Init

requirements.txt

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+streamlit
+google-generativeai
+python-dotenv

vision.py

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+import streamlit as st
+import os
+import google.generativeai as genai
+from PIL import Image
+
+genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
+
+## function to load Gemini Pro model and get responses
+model=genai.GenerativeModel("gemini-pro-vision")
+
+def get_gemini_response(input, image):
+    if input != "":
+        response=model.generate_content([input, image])
+    else:
+        response=model.generate_content(image)
+    return response.text
+
+
+## initalize our streamlit app
+
+st.set_page_config(page_title="Gemini Image Demo")
+
+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 image")
+
+## if submit is clicked
+if submit:
+    response = get_gemini_response(input, image)
+    st.subheader("The Response is")
+    st.write(response)