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import gradio as gr |
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import os, shutil, time |
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from gradio_client import Client |
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client = Client("ByteDance/Hyper-SDXL-1Step-T2I") |
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id=0 |
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def multimodalResponse(message,history): |
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global id |
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id=id+1 |
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print(message) |
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result = client.predict( |
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num_images=1, |
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height=1024, |
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width=1024, |
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prompt=message, |
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seed=3413, |
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api_name="/process_image") |
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shutil.copy(result[0]['image'],os.getcwd()) |
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os.rename('image.webp', 'image'+str(id)+'.webp') |
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return "Prompt '"+message+"': ![image](/file="+os.getcwd()+"/image"+str(id)+".webp)" |
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bot=gr.Chatbot( |
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value=[[None,"I'm a simple image-generating chatbot. Please tell me what you would like to see."]], |
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render_markdown=True) |
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interface=gr.ChatInterface(multimodalResponse,chatbot=bot, multimodal=False) |
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interface.launch(allowed_paths=["."]) |
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