Update app.py

app.py

@@ -62,51 +62,6 @@ async def health():
         "service": "NASA SpaceApp API"
     }
 
-@app.get("/debug/files")
-async def debug_files():
-    """Endpoint de debug para listar archivos disponibles"""
-    current_dir = os.getcwd()
-    files_info = {
-        "current_directory": current_dir,
-        "files_in_root": [],
-        "directories": [],
-        "csv_files_found": []
-    }
-    
-    try:
-        # Listar contenido del directorio actual
-        for item in os.listdir(current_dir):
-            item_path = os.path.join(current_dir, item)
-            if os.path.isfile(item_path):
-                files_info["files_in_root"].append(item)
-            elif os.path.isdir(item_path):
-                files_info["directories"].append(item)
-        
-        # Buscar archivos CSV recursivamente
-        for root, dirs, files in os.walk(current_dir):
-            for file in files:
-                if file.endswith('.csv'):
-                    full_path = os.path.join(root, file)
-                    relative_path = os.path.relpath(full_path, current_dir)
-                    files_info["csv_files_found"].append({
-                        "filename": file,
-                        "relative_path": relative_path,
-                        "full_path": full_path,
-                        "size_mb": round(os.path.getsize(full_path) / (1024*1024), 2)
-                    })
-        
-        # Verificar si la carpeta NASA_datasets existe
-        nasa_dir = os.path.join(current_dir, "NASA_datasets")
-        files_info["nasa_datasets_exists"] = os.path.exists(nasa_dir)
-        
-        if files_info["nasa_datasets_exists"]:
-            files_info["nasa_datasets_files"] = os.listdir(nasa_dir)
-        
-    except Exception as e:
-        files_info["error"] = str(e)
-    
-    return files_info
-
 @app.post("/predict", response_model=PredictResponse)
 def predict(
     req: PredictRequest,
@@ -160,47 +115,9 @@ def predict(
 def load_csv_dataset(filename: str) -> pd.DataFrame:
     """Carga un CSV de NASA con manejo de comentarios y errores"""
     try:
-        # Intentar diferentes ubicaciones posibles
-        possible_paths = [
-            os.path.join("NASA_datasets", filename),  # Ubicación local
-            filename,  # Directamente en el directorio raíz
-            os.path.join(".", filename),  # Explícitamente en directorio actual
-            os.path.join(os.getcwd(), "NASA_datasets", filename),  # Ruta absoluta
-            os.path.join(os.getcwd(), filename),  # Ruta absoluta directa
-        ]
-        
-        # Intentar cada ruta hasta que una funcione
-        for filepath in possible_paths:
-            if os.path.exists(filepath):
-                print(f"Loading dataset from: {filepath}")
-                df = pd.read_csv(filepath, comment='#')
-                return df
-        
-        # Si ninguna ruta funciona, listar contenido del directorio para debug
-        current_dir = os.getcwd()
-        print(f"Current directory: {current_dir}")
-        print(f"Files in current directory: {os.listdir(current_dir)}")
-        
-        # Buscar archivos CSV recursivamente
-        csv_files = []
-        for root, dirs, files in os.walk(current_dir):
-            for file in files:
-                if file.endswith('.csv'):
-                    csv_files.append(os.path.join(root, file))
-        
-        print(f"CSV files found: {csv_files}")
-        
-        # Intentar encontrar el archivo por nombre
-        for csv_path in csv_files:
-            if filename in csv_path:
-                print(f"Found matching file: {csv_path}")
-                df = pd.read_csv(csv_path, comment='#')
-                return df
-                
-        raise FileNotFoundError(f"Dataset {filename} not found in any location. Searched paths: {possible_paths}")
-        
-    except FileNotFoundError as e:
-        raise HTTPException(500, f"Error loading dataset {filename}: {str(e)}")
+        filepath = os.path.join("NASA_datasets", filename)
+        df = pd.read_csv(filepath, comment='#')
+        return df
     except Exception as e:
         raise HTTPException(500, f"Error loading dataset {filename}: {str(e)}")