DEPLOY.md

Linly-X-Gemini - Deployment Guide

🚀 Quick Deploy

Repository Name: Linly-X-Gemini

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GitHub Deployment

cd "d:/linly gg/Linly-Talker"

# Initialize git (if not already)
git init
git add .
git commit -m "feat: Linly-X-Gemini - Real-time AI Avatar with Gemini Live

- 8 applications with Gemini Live integration
- MuseTalk streaming engine (<1s latency)
- Railway WebSocket bridge
- Complete documentation"

# Push to GitHub
git remote add origin https://github.com/YOUR_USERNAME/linly-x-gemini.git
git branch -M main
git push -u origin main

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Hugging Face Spaces Deployment

Step 1: Create Space

1. Go to https://huggingface.co/spaces
2. Click "Create new Space"
3. Settings:
   • Name: linly-x-gemini
   • SDK: Gradio
   • SDK Version: 4.44.0
   • Hardware: GPU (T4 or better)
   • Persistent Storage: Enable (for model caching)

Step 2: Push Code

# Add Hugging Face remote
git remote add hf https://huggingface.co/spaces/YOUR_USERNAME/linly-x-gemini

# Push to Hugging Face
git push hf main

Step 3: Configure Space

The README.md file contains the Hugging Face configuration:

title: Linly-X-Gemini
emoji: 🎭
sdk: gradio
sdk_version: 4.44.0
app_file: webui.py

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📋 Pre-Deployment Checklist

• ✅ Repository renamed to Linly-X-Gemini
• ✅ No API keys in code
• ✅ All endpoints use Railway bridge
• ✅ configs.py import is optional
• ✅ Paths are correct (Musetalk/)
• ✅ .gitignore excludes models
• ✅ Documentation complete

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🎯 What Gets Deployed

Main App: webui.py

• Clean Gemini Live interface
• Default + custom avatars
• Real-time streaming

Additional Apps (optional):

• app.py - Unified (Gemini + Legacy)
• app_img.py - Talking photos
• app_multi.py - Multi-turn conversation
• app_talk.py - Avatar comparison lab
• app_musetalk.py - Debug tool
• app_gemini_live.py - Standalone demo
• app_vits.py - Voice cloning

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⚙️ Environment Requirements

Hugging Face Spaces:

• GPU: T4 minimum (8GB VRAM)
• Storage: 10GB+ for models
• Python: 3.10+

Models (auto-downloaded on first run):

• MuseTalk checkpoints (~2GB)
• Face alignment models
• Whisper ASR (optional)

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🔧 Post-Deployment

Test Checklist:

1. ✅ Space builds successfully
2. ✅ Models download correctly
3. ✅ Avatar preparation works
4. ✅ WebSocket connects to Railway
5. ✅ Real-time streaming works
6. ✅ Audio playback functions
7. ✅ Frame rate ~25 FPS

Expected Performance:

• Latency: <1 second
• FPS: 20-25
• VRAM: 6-8GB
• Connection: 99%+ uptime

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🎉 You're Ready!

Repository: Linly-X-Gemini
Status: Production Ready
Deploy: GitHub + Hugging Face Spaces

🚀 Let's go!