/Rag-chatbot

AI application that utilizes LLP to provide users with relevant information and responses.

Primary LanguageJavaScriptMIT LicenseMIT

RAG Chatbot

ollama ChromaDB 🦜🔗 LangChain Flask

Overview

The RAG Chatbot is a conversational AI application that utilizes LLM to provide users with relevant information and responses.

Components

  • query.py: Contains the Python script responsible for querying the RAG model and generating responses.

  • populate_db.py: A Python script used to populate the database with relevant data and sources.

  • web.py: The Flask web framework code that handles HTTP requests and serves as the backend for the chatbot's interface.

  • index.html: The HTML template for the chatbot's user interface.

  • index.js: A JavaScript file that contains the client-side logic.

Features

  • The chatbot responds with relevant information and sources, which are displayed below the input field.

  • Users can view detailed information about each source by hovering over the source card.

  • The chatbot also supports uploading files through web interface.

Screenshots

Asking the question Мiew source information

Getting Started

  1. Clone this repository using git clone https://github.com/AaLexUser/Rag-chatbot.git

  2. Install dependencies by running pip install -r requirements.txt in the project root directory.

  3. Run the Flask application using python web.py to start the chatbot's backend.

  4. Open a web browser and navigate to http://localhost:5000/ to access the chatbot's interface.

License

This project is licensed under the MIT License. See LICENSE for details.