mirror of
https://github.com/getcompanion-ai/co-mono.git
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5a9d844f9a
- Add agentLoopContinue() to pi-ai for resuming from existing context - Add Agent.continue() method and transport.continue() interface - Simplify AgentSession compaction to two cases: overflow (auto-retry) and threshold (no retry) - Remove proactive mid-turn compaction abort - Merge turn prefix summary into main summary - Add isCompacting property to AgentSession and RPC state - Block input during compaction in interactive mode - Show compaction count on session resume - Rename RPC.md to rpc.md for consistency Related to #128
510 lines
15 KiB
TypeScript
510 lines
15 KiB
TypeScript
import type { AssistantMessage, Model, ToolResultMessage, UserMessage } from "@mariozechner/pi-ai";
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import { calculateTool, getModel } from "@mariozechner/pi-ai";
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import { describe, expect, it } from "vitest";
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import { Agent, ProviderTransport } from "../src/index.js";
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function createTransport() {
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return new ProviderTransport({
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getApiKey: async (provider) => {
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const envVarMap: Record<string, string> = {
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google: "GEMINI_API_KEY",
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openai: "OPENAI_API_KEY",
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anthropic: "ANTHROPIC_API_KEY",
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xai: "XAI_API_KEY",
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groq: "GROQ_API_KEY",
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cerebras: "CEREBRAS_API_KEY",
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zai: "ZAI_API_KEY",
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};
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const envVar = envVarMap[provider] || `${provider.toUpperCase()}_API_KEY`;
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return process.env[envVar];
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},
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});
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}
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async function basicPrompt(model: Model<any>) {
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const agent = new Agent({
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initialState: {
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systemPrompt: "You are a helpful assistant. Keep your responses concise.",
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model,
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thinkingLevel: "off",
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tools: [],
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},
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transport: createTransport(),
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});
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await agent.prompt("What is 2+2? Answer with just the number.");
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expect(agent.state.isStreaming).toBe(false);
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expect(agent.state.messages.length).toBe(2);
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expect(agent.state.messages[0].role).toBe("user");
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expect(agent.state.messages[1].role).toBe("assistant");
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const assistantMessage = agent.state.messages[1];
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if (assistantMessage.role !== "assistant") throw new Error("Expected assistant message");
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expect(assistantMessage.content.length).toBeGreaterThan(0);
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const textContent = assistantMessage.content.find((c) => c.type === "text");
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expect(textContent).toBeDefined();
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if (textContent?.type !== "text") throw new Error("Expected text content");
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expect(textContent.text).toContain("4");
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}
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async function toolExecution(model: Model<any>) {
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const agent = new Agent({
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initialState: {
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systemPrompt: "You are a helpful assistant. Always use the calculator tool for math.",
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model,
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thinkingLevel: "off",
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tools: [calculateTool],
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},
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transport: createTransport(),
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});
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await agent.prompt("Calculate 123 * 456 using the calculator tool.");
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expect(agent.state.isStreaming).toBe(false);
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expect(agent.state.messages.length).toBeGreaterThanOrEqual(3);
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const toolResultMsg = agent.state.messages.find((m) => m.role === "toolResult");
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expect(toolResultMsg).toBeDefined();
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if (toolResultMsg?.role !== "toolResult") throw new Error("Expected tool result message");
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const textContent =
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toolResultMsg.content
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?.filter((c) => c.type === "text")
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.map((c: any) => c.text)
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.join("\n") || "";
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expect(textContent).toBeDefined();
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const expectedResult = 123 * 456;
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expect(textContent).toContain(String(expectedResult));
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const finalMessage = agent.state.messages[agent.state.messages.length - 1];
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if (finalMessage.role !== "assistant") throw new Error("Expected final assistant message");
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const finalText = finalMessage.content.find((c) => c.type === "text");
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expect(finalText).toBeDefined();
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if (finalText?.type !== "text") throw new Error("Expected text content");
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// Check for number with or without comma formatting
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const hasNumber =
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finalText.text.includes(String(expectedResult)) ||
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finalText.text.includes("56,088") ||
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finalText.text.includes("56088");
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expect(hasNumber).toBe(true);
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}
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async function abortExecution(model: Model<any>) {
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const agent = new Agent({
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initialState: {
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systemPrompt: "You are a helpful assistant.",
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model,
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thinkingLevel: "off",
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tools: [calculateTool],
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},
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transport: createTransport(),
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});
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const promptPromise = agent.prompt("Calculate 100 * 200, then 300 * 400, then sum the results.");
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setTimeout(() => {
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agent.abort();
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}, 100);
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await promptPromise;
