Streamcare is an prototype that aims to integrate AI to enhance primary care. It provides a platform for healthcare professionals to simulate medical scenarios, analyze medical conditions, and refine treatment plans using AI-generated insights.

• Installation
• Usage
• Configuration
• Features
• Directory Structure
• AI Model Integration

To get started with Streamcare, clone the repository and install the necessary dependencies:

    git clone https://github.com/AbisoyeOnanuga/streamcare.git
    cd streamcare
    pip install -r requirements.txt
    pip install replicate  # Install the Replicate package

Run the app locally with:

streamlit run main_app.py

Run the app locally in debug mode with: streamlit run main_app.py --logger.level debug

Set your API keys in the .env file or as environment variables:

REPLICATE_API_TOKEN=your_replicate_api_token

• Synthetic Test Mode: Simulate medical cases and receive AI analysis.
• Training Simulation Mode: Engage in medical scenario simulations with AI feedback.
• User Interaction Mode: Interact with AI for medical condition analysis and insights.
• UI/UX Enhancements: Improved user interface for an intuitive experience.

• /streamcare
  • carecli.py: # Terminal prototype
  • test.py: # Initial terminal test app
• main_app.py: # Streamlit app
• training_simulation.py: # Training simulation module
• synthetic_test.py: # Synthetic test module
• user_interaction.py: # User interaction module
• utils.py: # Utility functions
• Readme.md: # Project documentation (current file)
• requirements.txt: # Dependency list

Streamcare uses the replicate package to interact with the snowflake/snowflake-arctic-instruct model for generating medical insights.