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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
import tempfile
from pathlib import Path
from dotenv import load_dotenv
load_dotenv()
import os
GOOGLE_API_KEY=os.getenv("GOOGLE_API_KEY")
if GOOGLE_API_KEY:
genai.configure(api_key=GOOGLE_API_KEY)
# Page configuration
st.set_page_config(
page_title="AI Video Summarizer Tool",
page_icon="🎥",
layout="wide"
)
st.title("AI Video Summarizer Tool 🎥")
st.write("This tool can summarize uploaded vidoes as well as videos from YouTube. It is powered by Gemini.")
@st.cache_resource
def initialize_gemini_agent():
return Agent(
name="AI Video Summarizer",
model=Gemini(id="gemini-2.0-flash-exp"),
tools=[DuckDuckGo()],
markdown=True,
)
## Initialize the agent
video_summarizer_agent=initialize_gemini_agent()
video_type_selection = st.selectbox('Please Select Input Type', ['Enter YouTube URL', 'Upload a video'])
if video_type_selection == 'Upload a video':
# File uploader
uploaded_video_file = st.file_uploader(
"Upload a video file", type=['mp4', 'mov', 'avi'], help="Upload a video for summarization"
)
if uploaded_video_file:
with tempfile.NamedTemporaryFile(delete=False, suffix='.mp4') as temp_summarization_video:
temp_summarization_video.write(uploaded_video_file.read())
summarization_video_path = temp_summarization_video.name
st.video(summarization_video_path, format="video/mp4", start_time=0)
user_query = st.text_area(
"What insights are you seeking from the video?",
placeholder="Ask anything about the video content. The AI agent will analyze and gather additional context if needed.",
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 gathering insights..."):
# Upload and process video file
processed_video = upload_file(summarization_video_path)
while processed_video.state.name == "PROCESSING":
time.sleep(1)
processed_video = get_file(processed_video.name)
# Prompt generation for analysis
analysis_prompt = (
f"""
Analyze the uploaded video for content and context.
Respond to the following query using video insights and supplementary web research:
{user_query}
Provide a detailed, user-friendly, and actionable response.
"""
)
# AI agent processing
response = video_summarizer_agent.run(analysis_prompt, videos=[processed_video])
# Display the result
st.subheader("Results of Video Analysis")
st.markdown(response.content)
except Exception as error:
st.error(f"An error occurred during analysis: {error}")
finally:
# Clean up temporary video file
Path(summarization_video_path).unlink(missing_ok=True)
else:
st.info("Upload a video file to begin analysis.")
# Customize text area height
st.markdown(
"""
<style>
.stTextArea textarea {
height: 100px;
}
</style>
""",
unsafe_allow_html=True
)
elif video_type_selection == 'Enter YouTube URL':
# Input for YouTube video URL
video_url = st.text_input(
"Enter a YouTube video URL",
placeholder="Paste the URL of the video you'd like to summarize",
help="The app will analyze the content of the video based on your query."
)
if video_url:
user_query = st.text_area(
"What insights are you seeking from the video?",
placeholder="Ask anything about the video content. The AI agent will analyze and gather additional context if needed.",
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("Analyzing video and gathering insights..."):
# Generate the analysis prompt
analysis_prompt = (
f"""
Analyze the YouTube video at the following URL: {video_url}.
Respond to the following query using the video content and supplementary web research:
{user_query}
Provide a detailed, user-friendly, and actionable response.
"""
)
# AI agent processing
response = video_summarizer_agent.run(analysis_prompt)
# Display the result
st.subheader("Results of Video Analysis")
st.markdown(response.content)
except Exception as error:
st.error(f"An error occurred during analysis: {error}")
else:
st.info("Enter a YouTube video URL to begin analysis.")
# Customize text area height
st.markdown(
"""
<style>
.stTextArea textarea {
height: 100px;
}
</style>
""",
unsafe_allow_html=True
)
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