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.env

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+GOOGLE_API_KEY="AIzaSyCCR1ZGgDozOPB5CFDWxgMWAOkhOwmhrU4"

app.py

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+from turtle import up
+from dotenv import load_dotenv
+import streamlit as st
+import os
+from PIL import Image
+import google.generativeai as genai
+
+load_dotenv()
+
+genai.configure(api_key = os.getenv('GOOGLE_API_KEY'))
+
+model = genai.GenerativeModel('gemini-pro-vision')
+
+def get_response(input, image, prompt):
+    response = model.generate_content([input, image[0], prompt])
+    return response.parts
+
+def input_image_setup(image):
+    if image is not None:
+        data = image.getvalue()
+
+        image_data = [
+            {
+                "mime_type": image.type,
+                "data": data
+            }
+        ]
+        return image_data
+
+    else:
+        raise FileNotFoundError("NO FILE UPLOADED.")
+
+st.set_page_config('Invoice Extractor')
+st.header('Gemini Application')
+
+
+prompt = st.text_input("Enter Prompt : " , key='prompt_input')
+input = st.text_input("what do you want to know : " , key='user_input')
+uploaded_file = st.file_uploader("Choose an image " , type=["jpg", "jpeg", "png"])
+
+image = ""
+if uploaded_file is not None:
+    image = Image.open(uploaded_file)
+    st.image(image, use_column_width=True)
+
+submit = st.button("Tell me about the image")
+
+if submit:
+    image_data = input_image_setup(uploaded_file)
+    response = get_response(input=input, image=image_data, prompt=prompt)
+    st.subheader("The response is : ")
+    st.write(response)
+
+
+
+
+# You are an expert food analyst
+
+# List all food items shown in image
+
+
+# You are an invoice extractor
+
+# what is total amount
+

requirements.txt

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