نظرة عامة على الواجهة البرمجية

npm run docs:build   # writes docs/api/index.html

┌─────────────────────────────────────┐
│         Your Application            │
│    (React, Vue, Express, etc.)      │
└──────────────┬──────────────────────┘
               │
┌──────────────▼──────────────────────┐
│     @lousho/build-ai-agent          │
│  ┌────────────────────────────┐    │
│  │ createAgent / Builder /     │    │
│  │ Executor (approvals,        │    │
│  │ checkpoints, tracing)       │    │
│  ├────────────────────────────┤    │
│  │ Tools │ Delegation │ MCP    │    │
│  │ Flows │ Guardrails │ Evals  │    │
│  ├────────────────────────────┤    │
│  │       Core Engine          │    │
│  └────────────────────────────┘    │
└──────────────┬──────────────────────┘
               │
┌──────────────▼──────────────────────┐
│  Your LLM Provider & Deploy Target  │
│ (OpenAI/Anthropic/Ollama/OpenRouter,│
│  Node server / Docker / Workers)    │
└─────────────────────────────────────┘

import { createAgent, defineTool } from '@lousho/build-ai-agent';
import { mockModel } from '@lousho/build-ai-agent/testing';
import { z } from 'zod';

const refund = defineTool({ name: 'refund', description: 'Refunds an order', input: z.object({ orderId: z.string() }), execute: async () => 'ok' });

const agent = createAgent({
  provider: mockModel(['Hello!']),
  // A cheaper model for short inputs, tenant instructions, tools by role.
  model: ({ input }) => (typeof input === 'string' && input.length < 200 ? 'small-model' : 'large-model'),
  instructions: ({ metadata }) => `You are the support agent of ${String(metadata?.tenant ?? 'Acme')}.`,
  tools: ({ metadata }) => (metadata?.role === 'admin' ? [refund] : []),
});

await agent.send('Hi', { metadata: { tenant: 'Globex', role: 'admin' } });

import { createAgent, createMockProvider } from '@lousho/build-ai-agent';
const agent = createAgent({ prompt: 'You are helpful.', provider: createMockProvider() });
const controller = new AbortController();
setTimeout(() => controller.abort(), 5_000); // e.g. from a Stop button
const result = await agent.send('Write a long report', { signal: controller.signal });
console.log(result.finishReason); // 'aborted' if it was cancelled, else 'stop'

import { createAgent, createMockProvider } from '@lousho/build-ai-agent';
const agent = createAgent({ prompt: 'You are helpful.', provider: createMockProvider() });
const result = await agent.send('Summarize this', { signal: AbortSignal.timeout(30_000) });

import { createAgent, createMockProvider } from '@lousho/build-ai-agent';
const agent = createAgent({ prompt: 'You are helpful.', provider: createMockProvider(), maxSteps: 3 });
const result = await agent.send('Research this thoroughly');
if (result.finishReason === 'max-steps') console.warn(`Gave up after ${result.steps} steps`);

import { createAgent, createMockProvider, defineTool } from '@lousho/build-ai-agent';
import { z } from 'zod';

const getWeather = defineTool({
  name: 'get_weather',
  description: 'Current weather for a city',
  input: z.object({ city: z.string() }),
  execute: async ({ city }) => ({ city, tempC: 21 }),
});

const agent = createAgent({
  prompt: 'You are a travel assistant.',
  provider: createMockProvider(),
  tools: [getWeather],
  toolConcurrency: 4, // at most 4 tool calls of a turn in flight
});

import { defineTool } from '@lousho/build-ai-agent';
import { z } from 'zod';

const sendEmail = defineTool({
  name: 'send_email', // 1-64 chars: letters, digits, _ and -
  description: 'Send an email',
  input: z.object({ to: z.string().email(), subject: z.string() }),
  needsApproval: ({ to }) => !to.endsWith('@mycompany.com'), // `to` is typed
  async execute({ to, subject }) {
    return { messageId: `${to}:${subject}` };
  },
});

import { loadMcpTools } from '@lousho/build-ai-agent/mcp';

const tools = await loadMcpTools(mcpClient, 'my-server');

import { loadMcpTools, type SkippedMcpTool } from '@lousho/build-ai-agent/mcp';

const skipped: SkippedMcpTool[] = [];
const tools = await loadMcpTools(mcpClient, 'my-server', {
  logger: console,
  onSkip: (tool) => skipped.push(tool), // { name, reason }
});

import { createAgent, createTodoTools, type TodoStore } from '@lousho/build-ai-agent';

const todos = createTodoTools({ onChange: (list) => console.log(list.length, 'todos') });
const planner = createAgent({ prompt: 'Plan multi-step work, then do it.', provider, tools: todos.tools });

await planner.send('Migrate the repo to ESM');
console.log(await todos.getTodos()); // [{ id: 'todo_1', content: '...', status: 'completed' }, ...]

