# BAKO-AI Deployment Guide

This guide explains how to manage and deploy the BAKO-AI analysis pipeline to Hugging Face.

## 🏗 Architecture Overview
- **Application**: Hosted on Hugging Face Spaces (`icanedit2/BakoAI`).
- **Models**: Hosted on a dedicated Hugging Face Model Repository (`icanedit2/bakoai-models`).
- **Storage/DB**: Managed via Supabase.

## 🚀 Deployment Workflow

### 1. Push Code Changes
To push local changes from the `back-end` folder to the Hugging Face Space root:
```bash
# From the root directory:
git subtree split --prefix back-end -b hf-production-build
git push hf hf-production-build:main --force
git branch -D hf-production-build
```

### 🧠 2. Managing Models
Models are stored in the `icanedit2/bakoai-models` repository to prevent `git push` from deleting them.
- To add a new model, upload it to the `bakoai-models` repo.
- Update `download_models.py` in the Space repo to include the new filename.
- The build process will automatically download models into `/home/user/app/models/`.

### 🔐 3. Security (Hugging Face Secrets)
Ensure the following Secrets are set in your Space Settings:
- `HF_TOKEN`: Required for downloading models from private repositories.
- `SUPABASE_URL`: Your Supabase project URL.
- `SUPABASE_KEY`: Your Supabase anonymous/service key.
- `JWT_SECRET`: For authentication.

## 🎬 Video Playback Optimization
All annotated videos are processed through FFmpeg with the following settings for maximum browser compatibility:
- **Codec**: libx264
- **Pixel Format**: yuv420p
- **Dimensions**: Forced to even values (H.264 requirement)
- **Streaming**: `+faststart` enabled for instant playback.