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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 time
import google.generativeai as genai
from pathlib import Path
import tempfile
import os
import yt_dlp
from dotenv import load_dotenv
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="Agentic Video Captioning Platform::",
layout="wide"
)
st.title("Generate the story of videos:")
st.header("Agentic Video Captioning Platform:")
@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()
def download_tiktok_video(url: str, output_path: str):
"""Downloads a TikTok video using yt-dlp."""
ydl_opts = {
'outtmpl': output_path, # Path where the video will be saved
'format': 'best', # Download the best quality available
}
try:
with yt_dlp.YoutubeDL(ydl_opts) as ydl:
ydl.download([url])
return True, f"Video downloaded successfully to {output_path}"
except Exception as e:
return False, str(e)
# URL input for TikTok video
video_url = st.text_input("Enter TikTok video URL")
if st.button('Generate the story'):
if not video_url:
st.warning('PLEASE ENTER A VALID URL')
else:
# Download the TikTok video
with st.spinner("Downloading video..."):
temp_video_path = os.path.join(tempfile.gettempdir(), 'tiktok_video.mp4')
success, message = download_tiktok_video(video_url, temp_video_path)
if not success:
st.error(f"Error downloading video: {message}")
else:
st.success(message)
# Display the video
st.video(temp_video_path, format="video/mp4", start_time=0)
try:
with st.spinner("Generating the story of the video"):
# Upload and process the video
processed_video = upload_file(temp_video_path)
while processed_video.state.name == "PROCESSING":
time.sleep(1)
processed_video = get_file(processed_video.name)
# Analysis prompt
analysis_prompt = (
f'''
Analyze the video thoroughly and provide a comprehensive storyline. The total generation should not be more than 500 words. As a whole from the video, detail the following aspects:
1. **Story:** How the set scene introduced and tone is set. What is happening in the scene? Describe key visuals and actions.
2. **Characters**: Identify each character, noting their expressions, attire, actions, and interactions. Highlight emotional nuances and gestures.
1. **Narration or Voiceover**: Describe what types of narrations or voiceovers are used in the video.
3. **Transitions and Pacing**: Describe scene changes, including cuts, fades, zooms, or shifts in focus, and how they affect the flow.
4. **Mood and Tone**: Capture the overall mood and tone of each scene, mentioning any music or sound effects that enhance these elements.
5. **Visible Texts or Brandings**: Capture all the visible texts from the videos and brandings too only if some brandings of product or service is done.
Conclude with a cohesive summary that ties the scenes together, highlighting all promotional themes, ensuring each brand and key text is accurately referenced in the storyline.
'''
)
# AI agent processing
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: {error}")
finally:
# Delete the downloaded TikTok video
try:
os.remove(temp_video_path)
st.info("Downloaded TikTok video deleted.")
except Exception as e:
st.warning(f"Failed to delete video: {e}")
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