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