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https://github.com/rishabhraj43/emotion-detector-telegram-bot
A Telegram Bot made with pure JavaScript and Machine Learning model made in Python
https://github.com/rishabhraj43/emotion-detector-telegram-bot
flask javascript machine-learning-algorithms node-js python
Last synced: 3 days ago
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A Telegram Bot made with pure JavaScript and Machine Learning model made in Python
- Host: GitHub
- URL: https://github.com/rishabhraj43/emotion-detector-telegram-bot
- Owner: RishabhRaj43
- Created: 2024-08-14T15:36:48.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2024-08-15T18:45:12.000Z (3 months ago)
- Last Synced: 2024-08-19T20:06:38.744Z (3 months ago)
- Topics: flask, javascript, machine-learning-algorithms, node-js, python
- Language: JavaScript
- Homepage:
- Size: 1.6 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Telegram Emotion Bot
This is a Telegram bot built using JavaScript that interacts with users and predicts emotions from the text they input. The bot can also cheer up the user by telling jokes if a negative emotion is detected.
## Features
- **Start and Help Commands**: Basic commands to start and get help on using the bot.
- **Emotion Prediction**: Users can input text to check for emotions.
- **Jokes**: If a negative emotion is detected, the bot offers to cheer up the user with a joke.
- **Custom Keyboard**: Provides a custom keyboard for easy command selection.
## Technologies Used
- **Node.js**: Backend logic and bot interaction.
- **Telegram Bot API**: To interface with Telegram.
- **Express and Flask**: Flask is used for the emotion prediction API, and Express is used as a basic server (if needed).
- **Axios**: To handle HTTP requests.
- **Python**: For the emotion prediction model using scikit-learn.
## Setup and Installation
1. **Clone the Repository**:
```
git clone https://github.com/Zenith-Rish4bh/Emotion-Detector-Telegram-Bot.git
cd telegram-emotion-bot
```
3. **Install Node.js Dependencies**:
``` bash
npm install
```
5. **Set Up Environment Variables**:
- Create a `.env` file in the root directory.
- Add your Telegram bot token:
``` env
TOKEN = your-telegram-bot-token
```
6. **Install Python Dependencies**:
```bash
pip install flask flask-cors scikit-learn joblib
```
7. **Prepare the Emotion Model**:
- Train an emotion detection model and save it as `emotion.pkl` in the root directory.
8. **Run the Python Server**:
- Navigate to the directory containing your Python script and run:
```bash
python app.py
```
10. **Run the Telegram Bot**:
- Start the bot by running:
```bash
npm start
```
## Usage
- **Commands**:
- `/start`: Start the bot.
- `/help`: Get a list of available commands.
- `/checkemotion`: Enter text to analyze emotion.
- `/joke`: Get a random joke.
- `/command`: Display the custom keyboard.
- **Interaction Flow**:
1. Start the bot with `/start`.
2. Use `/checkemotion` to input text and receive an emotion analysis.
3. If a negative emotion is detected, the bot offers to tell a joke to cheer you up.
## API Endpoints
- **POST /predict**:
- Accepts: JSON containing the text to be analyzed.
- Returns: JSON containing the predicted emotion.
## Example Interaction
1. **User**: `/start`
- **Bot**: "Hello there! How can I help you?"
2. **User**: `/checkemotion`
- **Bot**: "Enter the text you want to check."
3. **User**: `"I'm feeling down today."`
- **Bot**: "The emotion is sadness. Do you want to cheer your mood by reading some jokes? Press /joke"
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Happy Coding 🎉