import OpenAI from 'openai';

// Initialize OpenAI client (for local simulation or external API)
const openai = new OpenAI({
  apiKey: process.env.NEXT_PUBLIC_OPENAI_API_KEY || 'dummy-key-for-demo',
});

export default async function handler(req, res) {
  if (req.method !== 'POST') {
    return res.status(405).json({ error: 'Method not allowed' });
  }

  const { prompt } = req.body;

  if (!prompt) {
    return res.status(400).json({ error: 'Prompt is required' });
  }

  try {
    // Simulate MedGemma response
    // Replace this with actual MedGemma inference logic or API call
    const response = await openai.chat.completions.create({
      model: 'medgemma-2-27b-it', // Example model name
      messages: [
        {
          role: 'system',
          content: 'You are a specialized dental assistant trained on medical data. Provide accurate, professional, and empathetic dental advice. Always include a disclaimer that this is not a substitute for professional medical advice.'
        },
        {
          role: 'user',
          content: prompt
        }
      ],
      max_tokens: 500,
      temperature: 0.7,
    });

    const reply = response.choices[0]?.message?.content || 'I am unable to generate a response at this time.';

    res.status(200).json({ reply });
  } catch (error) {
    console.error('API Error:', error);
    res.status(500).json({ error: 'Internal server error' });
  }
}