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expect(agent.state.isStreaming).toBe(false);
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expect(agent.state.messages.length).toBeGreaterThanOrEqual(2);
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const lastMessage = agent.state.messages[agent.state.messages.length - 1];
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if (lastMessage.role !== "assistant") throw new Error("Expected assistant message");
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expect(lastMessage.stopReason).toBe("aborted");
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expect(lastMessage.errorMessage).toBeDefined();
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expect(agent.state.error).toBeDefined();
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expect(agent.state.error).toBe(lastMessage.errorMessage);
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}
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async function stateUpdates(model: Model<any>) {
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const agent = new Agent({
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initialState: {
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systemPrompt: "You are a helpful assistant.",
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model,
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thinkingLevel: "off",
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tools: [],
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},
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transport: createTransport(),
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});
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const events: Array<string> = [];
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agent.subscribe((event) => {
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events.push(event.type);
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});
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await agent.prompt("Count from 1 to 5.");
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// Should have received lifecycle events
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expect(events).toContain("agent_start");
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expect(events).toContain("agent_end");
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expect(events).toContain("message_start");
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expect(events).toContain("message_end");
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// May have message_update events during streaming
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const hasMessageUpdates = events.some((e) => e === "message_update");
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expect(hasMessageUpdates).toBe(true);
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// Check final state
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expect(agent.state.isStreaming).toBe(false);
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expect(agent.state.messages.length).toBe(2); // User message + assistant response
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}
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async function multiTurnConversation(model: Model<any>) {
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const agent = new Agent({
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initialState: {
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systemPrompt: "You are a helpful assistant.",
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model,
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thinkingLevel: "off",
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tools: [],
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},
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transport: createTransport(),
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});
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await agent.prompt("My name is Alice.");
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expect(agent.state.messages.length).toBe(2);
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await agent.prompt("What is my name?");
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expect(agent.state.messages.length).toBe(4);
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const lastMessage = agent.state.messages[3];
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if (lastMessage.role !== "assistant") throw new Error("Expected assistant message");
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const lastText = lastMessage.content.find((c) => c.type === "text");
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if (lastText?.type !== "text") throw new Error("Expected text content");
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expect(lastText.text.toLowerCase()).toContain("alice");
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}
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describe("Agent E2E Tests", () => {
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describe.skipIf(!process.env.GEMINI_API_KEY)("Google Provider (gemini-2.5-flash)", () => {
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const model = getModel("google", "gemini-2.5-flash");
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it("should handle basic text prompt", async () => {
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await basicPrompt(model);
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});
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it("should execute tools correctly", async () => {
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await toolExecution(model);
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});
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it("should handle abort during execution", async () => {
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await abortExecution(model);
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});
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it("should emit state updates during streaming", async () => {
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await stateUpdates(model);
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});
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it("should maintain context across multiple turns", async () => {
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await multiTurnConversation(model);
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});
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});
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describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Provider (gpt-4o-mini)", () => {
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const model = getModel("openai", "gpt-4o-mini");
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it("should handle basic text prompt", async () => {
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await basicPrompt(model);
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});
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it("should execute tools correctly", async () => {
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await toolExecution(model);
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});
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it("should handle abort during execution", async () => {
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await abortExecution(model);
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});
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it("should emit state updates during streaming", async () => {
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await stateUpdates(model);
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});
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it("should maintain context across multiple turns", async () => {
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await multiTurnConversation(model);
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});
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});
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describe.skipIf(!process.env.ANTHROPIC_API_KEY)("Anthropic Provider (claude-haiku-4-5)", () => {
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const model = getModel("anthropic", "claude-haiku-4-5");
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it("should handle basic text prompt", async () => {
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await basicPrompt(model);
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});
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it("should execute tools correctly", async () => {
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await toolExecution(model);
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});
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it("should handle abort during execution", async () => {
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await abortExecution(model);
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});
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it("should emit state updates during streaming", async () => {
