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app.py

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+### 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)

requirements.txt

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+streamlit
+google-generativeai
+python-dotenv
+langchain-community
+langchain
+PyPDF2
+chromadb