Files
clawdbot/src/agents/pi-embedded-runner.test.ts
2026-01-24 00:25:58 +00:00

462 lines
14 KiB
TypeScript

import fs from "node:fs/promises";
import os from "node:os";
import path from "node:path";
import { afterAll, beforeAll, describe, expect, it, vi } from "vitest";
import type { ClawdbotConfig } from "../config/config.js";
import { ensureClawdbotModelsJson } from "./models-config.js";
vi.mock("@mariozechner/pi-ai", async () => {
const actual = await vi.importActual<typeof import("@mariozechner/pi-ai")>("@mariozechner/pi-ai");
const buildAssistantMessage = (model: { api: string; provider: string; id: string }) => ({
role: "assistant" as const,
content: [{ type: "text" as const, text: "ok" }],
stopReason: "stop" as const,
api: model.api,
provider: model.provider,
model: model.id,
usage: {
input: 1,
output: 1,
cacheRead: 0,
cacheWrite: 0,
totalTokens: 2,
cost: {
input: 0,
output: 0,
cacheRead: 0,
cacheWrite: 0,
total: 0,
},
},
timestamp: Date.now(),
});
const buildAssistantErrorMessage = (model: { api: string; provider: string; id: string }) => ({
role: "assistant" as const,
content: [] as const,
stopReason: "error" as const,
errorMessage: "boom",
api: model.api,
provider: model.provider,
model: model.id,
usage: {
input: 0,
output: 0,
cacheRead: 0,
cacheWrite: 0,
totalTokens: 0,
cost: {
input: 0,
output: 0,
cacheRead: 0,
cacheWrite: 0,
total: 0,
},
},
timestamp: Date.now(),
});
return {
...actual,
complete: async (model: { api: string; provider: string; id: string }) => {
if (model.id === "mock-error") return buildAssistantErrorMessage(model);
return buildAssistantMessage(model);
},
completeSimple: async (model: { api: string; provider: string; id: string }) => {
if (model.id === "mock-error") return buildAssistantErrorMessage(model);
return buildAssistantMessage(model);
},
streamSimple: (model: { api: string; provider: string; id: string }) => {
const stream = new actual.AssistantMessageEventStream();
setTimeout(() => {
stream.push({
type: "done",
reason: "stop",
message:
model.id === "mock-error"
? buildAssistantErrorMessage(model)
: buildAssistantMessage(model),
});
stream.end();
}, 0);
return stream;
},
};
});
let runEmbeddedPiAgent: typeof import("./pi-embedded-runner.js").runEmbeddedPiAgent;
let tempRoot: string | undefined;
let agentDir: string;
let workspaceDir: string;
let sessionCounter = 0;
beforeAll(async () => {
vi.useRealTimers();
({ runEmbeddedPiAgent } = await import("./pi-embedded-runner.js"));
tempRoot = await fs.mkdtemp(path.join(os.tmpdir(), "clawdbot-embedded-agent-"));
agentDir = path.join(tempRoot, "agent");
workspaceDir = path.join(tempRoot, "workspace");
await fs.mkdir(agentDir, { recursive: true });
await fs.mkdir(workspaceDir, { recursive: true });
}, 20_000);
afterAll(async () => {
if (!tempRoot) return;
await fs.rm(tempRoot, { recursive: true, force: true });
tempRoot = undefined;
});
const makeOpenAiConfig = (modelIds: string[]) =>
({
models: {
providers: {
openai: {
api: "openai-responses",
apiKey: "sk-test",
baseUrl: "https://example.com",
models: modelIds.map((id) => ({
id,
name: `Mock ${id}`,
reasoning: false,
input: ["text"],
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
contextWindow: 16_000,
maxTokens: 2048,
})),
},
},
},
}) satisfies ClawdbotConfig;
const ensureModels = (cfg: ClawdbotConfig) => ensureClawdbotModelsJson(cfg, agentDir);
const nextSessionFile = () => {
sessionCounter += 1;
return path.join(workspaceDir, `session-${sessionCounter}.jsonl`);
};
const testSessionKey = "agent:test:embedded";
const immediateEnqueue = async <T>(task: () => Promise<T>) => task();
const textFromContent = (content: unknown) => {
if (typeof content === "string") return content;
if (Array.isArray(content) && content[0]?.type === "text") {
return (content[0] as { text?: string }).text;
}
return undefined;
};
const readSessionMessages = async (sessionFile: string) => {
