===================
Global Architecture
===================

:Authors:
    Cao Tri DO <cao-tri.do@keyrus.com>
:Version: 2025-09

.. admonition:: Objectives
    :class: important

    This article is intended to provide a comprehensive overview of the global architecture of the solution.

.. mermaid::

    graph TD
        A["📦 Data Source (Kaggle / Local)"] -->|📤 Upload| B["🗄️ Databricks Volume (Raw Data)"]
        B -->|"🧹 Cleaning & Preprocessing<br>(scripts/run_cleanup_data.py, data/cleanup.py)"| C["🧪 Data Processing (Feature Engineering)"]
        C -->|✂️ Train / Test Split| D["🧠 MLflow Experiment<br>(train_register_model.py)"]
        D -->|📊 Track Experiments & Metrics| E["📈 MLflow Tracking Server"]
        E -->|🏷️ Model Versioning| F["📚 MLflow Model Registry"]
        F -->|🚀 Deployment & Integration| G["☁️ Databricks Workspace (Dev / Acc / Prod)"]
        G -->|📊 Monitoring & Reporting| H["📉 Dashboard / Visualization (vizualization/)"]

        subgraph "🧰 Tooling & Environment"
            I["🧩 Devbox + UV + Taskfile (Reproducibility & Environments)"]
            J["⚙️ GitHub / GitLab CI-CD (Automated CI/CD)"]
            K["🧼 Pre-commit / Ruff / Commitizen (Code Quality & Standardization)"]
        end

        I --> G
        J --> G
        K --> G

        style A fill:#e6f7ff,stroke:#007acc,stroke-width:2px
        style B fill:#e6f7ff,stroke:#007acc,stroke-width:2px
        style C fill:#e6f7ff,stroke:#007acc,stroke-width:2px
        style D fill:#fff2cc,stroke:#f1c232,stroke-width:2px
        style E fill:#fff2cc,stroke:#f1c232,stroke-width:2px
        style F fill:#d9ead3,stroke:#6aa84f,stroke-width:2px
        style G fill:#d9ead3,stroke:#6aa84f,stroke-width:2px
        style H fill:#d9ead3,stroke:#6aa84f,stroke-width:2px
        style I fill:#f9cb9c,stroke:#e69138,stroke-width:2px
        style J fill:#f9cb9c,stroke:#e69138,stroke-width:2px
        style K fill:#f9cb9c,stroke:#e69138,stroke-width:2px