ac7467f0b4
- Added comprehensive AI Assistant system (aiassist/ directory): * Vector search and embedding capabilities * Typebot proxy integration * Elastic search functionality * Message classification and chat history * MCP proxy for external integrations - Implemented Court Status API (GetCourtStatus.php): * Real-time court document status checking * Integration with external court systems * Comprehensive error handling and logging - Enhanced S3 integration: * Improved file backup system with metadata * Batch processing capabilities * Enhanced error logging and recovery * Copy operations with URL fixing - Added Telegram contact creation API - Improved error logging across all modules - Enhanced callback system for AI responses - Extensive backup file storage with timestamps - Updated documentation and README files - File storage improvements: * Thousands of backup files with proper metadata * Fix operations for broken file references * Project-specific backup and recovery systems * Comprehensive file integrity checking Total: 26,461+ files added/modified including AWS SDK, vendor dependencies, and extensive backup system.
386 lines
14 KiB
PHP
386 lines
14 KiB
PHP
<?php
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// aiassist/vectorgpt.php
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require_once 'config.php';
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require_once 'logger.php';
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function createVectorStore() {
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$curl = curl_init();
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$payload = json_encode(['name' => 'Vector Store']);
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logMessage("Создание Vector Store. Отправляем payload: " . $payload);
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curl_setopt_array($curl, [
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CURLOPT_URL => OPENAI_VECTOR_STORES_API,
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CURLOPT_RETURNTRANSFER => true,
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CURLOPT_POST => true,
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CURLOPT_POSTFIELDS => $payload,
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CURLOPT_HTTPHEADER => [
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'Content-Type: application/json',
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'Authorization: Bearer ' . OPENAI_API_KEY,
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'OpenAI-Beta: assistants=v2'
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]
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]);
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$response = curl_exec($curl);
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$httpCode = curl_getinfo($curl, CURLINFO_HTTP_CODE);
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$curlError = curl_error($curl);
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curl_close($curl);
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logMessage("Ответ OpenAI (создание Vector Store): HTTP $httpCode - " . $response);
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if ($curlError) {
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logMessage("Ошибка cURL при создании Vector Store: " . $curlError);
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return null;
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}
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$decoded = json_decode($response, true);
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if ($httpCode !== 200 || !isset($decoded['id'])) {
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logMessage("Ошибка при создании Vector Store: " . json_encode($decoded, JSON_UNESCAPED_UNICODE));
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return null;
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}
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return $decoded['id'];
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}
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function uploadFileToOpenAI($filePath) {
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if (!file_exists($filePath) || filesize($filePath) == 0) {
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logMessage("❌ Ошибка: Файл не найден или пустой! $filePath");
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return null;
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}
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logMessage("📤 Загружаем файл в OpenAI: $filePath");
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logMessage("🔑 Используем API-ключ: " . substr(OPENAI_API_KEY, 0, 8) . "********");
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$curl = curl_init();
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curl_setopt_array($curl, [
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CURLOPT_URL => OPENAI_FILES_API,
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CURLOPT_RETURNTRANSFER => true,
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CURLOPT_POST => true,
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CURLOPT_POSTFIELDS => [
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'file' => new CURLFile($filePath),
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'purpose' => 'assistants'
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],
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CURLOPT_HTTPHEADER => [
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"Authorization: Bearer " . OPENAI_API_KEY,
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"OpenAI-Beta: assistants=v2"
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// Content-Type: multipart/form-data автоматически добавляется cURL с правильным boundary
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]
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]);
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$response = curl_exec($curl);
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$httpCode = curl_getinfo($curl, CURLINFO_HTTP_CODE);
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$curlError = curl_error($curl);
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curl_close($curl);
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logMessage("📡 Ответ OpenAI (загрузка файла): HTTP $httpCode - " . $response);
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if ($curlError) {
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logMessage("❌ Ошибка cURL при загрузке файла: " . $curlError);
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return null;
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}
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$decoded = json_decode($response, true);
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if ($httpCode !== 200 || !isset($decoded['id'])) {
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logMessage("❌ Ошибка при загрузке файла в OpenAI: " . json_encode($decoded, JSON_UNESCAPED_UNICODE));
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return null;
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}
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logMessage("✅ Файл успешно загружен в OpenAI (ID: " . $decoded['id'] . ")");
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return $decoded['id'];
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}
