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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' });
}
}