app.py

import gradio as gr
import base64
import prompts
from openai import OpenAI
from dotenv import load_dotenv

load_dotenv()
client = OpenAI()

PROMPT = prompts.SINGLE_QCM_PROMPT


# Function to encode the image
def encode_image(image_path):
    with open(image_path, "rb") as image_file:
        return base64.b64encode(image_file.read()).decode("utf-8")


def process(image_path):
    try:
        response = client.chat.completions.create(
            model="gpt-4o",
            # response_format={ "type": "json_object" }, # si nécessaire
            messages=[
                # {"role": "system", "content": "You are a helpful assistant designed to output JSON."},
                {
                    "role": "user",
                    "content": [
                        {"type": "text", "text": PROMPT},
                        {
                            "type": "image_url",
                            "image_url": {
                                "url": f"data:image/jpeg;base64,{encode_image(image_path)}"
                            },
                        },
                    ],
                }
            ],
            temperature=0.2,
            #    max_tokens=256,
            #    top_p=1,
            #    frequency_penalty=0,
            #    presence_penalty=0
        )
        return response.choices[0].message.content

    except Exception as e:
        print(f"an error occurred : {e}")
        return {"error": str(e)}


iface = gr.Interface(
    fn=process,
    inputs=gr.Image(type="filepath"),
    outputs=gr.JSON(),
)

iface.launch()