DEPLOYMENT.md

🚀 Deployment Guide for Hugging Face Spaces

Files Created for Deployment

1. app.py - Main Gradio application
2. README.md - Space configuration and documentation
3. requirements.txt - Python dependencies
4. packages.txt - System dependencies for Manim
5. .gitignore - Files to exclude from git
6. test_deployment.py - Local testing script

Step-by-Step Deployment Instructions

1. Create a New Hugging Face Space

1. Go to Hugging Face Spaces
2. Click "Create new Space"
3. Choose:
   • Space name: ai-video-generator (or your preferred name)
   • License: MIT
   • SDK: Gradio
   • Hardware: CPU Basic (free tier) or GPU if you have Pro subscription

2. Upload Files

Upload all the files from your video_generator folder:

• app.py
• README.md
• requirements.txt
• packages.txt
• .gitignore

DO NOT upload:

• .env file (contains your API key)
• video_generator.py (original file, not needed)

3. Set Environment Variables

1. Go to your Space settings
2. Click on "Variables and secrets"
3. Add a new secret:
   • Name: GEMINI_API_KEY
   • Value: Your actual Gemini API key (from your .env file)

4. Wait for Build

• The space will automatically build and install dependencies
• This may take 5-15 minutes due to Manim installation
• Check the build logs for any errors

5. Test the Application

1. Once built, test with a simple topic like "Introduction to Python"
2. Check if videos generate correctly
3. Verify the interface works smoothly

Troubleshooting

Common Issues and Solutions

1. Build Timeout

   • Manim installation can be slow
   • Try using a smaller requirements.txt with fewer versions specified

2. Memory Issues

   • Use shorter video durations (1 minute)
   • Consider upgrading to GPU hardware

3. API Key Issues

   • Double-check the secret name is exactly GEMINI_API_KEY
   • Verify the API key is valid and has quota

4. Video Generation Fails

   • Check the generation logs in the interface
   • Manim syntax might need adjustment for the cloud environment

Alternative Deployment (GitHub → HF Spaces)

If you prefer using Git:

1. Create a GitHub repository
2. Push all files (except .env)
3. Connect the repository to Hugging Face Spaces
4. Set the API key in Spaces secrets

Performance Tips

1. Use shorter durations (1-2 minutes max)
2. Simple topics work better than complex ones
3. Monitor usage to stay within API limits
4. Consider caching for frequently requested topics

Security Notes

• Never commit API keys to public repositories
• Use Hugging Face Spaces secrets for sensitive data
• The .gitignore file excludes sensitive files

Support

If you encounter issues:

1. Check the Space logs
2. Verify all dependencies in requirements.txt
3. Test locally first with test_deployment.py
4. Consider the Hugging Face Spaces documentation