Streamlit Chatbot with OpenAI, FAISS, & Langchain 🦜️🔗

This repository contains a Streamlit application for a chatbot that utilizes OpenAI's language model, FAISS for document retrieval, and Langchain for managing conversation chains. The chatbot engages in conversations and retrieves relevant documents based on the user's input.

Features

• OpenAI Language Model: Provides natural language understanding and generation.
• FAISS for Document Retrieval: Efficiently retrieves relevant documents based on user queries.
• Langchain for Conversation Management: Manages conversation chains with memory capabilities.
• Conversation History: Maintains conversation history within the session.
• Customizable UI: Includes custom CSS for enhanced user experience.

Setup

Prerequisites

• Python 3.11+
• Streamlit
• OpenAI API key
• LangChain
• FAISS library

Installation

1. Clone the repository:

   git clone https://github.com/arnabsaha7/Chatbot-with-LLM_RAG.git
   cd Chatbot-with-LLM_RAG

2. Install the required packages:

   pip install -r requirements.txt

3. Set up your OpenAI API key:

   Replace the placeholder API key in the code with your actual OpenAI API key.

   os.environ["OPENAI_API_KEY"] = "your-openai-api-key"

4. Prepare the FAISS index and documents:

   Ensure you have the FAISS index (faiss_index_1) and documents file (documents.json) in the project directory.

Running the Application

1. Start the Streamlit app:

   streamlit run app.py

2. Open your browser:

   The application will be available at http://localhost:8501.

Usage

• Welcome Screen: The app starts with a welcome screen. You can begin interacting with the chatbot by typing your message in the input box.

• Conversation History: The conversation history is displayed on the screen. User messages are shown in one style, while the bot's responses are shown in another.

• Document Retrieval: When you send a message, the chatbot retrieves relevant documents from the FAISS index and uses them to provide a more informed response.

• Reset Conversation: Use the "Reset Conversation" button to clear the conversation history and start a new session.

File Structure

• Chatbot.py --> The main Streamlit application file.
• requirements.txt --> Lists all Python dependencies.
• faiss_index_1 --> The FAISS index file.
• documents.json --> JSON file containing documents with metadata.
• styles.css --> Custom CSS for styling the app.

Acknowledgements

• OpenAI
• FAISS
• Streamlit
• Langchain

Contributing

Contributions are welcome! Please open an issue or submit a pull request.

Contact

For any questions or inquiries, please contact Email.