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initial app commit
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app.py
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import gradio as gr
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import websockets
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import asyncio
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import json
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import base64
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from PIL import Image
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import io
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def process_image_stream(image, question, max_tokens):
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return "This is a test response"
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# Create Gradio interface
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demo = gr.Interface(
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fn=process_image_stream,
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inputs=[
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gr.Image(type="filepath", label="Upload Image"),
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gr.Textbox(
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label="Question",
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placeholder="Ask a question about the image...",
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value="Describe this image"
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),
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gr.Slider(
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minimum=50,
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maximum=200,
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value=200,
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step=1,
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label="Max Tokens"
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)
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],
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outputs=gr.Textbox(label="Response", interactive=False),
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title="Nexa Omni Vision",
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description=f"""
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Model Repo: <a href="https://huggingface.co/NexaAIDev/omnivision-968M">NexaAIDev/omnivision-968M</a>
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*Model updated on Nov 21, 2024\n
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Upload an image and ask questions about it. The model will analyze the image and provide detailed answers to your queries.
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""",
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)
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if __name__ == "__main__":
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demo.queue().launch(server_name="0.0.0.0", server_port=7860)
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