Spaces:
Runtime error
Runtime error
File size: 3,881 Bytes
1fc91f5 dda0b8c 1fc91f5 dda0b8c 1fc91f5 dda0b8c |
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 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 |
# Importamos la librería
from youtube_transcript_api import YouTubeTranscriptApi
import re
from langchain.vectorstores import FAISS
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.embeddings import AwaEmbeddings
import os
import openai
import streamlit as st
def get_transcript(url):
video_id = re.search(r"(?<=v=)([^&#]+)", url)
video_id = video_id.group(0)
# retrieve the available transcripts
transcript_list = YouTubeTranscriptApi.list_transcripts(video_id)
# iterate over all available transcripts
for transcript in transcript_list:
subtitles = transcript.translate('en').fetch()
# Imprimimos los transcript
text = ''
for sub in subtitles:
text = text + ' ' + sub['text']
return text
embeddings = AwaEmbeddings()
text_splitter = RecursiveCharacterTextSplitter(
# Set a really small chunk size, just to show.
chunk_size = 1500,
chunk_overlap = 100,
length_function = len,
is_separator_regex = False,
)
def chat(question):
if 'database' in st.session_state:
docs = st.session_state.database.similarity_search(question)
prompt = [
{"role": "system", "content": """You are my Youtube Asisstant. I will pass you texts from a Youtube Video Transcrip and I need you to use them to answer my question from the Youtube Video.
Please do not invent any information, and I am asking about information in the Youtube Video."""},
{"role":"user", "content": f"Context:{docs}"},
{"role":"user", "content": f"Question:{question}"},
]
response = openai.ChatCompletion.create(
model="gpt-3.5-turbo-0613",
messages=prompt,
temperature = 0
)
return response["choices"][0]["message"]["content"]
else:
return "Error, not generated database"
#------------------------------------------------------------- APP STREAMLIT--------------------------------------------------------------------
st.title("Ask Question Youtube Videos")
with st.sidebar:
if "api" not in st.session_state:
api_key= st.text_input(label="api", placeholder="API Key from OpenAI", label_visibility="hidden")
if st.button(label="Save"):
os.environ["OPENAI_API_KEY"] = api_key
openai.api_key = api_key
st.session_state['api'] = api_key
else:
url = st.text_input(label="url", placeholder="Youtube Video URL", label_visibility="hidden")
if st.button(label="Save"):
st.session_state['url'] = url
info = get_transcript(url)
texts = text_splitter.create_documents([info])
st.session_state['database'] = FAISS.from_documents(texts, embeddings)
if "api" not in st.session_state:
st.write("Please, introduce your OpenAI API key to ask questions to any YouTube Video")
elif 'url' not in st.session_state:
st.write("Please, introduce link URL from the YouTube Video")
else:
# Initialize chat history
if "messages" not in st.session_state:
st.session_state.messages = []
# Display chat messages from history on app rerun
for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.markdown(message["content"])
# Accept user input
if prompt := st.chat_input("What is up?"):
# Add user message to chat history
st.session_state.messages.append({"role": "user", "content": prompt})
# Display user message in chat message container
with st.chat_message("user"):
st.markdown(prompt)
# Get response from your custom chat function
response = chat(prompt)
# Display assistant response in chat message container
with st.chat_message("assistant"):
st.markdown(response)
st.session_state.messages.append({"role": "assistant", "content": response}) |