Update app.py

app.py

@@ -39,12 +39,15 @@ def handle_image_submission(_chatbot, task_history, file):
     print("handle_image_submission called")
     if file is None:
         print("No file uploaded")
-        return _chatbot, task_history  
-    file_path = save_image(file, uploaded_file_dir) 
+        return _chatbot, task_history
+    print("File received:", file)
+    file_path = save_image(file, uploaded_file_dir)
+    print("File saved at:", file_path)
     history_item = ((file_path,), None)
     _chatbot.append(history_item)
     task_history.append(history_item)
     return predict(_chatbot, task_history)
+
     
 def _load_model_tokenizer(args):
     model_id = args.checkpoint_path
@@ -104,15 +107,15 @@ def _parse_text(text):
     return text
 
 def save_image(image_file, upload_dir):
+    print("save_image called with:", image_file)
     Path(upload_dir).mkdir(parents=True, exist_ok=True)
-    if image_file is not None:
-        filename = secrets.token_hex(10) + Path(image_file.name).suffix
-        file_path = Path(upload_dir) / filename
-        with open(file_path, "wb") as f:
-            f.write(image_file.read())
-        return str(file_path)
-    else:
-        return None
+    filename = secrets.token_hex(10) + Path(image_file.name).suffix
+    file_path = Path(upload_dir) / filename
+    print("Saving to:", file_path)
+    with open(image_file.name, "rb") as f_input, open(file_path, "wb") as f_output:
+        f_output.write(f_input.read())
+    return str(file_path)
+
 
 def add_file(history, task_history, file):
     if file is None:
@@ -126,20 +129,26 @@ def _launch_demo(args, model, tokenizer):
     uploaded_file_dir = os.environ.get("GRADIO_TEMP_DIR") or str(
         Path(tempfile.gettempdir()) / "gradio"
     )
-
     def predict(_chatbot, task_history):
+        print("predict called")
         if not _chatbot:
             return _chatbot 
         chat_query = _chatbot[-1][0]
+        print("Chat query:", chat_query)
+
         if isinstance(chat_query, tuple):
             query = [{'image': chat_query[0]}]
         else:
             query = [{'text': _parse_text(chat_query)}]
+
+        print("Query for model:", query)
         inputs = tokenizer.from_list_format(query)
         tokenized_inputs = tokenizer(inputs, return_tensors='pt')
         tokenized_inputs = tokenized_inputs.to(model.device)
+
         pred = model.generate(**tokenized_inputs)
         response = tokenizer.decode(pred.cpu()[0], skip_special_tokens=False)
+        print("Model response:", response)
         if 'image' in query[0]:
             image = tokenizer.draw_bbox_on_latest_picture(response)
             if image is not None:
@@ -151,7 +160,6 @@ def _launch_demo(args, model, tokenizer):
             _chatbot[-1] = (chat_query, response)
         return _chatbot
 
-
     def save_uploaded_image(image_file, upload_dir):
         if image is None:
             return None