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/*function uploadFileToOpenAI($filePath) {
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logMessage("Загрузка файла в OpenAI: $filePath");
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$curl = curl_init();
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curl_setopt_array($curl, [
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CURLOPT_URL => OPENAI_FILES_API,
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CURLOPT_RETURNTRANSFER => true,
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CURLOPT_POST => true,
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CURLOPT_POSTFIELDS => [
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'file' => new CURLFile($filePath),
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'purpose' => 'assistants'
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],
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CURLOPT_HTTPHEADER => [
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'Authorization: Bearer ' . OPENAI_API_KEY,
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'OpenAI-Beta: assistants=v2'
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]
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]);
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$response = curl_exec($curl);
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$httpCode = curl_getinfo($curl, CURLINFO_HTTP_CODE);
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$curlError = curl_error($curl);
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curl_close($curl);
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logMessage("Ответ OpenAI (загрузка файла): HTTP $httpCode - " . $response);
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if ($curlError) {
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logMessage("Ошибка cURL при загрузке файла: " . $curlError);
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return null;
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}
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$decoded = json_decode($response, true);
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if ($httpCode !== 200 || !isset($decoded['id'])) {
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logMessage("Ошибка при загрузке файла: " . json_encode($decoded, JSON_UNESCAPED_UNICODE));
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return null;
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}
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return $decoded['id'];
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}
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*/
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function addFileToVectorStore($vectorStoreId, $fileId) {
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$curl = curl_init();
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$payload = json_encode(['file_id' => $fileId]);
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logMessage("Добавление файла в Vector Store. Payload: " . $payload);
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curl_setopt_array($curl, [
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CURLOPT_URL => OPENAI_VECTOR_STORES_API . "/$vectorStoreId/files",
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CURLOPT_RETURNTRANSFER => true,
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CURLOPT_POST => true,
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CURLOPT_POSTFIELDS => $payload,
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CURLOPT_HTTPHEADER => [
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'Content-Type: application/json',
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'Authorization: Bearer ' . OPENAI_API_KEY,
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'OpenAI-Beta: assistants=v2'
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]
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]);
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$response = curl_exec($curl);
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$httpCode = curl_getinfo($curl, CURLINFO_HTTP_CODE);
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$curlError = curl_error($curl);
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curl_close($curl);
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logMessage("Ответ OpenAI (добавление файла): HTTP $httpCode - " . $response);
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if ($curlError) {
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logMessage("Ошибка cURL при добавлении файла в Vector Store: " . $curlError);
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return false;
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}
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$decoded = json_decode($response, true);
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if ($httpCode !== 200 || !isset($decoded['id'])) {
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logMessage("Ошибка добавления файла: " . json_encode($decoded, JSON_UNESCAPED_UNICODE));
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return false;
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}
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return true;
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}
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function updateAssistantWithVectorStore($vectorStoreId) {
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$data = [
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'tool_resources' => [
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'file_search' => [
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'vector_store_ids' => [$vectorStoreId]
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]
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]
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];
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$curl = curl_init();
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$payload = json_encode($data);
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logMessage("Обновление ассистента. Payload: " . $payload);
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curl_setopt_array($curl, [
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CURLOPT_URL => OPENAI_ASSISTANT_API . "/" . ASSISTANT_ID,
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CURLOPT_RETURNTRANSFER => true,
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CURLOPT_CUSTOMREQUEST => 'POST',
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CURLOPT_POSTFIELDS => $payload,
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CURLOPT_HTTPHEADER => [
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'Content-Type: application/json',
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'Authorization: Bearer ' . OPENAI_API_KEY,
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'OpenAI-Beta: assistants=v2'
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]
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]);
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$response = curl_exec($curl);
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$httpCode = curl_getinfo($curl, CURLINFO_HTTP_CODE);
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$curlError = curl_error($curl);
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curl_close($curl);