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await stateUpdates(model);
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});
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it("should maintain context across multiple turns", async () => {
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await multiTurnConversation(model);
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});
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});
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describe.skipIf(!process.env.XAI_API_KEY)("xAI Provider (grok-3)", () => {
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const model = getModel("xai", "grok-3");
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it("should handle basic text prompt", async () => {
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await basicPrompt(model);
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});
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it("should execute tools correctly", async () => {
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await toolExecution(model);
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});
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it("should handle abort during execution", async () => {
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await abortExecution(model);
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});
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it("should emit state updates during streaming", async () => {
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await stateUpdates(model);
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});
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it("should maintain context across multiple turns", async () => {
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await multiTurnConversation(model);
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});
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});
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describe.skipIf(!process.env.GROQ_API_KEY)("Groq Provider (openai/gpt-oss-20b)", () => {
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const model = getModel("groq", "openai/gpt-oss-20b");
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it("should handle basic text prompt", async () => {
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await basicPrompt(model);
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});
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it("should execute tools correctly", async () => {
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await toolExecution(model);
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});
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it("should handle abort during execution", async () => {
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await abortExecution(model);
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});
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it("should emit state updates during streaming", async () => {
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await stateUpdates(model);
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});
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it("should maintain context across multiple turns", async () => {
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await multiTurnConversation(model);
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});
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});
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describe.skipIf(!process.env.CEREBRAS_API_KEY)("Cerebras Provider (gpt-oss-120b)", () => {
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const model = getModel("cerebras", "gpt-oss-120b");
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it("should handle basic text prompt", async () => {
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await basicPrompt(model);
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});
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it("should execute tools correctly", async () => {
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await toolExecution(model);
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});
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it("should handle abort during execution", async () => {
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await abortExecution(model);
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});
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it("should emit state updates during streaming", async () => {
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await stateUpdates(model);
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});
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it("should maintain context across multiple turns", async () => {
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await multiTurnConversation(model);
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});
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});
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describe.skipIf(!process.env.ZAI_API_KEY)("zAI Provider (glm-4.5-air)", () => {
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const model = getModel("zai", "glm-4.5-air");
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it("should handle basic text prompt", async () => {
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await basicPrompt(model);
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});
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it("should execute tools correctly", async () => {
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await toolExecution(model);
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});
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it("should handle abort during execution", async () => {
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await abortExecution(model);
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});
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it("should emit state updates during streaming", async () => {
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await stateUpdates(model);
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});
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it("should maintain context across multiple turns", async () => {
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await multiTurnConversation(model);
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});
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});
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});
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describe("Agent.continue()", () => {
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describe("validation", () => {
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it("should throw when no messages in context", async () => {
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const agent = new Agent({
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initialState: {
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systemPrompt: "Test",
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model: getModel("anthropic", "claude-haiku-4-5"),
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},
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transport: createTransport(),
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});
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await expect(agent.continue()).rejects.toThrow("No messages to continue from");
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});
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it("should throw when last message is assistant", async () => {
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const agent = new Agent({
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initialState: {
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systemPrompt: "Test",
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model: getModel("anthropic", "claude-haiku-4-5"),
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},
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transport: createTransport(),
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});
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const assistantMessage: AssistantMessage = {
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role: "assistant",
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content: [{ type: "text", text: "Hello" }],
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api: "anthropic-messages",
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provider: "anthropic",
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model: "claude-haiku-4-5",
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usage: {
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input: 0,
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output: 0,
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cacheRead: 0,
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cacheWrite: 0,
