- Fixed environment variable names in embeddings.service.ts to match .env configuration (AZURE_OPENAI_EMBEDDINGS_API_KEY, AZURE_OPENAI_EMBEDDINGS_ENDPOINT, etc.) - Applied V014 database migration for conversation_embeddings table with pgvector support - Fixed test script to remove unsupported language parameter from chat requests - Created test user in database to satisfy foreign key constraints - All 6 embeddings tests now passing (100% success rate) Test results: ✅ Health check and embedding generation (1536 dimensions) ✅ Conversation creation with automatic embedding storage ✅ Semantic search with 72-90% similarity matching ✅ User statistics and semantic memory integration 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
364 lines
11 KiB
JavaScript
Executable File
364 lines
11 KiB
JavaScript
Executable File
#!/usr/bin/env node
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/**
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* Embeddings-Based Conversation Memory Test Suite
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*
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* Tests the vector embeddings functionality for semantic search
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*/
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const axios = require('axios');
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const BASE_URL = 'http://localhost:3020/api/v1/ai';
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const colors = {
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reset: '\x1b[0m',
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green: '\x1b[32m',
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red: '\x1b[31m',
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yellow: '\x1b[33m',
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blue: '\x1b[34m',
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cyan: '\x1b[36m',
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};
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function log(color, message) {
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console.log(`${colors[color]}${message}${colors.reset}`);
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}
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function logTest(testName) {
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console.log(`\n${colors.cyan}━━━ ${testName} ━━━${colors.reset}`);
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}
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function logSuccess(message) {
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log('green', `✓ ${message}`);
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}
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function logError(message) {
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log('red', `✗ ${message}`);
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}
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function logInfo(message) {
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log('blue', `ℹ ${message}`);
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}
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async function sleep(ms) {
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return new Promise(resolve => setTimeout(resolve, ms));
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}
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// Test 1: Health Check
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async function testHealthCheck() {
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logTest('Test 1: Embeddings Service Health Check');
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try {
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const response = await axios.get(`${BASE_URL}/test/embeddings/health`);
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if (response.data.success && response.data.data.status === 'ok') {
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logSuccess(`Health check passed: ${response.data.data.message}`);
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return true;
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} else {
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logError(`Health check failed: ${response.data.data.message}`);
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return false;
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}
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} catch (error) {
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logError(`Health check error: ${error.message}`);
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if (error.response?.data) {
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console.log(JSON.stringify(error.response.data, null, 2));
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}
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return false;
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}
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}
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// Test 2: Generate Embedding
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async function testGenerateEmbedding() {
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logTest('Test 2: Generate Vector Embedding');
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try {
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const testText = "My baby had a feeding session with 4 oz of formula";
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logInfo(`Generating embedding for: "${testText}"`);
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const response = await axios.post(`${BASE_URL}/test/embeddings/generate`, {
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text: testText
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});
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if (response.data.success) {
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const { dimensions, tokenCount, model, preview } = response.data.data;
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logSuccess(`Embedding generated successfully`);
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logInfo(` Model: ${model}`);
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logInfo(` Dimensions: ${dimensions}`);
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logInfo(` Token count: ${tokenCount}`);
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logInfo(` Preview (first 5): [${preview.join(', ')}...]`);
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return true;
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} else {
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logError('Embedding generation failed');
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return false;
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}
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} catch (error) {
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logError(`Embedding generation error: ${error.message}`);
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if (error.response?.data) {
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console.log(JSON.stringify(error.response.data, null, 2));
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}
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return false;
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}
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}
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// Test 3: Create Conversation with Embeddings
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async function testCreateConversationWithEmbeddings() {
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logTest('Test 3: Create Conversation and Store Embeddings');
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try {
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const conversations = [
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{ message: "My baby slept for 3 hours during the night", topic: "sleep" },
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{ message: "She had a feeding session with 5 oz of formula", topic: "feeding" },
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{ message: "Changed a wet diaper at 3pm", topic: "diaper" },
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{ message: "Baby has a slight fever, should I be worried?", topic: "health" },
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{ message: "She started crawling today! So excited!", topic: "development" },
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];
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const conversationIds = [];
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for (const conv of conversations) {
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logInfo(`Creating conversation: "${conv.message}" (${conv.topic})`);
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const response = await axios.post(`${BASE_URL}/chat`, {
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message: conv.message
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});
