Create utils/model.py

utils/model.py

@@ -0,0 +1,28 @@
+from transformers import pipeline, AutoModelForTimeSeriesPrediction
+import torch
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+def predict_umkm(data):
+    # Load model TTM
+    ttm = AutoModelForTimeSeriesPrediction.from_pretrained(
+        "ibm/granite-ttm-r2"
+    ).to(device)
+    
+    # Prediksi demand
+    inputs = {"values": data['demand'].tolist()}
+    demand_pred = ttm.generate(**inputs, max_length=7)
+    
+    # Rekomendasi dengan Chronos-T5
+    chronos = pipeline(
+        "text-generation", 
+        model="amazon/chronos-t5-small",
+        device=device
+    )
+    prompt = f"""
+    Data UMKM:
+    - Prediksi demand: {demand_pred}
+    - Stok saat ini: {data['supply'].iloc[-1]}
+    Beri rekomendasi dalam 1 kalimat:
+    """
+    return chronos(prompt, max_length=50)[0]['generated_text']