import os import streamlit as st from models import CLIP, T2T from tasks import Summary, VideoSearch from log_generation import download_youtube, extract_video_frames, generate_log os.system('pip uninstall opencv-python-headless -y') os.system('pip uninstall opencv-python -y') os.system('pip install opencv-python') st.set_page_config(page_title="Socratic Models Demo", page_icon="", layout="wide") st.title("Socratic Models Demo") if "vlm" not in st.session_state: st.session_state.vlm = CLIP() if "llm" not in st.session_state: st.session_state.llm = T2T() col1, col2, _ = st.columns([2, 2, 3]) with col1: url = st.text_input( "YouTube Video URL", "https://www.youtube.com/watch?v=tQG6jYy9xto" ) video_id = url.split("watch?v=")[-1] with col2: st.video(url) if not os.path.exists(f"{video_id}/history.txt"): st.write("Video not found locally. Downloading may take several minutes. Continue?") click = st.button("Download") if not click: st.stop() st.success("Downloading...") download_youtube(url) st.write("Extracting frames...") extract_video_frames( f"{video_id}/{video_id}.mp4", dims=(600, 400), sampling_rate=100 ) st.write("Generating log...") generate_log( f"{video_id}/history.txt", f"{video_id}", st.session_state.vlm, st.session_state.llm, ) refresh = st.button("Click to refresh") if not refresh: st.stop() search = VideoSearch(video_id, st.session_state.vlm) st.title("Video Search") query = st.text_input("Search Query", "working at my computer") images = search.search_engine(query) with st.expander(label="See results"): for image in images: st.image(image) st.title("Event Summaries") summ = Summary(video_id, st.session_state.llm) summaries = summ.generate_summaries() with st.expander(label="See results"): for (prompt, result) in summaries: st.markdown("*Event Log*") st.write(prompt) st.markdown("*Summary*") st.write(result) st.title("Video Event Log") with open(f"{video_id}/history.txt", "r") as f: st.text(f.read())