Update Dockerfile

Dockerfile

@@ -1,98 +1,21 @@
-from flask import Flask, request, jsonify, make_response
-import joblib, pandas as pd, numpy as np, os, sys, time
+FROM python:3.10-slim
 
-app = Flask(__name__)
+# Prevent buffering & control thread usage
+ENV PYTHONUNBUFFERED=1
+ENV OMP_NUM_THREADS=1 OPENBLAS_NUM_THREADS=1 MKL_NUM_THREADS=1 NUMEXPR_NUM_THREADS=1
 
-# -----------------------------
-# Config & Model Loading
-# -----------------------------
-MODEL_PATH = os.getenv("MODEL_PATH", "best_model_random_forest.joblib")
-PORT = int(os.getenv("PORT", "5000"))
+ARG BUILD_ID=10
+WORKDIR /app
 
-print(f"==> [BOOT] Starting Flask app on port {PORT}")
-print(f"==> [BOOT] MODEL_PATH={MODEL_PATH}", flush=True)
+# Install dependencies
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
 
-def load_pipeline(path: str):
-    start = time.time()
-    if not os.path.exists(path):
-        raise FileNotFoundError(f"Model file not found: {path}")
-    print(f"==> [LOAD] Loading model from {path} ...", flush=True)
-    model_obj = joblib.load(path)
-    if isinstance(model_obj, dict) and "pipeline" in model_obj:
-        pipe = model_obj["pipeline"]
-        print("==> [LOAD] Loaded dict bundle with 'pipeline'", flush=True)
-    else:
-        pipe = model_obj
-        print("==> [LOAD] Loaded pipeline object", flush=True)
-    print(f"==> [LOAD] Model load complete in {time.time()-start:.2f}s", flush=True)
-    return pipe
+# Copy app & model (make sure this filename matches your artifact)
+COPY app.py best_model_random_forest.joblib ./
+ENV MODEL_PATH=best_model_random_forest.joblib
 
-try:
-    pipe = load_pipeline(MODEL_PATH)
-    MODEL_READY, LOAD_ERROR = True, None
-except Exception as e:
-    print(f"==> [ERROR] Model load failed: {e}", file=sys.stderr, flush=True)
-    pipe, MODEL_READY, LOAD_ERROR = None, False, str(e)
+EXPOSE 7860
 
-# -----------------------------
-# Basic CORS (no external deps)
-# -----------------------------
-@app.after_request
-def add_cors_headers(resp):
-    resp.headers["Access-Control-Allow-Origin"] = "*"
-    resp.headers["Access-Control-Allow-Headers"] = "Content-Type, Authorization"
-    resp.headers["Access-Control-Allow-Methods"] = "GET, POST, OPTIONS"
-    return resp
-
-# -----------------------------
-# Health & Root
-# -----------------------------
-@app.get("/")
-def root():
-    return jsonify({
-        "service": "SuperKart Sales Forecast API",
-        "health": "/health",
-        "predict": "/predict",
-        "model_path": MODEL_PATH
-    })
-
-@app.get("/health")
-def health():
-    if MODEL_READY:
-        return jsonify({"status": "ok", "model_path": MODEL_PATH}), 200
-    return jsonify({"status": "error", "error": LOAD_ERROR, "model_path": MODEL_PATH}), 500
-
-# -----------------------------
-# Prediction
-# -----------------------------
-@app.route("/predict", methods=["OPTIONS"])
-def predict_options():
-    return make_response(("", 204))
-
-@app.post("/predict")
-def predict():
-    if not MODEL_READY or pipe is None:
-        return jsonify({"error": "Model not loaded", "details": LOAD_ERROR}), 503
-
-    try:
-        data = request.get_json(force=True)
-        if isinstance(data, dict):
-            df = pd.DataFrame([data])
-        elif isinstance(data, list):
-            df = pd.DataFrame(data)
-        else:
-            return jsonify({"error": "Invalid input. Must be JSON object or list of objects."}), 400
-
-        preds = pipe.predict(df)
-        preds = [float(p) if isinstance(p, (np.floating, float, int)) else p for p in preds]
-        return jsonify({"predictions": preds})
-
-    except Exception as e:
-        return jsonify({"error": "Prediction failed", "details": str(e)}), 500
-
-# -----------------------------
-# Entry Point
-# -----------------------------
-if __name__ == "__main__":
-    print("==> [RUN] Flask dev server starting...", flush=True)
-    app.run(host="0.0.0.0", port=PORT)
+# ✅ Use $PORT (Hugging Face default) instead of fixed 5000
+CMD ["sh", "-c", "gunicorn -w 2 -k gthread --threads 2 --timeout 120 -b 0.0.0.0:$PORT app:app"]