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https://github.com/shz-code/chatbot-nltk
Python Contextual Chatbot with Voice Recognition.
https://github.com/shz-code/chatbot-nltk
chatbot pipeline python python-chatbot pytorch-implementation pyttsx3 speech-recognition speech-to-text
Last synced: about 2 months ago
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Python Contextual Chatbot with Voice Recognition.
- Host: GitHub
- URL: https://github.com/shz-code/chatbot-nltk
- Owner: shz-code
- Created: 2023-01-26T06:38:05.000Z (almost 2 years ago)
- Default Branch: master
- Last Pushed: 2023-01-29T14:55:53.000Z (almost 2 years ago)
- Last Synced: 2024-04-20T16:03:55.547Z (9 months ago)
- Topics: chatbot, pipeline, python, python-chatbot, pytorch-implementation, pyttsx3, speech-recognition, speech-to-text
- Language: Python
- Homepage:
- Size: 17.6 KB
- Stars: 4
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: Readme.md
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README
# Python contextual chatbot with voice recognition.
## Major packages used
- Speech Recognition
- PyTorch
- Pyttsx
- NLTK
## Project requirements
- `Python 3.7-3.9` (Pytorch limitation)
## Installation Process
First clone this git repository or download zip
```console
git clone https://github.com/shz-code/chatbot-nltk.git
```
Create a new virtual environment(Use Conda/ Virtual Environment) [Learn More.](https://docs.python.org/3/library/venv.html#:~:text=A%20virtual%20environment%20is%20created,the%20virtual%20environment%20are%20available.)
**If virtual environment is not installed on your machine install it using below command.*
```console
pip install virtualenv
```
Activate **virtualenv**
```console
virtualenv env
.\env\Scripts\activate
```
Run pip to install all the dependencies
```console
pip install -r requirements.txt
```
Train your model based on [intents.json](https://github.com/shz-code/chatbot-nltk/blob/master/nlp_pipeline/training%20data/intents.json)
It will create `data.pth` which is the model data.
```console
py .\nlp_pipeline\train.py
```
If you get an error during the first run, you also need to install `nltk.tokenize.punkt`:
*Run this once in your terminal:*
```console
python
>>> import nltk
>>> nltk.download('punkt')
```
Finally start main.py
```console
py main.py
```
## Features
- Users can chat or speak with the bot.
- The bot can generate answers based on pre-defined conditions or it will generate answer trained from [intents.json](https://github.com/shz-code/chatbot-nltk/blob/master/nlp_pipeline/training%20data/intents.json) data.
## Customize
You can easily feed more data or customize the model by adding or modifying [intents.json](https://github.com/shz-code/chatbot-nltk/blob/master/nlp_pipeline/training%20data/intents.json) file.
For example
```json
{
"intents": [
{
"tag": "new-tag",
"patterns": [
"all the question patterns related to that tag",
"question 1",
"question 2"
],
"responses": [
"all the response patterns related to that tag",
"response 1",
"response 2"
]
},
...
]
}
```
**NB**: You need to train your model again if you have modified the [intents.json](https://github.com/shz-code/chatbot-nltk/blob/master/nlp_pipeline/training%20data/intents.json) file. Run `train.py` file to train your chatbot. If you see no changes happening than delete the old **data.pth** file and train again.
## Acknowledgements
- Main Project idea [Patrick Loeber](https://github.com/patrickloeber/pytorch-chatbot)
- Main article [Contextual Chatbots with TenserFlow](https://chatbotsmagazine.com/contextual-chat-bots-with-tensorflow-4391749d0077)
- Supporting article [Complete guide to build your ai chatbot with nlp in python](https://www.analyticsvidhya.com/blog/2021/10/complete-guide-to-build-your-ai-chatbot-with-nlp-in-python/)