app.py

import os
import gradio as gr
from openai import OpenAI

# Initialize the Nebius OpenAI client
client = OpenAI(
    base_url="https://api.studio.nebius.ai/v1/",
    api_key=os.getenv("OPENAI_API_KEY"),  # Use the environment variable
)

# Function to process input and return the response
def analyze_image(image_url):
    # Construct the prompt with the image URL
    prompt = f"What’s in this image? [image_url: {image_url}]"
    
    try:
        # Call the Nebius OpenAI API
        response = client.chat.completions.create(
            model="Qwen/Qwen2-VL-72B-Instruct",
            messages=[
                {"role": "user", "content": prompt}  # Simplified messages format
            ],
            max_tokens=300,
        )
        
        # Extract and return the AI's response
        return response.choices[0].get("message", {}).get("content", "No response found.")
    
    except Exception as e:
        return f"Error: {str(e)}"

# Create the Gradio interface
with gr.Blocks() as app:
    gr.Markdown("# Image Analysis with Nebius OpenAI")
    image_url_input = gr.Textbox(
        label="Image URL",
        placeholder="Enter an image URL for analysis",
    )
    output = gr.Textbox(
        label="AI Response",
        placeholder="The description of the image will appear here.",
    )
    submit_button = gr.Button("Analyze Image")
    submit_button.click(analyze_image, inputs=image_url_input, outputs=output)

# Launch the app
if __name__ == "__main__":
    app.launch()