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Football Injury Rehab Chatbot

This repository contains a simple chatbot designed to provide rehabilitation advice for football-related injuries using Google's Gemini API. The chatbot is built using Python and Streamlit, leveraging prompt engineering to tailor responses for football players seeking recovery and injury management guidance.

Features

  • Provides advice for football-related injuries such as recovery plans, exercises, and injury management.
  • Lightweight, interactive user interface built with Streamlit.
  • Utilizes prompt engineering to focus responses on football injury rehabilitation.
  • No history is stored to maintain a clean, stateless interaction for each question.

Prerequisites

Software Requirements

  • Python 3.8 or higher
  • Virtual environment tools (e.g., venv, conda)
  • Internet access to interact with the Gemini API

Libraries Used

  • streamlit for the user interface
  • google.generativeai for the Gemini API integration
  • python-dotenv for securely managing the API key

Installation and Setup

  1. Clone the Repository:

    git clone https://github.com/38832/Gemini-Bot.git
cd Gemini-Bot

  2. Set Up a Virtual Environment:

    python -m venv venv
source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

  3. Install Dependencies:

    pip install -r requirements.txt

  4. Configure the API Key:

    • Create a .env file in the root of the project.
    • Add the following line to the .env file, replacing <YOUR_API_KEY> with your Gemini API key: 
      GOOGLE_API_KEY=<YOUR_API_KEY>

Running the Application

  1. Start the Streamlit Server:

    streamlit run app.py

  2. Access the Application:

    • Open your browser and navigate to the URL provided by Streamlit (usually http://localhost:8501).

  3. Ask Questions:

    • Enter football injury-related questions, such as:
      • "What are the best recovery exercises for an ACL tear?"
      • "How do I manage a sprained ankle after football practice?"
      • "What stretches can I do for hamstring injuries?"

File Structure

Gemini-Bot/
├── app.py               # Main application file
├── requirements.txt     # Required Python libraries
├── .env.example         # Example file for API key configuration
├── README.md            # Project documentation
└── venv/                # Virtual environment (not included in the repo)

Customization

Prompt Engineering

The chatbot uses prompt engineering to tailor responses. You can modify the prompt in the get_gemini_response function within app.py to customize the chatbot’s behavior. For example:

football_prompt = (
    "You are a highly specialized rehabilitation assistant for football players. "
    "Provide detailed advice for recovery, rehabilitation exercises, and injury management. "
    "Question: " + question
)

Limitations

  • The chatbot does not store session history.
  • It depends on the Gemini API for all responses, so it requires an active API key and internet connection.
  • Responses are generated based on the model’s training and may not always be medically accurate. Always consult a professional for serious injuries.

Future Enhancements

  • Add session storage for user interactions.
  • Enable integration with external resources or databases for enhanced knowledge.
  • Fine-tune a custom model using specialized rehabilitation datasets.

License

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

Acknowledgments