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from dotenv import load_dotenv | |
load_dotenv() | |
import pathlib | |
import textwrap | |
import streamlit as st | |
import os | |
from PIL import Image | |
import google.generativeai as genai | |
os.getenv("GOOGLE_API_KEY") | |
genai.configure(api_key=os.getenv("GOOGLE_API_KEY")) | |
#input means what to do by this app which is the input prompt and is general | |
#prompt means what it wants at that point of time | |
#image means what image we want to apply | |
#this function gives the response from the model | |
def get_gemini_response(input,image,prompt): | |
model=genai.GenerativeModel('gemini-pro-vision') | |
response=model.generate_content([input,image[0],prompt]) | |
return response.text | |
#load the image and convert the image in bytes | |
def input_image_setup(uploaded_file): | |
if uploaded_file is not None: | |
# Read the file into bytes | |
bytes_data = uploaded_file.getvalue() | |
image_parts = [ | |
{ | |
"mime_type": uploaded_file.type, | |
"data": bytes_data | |
} | |
] | |
return image_parts | |
else: | |
raise FileNotFoundError("No file uploaded") | |
st.set_page_config(page_title="Mulitlanguage Invoice Extractor") | |
st.header("Mulitlanguage Invoice Extractor") | |
input=st.text_input("Input Prompt: ",key="input") | |
uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"]) | |
image="" | |
if uploaded_file is not None: | |
image = Image.open(uploaded_file) | |
st.image(image, caption="Uploaded Image.", use_column_width=True) | |
submit=st.button("Tell me about the image") | |
input_prompt = """ | |
You are an expert in understanding invoices. | |
You will receive input images as invoices & | |
you will have to answer questions based on the input image | |
""" | |
if submit: | |
image_data=input_image_setup(uploaded_file) #get the image data | |
response=get_gemini_response(input_prompt,image_data,input) | |
st.subheader("The response is") | |
st.write(response) |