{"library":"llama-index-vector-stores-neo4jvector","type":"library","category":null,"description":"The `llama-index-vector-stores-neo4jvector` library provides an integration for LlamaIndex to use Neo4j as a vector store. It enables storing, indexing, and querying of document embeddings within a Neo4j graph database, supporting operations like vector search, hybrid search, and metadata filtering. The current version is 0.6.0, and it maintains an active development and release cadence within the LlamaIndex ecosystem.","language":"python","status":"active","version":"0.6.0","tags":["LlamaIndex","Neo4j","Vector Store","LLM","RAG","Graph Database"],"last_verified":"Mon May 25","install":[{"cmd":"pip install llama-index-vector-stores-neo4jvector llama-index-llms-openai llama-index-embeddings-openai neo4j","imports":["from llama_index.vector_stores.neo4jvector import Neo4jVectorStore","from llama_index.core import VectorStoreIndex"]}],"homepage":"https://neo4j.com/product/neo4j-graph-database/","github":null,"docs":null,"changelog":null,"pypi":"https://pypi.org/project/llama-index-vector-stores-neo4jvector/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":100,"avg_install_s":20.5,"avg_import_s":6.19,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/llama-index-vector-stores-neo4jvector/compatibility"}}