Crie agentes que executam por horas, não segundos

import { OpenRouter, stepCountIs, maxCost } from '@openrouter/agent';
import type { ConversationState, StateAccessor } from '@openrouter/agent';
import { readFile, rename, writeFile } from 'node:fs/promises';

// Persist conversation state to disk between runs. Write to a temp file
// then rename so a crash mid-write cannot leave a truncated state file.
// Only swallow ENOENT on load — real I/O or permission errors should
// surface instead of silently restarting the agent from scratch.
const fileStateAccessor = (path: string): StateAccessor => ({
  load: async () => {
    const raw = await readFile(path, 'utf8').catch((err: NodeJS.ErrnoException) => {
      if (err.code === 'ENOENT') return null;
      throw err;
    });
    return raw ? (JSON.parse(raw) as ConversationState) : null;
  },
  save: async (state) => {
    const tmp = `${path}.tmp`;
    await writeFile(tmp, JSON.stringify(state));
    await rename(tmp, path);
  },
});

const openrouter = new OpenRouter();

// First run — checkpoint after every step. Always cap cost + steps.
const first = openrouter.callModel({
  model: '~anthropic/claude-opus-latest',
  input: 'Plan and start a 3-day data migration.',
  state: fileStateAccessor('./run.json'),
  stopWhen: [stepCountIs(200), maxCost(5)],
});
await first.getResponse();

// Crash, redeploy, or human approval — then resume from disk.
// 'input: []' means "no new user turn, continue from saved state".
const resumed = openrouter.callModel({
  model: '~anthropic/claude-opus-latest',
  input: [],
  state: fileStateAccessor('./run.json'),
  stopWhen: [stepCountIs(200), maxCost(5)],
});
await resumed.getResponse();

import { OpenRouter } from '@openrouter/sdk';
import { OpenRouter as Agent, stepCountIs, maxCost } from '@openrouter/agent';
import { readFile } from 'node:fs/promises';

const sdk = new OpenRouter();
const agent = new Agent();

// 1. Transcribe a voice memo into text
const audioBuffer = await readFile('./voice-memo.wav');
const transcription = await sdk.stt.createTranscription({
  model: 'openai/whisper-1',
  inputAudio: { data: audioBuffer.toString('base64'), format: 'wav' },
});

// 2. Hand the transcript to a long-horizon agent loop
const result = agent.callModel({
  model: '~anthropic/claude-opus-latest',
  input: transcription.text,
  stopWhen: [stepCountIs(50), maxCost(2)],
});

console.log(await result.getText());

import { OpenRouter, stepCountIs, maxCost } from '@openrouter/agent';

// The tool from "Long-Running Loop", extracted to a module.
import { searchTool } from './tools';

const openrouter = new OpenRouter();

const SELF_ASK_MAX_ITERATIONS = 10;
const REVIEW_PROMPT =
  'Review your last response adversarially. If the work is complete and ' +
  'every claim is verified, reply with only [DONE]. Otherwise list the ' +
  'gaps and keep researching.';

// Each iteration appends a new turn to the persisted state, so the agent
// builds on its prior work instead of starting over.
let input: string | unknown[] =
  'Research the fusion energy landscape and produce a 5-page report.';
let final = '';

for (let i = 0; i < SELF_ASK_MAX_ITERATIONS; i++) {
  const result = openrouter.callModel({
    model: '~anthropic/claude-opus-latest',
    input,
    tools: [searchTool],
    stopWhen: [stepCountIs(50), maxCost(2)],
  });
  final = await result.getText();
  if (final.includes('[DONE]')) break;
  // Hand the assistant's own output back as an adversarial reviewer turn.
  input = REVIEW_PROMPT;
}