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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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