🐦 Twitter Voice Poster for OMI

Voice-activated Twitter posting through your OMI device. Simply say "Tweet Now" followed by your message, and it will be automatically posted to Twitter!

Live Demo: omi-twitter.up.railway.app

✨ Features

• 🎤 Voice-Activated - Say "Tweet Now" and speak your message
• 🧠 AI-Powered - Collects 3 segments, intelligently extracts and cleans your tweet
• 🔐 One-Time Auth - Connect Twitter once, works forever (auto token refresh)
• 🤖 Smart Extraction - AI knows what's the tweet vs side comments
• 🔕 Silent Collection - Only notifies when tweet is posted
• 📱 Works 24/7 - Deployed on Railway with persistent storage

🚀 Quick Start

For OMI Users

1. Install the app in your OMI mobile app
2. Authenticate your Twitter account (one-time)
3. Start tweeting!
   • Say: "Tweet Now, I love using OMI to tweet with my voice!"
   • The app collects your speech (up to 3 segments)
   • AI extracts and posts the tweet
   • You get a notification when it's posted! ✅

Trigger Phrases

• "Tweet Now"
• "Post Tweet"
• "Send Tweet"
• "Tweet This"

How It Works

The app is smart about collecting your speech:

1. Detects "Tweet Now" → Starts collecting
2. Automatically collects the next 2 segments (or waits for them)
3. Sends all 3 segments to AI
4. AI extracts the actual tweet, removes filler words
5. Posts to Twitter!
6. Notifies you once ✅

Example:

You: "Tweet Now, I just had"
     [collecting silently...]
You: "an incredible idea about"
     [collecting silently...]
You: "voice AI and social media!"
     → AI processes all 3 segments
     → Posts: "I just had an incredible idea about voice AI and social media!"
     → Notification sent! 🔔

🎯 OMI App Configuration

🛠️ Development Setup

Prerequisites

• Python 3.10+
• Twitter Developer Account with API v2 access
• OpenAI API key
• OMI device and app

Installation

# Clone the repository
git clone https://github.com/aaravgarg/omi-twitter-app.git
cd omi-twitter-app

# Create virtual environment
python3 -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Configure environment
cp .env.example .env
# Edit .env with your API keys

Configuration

Create .env file with:

# Twitter API Credentials (from developer.twitter.com)
TWITTER_API_KEY=your_api_key
TWITTER_API_SECRET=your_api_secret
TWITTER_CLIENT_ID=your_client_id
TWITTER_CLIENT_SECRET=your_client_secret

# OAuth Redirect URL
OAUTH_REDIRECT_URL=http://localhost:8000/auth/callback

# OpenAI API Key (for AI tweet extraction)
OPENAI_API_KEY=your_openai_key

# App Settings
APP_HOST=0.0.0.0
APP_PORT=8000

Twitter Developer Setup

1. Go to Twitter Developer Portal
2. Create a new app or use existing
3. Enable OAuth 2.0
4. Set permissions to Read and Write
5. Add callback URL: http://localhost:8000/auth/callback (for local dev)
6. Note your API credentials

Run Locally

source venv/bin/activate
python main_simple.py

Visit http://localhost:8000/test to test!

☁️ Railway Deployment

Quick Deploy

1. Push to GitHub

   bashCopy

   git push origin main
   

2. Deploy on Railway

   • Go to railway.app
   • New Project → Deploy from GitHub
   • Select your repo
   • Add environment variables (from your .env)

3. Get your URL

   • Settings → Networking → Generate Domain
   • You'll get: your-app.up.railway.app

4. Update OAuth Redirect

   • Railway Variables: OAUTH_REDIRECT_URL=https://your-app.up.railway.app/auth/callback
   • Twitter Portal: Add same callback URL

5. Configure OMI

   • Use your Railway URLs in OMI app settings

Railway Environment Variables

Add these in Railway dashboard:

