مخطط LLM

import { createLLMTracker } from "@dodopayments/ingestion-blueprints";
import { generateText } from "ai";
import { google } from "@ai-sdk/google";
import "dotenv/config";

async function aiSdkExample() {
  console.log("🤖 AI SDK Simple Usage Example\n");

  try {
    // 1. Create tracker
    const llmTracker = createLLMTracker({
      apiKey: process.env.DODO_PAYMENTS_API_KEY,
      environment: "test_mode",
      eventName: "your_meter_event_name",
    });

    // 2. Wrap the ai-sdk methods
    const client = llmTracker.wrap({
      client: { generateText },
      customerId: "cus_123",
      metadata: {
        provider: "ai-sdk",
      },
    });

    // 3. Use the wrapped function
    const response = await client.generateText({
      model: google("gemini-2.5-flash"),
      prompt: "Hello, I am a cool guy! Tell me a fun fact.",
      maxOutputTokens: 500,
    });

    console.log(response);
    console.log(response.usage);
    console.log("✅ Automatically tracked for customer\n");
  } catch (error) {
    console.error(error);
  }
}

aiSdkExample().catch(console.error);

import { createLLMTracker } from '@dodopayments/ingestion-blueprints';
import OpenAI from 'openai';
import Groq from 'groq-sdk';
import Anthropic from '@anthropic-ai/sdk';
import { GoogleGenAI } from '@google/genai';

// Create separate trackers for different providers
const openaiTracker = createLLMTracker({
  apiKey: process.env.DODO_PAYMENTS_API_KEY,
  environment: 'live_mode',
  eventName: 'openai.usage'
});

const groqTracker = createLLMTracker({
  apiKey: process.env.DODO_PAYMENTS_API_KEY,
  environment: 'live_mode',
  eventName: 'groq.usage'
});

const anthropicTracker = createLLMTracker({
  apiKey: process.env.DODO_PAYMENTS_API_KEY,
  environment: 'live_mode',
  eventName: 'anthropic.usage'
});

const geminiTracker = createLLMTracker({
  apiKey: process.env.DODO_PAYMENTS_API_KEY,
  environment: 'live_mode',
  eventName: 'gemini.usage'
});

const openrouterTracker = createLLMTracker({
  apiKey: process.env.DODO_PAYMENTS_API_KEY,
  environment: 'live_mode',
  eventName: 'openrouter.usage'
});

// Initialize clients
const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
const groq = new Groq({ apiKey: process.env.GROQ_API_KEY });
const anthropic = new Anthropic({ apiKey: process.env.ANTHROPIC_API_KEY });
const googleGenai = new GoogleGenAI({ apiKey: process.env.GOOGLE_GENERATIVE_AI_API_KEY });
const openrouter = new OpenAI({ 
  baseURL: 'https://openrouter.ai/api/v1',
  apiKey: process.env.OPENROUTER_API_KEY 
});

// Wrap clients
const trackedOpenAI = openaiTracker.wrap({ client: openai, customerId: 'cus_123' });
const trackedGroq = groqTracker.wrap({ client: groq, customerId: 'cus_123' });
const trackedAnthropic = anthropicTracker.wrap({ client: anthropic, customerId: 'cus_123' });
const trackedGemini = geminiTracker.wrap({ client: googleGenai, customerId: 'cus_123' });
const trackedOpenRouter = openrouterTracker.wrap({ client: openrouter, customerId: 'cus_123' });

// Use whichever provider you need
const response = await trackedOpenAI.chat.completions.create({
  model: 'gpt-4',
  messages: [{ role: 'user', content: 'Hello!' }]
});
// or
const geminiResponse = await trackedGemini.models.generateContent({
  model: 'gemini-2.5-flash',
  contents: 'Hello!'
});
// or
const openrouterResponse = await trackedOpenRouter.chat.completions.create({
  model: 'qwen/qwen3-max',
  messages: [{ role: 'user', content: 'Hello!' }]
});

import express from 'express';
import { createLLMTracker } from '@dodopayments/ingestion-blueprints';
import OpenAI from 'openai';

const app = express();
app.use(express.json());

// Initialize OpenAI client
const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });

// Create tracker once at startup
const tracker = createLLMTracker({
  apiKey: process.env.DODO_PAYMENTS_API_KEY,
  environment: process.env.NODE_ENV === 'production' ? 'live_mode' : 'test_mode',
  eventName: 'api.chat_completion'
});

// Chat endpoint with automatic tracking
app.post('/api/chat', async (req, res) => {
  try {
    const { message, userId } = req.body;
    
    // Validate input
    if (!message || !userId) {
      return res.status(400).json({ error: 'Missing message or userId' });
    }
    
    // Wrap client for this specific user
    const trackedClient = tracker.wrap({
      client: openai,
      customerId: userId,
      metadata: { 
        endpoint: '/api/chat',
        timestamp: new Date().toISOString()
      }
    });
    
    // Make LLM request - automatically tracked
    const response = await trackedClient.chat.completions.create({
      model: 'gpt-4',
      messages: [{ role: 'user', content: message }],
      temperature: 0.7
    });
    
    const completion = response.choices[0].message.content;
    
    res.json({ 
      message: completion,
      usage: response.usage
    });
  } catch (error) {
    console.error('Chat error:', error);
    res.status(500).json({ error: 'Internal server error' });
  }
});

app.listen(3000, () => {
  console.log('Server running on port 3000');
});

{
  "event_id": "llm_1704709800000_abc123",
  "customer_id": "cus_123",
  "event_name": "llm.chat_completion",
  "timestamp": "2024-01-08T10:30:00.000Z",
  "metadata": {
    "inputTokens": 10,
    "outputTokens": 25,
    "totalTokens": 35,
    "model": "gpt-4"
  }
}