M.I.M.I.R - Multi-agent Intelligent Memory & Insight Repository

#!/usr/bin/env node /** * Drop and recreate vector index with correct dimensions */ import neo4j from 'neo4j-driver'; import { LLMConfigLoader } from '../build/config/LLMConfigLoader.js'; async function dropVectorIndex() { const driver = neo4j.driver( 'bolt://localhost:7687', neo4j.auth.basic('neo4j', 'password') ); const session = driver.session(); try { console.log('🗑️ Dropping existing vector index...'); await session.run('DROP INDEX node_embedding_index IF EXISTS'); console.log('✅ Vector index dropped'); // Get correct dimensions from env var or default to 768 const dimensions = parseInt(process.env.MIMIR_EMBEDDINGS_DIMENSIONS || '768', 10); console.log(`🔧 MIMIR_EMBEDDINGS_DIMENSIONS env var: ${process.env.MIMIR_EMBEDDINGS_DIMENSIONS}`); console.log(`🔧 Creating vector index with ${dimensions} dimensions...`); await session.run(` CREATE VECTOR INDEX node_embedding_index IF NOT EXISTS FOR (n:Node) ON (n.embedding) OPTIONS {indexConfig: { \`vector.dimensions\`: ${dimensions}, \`vector.similarity_function\`: 'cosine' }} `); console.log('✅ Vector index created successfully'); } catch (error) { console.error('❌ Error:', error.message); throw error; } finally { await session.close(); await driver.close(); } } dropVectorIndex() .then(() => { console.log('✅ Done!'); process.exit(0); }) .catch((error) => { console.error('❌ Failed:', error); process.exit(1); });