[HN Gopher] Show HN: Scribbler - Podcast Summaries Using GPT
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Show HN: Scribbler - Podcast Summaries Using GPT
Hey, we're Phil and Ian, the founders of Scribbler. We're huge
podcast fans, but found we never had enough time to soak it all in.
So, we built Scribbler - a tool that leverages GPT to condense
podcast episodes into bite-sized summaries for when life's too
busy. Now, we can catch the best bits from any episode, discover
new shows, and best of all, stop wasting valuable time figuring out
what's worth listening to and what's not. We hope you'll find it
useful!
Author : _fill
Score : 78 points
Date : 2023-06-14 13:43 UTC (9 hours ago)
(HTM) web link (app.scribbler.so)
(TXT) w3m dump (app.scribbler.so)
| edison0xyz wrote:
| Very good product! I've been using it to catch up on certain
| podcasts. But was just wondering if it might also work for some
| things like transcribing certain hearings like CPI announcement
| videos or statements made by politicians?
|
| Can see that this is a transcriber for everything that is a
| generic media.
| FanaHOVA wrote:
| Thanks for having Latent Space on it! :) I noticed we have two
| entries (because we changed the full name of the podcast) and
| some episodes are there twice if we tweaked the title. Are you
| pulling from our RSS feed?
|
| Also curious about what models you are using on the backend; we
| use Claude 100k to do timestamps generation for show notes and
| whisper-diarization [0] for transcription. The main post for each
| episode is manually written though, as we try to write a higher
| level summary of the episode + topics in it.
|
| [0] https://replicate.com/thomasmol/whisper-diarization
| fils wrote:
| I know the podcast app Snipd (https://www.snipd.com/) offers some
| similar things. It will build chapters with AI generated
| summaries of each chapter.
|
| Not sure if they are leveraging that for search and discovery or
| not but it looks like they do (https://www.snipd.com/podcasters)
|
| A user can request it for any podcast and it doesn't seem to take
| that long the times I have tried it.
| alexcannan wrote:
| Very cool! I'm curious--I'd imagine that some long tail podcasts
| have transcripts that are too long to fit within a standard
| context window. Do you have some strategy for handling these?
| victorbjorklund wrote:
| Not OP but I have seen several use cases where first
| summarising parts and then summarising the summaries have been
| used.
| davepeck wrote:
| There are a few strategies in use today. All involve splitting
| the content to be summarized into chunks smaller than the
| context size, summarizing each, and building a full final
| summary from there (potentially in multiple steps).
|
| I wouldn't necessarily recommend _using_ LangChain, but their
| summarization docs might be of interest:
| https://python.langchain.com/en/latest/modules/chains/index_...
| BigElephant wrote:
| What would you use besides LangChain?
| davepeck wrote:
| I've found it preferable to build directly on top of
| OpenAI's API. (I've also written a simple API wrapper for
| llama.cpp hosted LLMs.) Over time I've built a small
| library of utilities, including for summarization. It's not
| that much code.
|
| I don't know if this is a spicy or a generally-agreed-upon
| take: my feeling is that, while LangChain was useful in
| that it helped the community codify some early intuitions
| about LLM invocation patterns, it's basically a grab bag of
| partially complete somewhat disconnected utilities. It nods
| to composability but, in practice, its pieces often don't
| fit together. On the Python side, it suffers from poor
| typing: when creating a chain, it's often impossible to
| know what the full set of configuration options is without
| digging deep into LangChain's code. It's catch-as-can
| whether you can deeply configure specific sub-aspects of a
| chain.
|
| There are other things I want in my own code at the moment,
| including keeping track of how many input/output tokens
| each of my actions takes, etc.
|
| I dunno, maybe I'm the only one here. Curious what others
| think.
| thatcherthorn wrote:
| I am also interested in the answer to this
| majimak wrote:
| Checked out and it works great! Just thinking if it would be even
| better if there's some way to make all that knowledge searchable,
| or to find some way to help users discover podcast summaries that
| they might be into?
| Solvency wrote:
| You've basically created a really great show notes generator.
| Kudos.
|
| What I'd really value is a podcast powered GPT chatbot, or at the
| very least, a very good search engine.
|
| Podcasts like Peter Attia's or Paul Saladino's contain so much
| good knowledge on human biology in the context of nutrition, but
| it's buried in longform conversations. I often wish I could find
| a "soundbyte", or in this case, a textbyte. Paul has had guests
| perfectly articulate the top 10 functions of insulin, or pose
| perfect explanations for the value of saturated fat and its
| demonization via the sugar industry. Hell, there is a plethora of
| knowledge around basic salt that you don't find very easily in
| Google.
|
| Being able to search for or rapidly recall things like this would
| be so useful.
| iamflimflam1 wrote:
| That's kind of what's missing from all these summarisation
| services - what are the actual bits of content that are worth
| listening to amongst all the padding?
| huevosabio wrote:
| I built a proof of concept [0] of exactly this because I listen
| to tons of podcasts but then fetching back that info is a pain.
| I left it at that because I saw there were plenty of other
| efforts doing something similar (e.g. [1])
|
| [0] https://youtu.be/Q6G2m4xw3E4
|
| [1] https://podsmart-frontend.vercel.app/
| nittanymount wrote:
| nice one ! thanks for sharing
| voisin wrote:
| FWIW, I've tried to sign up and the email verification code has
| not been received despite having it resent multiple times and
| checked spam and confirmed the email address.
| causi wrote:
| We are _so_ close to AI-powered podcast sponsorblock I can taste
| it.
| dewey wrote:
| Maintainer of sponsorblock said they don't think it'll work
| https://github.com/ajayyy/SponsorBlock/issues/1766 but there's
| https://github.com/xenova/sponsorblock-ml.
| ajayyy wrote:
| I was referring to video, because you need to take into
| account visuals too. It would be simpler when it is audio-
| only.
| 101008 wrote:
| I hope this never happens. Sponsors in the middle of podcasts,
| that are not targeted, are totally fine. You want people to
| produce something for you and consume it for free? If you don't
| want ads pay for it.
| wahnfrieden wrote:
| Not the one and only way for society to organize
| causi wrote:
| I don't even fast forward through ads that aren't obnoxious.
| When it starts with three solid minutes of ads, then has a
| block of ads in the middle, then more at the end for a half-
| hour show, I'm either skipping or not listening.
|
| _If you don 't want ads pay for it._
|
| I do. Funny enough a lot of creators seem to be too lazy to
| edit _all_ the ads out of their "ad-free" feeds. In one
| instance a creator I backed had more ads in their ad-free
| premium feed than I had in my original downloads of the show
| from when they got started. Screw that.
| ramg wrote:
| I like this idea! Thanks for sharing.
|
| Will I be able to point it at any podcast? The ones I saw look
| interesting but are not what I normally listen to.
|
| I assume you can take any audio sample (say, a monologue) and
| generate a summary of it. I wonder if students would do this with
| their lectures.
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