Nebula Chatbot

Description

This project is an AI chatbot application built using Streamlit. It leverages OpenAI's GPT-4o-mini model to provide intelligent and context-aware responses. The application supports multiple chat sessions and allows users to input their OpenAI API key for personalized interactions.

Features

• Multiple chat sessions management
• User-friendly interface with Streamlit
• Secure API key input
• Context-aware responses using GPT-4o-mini

Libraries and Tools Used

• LangChain
• Streamlit
• OpenAI GPT-4o-mini
• python-dotenv

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/ai-chatbot.git
   cd ai-chatbot

2. Create a virtual enviorment:

   python -m venv venv

3. Activate the virtual enviorment:

   venv/Scripts/activate

4. Install the required packages:

   pip install -r requirements.txt

5. Create a .env file in the root directory and add your OpenAI API key and Langchain API key:

   OPENAI_API_KEY=your_openai_api_key
   LANGCHAIN_API_KEY=your_langchain_api_key

Running the Project

To run the application, use the following command:

streamlit run src/app.py

Modules and Components

• config.py: Manages configuration settings and environment variables.
• session_manager.py: Handles session management and chat history.
• chatbot.py: Implements the core chatbot functionality using LangChain components.
• app.py: Main Streamlit application file that coordinates between different components.

Folder Structure

• /script: Contains just the script for running the chatbot without ui with explanation on how everythin works. It is exactly the same as I write while creating it without ui for instructions and any related references.
• /src: Contains the main application files.
  • config.py: Configuration management.
  • session_manager.py: Session management.
  • chatbot.py: Chatbot logic.
  • app.py: Streamlit application.

Contributing

Contributions are welcome! Please follow these steps:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Make your changes.
4. Commit your changes (git commit -m 'Add new feature').
5. Push to the branch (git push origin feature-branch).
6. Open a pull request.

License

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