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totalTokens: 0,
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cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
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},
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stopReason: "stop",
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timestamp: Date.now(),
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};
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agent.replaceMessages([assistantMessage]);
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await expect(agent.continue()).rejects.toThrow("Cannot continue from message role: assistant");
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});
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});
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describe.skipIf(!process.env.ANTHROPIC_API_KEY)("continue from user message", () => {
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const model = getModel("anthropic", "claude-haiku-4-5");
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it("should continue and get response when last message is user", async () => {
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const agent = new Agent({
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initialState: {
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systemPrompt: "You are a helpful assistant. Follow instructions exactly.",
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model,
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thinkingLevel: "off",
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tools: [],
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},
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transport: createTransport(),
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});
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// Manually add a user message without calling prompt()
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const userMessage: UserMessage = {
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role: "user",
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content: [{ type: "text", text: "Say exactly: HELLO WORLD" }],
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timestamp: Date.now(),
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};
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agent.replaceMessages([userMessage]);
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// Continue from the user message
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await agent.continue();
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expect(agent.state.isStreaming).toBe(false);
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expect(agent.state.messages.length).toBe(2);
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expect(agent.state.messages[0].role).toBe("user");
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expect(agent.state.messages[1].role).toBe("assistant");
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const assistantMsg = agent.state.messages[1] as AssistantMessage;
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const textContent = assistantMsg.content.find((c) => c.type === "text");
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expect(textContent).toBeDefined();
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if (textContent?.type === "text") {
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expect(textContent.text.toUpperCase()).toContain("HELLO WORLD");
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}
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});
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});
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describe.skipIf(!process.env.ANTHROPIC_API_KEY)("continue from tool result", () => {
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const model = getModel("anthropic", "claude-haiku-4-5");
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it("should continue and process tool results", async () => {
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const agent = new Agent({
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initialState: {
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systemPrompt:
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"You are a helpful assistant. After getting a calculation result, state the answer clearly.",
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model,
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thinkingLevel: "off",
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tools: [calculateTool],
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},
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transport: createTransport(),
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});
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// Set up a conversation state as if tool was just executed
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const userMessage: UserMessage = {
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role: "user",
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content: [{ type: "text", text: "What is 5 + 3?" }],
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timestamp: Date.now(),
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};
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const assistantMessage: AssistantMessage = {
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role: "assistant",
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content: [
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{ type: "text", text: "Let me calculate that." },
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{ type: "toolCall", id: "calc-1", name: "calculate", arguments: { expression: "5 + 3" } },
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],
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api: "anthropic-messages",
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provider: "anthropic",
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model: "claude-haiku-4-5",
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usage: {
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input: 0,
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output: 0,
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cacheRead: 0,
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cacheWrite: 0,
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totalTokens: 0,
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cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
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},
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stopReason: "toolUse",
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timestamp: Date.now(),
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};
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const toolResult: ToolResultMessage = {
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role: "toolResult",
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toolCallId: "calc-1",
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toolName: "calculate",
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content: [{ type: "text", text: "5 + 3 = 8" }],
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isError: false,
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timestamp: Date.now(),
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};
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agent.replaceMessages([userMessage, assistantMessage, toolResult]);
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// Continue from the tool result
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await agent.continue();
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expect(agent.state.isStreaming).toBe(false);
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// Should have added an assistant response
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expect(agent.state.messages.length).toBeGreaterThanOrEqual(4);
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const lastMessage = agent.state.messages[agent.state.messages.length - 1];
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expect(lastMessage.role).toBe("assistant");
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if (lastMessage.role === "assistant") {
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const textContent = lastMessage.content
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.filter((c) => c.type === "text")
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.map((c) => (c as { type: "text"; text: string }).text)
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.join(" ");
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// Should mention 8 in the response
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expect(textContent).toMatch(/8/);
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}
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});
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});
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});
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