mirror of
https://github.com/harivansh-afk/clanker-agent.git
synced 2026-04-15 04:03:27 +00:00
Harivansh Rathi
536241053c
Complete the remaining pi-to-companion rename across companion-os, web, vm-orchestrator, docker, and archived fixtures. Verification: - semantic rg sweeps for Pi/piConfig/getPi/.pi runtime references - npm run check in apps/companion-os (fails in this worktree: biome not found) Co-authored-by: Codex <noreply@openai.com>
1912 lines
53 KiB
TypeScript
1912 lines
53 KiB
TypeScript
import { Type } from "@sinclair/typebox";
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import { type ChildProcess, execSync, spawn } from "child_process";
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import { readFileSync } from "fs";
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import { dirname, join } from "path";
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import { fileURLToPath } from "url";
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import { afterAll, beforeAll, 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 type {
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Api,
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Context,
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ImageContent,
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Model,
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StreamOptions,
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Tool,
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ToolResultMessage,
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} from "../src/types.js";
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type StreamOptionsWithExtras = StreamOptions & Record<string, unknown>;
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import { StringEnum } from "../src/utils/typebox-helpers.js";
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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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const __filename = fileURLToPath(import.meta.url);
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const __dirname = dirname(__filename);
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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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// Calculator tool definition (same as examples)
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// Note: Using StringEnum helper because Google's API doesn't support anyOf/const patterns
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// that Type.Enum generates. Google requires { type: "string", enum: [...] } format.
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const calculatorSchema = Type.Object({
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a: Type.Number({ description: "First number" }),
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b: Type.Number({ description: "Second number" }),
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operation: StringEnum(["add", "subtract", "multiply", "divide"], {
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description:
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"The operation to perform. One of 'add', 'subtract', 'multiply', 'divide'.",
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}),
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});
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const calculatorTool: Tool<typeof calculatorSchema> = {
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name: "math_operation",
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description: "Perform basic arithmetic operations",
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parameters: calculatorSchema,
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};
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async function basicTextGeneration<TApi extends Api>(
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model: Model<TApi>,
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options?: StreamOptionsWithExtras,
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) {
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const context: Context = {
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systemPrompt: "You are a helpful assistant. Be concise.",
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messages: [
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{
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role: "user",
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content: "Reply with exactly: 'Hello test successful'",
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timestamp: Date.now(),
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},
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],
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};
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const response = await complete(model, context, options);
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expect(response.role).toBe("assistant");
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expect(response.content).toBeTruthy();
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expect(response.usage.input + response.usage.cacheRead).toBeGreaterThan(0);
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expect(response.usage.output).toBeGreaterThan(0);
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expect(response.errorMessage).toBeFalsy();
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expect(
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response.content.map((b) => (b.type === "text" ? b.text : "")).join(""),
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).toContain("Hello test successful");
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context.messages.push(response);
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context.messages.push({
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role: "user",
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content: "Now say 'Goodbye test successful'",
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timestamp: Date.now(),
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});
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const secondResponse = await complete(model, context, options);
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expect(secondResponse.role).toBe("assistant");
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expect(secondResponse.content).toBeTruthy();
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expect(
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secondResponse.usage.input + secondResponse.usage.cacheRead,
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).toBeGreaterThan(0);
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expect(secondResponse.usage.output).toBeGreaterThan(0);
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expect(secondResponse.errorMessage).toBeFalsy();
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expect(
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secondResponse.content
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.map((b) => (b.type === "text" ? b.text : ""))
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.join(""),
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).toContain("Goodbye test successful");
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}
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async function handleToolCall<TApi extends Api>(
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model: Model<TApi>,
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options?: StreamOptionsWithExtras,
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) {
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const context: Context = {
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systemPrompt: "You are a helpful assistant that uses tools when asked.",
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messages: [
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{
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role: "user",
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content: "Calculate 15 + 27 using the math_operation tool.",
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timestamp: Date.now(),
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},
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],
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tools: [calculatorTool],
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};
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const s = await stream(model, context, options);
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let hasToolStart = false;
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let hasToolDelta = false;
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let hasToolEnd = false;
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let accumulatedToolArgs = "";
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let index = 0;
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for await (const event of s) {
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if (event.type === "toolcall_start") {
