https://github.com/jagadishdas21/ai-doctor

AI Doctor is an intelligent chatbot designed to assist users in medical research and diagnosis-related queries. Built using Natural Language Toolkit (NLTK) and TensorFlow, this project leverages advanced machine learning techniques to provide accurate and relevant responses to users' health-related questions.
https://github.com/jagadishdas21/ai-doctor

Last synced: 17 days ago
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AI Doctor is an intelligent chatbot designed to assist users in medical research and diagnosis-related queries. Built using Natural Language Toolkit (NLTK) and TensorFlow, this project leverages advanced machine learning techniques to provide accurate and relevant responses to users' health-related questions.

• Host: GitHub
• URL: https://github.com/jagadishdas21/ai-doctor
• Owner: jagadishdas21
• Created: 2024-10-05T06:52:43.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2024-10-14T08:50:45.000Z (3 months ago)
• Last Synced: 2024-10-26T14:44:04.750Z (2 months ago)
• Language: Python
• Homepage:
• Size: 1.52 MB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# ChatBot

A chatbot is a digital tool that engages in conversations with users, simulating human-like interactions through text or speech. These bots can be simple, rule-based systems, responding to predefined commands, or advanced AI-driven applications that understand and process natural language (NLP) to offer more dynamic, context-aware responses. They are often used in customer service, providing instant support, answering frequently asked questions, or assisting with tasks like booking appointments. Modern chatbots are used in industries ranging from e-commerce to healthcare, improving efficiency and user experience by automating interactions.

## Project Overview

This chatbot utilizes machine learning techniques to understand and respond to user queries in a natural and conversational manner. It leverages TensorFlow for training a neural network model and NLTK for natural language processing tasks. The chatbot's responses are defined in an intents file, making it easy to modify and adapt the bot's behavior.

## Features

- Natural Language Understanding: Uses NLTK to process and interpret user input.

- Machine Learning Model: Implements a neural network model using TensorFlow for intent classification.

- Customizable: Easily modify the bot's responses and behaviors by editing the intents file.

- Interactive: Engages in conversation with users based on predefined patterns.

## Installation

To set up the chatbot on your local machine, follow these steps:

1. Clone the repository:

bash $ git clone `https://github.com/jagadishdas21/ChatBot.git`

cd ChatBot

2. Install the required dependencies: It is recommended to use a virtual environment:

bash $ python -m venv chatbot_env

source # On Windows, use `chatbot_env\Scripts\activate`

pip install -r requirements.txt

3. Run the chatbot: bash $ python chatbot.py

   

## File Descriptions

- chatbot.py: The main file that runs the chatbot.

- chatbot_model.h5: The trained neural network model used for intent classification.

- classes.pkl: Serialized list of unique classes or intents.

- intents.json: JSON file containing predefined patterns and responses for the chatbot.

- new.py: Additional Python script with supplementary functions.

- pyvenv.cfg: Configuration file for the Python virtual environment.

- words.pkl: Serialized list of processed words used for training.

## Usage

- Launch the chatbot using python chatbot.py and interact with it in the terminal.

- Modify the intents.json file to add new intents or responses as required.

## Customization

To customize the chatbot's behavior:

- Open the intents.json file.

- Add or modify intents, patterns, and responses according to your needs.

- Retrain the model using the updated data to improve response accuracy.

## Contribution

Contributions are welcome! Please follow these steps to contribute:

- Fork the repository.

- Create a new branch: git checkout -b feature-branch.

- Make your changes and commit them: git commit -m 'Add some feature'.

- Push to the branch: git push origin feature-branch.

- Submit a pull request.