# sukstudent/ibm_csrbox architecture

> Architecture diagram of the GitHub repository sukstudent/ibm_csrbox, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-09-28). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/sukstudent/ibm_csrbox
- Repository: https://github.com/sukstudent/ibm_csrbox

## Overview

This repository provides a Streamlit application for entering space-mission details and predicting an outcome with a saved Random Forest model. The README also describes dataset preprocessing, feature engineering, model comparison, and evaluation, but the corresponding training source and dataset are not present in the supplied tree, so their wiring cannot be established. The prediction implementation is excerpted only partially.

Main entry points: [`app.py`](https://github.com/sukstudent/ibm_csrbox/blob/main/app.py) (Streamlit application), [`space_mission_model.pkl`](https://github.com/sukstudent/ibm_csrbox/blob/main/space_mission_model.pkl) (Random Forest model)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_interface["User interface"]
  node_app["Streamlit application<br/>[app.py]"]
  node_mission_form["Mission details form<br/>[app.py]"]
  node_result_view["Prediction result<br/>[app.py]"]
end

subgraph group_inference["Prediction"]
  node_inference["Outcome inference<br/>[app.py]"]
  node_model["Random Forest model"]
end

subgraph group_model_development["Model development"]
  node_training_workflow["Preprocess, train, evaluate"]
end

node_user(("Mission user"))

node_user -->|"uses"| node_app
node_app -->|"renders"| node_mission_form
node_mission_form -->|"submits details"| node_inference
node_app -->|"loads"| node_model
node_inference -->|"predicts with"| node_model
node_inference -->|"returns outcome"| node_result_view
node_result_view -->|"displays"| node_user

click node_app "https://github.com/sukstudent/ibm_csrbox/blob/main/app.py"
click node_mission_form "https://github.com/sukstudent/ibm_csrbox/blob/main/app.py"
click node_result_view "https://github.com/sukstudent/ibm_csrbox/blob/main/app.py"
click node_inference "https://github.com/sukstudent/ibm_csrbox/blob/main/app.py"
click node_model "https://github.com/sukstudent/ibm_csrbox/blob/main/space_mission_model.pkl"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_app,node_mission_form,node_result_view,node_user toneBlue
class node_inference,node_model toneAmber
class node_training_workflow toneMint
```

## Components

### User interface

- [Streamlit application](https://github.com/sukstudent/ibm_csrbox/blob/main/app.py): `app.py`
- [Mission details form](https://github.com/sukstudent/ibm_csrbox/blob/main/app.py): `app.py`
- [Prediction result](https://github.com/sukstudent/ibm_csrbox/blob/main/app.py): `app.py`

### Prediction

- [Outcome inference](https://github.com/sukstudent/ibm_csrbox/blob/main/app.py): `app.py`
- [Random Forest model](https://github.com/sukstudent/ibm_csrbox/blob/main/space_mission_model.pkl): `space_mission_model.pkl`

### Model development

- **Preprocess, train, evaluate**

### Other components

- **Mission user**

## Connections

- Mission user → Streamlit application: uses
- Streamlit application → Mission details form: renders
- Mission details form → Outcome inference: submits details
- Streamlit application → Random Forest model: loads
- Outcome inference → Random Forest model: predicts with
- Outcome inference → Prediction result: returns outcome
- Prediction result → Mission user: displays