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Update app.py
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app.py
CHANGED
@@ -47,7 +47,7 @@ vision_model = AutoModelForCausalLM.from_pretrained(
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vision_processor = AutoProcessor.from_pretrained(VISION_MODEL_ID, trust_remote_code=True)
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# Helper functions
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@spaces.GPU
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def stream_text_chat(message, history, system_prompt, temperature=0.8, max_new_tokens=1024, top_p=1.0, top_k=20):
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conversation = [{"role": "system", "content": system_prompt}]
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for prompt, answer in history:
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@@ -78,7 +78,7 @@ def stream_text_chat(message, history, system_prompt, temperature=0.8, max_new_t
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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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yield buffer
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@spaces.GPU # Add this decorator
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def process_vision_query(image, text_input):
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@@ -97,6 +97,7 @@ def process_vision_query(image, text_input):
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response = vision_processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
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return response
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with gr.Blocks() as demo:
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gr.HTML(TITLE)
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gr.Markdown(DESCRIPTION)
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vision_processor = AutoProcessor.from_pretrained(VISION_MODEL_ID, trust_remote_code=True)
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# Helper functions
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@spaces.GPU
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def stream_text_chat(message, history, system_prompt, temperature=0.8, max_new_tokens=1024, top_p=1.0, top_k=20):
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conversation = [{"role": "system", "content": system_prompt}]
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for prompt, answer in history:
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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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yield history + [[message, buffer]]
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@spaces.GPU # Add this decorator
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def process_vision_query(image, text_input):
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response = vision_processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
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return response
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# Update the Gradio interface part
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with gr.Blocks() as demo:
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gr.HTML(TITLE)
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gr.Markdown(DESCRIPTION)
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