Langfuse
Open Source LLM Engineering Platform
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Langfuse 2.0 - the open source LLM engineering platform

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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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Maker
Giveaway: Sign up for Langfuse stickers here: we'll send these in the coming weeks!
Maker
I want some 🪢🪢🪢
congrats on the launch! It's awesome to follow your journey which is truly lightspeedy. 🔥
Maker
thanks for your excitement and support, really appreciate it ❤️
The prompt management and tracing features are particularly intriguing. What measures have you taken to ensure data security and privacy, especially since this is a platform that interacts with potentially sensitive information?
Maker
data security and privacy is extremely important to us as many traces in Langfuse contain PII or valuable IP of our customers. Short summary: - US / data residency options - Professional penetration test to ensure our interfaces are safe - Following security best practices - GDPR, ISO 27001, and soon SOC 2 Type 2 compliance (pending) Find out more information here and feel free to reach out to me or if you have any questions.
Congrats 👏 on the launch! Excited to try some of these new features!
Maker
thank you! list of all the latest releases: let me know if you have any feedback!
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!
Maker
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 🙏
This team ships faster than ⚡
Maker
thank you, Jean! Likewise with sevn!
Maker
thanks, Jean, means a lot!
🔌 Plugged in
We love to use Langfuse to build our RAG systems and get the visibility into what prompts actually hitting the LLM! Btw, the new decorate is awesome
Maker
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:
Love the new features! Great job on shipping so fast!
Maker
thanks , you are an inspiration! shipping is all we do, follow along here:
Congrats on the launch! I'm curious about how Langfuse handles scaling, especially with the growing volume of events and users. Can you elaborate on the scaling strategies you've implemented to ensure smooth performance as you scale?
Maker
we currently scale out our application, on Google Cloud Run and Vercel. We closely measure capacity and performance and this setup scales really well. We are currently working on v3.0 of Langfuse which will include some infrastructure changes to make Langfuse even more scalable, support larger traces with videos/images, and faster dashboard performance.
best LLM engineering platform I have seen so far. Great job!
Maker
thanks for your kind words, let us know if you have any feedback! love what you built with Fixkey:
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