Configure FastAPI Docker Space

Dockerfile

@@ -2,14 +2,12 @@ FROM python:3.12-slim
 
 WORKDIR /app
 
-COPY pyproject.toml uv.lock ./
+COPY . .
 
 RUN pip install --no-cache-dir uv \
     && uv pip install --system . \
     && uv pip install --system pytest pytest-cov
 
-COPY . .
-
-EXPOSE 8000
+EXPOSE 7860
 
-CMD ["uvicorn", "serving.api:app", "--host", "0.0.0.0", "--port", "8000"]
+CMD ["uvicorn", "serving.api:app", "--host", "0.0.0.0", "--port", "7860"]

README.md

@@ -1,12 +1,10 @@
 ---
-title: MLOps End2end MSDS2026
-emoji: 💻
+title: MLOps End2end API
+emoji: 🚀
 colorFrom: blue
 colorTo: green
-sdk: gradio
-sdk_version: "4.42.0"
-python_version: "3.12"
-app_file: app.py
+sdk: docker
+app_port: 7860
 pinned: false
 ---
 

serving/api.py

@@ -43,7 +43,10 @@ def _load_artifacts() -> None:
     if META_PATH.exists():
         meta = json.loads(META_PATH.read_text())
         _feature_cols = meta["feature_cols"]
-        _scaler = joblib.load(meta["scaler_path"])
+        scaler_path = Path(meta["scaler_path"])
+        if not scaler_path.exists():
+            scaler_path = MODELS_DIR / scaler_path.name
+        _scaler = joblib.load(scaler_path)
     else:
         raise RuntimeError("feature_meta.json not found — run the Dagster pipeline first.")
 
@@ -88,6 +91,16 @@ def health() -> dict:
     return {"status": "ok", "model_loaded": _model is not None}
 
 
+@app.get("/")
+def root() -> dict:
+    return {
+        "service": "Computer Durability Classifier API",
+        "health": "/health",
+        "docs": "/docs",
+        "predict": "/predict",
+    }
+
+
 @app.get("/info")
 def model_info() -> dict:
     if INFO_PATH.exists():