Update app.py

app.py

@@ -13,14 +13,24 @@ image_to_text = pipeline("image-to-text", model="Salesforce/blip-image-captionin
 def generate_recipe(description):
     url = "https://api-inference.huggingface.co/models/Qwen/Qwen2.5-72B-Instruct"
     headers = {"Authorization": f"Bearer {hf_token}"}
-    # Reformulamos el prompt para que sea más específico
+    
+    # Añade el system input para definir el rol del modelo
+    system_input = (
+        "Act as a professional chef. Your task is to explain to a regular person "
+        "how to cook a given dish, providing a step-by-step guide and a list of ingredients with exact quantities."
+    )
+    
     prompt = (
-        f"Provide a full recipe for a dish described as: {description}. "
-        "Include a list of ingredients and detailed step-by-step instructions."
+        f"{system_input} The dish is described as: {description}. "
+        "Provide a list of ingredients followed by detailed cooking instructions."
     )
+    
     payload = {
         "inputs": prompt,
-        "parameters": {"max_length": 5000}  # Increase max_length for a more detailed response
+        "parameters": {
+            "max_length": 5000,   # Maximum length for the response
+            "min_length": 2000     # Minimum length for the response
+        }
     }
 
     response = requests.post(url, headers=headers, json=payload)