/**
 * OpenAI Chat Completion via Lava
 *
 * 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 callOpenAIViaLava() {
  // 1. Define the provider endpoint
  const PROVIDER_ENDPOINT = 'https://api.openai.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: 'gpt-5',  // or gpt-4o, gpt-4.1, etc.
    messages: [
      { role: 'system', content: 'You are a helpful assistant.' },
      { role: 'user', content: 'Say hello in one sentence.' }
    ],
    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}`);

    // Check for cached tokens (GPT-4o feature)
    if (usage.prompt_tokens_details?.cached_tokens) {
      console.log(`  Cached tokens: ${usage.prompt_tokens_details.cached_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 OpenAI via Lava:', error.message);
    throw error;
  }
}

// Run the example
callOpenAIViaLava();

{
  "model": "gpt-4o",
  "messages": [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "Hello!"}
  ],
  "temperature": 0.7,
  "max_tokens": 1024,
  "stream": false
}

{
  "id": "chatcmpl-123",
  "object": "chat.completion",
  "created": 1677652288,
  "model": "gpt-4o",
  "choices": [{
    "index": 0,
    "message": {
      "role": "assistant",
      "content": "Hello! How can I help you today?"
    },
    "finish_reason": "stop"
  }],
  "usage": {
    "prompt_tokens": 13,
    "completion_tokens": 7,
    "total_tokens": 20,
    "prompt_tokens_details": {
      "cached_tokens": 0
    }
  }
}

{
  "model": "gpt-4o",
  "messages": [...],
  "tools": [{
    "type": "function",
    "function": {
      "name": "get_weather",
      "description": "Get current weather",
      "parameters": {
        "type": "object",
        "properties": {
          "location": {"type": "string"}
        }
      }
    }
  }]
}

{
  "model": "gpt-4o",
  "messages": [...],
  "response_format": {"type": "json_object"}
}