A sophisticated AI-powered chatbot designed to provide medical advice using the Rasa framework and LangGraph. This project leverages natural language understanding (NLU) to deliver tailored responses to user queries, making healthcare assistance more accessible and user-friendly.
The GenAI-Powered Medical Advice Chatbot is a conversational assistant aimed at providing medical advice and guidance. It combines the robust capabilities of Rasa for managing dialogues and intents with LangGraph for advanced language processing. This tool is ideal for users seeking quick medical information or guidance in a conversational format.
- Natural Language Understanding (NLU): Enables the chatbot to process user queries with high accuracy.
- Customizable Intents and Responses: Easily expandable to handle various use cases in healthcare and beyond.
- Integrates with Python Actions: Extends functionality with custom actions written in Python.
- Scenario-Based Training: Includes predefined stories to handle complex conversation flows.
- Interactive Dialogue Management: Provides context-aware responses.
- Lightweight and Scalable: Designed to work efficiently in various deployment environments.
Ensure you have the following installed on your system:
- Python 3.7 or higher
- pip (Python package manager)
- Clone the repository:
git clone https://github.com/saikiransomanagoudar/medical-advice cd medical-advice - Set up a virtual environment (optional but recommended):
python -m venv venv venv\Scripts\activate # On Mac: source venv/bin/activate
- Install dependencies:
pip install -r requirements.txt
- Train the NLU and Core models:
rasa train
- Run the chatbot:
rasa run
- Start the action server:
rasa run actions
- To interact with the chatbot, use the Rasa shell:
rasa shell
- For web or app integration, configure the endpoints.yml file and deploy on a server.