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https://github.com/khaledalabssi/buzzy_the_chatbot
Simple chatbot implemented using TensorFlow and Natural Language Processing (NLP) techniques. The chatbot is trained on a predefined set of data and can respond to user inputs accordingly.
https://github.com/khaledalabssi/buzzy_the_chatbot
chatbot chatbot-experiment tensorflow-examples tensorflow2
Last synced: 11 days ago
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Simple chatbot implemented using TensorFlow and Natural Language Processing (NLP) techniques. The chatbot is trained on a predefined set of data and can respond to user inputs accordingly.
- Host: GitHub
- URL: https://github.com/khaledalabssi/buzzy_the_chatbot
- Owner: KhaledAlabssi
- Created: 2024-06-09T15:27:57.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2024-06-09T17:49:15.000Z (5 months ago)
- Last Synced: 2024-10-17T13:14:11.717Z (28 days ago)
- Topics: chatbot, chatbot-experiment, tensorflow-examples, tensorflow2
- Language: Python
- Homepage:
- Size: 10.7 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Buzzy the Chatbot
## Description
Simple chatbot implemented using TensorFlow and (NLP). The chatbot is trained on a predefined data and can respond to inputs accordingly.
## File Structure
- `preparation.py`: => load, preprocess data, and save data.
- `training.py`: => build and train the model.
- `util.py`: => processing sentences and making predictions.
- `app.py`: => execute the training and test the chatbot.
## Requirements
- Python 3.x
- TensorFlow
- NLTK
- NumPy
- Pickle
## Installation
1. Clone the repository:
```bash
git clone https://github.com/KhaledAlabssi/Buzzy_the_Chatbot.git
cd Buzzy_the_Chatbot
```
2. Install the required packages:
```bash
pip install -r requirements.txt
```
## Usage
1. Prepare the intents file (`intents.json`) with the training data "data examples" are shared in (`internts.example.json`).
2. Run the main script to train the model:
```bash
python app.py
```
3. The trained model will be saved as `chatbot_model.h5`, and the processed data will be saved as `words.pkl` and `classes.pkl`.
## Get in Touch
> LinkedIn: [linkedIn.com/in/Khaled-Alabssi](https://www.linkedin.com/in/khaled-alabssi/)
> GitHub: [github.com/KhaledAlabssi](https://github.com/KhaledAlabssi)
> Website: [khaled.alabssi.com](https://www.khaled.alabssi.com)
## Happy Coding!