A simple chatbot that can help users check their symptoms and provide relevant information. This chatbot uses natural language processing (NLP) techniques and a recurrent neural network (RNN) model to understand user queries and respond accordingly.
This repository contains code for a symptom checker chatbot. The chatbot can engage in conversations with users, gather information about their symptoms, and provide information about potential conditions or nearby medical centers. It uses a pre-trained RNN model for natural language understanding.
To get started with the Symptom Checker Chatbot, follow these steps:
-
Clone the repository to your local machine:
git clone https://github.com/your-username/symptom-checker-chatbot.git
-
Install the required dependencies:
pip install -r requirements.txt
-
Download the necessary data files and place them in the appropriate directories:
intents.json
: Contains predefined intents for the chatbot.data_rnn.pth
: Pre-trained RNN model for natural language understanding.medical_centers.json
: Data file containing information about medical centers.
To use the Symptom Checker Chatbot, run the app.py
file:
python app.py
This will start a Flask web application that you can interact with. Visit the URL http://localhost:5000
in your web browser to access the chat interface.
If you want to retrain the RNN model or modify the chatbot's behavior, follow these steps:
-
Modify the intents and patterns in
intents.json
to customize the chatbot's responses. -
Run the training script to retrain the RNN model:
python train.py
-
Save the trained model with a new filename and update the
FILE
variable inchat.py
with the new filename.
The Symptom Checker Chatbot relies on the following dependencies:
- Python 3.x
- PyTorch
- Flask
- NLTK
- geocoder
You can install these dependencies using the provided requirements.txt
file.
If you'd like to contribute to this project, feel free to fork the repository and submit pull requests. Contributions are welcome, whether it's bug fixes, feature enhancements, or documentation improvements.
This project is licensed under the MIT License - see the LICENSE file for details.
For questions or collaboration opportunities, feel free to contact us at monishkumarpecai@gmail.com.