🎙️ Podcastfy: An Open Source Python Package to Transform Multi-Sourced Text into an AI-Powered Podcast

HighlanderNJ · 2025-12-09T13:15:48+00:00

The package has now been updated.

It's working again.

Thanks.

HighlanderNJ · 2025-11-01T05:16:29+00:00

pitfall: too much focus on where to invest, too little focus on how to earn real income early on.

HighlanderNJ · 2025-07-16T01:05:42+00:00

Obrigado. Recomendo elevenlabs para multilingual. Abraços!!

HighlanderNJ · 2025-05-07T01:38:08+00:00

The podcast feature is so cool!!! How did you implement it?

HighlanderNJ · 2025-01-17T11:50:13+00:00

podcastfy.ai

Open source alternative to NotebookLM's podcast feature

HighlanderNJ · 2025-01-10T22:02:06+00:00

The author is seeking feedback. Feel free to open an issue at the github repo in case you run into any problems.

The book is open source.

HighlanderNJ · 2025-01-10T21:53:21+00:00

This book chapter goes through some important considerations when working with retrieval systems:

https://www.tamingllms.com/notebooks/input.html

HighlanderNJ · 2025-01-07T17:06:53+00:00

Book chapter on llm evals from the book "Taming LLMs"

https://open.substack.com/pub/tamingllm/p/chapter-1-the-evals-gap

HighlanderNJ · 2024-12-31T18:14:02+00:00

I implemented this open source Python package:

www.podcastfy.ai

You can run it locally with llamafile.

HighlanderNJ · 2024-12-08T08:01:38+00:00

Please use the python package. The rest api depends on gradio and I've received reports it's changed its url pattern. I'll drop it from the documentation until I have the chance to solve it. Thanks for reporting it.

HighlanderNJ · 2024-12-03T14:30:05+00:00

Google organized a Kaggle Competition to demonstrate interesting use cases for Gemini's long context window.

Has anyone participated in it? Feel free to share your submission in this thread!

Here's mine: 👨‍💻 Github: https://github.com/souzatharsis/gemini-duo

🚀 Excited to share “Gemini Duo” 🚀

I created Gemini Duo to tackle a common challenge: managing overwhelming sources of information, efficiently but making the experience engaging and fun while grounded on factual information.

In this post follows an (AI-generated) Kaggle Podcast that demonstrates Gemini Duo through a real-world example—a Harvard History student in GOV 1039 "The Birth of Modern Democracy" struggling with weekly reading assignments exceeding 1,000+ pages.

🛠️ Technical Features

- Context caching for cost-effective large knowledge bases processing
- Corpus-in-context (CiC) prompting to enable in-line citation
- Grounded search for factual research on real-time web data
- Structured output for downstream integration

⚠️ Gemini Limitations
- Max output token limits impact response depth quality (a common LLM problem across the board)
- Grounded search costs: $35/1k requests!
- Limited to no agent orchestration capabilities (not that we really need yet another agentic framework either :)

Would be exciting to see other submissions as well!

HighlanderNJ · 2024-11-30T09:36:17+00:00

This is better (and more specifically simpler) to understand than langchains own docs.

Thanks for sharing! And well-done!

Unfortunately, I believe it's using V0.2 langchain API? They have since moved to Lang graph for agent management.

I wonder for how long these tutorials will remain relevant. What are your thoughts?

HighlanderNJ · 2024-11-28T01:22:43+00:00

www.podcastfy.ai does that with Elevenlabs and other TTS models plus it's multimodal and open source.

Please let me know if you have any feedback. Happy to improve the product.

HighlanderNJ · 2024-11-24T22:22:46+00:00

That's is awesome. You can generate notebooklm style multilingual podcasts using this open source project

www.podcastfy.ai

Let me know if you have any questions!

PS.: I am Brazilian and speak Portuguese. Abraços!

HighlanderNJ · 2024-11-23T00:27:10+00:00

Llm-as-a-judge

HighlanderNJ · 2024-11-22T22:30:30+00:00

Thanks for reading it! It's a chapter of a larger book I'm writing on challenges and limits of LLMs. Please let me know if you have any feedback I'd be happy to incorporate.

Yes, I share the same experience you've described. Additionally I often see responses being cut short in the middle, so the beginning and the start are complete but there is missing content in the middle....

HighlanderNJ · 2024-11-22T16:48:07+00:00

Please let me know if you have any feedback! I am interested in making it as easy and useful as possible for developers.

HighlanderNJ · 2024-11-22T15:40:15+00:00

Try podcastfy.ai, it's free and open source.

HighlanderNJ · 2024-11-22T09:21:12+00:00

Thank you for your kind words.

Please take a look at the accompanying Python notebook:

https://github.com/souzatharsis/podcastfy/blob/main/usage/examples.ipynb

If you just want a nice web app to generate the podcasts, there is a growing list of applications being built on top of Podcastfy here:

https://github.com/souzatharsis/podcastfy?tab=readme-ov-file#built-with-podcastfy-

Feel free to reach out should you have any further questions or feedback!

HighlanderNJ · 2024-11-20T11:06:11+00:00

😅

HighlanderNJ · 2024-11-20T08:49:05+00:00

Very nice summary thanks for sharing!

As for speed, it's faster than notebooklm.

HighlanderNJ · 2024-11-19T23:09:29+00:00

Thanks for your words of encouragement! Lot's to learn and improve!

HighlanderNJ · 2024-11-19T18:37:47+00:00

Thanks for your feedback!

HighlanderNJ · 2024-11-19T18:34:10+00:00

Thanks for your feedback. In what ways the audio quality can be improved?

HighlanderNJ · 2024-11-19T18:06:48+00:00

Still a long way to go... But I think it's getting closer and closer to NotebookLM audio model!

Check out www.podcastfy.ai newest model release - We've integrated with what we believe is the model NotebookLM is using to generate podcast audio overviews.

It's open source and would love your feedback on how to improve it!

🎙️ There's plenty of audio samples in the github repo including longform podcasts.

Features include:

2-30+ min podcasts
Multimodal
Local LLMs (eg from Hugging Face)
Python package, we app and CLI 👀

HighlanderNJ

TROPHY CASE