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requirements.txt

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+streamlit
+google-generativeai
+python-dotenv

vision.py

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+from dotenv import load_dotenv
+
+load_dotenv()
+
+import streamlit as st
+import os
+import pathlib
+import textwrap
+from PIL import Image
+
+import google.generativeai as genai
+
+os.getenv("GOOGLE_API_KEYS")
+genai.configure(api_keys = os.getenv("GOOGLE_API_KEYS"))
+
+#function to load genai model and get response
+
+def get_gemini_response(input,image)
+    model = genai.GenerativeModel('gemini-pro-vision')
+    if input!="":
+        response = model.generate_content([input,image])
+    else:
+        response  = model.generate_content(image)
+    return response.text      
+
+
+##streamlit
+
+st.header("Decoding Data Science image Recognition Demo")
+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)
+
+
+if submit:
+    response= get_gemini_response(input,image)
+    st.subheader("The Image Response is")
+    st.write(response)
+