This web app is a customized Retrieval-Augmented Generation (RAG) chatbot built using Langchain, Python, and React. The chatbot provides detailed information and assistance based on a curated knowledge base. (Will be deployed soon, currently debugging deployment errors.)
- Information Retrieval: The chatbot retrieves relevant information from a curated knowledge base. Currently using LangChain (will be setting up a custom pipeline instead)
- Conversational AI: Utilizes OpenAI's GPT model to generate human-like responses.
- Customizable Responses: Designed to handle specific queries and provide informative answers.
- Responsive Design: The user interface is optimized for various devices, ensuring a seamless user experience.
To set up the project locally, follow these steps:
-
Clone the repository:
git clone https://github.com/your-username/rag-chatbot.git cd rag-chatbot -
Install Python dependencies: Make sure you have Python installed, then run:
pip install -r requirements.txt
-
Install Node.js dependencies: Navigate to the
chatbot-uidirectory and install the Node.js dependencies:cd chatbot-ui npm install -
Run the development server: Start the server using:
npm run dev
-
Open the application: Open your browser and go to http://localhost:3000 to see the result.
- Langchain: For building and managing the knowledge base and handling document retrieval.
- OpenAI GPT: To generate conversational responses.
- Python: The core programming language used for developing the backend.
- Next.js: A React framework for building the frontend.
- Axios: For making HTTP requests from the frontend.
- Tailwind CSS: For styling the user interface.
- Heroku: Hosting platform for deploying the web app.
This project is licensed under the MIT License - see the LICENSE file for details.
For any questions or feedback, please reach out to the project maintainers.
Thank you for using the RAG Chatbot! I hope you find it helpful and informative.