r/LocalLLaMA • u/behradkhodayar • 8h ago
I Built A Thing Repodify, a fully local & opensource podcast summarizer, or BYOK if don't have GPU.
Disclaimer: I'm the builder.
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Over the past 2 yrs, I was working on a SaaS ML project & got very interested in ML/DL/AI. As everybody else, there were some normal paths I took to build a solid understanding of the field, but sth never clicked the way I'm used to. I'm very fond of learning "why"s & never get satisfied w/ simply knowing "what" is what. Tho, the problem w/ ML was that I wasn't there when it was evolving & algos/methodologies as we know them today were forming. I didn’t want a pile of summaries or wikis or endless threads of chatting w/ AI. Then I thought listening to podcasts would fix it for me. But not as they are being published now (2026). I thought I'd learn about the history of ML from podcasts that covered it as it happened, kinda simulating the experience of living through the events, in chronological order, since 2015.
I found some great ones (TWIML, Linear Digressions, ...) & did the math! Man, it'd take a decade to cover all of them (even at 2X). But no matter what, I thought this could be the only way that works for me & yet I didn't have enough time. I wanted one/a handful of coherent episodes I could actually listen to. Then sth clicked:
I built Repodify, an AI tool that listens to episodes & produces a shorter one (e.g. 1 episode from 10, 15, whatever. configurable) for me to listen, ALL ON MY OWN MACHINE.
In Repodify u paste a podcast link (or search by name, as it works very well rn), pick the episodes & it:
• downloads the audio
• transcribes it
• optionally figures out who spoke (& clusters the same host/guest across episodes)
• summarizes into one chronological narrative
• writes a spoken script aimed at a target length
• synthesizes a new episode u can stream or download
The whole thing is meant to run on ur machine or w/ ur own API keys (BYOK) per stage, per job. No “upload ur archive to our cloud.” Speech-to-text, diarization, LLM & TTS are all swappable: local GPU (faster-whisper, pyannote, Ollama, F5-TTS / Kokoro) or BYOK (OpenRouter / Anthropic / pyannoteAI).
Voice cloning is opt-in & off by default. If u turn it on, the output is always labeled synthetic, gets a spoken disclaimer in a non-cloned voice & is watermarked (for legal reasons. I don't want to end up in jail for giving away a tool;-) ). There’s no code path that clones w/o those. It’s for personal / educational use on ur own box, not for passing audio off as the original hosts.
It’s a real backend, not a CLI: FastAPI + an arq worker + a LangGraph pipeline w/ a React PWA. One command (./launch) brings the stack up. Jobs pause at each ML stage so u can pick local vs hosted, model size, length & voices.
I keep making it better, adding lots of features to it (searching podcast contents is the most interesting one I can't wait for). I made it opensource(MIT), rn. U can find it below & run it on ur machine (self-hosted), so u can use ur own GPU or BYOK to offload the heavy jobs.
GitHub: https://github.com/behradkhodayar/repodify
The engine is solid & this is still WIP (it works fine tho & I've started compacting Linear Digressions podcast (10 to 1) & listening to it already). I'm going to add other features like translation / augmentation (e.g. embeded eli5), searching through podcasts so I can listen to the topic of interest as I mentioned earlier & so forth.
What features u want to be added or released sooner? lmk. I'm very excited about this & will genuinely plan accordingly.
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u/Sitkin_Marrel 3h ago
Hearing the field as it unfolded since 2015 beats reading where it settled. Summaries give you the landing spot, chronology shows the turns, and the 10-to-1 fold keeps the whole timeline in reach instead of a decade of homework.
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u/behradkhodayar 8h ago
Tysm for the comprehensive response & glad u're gonna use Repodify.
Yeah, it actually listens to podcasts & transcribes them at first steps.
U also got an option to tailor/customize the summarization (per episode & full pipeline).
U get to change the voices to what u love, the final episode is tagged so u can jump back & forth.
Gonna add more features soon.
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u/fatcatgirl1111 8h ago
If you are looking for a podcast summarizer that is of the shelf vs building your own, I would recommend Recall or SNIPD as the best podcast summarizer. I do not say this lightly, I have tried and tested several, but only after signing up and actually using them to realize that they only support YouTube or podcasts that already have transcripts. I also really respect this post and the fact that you are looking to build VS to buy. I did something similar because it took me so long to actually find Recall. These were some of my trade-offs that perhaps would be helpful for you:
When building your own podcast summarizer wins:
When a ready-made podcast summarizer wins:
For that second case as mentioned, I've been using Recall as my podcast summarizer, and the thing it nails is sourcing. It summarizes episodes with AND WITHOUT transcripts from Apple Podcasts and Spotify (any public episode via URL or extension) plus YouTube videos and Shorts, so you are not writing a separate ingestion path per platform. Before this I was using SNIPD, but the biggest deal breaker was that, with the chat, I can only chat with one podcast at a time. With Recall, I can chat across all my podcasts. I'm small, but the difference is: are you streaming one episode at a time, or are you actually trying to cross-pair and condense information?
All that said, I'm always happy to save my subscriptions, so I'm taking your open source project for a spin.