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hasToolStart = true;
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const toolCall = event.partial.content[event.contentIndex];
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index = event.contentIndex;
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expect(toolCall.type).toBe("toolCall");
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if (toolCall.type === "toolCall") {
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expect(toolCall.name).toBe("math_operation");
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expect(toolCall.id).toBeTruthy();
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}
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}
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if (event.type === "toolcall_delta") {
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hasToolDelta = true;
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const toolCall = event.partial.content[event.contentIndex];
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expect(event.contentIndex).toBe(index);
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expect(toolCall.type).toBe("toolCall");
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if (toolCall.type === "toolCall") {
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expect(toolCall.name).toBe("math_operation");
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accumulatedToolArgs += event.delta;
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// Check that we have a parsed arguments object during streaming
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expect(toolCall.arguments).toBeDefined();
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expect(typeof toolCall.arguments).toBe("object");
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// The arguments should be partially populated as we stream
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// At minimum it should be an empty object, never undefined
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expect(toolCall.arguments).not.toBeNull();
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}
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}
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if (event.type === "toolcall_end") {
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hasToolEnd = true;
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const toolCall = event.partial.content[event.contentIndex];
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expect(event.contentIndex).toBe(index);
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expect(toolCall.type).toBe("toolCall");
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if (toolCall.type === "toolCall") {
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expect(toolCall.name).toBe("math_operation");
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JSON.parse(accumulatedToolArgs);
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expect(toolCall.arguments).not.toBeUndefined();
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expect((toolCall.arguments as any).a).toBe(15);
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expect((toolCall.arguments as any).b).toBe(27);
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expect((toolCall.arguments as any).operation).oneOf([
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"add",
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"subtract",
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"multiply",
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"divide",
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]);
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}
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}
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}
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expect(hasToolStart).toBe(true);
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expect(hasToolDelta).toBe(true);
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expect(hasToolEnd).toBe(true);
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const response = await s.result();
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expect(response.stopReason).toBe("toolUse");
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expect(response.content.some((b) => b.type === "toolCall")).toBeTruthy();
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const toolCall = response.content.find((b) => b.type === "toolCall");
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if (toolCall && toolCall.type === "toolCall") {
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expect(toolCall.name).toBe("math_operation");
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expect(toolCall.id).toBeTruthy();
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} else {
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throw new Error("No tool call found in response");
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}
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}
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async function handleStreaming<TApi extends Api>(
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model: Model<TApi>,
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options?: StreamOptionsWithExtras,
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) {
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let textStarted = false;
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let textChunks = "";
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let textCompleted = false;
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const context: Context = {
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messages: [
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{ role: "user", content: "Count from 1 to 3", timestamp: Date.now() },
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],
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systemPrompt: "You are a helpful assistant.",
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};
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const s = stream(model, context, options);
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for await (const event of s) {
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if (event.type === "text_start") {
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textStarted = true;
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} else if (event.type === "text_delta") {
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textChunks += event.delta;
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} else if (event.type === "text_end") {
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textCompleted = true;
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}
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}
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const response = await s.result();
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expect(textStarted).toBe(true);
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expect(textChunks.length).toBeGreaterThan(0);
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expect(textCompleted).toBe(true);
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expect(response.content.some((b) => b.type === "text")).toBeTruthy();
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}
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async function handleThinking<TApi extends Api>(
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model: Model<TApi>,
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options?: StreamOptionsWithExtras,
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) {
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let thinkingStarted = false;
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let thinkingChunks = "";
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let thinkingCompleted = false;
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const context: Context = {
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messages: [
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{
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role: "user",
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content: `Think long and hard about ${(Math.random() * 255) | 0} + 27. Think step by step. Then output the result.`,
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timestamp: Date.now(),
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},
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],
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systemPrompt: "You are a helpful assistant.",
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};
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const s = stream(model, context, options);
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for await (const event of s) {
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if (event.type === "thinking_start") {
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thinkingStarted = true;
