app.py

import streamlit as st 
import os
import pathlib
import textwrap 
from PIL import Image

import google.generativeai as genai

genai.configure(api_key='AIzaSyCeNgXfZx0kJ736XFVtxXxev_RdscB0i5s')

## Function to load OpenAI model and get respones
def get_gemini_response(input,image,prompt):
    model = genai.GenerativeModel('gemini-pro-vision')
    response = model.generate_content([input,image[0],prompt])
    return response.text

def input_image_setup(uploaded_file): # Check if a file has been uploaded
    if uploaded_file is not None: # Read the file into bytes
        bytes_data = uploaded_file.getvalue()
        image_parts = [
            {
            "mime_type": uploaded_file.type,  # Get the mime type of the uploaded file
            "data": bytes_data
            }
        ]
        return image_parts
    else:
        raise FileNotFoundError("No file uploaded")

if uploaded_file is not None: 
    image = Image.open(uploaded_file)
    st.image(image, caption="Uploaded Image.", use_column_width=True)

submit=st.button("Submit")

input_prompt ="""
               You are an expert in understanding business cards.
               Input: Image of a business card.
               Task: Extract and label the following information in JSON format:
               Lagels : person_name, company_name, occupation, contact_number, email addresse, website, address, other_details (services, features, etc.)  
               Constraints: Do not include missing information.
               """

if submit:
    image_data = input_image_setup(uploaded_file)
    if image_data is not None:
        response = get_gemini_response(input_prompt, image_data, input_text)
        st.subheader("Output :")
        st.write(response)