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dockerfile

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+# Read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
+# you will also find guides on how best to write your Dockerfile
+
+FROM python:3.9
+
+RUN useradd -m -u 1000 user
+USER user
+ENV PATH="/home/user/.local/bin:$PATH"
+
+WORKDIR /app
+
+COPY --chown=user ./requirements.txt requirements.txt
+RUN pip install --no-cache-dir --upgrade -r requirements.txt
+
+COPY --chown=user . /app
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

main.py

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+from fastapi import FastAPI, Request
+import pickle
+import numpy as np
+import os
+
+app = FastAPI(title="Shipment Delay Prediction API")
+
+# -------- Load ML model --------
+MODEL_PATH = "shipment_delay_model.pkl"
+model = None
+if os.path.exists(MODEL_PATH):
+    with open(MODEL_PATH, "rb") as f:
+        model = pickle.load(f)
+
+
+# -------- ML predictor --------
+def ml_score(features: dict) -> float:
+    arr = np.array([[
+        features.get("distance_km", 0.0),
+        features.get("hours_to_deadline", 0.0),
+        features.get("origin_rain_mm", 0.0),
+        features.get("origin_storm", 0),
+        features.get("congestion_index", 0.0),
+        features.get("carrier_reliability", 0.7),
+    ]])
+
+    if hasattr(model, "predict_proba"):  # classifier
+        return float(model.predict_proba(arr)[0][1])
+    return float(model.predict(arr)[0])  # regression
+
+
+# -------- API endpoints --------
+@app.get("/health")
+def health():
+    return {"status": "alive", "model_loaded": model is not None}
+
+@app.post("/predict")
+async def predict_endpoint(request: Request):
+    shipment = await request.json()
+    features = shipment.get("features", {})
+
+    if model is None:
+        return {"error": "Model not loaded on server."}
+
+    delay_prob = ml_score(features)
+    return {
+        "delay_prob": round(delay_prob, 3),
+        "risk_level": "HIGH" if delay_prob >= 0.6 else "MEDIUM" if delay_prob >= 0.3 else "LOW"
+    }

requirements.txt

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+fastapi
+uvicorn
+numpy
+scikit-learn==1.3.2

shipment_delay_model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:1428981ca03239b41646bcd68096a61996bfbc33fabc307386c6cb0b627013c2
+size 979878