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} else if (event.type === "thinking_delta") {
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thinkingChunks += event.delta;
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} else if (event.type === "thinking_end") {
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thinkingCompleted = true;
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}
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}
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const response = await s.result();
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expect(response.stopReason, `Error: ${response.errorMessage}`).toBe("stop");
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expect(thinkingStarted).toBe(true);
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expect(thinkingChunks.length).toBeGreaterThan(0);
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expect(thinkingCompleted).toBe(true);
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expect(response.content.some((b) => b.type === "thinking")).toBeTruthy();
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}
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async function handleImage<TApi extends Api>(
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model: Model<TApi>,
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options?: StreamOptionsWithExtras,
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) {
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// Check if the model supports images
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if (!model.input.includes("image")) {
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console.log(
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`Skipping image test - model ${model.id} doesn't support images`,
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);
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return;
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}
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// Read the test image
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const imagePath = join(__dirname, "data", "red-circle.png");
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const imageBuffer = readFileSync(imagePath);
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const base64Image = imageBuffer.toString("base64");
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const imageContent: ImageContent = {
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type: "image",
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data: base64Image,
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mimeType: "image/png",
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};
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const context: Context = {
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messages: [
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{
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role: "user",
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content: [
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{
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type: "text",
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text: "What do you see in this image? Please describe the shape (circle, rectangle, square, triangle, ...) and color (red, blue, green, ...). You MUST reply in English.",
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},
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imageContent,
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],
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timestamp: Date.now(),
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},
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],
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systemPrompt: "You are a helpful assistant.",
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};
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const response = await complete(model, context, options);
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// Check the response mentions red and circle
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expect(response.content.length > 0).toBeTruthy();
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const textContent = response.content.find((b) => b.type === "text");
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if (textContent && textContent.type === "text") {
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const lowerContent = textContent.text.toLowerCase();
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expect(lowerContent).toContain("red");
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expect(lowerContent).toContain("circle");
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}
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}
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async function multiTurn<TApi extends Api>(
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model: Model<TApi>,
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options?: StreamOptionsWithExtras,
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) {
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const context: Context = {
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systemPrompt:
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"You are a helpful assistant that can use tools to answer questions.",
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messages: [
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{
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role: "user",
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content:
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"Think about this briefly, then calculate 42 * 17 and 453 + 434 using the math_operation tool.",
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timestamp: Date.now(),
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},
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],
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tools: [calculatorTool],
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};
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// Collect all text content from all assistant responses
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let allTextContent = "";
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let hasSeenThinking = false;
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let hasSeenToolCalls = false;
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const maxTurns = 5; // Prevent infinite loops
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for (let turn = 0; turn < maxTurns; turn++) {
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const response = await complete(model, context, options);
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// Add the assistant response to context
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context.messages.push(response);
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// Process content blocks
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const results: ToolResultMessage[] = [];
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for (const block of response.content) {
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if (block.type === "text") {
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allTextContent += block.text;
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} else if (block.type === "thinking") {
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hasSeenThinking = true;
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} else if (block.type === "toolCall") {
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hasSeenToolCalls = true;
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// Process the tool call
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expect(block.name).toBe("math_operation");
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expect(block.id).toBeTruthy();
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expect(block.arguments).toBeTruthy();
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const { a, b, operation } = block.arguments;
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let result: number;
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switch (operation) {
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case "add":
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result = a + b;
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break;
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case "multiply":
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result = a * b;
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break;
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default:
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result = 0;
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}
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// Add tool result to context
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results.push({
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role: "toolResult",
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toolCallId: block.id,
