This project implements a chatbot interface for a hospital system. It uses a LangChain agent designed to answer questions about hospitals, patients, visits, physicians, and insurance payers in a simulated hospital system. The chatbot utilizes retrieval-augmented generation (RAG) over both structured and unstructured synthetically generated data. Here i am using the gpt-2 llm for query encoding, parsing to mongo_db database and intelligent generation of responses.
- Interactive web-based chat interface
- Answers questions about various aspects of the hospital system
- Utilizes a LangChain agent with RAG for information retrieval and response generation
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Clone the repository:
git clone https://github.com/Transcendental-Programmer/Healio-LLM-Integrated-chatbot.git cd Healio-LLM-Integrated-chatbot -
Set up a virtual environment (optional but recommended):
python -m venv venv source venv/bin/activate # On Windows use `venv\Scripts\activate` -
Install the required dependencies:
pip install -r requirements.txt
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Start the Flask server:
python app.py -
Open a web browser and navigate to
http://localhost:8000 -
Start interacting with the chatbot by typing questions in the input field
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run the requirements.txt
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Place this Dockerfile in your project's root directory.
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Build the Docker image:
docker build -t hospital-system-chatbot . -
Run the container:
docker run -p 5000:5000 hospital-system-chatbot
- Python
- Flask
- LangChain
- MongoDB
- HTML/CSS/JavaScript
Contributions to improve the chatbot are welcome. Please follow these steps:
- Fork the repository
- Create a new branch (
git checkout -b feature-branch) - Make your changes and commit them (
git commit -am 'Add some feature') - Push to the branch (
git push origin feature-branch) - Create a new Pull Request
Your Name - priyena.career@gmail.com
Project Link: https://github.com/Transcendental-Programmer/Healio-LLM-Integrated-chatbot/