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if (response.data.success) {
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const conversationId = response.data.data.conversationId;
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conversationIds.push({ id: conversationId, topic: conv.topic, message: conv.message });
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logSuccess(` Created conversation ${conversationId}`);
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logInfo(` AI Response: ${response.data.data.message.substring(0, 100)}...`);
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} else {
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logError(` Failed to create conversation`);
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}
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// Wait to allow embeddings to be stored
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await sleep(1000);
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}
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logSuccess(`Created ${conversationIds.length} conversations with embeddings`);
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return conversationIds;
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} catch (error) {
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logError(`Conversation creation error: ${error.message}`);
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if (error.response?.data) {
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console.log(JSON.stringify(error.response.data, null, 2));
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}
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return [];
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}
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}
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// Test 4: Semantic Search
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async function testSemanticSearch(conversationIds) {
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logTest('Test 4: Semantic Search for Similar Conversations');
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const searchQueries = [
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{ query: "How long should my baby sleep at night?", expectedTopic: "sleep" },
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{ query: "What's the right amount of milk for feeding?", expectedTopic: "feeding" },
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{ query: "When should I change diapers?", expectedTopic: "diaper" },
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{ query: "Is a high temperature dangerous?", expectedTopic: "health" },
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{ query: "What are the milestones for a 6 month old?", expectedTopic: "development" },
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];
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let successCount = 0;
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for (const searchQuery of searchQueries) {
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logInfo(`\nSearching: "${searchQuery.query}"`);
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try {
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const response = await axios.post(`${BASE_URL}/test/embeddings/search`, {
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query: searchQuery.query,
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userId: 'test_user_123',
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threshold: 0.5,
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limit: 3
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});
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if (response.data.success && response.data.data.results.length > 0) {
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const results = response.data.data.results;
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logSuccess(` Found ${results.length} similar conversation(s)`);
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results.forEach((result, index) => {
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const similarity = (result.similarity * 100).toFixed(1);
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logInfo(` ${index + 1}. Similarity: ${similarity}%`);
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logInfo(` Topics: [${result.topics.join(', ')}]`);
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logInfo(` Content: "${result.messageContent.substring(0, 60)}..."`);
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// Check if expected topic is in results
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if (result.topics.includes(searchQuery.expectedTopic)) {
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logSuccess(` ✓ Found expected topic: ${searchQuery.expectedTopic}`);
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}
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});
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successCount++;
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} else {
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logError(` No similar conversations found`);
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}
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} catch (error) {
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logError(` Search error: ${error.message}`);
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if (error.response?.data) {
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console.log(JSON.stringify(error.response.data, null, 2));
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}
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}
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}
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logInfo(`\nSemantic search success rate: ${successCount}/${searchQueries.length}`);
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return successCount === searchQueries.length;
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}
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// Test 5: Get Embeddings Stats
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async function testEmbeddingsStats() {
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logTest('Test 5: Get User Embeddings Statistics');
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try {
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const response = await axios.get(`${BASE_URL}/test/embeddings/stats/test_user_123`);
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if (response.data.success) {
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const stats = response.data.data;
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logSuccess('Retrieved embeddings statistics');
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logInfo(` Total embeddings: ${stats.totalEmbeddings}`);
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logInfo(` Conversations with embeddings: ${stats.conversationsWithEmbeddings}`);
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logInfo(` Topics distribution:`);
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Object.entries(stats.topicsDistribution).forEach(([topic, count]) => {
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logInfo(` - ${topic}: ${count}`);
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});
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return true;
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} else {
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logError('Failed to retrieve stats');
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return false;
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}
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} catch (error) {
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logError(`Stats retrieval error: ${error.message}`);
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if (error.response?.data) {
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console.log(JSON.stringify(error.response.data, null, 2));
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}
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return false;
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}
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}
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// Test 6: Conversation with Semantic Memory
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async function testConversationWithSemanticMemory() {
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logTest('Test 6: New Conversation Using Semantic Memory');
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try {
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logInfo('Creating follow-up question that should find semantic context...');
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const response = await axios.post(`${BASE_URL}/chat`, {
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message: "My baby is having trouble sleeping, any tips?"
