import gradio as gr
import google.generativeai as genai
import numpy as np
import base64
import pathlib
import textwrap
# from google.colab import userdata
# from IPython.display import display
# from IPython.display import Markdown

# apiKey = userdata.get('APIKEY')
genai.configure(api_key = 'APIKEY')

model = genai.GenerativeModel('gemini-pro-vision')
def generate_prescription(image):
    response = model.generate_content(["Write a prescription in pointer format ordered by name of medicine, symptoms, primary diagnosis, usage and dosage of medicine in the image. Make sure to ask person to visit doctor if problem presists.", image])
    return response.text

interface = gr.Interface(fn=generate_prescription,
                    inputs=gr.Image(label="Upload image", sources=['upload', 'webcam'], type="pil"),
                    outputs=gr.Textbox(label="Your prescription is here:"),
                    title="Medicine Prescription",
                    description="Find Prescription to any medicine",
                    allow_flagging="never")
                    # examples=["Combiflam.jpg", "Zintac.jpg"])
# interface.launch(debug = True)

if __name__ == "__main__":
    interface.launch()