Spaces:
Running
Running
File size: 2,251 Bytes
bf12aca |
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 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 |
import os
import streamlit as st
import re
from modules.layout import Layout
from modules.utils import Utilities
from modules.sidebar import Sidebar
from youtube_transcript_api import YouTubeTranscriptApi
from langchain.chains.summarize import load_summarize_chain
from langchain.chains import AnalyzeDocumentChain
from youtube_transcript_api import YouTubeTranscriptApi
from langchain.llms import OpenAI
import os
from langchain.text_splitter import CharacterTextSplitter
st.set_page_config(layout="wide", page_icon="💬", page_title="Robby | Chat-Bot 🤖")
# Instantiate the main components
layout, sidebar, utils = Layout(), Sidebar(), Utilities()
st.markdown(
f"""
<h1 style='text-align: center;'> Ask Robby to summarize youtube video ! 😁</h1>
""",
unsafe_allow_html=True,
)
user_api_key = utils.load_api_key()
sidebar.about()
if not user_api_key:
layout.show_api_key_missing()
else:
os.environ["OPENAI_API_KEY"] = user_api_key
script_docs = []
def get_youtube_id(url):
video_id = None
match = re.search(r"(?<=v=)[^&#]+", url)
if match :
video_id = match.group()
else :
match = re.search(r"(?<=youtu.be/)[^&#]+", url)
if match :
video_id = match.group()
return video_id
video_url = st.text_input(placeholder="Enter Youtube Video URL", label_visibility="hidden", label =" ")
if video_url :
video_id = get_youtube_id(video_url)
if video_id != "":
t = YouTubeTranscriptApi.get_transcript(video_id, languages=('en','fr','es', 'zh-cn', 'hi', 'ar', 'bn', 'ru', 'pt', 'sw' ))
finalString = ""
for item in t:
text = item['text']
finalString += text + " "
text_splitter = CharacterTextSplitter()
chunks = text_splitter.split_text(finalString)
summary_chain = load_summarize_chain(OpenAI(temperature=0),
chain_type="map_reduce",verbose=True)
summarize_document_chain = AnalyzeDocumentChain(combine_docs_chain=summary_chain)
answer = summarize_document_chain.run(chunks)
st.subheader(answer)
|