Update app/database.py

Update app/database.py

Update app/database.py

Add ai_edit_daily_count tracking to media_clicks collection

Change ai_edit_last_date to MongoDB Date object format - Store as Date object instead of string format

Add ai_edit_complete and ai_edit_last_date to media_clicks collection

Add success/failure logging to colorizations collection

Only log to media_clicks when user_id is provided

Update default fallback category ID to 69368fcd2e46bd68ae1889b2

Set admin database name to adminPanel for media_clicks collection

Fix empty string handling and support both subCategories and categories schemas

Add MongoDB media click logging with per-user category counts

first commit

Delete README_HF.md

Delete .history

Delete MONGODB_DATA_STRUCTURE.md

Delete SETUP.md

Delete FIREBASE_SETUP.md

Delete FASTAI_MODEL_GUIDE.md

Delete DEPLOYMENT.md

Delete CURL_EXAMPLES.md

Delete API_EXAMPLES.md

Delete API_DOCUMENTATION.md

Fix MongoDB database boolean check - use 'is None' instead of truthiness

Add MongoDB test scripts and documentation (no credentials exposed)

Fix Gradio compatibility: remove show_copy_button parameter

Add MongoDB verification to test.py

Add MongoDB integration for API call logging with timestamps

Update Firebase initialization to auto-detect credentials file and add setup guide

Add Firebase email/password authentication endpoints - Add /auth/register endpoint for user registration - Add /auth/login endpoint with Firebase REST API integration - Add /auth/me endpoint to get current user info - Add /auth/refresh endpoint for token refresh - Integrate with existing Firebase App Check - Add httpx and email-validator dependencies

Add comprehensive cURL examples for API testing

Refactor to use Hugging Face Inference API with fal-ai provider - Replace local model loading with InferenceClient API - Remove heavy SDXL/ControlNet/BLIP model dependencies - Use FLUX.1-Kontext-dev model via API - Keep FastAPI and Firebase authentication - Significantly reduce memory usage (no local models)

Add memory optimizations for SDXL pipeline - Enable VAE slicing and tiling - Enable attention slicing for UNet and ControlNet - Use sequential CPU offloading for pipeline - Keep BLIP model on CPU to save GPU memory - Add torch.no_grad() and cache clearing - Reduce guidance scale for lower memory usage

Fix permission errors and environment variables for model loading - Use /tmp directory for writable model storage - Set OMP_NUM_THREADS and cache directories at startup - Add better error handling and permission checks

Add FastAPI version using SDXL + ControlNet for text-guided colorization (from fffiloni)

Improve health check and UI messaging for fallback mode

Improve fallback colorization with better color hints and saturation

Add simple colorization fallback using LAB color space when model fails to load

Update app/main.py

Update app/main.py

Clean up ResNetGenerator architecture - simplified structure

Fix: Try ResNet first, improve size validation, and skip configs with too many mismatches

Improve weight loading verification and skip configs with too many missing keys

Fix colorization: Add ResNet generator architecture and fix minimum image size to prevent kernel errors

Improve PyTorch colorizer: Better preprocessing, output handling, and debugging

Fix image colorization: Add PyTorch GAN colorizer fallback, update Dockerfile to use main_fastai, and add missing dependencies

Update app/main.py

Update app/main.py

Update requirements.txt

Update app/main.py