Enables local RAG systems by registering diverse document formats for advanced search capabilities through an MCP server.
This Docker Compose-based backend provides a comprehensive RAG (Retrieval-Augmented Generation) system for local environments. It supports the ingestion of documents in 28 different file formats using `unstructured`, creating a rich knowledge base. Leveraging `graphiti` and a `Neo4j` database, it offers sophisticated search capabilities combining vector, graph, and full-text search, with results intelligently reranked based on relevance. A unique feature is its ability to track changes in conceptual relationships within documents over time through `graphiti`'s episode functionality, making it ideal for evolving knowledge domains accessible via an MCP server.