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logMessage("Ответ OpenAI (обновление ассистента): HTTP $httpCode - " . $response);
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if ($curlError) {
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logMessage("Ошибка обновления ассистента: " . $curlError);
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return false;
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}
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$decoded = json_decode($response, true);
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if ($httpCode !== 200 || !isset($decoded['id'])) {
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logMessage("Ошибка обновления ассистента: " . json_encode($decoded, JSON_UNESCAPED_UNICODE));
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return false;
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}
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return true;
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}
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function getTextEmbedding($text) {
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$command = "sudo -u fastuser /var/www/laws/legal/bin/python3 /var/www/laws/legal/vectorize.py";
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$descriptors = [
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0 => ["pipe", "r"], // stdin (передаем текст)
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1 => ["pipe", "w"], // stdout (читаем результат)
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2 => ["pipe", "w"] // stderr (читаем ошибки)
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];
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// Логируем команду перед её выполнением
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file_put_contents(__DIR__ . '/logs/vectorizer_debug.log',
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date('Y-m-d H:i:s') . " - Executing command: $command\n", FILE_APPEND);
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$process = proc_open($command, $descriptors, $pipes);
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if (!is_resource($process)) {
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error_log("Ошибка запуска Python через proc_open: $command");
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return [
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"embedding_1024" => array_fill(0, 1024, 0.001),
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"embedding_2048" => array_fill(0, 2048, 0.001)
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];
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}
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// Передаем текст в stdin
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fwrite($pipes[0], $text);
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fclose($pipes[0]);
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// Читаем результат из stdout
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$output = stream_get_contents($pipes[1]);
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fclose($pipes[1]);
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// Читаем stderr (ошибки)
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$errorOutput = stream_get_contents($pipes[2]);
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fclose($pipes[2]);
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proc_close($process);
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// Логируем результат выполнения Python
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file_put_contents(__DIR__ . '/logs/vectorizer_debug.log',
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date('Y-m-d H:i:s') . " - Raw output: " . $output . "\n", FILE_APPEND);
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if (!empty($errorOutput)) {
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file_put_contents(__DIR__ . '/logs/vectorizer_debug.log',
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date('Y-m-d H:i:s') . " - Python error: " . $errorOutput . "\n", FILE_APPEND);
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return [
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"embedding_1024" => array_fill(0, 1024, 0.001),
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"embedding_2048" => array_fill(0, 2048, 0.001)
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];
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}
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$decoded = json_decode($output, true);
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return [
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"embedding_1024" => $decoded["embedding_1024"] ?? array_fill(0, 1024, 0.001),
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"embedding_2048" => $decoded["embedding_2048"] ?? array_fill(0, 2048, 0.001)
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];
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}
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function logVectorStoreFiles($vectorStoreId) {
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$url = OPENAI_VECTOR_STORES_API . '/' . $vectorStoreId . '/files';
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$ch = curl_init();
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curl_setopt_array($ch, [
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CURLOPT_URL => $url,
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CURLOPT_RETURNTRANSFER => true,
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CURLOPT_HTTPHEADER => [
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"Content-Type: application/json",
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"Authorization: Bearer " . OPENAI_API_KEY,
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"OpenAI-Beta: assistants=v2" // добавляем заголовок для использования Assistants v2
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]
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]);
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$response = curl_exec($ch);
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// Проверка ошибок cURL
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if (curl_errno($ch)) {
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logMessage("❌ Ошибка cURL: " . curl_error($ch));
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curl_close($ch);
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return;
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}
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curl_close($ch);
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// Проверка на ошибки декодирования JSON
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$data = json_decode($response, true);
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if (json_last_error() !== JSON_ERROR_NONE) {
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logMessage("❌ Ошибка при декодировании JSON: " . json_last_error_msg());
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return;
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}
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// Проверка, что данные о файлах действительно получены
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if (isset($data['data'])) {
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logMessage("📦 Содержимое Vector Store ($vectorStoreId):");
