Update app.py

app.py

@@ -1,88 +1,67 @@
-import streamlit as st
-import os
-from dotenv import load_dotenv
-from PIL import Image
-import google.generativeai as genai
-
-# Load environment variables from .env.
-load_dotenv()
-
-# Configure Google Generative AI
-genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
-
-# Function to get response from Gemini text model
-def get_gemini_text_response(input_text):
-    model = genai.GenerativeModel('gemini-pro')
-    response = model.generate_content(input_text)
-    return response.text if response else "Please provide a valid text prompt."
-
-# Function to get response from Gemini vision model
-def get_gemini_image_response(image, input_text=None):
-    model = genai.GenerativeModel('gemini-pro-vision')
-    if input_text:
-        response = model.generate_content([input_text, image])
-    else:
-        response = model.generate_content(image)
-    return response.text if response else "Please provide a valid image."
-
-# Initialize Streamlit app
-st.set_page_config(page_title="Gemini Q&A and Image Analysis", page_icon="🤖")
-
-# Sidebar for additional options
-st.sidebar.title("About")
-st.sidebar.info("This is a Q&A chatbot powered by Google's Gemini AI model.")
-st.sidebar.title("Instructions")
-st.sidebar.info("1. Choose either 'Q&A Chatbot' or 'Image Analysis' from the options.\n"
-                "2. Enter your question/prompt or upload an image.\n"
-                "3. Click the 'Ask' button to get the response.\n"
-                "4. The response will be displayed below.")
-
-# Main interface
-st.title("Gemini Q&A and Image Analysis Chatbot")
-st.write("Select an option to either ask a question or analyze an image.")
-
-# User selection
-option = st.selectbox("Choose an option:", ("Q&A Chatbot", "Image Analysis"))
-
-# Input fields based on user selection
-if option == "Q&A Chatbot":
-    input_text = st.text_input("Enter your question or prompt:", key="input_text")
-    if st.button("Ask"):
-        with st.spinner("Generating response..."):
-            response = get_gemini_text_response(input_text)
-        st.subheader("Response:")
-        st.write(response)
-
-elif option == "Image Analysis":
-    uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
-    image_input_text = st.text_input("Enter your question or prompt related to the image (optional):", key="image_input_text")
-    if uploaded_file is not None:
-        image = Image.open(uploaded_file)
-        st.image(image, caption="Uploaded Image.", use_column_width=True)
-        if st.button("Analyze"):
-            with st.spinner("Generating response..."):
-                response = get_gemini_image_response(image, input_text=image_input_text)
-            st.subheader("Response:")
-            st.write(response)
-
-# Footer
-st.markdown(
-    """
-    <style>
-    .footer {
-        position: fixed;
-        left: 0;
-        bottom: 0;
-        width: 100%;
-        background-color: #f1f1f1;
-        color: black;
-        text-align: center;
-        padding: 10px;
-    }
-    </style>
-    <div class="footer">
-        <p>Powered by Google's Gemini AI | Made with ❤️ by Amit_J</p>
-    </div>
-    """,
-    unsafe_allow_html=True
-)
+import streamlit as st
+import os
+from dotenv import load_dotenv
+from PIL import Image
+import google.generativeai as genai
+
+# Load environment variables from .env.
+load_dotenv()
+
+# Configure Google Generative AI
+genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
+
+# Function to get response from Gemini text model
+def get_gemini_text_response(input_text):
+    model = genai.GenerativeModel('gemini-pro')
+    response = model.generate_content(input_text)
+    return response.text if response else "Please provide a text prompt."
+
+# Function to get response from Gemini vision model
+def get_gemini_image_response(image, input_text=None):
+    model = genai.GenerativeModel('gemini-pro-vision')
+    if input_text:
+        response = model.generate_content([input_text, image])
+    else:
+        response = model.generate_content(image)
+    return response.text if response else "Please provide a image."
+
+# Initialize Streamlit app
+st.set_page_config(page_title="Gemini Q&A and Image Analysis", page_icon="🤖")
+
+# Sidebar for additional options
+st.sidebar.title("About")
+st.sidebar.info("This is a Q&A chatbot powered by Google's Gemini AI model.")
+st.sidebar.title("Instructions")
+st.sidebar.info("1. Choose either 'Q&A Chatbot' or 'Image Analysis' from the options.\n"
+                "2. Enter your question/prompt or upload an image.\n"
+                "3. Click the 'Ask' button to get the response.\n"
+                "4. The response will be displayed below.")
+
+# Main interface
+st.title("Gemini Q&A and Image Analysis Chatbot")
+st.write("Select an option to either ask a question or analyze an image.")
+
+# User selection
+option = st.selectbox("Choose an option:", ("Q&A Chatbot", "Image Analysis"))
+
+# Input fields based on user selection
+if option == "Q&A Chatbot":
+    input_text = st.text_input("Enter your question or prompt:", key="input_text")
+    if st.button("Ask"):
+        with st.spinner("Generating response..."):
+            response = get_gemini_text_response(input_text)
+        st.subheader("Response:")
+        st.write(response)
+
+elif option == "Image Analysis":
+    uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
+    image_input_text = st.text_input("Enter your question or prompt related to the image (optional):", key="image_input_text")
+    if uploaded_file is not None:
+        image = Image.open(uploaded_file)
+        st.image(image, caption="Uploaded Image.", use_column_width=True)
+        if st.button("Analyze"):
+            with st.spinner("Generating response..."):
+                response = get_gemini_image_response(image, input_text=image_input_text)
+            st.subheader("Response:")
+            st.write(response)
+