Question answering over YouTube videos with embeddings and LLMs.
Project description
YouTube Question Answer
Simple experiment for question answering on YouTube videos using embeddings and the top n YouTube search result transcripts.
The function will take a question and optionally a YouTube search query (otherwise an LLM will auto-generate one), will compile transcripts for each video result, generate an embedding index using the transcripts and then answer the question using the relevant embeddings.
The function will return both a string response and a list of sources that were used for the answer.
Installation
The package can be installed from PyPI with pip install youtube-qa
. Make sure to set your OPENAI_API_KEY
environment variable before using.
Example
from youtube_qa.answer_question import answer_question_using_youtube
response, sources = answer_question_using_youtube(
search_term="peter attia running endurance",
question="how to train for endurance",
)
print(response)
Or to let the LLM auto-generate a relevant search query:
from youtube_qa.answer_question import answer_question_using_youtube
response, sources = answer_question_using_youtube(
question="how to train for endurance",
)
print(response)
Project details
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