const raw = await fs.readFile(sessionFile, "utf-8");
return raw
.split(/\r?\n/)
.filter(Boolean)
.map(
(line) =>
JSON.parse(line) as {
type?: string;
message?: { role?: string; content?: unknown };
},
)
.filter((entry) => entry.type === "message")
.map((entry) => entry.message as { role?: string; content?: unknown });
};
describe("runEmbeddedPiAgent", () => {
it("writes models.json into the provided agentDir", async () => {
const sessionFile = nextSessionFile();
const cfg = {
models: {
providers: {
minimax: {
baseUrl: "https://api.minimax.io/anthropic",
api: "anthropic-messages",
apiKey: "sk-minimax-test",
models: [
{
id: "MiniMax-M2.1",
name: "MiniMax M2.1",
reasoning: false,
input: ["text"],
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
contextWindow: 200000,
maxTokens: 8192,
},
],
},
},
},
} satisfies ClawdbotConfig;
await expect(
runEmbeddedPiAgent({
sessionId: "session:test",
sessionKey: testSessionKey,
sessionFile,
workspaceDir,
config: cfg,
prompt: "hi",
provider: "definitely-not-a-provider",
model: "definitely-not-a-model",
timeoutMs: 1,
agentDir,
enqueue: immediateEnqueue,
}),
).rejects.toThrow(/Unknown model:/);
await expect(fs.stat(path.join(agentDir, "models.json"))).resolves.toBeTruthy();
});
it("persists the first user message before assistant output", { timeout: 60_000 }, async () => {
const sessionFile = nextSessionFile();
const cfg = makeOpenAiConfig(["mock-1"]);
await ensureModels(cfg);
await runEmbeddedPiAgent({
sessionId: "session:test",
sessionKey: testSessionKey,
sessionFile,
workspaceDir,
config: cfg,
prompt: "hello",
provider: "openai",
model: "mock-1",
timeoutMs: 5_000,
agentDir,
enqueue: immediateEnqueue,
});
const messages = await readSessionMessages(sessionFile);
const firstUserIndex = messages.findIndex(
(message) => message?.role === "user" && textFromContent(message.content) === "hello",
);
const firstAssistantIndex = messages.findIndex((message) => message?.role === "assistant");
expect(firstUserIndex).toBeGreaterThanOrEqual(0);
if (firstAssistantIndex !== -1) {
expect(firstUserIndex).toBeLessThan(firstAssistantIndex);
}
});
it("persists the user message when prompt fails before assistant output", async () => {
const sessionFile = nextSessionFile();
const cfg = makeOpenAiConfig(["mock-error"]);
await ensureModels(cfg);
const result = await runEmbeddedPiAgent({
sessionId: "session:test",
sessionKey: testSessionKey,
sessionFile,
workspaceDir,
config: cfg,
prompt: "boom",
provider: "openai",
model: "mock-error",
timeoutMs: 5_000,
agentDir,
enqueue: immediateEnqueue,
});
expect(result.payloads[0]?.isError).toBe(true);
const messages = await readSessionMessages(sessionFile);
const userIndex = messages.findIndex(
(message) => message?.role === "user" && textFromContent(message.content) === "boom",
);
expect(userIndex).toBeGreaterThanOrEqual(0);
});
it(
"appends new user + assistant after existing transcript entries",
{ timeout: 90_000 },
async () => {
const { SessionManager } = await import("@mariozechner/pi-coding-agent");
const sessionFile = nextSessionFile();
const sessionManager = SessionManager.open(sessionFile);
sessionManager.appendMessage({
role: "user",
content: [{ type: "text", text: "seed user" }],
});
sessionManager.appendMessage({
role: "assistant",
content: [{ type: "text", text: "seed assistant" }],
stopReason: "stop",
api: "openai-responses",
provider: "openai",
model: "mock-1",
usage: {
input: 1,
output: 1,
cacheRead: 0,
cacheWrite: 0,
totalTokens: 2,
cost: {
input: 0,
output: 0,
cacheRead: 0,
cacheWrite: 0,
total: 0,
},
},
timestamp: Date.now(),
});
const cfg = makeOpenAiConfig(["mock-1"]);
await ensureModels(cfg);
await runEmbeddedPiAgent({
sessionId: "session:test",
sessionKey: testSessionKey,
sessionFile,
workspaceDir,
config: cfg,
prompt: "hello",
provider: "openai",
model: "mock-1",
timeoutMs: 5_000,
agentDir,
enqueue: immediateEnqueue,
