Create app.py

app.py

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+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 time
+from pathlib import Path
+import tempfile
+from dotenv import load_dotenv
+load_dotenv()
+import os
+
+API_KEY = os.getenv("GOOGLE_API_KEY")
+if API_KEY:
+    genai.configure(api_key=API_KEY)
+
+# Page configuration
+st.set_page_config(
+    page_title="Multimodal AI Agent- Video Summarizer",
+    page_icon="🎥",
+    layout="wide"
+)
+
+st.title("Phidata Video AI Summarizer Agent 🎥🎤🖬")
+st.header("Powered by Gemini 2.0 Flash Exp")
+
+@st.cache_resource
+def initialize_agent():
+    return Agent(
+        name="Video AI Summarizer",
+        model=Gemini(id="gemini-2.0-flash-exp"),
+        tools=[DuckDuckGo()],
+        markdown=True,
+    )
+
+## Initialize the agent
+multimodal_Agent = initialize_agent()
+
+# File uploader
+video_file = st.file_uploader(
+    "Upload a video file", type=['mp4', 'mov', 'avi'], help="Upload a video for AI analysis"
+)
+
+if video_file:
+    with tempfile.NamedTemporaryFile(delete=False, suffix='.mp4') as temp_video:
+        temp_video.write(video_file.read())
+        video_path = temp_video.name
+    
+    st.video(video_path, format="video/mp4", start_time=0)
+    
+    user_query = st.text_area(
+        "What insights are you seeking from the video?",
+        value="Generate detailed student-style notes from this video, including key points, definitions, and important concepts.",
+        help="Provide specific questions or insights you want from the video."
+    )
+    
+    if st.button("🔍 Analyze Video", key="analyze_video_button"):
+        if not user_query:
+            st.warning("Please enter a question or insight to analyze the video.")
+        else:
+            try:
+                with st.spinner("Processing video and creating detailed notes..."):
+                    # Upload and process video file
+                    processed_video = upload_file(video_path)
+                    while processed_video.state.name == "PROCESSING":
+                        time.sleep(1)
+                        processed_video = get_file(processed_video.name)
+                    
+                    # Enhanced prompt for detailed student notes
+                    analysis_prompt = (
+                        f"""
+                        Analyze the uploaded video thoroughly and create EXTREMELY DETAILED STUDENT NOTES. 
+                        
+                        Your notes should:
+                        - Include a clear title and organized sections with headings
+                        - Capture ALL key information, definitions, and concepts
+                        - Use bullet points for clarity and organization
+                        - Highlight important points, dates, names, and formulas
+                        - Include examples to explain difficult concepts
+                        - Provide comprehensive coverage like a diligent student would create
+                        
+                        Additional context/question from user: {user_query}
+                        
+                        Format the notes in a clean, organized manner with proper headings, subheadings, and emphasis on key points.
+                        """
+                    )
+                    
+                    # AI agent processing
+                    response = multimodal_Agent.run(analysis_prompt, videos=[processed_video])
+                
+                # Display the result
+                st.subheader("📝 Detailed Notes")
+                st.markdown(response.content)
+                
+                # Simple download option
+                st.download_button(
+                    label="Download Notes",
+                    data=response.content,
+                    file_name="video_notes.md",
+                    mime="text/markdown",
+                )
+                
+            except Exception as error:
+                st.error(f"An error occurred during analysis: {error}")
+            finally:
+                # Clean up temporary video file
+                Path(video_path).unlink(missing_ok=True)
+else:
+    st.info("Upload a video file to begin analysis.")