rag_integration.php

<?php
/**
 * RAG Integration for Chat - PHP Integration Layer
 * Connects PHP backend with Python RAG API (powered by NVIDIA Mistral)
 * 
 * This file provides functions to:
 * 1. Fetch products from database
 * 2. Call the RAG API
 * 3. Format and return responses to the frontend
 * 
 * The RAG API uses:
 * - Sentence-Transformers for semantic search
 * - FAISS for vector similarity
 * - NVIDIA Mistral models for intelligent recommendations
 */

// Configuration
define('RAG_API_URL', getenv('RAG_API_URL') ?: 'http://localhost:8004');
define('RAG_ENDPOINT', '/search-products');

/**
 * Fetch products from database
 * Customize this function based on your database schema
 * 
 * @param mysqli $conn Database connection
 * @param string $category Optional category filter
 * @param int $limit Max products to fetch
 * @return array Array of product objects
 */
function get_products_for_rag($conn, $category = null, $limit = 50) {
    $query = "SELECT id, name, description, price, category, brand, image_path, rating 
              FROM products 
              WHERE status = 'active'";
    
    if ($category) {
        $category = $conn->real_escape_string($category);
        $query .= " AND category = '$category'";
    }
    
    $query .= " LIMIT $limit";
    
    $result = $conn->query($query);
    
    if (!$result) {
        error_log("Database error in get_products_for_rag: " . $conn->error);
        return [];
    }
    
    $products = [];
    while ($row = $result->fetch_assoc()) {
        $products[] = [
            'id' => (int)$row['id'],
            'name' => $row['name'],
            'description' => $row['description'],
            'price' => (float)$row['price'],
            'category' => $row['category'],
            'brand' => $row['brand'] ?? null,
            'image_path' => $row['image_path'] ?? null,
            'rating' => $row['rating'] ?? null,
        ];
    }
    
    return $products;
}

/**
 * Call the RAG API for product recommendations
 * 
 * @param string $query User's natural language query
 * @param array $products Array of product objects
 * @param int $top_k Number of top recommendations to return
 * @return array|false Response from RAG API or false on error
 */
function call_rag_api($query, $products, $top_k = 5) {
    if (!$query || empty($products)) {
        error_log("RAG API error: Empty query or products");
        return false;
    }
    
    // Prepare payload
    $payload = [
        'query' => $query,
        'products' => $products,
        'top_k' => $top_k
    ];
    
    // Make POST request to RAG API
    $ch = curl_init();
    curl_setopt($ch, CURLOPT_URL, RAG_API_URL . RAG_ENDPOINT);
    curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
    curl_setopt($ch, CURLOPT_POST, true);
    curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload));
    curl_setopt($ch, CURLOPT_HTTPHEADER, [
        'Content-Type: application/json',
        'Accept: application/json'
    ]);
    curl_setopt($ch, CURLOPT_TIMEOUT, 30);
    
    $response = curl_exec($ch);
    $http_code = curl_getinfo($ch, CURLINFO_HTTP_CODE);
    $curl_error = curl_error($ch);
    curl_close($ch);
    
    // Handle curl errors
    if ($curl_error) {
        error_log("RAG API curl error: $curl_error");
        return false;
    }
    
    // Handle HTTP errors
    if ($http_code !== 200) {
        error_log("RAG API HTTP error: $http_code - $response");
        return false;
    }
    
    // Parse and return response
    $data = json_decode($response, true);
    if (!$data) {
        error_log("RAG API response parse error: " . json_last_error_msg());
        return false;
    }
    
    return $data;
}

/**
 * Check if RAG API is healthy
 * 
 * @return bool True if API is responsive
 */
function check_rag_health() {
    $ch = curl_init();
    curl_setopt($ch, CURLOPT_URL, RAG_API_URL . '/health');
    curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
    curl_setopt($ch, CURLOPT_TIMEOUT, 5);
    
    curl_exec($ch);
    $http_code = curl_getinfo($ch, CURLINFO_HTTP_CODE);
    curl_close($ch);
    
    return $http_code === 200;
}

/**
 * Main function: Get AI recommendations for user query
 * This is the primary function to call from your chat endpoint
 * 
 * @param mysqli $conn Database connection
 * @param string $user_query User's question/query
 * @param string $category Optional product category to search in
 * @return array Response containing message and products
 */
function get_rag_recommendations($conn, $user_query, $category = null) {
    // Check RAG API health
    if (!check_rag_health()) {
        error_log("RAG API is not available");
        return [
            'success' => false,
            'message' => 'Recommendation service temporarily unavailable',
            'products' => []
        ];
    }
    
    // Fetch products from database
    $products = get_products_for_rag($conn, $category, 50);
    
    if (empty($products)) {
        return [
            'success' => false,
            'message' => 'No products available for recommendation',
            'products' => []
        ];
    }
    
    // Call RAG API
    $rag_response = call_rag_api($user_query, $products, 5);
    
    if (!$rag_response) {
        error_log("Failed to get RAG recommendations");
        return [
            'success' => false,
            'message' => 'Failed to generate recommendations',
            'products' => []
        ];
    }
    
    return [
        'success' => true,
        'message' => $rag_response['message'] ?? 'No message',
        'products' => $rag_response['products'] ?? [],
        'timestamp' => $rag_response['timestamp'] ?? date('c')
    ];
}

// ── Example Usage (if this file is called directly) ──────────────────────────

if ($_SERVER['REQUEST_METHOD'] === 'POST' && php_sapi_name() !== 'cli') {
    header('Content-Type: application/json');
    
    $input = json_decode(file_get_contents('php://input'), true);
    $query = $input['query'] ?? '';
    
    if (!$query) {
        http_response_code(400);
        echo json_encode(['error' => 'Query is required']);
        exit;
    }
    
    // Include your database connection
    // require_once 'db.php';
    
    // Uncomment below when integrated with your system:
    // $result = get_rag_recommendations($conn, $query);
    // echo json_encode($result);
    
    // For now, return example response
    echo json_encode([
        'success' => true,
        'message' => 'RAG API integration ready. Call get_rag_recommendations($conn, $query) from your chat handler.',
        'products' => []
    ]);
}
?>