Update app.py

app.py

@@ -10,15 +10,6 @@ from transformers import TextIteratorStreamer
 import spaces
 
 
-PLACEHOLDER = """
-<div style="padding: 30px; text-align: center; display: flex; flex-direction: column; align-items: center;">
-   <img src="https://cdn-uploads.huggingface.co/production/uploads/64ccdc322e592905f922a06e/DDIW0kbWmdOQWwy4XMhwX.png" style="width: 80%; max-width: 550px; height: auto; opacity: 0.55;  "> 
-   <h1 style="font-size: 28px; margin-bottom: 2px; opacity: 0.55;">LLaVA-Llama-3-8B</h1>
-   <p style="font-size: 18px; margin-bottom: 2px; opacity: 0.65;">Llava-Llama-3-8b is a LLaVA model fine-tuned from Meta-Llama-3-8B-Instruct and CLIP-ViT-Large-patch14-336 with ShareGPT4V-PT and InternVL-SFT by XTuner</p>
-</div>
-"""
-
-
 model_id = "xtuner/llava-llama-3-8b-v1_1-transformers"
 
 processor = AutoProcessor.from_pretrained(model_id)
@@ -36,26 +27,22 @@ model.generation_config.eos_token_id = 128009
 @spaces.GPU
 def bot_streaming(message, history):
     print(message)
-    image = None  # Initialize image variable
+    image = None
     if message["files"]:
-        # message["files"][-1] is a Dict or just a string
         if type(message["files"][-1]) == dict:
             image = message["files"][-1]["path"]
         else:
             image = message["files"][-1]
     else:
-        # if there's no image uploaded for this turn, look for images in the past turns
-        # kept inside tuples, take the last one
         for hist in history:
             if type(hist[0]) == tuple:
                 image = hist[0][0]
-                break  # Exit loop after finding the first image
+                break
 
     if image is None:
         image = "ignore.png"
     
     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)
 
@@ -66,25 +53,20 @@ def bot_streaming(message, history):
     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}")
 
     buffer = ""
     time.sleep(0.5)
     for new_text in streamer:
-        # find <|eot_id|> and remove it from the new_text
         if "<|eot_id|>" in new_text:
             new_text = new_text.split("<|eot_id|>")[0]
         buffer += new_text
 
-        # generated_text_without_prompt = buffer[len(text_prompt):]
         generated_text_without_prompt = buffer
-        # print(generated_text_without_prompt)
         time.sleep(0.06)
-        # print(f"new_text: {generated_text_without_prompt}")
         yield generated_text_without_prompt
 
 
-chatbot=gr.Chatbot(placeholder=PLACEHOLDER,scale=1)
+chatbot=gr.Chatbot(scale=1)
 chat_input = gr.MultimodalTextbox(interactive=True, file_types=["image"], placeholder="Enter message or upload file...", show_label=False)
 with gr.Blocks(fill_height=True, ) as demo:
     gr.ChatInterface(