File size: 2,045 Bytes
f7a8c8e 295d67b f7a8c8e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 | import streamlit as st
import os
import langchain
import langchain_huggingface
import huggingface_hub
from langchain_community.document_loaders import YoutubeLoader
from langchain_huggingface import HuggingFaceEndpoint,ChatHuggingFace
os.environ['HUGGINGFACEHUB_API_TOKEN'] = os.getenv("hf_token")
os.environ['HF_TOKEN'] = os.getenv("hf_token")
meta_llm=HuggingFaceEndpoint(repo_id="meta-llama/Llama-3.1-8B-Instruct",
provider="nebius",
temperature=0.5,max_new_tokens=150,
task="conversational")
model=ChatHuggingFace(llm=meta_llm,
repo_id="meta-llama/Llama-3.1-8B-Instruct",
provider="nebius",
temperature=0.5,
max_new_tokens=50,
task="conversational")
def get_youtube_transcript(url):
loader = YoutubeLoader.from_youtube_url(url)
docs = loader.load()
return docs[0].page_content
# 📝 Function to summarize
def summarize_youtube_video(url):
transcript = get_youtube_transcript(url)
if len(transcript) > 3000:
transcript = transcript[:3000] # Trim to avoid token limit
prompt = f"Summarize this YouTube video transcript:\n\n{transcript}"
response = model.invoke(prompt)
return response.content
st.set_page_config(page_title="YouTube Video Summarizer", layout="centered")
st.title("🎬 YouTube Video Summarizer")
st.write("Paste a YouTube video URL below to get a concise summary using Llama 3.1 🧠")
youtube_url = st.text_input("📥 Enter YouTube URL:")
if st.button("Summarize"):
if youtube_url.strip() == "":
st.warning("Please enter a valid YouTube video URL.")
else:
with st.spinner("Fetching and summarizing..."):
try:
summary = summarize_youtube_video(youtube_url)
st.success("✅ Summary Generated:")
st.write(summary)
except Exception as e:
st.error(f"Something went wrong: {e}") |