Update app.py

app.py

@@ -12,7 +12,7 @@ import requests
 
 app = FastAPI()
 
-# Hugging Face Dataset URL
+# ✅ Correct Hugging Face Dataset URL
 DATASET_URL = "https://huggingface.co/datasets/SailajaS/CDART/resolve/main/train.csv"
 
 # File path for saving dataset
@@ -21,31 +21,28 @@ DATASET_PATH = "dataset.csv"
 # Function to download dataset
 def download_dataset():
     if not os.path.exists(DATASET_PATH):
+        print("📥 Downloading dataset...")
         response = requests.get(DATASET_URL)
+        
         if response.status_code == 200:
             with open(DATASET_PATH, "wb") as file:
                 file.write(response.content)
             print("✅ Dataset downloaded successfully!")
         else:
-            raise Exception(f"❌ Failed to download dataset: {response.status_code}")
-
-# Function to load dataset
-def load_data(file_path):
-    df = pd.read_csv(file_path)  # Load CSV directly
-    return df
-
-# Placeholder for dataset and model
-df = None
-model = None
-encoder = LabelEncoder()
+            print(f"❌ Failed to download dataset: {response.status_code}")
+            return False
+    return True
 
 # Download dataset at startup
-download_dataset()
+dataset_downloaded = download_dataset()
+if not dataset_downloaded:
+    raise Exception("❌ Unable to start app: Dataset download failed.")
 
 # Load dataset
-df = load_data(DATASET_PATH)
+df = pd.read_csv(DATASET_PATH)
 
 # Encode categorical variables
+encoder = LabelEncoder()
 df["Case Problem"] = encoder.fit_transform(df["Case Problem"])
 df["Feedback"] = encoder.fit_transform(df["Feedback"])