A Python module that fetches the top news articles for a given keyword using NewsAPI.org.
Features:
- Fetch top 3 news articles (can be changed in script).
- Display title + URL.
- Shortens long URLs for cleaner output.
- Logs fetched news to
news_log.txt. - Accepts commands like
show news about AI.
- Install dependencies:
A production-ready voice assistant with facial recognition authentication, built on modern Python architecture and web technologies.
Features • Installation • Usage • Documentation • Contributing
| 🎤 Voice Control | 👤 Face Recognition | 🔥 Hotword Detection | 🌐 Web Integration |
|---|---|---|---|
| Advanced speech-to-text | Secure biometric auth | Always-on wake word | Modern responsive UI |
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graph TD
A[🌐 Web Frontend] -->|Eel Bridge| B[🎯 Main Process]
B --> C[🎤 Speech Recognition]
B --> D[👤 Face Authentication]
B --> E[🔥 Hotword Detection]
C --> F[📝 Command Parser]
F --> G[⚡ Feature Handlers]
G --> H[💾 SQLite Database]
G --> I[📱 WhatsApp Integration]
G --> J[🎬 YouTube Control]
G --> K[💬 AI Chatbot]
style A fill:#e1f5ff
style B fill:#fff3e0
style G fill:#f3e5f5
style H fill:#e8f5e9
OS: Windows 10/11, Linux, macOS
Python: 3.10+
RAM: 4GB minimum
Storage: 500MB free space |
Microphone: Required for voice input
Webcam: Required for face recognition
Internet: Active connection needed
Audio Output: Speakers/Headphones |
📦 Quick Install (Click to expand)
git clone https://github.com/vannu07/jarvis.git
cd jarvis|
🪟 Windows python -m venv venv
venv\Scripts\activate |
🐧 Linux/Mac python3 -m venv venv
source venv/bin/activate |
pip install -r requirements.txtCreate a .env file:
# API Keys
HUGGINGFACE_TOKEN=your_token_here
PORCUPINE_ACCESS_KEY=your_key_here
# Voice Settings
TTS_RATE=150
TTS_VOICE=0
# Recognition Settings
FACE_CONFIDENCE_THRESHOLD=50
HOTWORD_SENSITIVITY=0.5python backend/auth/trainer.py
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| Shortcut | Action |
|---|---|
Win + J (Windows) |
Manual Activation |
Cmd + J (macOS) |
Manual Activation |
Ctrl + Q |
Quit Application |
F11 |
Fullscreen Toggle |
Say "Jarvis" or "Alexa" followed by your command!
📦 jarvis/
┣ 📂 backend/
┃ ┣ 📂 auth/
┃ ┃ ┣ 📄 haarcascade_frontalface_default.xml
┃ ┃ ┣ 📄 recognize.py # 👤 Face recognition
┃ ┃ ┣ 📄 trainer.py # 🎓 Model training
┃ ┃ ┗ 📂 trainer/ # 💾 Trained models
┃ ┣ 📄 command.py # 🎯 Command parser
┃ ┣ 📄 config.py # ⚙️ Configuration
┃ ┣ 📄 db.py # 💾 Database ops
┃ ┣ 📄 feature.py # ⚡ Feature handlers
┃ ┗ 📄 helper.py # 🛠️ Utilities
┣ 📂 frontend/
┃ ┣ 📂 assets/
┃ ┃ ┣ 📂 audio/ # 🔊 Sound files
┃ ┃ ┣ 📂 img/ # 🖼️ Images & icons
┃ ┃ ┗ 📂 vendor/ # 📚 Third-party libs
┃ ┣ 📄 index.html # 🌐 Main UI
┃ ┣ 📄 style.css # 🎨 Styles
┃ ┣ 📄 script.js # ✨ Particle effects
┃ ┣ 📄 main.js # 🎮 Core logic
┃ ┗ 📄 controller.js # 🎛️ Event handlers
┣ 📄 main.py # 🚀 Entry point
┣ 📄 run.py # 🔄 Launcher
┣ 📄 requirements.txt # 📦 Dependencies
┗ 📄 jarvis.db # 💾 SQLite DB
🎨 Adding Custom Commands
Edit backend/command.py:
def parse_command(query: str) -> dict:
if "my custom action" in query.lower():
return {
"action": "custom_action",
"params": {"param1": "value1"}
}Edit backend/feature.py:
def handle_custom_action(params: dict) -> str:
# Your implementation here
result = do_something(params)
return f"Action completed: {result}"COMMAND_HANDLERS = {
"custom_action": handle_custom_action,
# ... other handlers
}💾 Database Schema
-- 📇 Contacts Table
