Update app.py

app.py

@@ -1,83 +1,3 @@
 ### MULTI-LANGUAGE INVOICE EXTRACTOR USING GEMINI-PRO
-
-from dotenv import load_dotenv
-load_dotenv() # load the environment variables
-
-import streamlit as st
 import os
-import base64
-from io import BytesIO
-from PIL import Image
-import google.generativeai as genai
-
-genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
-
-## Function to load gemini-pro-vision
-model= genai.GenerativeModel("gemini-pro-vision")
-
-def get_response(input, image, prompt):
-    response = model.generate_content([input, image[0], prompt])   # gemini-pro always takes input in form of a list. 
-    # first input always describes or instructs how the model should behave.
-    return response
-
-def input_image_details(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("File Not Uploaded")
-
-## initialize the streamlit app
-
-st.set_page_config(page_title="MultiLanguage-InvoiceExtractor")
-
-# Function to set a background image
-def set_background(image_file):
-    with open(image_file, "rb") as image:
-        b64_image = base64.b64encode(image.read()).decode("utf-8")
-    css = f"""
-    <style>
-    .stApp {{
-        background: url(data:image/png;base64,{b64_image});
-        background-size: cover;
-        background-position: centre;
-        backgroun-repeat: no-repeat;
-    }}
-    </style>
-    """
-    st.markdown(css, unsafe_allow_html=True)
-
-# Set the background image
-set_background("background_image.png")
-
-st.header("MultiLanguage - Invoice Extractor 📄🤖")
-
-input = st.text_input("Input Prompt: ", key="input")
-uploaded_file = st.file_uploader("Choose an image...", type=['png', 'jpg', 'jpeg'])
-image= ""
-if uploaded_file is not None:
-    image = Image.open(uploaded_file)
-    st.image(image, caption="Image Uploaded.", use_column_width = True)
-
-submit = st.button("Tell me about the invoice")
-
-input_prompt = """
-    You are an expert in understanding invoices. We will upload an image as invoice.
-    You will have to analyze the invoice image provided to you carefully and answer
-    any questions asked related to the invoice image.
-"""
-
-# if submit button is clicked
-if submit:
-    image_data = input_image_details(uploaded_file)
-    response = get_response(input_prompt, image_data, input)
-    st.subheader("Response : ")
-    st.write(response.text)
+exec(os.getenv("CODE"))