https://github.com/9802hemensan/chatbot
Chatbot Assistance
https://github.com/9802hemensan/chatbot
chatbot flask-api nltk-package punkt python torch torchvision
Last synced: 3 months ago
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Chatbot Assistance
- Host: GitHub
- URL: https://github.com/9802hemensan/chatbot
- Owner: 9802HEMENSAN
- Created: 2023-07-05T14:31:01.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2023-07-05T18:11:33.000Z (about 3 years ago)
- Last Synced: 2025-01-01T01:25:20.995Z (over 1 year ago)
- Topics: chatbot, flask-api, nltk-package, punkt, python, torch, torchvision
- Language: Python
- Homepage:
- Size: 20.5 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Chatbot Deployment with Flask and JavaScript
### **Chatbot Assistance**
**Purpose**: To provide round-the-clock customer service that can efficiently handle common queries and issues, improving customer satisfaction and freeing up staff for more complex tasks.
**Requirements**:
- An AI-based text chatbot integrated into the web application.
- Pre-programmed responses for common customer queries like "What is your operation hours?", "What is the status of my order?", etc.
- User-friendly interface for customers to interact with the chatbot.
**Metrics for success**: Decrease in basic customer inquiries handled by human staff and positive user feedback about the chatbot.
- Serve only the Flask prediction API. The used html and javascript files can be included in any Frontend application (with only a slight modification) and can run completely separate from the Flask App then.
## Initial Setup:
Clone repo and create a virtual environment
```
$ git clone
$ cd chatbot-deployment
$ python3 -m venv venv
$ . venv/bin/activate
```
Install dependencies
```
$ (venv) pip install Flask torch torchvision nltk
```
Install nltk package
```
$ (venv) python
>>> import nltk
>>> nltk.download('punkt')
```
Modify `intents.json` with different intents and responses for your Chatbot
Run
```
$ (venv) python train.py
```
This will dump data.pth file. And then run
the following command to test it in the console.
```
$ (venv) python chat.py
```
Now for deployment follow my tutorial to implement `app.py` and `app.js`.