refactor(model_loader): update dataset names for model registrations in the loader

refactor(logging): move CustomFormatter to agent_logger and update log handlers

major(feat): per-agent logging system with AgentLogger class

Load environment variables from .env file in hf_logger.py

fix: add model paths and class names for ONNX models in model_loader

fix: add missing import for postprocess_onnx_output in model_loader

fix: add missing import for infer_onnx_model in model_loader and update its definition in onnx_helpers

fix: add missing import for infer_onnx_model in model_loader

fix: add missing import for preprocess_onnx_input in model_loader

feat: implement model registration logic for ONNX, HuggingFace, and Gradio API

refactor: extract Gradio logging setup into a separate module

refactor: ONNX model loading and caching functions

feat: add Gradio API integration and ONNX preprocessing functions

major(refactor): prep for refactor project

sync (#2)

fix: ensure Hugging Face API token is used for dataset repository initialization

feat: implement CommitScheduler for automated logging to Hugging Face dataset and refactor dataset initialization process

fix: enable dataset logging to Hugging Face Hub by uncommenting push_to_hub functionality

feat: implement custom JSON encoder for numpy types and ensure type consistency in inference results

feat: improve JSON handling and type safety in inference results and dataset logging

feat: add detailed logging for input types in inference data processing

feat: enhance image handling by ensuring input is a PIL Image and updating forensic image logging

major(feat): restructure models and introduce new monitoring and weight management agents

feat: add logging

make clear distinction between ensemble agents and smart agents

major: prep implementtation of vLLM smart agents

cv2

(major)feat: add new functionalities for AI-generated content detection

UPDATED: Updated ELA image processing in app.py and ela.py

🏗️ build(utils): update image preprocess and functionality expansion

```

🐛 fix(image processing): ensure image consistency for gradient and minmax preprocessors

✨ feat(image processing): add MinMax pre-processing to image pipeline

✨ feat(image): add gradient processing in predict_image Function

✨ feat(predict): add Error Level Analysis to image prediction

✨ feat(ui): add sharpen and noise augmentation

🐛 fix(app): add input degrees having a bug for cases without augmentation

♻️ refactor(app): code cleanup

Refactor project interface and remove unused utility files

Refine UI layout and GOAT inference call

Update utils/goat.py

Update utils/goat.py

Create __init__.py

Create goat.py

Create utils/onnx.py