{"repo":"ErickWendel/neo4j-ai-experiments","free":true,"listed":false,"github":"https://github.com/ErickWendel/neo4j-ai-experiments","clone":"git clone https://github.com/ErickWendel/neo4j-ai-experiments.git","description":"Examples of my tutorial on how to use Neo4j for empowering AI RAG systems","language":"JavaScript","stars":78,"topics":["deepseek-coder","gemma-7b","javascript","langchain-js","langchain4j","neo4j","rag","retrieval-augmented-generation","similarity-search","vector-database"],"license":"MIT","category":"databases-storage","readme_excerpt":"Neo4j AI-Powered Query System Overview This project integrates Neo4j with AI models to generate Cypher queries from natural language prompts. It utilizes local AI models for natural language processing and a vector database approach for efficient querying. This is the source code shown on my video tutorial, consider watching it first! Folder Structure Setup Instructions Prerequisites Ensure you have the following installed: - Ollama for running local AI models - Docker for running Neo4j - Node.js (v22+ recommended) Installation Steps 1. Start Ollama 2. Download AI models 3. Start Neo4j 4. Install dependencies 5. Seed the database 6. Run the application 7. Test caching mechanism (Run twice to observe caching behavior) Features - AI-powered natural language to Cypher query conversion - Neo4j integration with vector search capabilities - RAG (Retrieval-Augmented Generation) example included - Database seeding for reproducible testing - Dockerized Neo4j instance Usage Once the application is running, you can send natural language queries to the AI, which will convert them into optimized Cypher queries for Neo4j. The system caches responses for better performance on repeated queries. Contributing Feel free to open issues and submit PRs for enhancements! License MIT License","default_branch":null,"files":null,"tree":[],"storefront":"/r/ErickWendel","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/ErickWendel/neo4j-ai-experiments/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}