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Update app.py (#22)
Browse files- Update app.py (5c0dfe46b2e67fa3f0316a7361086b2b171cbe0a)
app.py
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@@ -39,31 +39,36 @@ def bot_streaming(message, history):
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if type(hist[0])==tuple:
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image = hist[0][0]
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demo = gr.ChatInterface(fn=bot_streaming, css=CSS, fill_height=True, title="LLaVA Llama-3-8B", examples=[{"text": "What is on the flower?", "files":["./bee.jpg"]},
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if type(hist[0])==tuple:
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image = hist[0][0]
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try:
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if image is None:
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# Handle the case where image is None
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gr.Error("You need to upload an image for LLaVA to work.")
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else:
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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"
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print(f"prompt: {prompt}")
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image = Image.open(image)
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inputs = processor(prompt, image, return_tensors='pt').to(0, torch.float16)
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streamer = TextIteratorStreamer(processor, **{"skip_special_tokens": True})
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generation_kwargs = dict(inputs, streamer=streamer, max_new_tokens=1024)
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generated_text = ""
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thread = Thread(target=model.generate, kwargs=generation_kwargs)
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thread.start()
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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"
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print(f"text_prompt: {text_prompt}")
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buffer = ""
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for new_text in streamer:
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buffer += new_text
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generated_text_without_prompt = buffer[len(text_prompt):]
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time.sleep(0.08)
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yield generated_text_without_prompt
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except NameError:
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gr.Error("You need to upload an image for LLaVA to work.")
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demo = gr.ChatInterface(fn=bot_streaming, css=CSS, fill_height=True, title="LLaVA Llama-3-8B", examples=[{"text": "What is on the flower?", "files":["./bee.jpg"]},
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