I generated an interactive diagram for the pygod project

[ivanmilevtues]

Hey, all I've always wanted to contribute to open-source projects. But at the very begining I found it a bit too difficult to navigate them and wrap my head around on the main flow and the main "logical" components. That is why I started working on a project to help people like me, who are visual learners. The project generates an interactive diagram starting from the highest level of abstraction and allows you to dive deeper into interesting components.

This is the highest level of abstraction for the pygod project:

graph LR
    Data_Loading_Management["Data Loading & Management"]
    Data_Preprocessing_Graph_Utilities["Data Preprocessing & Graph Utilities"]
    Base_Detector_API["Base Detector API"]
    Specific_Detector_Implementations["Specific Detector Implementations"]
    Neural_Network_Modules["Neural Network Modules"]
    Score_Post_processing_Prediction["Score Post-processing & Prediction"]
    Data_Loading_Management -- "supplies raw graph data to" --> Data_Preprocessing_Graph_Utilities
    Data_Preprocessing_Graph_Utilities -- "provides processed graph data to" --> Base_Detector_API
    Base_Detector_API -- "orchestrates lifecycle for" --> Specific_Detector_Implementations
    Specific_Detector_Implementations -- "utilizes" --> Neural_Network_Modules
    Neural_Network_Modules -- "returns scores/embeddings to" --> Specific_Detector_Implementations
    Specific_Detector_Implementations -- "provides raw scores to" --> Score_Post_processing_Prediction
    Base_Detector_API -- "orchestrates final prediction with" --> Score_Post_processing_Prediction
    click Data_Preprocessing_Graph_Utilities href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/pygod/Data_Preprocessing_Graph_Utilities.md" "Details"
    click Specific_Detector_Implementations href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/pygod/Specific_Detector_Implementations.md" "Details"
    click Neural_Network_Modules href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/pygod/Neural_Network_Modules.md" "Details"
    click Score_Post_processing_Prediction href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/pygod/Score_Post_processing_Prediction.md" "Details"

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The generation tool is based on Static Analysis and LLMs and is fully open-source: https://github.com/CodeBoarding/CodeBoarding

You can see the full diagram here: https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/pygod/on_boarding.md

Any feedback is appreciated! Would love to hear your opinion on diagrams as an exploration tooling and diagram first documentation!