A document based RAG application
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Updated
Mar 28, 2025 - Rust
A document based RAG application
Scalable Qdrant vector database cluster with Docker Compose, monitoring, and comprehensive documentation for high-performance similarity search applications.
RAG-Ingest: A tool for converting PDFs to markdown and indexing them for enhanced Retrieval Augmented Generation (RAG) capabilities.
This is a RAG (Retrieval-Augmented Generation) model that leverages Qdrant as a vector store and Google Gemini for intelligent document retrieval and context-aware response generation. It efficiently processes PDF documents to provide detailed answers to user queries based on the extracted context.
A tool for collecting and vectorizing technical content from multiple sources and storing it in a QDrant vector database.
Demonstration on how to implement storage and search for JSON structured data
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