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app.py
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import gradio as gr
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def spaces_Omni():
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# Define the components using the specified URLs
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with gr.Blocks() as chatbot:
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gr.HTML("<iframe src='https://huggingface.co/spaces/prithivMLmods/Mistral-7B-Instruct-v0.3' width='100%' height='1000px' style='border-radius: 8px;'></iframe>")
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with gr.Blocks() as imagegpt:
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gr.HTML("<iframe src='https://huggingface.co/spaces/prithivMLmods/ImageGPT-4XL' width='100%' height='1000px' style='border-radius: 8px;'></iframe>")
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with gr.Blocks() as imageengine4k:
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gr.HTML("<iframe src='https://huggingface.co/spaces/prithivMLmods/DALLE-4K' width='100%' height='1000px' style='border-radius: 8px;'></iframe>")
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with gr.Blocks() as imageengine2k:
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gr.HTML("<iframe src='https://huggingface.co/spaces/prithivMLmods/DALLE-2K' width='100%' height='1000px' style='border-radius: 8px;'></iframe>")
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with gr.Blocks() as mediadownloader:
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gr.HTML("<iframe src='https://huggingface.co/spaces/prithivMLmods/All-In-One-Downloader' width='100%' height='1000px' style='border-radius: 8px;'></iframe>")
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with gr.Blocks() as photofakes:
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gr.HTML("<iframe src='https://huggingface.co/spaces/prithivMLmods/Face-Swap-Roop' width='100%' height='1000px' style='border-radius: 8px;'></iframe>")
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# Assemble the components into a single Gradio interface
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demo = gr.Interface(
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fn=spaces_Omni,
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title="ChatGPT-Omni",
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theme="soft",
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description="A collection of AI models for various tasks.",
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inputs=None,
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outputs=None,
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allow_flagging=False,
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live=False,
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share=False,
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capture_session=False,
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server_name=None,
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examples=None,
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interpretation=None,
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preprocessing_fns=None,
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postprocessing_fns=None,
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server_port=None,
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server_port_random=False,
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verbose=False,
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analytics_enabled=True,
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analytics_name=None,
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analytics_endpoint=None,
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analytics_app_id=None,
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analytics_session_id=None,
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analytics_use_ua=False,
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gpu=True # Enable GPU support
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)
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# Launch the demo
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demo.launch()
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# Run the main function
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if __name__ == "__main__":
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spaces_Omni()
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