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RAG HCSRL
Builds a comprehensive Retrieval-Augmented Generation (RAG) system with a local vector database for AI assistant integration.
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This system provides a complete Retrieval-Augmented Generation (RAG) solution, enabling users to ingest PDF documents, generate vector embeddings, and perform semantic queries using natural language. It integrates seamlessly with popular AI assistants like Claude, ChatGPT, and Gemini via the Model Context Protocol (MCP), exposing a local vector database through standardized API tools. Designed for local storage and fast performance, it offers an easy setup to enhance AI assistant capabilities with custom document collections.
Database Management
API Development
Data Science & ML
