Doctor Assist using crewAI

This project leverages advanced AI agents to assist doctors in diagnosing medical conditions and recommending treatment plans based on patient-reported symptoms and medical history. The solution uses Streamlit for the user interface and crewAI library to define and manage AI agents and tasks.

Features

• Symptom Analysis: Collects patient symptoms and medical history.
• Preliminary Diagnosis: Provides a preliminary diagnosis with a list of possible conditions.
• Treatment Recommendations: Offers detailed treatment plans tailored to individual patient needs.
• Document Generation: Generates a downloadable document with diagnosis and treatment recommendations.

Installation

1. Clone the repository:

git clone https://github.com/shaadclt/Doctor-Assist-crewAI.git
cd Doctor-Assist-crewAI

2. Create a virtual environment and activate it:

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

3. Install the dependencies:

pip install -r requirements.txt

4. Set up environment variables:

• Create a .env file in the project directory with the following content:

OPENAI_API_KEY=your_openai_api_key
SERPER_API_KEY=your_serper_api_key
GROQ_API_KEY=your_groq_api_key

Usage

1. Run the Streamlit app:

streamlit run app_openi.py or streamlit run app_groq.py

2. Use the application:

• Open the provided local URL in your web browser.
• Enter the patient's gender, age, symptoms, and medical history.
• Click the "Get Diagnosis and Treatment Plan" button.
• View and download the generated diagnosis and treatment plan.

Project Structure

• app.py: The main application script that defines the Streamlit UI and integrates the AI agents.
• requirements.txt: A list of required Python packages.
• .env: Environment variables for API keys (not included in the repository).

License

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

Contributing

Contributions are welcome! Please fork the repository and create a pull request with your changes.

Acknowledgements

• OpenAI for the powerful language models.
• Streamlit for the easy-to-use UI framework.
• CrewAI for the agent and task management tools.

Contact

For any questions or suggestions, please contact Mohamed Shaad at [email protected].