Update app.py

app.py

@@ -1,71 +1,48 @@
-import streamlit as st
-import os
-import pathlib
-import textwrap
-from PIL import Image
+import streamlit as st 
+import os import pathlib
+import textwrap from PIL
+import Image
 
 import google.generativeai as genai
 
 genai.configure(api_key='AIzaSyCeNgXfZx0kJ736XFVtxXxev_RdscB0i5s')
 
-# Function to load OpenAI model and get responses
-def get_gemini_response(input, image, prompt):
+Function to load OpenAI model and get respones
+def get_gemini_response(input,image,prompt):
     model = genai.GenerativeModel('gemini-pro-vision')
-    response = model.generate_content([input, image[0], prompt])
+    response = model.generate_content([input,image[0],prompt])
     return response.text
 
-def input_image_setup(uploaded_file):
-    # Check if a file has been uploaded
-    if uploaded_file is not None:
-        # Read the file into bytes
+def input_image_setup(uploaded_file): # Check if a file has been uploaded
+    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
+            "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="Gemini Image Demo")
-
-st.header("Generative AI : Business card Reader")
-input_prompt = textwrap.dedent("""
-    You are an expert in understanding business cards.
-    You will receive input images of business card & you will have to answer questions based on the input image.
-    You have to extract information from business card images and give correct tag to the output text 
-    like person name, company name, occupation, address, telephone number, mobile number, email, website, etc. Give output in json format.
-    """)
-
-# Display sample input images
-sample_images_folder = pathlib.Path(__file__).parent / "sample_images"
-sample_images = [sample_image.name for sample_image in sample_images_folder.glob("*.jpg") if sample_image.is_file()]
+if uploaded_file is not None: 
+    image = Image.open(uploaded_file)
+    st.image(image, caption="Uploaded Image.", use_column_width=True)
 
-sample_image_selected = st.sidebar.selectbox("Choose a sample image", sample_images)
-
-uploaded_file = st.sidebar.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
-
-if uploaded_file is not None:
-    if sample_image_selected:
-        sample_image_path = sample_images_folder / sample_image_selected
-        uploaded_file.name = sample_image_selected
-        uploaded_file.seek(0)
-        with open(sample_image_path, "wb") as f:
-            f.write(uploaded_file.read())
-        image = Image.open(sample_image_path)
-        st.image(image, caption="Uploaded Image.", use_column_width=True)
-    else:
-        image = Image.open(uploaded_file)
-        st.image(image, caption="Uploaded Image.", use_column_width=True)
+submit=st.button("Submit")
 
-submit = st.button("Submit")
+input_prompt ="""
+               You are an expert in understanding business cards.
+               Input: Image of a business card.
+               Task: Extract and label the following information in JSON format:
+               Lagels : person_name, company_name, occupation, contact_number, email addresse, website, address, other_details (services, features, etc.)  
+               Constraints: Do not include missing information.
+               """
 
 if submit:
     image_data = input_image_setup(uploaded_file)
-    response = get_gemini_response(input_prompt, image_data, input)
-    st.subheader("Output :")
-    st.write(response)
+    if image_data is not None:
+        response = get_gemini_response(input_prompt, image_data, input_text)
+        st.subheader("Output :")
+        st.write(response)