Langfuse 2.0 - the open source LLM engineering platform

When I found Langfuse, I was so impressed that I made it my priority to integrate it CVToBlind's product stack. Having the ability to not only track the cost of my prompts, but also compare them between different LLM's, group each calls by various ID's and track individual user usage - this is a killer set of features, all while staying well within the free tier. Their recent addition of Posthog integration allowed for us to track our product usage even better. I did miss one feature to fully support my needs, but since it's open source I could just add that code myself - and that's exactly what I did. Working with @marc_klingen has been great, the code is in a great shape and they definitely have my confidence in serving our prompts for production use. We need more products like this. Best of luck, keep it up!

Nice!

Very intuitive sign up process

Amazing tool. Congratulations on the launch!

LLMs always go over my head but not Langfuse.

Langfuse revolutionizes language learning with its innovative approach on LLM apps. By combining cutting-edge technology with proven language acquisition methods, Langfuse offers a comprehensive platform for learners of all levels. Its adaptive learning algorithms tailor lessons to individual proficiency levels, ensuring efficient and effective progress. With features like immersive practice exercises, real-time feedback, and interactive lessons, Langfuse makes language learning engaging, rewarding, and accessible for users worldwide.

Really well done, very smoothly put together! Well done on this excellent product, team! 🙌

We've been using Langfuse since v1 — and have been loving it! The pace of improvements is crazy. Also highly recommend their Posthog integration to keep all your analytics — including LLMs — in one place.

Damn @clemo_sf ! Congratulations on the launch of Langfuse 2.0 and on your success with the Golden Kitty award—what an achievement! 🌟 It's fantastic to see how Langfuse has evolved from an observability tool to a comprehensive LLM engineering platform. The inclusion of features like the LLM Playground and prompt management must be incredibly helpful for developers. I'm curious about how the new tracing decorator in TypeScript and Python enhances the functionality for users. Also, with the scaling improvements you've mentioned, could you share how Langfuse handles large spikes in user activity without compromising performance? It’s exciting to see such a robust community forming around your platform. Keep up the great work, and I can’t wait to see where Langfuse goes from here!

Congrats @clemo_sf and team on the launch of LangFuse v2!! I love the major upgrade in the tracing subsystem 🔥