import gradio as gr
from groq import Groq
import base64

client = Groq(api_key = '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')

def encode_image(image_path) : 

    with open(image_path , 'rb') as image_file : return base64.b64encode(image_file.read()).decode('utf-8')

def analyze_image(image_path , prompt) : 

    base64_image = encode_image(image_path)

    chat_completion = client.chat.completions.create(
        messages = [
            {
                'role': 'user' , 
                'content' : [
                    {
                        'type' : 'text' , 
                        'text' : prompt
                    } , 
                    {
                        'type' : 'image_url' , 
                        'image_url' : {'url' : f'data:image/jpeg;base64,{base64_image}'}
                    }
                ]
            }
        ] , 
        model = 'llama-3.2-90b-vision-preview'
    )

    return chat_completion.choices[0].message.content
demo = gr.Interface(
    fn=analyze_image,
    inputs=[
        gr.Image(type = 'filepath') ,  
        gr.Textbox(label = 'Prompt' , placeholder = 'Describe the Image' )
    ],
    outputs = 'text'
)

demo.launch()