// Persist the list somewhere else:
let saved: Awaited<ReturnType<TodoStore['get']>> = [];
createTodoTools({ store: { get: () => saved, set: (next) => void (saved = next) } });

{
  "error": "ToolArgumentsValidationError",
  "toolName": "sendEmail",
  "message": "Invalid arguments for tool 'sendEmail': 2 issues (to: Required; count: Expected number, received string)",
  "kind": "validation",
  "issues": [
    { "path": "to", "message": "Required" },
    { "path": "count", "message": "Expected number, received string" }
  ]
}

{ "error": "TypeError", "toolName": "search", "message": "query must not be empty", "kind": "execution" }

import { estimateTokens, estimateCost, getModelInfo, registerModel } from '@lousho/build-ai-agent';

// A custom or self-hosted model: add it (or override a built-in) before use.
registerModel({
  id: 'my-llama',
  provider: 'ollama',
  contextWindow: 32768,
  inputCostPerMTok: 0.2, // optional; omit for unknown or free
  outputCostPerMTok: 0.6,
});

const used = estimateTokens([{ role: 'user', content: 'Summarise this report' }], { model: 'my-llama' });
const info = getModelInfo('openai/gpt-4o-mini'); // exact id, `provider/id`, or a dated snapshot
const usd = estimateCost({ inputTokens: used, outputTokens: 500 }, 'my-llama'); // undefined if unpriced

import { AgentExecutor, formatUsage } from '@lousho/build-ai-agent';

const result = await AgentExecutor.execute({ agent, input: 'Compare 3 cities', provider });

result.usage.inputTokens; // all model calls of the run, delegated children included
result.usage.costUsd; // number, or undefined if any model used has no known price
result.usage.estimated; // true if some call reported no usage and was estimated
result.usage.byModel['gpt-4o-mini']; // { inputTokens, outputTokens, costUsd?, calls }
result.stepUsage?.[0]; // { step, model, usage, estimated, costUsd? } per model call
console.log(formatUsage(result.usage)); // 1,234 in / 567 out tokens · $0.0042 (2 model calls)

import { registerModel } from '@lousho/build-ai-agent';

registerModel({
  id: 'ft:gpt-4o-mini:acme',
  provider: 'openai',
  contextWindow: 128000,
  inputCostPerMTok: 0.3,
  outputCostPerMTok: 1.2,
});

import { createAgent, type AgentHook } from '@lousho/build-ai-agent';

const guard: AgentHook = {
  name: 'guard',
  preToolCall(ctx) {
    if (ctx.toolName === 'shell') return { deny: 'Use the workspace tools instead' };
    if (ctx.toolName === 'search') return { input: { ...ctx.args, limit: 10 } };
    return undefined; // continue unchanged
  },
  postToolCall(_ctx, result) {
    return typeof result.result === 'string' ? { result: result.result.slice(0, 2000) } : undefined;
  },
};

const agent = createAgent({ provider, instructions: 'You research things.', hooks: [guard] });

import { createAgent, createMockProvider } from '@lousho/build-ai-agent';
import { WebhookTriggerAdapter } from '@lousho/build-ai-agent/triggers';

const agent = createAgent({ prompt: 'You are helpful.', provider: createMockProvider() });

// HMAC of the RAW request body (GitHub / Shopify style): header `x-signature-256: sha256=<hex>`.
new WebhookTriggerAdapter({
  port: 8787,
  auth: { type: 'hmac', secret: process.env.WEBHOOK_SECRET ?? '' },
}).listen(agent, (input) => agent.send(input));

// Replay protection: the signed payload becomes `${timestamp}.${body}` and
// requests more than `toleranceSeconds` (default 300) old are rejected.
new WebhookTriggerAdapter({
  auth: {
    type: 'hmac',
    secret: process.env.WEBHOOK_SECRET ?? '',
    header: 'x-signature',
    timestampHeader: 'x-timestamp',
    toleranceSeconds: 120,
  },
});

// A shared bearer token (`Authorization: Bearer <token>`).
new WebhookTriggerAdapter({ auth: { type: 'bearer', token: process.env.WEBHOOK_TOKEN ?? '' } });

// Anything else: return true to accept. `rawBody` is a Buffer of the exact bytes received.
new WebhookTriggerAdapter({
  auth: { type: 'custom', verify: (req) => req.headers['x-api-key'] === process.env.API_KEY },
});

import { createAgent, createMockProvider } from '@lousho/build-ai-agent';
import { SlackTriggerAdapter, verifySlackSignature } from '@lousho/build-ai-agent/triggers';
import * as http from 'node:http';

const agent = createAgent({ prompt: 'You are helpful.', provider: createMockProvider() });
const slack = new SlackTriggerAdapter({ signingSecret: process.env.SLACK_SIGNING_SECRET });
slack.listen(agent, (input) => agent.send(input));

http
  .createServer((req, res) => {
    const chunks: Buffer[] = [];
    req.on('data', (chunk: Buffer) => chunks.push(chunk));
    req.on('end', async () => {
      const { status, body } = await slack.handleRequest({ headers: req.headers, rawBody: Buffer.concat(chunks) });
      res.writeHead(status, { 'Content-Type': 'application/json' }).end(JSON.stringify(body));
    });
  })
  .listen(3000);

// Your own handler (slash commands, interactivity)? Verify the RAW body yourself:
const authentic = verifySlackSignature({
  signingSecret: process.env.SLACK_SIGNING_SECRET ?? '',
  timestamp: '1700000000', // the X-Slack-Request-Timestamp header
  signature: 'v0=...', // the X-Slack-Signature header
  rawBody: '{"type":"url_verification"}',
});

import { createAgent, createMockProvider } from '@lousho/build-ai-agent';
import { CronTriggerAdapter } from '@lousho/build-ai-agent/triggers';

const agent = createAgent({ prompt: 'You are helpful.', provider: createMockProvider() });

new CronTriggerAdapter({
  cron: '*/15 9-17 * * MON-FRI', // minute hour day-of-month month day-of-week
  timezone: 'Europe/Paris', // IANA name; defaults to the machine's local zone
  input: 'Check the support queue',
  onResult: (result, error) => console.log(error ?? result?.text),
}).listen(agent, (input) => agent.send(input));