import requests
import gradio as gr
import openai

openai.api_key = "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"



def infer(im):
    im.save("converted.png")
    url = "https://ajax.thehive.ai/api/demo/classify?endpoint=text_recognition"
    files = {
        "image": ("converted.png", open("converted.png", "rb"), "image/png"),
        "model_type": (None, "detection"),
        "media_type": (None, "photo"),
    }
    headers = {"referer": "https://thehive.ai/"}

    res = requests.post(url, headers=headers, files=files)

    text = ""
    blocks = []
    for output in res.json()["response"]["output"]:
        text += output["block_text"]
        for poly in output["bounding_poly"]:
            blocks.append({
                "text": "".join([c["class"] for c in poly["classes"]]),
                "rect": poly["dimensions"]
            })

            
    print(blocks)
    return blocks


def gpt(text):
    print(text)
    if not text:
        return "Veuillez saisir une question."
    f_prompt = f""" reformule ça 
    {text}. """

    response = openai.Completion.create(
        model="text-davinci-003",
        prompt=f_prompt,
        temperature=0.9,
        max_tokens=3500,
        top_p=1)

    answer = response.choices[0].text.strip()
    print(answer)
    return answer

iface = gr.Interface(
    fn=gpt,
    title="Mariam - Beta",
    description=" La maj du siècle. ",
    inputs=[gr.Image(type="pil")],
    outputs=gr.Text(),
).launch()