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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
import os
from phi.model.groq import Groq
from phi.tools.youtube_tools import YouTubeTools
# Load environment variables
load_dotenv()
# Configure API keys
API_KEY = os.getenv("GOOGLE_API_KEY")
groq_api_key = os.getenv("GROQ_API_KEY")
if API_KEY:
genai.configure(api_key=API_KEY)
# Page configuration
st.set_page_config(
page_title="Multimodal AI Applications",
page_icon="🌐",
layout="wide"
)
# Tabs for the two applications
tab1, tab2 = st.tabs(["Video Summarizer", "YouTube Video Analyzer"])
# Tab 1: Video Summarizer with Gemini
with tab1:
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,
)
multimodal_Agent = initialize_agent()
video_file = st.file_uploader(
"Upload a video file",
type=['mp4'],
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?",
placeholder="Ask anything about the video content. The AI agent will analyze and gather additional context if needed. This AI agent can search the internet.",
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..."):
processed_video = upload_file(video_path)
while processed_video.state.name == "PROCESSING":
time.sleep(1)
processed_video = get_file(processed_video.name)
analysis_prompt = (
f"""
Analyze the uploaded video for content and context. Provide a detailed summary. Search the internet for similar topics discussed in the uploaded video.
Respond to the following query using video insights and supplementary web research: {user_query}
Provide a detailed, user-friendly, and actionable response.
"""
)
response = multimodal_Agent.run(analysis_prompt, videos=[processed_video])
st.subheader("Analysis Result")
st.markdown(response.content)
except Exception as error:
st.error(f"An error occurred during analysis: {error}")
finally:
Path(video_path).unlink(missing_ok=True)
else:
st.info("Upload a video file to begin analysis.")
# Tab 2: YouTube Video Analyzer with Groq
with tab2:
st.title("YouTube Video Analyzer")
st.header("Analyze Youtube video using video link 🎬 🧷")
try:
youtube_agent = Agent(
model=Groq(id="llama3-8b-8192", api_key=groq_api_key),
tools=[YouTubeTools(), DuckDuckGo()],
show_tool_calls=True,
get_video_captions=True,
get_video_data = True,
description="You are a YouTube agent. Obtain the captions of a YouTube video, analyze its content and context, provide detailed summaries with key points, conduct web research on similar topics, and answer user questions.",
)
except Exception as e:
st.error(f"Error initializing the agent: {e}")
st.stop()
video_url = st.text_input("Enter YouTube Video URL:", "")
user_query = st.text_area("Enter your question about the video (optional):", "")
if st.button("✨ Analyze the Video", key="Analyze_Video_Button"):
if video_url:
with st.spinner("Analyzing..."):
try:
prompt_prefix = """Analyze the YouTube video provided by the URL. Provide a detailed summary of the video, including key points.
Structure the output as follows:
**Detailed Summary:**
[Detailed summary of the video content]
**Key Points:**
* [Key point 1]
* [Key point 2]
* [Key point 3]
... (and so on)
Conduct web research on similar topics discussed in the video to provide additional context.
"""
if user_query:
prompt = f"""{prompt_prefix}
Respond to the following query using video insights and supplementary web research:
{user_query}
Provide a detailed, user-friendly, and actionable response.
Video URL: {video_url}"""
else:
prompt = f"""{prompt_prefix}
Video URL: {video_url}"""
output = youtube_agent.run(prompt)
st.markdown(output.content)
except Exception as e:
st.error(f"Error analyzing the video: {e}")
else:
st.warning("Please enter a YouTube video URL.")
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