61 Lines of Code: Build Your Own AI-Powered Document Chatbot in Minutes with Simple Vanilla RAG!
Ever wished you could ask a chatbot questions about any research paper or document? Now you can, with our simple Retrieval Augmented Generation (RAG) framework!
This project leverages Gradio, LangChain, and Chroma-based vector databases to help you easily load, split, and search through PDFs for accurate, context-aware answers.
Key Features:
Document Loader: Effortlessly load PDFs for analysis.
Text Splitting: Efficiently chunk documents for better processing.
Vector Store: Powered by HuggingFaceEmbeddings for accurate retrieval.
Retrieval-Based Question Answering: Get contextually relevant responses.
Gradio Interface: Simple and user-friendly interface for querying.
Perfect For:
Answering questions about AI research papers.
Customizing Q&A systems for any document type.
Check it out and start building your own custom document chatbot today!
Check the repo link in the comment below!
https://github.com/mayur-ml/Simple-Retrieval-Augmented-Generation-RAG-
