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Langfuse 2.0 — the open source LLM engineering platform
Langfuse is the open source LLM Engineering Platform.
It provides observability, tracing, evaluations, prompt management, playground and metrics to debug and improve LLM apps.
Langfuse is open. It works with any model, framework and you can export all data.
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@marc_klingen @max_deichmann @clemo_sf opensourcing LLM engineering platform is great thing in the AI space. Keep up the good work. Congratulations
@marc_klingen @max_deichmann @clemo_sf Really amazing product, best in class, Congratulations langfuse team!
Congrats on Langfuse 2.0! From observability to a full LLM engineering platform, impressive growth! The features are powerful, catering to user needs. Like snazzystep shoes, Langfuse empowers users to excel. Best wishes on your Product Hunt launch!https://snazzystep.com/wp-admin/
We were notified automatically about the new launch. It triggered a Slack discussion of our AI infra experts:
'a very nice alternative to langsmith, and it's also cheaper since it isn't per user :+1: It's also open source, so if we don't want to pay for the service we can host it ourselves.'
'We want to remove langchain anyway next week so it kinda fits'
Next steps: we check out if the API works for us.
Congrats to the Product(hunt)-led growth! :)
@marc_mengler Thank you, Marc!
have a look at the API at https://api.reference.langfuse.com/
+ feel free to have your team reach out to me, we're always happy to add endpoints.
@marc_mengler thanks Marc (hi from Marc to Marc) 🙏
Please reach out any time if you have questions or feedback, I'd love to chat!
For more context on Langfuse 2.0, the recording of our launch week town hall might be interesting:
Some more links:
We have noted down why we build Langfuse here (open, no framework/llm lock-in, great API to build custom workflows around it): https://langfuse.com/why
Public roadmap: https://langfuse.com/roadmap
Public roadmap discussions: https://langufse.com/ideas
Thanks again, appreciate your support!
Giveaway: Sign up for Langfuse stickers here: https://langfuse.com/stickers
we'll send these in the coming weeks!
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.
@dan_meier1 thanks, the decorator is for sure the biggest upgrade to the Langfuse developer experience in Python!
We wrote a more technical blog post on it here: https://langfuse.com/blog/2024-0...
@clemo_sf @marc_klingen @max_deichmann congrats on the launch! It's awesome to follow your journey which is truly lightspeedy. 🔥
@clemo_sf @max_deichmann @sebastian_schuller thanks for your excitement and support, really appreciate it ❤️
This is very cool! Will share it with my team at QueryPal(https://www.querypal.com), as we start benchmarking and evaluating, we are currently looking into WandB.
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!
@lukmyslinski thank you so much for your kind words and continued feedback and contributions to Langfuse. We really appreciate it!
Let me know if you have additional feedback, would love to chat.
@clemo_sf @hamza_zia Thanks Hamza! The decorator-based integration has been a big upgrade to tracing in Langfuse. We wrote a short piece on it here: https://langfuse.com/blog/2024-0...
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.
@david_paffenholz1 thanks David! You guys are an inspiration, we’re just trying to ship close to as quickly as you do.
More improvements to prompt management are planned as we had no new releases for prompt management this week.
A great product to productionize your LLM applications. Once you create a prototype, the next step is understanding the cost structure, and tracing the paths - and Langfuse helps you to solve those challenges. The new decorators make it easy to track anything easily from your code.
Good luck with the launch!
@tevfik_oytun_aloglu thanks Tevfik, appreciate your feedback. The decorator has been a big step up recently, glad you like it!
Congrats on the launch, Clemens and team! Been using the product since the start and love the execution speed!! Particularly excited about the new tracing and prompt management features. Excited to explore more!!
@roman_geu Thanks Roman! Appreciate your support since day one, no matter if it is product or general founder/life advice. Thank you 🙏
Really happy with the product. It's very intuitive
- Traces work very well for Agentic Workflows
- Scores is another great feature to help us create datasets for finetuning
- Plus, looking forward to your new eval feature!
@aqib_ansari thanks Aqib, appreciate your continuous product feedback a lot! It really helps us build the best product and continuously learn what your team needs to build the best agents 🙏
Building an LLM solution without langfuse is unreasonable. The product gives visibility on all our traces.
The team is always ready to lend a hand as well.
Keep building!
@pablo_jimenez_de_parga Thank you, Pablo. It's been an immense pleasure working for you for such a long time now!
@pablo_jimenez_de_parga your feedback has been invaluable, thanks team throxy!
@timon_christiansen love that you guys actually built your own golang wrapper
Highly recommend Langfuse! Been partnering with them on integrating it into our platform, lots of users love it!
@henryheng94 thanks Henry! Love what you built with flowise and the feedback by the super users who really cared about the flowise x Langfuse integration and sent tons of feedback. Thanks everyone!
Side note: we need to get that llamaindex js integration going for you :)
Congrats on the launch! Langfuse is really an amazing tool to get llm apps production-ready, glad to see it getting so much traction on here.
@stefan_faistenauer1 thanks Stefan! That’s our core mission, help everyone launch and build faster
Langfuse is production ready application for LLM Observability and LLMops. Thank you for awesome open source application!
@aleksandr_iakubovich thanks Aleksandr! Let me know if you have any feedback or questions
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