test4
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Commit History
test3
7df11bc
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test2
87da6f6
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test
c7db87b
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fix: add model paths and class names for ONNX models in model_loader
a4381af
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fix: add missing import for postprocess_onnx_output in model_loader
0adef02
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fix: add missing import for infer_onnx_model in model_loader and update its definition in onnx_helpers
ceff40b
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fix: add missing import for infer_onnx_model in model_loader
3232315
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fix: add missing import for preprocess_onnx_input in model_loader
eeb602e
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refactor: consolidate model registration logic for ONNX and Gradio API
59627db
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feat: implement model registration logic for ONNX, HuggingFace, and Gradio API
f00c873
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fix: update ONNX model cache handling in inference functions
fccbc0f
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refactor: extract Gradio logging setup into a separate module
68f9986
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refactor: ONNX model loading and caching functions
80c3f0c
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feat: add Gradio API integration and ONNX preprocessing functions
4cb6734
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major(refactor): prep for refactor project
6555f50
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Update README.md
ba1f85f
verified
Update app_mcp.py
4274392
verified
docs: enhance docstring for Bit Plane Extractor interface to improve clarity and usability
0457419
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refactor: update API names for prediction functions to improve clarity and consistency
392abb7
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fix: update demo launch configuration to enable MCP server mode
6432eef
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feat: add API names to prediction functions and update README title for clarity
2f1900e
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fix: ensure Hugging Face API token is used for dataset repository initialization
f69af75
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fix: update dataset name for improved clarity and consistency in logging
489bc21
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fix: update dataset privacy settings and enable token usage for Hugging Face dataset logging
1cbfb0b
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feat: implement CommitScheduler for automated logging to Hugging Face dataset and refactor dataset initialization process
5967d4d
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fix: enable dataset logging to Hugging Face Hub by uncommenting push_to_hub functionality
87fc2bb
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feat: implement custom JSON encoder for numpy types and ensure type consistency in inference results
0f427f3
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feat: improve JSON handling and type safety in inference results and dataset logging
febce11
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feat: add detailed logging for input types in inference data processing
679e047
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feat: enhance image handling by ensuring input is a PIL Image and updating forensic image logging
d20c076
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refactor: reorganize agent structure by moving models to agents directory, update logging level, and enhance .gitignore for model files
c1d03da
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fix: extract prediction label for accurate weight management in consensus calculation
91479f7
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feat: integrate dotenv for environment variable management and update weight management logic for prediction handling
73783f9
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fix: store full result dictionary in model predictions for enhanced data tracking
d7aaf8c
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fix: correct string formatting in anomaly detection logging
e8835e7
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chore: fix deps naming
7812ef2
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fix: update .gitignore and requirements.txt for Python version compatibility and correct package names
5bd979e
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major(feat): restructure models and introduce new monitoring and weight management agents
ae1c2a2
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feat: rename app file for confusion
bb30d5b
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feat: add logging
58f23d5
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make clear distinction between ensemble agents and smart agents
8f7f87a
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major: prep implementtation of vLLM smart agents
1af0cb5
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dep: psutil
a986afb
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major: testing out first implentation of an ensemble team
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a
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woops
b919494
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pls fix dev mode T_T
16601a0
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cv2
32d1ae3
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