Upload 3 files

.env

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+GOOGLE_API_KEY="AIzaSyAJjp2hRJBGsei-o6kfvnZ8EeKkXl4-XuI"

app.py

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+from dotenv import load_dotenv
+
+load_dotenv() ## load all the environment variables 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"))
+
+## Function to load Gemini Pro Vision
+model=genai.GenerativeModel('gemini-pro-vision')
+
+def get_gemini_response(input,image,prompt):
+    response=model.generate_content([input,image[0],prompt])
+    return response.text
+
+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, # Get the 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("Choose an image of the invoice...", 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 invoice")
+
+input_prompt="""
+You are an expert in understanding invoices. We will upload an image as invoice and you will have to answer any questions based on the uploaded invoice image.
+"""
+
+# If submit button is clicked
+
+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
+python-dotenv
+langchain
+PyPDF2
+chromadb