Upload 2 files

two files uploaded

app.py

@@ -0,0 +1,63 @@
+## Invoice Extractor..
+
+from dotenv import load_dotenv
+load_dotenv() ## load all environment variables into the project
+import streamlit as st
+import os
+from PIL import Image
+import google.generativeai as genai
+
+## Configuring API key
+genai.configure(api_key = os.getenv("GOOGLE_API_KEY"))
+
+
+## Function to load Gemini Pro Vision Model and get Response
+def get_gemini_response(input, image, prompt):
+    # Loading the Gemini Model
+    model = genai.GenerativeModel('gemini-pro-vision')
+    response = model.generate_content([input, image[0], prompt])
+
+    return response.text
+
+
+def input_image_setup(uploaded_file):
+    if uploaded_file is not None:
+        # read the file into bytes
+        bytes_data = uploaded_file.getvalue()
+        image_part = [{
+            "mime_type": uploaded_file.type,
+            "data": bytes_data
+        }]
+        return image_part
+    else:
+        raise FileNotFoundError("No File Uploaded...")
+    
+
+# Initialize our streamlit app
+st.set_page_config(page_title= "Invoice Extractor")
+
+st.header("Gemini Application")
+input = st.text_input("Input Prompt: ", key = "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, caption="Uploaded Image", use_column_width=True)
+
+
+
+submit = st.button('Tell Me about the Invoice')
+
+input_prompt = """
+you are an expert in understanding invoices. 
+you will receive input images as invoices and you will 
+have to answer questions based on the input image.
+"""
+## If Submit button is clicked...
+
+if submit:
+    image_data = input_image_setup(uploaded_file)
+    response = get_gemini_response(input_prompt, image_data, input)
+
+    st.subheader("The Response is :")
+    st.write(response)

requirements.txt

@@ -0,0 +1,3 @@
+google-generativeai
+streamlit
+python-dotenv