4min chapter

MLOps.community  cover image

Treating Prompt Engineering More Like Code // Maxime Beauchemin // MLOps Podcast #167

MLOps.community

CHAPTER

Python Prompts: How to Generate and Track Data in Reports

So you derive a class that is expected to take some input and generate a prompt. And then, for each one of these text prompt, there'll be an eval function that assesses whether it might assess like, oh, if I pass these numbers, do I get this number out? So by default, we're going to log all of the, the open AI type parameters, like temperature and how long it took to answer how many tokens were used in the prompt. But you can augment that blob with whatever is relevant to your prompt. Right. Maybe the most valuable thing in the nose times where things are changing so fast is the anchor that tests how well you're doing, right?

00:00

Get the Snipd
podcast app

Unlock the knowledge in podcasts with the podcast player of the future.
App store bannerPlay store banner

AI-powered
podcast player

Listen to all your favourite podcasts with AI-powered features

Discover
highlights

Listen to the best highlights from the podcasts you love and dive into the full episode

Save any
moment

Hear something you like? Tap your headphones to save it with AI-generated key takeaways

Share
& Export

Send highlights to Twitter, WhatsApp or export them to Notion, Readwise & more

AI-powered
podcast player

Listen to all your favourite podcasts with AI-powered features

Discover
highlights

Listen to the best highlights from the podcasts you love and dive into the full episode