API инструментов AI-агента: эндпоинты-функции с авторизацией для LLM

export async function handler(event) {
  // API key verified at gateway — handler assumes authenticated caller
  const { customerId } = JSON.parse(event.body || '{}');
  if (!customerId) return { statusCode: 400, body: JSON.stringify({ error: 'customerId required' }) };
  const record = await db.customers.findById(customerId); // DB_URL from workspace secrets
  if (!record) return { statusCode: 404, body: JSON.stringify({ error: 'not found' }) };
  return { statusCode: 200, body: JSON.stringify({ customer: record }) };
}

import json, os
from openai import OpenAI

client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])  # scoped to this tool only

def handler(event, context):
    body = json.loads(event.get("body") or "{}")
    text = body.get("text")
    if not text:
        return {"statusCode": 400, "body": json.dumps({"error": "text required"})}
    r = client.chat.completions.create(model="gpt-4o-mini",
        messages=[{"role": "user", "content": f"Classify intent: {text}"}])
    return {"statusCode": 200, "body": json.dumps({"intent": r.choices[0].message.content})}

// When the model returns a tool_call, dispatch it to the matching gateway route
const ROUTES = {
  lookup_customer: process.env.GATEWAY_URL + '/tools/lookup',
  classify_intent: process.env.GATEWAY_URL + '/tools/classify',
};

export async function dispatchToolCall(toolCall) {
  const { name, arguments: args } = toolCall.function ?? toolCall;
  const url = ROUTES[name];
  if (!url) return { error: `Unknown tool: ${name}` }; // returned to the model as the tool result
  const res = await fetch(url, {
    method: 'POST',
    headers: { 'Content-Type': 'application/json', 'X-Api-Key': process.env.TOOLS_API_KEY },
    body: typeof args === 'string' ? args : JSON.stringify(args),
  });
  return res.json(); // structured JSON (result or error) goes back to the model
}