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toolName: block.name,
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content: [{ type: "text", text: `${result}` }],
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isError: false,
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timestamp: Date.now(),
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});
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}
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}
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context.messages.push(...results);
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// If we got a stop response with text content, we're likely done
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expect(response.stopReason, `Error: ${response.errorMessage}`).not.toBe(
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"error",
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);
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if (response.stopReason === "stop") {
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break;
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}
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}
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// Verify we got either thinking content or tool calls (or both)
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expect(hasSeenThinking || hasSeenToolCalls).toBe(true);
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// The accumulated text should reference both calculations
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expect(allTextContent).toBeTruthy();
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expect(allTextContent.includes("714")).toBe(true);
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expect(allTextContent.includes("887")).toBe(true);
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}
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describe("Generate E2E Tests", () => {
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describe.skipIf(!process.env.GEMINI_API_KEY)(
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"Gemini Provider (gemini-2.5-flash)",
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() => {
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const llm = getModel("google", "gemini-2.5-flash");
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it("should complete basic text generation", { retry: 3 }, async () => {
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await basicTextGeneration(llm);
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});
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it("should handle tool calling", { retry: 3 }, async () => {
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await handleToolCall(llm);
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});
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it("should handle streaming", { retry: 3 }, async () => {
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await handleStreaming(llm);
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});
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it("should handle thinking", { retry: 3 }, async () => {
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await handleThinking(llm, {
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thinking: { enabled: true, budgetTokens: 1024 },
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});
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});
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it(
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"should handle multi-turn with thinking and tools",
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{ retry: 3 },
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async () => {
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await multiTurn(llm, {
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thinking: { enabled: true, budgetTokens: 2048 },
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});
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},
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);
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it("should handle image input", { retry: 3 }, async () => {
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await handleImage(llm);
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});
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},
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);
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describe("Google Vertex Provider (gemini-3-flash-preview)", () => {
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const vertexProject =
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process.env.GOOGLE_CLOUD_PROJECT || process.env.GCLOUD_PROJECT;
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const vertexLocation = process.env.GOOGLE_CLOUD_LOCATION;
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const isVertexConfigured = Boolean(vertexProject && vertexLocation);
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const vertexOptions = {
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project: vertexProject,
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location: vertexLocation,
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} as const;
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const llm = getModel("google-vertex", "gemini-3-flash-preview");
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it.skipIf(!isVertexConfigured)(
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"should complete basic text generation",
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{ retry: 3 },
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async () => {
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await basicTextGeneration(llm, vertexOptions);
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},
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);
|
|
|
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it.skipIf(!isVertexConfigured)(
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"should handle tool calling",
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{ retry: 3 },
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async () => {
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await handleToolCall(llm, vertexOptions);
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},
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);
|
|
|
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it.skipIf(!isVertexConfigured)(
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"should handle thinking",
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{ retry: 3 },
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async () => {
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const { ThinkingLevel } = await import("@google/genai");
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await handleThinking(llm, {
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|
...vertexOptions,
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thinking: {
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|
enabled: true,
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|
budgetTokens: 1024,
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|
level: ThinkingLevel.LOW,
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|
},
|
|
});
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|
},
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|
);
|
|
|
|
it.skipIf(!isVertexConfigured)(
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|
"should handle streaming",
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|
{ retry: 3 },
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|
async () => {
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await handleStreaming(llm, vertexOptions);
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|
},
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);
|
|
|
|
it.skipIf(!isVertexConfigured)(
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"should handle multi-turn with thinking and tools",
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{ retry: 3 },
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async () => {
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const { ThinkingLevel } = await import("@google/genai");
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await multiTurn(llm, {
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...vertexOptions,
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thinking: {
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enabled: true,
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budgetTokens: 1024,
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level: ThinkingLevel.MEDIUM,
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},
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});
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},
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);
|
|
|
|
it.skipIf(!isVertexConfigured)(
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"should handle image input",
