DeepSeek

/**
 * DeepSeek Chat Completion via Lava
 *
 * Prerequisites:
 * - Lava forward token (get from dashboard: Build > Secret Keys)
 * - Backend server (CORS blocks frontend calls for security)
 *
 * Current Models (October 2025):
 * - deepseek-v3.2: Latest enhanced model with improved reasoning
 * - deepseek-v3: Third-generation general model
 * - deepseek-coder: Code-specialized model
 * - deepseek-chat: General conversational model
 *
 * Response Data:
 * - Usage tracking: Available in response body at `data.usage`
 * - Request ID: Available in `x-lava-request-id` response header
 */

// Load environment variables
require('dotenv').config({ path: '.env.local' });

async function callDeepSeekViaLava() {
  // 1. Define the DeepSeek endpoint
  const PROVIDER_ENDPOINT = 'https://api.deepseek.com/v1/chat/completions';

  // 2. Build the Lava forward proxy URL
  const url = `${process.env.LAVA_BASE_URL}/forward?u=${PROVIDER_ENDPOINT}`;

  // 3. Set up authentication headers
  const headers = {
    'Content-Type': 'application/json',
    'Authorization': `Bearer ${process.env.LAVA_FORWARD_TOKEN}`
  };

  // 4. Define the request body (standard OpenAI format)
  const requestBody = {
    model: 'deepseek-v3.2',  // Use latest enhanced model
    messages: [
      { role: 'system', content: 'You are an expert programmer.' },
      { role: 'user', content: 'Write a Python function to check if a number is prime.' }
    ],
    temperature: 0.7,
    max_tokens: 1024
  };

  // 5. Make the request
  try {
    const response = await fetch(url, {
      method: 'POST',
      headers: headers,
      body: JSON.stringify(requestBody)
    });

    // 6. Parse the response
    const data = await response.json();

    // 7. Extract usage data (from response body)
    const usage = data.usage;
    console.log('\nUsage Tracking:');
    console.log(`  Prompt tokens: ${usage.prompt_tokens}`);
    console.log(`  Completion tokens: ${usage.completion_tokens}`);
    console.log(`  Total tokens: ${usage.total_tokens}`);

    // 8. Extract request ID (from response header)
    const requestId = response.headers.get('x-lava-request-id');
    console.log(`\nLava Request ID: ${requestId}`);
    console.log('  (Use this ID to find the request in your dashboard)');

    // 9. Display the AI response
    console.log('\nAI Response:');
    console.log(data.choices[0].message.content);

    return data;
  } catch (error) {
    console.error('Error calling DeepSeek via Lava:', error.message);
    throw error;
  }
}

// Run the example
callDeepSeekViaLava();

{
  "model": "deepseek-v3.2",
  "messages": [
    { "role": "system", "content": "You are an expert programmer." },
    { "role": "user", "content": "Write a Python function to check if a number is prime." }
  ],
  "temperature": 0.7,
  "max_tokens": 1024,
  "stream": false
}

{
  "id": "chatcmpl-xxx",
  "object": "chat.completion",
  "created": 1234567890,
  "model": "deepseek-v3.2",
  "choices": [{
    "index": 0,
    "message": {
      "role": "assistant",
      "content": "Here's a Python function to check if a number is prime:\n\n```python\ndef is_prime(n):\n    if n <= 1:\n        return False\n    for i in range(2, int(n**0.5) + 1):\n        if n % i == 0:\n            return False\n    return True\n```"
    },
    "finish_reason": "stop"
  }],
  "usage": {
    "prompt_tokens": 25,
    "completion_tokens": 85,
    "total_tokens": 110
  }
}

const requestBody = {
  model: 'deepseek-coder',
  messages: [
    { role: 'user', content: 'Explain async/await in JavaScript.' }
  ],
  stream: true,
  stream_options: {
    include_usage: true  // Include token usage with streaming
  }
};

{
  "usage": {
    "prompt_tokens": 100,
    "completion_tokens": 50,
    "total_tokens": 150
  }
}

const usage = data.usage;
console.log(`Prompt tokens: ${usage.prompt_tokens}`);
console.log(`Completion tokens: ${usage.completion_tokens}`);
console.log(`Total tokens: ${usage.total_tokens}`);

const requestId = response.headers.get('x-lava-request-id');
console.log(`Request ID: ${requestId}`);
// Use this ID to find the request in your Lava dashboard

${LAVA_SECRET_KEY}.${CONNECTION_SECRET}.${PRODUCT_SECRET}.${YOUR_DEEPSEEK_API_KEY}