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import streamlit as st | |
from PIL import Image | |
import google.generativeai as genai | |
import os | |
gemini_api_key = genai.configure(api_key = os.environ.get("Google_API_KEY")) | |
model = genai.GenerativeModel('gemini-1.5-flash') | |
input_prompts = """ | |
You are an expert Invoice Entity Extractor and you are expert in understanding Invoices. | |
We will upload an image as Invoice and you will have to answer any question based on the uploaded invoice. | |
""" | |
def response_gemini(input, image, prompt): | |
response = model.generate_content([input, image[0], prompt]) | |
return response.text | |
st.title("Invoice Entity Extractor") | |
uploaded_file = st.file_uploader("Choose an invoice image", type=["jpg", "jpeg", "png"]) | |
if uploaded_file is not None: | |
image = Image.open(uploaded_file) | |
st.image(image, caption='Uploaded Invoice', use_column_width=True) | |
question = st.text_input("Ask a question about the invoice:") | |
if st.button("Extract"): | |
if question: | |
answer = response_gemini(input_prompts, [image], question) | |
#st.write("**Answer:**", answer) | |
st.markdown(f"**Answer:** {answer}") | |
else: | |
st.warning("Please enter a question.") |