The application is containerized with Docker and uses uv for fast, optimized dependency management. It also includes an mcp-rag-service for integration with MCP (Model Context Protocol).
Formerly RAG-DuckDB-with-MCP. Engram is a local, sovereign hub that centralizes project reports outside their repos and makes them hybrid-searchable (RAG), with a recursive-reasoning (RLM) layer planned on top.
Features
Web Interface: Minimalist UI for uploading files, initiating processing, and performing searches.
JSON API: Provides /api/search, /api/stats, and /health endpoints for programmatic integration.
Wide File Support: Handles various file types including.txt,.md,.pdf, and multiple programming language source files (.py,.js,.java, etc.).
Advanced Chunking: Uses different strategies based on file type (e.g., CodeSplitter for source code, RecursiveCharacterTextSplitter for text).
High-Quality Embeddings: Uses sentence-transformers/paraphrase-multilingual-mpnet-base-v2 (primary, 768d) or sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 (fallback, 384d).
Vector Database: Leverages DuckDB with the VSS (Vector Similarity Search) extension for efficient storage and querying of embeddings.
Dockerized & Optimized:
MCP Integration: Includes a sample mcp-rag-service to demonstrate integration with external systems.
Directory Upload: Support for uploading entire directories with file extension filtering.
Health Monitoring: Built-in health check endpoint for monitoring and load balancers.
Details on this page are taken from the project's README. Open README
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