Update handler.py

handler.py

@@ -16,28 +16,28 @@ class EndpointHandler:
         self.model_path = 'DAMO-NLP-SG/VideoLLaMA2-7B'
         self.model, self.processor, self.tokenizer = model_init(self.model_path)
 
-def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
-    print(f"Received data: {data}")  # Debugging: Print received data
-
-    modal = data.get("modal", "video")
-    modal_path = data.get("modal_path", "")
-    instruct = data.get("instruct", "")
-
-    print(f"Modal: {modal}, Modal Path: {modal_path}, Instruct: {instruct}")  # Debugging: Print extracted values
-
-    if not modal_path or not instruct:
-        raise ValueError("Both 'modal_path' and 'instruct' must be provided in the input data.")
-
-    # Perform inference
-    output = mm_infer(
-        self.processor[modal](modal_path), 
-        instruct, 
-        model=self.model, 
-        tokenizer=self.tokenizer, 
-        do_sample=False, 
-        modal=modal
-    )
-
-    return [{"output": output}]
+    def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
+        print(f"Received data: {data}")  # Debugging: Print received data
+    
+        modal = data.get("modal", "video")
+        modal_path = data.get("modal_path", "")
+        instruct = data.get("instruct", "")
+    
+        print(f"Modal: {modal}, Modal Path: {modal_path}, Instruct: {instruct}")  # Debugging: Print extracted values
+    
+        if not modal_path or not instruct:
+            raise ValueError("Both 'modal_path' and 'instruct' must be provided in the input data.")
+    
+        # Perform inference
+        output = mm_infer(
+            self.processor[modal](modal_path), 
+            instruct, 
+            model=self.model, 
+            tokenizer=self.tokenizer, 
+            do_sample=False, 
+            modal=modal
+        )
+    
+        return [{"output": output}]