Doctor Assistant Chatbot

This project is a Doctor Assistant chatbot that can answer medical questions. It uses the Gemini 2.5 Flash language model through the LangChain library. The chatbot can be run in three different ways: as a command-line application, as a web application using Streamlit, or as an API using FastAPI.

Features

• Multiple Interfaces: Run the chatbot in the terminal, as a Streamlit web app, or as a FastAPI-powered API.
• Conversational Memory: The chatbot remembers the context of the conversation for each user.
• Powered by Gemini 2.5 Flash: Utilizes Google's powerful and efficient language model.
• Easy to Use: Simple and intuitive interfaces for interacting with the chatbot.

Prerequisites

• Python 3.7+
• An API key for the Gemini API.

Setup

1. Clone the repository:

   git clone https://github.com/myz21/DoctorGPT.git
   cd DoctorGPT

2. Create and activate a virtual environment:

   python -m venv doctor_gpt
   source doctor_gpt/bin/activate

3. Install the required dependencies:

   pip install -r requirements.txt

4. Set up your environment variables:

   Create a file named .env in the root directory of the project and add your Gemini API key to it:

   GEMINI_API_KEY="your_api_key_here"
   

Usage

You can run the Doctor Assistant chatbot in three different ways:

1. Terminal Application

To run the chatbot in your terminal, execute the following command:

python doctor_assistant_terminal.py

The application will prompt you for your name and age, and then you can start chatting with the assistant.

2. Streamlit Web Application

To run the chatbot as a web application, use the following command:

streamlit run streamlit_app.py

This will start a local web server, and you can interact with the chatbot in your browser.

3. FastAPI Application

To run the chatbot as an API, you need to use uvicorn:

uvicorn doctor_assistant_api:app --reload

The API will be available at http://127.0.0.1:8000. You can send POST requests to the /chat endpoint with a JSON payload containing the user's name, age, and message.

You can test the API using the client_test.py script:

python client_test.py

Project Structure

• doctor_assistant_terminal.py: The command-line interface for the chatbot.
• streamlit_app.py: The Streamlit web application.
• doctor_assistant_api.py: The FastAPI application.
• client_test.py: A script to test the FastAPI endpoint.
• requirements.txt: A list of the Python dependencies for the project.
• .env: A file for storing environment variables (e.g., your Gemini API key).
• README.md: This file.