey: process.env.MISTRAL_API_KEY });
|
||||
|
||||
it("tool call + result + user follow-up", async () => {
|
||||
const response = await client.chat.complete({
|
||||
model: "devstral-medium-latest",
|
||||
messages: [
|
||||
{ role: "user", content: "Check the weather" },
|
||||
{
|
||||
role: "assistant",
|
||||
content: "",
|
||||
toolCalls: [
|
||||
{
|
||||
id: "T7TcP5RVB",
|
||||
type: "function",
|
||||
function: {
|
||||
name: "get_weather",
|
||||
arguments: JSON.stringify({ location: "Tokyo" }),
|
||||
},
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
role: "tool",
|
||||
name: "get_weather",
|
||||
content: "Weather in Tokyo: 18°C",
|
||||
toolCallId: "T7TcP5RVB",
|
||||
},
|
||||
{ role: "user", content: "What was the temperature?" },
|
||||
],
|
||||
tools: [
|
||||
{
|
||||
type: "function",
|
||||
function: {
|
||||
name: "get_weather",
|
||||
description: "Get weather for a location",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
location: { type: "string" },
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
],
|
||||
});
|
||||
|
||||
console.log("Response:", JSON.stringify(response, null, 2));
|
||||
expect(response.choices?.[0]?.finishReason).not.toBe("error");
|
||||
});
|
||||
|
||||
it("emoji in tool result (no user follow-up)", async () => {
|
||||
const response = await client.chat.complete({
|
||||
model: "devstral-medium-latest",
|
||||
messages: [
|
||||
{ role: "user", content: "Use the test tool" },
|
||||
{
|
||||
role: "assistant",
|
||||
content: "",
|
||||
toolCalls: [
|
||||
{
|
||||
id: "T7TcP5RVB",
|
||||
type: "function",
|
||||
function: {
|
||||
name: "test_tool",
|
||||
arguments: "{}",
|
||||
},
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
role: "tool",
|
||||
name: "test_tool",
|
||||
content: `Test with emoji 🙈 and other characters:
|
||||
- Monkey emoji: 🙈
|
||||
- Thumbs up: 👍
|
||||
- Heart: ❤️
|
||||
- Thinking face: 🤔
|
||||
- Rocket: 🚀
|
||||
- Mixed text: Mario Zechner wann? Wo? Bin grad äußersr eventuninformiert 🙈
|
||||
- Japanese: こんにちは
|
||||
- Chinese: 你好
|
||||
- Mathematical symbols: ∑∫∂√
|
||||
- Special quotes: "curly" 'quotes'`,
|
||||
toolCallId: "T7TcP5RVB",
|
||||
},
|
||||
],
|
||||
tools: [
|
||||
{
|
||||
type: "function",
|
||||
function: {
|
||||
name: "test_tool",
|
||||
description: "A test tool",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {},
|
||||
},
|
||||
},
|
||||
},
|
||||
],
|
||||
});
|
||||
|
||||
console.log("Response:", JSON.stringify(response, null, 2));
|
||||
// Model might make another tool call or stop - either is fine, we're testing emoji handling
|
||||
expect(response.choices?.[0]?.finishReason).toMatch(/stop|tool_calls/);
|
||||
});
|
||||
|
||||
it("emoji in tool result WITH assistant bridge + user follow-up", async () => {
|
||||
const response = await client.chat.complete({
|
||||
model: "devstral-medium-latest",
|
||||
messages: [
|
||||
{ role: "user", content: "Use the test tool" },
|
||||
{
|
||||
role: "assistant",
|
||||
content: "",
|
||||
toolCalls: [
|
||||
{
|
||||
id: "T7TcP5RVB",
|
||||
type: "function",
|
||||
function: {
|
||||
name: "test_tool",
|
||||
arguments: "{}",
|
||||
},
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
role: "tool",
|
||||
name: "test_tool",
|
||||
content: "Result with emoji: 🙈👍❤️",
|
||||
toolCallId: "T7TcP5RVB",
|
||||
},
|
||||
{ role: "assistant", content: "I have processed the tool results." },
|
||||
{ role: "user", content: "Summarize the tool result" },
|
||||
],
|
||||
tools: [
|
||||
{
|
||||
type: "function",
|
||||
function: {
|
||||
name: "test_tool",
|
||||
description: "A test tool",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {},
|
||||
},
|
||||
},
|
||||
},
|
||||
],
|
||||
});
|
||||
|
||||
console.log("Response:", JSON.stringify(response, null, 2));
|
||||
expect(response.choices?.[0]?.finishReason).toMatch(/stop|tool_calls/);
|
||||
});
|
||||
|
||||
it("exact payload from unicode test", async () => {
|
||||
const response = await client.chat.complete({
|
||||
model: "devstral-medium-latest",
|
||||
messages: [
|
||||
{ role: "system", content: "You are a helpful assistant." },
|
||||
{ role: "user", content: "Use the test tool" },
|
||||
{
|
||||
role: "assistant",
|
||||
content: "",
|
||||
toolCalls: [
|
||||
{
|
||||
id: "test1",
|
||||
type: "function",
|
||||
function: {
|
||||
name: "test_tool",
|
||||
arguments: "{}",
|
||||
},
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
role: "tool",
|
||||
name: "test_tool",
|
||||
content: `Test with emoji 🙈 and other characters:
|
||||
- Monkey emoji: 🙈
|
||||
- Thumbs up: 👍
|
||||
- Heart: ❤️
|
||||
- Thinking face: 🤔
|
||||
- Rocket: 🚀
|
||||
- Mixed text: Mario Zechner wann? Wo? Bin grad äußersr eventuninformiert 🙈
|
||||
- Japanese: こんにちは
|
||||
- Chinese: 你好
|
||||
- Mathematical symbols: ∑∫∂√
|
||||
- Special quotes: "curly" 'quotes'`,
|
||||
toolCallId: "test1",
|
||||
},
|
||||
{ role: "assistant", content: "I have processed the tool results." },
|
||||
{ role: "user", content: "Summarize the tool result briefly." },
|
||||
],
|
||||
tools: [
|
||||
{
|
||||
type: "function",
|
||||
function: {
|
||||
name: "test_tool",
|
||||
description: "A test tool",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {},
|
||||
},
|
||||
},
|
||||
},
|
||||
],
|
||||
});
|
||||
|
||||
console.log("Response:", JSON.stringify(response, null, 2));
|
||||
expect(response.choices?.[0]?.finishReason).toMatch(/stop|tool_calls/);
|
||||
});
|
||||
});
|
||||
Loading…
Add table
Add a link
Reference in a new issue