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.

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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.

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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

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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>
     

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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?"

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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)

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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
)

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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.

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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.

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License

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

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Acknowledgments

• Google Gemini API
• Streamlit Documentation
• OpenAI for inspiring the use of large language models.