|
|
{ retry: 3 },
|
|
async () => {
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|
await handleImage(llm, vertexOptions);
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|
},
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|
);
|
|
});
|
|
|
|
describe.skipIf(!process.env.OPENAI_API_KEY)(
|
|
"OpenAI Completions Provider (gpt-4o-mini)",
|
|
() => {
|
|
const { compat: _compat, ...baseModel } = getModel(
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|
"openai",
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|
"gpt-4o-mini",
|
|
);
|
|
void _compat;
|
|
const llm: Model<"openai-completions"> = {
|
|
...baseModel,
|
|
api: "openai-completions",
|
|
};
|
|
|
|
it("should complete basic text generation", { retry: 3 }, async () => {
|
|
await basicTextGeneration(llm);
|
|
});
|
|
|
|
it("should handle tool calling", { retry: 3 }, async () => {
|
|
await handleToolCall(llm);
|
|
});
|
|
|
|
it("should handle streaming", { retry: 3 }, async () => {
|
|
await handleStreaming(llm);
|
|
});
|
|
|
|
it("should handle image input", { retry: 3 }, async () => {
|
|
await handleImage(llm);
|
|
});
|
|
},
|
|
);
|
|
|
|
describe.skipIf(!process.env.OPENAI_API_KEY)(
|
|
"OpenAI Responses Provider (gpt-5-mini)",
|
|
() => {
|
|
const llm = getModel("openai", "gpt-5-mini");
|
|
|
|
it("should complete basic text generation", { retry: 3 }, async () => {
|
|
await basicTextGeneration(llm);
|
|
});
|
|
|
|
it("should handle tool calling", { retry: 3 }, async () => {
|
|
await handleToolCall(llm);
|
|
});
|
|
|
|
it("should handle streaming", { retry: 3 }, async () => {
|
|
await handleStreaming(llm);
|
|
});
|
|
|
|
it("should handle thinking", { retry: 2 }, async () => {
|
|
await handleThinking(llm, { reasoningEffort: "high" });
|
|
});
|
|
|
|
it(
|
|
"should handle multi-turn with thinking and tools",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await multiTurn(llm, { reasoningEffort: "high" });
|
|
},
|
|
);
|
|
|
|
it("should handle image input", { retry: 3 }, async () => {
|
|
await handleImage(llm);
|
|
});
|
|
},
|
|
);
|
|
|
|
describe.skipIf(!process.env.ANTHROPIC_API_KEY)(
|
|
"Anthropic Provider (claude-3-5-haiku-20241022)",
|
|
() => {
|
|
const model = getModel("anthropic", "claude-3-5-haiku-20241022");
|
|
|
|
it("should complete basic text generation", { retry: 3 }, async () => {
|
|
await basicTextGeneration(model, { thinkingEnabled: true });
|
|
});
|
|
|
|
it("should handle tool calling", { retry: 3 }, async () => {
|
|
await handleToolCall(model);
|
|
});
|
|
|
|
it("should handle streaming", { retry: 3 }, async () => {
|
|
await handleStreaming(model);
|
|
});
|
|
|
|
it("should handle image input", { retry: 3 }, async () => {
|
|
await handleImage(model);
|
|
});
|
|
},
|
|
);
|
|
|
|
describe.skipIf(!hasAzureOpenAICredentials())(
|
|
"Azure OpenAI Responses Provider (gpt-4o-mini)",
|
|
() => {
|
|
const llm = getModel("azure-openai-responses", "gpt-4o-mini");
|
|
const azureDeploymentName = resolveAzureDeploymentName(llm.id);
|
|
const azureOptions = azureDeploymentName ? { azureDeploymentName } : {};
|
|
|
|
it("should complete basic text generation", { retry: 3 }, async () => {
|
|
await basicTextGeneration(llm, azureOptions);
|
|
});
|
|
|
|
it("should handle tool calling", { retry: 3 }, async () => {
|
|
await handleToolCall(llm, azureOptions);
|
|
});
|
|
|
|
it("should handle streaming", { retry: 3 }, async () => {
|
|
await handleStreaming(llm, azureOptions);
|
|
});
|
|
|
|
it("should handle image input", { retry: 3 }, async () => {
|
|
await handleImage(llm, azureOptions);
|
|
});
|
|
},
|
|
);
|
|
|
|
describe.skipIf(!process.env.XAI_API_KEY)(
|
|
"xAI Provider (grok-code-fast-1 via OpenAI Completions)",
|
|
() => {
|
|
const llm = getModel("xai", "grok-code-fast-1");
|
|
|
|
it("should complete basic text generation", { retry: 3 }, async () => {
|
|
await basicTextGeneration(llm);
|
|
});
|
|
|
|
it("should handle tool calling", { retry: 3 }, async () => {
|
|
await handleToolCall(llm);
|
|
});
|
|
|
|
it("should handle streaming", { retry: 3 }, async () => {
|
|
await handleStreaming(llm);
|
|
});
|
|
|
|
it("should handle thinking mode", { retry: 3 }, async () => {
|
|
await handleThinking(llm, { reasoningEffort: "medium" });
|
|
});
|
|
|
|
it(
|
|
"should handle multi-turn with thinking and tools",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await multiTurn(llm, { reasoningEffort: "medium" });
|
|
},
|
|
);
|
|
},
|
|
);
|
|
|
|
describe.skipIf(!process.env.GROQ_API_KEY)(
|
|
"Groq Provider (gpt-oss-20b via OpenAI Completions)",
|
|
() => {
|
|
const llm = getModel("groq", "openai/gpt-oss-20b");
|
|
|
|
it("should complete basic text generation", { retry: 3 }, async () => {
|
|
await basicTextGeneration(llm);
|
|
});
|
|
|
|
it("should handle tool calling", { retry: 3 }, async () => {
|
|
await handleToolCall(llm);
|
|
});
|
|
|
|
it("should handle streaming", { retry: 3 }, async () => {
|
|
await handleStreaming(llm);
|
|
});
|
|
|
|
it("should handle thinking mode", { retry: 3 }, async () => {
|
|
await handleThinking(llm, { reasoningEffort: "medium" });
|
|
});
|
|
|
|
it(
|
|
"should handle multi-turn with thinking and tools",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await multiTurn(llm, { reasoningEffort: "medium" });
|
|
},
|
|
);
|
|
},
|
|
);
|
|
|
|
describe.skipIf(!process.env.CEREBRAS_API_KEY)(
|
|
"Cerebras Provider (gpt-oss-120b via OpenAI Completions)",
|
|
() => {
|
|
const llm = getModel("cerebras", "gpt-oss-120b");
|
|
|
|
it("should complete basic text generation", { retry: 3 }, async () => {
|
|
await basicTextGeneration(llm);
|
|
});
|
|
|
|
it("should handle tool calling", { retry: 3 }, async () => {
|
|
await handleToolCall(llm);
|
|
});
|
|
|
|
it("should handle streaming", { retry: 3 }, async () => {
|
|
await handleStreaming(llm);
|
|
});
|
|
|
|
it("should handle thinking mode", { retry: 3 }, async () => {
|
|
await handleThinking(llm, { reasoningEffort: "medium" });
|
|
});
|
|
|
|
it(
|
|
"should handle multi-turn with thinking and tools",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await multiTurn(llm, { reasoningEffort: "medium" });
|
|
},
|
|
);
|
|
},
|
|
);
|
|
|
|
describe.skipIf(!process.env.HF_TOKEN)(
|
|
"Hugging Face Provider (Kimi-K2.5 via OpenAI Completions)",
|
|
() => {
|
|
const llm = getModel("huggingface", "moonshotai/Kimi-K2.5");
|
|
|
|
it("should complete basic text generation", { retry: 3 }, async () => {
|
|
await basicTextGeneration(llm);
|
|
});
|
|
|
|
it("should handle tool calling", { retry: 3 }, async () => {
|
|
await handleToolCall(llm);
|
|
});
|
|
|
|
it("should handle streaming", { retry: 3 }, async () => {
|
|
await handleStreaming(llm);
|
|
});
|
|
|
|
it("should handle thinking mode", { retry: 3 }, async () => {
|
|
await handleThinking(llm, { reasoningEffort: "medium" });
|
|
});
|
|
|
|
it(
|
|
"should handle multi-turn with thinking and tools",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await multiTurn(llm, { reasoningEffort: "medium" });
|
|
},
|
|
);
|
|
},
|
|
);
|
|
|
|
describe.skipIf(!process.env.OPENROUTER_API_KEY)(
|
|
"OpenRouter Provider (glm-4.5v via OpenAI Completions)",
|
|
() => {
|
|
const llm = getModel("openrouter", "z-ai/glm-4.5v");
|
|
|
|
it("should complete basic text generation", { retry: 3 }, async () => {
|
|
await basicTextGeneration(llm);
|
|
});
|
|
|
|
it("should handle tool calling", { retry: 3 }, async () => {
|
|
await handleToolCall(llm);
|
|
});
|
|
|
|
it("should handle streaming", { retry: 3 }, async () => {
|
|
await handleStreaming(llm);
|
|
});
|
|
|
|
it("should handle thinking mode", { retry: 3 }, async () => {
|
|
await handleThinking(llm, { reasoningEffort: "medium" });
|
|
});
|
|
|
|
it(
|
|
"should handle multi-turn with thinking and tools",
|
|
{ retry: 2 },
|
|
async () => {
|
|
await multiTurn(llm, { reasoningEffort: "medium" });
|
|
},
|
|
);
|
|
|
|
it("should handle image input", { retry: 3 }, async () => {
|
|
await handleImage(llm);
|
|
});
|
|
},
|
|
);
|
|
|
|
describe.skipIf(!process.env.AI_GATEWAY_API_KEY)(
|
|
"Vercel AI Gateway Provider (google/gemini-2.5-flash via Anthropic Messages)",
|
|
() => {
|
|
const llm = getModel("vercel-ai-gateway", "google/gemini-2.5-flash");
|
|
|
|
it("should complete basic text generation", { retry: 3 }, async () => {
|
|
await basicTextGeneration(llm);
|
|
});
|
|
|
|
it("should handle tool calling", { retry: 3 }, async () => {
|
|
await handleToolCall(llm);
|
|
});
|
|
|
|
it("should handle streaming", { retry: 3 }, async () => {
|
|
await handleStreaming(llm);
|
|
});
|
|
|
|
it("should handle image input", { retry: 3 }, async () => {
|
|
await handleImage(llm);
|
|
});
|
|
|
|
it("should handle multi-turn with tools", { retry: 3 }, async () => {
|
|
await multiTurn(llm);
|
|
});
|
|
},
|
|
);
|
|
|
|
describe.skipIf(!process.env.AI_GATEWAY_API_KEY)(
|
|
"Vercel AI Gateway Provider (anthropic/claude-opus-4.5 via Anthropic Messages)",
|
|
() => {
|
|
const llm = getModel("vercel-ai-gateway", "anthropic/claude-opus-4.5");
|
|
|
|
it("should complete basic text generation", { retry: 3 }, async () => {
|
|
await basicTextGeneration(llm);
|
|
});
|
|
|
|
it("should handle tool calling", { retry: 3 }, async () => {