TWITTER_API_KEY
TWITTER_API_SECRET
TWITTER_CLIENT_ID
TWITTER_CLIENT_SECRET
OPENAI_API_KEY
OAUTH_REDIRECT_URL=https://your-app.up.railway.app/auth/callback
APP_HOST=0.0.0.0
APP_PORT=8000

🧪 Testing

Web Interface

Visit https://omi-twitter.up.railway.app/test to:

• Authenticate your Twitter account
• Test voice commands by typing
• See real-time logs
• Verify tweets are posting

With OMI Device

1. Configure webhook URLs in OMI Developer Settings
2. Enable the integration
3. Authenticate Twitter
4. Say: "Tweet Now, This is a test!"
5. Wait for collection (silent)
6. Get notification when posted! 🎉

🧠 AI Processing

The app uses OpenAI for two things:

1. Tweet Extraction - Analyzes all 3 segments to extract what's actually the tweet
2. Cleanup - Removes filler words, fixes grammar, capitalizes properly

Example:

Input (3 segments):
"that this is amazing and um I think"
"it's really cool and oh wait"
"I need to remember to buy milk later"

AI Output:
"That this is amazing and I think it's really cool"
(Milk reminder correctly excluded!)

📊 How Segments Work

OMI sends transcripts in segments as you speak. The app:

• ✅ Detects "Tweet Now" trigger
• ✅ Collects exactly 3 segments
• ✅ Silent during collection (no spam)
• ✅ AI processes all 3 together
• ✅ One notification on completion

Why 3 segments?

• Gives you time to complete your thought
• Captures ~10-20 seconds of speech
• AI has full context for extraction
• Balances speed vs completeness

🔐 Security & Privacy

• ✅ Tokens stored securely with file persistence
• ✅ Auto token refresh (never expires)
• ✅ OAuth 2.0 authentication
• ✅ Environment variables for secrets
• ✅ Per-user token isolation
• ✅ HTTPS enforced in production

🐛 Troubleshooting

"User not authenticated"

• Complete Twitter OAuth flow
• Check Railway logs for auth errors
• Re-authenticate if needed

"Tweet not posting"

• Check Railway logs for errors
• Verify Twitter app has "Read and Write" permissions
• Ensure you said "Tweet Now" trigger phrase
• Wait for all 3 segments to be collected

"Session resets between segments"

• This should be fixed! Session uses consistent ID per user
• Check Railway logs - should see same session_id
• Contact support if issue persists

"Railway deployment fails"

• Verify all environment variables are set
• Check build logs for specific errors
• Ensure OAUTH_REDIRECT_URL is set correctly

📁 Project Structure

omi-twitter-app/
├── main_simple.py           # FastAPI application
├── twitter_client.py        # Twitter API integration
├── tweet_detector.py        # AI-powered tweet detection & extraction
├── simple_storage.py        # File-based storage (users & sessions)
├── requirements.txt         # Python dependencies
├── railway.toml            # Railway deployment config
├── runtime.txt             # Python version
├── Procfile                # Alternative deployment platforms
├── .env.example            # Environment template
├── .gitignore             # Git ignore rules
├── LICENSE                # MIT License
└── README.md              # This file

🔧 API Endpoints

🤝 Contributing

1. Fork the repository
2. Create feature branch (git checkout -b feature/amazing)
3. Commit changes (git commit -m 'Add amazing feature')
4. Push to branch (git push origin feature/amazing)
5. Open a Pull Request

📝 License

MIT License - see LICENSE file for details.

🆘 Support

• Issues: GitHub Issues
• OMI Docs: docs.omi.me
• Twitter API: developer.twitter.com/en/docs

🎉 Credits

Built for the OMI ecosystem.

• OMI Team - Amazing wearable AI platform
• Twitter API - Social media integration
• OpenAI - Intelligent text processing

Made with ❤️ for voice-first social media

Deployed at: omi-twitter.up.railway.app