PDF to Podcast (via) At first glance this project by Stephan Fitzpatrick is a cute demo of a terrible sounding idea... but then I tried it out and the results are weirdly effective. You can listen to a fake podcast version of the transformers paper, or upload your own PDF (with your own OpenAI API key) to make your own.
It's open source (Apache 2) so I had a poke around in the code. It gets a lot done with a single 180 line Python script.
When I'm exploring code like this I always jump straight to the prompt - it's quite long, and starts like this:
Your task is to take the input text provided and turn it into an engaging, informative podcast dialogue. The input text may be messy or unstructured, as it could come from a variety of sources like PDFs or web pages. Don't worry about the formatting issues or any irrelevant information; your goal is to extract the key points and interesting facts that could be discussed in a podcast. [...]
So I grabbed a copy of it and pasted in my blog entry about WWDC, which produced this result when I ran it through Gemini Flash using llm-gemini:
cat prompt.txt | llm -m gemini-1.5-flash-latest
Then I piped the result through my ospeak CLI tool for running text-to-speech with the OpenAI TTS models (after truncating to 690 tokens with ttok because it turned out to be slightly too long for the API to handle):
llm logs --response | ttok -t 690 | ospeak -s -o wwdc-auto-podcast.mp3
And here's the result (3.9MB 3m14s MP3).
It's not as good as the PDF-to-Podcast version because Stephan has some really clever code that uses different TTS voices for each of the characters in the transcript, but it's still a surprisingly fun way of repurposing text from my blog. I enjoyed listening to it while I was cooking dinner.
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