server.js

const express = require('express');
const cors = require('cors');
const fetch = require('node-fetch');
const path = require('path');

const app = express();
const PORT = process.env.PORT || 3000;

// Middleware
app.use(cors());
app.use(express.json());
app.use(express.static('.'));

// Serve static files
app.get('/', (req, res) => {
    res.sendFile(path.join(__dirname, 'index.html'));
});

app.get('/search', (req, res) => {
    res.sendFile(path.join(__dirname, 'search.html'));
});

// Azure OpenAI with search endpoint
app.post('/api/openai-search', async (req, res) => {
    try {
        const { 
            endpoint, 
            apiKey, 
            deployment, 
            query, 
            searchEndpoint, 
            searchKey, 
            indexName,
            maxTokens, 
            temperature 
        } = req.body;
        
        if (!endpoint || !apiKey || !deployment || !query) {
            return res.status(400).json({ error: 'Missing required parameters' });
        }

        const openAIUrl = `${endpoint}/openai/deployments/${deployment}/chat/completions?api-version=2024-02-15-preview`;
        
        // Prepare the request body with search configuration
        const requestBody = {
            messages: [
                {
                    role: "system",
                    content: `You are a helpful assistant that answers questions based on the provided search results. 
                    Always cite the specific documents you reference in your answer. 
                    If the search results don't contain enough information to answer the question, say so clearly.
                    Format your response with clear citations to the source documents.`
                },
                {
                    role: "user",
                    content: query
                }
            ],
            max_tokens: maxTokens || 1000,
            temperature: temperature || 0.7
        };

        // Add search configuration if provided
        if (searchEndpoint && searchKey && indexName) {
            requestBody.data_sources = [
                {
                    type: "AzureCognitiveSearch",
                    parameters: {
                        endpoint: searchEndpoint,
                        key: searchKey,
                        indexName: indexName
                    }
                }
            ];
        }

        const response = await fetch(openAIUrl, {
            method: 'POST',
            headers: {
                'Content-Type': 'application/json',
                'api-key': apiKey
            },
            body: JSON.stringify(requestBody)
        });

        if (!response.ok) {
            const errorText = await response.text();
            throw new Error(`OpenAI API failed: ${response.status} ${response.statusText} - ${errorText}`);
        }

        const data = await response.json();
        res.json(data);
    } catch (error) {
        console.error('OpenAI search error:', error);
        res.status(500).json({ error: error.message });
    }
});

// Health check endpoint
app.get('/api/health', (req, res) => {
    res.json({ status: 'OK', timestamp: new Date().toISOString() });
});

app.listen(PORT, () => {
    console.log(`Server running on http://localhost:${PORT}`);
    console.log(`Video Indexer: http://localhost:${PORT}`);
    console.log(`AI Search: http://localhost:${PORT}/search`);
});