mirror of
https://github.com/harivansh-afk/clanker-agent.git
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- Rename all package names from companion-* to clanker-* - Update npm scopes from @mariozechner to @harivansh-afk - Rename config directories .companion -> .clanker - Rename environment variables COMPANION_* -> CLANKER_* - Update all documentation, README files, and install scripts - Rename package directories (companion-channels, companion-grind, companion-teams) - Update GitHub URLs to harivansh-afk/clanker-agent - Preserve full git history from companion-cloud monorepo
412 lines
13 KiB
TypeScript
412 lines
13 KiB
TypeScript
import { Type } from "@sinclair/typebox";
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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 } from "../src/stream.js";
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import type { Api, Context, Model, StreamOptions, Tool } from "../src/types.js";
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type StreamOptionsWithExtras = StreamOptions & Record<string, unknown>;
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import {
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hasAzureOpenAICredentials,
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resolveAzureDeploymentName,
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} from "./azure-utils.js";
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import { hasBedrockCredentials } from "./bedrock-utils.js";
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import { resolveApiKey } from "./oauth.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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resolveApiKey("openai-codex"),
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]);
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const [
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anthropicOAuthToken,
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githubCopilotToken,
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geminiCliToken,
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antigravityToken,
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openaiCodexToken,
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] = oauthTokens;
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// Simple calculate tool
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const calculateSchema = Type.Object({
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expression: Type.String({
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description: "The mathematical expression to evaluate",
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}),
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});
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const calculateTool: Tool = {
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name: "calculate",
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description: "Evaluate mathematical expressions",
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parameters: calculateSchema,
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};
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async function testToolCallWithoutResult<TApi extends Api>(
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model: Model<TApi>,
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options: StreamOptionsWithExtras = {},
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) {
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// Step 1: Create context with the calculate tool
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const context: Context = {
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systemPrompt:
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"You are a helpful assistant. Use the calculate tool when asked to perform calculations.",
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messages: [],
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tools: [calculateTool],
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};
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// Step 2: Ask the LLM to make a tool call
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context.messages.push({
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role: "user",
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content: "Please calculate 25 * 18 using the calculate tool.",
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timestamp: Date.now(),
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});
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// Step 3: Get the assistant's response (should contain a tool call)
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const firstResponse = await complete(model, context, options);
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context.messages.push(firstResponse);
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console.log("First response:", JSON.stringify(firstResponse, null, 2));
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// Verify the response contains a tool call
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const hasToolCall = firstResponse.content.some(
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(block) => block.type === "toolCall",
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);
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expect(hasToolCall).toBe(true);
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if (!hasToolCall) {
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throw new Error(
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"Expected assistant to make a tool call, but none was found",
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);
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}
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// Step 4: Send a user message WITHOUT providing tool result
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// This simulates the scenario where a tool call was aborted/cancelled
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context.messages.push({
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role: "user",
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content: "Never mind, just tell me what is 2+2?",
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timestamp: Date.now(),
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});
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// Step 5: The fix should filter out the orphaned tool call, and the request should succeed
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const secondResponse = await complete(model, context, options);
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console.log("Second response:", JSON.stringify(secondResponse, null, 2));
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// The request should succeed (not error) - that's the main thing we're testing
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expect(secondResponse.stopReason).not.toBe("error");
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// Should have some content in the response
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expect(secondResponse.content.length).toBeGreaterThan(0);
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// The LLM may choose to answer directly or make a new tool call - either is fine
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// The important thing is it didn't fail with the orphaned tool call error
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const textContent = secondResponse.content
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.filter((block) => block.type === "text")
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.map((block) => (block.type === "text" ? block.text : ""))
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.join(" ");
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const toolCalls = secondResponse.content.filter(
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(block) => block.type === "toolCall",
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).length;
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expect(toolCalls || textContent.length).toBeGreaterThan(0);
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console.log("Answer:", textContent);
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// Verify the stop reason is either "stop" or "toolUse" (new tool call)
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expect(["stop", "toolUse"]).toContain(secondResponse.stopReason);
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}
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describe("Tool Call Without Result Tests", () => {
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// =========================================================================
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// API Key-based providers
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// =========================================================================
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describe.skipIf(!process.env.GEMINI_API_KEY)("Google Provider", () => {
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const model = getModel("google", "gemini-2.5-flash");
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it(
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"should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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await testToolCallWithoutResult(model);
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},
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);
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});
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describe.skipIf(!process.env.OPENAI_API_KEY)(
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"OpenAI Completions Provider",
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() => {
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const { compat: _compat, ...baseModel } = getModel(
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"openai",
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"gpt-4o-mini",
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)!;
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void _compat;
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const model: Model<"openai-completions"> = {
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...baseModel,
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api: "openai-completions",
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};
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it(
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"should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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await testToolCallWithoutResult(model);
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},
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);
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},
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);
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describe.skipIf(!process.env.OPENAI_API_KEY)(
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"OpenAI Responses Provider",
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() => {
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const model = getModel("openai", "gpt-5-mini");
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it(
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"should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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await testToolCallWithoutResult(model);
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},
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);
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},
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);
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describe.skipIf(!hasAzureOpenAICredentials())(
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"Azure OpenAI Responses Provider",
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() => {
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const model = getModel("azure-openai-responses", "gpt-4o-mini");
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const azureDeploymentName = resolveAzureDeploymentName(model.id);
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const azureOptions = azureDeploymentName ? { azureDeploymentName } : {};
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it(
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"should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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await testToolCallWithoutResult(model, azureOptions);
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},
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);
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},
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);
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describe.skipIf(!process.env.ANTHROPIC_API_KEY)("Anthropic Provider", () => {
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const model = getModel("anthropic", "claude-3-5-haiku-20241022");
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it(