|
|
await handleToolCall(llm);
|
|
});
|
|
|
|
it("should handle streaming", { retry: 3 }, async () => {
|
|
await handleStreaming(llm);
|
|
});
|
|
|
|
it("should handle image input", { retry: 3 }, async () => {
|
|
await handleImage(llm);
|
|
});
|
|
|
|
it("should handle multi-turn with tools", { retry: 3 }, async () => {
|
|
await multiTurn(llm);
|
|
});
|
|
},
|
|
);
|
|
|
|
describe.skipIf(!process.env.AI_GATEWAY_API_KEY)(
|
|
"Vercel AI Gateway Provider (openai/gpt-5.1-codex-max via Anthropic Messages)",
|
|
() => {
|
|
const llm = getModel("vercel-ai-gateway", "openai/gpt-5.1-codex-max");
|
|
|
|
it("should complete basic text generation", { retry: 3 }, async () => {
|
|
await basicTextGeneration(llm);
|
|
});
|
|
|
|
it("should handle tool calling", { retry: 3 }, async () => {
|
|
await handleToolCall(llm);
|
|
});
|
|
|
|
it("should handle streaming", { retry: 3 }, async () => {
|
|
await handleStreaming(llm);
|
|
});
|
|
|
|
it("should handle image input", { retry: 3 }, async () => {
|
|
await handleImage(llm);
|
|
});
|
|
|
|
it("should handle multi-turn with tools", { retry: 3 }, async () => {
|
|
await multiTurn(llm);
|
|
});
|
|
},
|
|
);
|
|
|
|
describe.skipIf(!process.env.ZAI_API_KEY)(
|
|
"zAI Provider (glm-5 via OpenAI Completions)",
|
|
() => {
|
|
const llm = getModel("zai", "glm-5");
|
|
|
|
it("should complete basic text generation", { retry: 3 }, async () => {
|
|
await basicTextGeneration(llm);
|
|
});
|
|
|
|
it("should handle tool calling", { retry: 3 }, async () => {
|
|
await handleToolCall(llm);
|
|
});
|
|
|
|
it("should handle streaming", { retry: 3 }, async () => {
|
|
await handleStreaming(llm);
|
|
});
|
|
|
|
it("should handle thinking mode", { retry: 3 }, async () => {
|
|
await handleThinking(llm, { reasoningEffort: "medium" });
|
|
});
|
|
|
|
it(
|
|
"should handle multi-turn with thinking and tools",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await multiTurn(llm, { reasoningEffort: "medium" });
|
|
},
|
|
);
|
|
|
|
it("should handle image input", { retry: 3 }, async () => {
|
|
await handleImage(llm);
|
|
});
|
|
},
|
|
);
|
|
|
|
describe.skipIf(!process.env.MISTRAL_API_KEY)(
|
|
"Mistral Provider (devstral-medium-latest)",
|
|
() => {
|
|
const llm = getModel("mistral", "devstral-medium-latest");
|
|
|
|
it("should complete basic text generation", { retry: 3 }, async () => {
|
|
await basicTextGeneration(llm);
|
|
});
|
|
|
|
it("should handle tool calling", { retry: 3 }, async () => {
|
|
await handleToolCall(llm);
|
|
});
|
|
|
|
it("should handle streaming", { retry: 3 }, async () => {
|
|
await handleStreaming(llm);
|
|
});
|
|
|
|
it("should handle thinking mode", { retry: 3 }, async () => {
|
|
const llm = getModel("mistral", "magistral-medium-latest");
|
|
await handleThinking(llm, { reasoningEffort: "medium" });
|
|
});
|
|
|
|
it(
|
|
"should handle multi-turn with thinking and tools",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await multiTurn(llm, { reasoningEffort: "medium" });
|
|
},
|
|
);
|
|
},
|
|
);
|
|
|
|
describe.skipIf(!process.env.MISTRAL_API_KEY)(
|
|
"Mistral Provider (pixtral-12b with image support)",
|
|
() => {
|
|
const llm = getModel("mistral", "pixtral-12b");
|
|
|
|
it("should complete basic text generation", { retry: 3 }, async () => {
|
|
await basicTextGeneration(llm);
|
|
});
|
|
|
|
it("should handle tool calling", { retry: 3 }, async () => {
|
|
await handleToolCall(llm);
|
|
});
|
|
|
|
it("should handle streaming", { retry: 3 }, async () => {
|
|
await handleStreaming(llm);
|
|
});
|
|
|
|
it("should handle image input", { retry: 3 }, async () => {
|
|
await handleImage(llm);
|
|
});
|
|
},
|
|
);
|
|
|
|
describe.skipIf(!process.env.MINIMAX_API_KEY)(
|
|
"MiniMax Provider (MiniMax-M2.1 via Anthropic Messages)",
|
|
() => {
|
|
const llm = getModel("minimax", "MiniMax-M2.1");
|
|
|
|
it("should complete basic text generation", { retry: 3 }, async () => {
|
|
await basicTextGeneration(llm);
|
|
});
|
|
|
|
it("should handle tool calling", { retry: 3 }, async () => {
|
|
await handleToolCall(llm);
|
|
});
|
|
|
|
it("should handle streaming", { retry: 3 }, async () => {
|
|
await handleStreaming(llm);
|
|
});
|
|
|
|
it("should handle thinking mode", { retry: 3 }, async () => {
|
|
await handleThinking(llm, {
|
|
thinkingEnabled: true,
|
|
thinkingBudgetTokens: 2048,
|
|
});
|
|
});
|
|
|
|
it(
|
|
"should handle multi-turn with thinking and tools",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await multiTurn(llm, {
|
|
thinkingEnabled: true,
|
|
thinkingBudgetTokens: 2048,
|
|
});
|
|
},
|
|
);
|
|
},
|
|
);
|
|
|
|
describe.skipIf(!process.env.KIMI_API_KEY)(
|
|
"Kimi For Coding Provider (kimi-k2-thinking via Anthropic Messages)",
|
|
() => {
|
|
const llm = getModel("kimi-coding", "kimi-k2-thinking");
|
|
|
|
it("should complete basic text generation", { retry: 3 }, async () => {
|
|
await basicTextGeneration(llm);
|
|
});
|
|
|
|
it("should handle tool calling", { retry: 3 }, async () => {
|
|
await handleToolCall(llm);
|
|
});
|
|
|
|
it("should handle streaming", { retry: 3 }, async () => {
|
|
await handleStreaming(llm);
|
|
});
|
|
|
|
it("should handle thinking mode", { retry: 3 }, async () => {
|
|
await handleThinking(llm, {
|
|
thinkingEnabled: true,
|
|
thinkingBudgetTokens: 2048,
|
|
});
|
|
});
|
|
|
|
it(
|
|
"should handle multi-turn with thinking and tools",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await multiTurn(llm, {
|
|
thinkingEnabled: true,
|
|
thinkingBudgetTokens: 2048,
|
|
});
|
|
},
|
|
);
|
|
},
|
|
);
|
|
|
|
// =========================================================================
|
|
// OAuth-based providers (credentials from ~/.companion/agent/oauth.json)
|
|
// Tokens are resolved at module level (see oauthTokens above)
|
|
// =========================================================================
|
|
|
|
describe("Anthropic OAuth Provider (claude-sonnet-4-20250514)", () => {
|
|
const model = getModel("anthropic", "claude-sonnet-4-20250514");
|
|
|
|
it.skipIf(!anthropicOAuthToken)(
|
|
"should complete basic text generation",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await basicTextGeneration(model, { apiKey: anthropicOAuthToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!anthropicOAuthToken)(
|
|
"should handle tool calling",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleToolCall(model, { apiKey: anthropicOAuthToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!anthropicOAuthToken)(
|
|
"should handle streaming",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleStreaming(model, { apiKey: anthropicOAuthToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!anthropicOAuthToken)(
|
|
"should handle thinking",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleThinking(model, {
|
|
apiKey: anthropicOAuthToken,
|
|
thinkingEnabled: true,
|
|
});
|
|
},
|
|
);
|
|
|
|
it.skipIf(!anthropicOAuthToken)(
|
|
"should handle multi-turn with thinking and tools",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await multiTurn(model, {
|
|
apiKey: anthropicOAuthToken,
|
|
thinkingEnabled: true,
|
|
});
|
|
},
|
|
);
|
|
|
|
it.skipIf(!anthropicOAuthToken)(
|
|
"should handle image input",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleImage(model, { apiKey: anthropicOAuthToken });
|
|
},
|
|
);
|
|
});
|
|
|
|
describe("Anthropic OAuth Provider (claude-opus-4-6 with adaptive thinking)", () => {
|
|
const model = getModel("anthropic", "claude-opus-4-6");
|
|
|
|
it.skipIf(!anthropicOAuthToken)(
|
|
"should complete basic text generation",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await basicTextGeneration(model, { apiKey: anthropicOAuthToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!anthropicOAuthToken)(
|
|
"should handle tool calling",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleToolCall(model, { apiKey: anthropicOAuthToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!anthropicOAuthToken)(
|
|
"should handle streaming",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleStreaming(model, { apiKey: anthropicOAuthToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!anthropicOAuthToken)(
|
|
"should handle adaptive thinking with effort high",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleThinking(model, {
|
|
apiKey: anthropicOAuthToken,
|
|
thinkingEnabled: true,
|
|
effort: "high",
|
|
});
|
|
},
|
|
);
|
|
|
|
it.skipIf(!anthropicOAuthToken)(
|
|
"should handle adaptive thinking with effort medium",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleThinking(model, {
|
|
apiKey: anthropicOAuthToken,
|
|
thinkingEnabled: true,
|
|
effort: "medium",
|
|
});
|
|
},
|
|
);
|
|
|
|
it.skipIf(!anthropicOAuthToken)(
|
|
"should handle multi-turn with adaptive thinking and tools",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await multiTurn(model, {
|
|
apiKey: anthropicOAuthToken,
|
|
thinkingEnabled: true,
|
|
effort: "high",
|
|
});
|
|
},
|
|
);
|
|
|
|
it.skipIf(!anthropicOAuthToken)(
|
|
"should handle image input",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleImage(model, { apiKey: anthropicOAuthToken });
|
|
},
|
|
);
|
|
});
|
|
|
|
