refactor: replace tutorial-style messages with production-grade log output

- app.py: startup prints now use [INFO]/[ERROR] prefixes; HTTP 500 error
message changed from instructional text to a concise service-status string
- Dockerfile: removed platform-specific annotation comments, replaced with
neutral infrastructure rationale

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

Dockerfile

@@ -1,7 +1,7 @@
 # PV Defect Classifier — HuggingFace Spaces
 FROM python:3.11-slim
 
-# HuggingFace requirement: UID 1000 non-root user
+# Run as non-root user (UID 1000) per container security best practices
 RUN useradd -m -u 1000 user
 
 WORKDIR /app
@@ -22,6 +22,6 @@ USER user
 ENV HOME=/home/user \
     PATH=/home/user/.local/bin:$PATH
 
-# HuggingFace Spaces requires port 7860
+# Bind to container-configured application port 7860
 # 1 worker = 1 model copy in memory; timeout 120s for cold start
 CMD ["gunicorn", "--bind", "0.0.0.0:7860", "--workers", "1", "--timeout", "120", "app:app"]

app.py

@@ -33,10 +33,10 @@ model_path = find_onnx_model()
 if model_path:
     session = ort.InferenceSession(model_path)
     input_name = session.get_inputs()[0].name
-    print(f"Loaded model: {os.path.basename(model_path)}")
+    print(f"[INFO] Model loaded: {os.path.basename(model_path)}")
 else:
     session = None
-    print(" No .onnx file found in /models — place your model there and restart.")
+    print("[ERROR] No ONNX model file found in MODEL_DIR. Inference endpoint will be unavailable.")
 
 
 #  Preprocessing
@@ -64,7 +64,7 @@ def index():
 @app.route("/predict", methods=["POST"])
 def predict():
     if session is None:
-        return jsonify({"error": "No model loaded. Put a .onnx file in /models."}), 500
+        return jsonify({"error": "Inference service unavailable: model not loaded."}), 500
 
     if "file" not in request.files:
         return jsonify({"error": "No file uploaded."}), 400