CREATE TABLE contacts (
id INTEGER PRIMARY KEY AUTOINCREMENT,
name TEXT NOT NULL,
phone TEXT,
whatsapp TEXT,
email TEXT,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);
-- 💻 Applications Table
CREATE TABLE apps (
id INTEGER PRIMARY KEY AUTOINCREMENT,
name TEXT NOT NULL,
path TEXT NOT NULL,
keywords TEXT, -- JSON array
icon TEXT,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);
-- 🌐 Web Commands Table
CREATE TABLE web_commands (
id INTEGER PRIMARY KEY AUTOINCREMENT,
command TEXT NOT NULL,
url TEXT NOT NULL,
description TEXT,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);🧪 Testing
# Run all tests
pytest tests/ -v
# Run with coverage
pytest --cov=backend --cov-report=html tests/
# Run specific test file
pytest tests/test_command.py -v
# Linting
black backend/ frontend/ --check
flake8 backend/
pylint backend/🐳 Docker Deployment
FROM python:3.10-slim
WORKDIR /app
# Install system dependencies
RUN apt-get update && apt-get install -y \
portaudio19-dev \
python3-pyaudio \
libopencv-dev \
&& rm -rf /var/lib/apt/lists/*
# Copy and install Python dependencies
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
# Copy application
COPY . .
EXPOSE 8000
CMD ["python", "run.py"]Build & Run:
docker build -t jarvis-ai .
docker run -p 8000:8000 -v $(pwd)/jarvis.db:/app/jarvis.db jarvis-ai| Metric | Value | Status |
|---|---|---|
| 🚀 Cold Start Time | ~3.5s | |
| ⚡ Response Latency | <200ms | |
| 🎯 Face Recognition Accuracy | 94.2% | |
| 💾 Memory Footprint | ~150MB | |
| 🔋 CPU Usage (Idle) | 2-5% |
Benchmarked on Windows 11, Intel i5-10400, 16GB RAM
🔴 Common Issues & Solutions
Windows:
pip install pipwin
pipwin install pyaudioLinux:
sudo apt-get install portaudio19-dev python3-pyaudio
pip install pyaudiomacOS:
brew install portaudio
pip install pyaudio- Ensure good lighting conditions
- Position face 2-3 feet from camera
- Retrain model:
python backend/auth/trainer.py
- Check camera permissions in system settings
- Check microphone permissions
- Test microphone:
python -m speech_recognition
- Verify internet connection
- Try different microphone device
pip install --upgrade --force-reinstall -r requirements.txt# Windows
set JARVIS_DEBUG=1
python run.py
# Linux/Mac
export JARVIS_DEBUG=1
python run.pyWe love contributions! 💖
- 🍴 Fork the repository
- 🌿 Create a feature branch (
git checkout -b feature/amazing-feature) - 💾 Commit your changes (
git commit -m 'feat: add amazing feature') - 📤 Push to the branch (
git push origin feature/amazing-feature) - 🎉 Open a Pull Request
type(scope): subject
[optional body]
[optional footer]
Types: feat, fix, docs, style, refactor, test, chore
Example:
git commit -m "feat(voice): add support for multiple languages"
git commit -m "fix(face): improve recognition accuracy in low light"
git commit -m "docs(readme): update installation instructions"- ✅ Follow PEP 8 for Python code
- ✅ Use type hints where applicable
- ✅ Write docstrings for public functions
- ✅ Run
blackandflake8before committing - ✅ Add unit tests for new features
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Special thanks to these amazing projects:
Varnit Kumar
Project Link: github.com/vannu07/jarvis
If you find this project helpful, please consider:
⭐ Starring this repository 🐛 Reporting bugs 💡 Suggesting new features 🤝 Contributing to the code 📢 Sharing with others
Made with ❤️ and Python
>>>>>>> bd1d8cfda59b40748beac88a96cbf5f19c082e32