describe("GitHub Copilot Provider (gpt-5.3-codex via OpenAI Completions)", () => {
|
|
const llm = getModel("github-copilot", "gpt-5.3-codex");
|
|
|
|
it.skipIf(!githubCopilotToken)(
|
|
"should complete basic text generation",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await basicTextGeneration(llm, { apiKey: githubCopilotToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!githubCopilotToken)(
|
|
"should handle tool calling",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleToolCall(llm, { apiKey: githubCopilotToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!githubCopilotToken)(
|
|
"should handle streaming",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleStreaming(llm, { apiKey: githubCopilotToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!githubCopilotToken)(
|
|
"should handle thinking",
|
|
{ retry: 2 },
|
|
async () => {
|
|
const thinkingModel = getModel("github-copilot", "gpt-5-mini");
|
|
await handleThinking(thinkingModel, {
|
|
apiKey: githubCopilotToken,
|
|
reasoningEffort: "high",
|
|
});
|
|
},
|
|
);
|
|
|
|
it.skipIf(!githubCopilotToken)(
|
|
"should handle multi-turn with thinking and tools",
|
|
{ retry: 3 },
|
|
async () => {
|
|
const thinkingModel = getModel("github-copilot", "gpt-5-mini");
|
|
await multiTurn(thinkingModel, {
|
|
apiKey: githubCopilotToken,
|
|
reasoningEffort: "high",
|
|
});
|
|
},
|
|
);
|
|
|
|
it.skipIf(!githubCopilotToken)(
|
|
"should handle image input",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleImage(llm, { apiKey: githubCopilotToken });
|
|
},
|
|
);
|
|
});
|
|
|
|
describe("GitHub Copilot Provider (claude-sonnet-4 via Anthropic Messages)", () => {
|
|
const llm = getModel("github-copilot", "claude-sonnet-4");
|
|
|
|
it.skipIf(!githubCopilotToken)(
|
|
"should complete basic text generation",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await basicTextGeneration(llm, { apiKey: githubCopilotToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!githubCopilotToken)(
|
|
"should handle tool calling",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleToolCall(llm, { apiKey: githubCopilotToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!githubCopilotToken)(
|
|
"should handle streaming",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleStreaming(llm, { apiKey: githubCopilotToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!githubCopilotToken)(
|
|
"should handle thinking",
|
|
{ retry: 2 },
|
|
async () => {
|
|
await handleThinking(llm, {
|
|
apiKey: githubCopilotToken,
|
|
thinkingEnabled: true,
|
|
});
|
|
},
|
|
);
|
|
|
|
it.skipIf(!githubCopilotToken)(
|
|
"should handle multi-turn with thinking and tools",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await multiTurn(llm, {
|
|
apiKey: githubCopilotToken,
|
|
thinkingEnabled: true,
|
|
});
|
|
},
|
|
);
|
|
|
|
it.skipIf(!githubCopilotToken)(
|
|
"should handle image input",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleImage(llm, { apiKey: githubCopilotToken });
|
|
},
|
|
);
|
|
});
|
|
|
|
describe("Google Gemini CLI Provider (gemini-2.5-flash)", () => {
|
|
const llm = getModel("google-gemini-cli", "gemini-2.5-flash");
|
|
|
|
it.skipIf(!geminiCliToken)(
|
|
"should complete basic text generation",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await basicTextGeneration(llm, { apiKey: geminiCliToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!geminiCliToken)(
|
|
"should handle tool calling",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleToolCall(llm, { apiKey: geminiCliToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!geminiCliToken)(
|
|
"should handle streaming",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleStreaming(llm, { apiKey: geminiCliToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!geminiCliToken)(
|
|
"should handle thinking",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleThinking(llm, {
|
|
apiKey: geminiCliToken,
|
|
thinking: { enabled: true, budgetTokens: 1024 },
|
|
});
|
|
},
|
|
);
|
|
|
|
it.skipIf(!geminiCliToken)(
|
|
"should handle multi-turn with thinking and tools",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await multiTurn(llm, {
|
|
apiKey: geminiCliToken,
|
|
thinking: { enabled: true, budgetTokens: 2048 },
|
|
});
|
|
},
|
|
);
|
|
|
|
it.skipIf(!geminiCliToken)(
|
|
"should handle image input",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleImage(llm, { apiKey: geminiCliToken });
|
|
},
|
|
);
|
|
});
|
|
|
|
describe("Google Gemini CLI Provider (gemini-3-flash-preview with thinkingLevel)", () => {
|
|
const llm = getModel("google-gemini-cli", "gemini-3-flash-preview");
|
|
|
|
it.skipIf(!geminiCliToken)(
|
|
"should handle thinking with thinkingLevel",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleThinking(llm, {
|
|
apiKey: geminiCliToken,
|
|
thinking: { enabled: true, level: "LOW" },
|
|
});
|
|
},
|
|
);
|
|
|
|
it.skipIf(!geminiCliToken)(
|
|
"should handle multi-turn with thinking and tools",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await multiTurn(llm, {
|
|
apiKey: geminiCliToken,
|
|
thinking: { enabled: true, level: "MEDIUM" },
|
|
});
|
|
},
|
|
);
|
|
});
|
|
|
|
describe("Google Antigravity Provider (gemini-3.1-pro-high)", () => {
|
|
const llm = getModel("google-antigravity", "gemini-3.1-pro-high");
|
|
|
|
it.skipIf(!antigravityToken)(
|
|
"should complete basic text generation",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await basicTextGeneration(llm, { apiKey: antigravityToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!antigravityToken)(
|
|
"should handle tool calling",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleToolCall(llm, { apiKey: antigravityToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!antigravityToken)(
|
|
"should handle streaming",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleStreaming(llm, { apiKey: antigravityToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!antigravityToken)(
|
|
"should handle thinking with thinkingLevel",
|
|
{ retry: 3 },
|
|
async () => {
|
|
// gemini-3-pro only supports LOW/HIGH
|
|
await handleThinking(llm, {
|
|
apiKey: antigravityToken,
|
|
thinking: { enabled: true, level: "LOW" },
|
|
});
|
|
},
|
|
);
|
|
|
|
it.skipIf(!antigravityToken)(
|
|
"should handle multi-turn with thinking and tools",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await multiTurn(llm, {
|
|
apiKey: antigravityToken,
|
|
thinking: { enabled: true, level: "HIGH" },
|
|
});
|
|
},
|
|
);
|
|
|
|
it.skipIf(!antigravityToken)(
|
|
"should handle image input",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleImage(llm, { apiKey: antigravityToken });
|
|
},
|
|
);
|
|
});
|
|
|
|
describe("Google Antigravity Provider (gemini-3.1-pro-high with thinkingLevel)", () => {
|
|
const llm = getModel("google-antigravity", "gemini-3.1-pro-high");
|
|
|
|
it.skipIf(!antigravityToken)(
|
|
"should handle thinking with thinkingLevel HIGH",
|
|
{ retry: 3 },
|
|
async () => {
|
|
// gemini-3-pro only supports LOW/HIGH
|
|
await handleThinking(llm, {
|
|
apiKey: antigravityToken,
|
|
thinking: { enabled: true, level: "HIGH" },
|
|
});
|
|
},
|
|
);
|
|
});
|
|
|
|
describe("Google Antigravity Provider (claude-sonnet-4-5)", () => {
|
|
const llm = getModel("google-antigravity", "claude-sonnet-4-5");
|
|
|
|
it.skipIf(!antigravityToken)(
|
|
"should complete basic text generation",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await basicTextGeneration(llm, { apiKey: antigravityToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!antigravityToken)(
|
|
"should handle tool calling",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleToolCall(llm, { apiKey: antigravityToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!antigravityToken)(
|
|
"should handle streaming",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleStreaming(llm, { apiKey: antigravityToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!antigravityToken)(
|
|
"should handle thinking",
|
|
{ retry: 3 },
|
|
async () => {
|
|
// claude-sonnet-4-5 has reasoning: false, use claude-sonnet-4-5-thinking
|
|
const thinkingModel = getModel(
|
|
"google-antigravity",
|
|
"claude-sonnet-4-5-thinking",
|
|
);
|
|
await handleThinking(thinkingModel, {
|
|
apiKey: antigravityToken,
|
|
thinking: { enabled: true, budgetTokens: 4096 },
|
|
});
|
|
},
|
|
);
|
|
|
|
it.skipIf(!antigravityToken)(
|
|
"should handle multi-turn with thinking and tools",
|
|
{ retry: 3 },
|
|
async () => {
|
|
const thinkingModel = getModel(
|
|
"google-antigravity",
|
|
"claude-sonnet-4-5-thinking",
|
|
);
|
|
await multiTurn(thinkingModel, {
|
|
apiKey: antigravityToken,
|
|
thinking: { enabled: true, budgetTokens: 4096 },
|
|
});
|
|
},
|
|
);
|
|
|
|
it.skipIf(!antigravityToken)(
|
|
"should handle image input",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleImage(llm, { apiKey: antigravityToken });
|
|
},
|
|
);
|
|
});
|
|
|
|
describe("OpenAI Codex Provider (gpt-5.2-codex)", () => {
|
|
const llm = getModel("openai-codex", "gpt-5.2-codex");
|
|
|
|
it.skipIf(!openaiCodexToken)(
|
|
"should complete basic text generation",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await basicTextGeneration(llm, { apiKey: openaiCodexToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!openaiCodexToken)(
