Update app/main.py

Add compressed image support with 2-3MB target file size - Add Compressed_Image_URL field to colorize endpoint response - Implement compress_image_to_target_size function with iterative quality/dimension adjustment - Original download_url returns uncompressed PNG (model output) - Compressed_Image_URL returns JPEG compressed to 2-3MB file size

Update app/main.py

Set fixed caption text for /colorize responses

Add CORS middleware to main.py for auth endpoints

Fix Firebase import handling in auth endpoints - Ensure firebase_admin is always defined - Fix Firebase initialization checks - Improve error messages

Add auth endpoints to main.py - Add /auth/register, /auth/login, /auth/me, /auth/refresh endpoints - Add Pydantic models for auth requests/responses - Add verify_request function for Firebase auth - Import httpx for Firebase REST API calls

Update health endpoint to match requested format with hf_inference_api and fal-ai

Update response formats for /colorize and /health endpoints - /colorize: Add filename, caption, change to PNG format, api_download_url - /health: Add model_type and provider fields

Make CCO model default for colorization - Change default model from GAN (dummy) to CCO (working) - Add fallback to GAN if CCO not available - Fix image format and saving issues

Remove model_used field from response to maintain original response format

Integrate CCO colorization models (eccv16 and siggraph17) - Add CCO colorizers module from kinsung/cco - Update /colorize endpoint to support model selection parameter - Add scikit-image dependency - Maintain backward compatibility with existing GAN model - Update MongoDB logging to track model type used

Add success/failure logging to colorizations collection

Update default fallback category ID to 69368fcd2e46bd68ae1889b2

Fix empty string handling and support both subCategories and categories schemas

Add MongoDB media click logging with per-user category counts

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

Add MongoDB integration for API call logging with timestamps

Update app/main.py

Update app/main.py

Update app/main.py

Update app/main.py

Update app/main.py

Update app/main.py

Update app/main.py

Update app/main.py

Update app/main.py

Fix Gradio permission error by setting GRADIO_TEMP_DIR to /tmp

Add fallback logic to handle PyTorch models and find actual model files - Add manual download fallback when from_pretrained_fastai fails - List repository files to find .pkl or .pt files - Provide clear error message for PyTorch models

Integrate FastAI colorization with Firebase auth and Gradio UI - Replace main.py with FastAI implementation - Add Gradio interface for Space UI - Add Firebase authentication to /colorize endpoint - Add curl examples documentation - Update test.py with User-Agent headers

Fix cache directory permissions and OMP_NUM_THREADS warnings - Set HF cache env vars before imports - Set MPLCONFIGDIR for matplotlib - Fix OMP_NUM_THREADS in Dockerfile

Switch to FastAI GAN colorization model (Hammad712/GAN-Colorization-Model)

Update cache paths to use /tmp

Align pipeline with text-guided colorization Space

Fix colorize pipeline call and fallback storage directories

Fix model loading: use /data for HF cache directory instead of /app/data

fix(runtime): use /data for uploads/results and write Firebase creds to /data; set DATA_DIR and OMP_NUM_THREADS

update Postman collection

Deploy: HF cache dir, img2img fallback, auth bypass, root route

feat(auth): accept Firebase Auth id_token (Authorization Bearer) in addition to App Check; add Postman collection and test script; default MODEL_ID to ControlNet color

Remove unused cv2 import and pin numpy version for compatibility

Initial commit: Colorize API with Firebase App Check integration