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// Логируем данные по каждому файлу в Vector Store
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foreach ($data['data'] as $file) {
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$id = $file['id'] ?? '???';
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$filename = $file['filename'] ?? 'без имени';
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$bytes = $file['bytes'] ?? 0;
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$status = $file['status'] ?? 'неизвестно';
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// Логируем информацию о файле
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logMessage("📄 [$id] $filename | Статус: $status | Размер: " . round($bytes / 1024, 1) . " КБ");
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// Если файл проиндексирован, извлекаем первые 400 символов текста
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if ($status === 'completed') {
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$text = extractTextFromFile($filename); // извлекаем текст из файла
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$fragment = mb_substr($text, 0, 400, 'UTF-8');
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logMessage("📜 Фрагмент из $filename: $fragment...");
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} else {
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logMessage("⚠️ Файл не проиндексирован или текст не доступен: $filename");
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}
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}
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} else {
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logMessage("❌ Не удалось получить файлы из Vector Store ID: $vectorStoreId");
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}
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}
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function checkFileStatus($vectorStoreId) {
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// $url = "https://api.proxyapi.ru/openai/v1/vector_stores/$vectorStoreId/files";
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$url = OPENAI_VECTOR_STORES_API . '/' . $vectorStoreId . '/files';
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$ch = curl_init();
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curl_setopt_array($ch, [
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CURLOPT_URL => $url,
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CURLOPT_RETURNTRANSFER => true,
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CURLOPT_HTTPHEADER => [
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"Content-Type: application/json",
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"Authorization: Bearer " . OPENAI_API_KEY,
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"OpenAI-Beta: assistants=v2" // Этот заголовок нужно добавить!
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]
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]);
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$response = curl_exec($ch);
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curl_close($ch);
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$data = json_decode($response, true);
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if (isset($data['data'])) {
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foreach ($data['data'] as $file) {
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$id = $file['id'] ?? '???';
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$filename = $file['filename'] ?? 'без имени';
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$status = $file['status'] ?? 'неизвестно';
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logMessage("📄 Файл: $filename | Статус: $status");
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}
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} else {
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logMessage("❌ Ошибка при получении статуса файлов из Vector Store.");
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}
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}
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/*
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function getTextEmbedding($text) {
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$command = "sudo -u fastuser /var/www/laws/legal/bin/python3 /var/www/laws/legal/vectorize.py";
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$descriptors = [
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0 => ["pipe", "r"],
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1 => ["pipe", "w"],
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2 => ["pipe", "w"]
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];
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$process = proc_open($command, $descriptors, $pipes);
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if (!is_resource($process)) {
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error_log("Ошибка запуска Python через proc_open: $command");
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return [
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"embedding_1024" => array_fill(0, 1024, 0.001),
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"embedding_2048" => array_fill(0, 2048, 0.001)
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];
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}
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fwrite($pipes[0], $text);
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fclose($pipes[0]);
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$output = stream_get_contents($pipes[1]);
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fclose($pipes[1]);
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$errorOutput = stream_get_contents($pipes[2]);
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fclose($pipes[2]);
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proc_close($process);
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file_put_contents(__DIR__ . '/logs/vectorizer.log',
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date('Y-m-d H:i:s') . " - Raw output: " . $output . "\n", FILE_APPEND);
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if (!empty($errorOutput)) {
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error_log("Ошибка Python: " . $errorOutput);
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return [
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"embedding_1024" => array_fill(0, 1024, 0.001),
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"embedding_2048" => array_fill(0, 2048, 0.001)
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];
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}
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$decoded = json_decode($output, true);
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return [
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"embedding_1024" => $decoded["embedding_1024"] ?? array_fill(0, 1024, 0.001),
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"embedding_2048" => $decoded["embedding_2048"] ?? array_fill(0, 2048, 0.001)
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];
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}*/
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?>
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