import gradio as gr
from azure.ai.inference import ChatCompletionsClient
from azure.ai.inference.models import (
    SystemMessage,
    UserMessage,
    TextContentItem,
    ImageContentItem,
    ImageUrl,
    ImageDetailLevel,
)
from azure.core.credentials import AzureKeyCredential

# Azure API credentials
token = "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"
endpoint = "https://models.inference.ai.azure.com"
model_name = "Llama-3.2-90B-Vision-Instruct"

# Initialize the ChatCompletionsClient
client = ChatCompletionsClient(
    endpoint=endpoint,
    credential=AzureKeyCredential(token),
)

# Define the function to handle the image and get predictions
def analyze_leaf_disease(image):
    try:
        # Convert the uploaded image to a compatible format (e.g., save it locally)
        image.save("uploaded_image.jpg")

        # Prepare and send the request to the Azure API
        response = client.complete(
            messages=[
                SystemMessage(
                    content="You are a helpful assistant that describes leaf disease in detail."
                ),
                UserMessage(
                    content=[
                        TextContentItem(text="What's the leaf disease in this image?"),
                        ImageContentItem(
                            image_url=ImageUrl.load(
                                image_file="uploaded_image.jpg",
                                image_format="jpg",
                                detail=ImageDetailLevel.LOW,
                            )
                        ),
                    ],
                ),
            ],
            model=model_name,
        )

        # Extract and return the response content
        return response.choices[0].message.content

    except Exception as e:
        return f"An error occurred: {e}"

# Define the Gradio interface
interface = gr.Interface(
    fn=analyze_leaf_disease,
    inputs=gr.Image(type="file", label="Upload an Image of a Leaf"),
    outputs="text",
    title="Leaf Disease Detector",
    description="Upload an image of a leaf, and this tool will identify the disease affecting it.",
)

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