This Medical Chatbot is designed for personal use and is built with Django on the backend and Vite.js on the frontend. It supports two AI modes: GeminiAI mode and OpenAI mode, allowing users to switch seamlessly between these two chatbot functionalities.
The project utilizes the Django Rest Framework (DRF) for API endpoints and Django Channels for handling WebSocket connections, providing a real-time chat experience.
Introduction
This Medical Chatbot Assistant aims to provide users with quick, accurate, and reliable medical information through an interactive chat interface. Whether you need answers to common medical queries or want to understand symptoms better, this assistant leverages advanced AI technology to assist you in making informed decisions about your health.
Key Functionalities
Real-time Chat: Interact with the chatbot in real-time for immediate responses.
AI Modes: Switch between GeminiAI and OpenAI for varied responses based on your preference.
Symptom Checker: Input symptoms to receive potential explanations and suggestions for further action.
Medication Information: Get information about various medications, including uses, side effects, and precautions.
Health Tips: Access a wealth of health and wellness tips to promote a healthier lifestyle.
User-Friendly Interface: A clean and intuitive chat interface for seamless interactions.
WebSockets: Real-time communication via Django Channels
AI Modes: GeminiAI and OpenAI
Environment Management: Conda & Pip
Containerization: Docker (planned for deployment)
Setup Instructions
To get started with this project, follow the steps below.
Prerequisites
Install Conda to manage the environment. If you don't have Conda installed, follow the instructions here to set it up.
How to Download the Repository
You can download or clone this repository using the following command:
bash
1git lfs install#installs lfs if not initialize earlier2git lfs clone https://huggingface.co/Vinay2701/Medical_Chat_App
Step 1: Create Conda Environment
Once Conda is installed, you can easily create the environment using the provided environment.yml file. Run the following command in your terminal:
conda env create -f environment.yml
Step 2: Activate Environment
After the environment is created, activate it using the command:
conda activate DTX_chat
Step 3: Add Environment Variables
Introduction to Tembo.io
For this project, we are utilizing the managed PostgreSQL database provided by Tembo.io. It's designed to help developers build, scale, and maintain Postgres databases effortlessly.
Setup Instructions
Before running the application, ensure that you have the necessary credentials for connecting to your Tembo.io PostgreSQL database. These credentials can be added to your environment variables or configuration files.
Obtaining API Keys
Google API Key
To obtain a Google API key, visit the Google Cloud Platform and create a project. Enable the necessary APIs and generate an API key for your application. Refer to the official Google Cloud documentation for more details.
OpenAI API Key
To get an OpenAI API key, sign up at the OpenAI website and navigate to the API section of your account. There, you can create and manage your API keys. Visit the OpenAI documentation for further information.
"""
Create a .env file in the root directory of the project and add the following environment variables:
bash
1GOOGLE_API_KEY=2TEMBO_HOST=## your host name3TEMBO_PASSWORD=#Tembo Password4OPENAI_API_KEY=
Make sure to replace these placeholder values with your actual API keys and credentials.
Step 4: Start the Project
Once the environment is set up and the necessary variables are added, you can start the project by running:
if you are running this project for first time then you need to setup necessary tables on the postgres to start using chat interface in that case you have to run,
If I have shared credentials with you do not run this file
python connection_setup.py
if you run connection_Setup again, it will reset your database and start from fresh. Since this is not a production-level project, I like to keep it simple like this.
Once everything is setup, stay in the project home directory and run the project:
python run_server.py
This command will launch both the backend server and the frontend server.
Note : I tried to make run_Server.py as robust as possible , If you are running through some errors , you might have to run both servers manually to launch the app
open two terminals and navigate to the parent directory
enable conda environment in both directories
run python manage.py in one, this should start djang server , ideally with out any errors
navigate to frontend folder on the other terminal
run npm install and npm run dev
this should start the chatbot on the frontend
Step 5: Access the Chat Interface
To access the frontend, open your browser and navigate to:
http://localhost:5173
You should see the chat interface where you can start interacting with the bot.
Switching AI Modes
You can easily switch between GeminiAI and OpenAI modes by using the switch button located at the top-right corner of the chat interface.
Future Plans
I am planning to implement Docker for containerization and deployment on Hugging Face, making the app easily deployable across different environments.
Feel free to contribute or provide feedback to improve this project!