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"should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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await testToolCallWithoutResult(model);
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},
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);
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});
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describe.skipIf(!process.env.XAI_API_KEY)("xAI Provider", () => {
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const model = getModel("xai", "grok-3-fast");
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it(
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"should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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await testToolCallWithoutResult(model);
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},
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);
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});
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describe.skipIf(!process.env.GROQ_API_KEY)("Groq Provider", () => {
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const model = getModel("groq", "openai/gpt-oss-20b");
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it(
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"should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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await testToolCallWithoutResult(model);
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},
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);
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});
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describe.skipIf(!process.env.CEREBRAS_API_KEY)("Cerebras Provider", () => {
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const model = getModel("cerebras", "gpt-oss-120b");
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it(
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"should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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await testToolCallWithoutResult(model);
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},
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);
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});
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describe.skipIf(!process.env.HF_TOKEN)("Hugging Face Provider", () => {
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const model = getModel("huggingface", "moonshotai/Kimi-K2.5");
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it(
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"should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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await testToolCallWithoutResult(model);
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},
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);
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});
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describe.skipIf(!process.env.ZAI_API_KEY)("zAI Provider", () => {
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const model = getModel("zai", "glm-4.5-flash");
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it(
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"should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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await testToolCallWithoutResult(model);
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},
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);
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});
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describe.skipIf(!process.env.MISTRAL_API_KEY)("Mistral Provider", () => {
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const model = getModel("mistral", "devstral-medium-latest");
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it(
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"should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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await testToolCallWithoutResult(model);
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},
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);
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});
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describe.skipIf(!process.env.MINIMAX_API_KEY)("MiniMax Provider", () => {
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const model = getModel("minimax", "MiniMax-M2.1");
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it(
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"should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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await testToolCallWithoutResult(model);
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},
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);
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});
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describe.skipIf(!process.env.KIMI_API_KEY)("Kimi For Coding Provider", () => {
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const model = getModel("kimi-coding", "kimi-k2-thinking");
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it(
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"should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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await testToolCallWithoutResult(model);
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},
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);
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});
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describe.skipIf(!process.env.AI_GATEWAY_API_KEY)(
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"Vercel AI Gateway Provider",
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() => {
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const model = getModel("vercel-ai-gateway", "google/gemini-2.5-flash");
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it(
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"should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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await testToolCallWithoutResult(model);
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},
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);
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},
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);
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describe.skipIf(!hasBedrockCredentials())("Amazon Bedrock Provider", () => {
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const model = getModel(
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"amazon-bedrock",
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"global.anthropic.claude-sonnet-4-5-20250929-v1:0",
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);
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it(
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"should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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await testToolCallWithoutResult(model);
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},
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);
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});
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// =========================================================================
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// OAuth-based providers (credentials from ~/.clanker/agent/oauth.json)
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// =========================================================================
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describe("Anthropic OAuth Provider", () => {
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const model = getModel("anthropic", "claude-3-5-haiku-20241022");
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it.skipIf(!anthropicOAuthToken)(
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"should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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await testToolCallWithoutResult(model, { apiKey: anthropicOAuthToken });
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},
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);
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});
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describe("GitHub Copilot Provider", () => {
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it.skipIf(!githubCopilotToken)(
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"gpt-4o - should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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const model = getModel("github-copilot", "gpt-4o");
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await testToolCallWithoutResult(model, { apiKey: githubCopilotToken });
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},
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);
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it.skipIf(!githubCopilotToken)(
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"claude-sonnet-4 - should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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const model = getModel("github-copilot", "claude-sonnet-4");
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await testToolCallWithoutResult(model, { apiKey: githubCopilotToken });
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},
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);
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});
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describe("Google Gemini CLI Provider", () => {
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it.skipIf(!geminiCliToken)(
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"gemini-2.5-flash - should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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const model = getModel("google-gemini-cli", "gemini-2.5-flash");
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await testToolCallWithoutResult(model, { apiKey: geminiCliToken });
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},
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);
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});
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describe("Google Antigravity Provider", () => {
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it.skipIf(!antigravityToken)(
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"gemini-3-flash - should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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const model = getModel("google-antigravity", "gemini-3-flash");
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await testToolCallWithoutResult(model, { apiKey: antigravityToken });
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},
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);
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it.skipIf(!antigravityToken)(
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"claude-sonnet-4-5 - should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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const model = getModel("google-antigravity", "claude-sonnet-4-5");
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await testToolCallWithoutResult(model, { apiKey: antigravityToken });
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},
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);
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it.skipIf(!antigravityToken)(
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"gpt-oss-120b-medium - should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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const model = getModel("google-antigravity", "gpt-oss-120b-medium");
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await testToolCallWithoutResult(model, { apiKey: antigravityToken });
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},
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);
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});
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describe("OpenAI Codex Provider", () => {
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it.skipIf(!openaiCodexToken)(
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"gpt-5.2-codex - should filter out tool calls without corresponding tool results",
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{ retry: 3, timeout: 30000 },
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async () => {
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const model = getModel("openai-codex", "gpt-5.2-codex");
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await testToolCallWithoutResult(model, { apiKey: openaiCodexToken });
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},
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);
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});
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});
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