RAG-Ingest: A tool for converting PDFs to markdown and indexing them for enhanced Retrieval Augmented Generation (RAG) capabilities.
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Updated
Nov 22, 2024 - Python
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.
This is the Proof Of Concept/Demo for the Final Year Project of Pranav Krishnakumar. It is a Meal Planner using Agentic RAG powered by Qwen2.5 Coder 32B, Qdrant Vector Database, Mem0 Chat Memory and Smolagents library for the AI Agent
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