yt-semantic-search VS generate-subtitles

Compare yt-semantic-search vs generate-subtitles and see what are their differences.

yt-semantic-search

OpenAI-powered semantic search for any YouTube playlist – featuring the All-In Podcast. 💪 (by transitive-bullshit)

generate-subtitles

Generate transcripts for audio and video content with a user friendly UI, powered by Open AI's Whisper with automatic translations and download videos automatically with yt-dlp integration (by mayeaux)
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yt-semantic-search generate-subtitles
6 32
508 671
- -
3.2 0.0
about 1 year ago about 1 year ago
TypeScript JavaScript
MIT License -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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yt-semantic-search

Posts with mentions or reviews of yt-semantic-search. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-09.
  • Dev LLM stack, production LLM stack, example projects, & things you'll discover
    2 projects | news.ycombinator.com | 9 Feb 2023
    The dev LLM stack

    - OpenAI + Pinecone + GPT-Index or Langchain

    - Perhaps also dust.tt for playing around with prompts, kinda like a more advanced gpt playground --

    The production LLM stack

    - The dev stack

    - OpenAI + Pinecone + GPT-Index or Langchain

    - arXiv for finding new research to build on

    - Prompt platforms such as Humanloop

    - ML frameworks such as PyTorch, Keras, Tensorflow

    - MLOps tools such as MLflow, Kubeflow, Metaflow, Airflow, Seldon Core, TFServing

    Example OpenAI Projects

    -

    -

    -

    -

    -

    What OpenAI/MSFT should do

    - Fund "AI white mirror" -- a tv show that has beautiful visions a future where intelligence costs ~0

    Things you'll probably discover

    - Embeddings work ok, but not great, from a user perspective. As a developer they're great to work with. As a user, the results aren't ranked quite right. Embeddings use cases will be better with GPT-4 or GPT-4.5.

    - All of the obvious gpt apps will be built. We'll get hundreds of basic gpt wrapper apps (and some of them will be big businesses!), hundreds of basic embeddings search apps. If someone can think of the idea and make it without needing specific relationships, credibility, or experience, then it'll probably exist by Summer 2023.

    - The developer energy in this space is intense. Adults are going to hackathons to build ai apps. This is awesome.

    - Devs using gpt will soon be a large enough market that startups will exist and succeed just by selling to developers that are using gpt-3 in production. We already saw it a little bit, but we'll get many more startups here.

    - How could AI not be better than me at all computer based things within 10 years?

    - AI is kinda like a kid. When they're young, they're not that smart. Then all of a sudden, they've gotten enough training data, and their brain (compute!) has grown, and they're doing useful stuff. This is related to why people will say that building models can feel frustrating because it doesn't work well for ages and then all of a sudden it works (CEO of Oasis said this, CTO of OpenAI said this, and Instagram co-founder said this).

    Would love input and feedback on this. I have similar things that I'm going to submit, covering what builders and engineers should do, what vector database to use, why no one else made ChatGPT before OpenAI, things holding ai powered apps back, and some other stuff like that. If you want a preview and are happy to give feedback, then email is in my profile.

  • Show HN: Semantic Search for Any Video
    5 projects | news.ycombinator.com | 4 Jan 2023
    Are you using whisper for transcription?

    For https://github.com/transitive-bullshit/yt-semantic-search, I'm using YouTube's built-in transcriptions which definitely aren't as high quality, but they work well enough to power the semantic search.

  • Show HN: OpenAI-powered semantic search for the All-In Podcast
    2 projects | news.ycombinator.com | 30 Dec 2022
  • OpenAI-powered semantic search for the All-In Podcast
    1 project | news.ycombinator.com | 21 Dec 2022

generate-subtitles

Posts with mentions or reviews of generate-subtitles. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-11-18.

What are some alternatives?

When comparing yt-semantic-search and generate-subtitles you can also consider the following projects:

openai-cookbook - Examples and guides for using the OpenAI API

whisper-asr-webservice - OpenAI Whisper ASR Webservice API

semantic-search-nextjs-pinecone-langchain-chatgpt - Embeds text files into vectors, stores them on Pinecone, and enables semantic search using GPT3 and Langchain in a Next.js UI

codesearch - Semantic Code Search tool. Query your codebases using natural language

whisper.cpp - Port of OpenAI's Whisper model in C/C++

client-vector-search - A client side vector search library that can embed, store, search, and cache vectors. Works on the browser and node. It outperforms OpenAI's text-embedding-ada-002 and is way faster than Pinecone and other VectorDBs.

pyannote-audio - Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding

youtube-summarized-browser-extension - YouTube Summarized - Browser extension for summarizing YouTube videos using GPT3 🎥

frogbase - Transform audio-visual content into navigable knowledge.

subtitleedit - the subtitle editor :)

NeMo - A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)