Update app.py (#11)

- Update app.py (1a74baf95b5d6875810d67052d06e4a6c6bb341f)

app.py

@@ -42,31 +42,31 @@ def bot_streaming(message, history):
       if type(hist[0])==tuple:
         image = hist[0][0]
 
-  if image is None:
-      gr.Error("You need to upload an image for LLaVA to work.")
-  prompt=f"<|start_header_id|>user<|end_header_id|>\n\n<image>\n{message['text']}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n"
-  print(f"prompt: {prompt}")
-  image = Image.open(image)
-  inputs = processor(prompt, image, return_tensors='pt').to(0, torch.float16)
+  # if image is None:
+  #     gr.Error("You need to upload an image for LLaVA to work.")
+  # prompt=f"<|start_header_id|>user<|end_header_id|>\n\n<image>\n{message['text']}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n"
+  # print(f"prompt: {prompt}")
+  # image = Image.open(image)
+  # inputs = processor(prompt, image, return_tensors='pt').to(0, torch.float16)
 
-  streamer = TextIteratorStreamer(processor, **{"skip_special_tokens": True})
-  generation_kwargs = dict(inputs, streamer=streamer, max_new_tokens=1024)
-  generated_text = ""
+  # streamer = TextIteratorStreamer(processor, **{"skip_special_tokens": True})
+  # generation_kwargs = dict(inputs, streamer=streamer, max_new_tokens=1024)
+  # generated_text = ""
 
-  thread = Thread(target=model.generate, kwargs=generation_kwargs)
-  thread.start()
+  # thread = Thread(target=model.generate, kwargs=generation_kwargs)
+  # thread.start()
 
-  text_prompt =f"<|start_header_id|>user<|end_header_id|>\n\n{message['text']}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n"
-  print(f"text_prompt: {text_prompt}")
+  # text_prompt =f"<|start_header_id|>user<|end_header_id|>\n\n{message['text']}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n"
+  # print(f"text_prompt: {text_prompt}")
 
-  buffer = ""
-  for new_text in streamer:
+  # buffer = ""
+  # for new_text in streamer:
     
-    buffer += new_text
+  #   buffer += new_text
     
-    generated_text_without_prompt = buffer[len(text_prompt):]
-    time.sleep(0.04)
-    yield generated_text_without_prompt
+  #   generated_text_without_prompt = buffer[len(text_prompt):]
+  #   time.sleep(0.04)
+  #   yield generated_text_without_prompt
 
 
 with gr.Blocks(css=CSS) as demo: