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https://github.com/sanjurajveer/chatbot
This is basic chatbot
https://github.com/sanjurajveer/chatbot
classification conversational-ai nlp-machine-learning streamlit
Last synced: 30 days ago
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This is basic chatbot
- Host: GitHub
- URL: https://github.com/sanjurajveer/chatbot
- Owner: sanjurajveer
- Created: 2024-12-29T20:12:35.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2024-12-29T20:35:20.000Z (about 1 month ago)
- Last Synced: 2024-12-29T21:23:29.106Z (about 1 month ago)
- Topics: classification, conversational-ai, nlp-machine-learning, streamlit
- Language: Python
- Homepage:
- Size: 8.79 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Chatbot with Intent Recognition
This project is a simple chatbot built using Python, Streamlit, and machine learning techniques. The chatbot can respond to a variety of user inputs based on predefined intents and patterns. It uses a logistic regression model to classify user inputs and generate appropriate responses.
To run this chatbot go to your terminal cd to your chatbot.py file then type: streamlit run chatbot.py
## Features
- Responds to common queries like greetings, goodbyes, and thanks.
- Provides help with Python programming concepts.
- Shares motivational quotes and jokes.
- Offers learning recommendations for Python, AI, and books.
- Handles fallback cases for unrecognized inputs.
- Built-in SSL workaround for downloading NLTK data.
## Technologies Used
- **Python**: Core programming language for the chatbot.
- **Streamlit**: For building the user interface.
- **NLTK**: For natural language preprocessing.
- **scikit-learn**: For vectorization (TfidfVectorizer) and intent classification (Logistic Regression).
## Installation
1. Clone this repository:
```bash
git clone https://github.com/sanjuraveer/chatbot.git
cd chatbot
```
2. Create a virtual environment and activate it:
```bash
python -m venv venv
# Activate on Windows:
venv\Scripts\activate
# Activate on macOS/Linux:
source venv/bin/activate
```
3. Install the required dependencies:
```bash
pip install -r requirements.txt
```
4. Download the necessary NLTK data:
```bash
python -c "import nltk; nltk.download('punkt')"
```
## Usage
1. Run the chatbot application:
```bash
streamlit run chatbot.py
```
2. Open your browser and navigate to the URL provided by Streamlit (usually `http://localhost:8501`).
3. Start chatting with the chatbot by typing your message in the input box.
## File Structure
```
chatbot/
├── chatbot.py # Main application script
├── nltk_data/ # Directory for NLTK data
├── requirements.txt # Python dependencies
└── README.md # Project documentation
```
## Example Intents
Below are some example intents and patterns supported by the chatbot:
| Tag | Example Patterns |
|-----------------|--------------------------------------------|
| greeting | Hi, Hello, Hey, How are you, What's up |
| goodbye | Bye, See you later, Goodbye, Take care |
| thanks | Thank you, Thanks, I appreciate it |
| programming_help| How to write a for loop in Python? |
| jokes | Tell me a joke, Make me laugh |
| motivation | I feel down, Motivate me, Give me a quote |
| learning_recommendations | How can I learn Python?, Good books |
## Customization
To add more intents:
1. Update the `intents` list in `chatbot.py` with new tags, patterns, and responses.
2. Retrain the model by running the script again.
## License
This project is licensed under the MIT License. See the LICENSE file for more information.
## Contributing
Contributions are welcome! Feel free to open issues or submit pull requests to improve the chatbot.
## Author
Developed by [Sanju Raj](https://github.com/sanjurajveer).
credits:Aman Kharwal