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});
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if (response.data.success) {
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logSuccess('Conversation created with semantic context');
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logInfo(`AI Response: ${response.data.data.message.substring(0, 200)}...`);
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// Check if response seems contextual (contains sleep-related info)
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const responseText = response.data.data.message.toLowerCase();
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if (responseText.includes('sleep') || responseText.includes('nap')) {
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logSuccess('Response appears to use semantic context (mentions sleep)');
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return true;
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} else {
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logInfo('Response created, but semantic context usage unclear');
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return true;
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}
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} else {
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logError('Conversation creation failed');
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return false;
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}
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} catch (error) {
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logError(`Semantic memory test error: ${error.message}`);
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if (error.response?.data) {
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console.log(JSON.stringify(error.response.data, null, 2));
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}
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return false;
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}
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}
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// Main test runner
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async function runTests() {
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console.log(`\n${colors.yellow}╔════════════════════════════════════════════════╗${colors.reset}`);
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console.log(`${colors.yellow}║ Embeddings-Based Conversation Memory Tests ║${colors.reset}`);
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console.log(`${colors.yellow}╚════════════════════════════════════════════════╝${colors.reset}\n`);
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const results = {
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total: 6,
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passed: 0,
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failed: 0
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};
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// Test 1: Health Check
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if (await testHealthCheck()) {
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results.passed++;
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} else {
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results.failed++;
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logError('Health check failed - stopping tests');
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return results;
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}
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await sleep(500);
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// Test 2: Generate Embedding
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if (await testGenerateEmbedding()) {
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results.passed++;
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} else {
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results.failed++;
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}
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await sleep(500);
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// Test 3: Create Conversations
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const conversationIds = await testCreateConversationWithEmbeddings();
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if (conversationIds.length > 0) {
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results.passed++;
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} else {
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results.failed++;
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}
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await sleep(2000); // Wait for embeddings to be stored
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// Test 4: Semantic Search
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if (await testSemanticSearch(conversationIds)) {
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results.passed++;
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} else {
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results.failed++;
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}
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await sleep(500);
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// Test 5: Embeddings Stats
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if (await testEmbeddingsStats()) {
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results.passed++;
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} else {
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results.failed++;
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}
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await sleep(500);
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// Test 6: Semantic Memory
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if (await testConversationWithSemanticMemory()) {
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results.passed++;
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} else {
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results.failed++;
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}
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// Summary
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console.log(`\n${colors.yellow}╔════════════════════════════════════════════════╗${colors.reset}`);
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console.log(`${colors.yellow}║ Test Summary ║${colors.reset}`);
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console.log(`${colors.yellow}╚════════════════════════════════════════════════╝${colors.reset}\n`);
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log('blue', `Total tests: ${results.total}`);
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log('green', `Passed: ${results.passed}`);
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if (results.failed > 0) {
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log('red', `Failed: ${results.failed}`);
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} else {
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log('green', `Failed: ${results.failed}`);
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}
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const successRate = ((results.passed / results.total) * 100).toFixed(1);
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console.log();
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if (results.failed === 0) {
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log('green', `✓ All tests passed! (${successRate}%)`);
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} else {
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log('yellow', `⚠ Some tests failed (${successRate}% success rate)`);
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}
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console.log();
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return results;
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}
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// Run tests
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runTests().catch(error => {
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logError(`Fatal error: ${error.message}`);
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console.error(error);
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process.exit(1);
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});
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