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Extractor.py

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+from dotenv import load_dotenv
+load_dotenv()                                             # Load the all envirement variable from .env
+
+import streamlit as st
+import os
+from PIL import Image
+
+
+import google.generativeai as genai
+genai.configure(api_key=os.getenv("google_api_key"))
+model=genai.GenerativeModel('gemini-1.5-flash')           # Load gemini pero version Model
+
+def get_gemini_response(input,image,user_prompt):
+    response=model.generate_content([input,image[0],user_prompt])
+    return response.text
+
+def input_image_details(uploaded_file):
+    if uploaded_file is not None:
+        bytes_data=uploaded_file.getvalue()               # Read the files into bytes
+        image_parts=[
+            {
+                "mine type":uploaded_file.type,           # get th mime type of the uploaded file
+                "data":bytes_data
+            }
+        ]
+        return image_parts
+    else:
+        raise FileNotFoundError("No file uploaded")
+    
+
+# Initialize our streamlit app
+
+st.set_page_config(page_title='Multilanguage Invoice Extractor')
+
+st.header('Multilanguage Invoice Extractor')
+input=st.text_input("input  prompt:",key="input")
+
+uploaded_file=st.file_uploader("Chose an image of the Invoice....",type=["jpg","jpeg","png"])
+
+if uploaded_file is not None:
+    image=Image.open(uploaded_file)
+    st.image(image,caption="uploaded image.",use_column_width=True)
+
+
+input_prompt="""
+You are an expert in understanding invoices. We upload a image as invoice
+and you will have to answer any quetions based on the uploaded invoice image 
+"""    
+
+submit=st.button('Tell me about the invoice')
+
+if submit:
+    image_data=input_image_details(uploaded_file)
+    response=get_gemini_response(input_prompt,image_data,input)
+    st.subheader("The Response is")
+    st.write(response)

requirements.txt

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+streamlit
+google-generativeai          # To create LLM model of google
+python-dotenv                # For hide my API key
+langchain
+pyPDF2                       # To process pdf file
+chromadb                     # vector database