Create app.py

app.py

@@ -0,0 +1,69 @@
+import streamlit as st
+import os
+import pathlib
+import textwrap
+from PIL import Image
+
+
+import google.generativeai as genai
+
+
+os.getenv("GOOGLE_API_KEY")
+genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
+
+# function to load gemini Pro model
+
+
+def get_gemini_response(input, image, prompt):
+    model = genai.GenerativeModel('gemini-pro-vision')
+    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 = [
+            {
+                # Get the mime type of the up]
+                "mime_type": uploaded_file.type,
+                "data": bytes_data
+            }
+        ]
+
+        return image_parts
+    else:
+        raise FileNotFoundError("No file uploaded")
+
+
+# Initialize streamlit app
+st.set_page_config(page_title="Data Extractor")
+
+st.header("Data Extractor")
+input = st.text_input("Input Prompt: ", key="input")
+
+uploaded_file = st.file_uploader(
+    "Choose an image of ... ", 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("Submit")
+
+input_prompt = """
+You are an expert in understanding financial reports. We will upload a a image as financial statement
+and you will have to answer any questions based on the uploaded invoice image
+"""
+
+# If submit button clicked
+if submit:
+    image_data = input_image_details(uploaded_file)
+    reponse = get_gemini_response(
+        input_prompt,  image_data, input)
+    st.subheader("The response is")
+    st.write(reponse)