AI Rag Agent
Period: May, 2025 - ∞
About this project
- •Developed a Retrieval-Augmented Generation (RAG) AI agent using LangChain to enable efficient querying of legal
- •documents and research papers.
- •Implemented parsing and chunking of PDF and TXT files to optimize document retrieval processes.
- •Utilized in-memory storage solutions to ensure fast access to document chunks during query processing.
- •Implemented query handling and answer generation to deliver accurate, contextually relevant responses based
- •solely on uploaded document content.
Key Features
- PDFand TXT document parsing and processing
- Intelligentdocument chunking for optimized retrieval
- In-memorystorage for fast query access
- RAG-basedcontextual question answering
- Supportfor legal documents and research papers
- Accurateresponses based solely on uploaded content
Technologies Used
PythonLangChainPyPDF2OpenAI