Update app.py

app.py

@@ -1,82 +1,63 @@
 import streamlit as st
-from phi.agent import Agent
-from phi.model.google import Gemini
-from phi.tools.duckduckgo import DuckDuckGo
-from google.generativeai import upload_file, get_file
+import google.generativeai as genai
+import os
 import time
-from pathlib import Path
-import tempfile
 
+# Setup page config
 st.set_page_config(
-    page_title="Multimodal AI Agent",
-    page_icon="🧬",
+    page_title="Gemini Streaming Demo",
+    page_icon="🤖",
     layout="wide"
 )
 
-st.title("Multimodal AI Agent 🧬")
-
-# Initialize single agent with both capabilities
-@st.cache_resource
-def initialize_agent():
-    return Agent(
-        name="Multimodal Analyst",
-        model=Gemini(id="gemini-2.0-flash-exp"),
-        tools=[DuckDuckGo()],
-        markdown=True,
-    )
-
-agent = initialize_agent()
-
-# File uploader
-uploaded_file = st.file_uploader("Upload a video file", type=['mp4', 'mov', 'avi'])
-
-if uploaded_file:
-    with tempfile.NamedTemporaryFile(delete=False, suffix='.mp4') as tmp_file:
-        tmp_file.write(uploaded_file.read())
-        video_path = tmp_file.name
-    
-    st.video(video_path)
+# Create a title
+st.title("🤖 Gemini API Streaming Demo")
+
+# Configure the Gemini API with environment variable
+genai.configure(api_key=os.environ['GOOGLE_API_KEY'])
+
+# Initialize the model
+model = genai.GenerativeModel('gemini-1.5-flash')
+
+# Create input text area
+user_input = st.text_area("Enter your prompt:", height=100)
+
+# Create a button to generate content
+if st.button("Generate", type="primary"):
+    if user_input:
+        # Create a placeholder for the streaming text
+        response_placeholder = st.empty()
+        
+        # Initialize full_response
+        full_response = ""
+        
+        # Generate streaming response
+        try:
+            response = model.generate_content(user_input, stream=True)
+            
+            # Stream the response
+            for chunk in response:
+                if chunk.text:
+                    full_response += chunk.text
+                    # Update the placeholder with the full response so far
+                    response_placeholder.markdown(full_response + "▌")
+                    time.sleep(0.05)  # Add a small delay for better visualization
+            
+            # Final update without the cursor
+            response_placeholder.markdown(full_response)
+            
+        except Exception as e:
+            st.error(f"An error occurred: {str(e)}")
+    else:
+        st.warning("Please enter a prompt first.")
+
+# Add instructions in the sidebar
+with st.sidebar:
+    st.markdown("""
+    ### Instructions
+    1. Type your prompt in the text area
+    2. Click 'Generate' to see the streaming response
     
-    user_prompt = st.text_area(
-        "What would you like to know?",
-        placeholder="Ask any question related to the video - the AI Agent will analyze it and search the web if needed",
-        help="You can ask questions about the video content and get relevant information from the web"
-    )
-    
-    if st.button("Analyze & Research"):
-        if not user_prompt:
-            st.warning("Please enter your question.")
-        else:
-            try:
-                with st.spinner("Processing video and researching..."):
-                    video_file = upload_file(video_path)
-                    while video_file.state.name == "PROCESSING":
-                        time.sleep(2)
-                        video_file = get_file(video_file.name)
-
-                    prompt = f"""
-                    First analyze this video and then answer the following question using both 
-                    the video analysis and web research: {user_prompt}
-                    
-                    Provide a comprehensive response focusing on practical, actionable information.
-                    """
-                    
-                    result = agent.run(prompt, videos=[video_file])
-                    
-                st.subheader("Result")
-                st.markdown(result.content)
-
-            except Exception as e:
-                st.error(f"An error occurred: {str(e)}")
-            finally:
-                Path(video_path).unlink(missing_ok=True)
-else:
-    st.info("Please upload a video to begin analysis.")
-
-st.markdown("""
-    <style>
-    .stTextArea textarea {
-        height: 100px;
-    }
-    </style>
-    """, unsafe_allow_html=True)
+    ### About
+    This demo shows how to use Gemini's streaming capabilities to generate text responses in real-time.
+    """)