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---
title: Predictive Maintenance Engine Classifier
emoji: 🔧
colorFrom: blue
colorTo: green
sdk: docker
app_port: 7860
pinned: false
---
# Predictive Maintenance Engine Classifier
This Hugging Face Space serves a Random Forest model for binary engine-condition prediction.
## Configuration
| Name | Default | Purpose |
|---|---:|---|
| `APP_HOST` | `0.0.0.0` | Host used by the Streamlit server. |
| `APP_PORT` | `7860` | Port exposed by the Docker container and Hugging Face Space. |
| `HF_MODEL_REPO` | `saranka85/predictive-maintenance-random-forest` | Hugging Face model repository containing `model.joblib`. |
| `HF_MODEL_FILENAME` | `model.joblib` | Model artifact filename inside the model repository. |
| `HF_TOKEN` | optional | Required only if the model repository or Space is private. |
| `PREDICTION_LOG_DIR` | `/tmp/prediction_logs` | Runtime directory where submitted inputs are appended as CSV. |
| `ENGINE_CLASS_0_LABEL` | `Requires Maintenance` | Display label for `engine_condition = 0`. |
| `ENGINE_CLASS_1_LABEL` | `Operating Normally` | Display label for `engine_condition = 1`. |
The app accepts six raw engine sensor values, saves them into a DataFrame, creates the engineered training features, loads the model from the Hugging Face Model Hub, and returns a maintenance decision:
- `Requires Maintenance`
- `Operating Normally`
The raw `engine_condition` class is still shown for traceability.