});
const messages = await readSessionMessages(sessionFile);
const seedUserIndex = messages.findIndex(
(message) => message?.role === "user" && textFromContent(message.content) === "seed user",
);
const seedAssistantIndex = messages.findIndex(
(message) =>
message?.role === "assistant" && textFromContent(message.content) === "seed assistant",
);
const newUserIndex = messages.findIndex(
(message) => message?.role === "user" && textFromContent(message.content) === "hello",
);
const newAssistantIndex = messages.findIndex(
(message, index) => index > newUserIndex && message?.role === "assistant",
);
expect(seedUserIndex).toBeGreaterThanOrEqual(0);
expect(seedAssistantIndex).toBeGreaterThan(seedUserIndex);
expect(newUserIndex).toBeGreaterThan(seedAssistantIndex);
expect(newAssistantIndex).toBeGreaterThan(newUserIndex);
},
);
it("persists multi-turn user/assistant ordering across runs", async () => {
const sessionFile = nextSessionFile();
const cfg = makeOpenAiConfig(["mock-1"]);
await ensureModels(cfg);
await runEmbeddedPiAgent({
sessionId: "session:test",
sessionKey: testSessionKey,
sessionFile,
workspaceDir,
config: cfg,
prompt: "first",
provider: "openai",
model: "mock-1",
timeoutMs: 5_000,
agentDir,
enqueue: immediateEnqueue,
});
await runEmbeddedPiAgent({
sessionId: "session:test",
sessionKey: testSessionKey,
sessionFile,
workspaceDir,
config: cfg,
prompt: "second",
provider: "openai",
model: "mock-1",
timeoutMs: 5_000,
agentDir,
enqueue: immediateEnqueue,
});
const messages = await readSessionMessages(sessionFile);
const firstUserIndex = messages.findIndex(
(message) => message?.role === "user" && textFromContent(message.content) === "first",
);
const firstAssistantIndex = messages.findIndex(
(message, index) => index > firstUserIndex && message?.role === "assistant",
);
const secondUserIndex = messages.findIndex(
(message, index) =>
index > firstAssistantIndex &&
message?.role === "user" &&
textFromContent(message.content) === "second",
);
const secondAssistantIndex = messages.findIndex(
(message, index) => index > secondUserIndex && message?.role === "assistant",
);
expect(firstUserIndex).toBeGreaterThanOrEqual(0);
expect(firstAssistantIndex).toBeGreaterThan(firstUserIndex);
expect(secondUserIndex).toBeGreaterThan(firstAssistantIndex);
expect(secondAssistantIndex).toBeGreaterThan(secondUserIndex);
});
it("repairs orphaned user messages and continues", async () => {
const { SessionManager } = await import("@mariozechner/pi-coding-agent");
const sessionFile = nextSessionFile();
const sessionManager = SessionManager.open(sessionFile);
sessionManager.appendMessage({
role: "user",
content: [{ type: "text", text: "orphaned user" }],
});
const cfg = makeOpenAiConfig(["mock-1"]);
await ensureModels(cfg);
const result = await runEmbeddedPiAgent({
sessionId: "session:test",
sessionKey: testSessionKey,
sessionFile,
workspaceDir,
config: cfg,
prompt: "hello",
provider: "openai",
model: "mock-1",
timeoutMs: 5_000,
agentDir,
enqueue: immediateEnqueue,
});
expect(result.meta.error).toBeUndefined();
expect(result.payloads?.length ?? 0).toBeGreaterThan(0);
});
it("repairs orphaned single-user sessions and continues", async () => {
const { SessionManager } = await import("@mariozechner/pi-coding-agent");
const sessionFile = nextSessionFile();
const sessionManager = SessionManager.open(sessionFile);
sessionManager.appendMessage({
role: "user",
content: [{ type: "text", text: "solo user" }],
});
const cfg = makeOpenAiConfig(["mock-1"]);
await ensureModels(cfg);
const result = await runEmbeddedPiAgent({
sessionId: "session:test",
sessionKey: testSessionKey,
sessionFile,
workspaceDir,
config: cfg,
prompt: "hello",
provider: "openai",
model: "mock-1",
timeoutMs: 5_000,
agentDir,
enqueue: immediateEnqueue,
});
expect(result.meta.error).toBeUndefined();
expect(result.payloads?.length ?? 0).toBeGreaterThan(0);
});
});