make code MCP compatible

app.py

@@ -5,8 +5,20 @@ import spaces
 import os
 from huggingface_hub import hf_hub_download
 
-# Helper function to download models from Hugging Face
 def get_model_path(model_name):
+    """
+    Downloads a specified model from the 'atalaydenknalbant/budgerigar_models'
+    Hugging Face repository and returns its local cached path.
+
+    This helper function streamlines the process of fetching model weights
+    from the Hugging Face Hub, ensuring the model is available locally for use.
+
+    Args:
+        model_name (str): The filename of the model to download (e.g., 'budgerigar_yolo11x.pt').
+
+    Returns:
+        str: The file path to the locally downloaded model.
+    """
     model_cache_path = hf_hub_download(
         repo_id="atalaydenknalbant/budgerigar_models", 
         filename=model_name
@@ -15,6 +27,30 @@ def get_model_path(model_name):
 
 @spaces.GPU
 def yolo_inference(images, model_id, conf_threshold, iou_threshold, max_detection):
+    """
+    Performs budgerigar gender determination inference on an image using a selected YOLO or RTDETR model.
+
+    This function handles input images, loads the appropriate model (YOLO or RTDETR)
+    based on the `model_id`, and then runs inference to detect budgerigars and
+    determine their gender. The results are then plotted onto the original image.
+    If no image is provided, it returns a blank image with a message.
+
+    Args:
+        images (PIL.Image.Image or None): The input image on which to perform detection.
+                                          Can be None if no image is uploaded.
+        model_id (str): The identifier of the model to use (e.g., 'budgerigar_yolo11x.pt',
+                        'budgerigar_rtdetr-x.pt').
+        conf_threshold (float): The confidence threshold for filtering detections.
+                                Detections with confidence below this value are discarded.
+        iou_threshold (float): The Intersection over Union (IoU) threshold for
+                               Non-Maximum Suppression (NMS) to remove overlapping detections.
+        max_detection (int): The maximum number of detections to return and display.
+
+    Returns:
+        PIL.Image.Image: The input image annotated with detection results, including
+                         bounding boxes and gender labels. Returns a blank image
+                         with a message if no input image is provided.
+    """
     if images is None:
         # Create a blank image
         width, height = 640, 480
@@ -85,4 +121,4 @@ interface = gr.Interface(
         ["Female.png", "budgerigar_yolo11x.pt", 0.25, 0.45, 300],
     ],
 )
-interface.launch()
+interface.launch(mcp_server=True)