https://github.com/mantreshkhurana/aetherai
This is a simple python chatbot which uses json file to store the data. It uses TF-IDF (Term Frequency-Inverse Document Frequency) vectorizer and a Multinomial Naive Bayes classifier to classify the user input and give the response.
https://github.com/mantreshkhurana/aetherai
chatbot flask machine-learning ml python scikit-learn sklearn tf-idf
Last synced: 4 months ago
JSON representation
This is a simple python chatbot which uses json file to store the data. It uses TF-IDF (Term Frequency-Inverse Document Frequency) vectorizer and a Multinomial Naive Bayes classifier to classify the user input and give the response.
- Host: GitHub
- URL: https://github.com/mantreshkhurana/aetherai
- Owner: mantreshkhurana
- License: mit
- Created: 2023-12-20T15:14:49.000Z (over 2 years ago)
- Default Branch: stable
- Last Pushed: 2025-02-17T10:02:40.000Z (over 1 year ago)
- Last Synced: 2025-10-26T04:19:29.296Z (8 months ago)
- Topics: chatbot, flask, machine-learning, ml, python, scikit-learn, sklearn, tf-idf
- Language: Python
- Homepage:
- Size: 53.2 MB
- Stars: 2
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Simple Python Chatbot
This is a simple python chatbot which uses json file to store the data. It uses TF-IDF (Term Frequency-Inverse Document Frequency) vectorizer and a Multinomial Naive Bayes classifier to classify the user input and give the response.
This project is under development and soon will be supported to web with multi modal support.
## Table of Contents
* [Demo](#demo)
* [Demo Video](#demo-video)
* [Screenshots](#screenshots)
* [Installation](#installation)
* [Usage](#usage)
* [API](./example.md)
* [Example Usage](#example-usage)
* [Features](#features)
* [Authors](#authors)
## Demo
### Demo Video
https://github.com/mantreshkhurana/simple-ml-python-chatbot/assets/120998049/8d3d7911-98b0-4d7f-88ab-437c691b194d
### Screenshots
## Installation
Use the package manager [pip](https://pip.pypa.io/en/stable/) to install the required packages.
```bash
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
python train.py
python app.py
```
or
```bash
python3 -m venv venv
source venv/bin/activate
pip3 install -r requirements.txt
python3 train.py
python3 app.py
```
## Usage
Arguments:
- `--port` or `-p`: Change the port number (default: 5000)
- `--server` or `-s`: Change the server (default: Server is True, no UI)
```bash
python train.py
python app.py
```
or
```bash
python3 train.py
python3 app.py
```
### Example:
```bash
python app.py --port 5001 --server 1 # Run the server on port 5001 and hide the UI
```
or
```bash
python app.py --port 5001 --server 0 # Run the server on port 5001 and show the UI
```
### Example Usage
A very basic implementation of API using Python `requests` library.
```python
import requests
url = "http://127.0.0.1:5000/api/chat"
if __name__ == "__main__":
while True:
input_data = str(input("Enter your question: "))
data = {"question": input_data}
response = requests.post(url, json=data)
print("Bot:", response.json()["response"])
```
## Features
- [x] Text support
- [x] TTS support
- [x] Custom response support
- [x] YouTube Search support
- [x] Google Search support
- [x] Wikipedia Search support
- [x] Google News support
- [x] Google Maps support
- [x] API support
- [x] YouTube Video support
- [ ] Conversation continuance support
- [ ] Image search support
- [ ] Translation support
- [x] Image support
- [ ] Audio support
- [ ] Video support
- [ ] Muliple language support
- [ ] Markdown support
- [ ] Speech to text support
- [ ] Text to speech support
- [ ] Customizable
## Authors
* [Mantresh Khurana](https://github.com/mantreshkhurana)