|
|
"should handle tool calling",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleToolCall(llm, { apiKey: openaiCodexToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!openaiCodexToken)(
|
|
"should handle streaming",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleStreaming(llm, { apiKey: openaiCodexToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!openaiCodexToken)(
|
|
"should handle thinking",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleThinking(llm, {
|
|
apiKey: openaiCodexToken,
|
|
reasoningEffort: "high",
|
|
});
|
|
},
|
|
);
|
|
|
|
it.skipIf(!openaiCodexToken)(
|
|
"should handle multi-turn with thinking and tools",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await multiTurn(llm, { apiKey: openaiCodexToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!openaiCodexToken)(
|
|
"should handle image input",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleImage(llm, { apiKey: openaiCodexToken });
|
|
},
|
|
);
|
|
});
|
|
|
|
describe("OpenAI Codex Provider (gpt-5.3-codex)", () => {
|
|
const llm = getModel("openai-codex", "gpt-5.3-codex");
|
|
|
|
it.skipIf(!openaiCodexToken)(
|
|
"should complete basic text generation",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await basicTextGeneration(llm, { apiKey: openaiCodexToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!openaiCodexToken)(
|
|
"should handle tool calling",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleToolCall(llm, { apiKey: openaiCodexToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!openaiCodexToken)(
|
|
"should handle streaming",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleStreaming(llm, { apiKey: openaiCodexToken });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!openaiCodexToken)(
|
|
"should handle thinking with reasoningEffort high",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleThinking(llm, {
|
|
apiKey: openaiCodexToken,
|
|
reasoningEffort: "high",
|
|
});
|
|
},
|
|
);
|
|
|
|
it.skipIf(!openaiCodexToken)(
|
|
"should handle multi-turn with thinking and tools",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await multiTurn(llm, {
|
|
apiKey: openaiCodexToken,
|
|
reasoningEffort: "high",
|
|
});
|
|
},
|
|
);
|
|
|
|
it.skipIf(!openaiCodexToken)(
|
|
"should handle image input",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleImage(llm, { apiKey: openaiCodexToken });
|
|
},
|
|
);
|
|
});
|
|
|
|
describe("OpenAI Codex Provider (gpt-5.3-codex via WebSocket)", () => {
|
|
const llm = getModel("openai-codex", "gpt-5.3-codex");
|
|
const wsOptions = {
|
|
apiKey: openaiCodexToken,
|
|
transport: "websocket" as const,
|
|
};
|
|
|
|
it.skipIf(!openaiCodexToken)(
|
|
"should complete basic text generation",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await basicTextGeneration(llm, wsOptions);
|
|
},
|
|
);
|
|
|
|
it.skipIf(!openaiCodexToken)(
|
|
"should handle tool calling",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleToolCall(llm, wsOptions);
|
|
},
|
|
);
|
|
|
|
it.skipIf(!openaiCodexToken)(
|
|
"should handle streaming",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleStreaming(llm, wsOptions);
|
|
},
|
|
);
|
|
|
|
it.skipIf(!openaiCodexToken)(
|
|
"should handle thinking with reasoningEffort high",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleThinking(llm, { ...wsOptions, reasoningEffort: "high" });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!openaiCodexToken)(
|
|
"should handle multi-turn with thinking and tools",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await multiTurn(llm, { ...wsOptions, reasoningEffort: "high" });
|
|
},
|
|
);
|
|
|
|
it.skipIf(!openaiCodexToken)(
|
|
"should handle image input",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await handleImage(llm, wsOptions);
|
|
},
|
|
);
|
|
});
|
|
|
|
describe.skipIf(!hasBedrockCredentials())(
|
|
"Amazon Bedrock Provider (claude-sonnet-4-5)",
|
|
() => {
|
|
const llm = getModel(
|
|
"amazon-bedrock",
|
|
"global.anthropic.claude-sonnet-4-5-20250929-v1:0",
|
|
);
|
|
|
|
it("should complete basic text generation", { retry: 3 }, async () => {
|
|
await basicTextGeneration(llm);
|
|
});
|
|
|
|
it("should handle tool calling", { retry: 3 }, async () => {
|
|
await handleToolCall(llm);
|
|
});
|
|
|
|
it("should handle streaming", { retry: 3 }, async () => {
|
|
await handleStreaming(llm);
|
|
});
|
|
|
|
it("should handle thinking", { retry: 3 }, async () => {
|
|
await handleThinking(llm, { reasoning: "medium" });
|
|
});
|
|
|
|
it(
|
|
"should handle multi-turn with thinking and tools",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await multiTurn(llm, { reasoning: "high" });
|
|
},
|
|
);
|
|
|
|
it("should handle image input", { retry: 3 }, async () => {
|
|
await handleImage(llm);
|
|
});
|
|
},
|
|
);
|
|
|
|
describe.skipIf(!hasBedrockCredentials())(
|
|
"Amazon Bedrock Provider (claude-opus-4-6 interleaved thinking)",
|
|
() => {
|
|
const llm = getModel(
|
|
"amazon-bedrock",
|
|
"global.anthropic.claude-opus-4-6-v1",
|
|
);
|
|
|
|
it(
|
|
"should use adaptive thinking without anthropic_beta",
|
|
{ retry: 3 },
|
|
async () => {
|
|
let capturedPayload: unknown;
|
|
const response = await complete(
|
|
llm,
|
|
{
|
|
systemPrompt:
|
|
"You are a helpful assistant that uses tools when asked.",
|
|
messages: [
|
|
{
|
|
role: "user",
|
|
content:
|
|
"Think first, then calculate 15 + 27 using the math_operation tool.",
|
|
timestamp: Date.now(),
|
|
},
|
|
],
|
|
tools: [calculatorTool],
|
|
},
|
|
{
|
|
reasoning: "xhigh",
|
|
interleavedThinking: true,
|
|
onPayload: (payload) => {
|
|
capturedPayload = payload;
|
|
},
|
|
},
|
|
);
|
|
|
|
expect(
|
|
response.stopReason,
|
|
`Error: ${response.errorMessage}`,
|
|
).not.toBe("error");
|
|
expect(capturedPayload).toBeTruthy();
|
|
|
|
const payload = capturedPayload as {
|
|
additionalModelRequestFields?: {
|
|
thinking?: { type?: string };
|
|
output_config?: { effort?: string };
|
|
anthropic_beta?: string[];
|
|
};
|
|
};
|
|
|
|
expect(payload.additionalModelRequestFields?.thinking).toEqual({
|
|
type: "adaptive",
|
|
});
|
|
expect(payload.additionalModelRequestFields?.output_config).toEqual({
|
|
effort: "max",
|
|
});
|
|
expect(
|
|
payload.additionalModelRequestFields?.anthropic_beta,
|
|
).toBeUndefined();
|
|
},
|
|
);
|
|
},
|
|
);
|
|
|
|
// Check if ollama is installed and local LLM tests are enabled
|
|
let ollamaInstalled = false;
|
|
if (!process.env.COMPANION_NO_LOCAL_LLM) {
|
|
try {
|
|
execSync("which ollama", { stdio: "ignore" });
|
|
ollamaInstalled = true;
|
|
} catch {
|
|
ollamaInstalled = false;
|
|
}
|
|
}
|
|
|
|
describe.skipIf(!ollamaInstalled)(
|
|
"Ollama Provider (gpt-oss-20b via OpenAI Completions)",
|
|
() => {
|
|
let llm: Model<"openai-completions">;
|
|
let ollamaProcess: ChildProcess | null = null;
|
|
|
|
beforeAll(async () => {
|
|
// Check if model is available, if not pull it
|
|
try {
|
|
execSync("ollama list | grep -q 'gpt-oss:20b'", { stdio: "ignore" });
|
|
} catch {
|
|
console.log("Pulling gpt-oss:20b model for Ollama tests...");
|
|
try {
|
|
execSync("ollama pull gpt-oss:20b", { stdio: "inherit" });
|
|
} catch (_e) {
|
|
console.warn(
|
|
"Failed to pull gpt-oss:20b model, tests will be skipped",
|
|
);
|
|
return;
|
|
}
|
|
}
|
|
|
|
// Start ollama server
|
|
ollamaProcess = spawn("ollama", ["serve"], {
|
|
detached: false,
|
|
stdio: "ignore",
|
|
});
|
|
|
|
// Wait for server to be ready
|
|
await new Promise<void>((resolve) => {
|
|
const checkServer = async () => {
|
|
try {
|
|
const response = await fetch("http://localhost:11434/api/tags");
|
|
if (response.ok) {
|
|
resolve();
|
|
} else {
|
|
setTimeout(checkServer, 500);
|
|
}
|
|
} catch {
|
|
setTimeout(checkServer, 500);
|
|
}
|
|
};
|
|
setTimeout(checkServer, 1000); // Initial delay
|
|
});
|
|
|
|
llm = {
|
|
id: "gpt-oss:20b",
|
|
api: "openai-completions",
|
|
provider: "ollama",
|
|
baseUrl: "http://localhost:11434/v1",
|
|
reasoning: true,
|
|
input: ["text"],
|
|
contextWindow: 128000,
|
|
maxTokens: 16000,
|
|
cost: {
|
|
input: 0,
|
|
output: 0,
|
|
cacheRead: 0,
|
|
cacheWrite: 0,
|
|
},
|
|
name: "Ollama GPT-OSS 20B",
|
|
};
|
|
}, 30000); // 30 second timeout for setup
|
|
|
|
afterAll(() => {
|
|
// Kill ollama server
|
|
if (ollamaProcess) {
|
|
ollamaProcess.kill("SIGTERM");
|
|
ollamaProcess = null;
|
|
}
|
|
});
|
|
|
|
it("should complete basic text generation", { retry: 3 }, async () => {
|
|
await basicTextGeneration(llm, { apiKey: "test" });
|
|
});
|
|
|
|
it("should handle tool calling", { retry: 3 }, async () => {
|
|
await handleToolCall(llm, { apiKey: "test" });
|
|
});
|
|
|
|
it("should handle streaming", { retry: 3 }, async () => {
|
|
await handleStreaming(llm, { apiKey: "test" });
|
|
});
|
|
|
|
it("should handle thinking mode", { retry: 3 }, async () => {
|
|
await handleThinking(llm, {
|
|
apiKey: "test",
|
|
reasoningEffort: "medium",
|
|
});
|
|
});
|
|
|
|
it(
|
|
"should handle multi-turn with thinking and tools",
|
|
{ retry: 3 },
|
|
async () => {
|
|
await multiTurn(llm, { apiKey: "test", reasoningEffort: "medium" });
|
|
},
|
|
);
|
|
},
|
|
);
|
|
});
|