Skip to content

Repository files navigation

Mini-DocBot

Overview

A lightweight Retrieval-Augmented Generation (RAG) chatbot for document-based question answering. Mini-DocBot processes PDF documents, converts content into vector embeddings using FAISS, and generates context-aware responses using Google's Gemini 1.5 Flash model.

Features

  • Document-based Q&A through RAG architecture
  • PDF processing and intelligent knowledge retrieval
  • Interactive interface via Streamlit

Demo

Try it live: mini-docbot.streamlit.app

Requirements

  • streamlit - Web application framework
  • google-generativeai - Google Gemini API access
  • langchain & langchain_google_genai - LLM framework integration
  • langchain-community - Additional LangChain components
  • PyPDF2 - PDF document processing
  • chromadb - Vector database for document storage
  • faiss-cpu - Vector similarity search library
  • streamlit secrets - Environment variable management

About

A lightweight Retrieval-Augmented Generation (RAG) chatbot that processes PDFs, converts them into vector embeddings using FAISS, and leverages the Gemini 1.5 Flash 8B model via API for intelligent and context-aware responses. Ideal for document-based Q&A and smart knowledge retrieval.

Resources

Stars

0 stars

Watchers

1 watching

Forks

Releases

Packages

Used by

Contributors

Languages