import gradio as gr
import google.generativeai as genai

import os 
token=os.environ.get("TOKEN") 
genai.configure(api_key=token)

# Chargez l'image
model = genai.GenerativeModel(model_name="gemini-pro-vision")
model_simple = genai.GenerativeModel(model_name="gemini-pro")

e =""
# Fonction pour générer le contenu
def generate_content(pro,image):
    global e

    if not image:
        response = model_simple.generate_content(pro)
        e = response.text

    else:
        response = model.generate_content([pro, image])
        print(response.text)
        e = response.text
    return e


markdown = r"""
e
""".format(e)
# Interface Gradio
iface = gr.Interface(fn=generate_content, inputs=[gr.Textbox(),gr.Image(type='pil')], outputs= gr.Markdown(markdown, latex_delimiters=[{ "left":"$$", "right":"$$", "display": True }]))

iface.launch()