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import streamlit as st
from pytube import YouTube
from youtube_transcript_api import YouTubeTranscriptApi
from youtube_transcript_api.formatters import SRTFormatter
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
from dotenv import load_dotenv
import os
import tempfile
# Load environment variables
load_dotenv()
API_KEY = os.getenv("GOOGLE_API_KEY")
if API_KEY:
genai.configure(api_key=API_KEY)
# Page configuration
st.set_page_config(
page_title="YouTube Video Summarizer",
page_icon="🎥",
layout="wide"
)
st.title("Phidata YouTube Video Summarizer Agent 🎥🎤🖬")
st.header("Powered by Gemini 2.0 Flash Exp")
@st.cache_resource
def initialize_agent():
return Agent(
name="YouTube Video Summarizer",
model=Gemini(id="gemini-2.0-flash-exp"),
tools=[DuckDuckGo()],
markdown=True,
)
# Initialize the agent
multimodal_Agent = initialize_agent()
# Function to get captions using youtube-transcript-api
def get_youtube_captions(youtube_url):
"""
Retrieves YouTube video captions using youtube-transcript-api.
Parameters:
- youtube_url: The URL of the YouTube video.
Returns:
- The captions of the video in SRT format, or a message if captions are not available.
"""
video_id = youtube_url.split("v=")[-1].split("&")[0]
try:
# Fetch transcript for the video
transcript = YouTubeTranscriptApi.get_transcript(video_id)
# Format the transcript in SRT format
formatter = SRTFormatter()
formatted_transcript = formatter.format_transcript(transcript)
return formatted_transcript
except Exception as e:
return f"Error: {str(e)}"
# YouTube video URL input
youtube_url = st.text_input(
"Enter the YouTube video link",
placeholder="Paste the YouTube video URL here",
help="Provide the link to the YouTube video you want to summarize."
)
if youtube_url:
try:
with st.spinner("Fetching and processing the YouTube video..."):
# Get captions using youtube-transcript-api
captions = get_youtube_captions(youtube_url)
# Check if captions are available
if "Error" not in captions:
# Display captions
st.subheader("Video Captions:")
st.text(captions)
else:
st.error(captions)
# User query input
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..."):
# Upload and process the transcript (captions)
processed_captions = upload_file(captions)
while processed_captions.state.name == "PROCESSING":
time.sleep(1)
processed_captions = get_file(processed_captions.name)
# Prompt generation for analysis
analysis_prompt = (
f"""
Analyze the content of the uploaded YouTube video.
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 = multimodal_Agent.run(analysis_prompt, videos=[processed_captions])
# Display the result
st.subheader("Analysis Result")
st.markdown(response.content)
except Exception as error:
st.error(f"An error occurred during analysis: {error}")
except Exception as e:
st.error(f"An error occurred: {e}")
else:
st.info("Enter a YouTube video link to begin analysis.")
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