How does Langfuse manage to streamline the process of exploring complex logs and traces, making it efficient and user-friendly? Exciting to see how this tool can elevate app observability and analytics!
This looks absolutely brilliant idea to track and stay informed about the performance of LLM applications. I am in the process of building one and certainly give it a try to measure my LLM app.
We’ve been unsung Langfuse for 2 months now. It’s easy to integrate and makes it simpler for us to monitor & debug LLM requests during development and beyond.
Stellar work @max_deichmann , @marc_klingen , @clemo_sf ! If anything, I dare to say a bit too good for a launch ;). Stoked to test it out on some projects - godspeed!
Have been using Langfuse for analytics for our chatbots and have to say its quite well done! Kudos to the team for such an amazing execution! I am definitely going to be a long term user.
Langfuse has been indispensable for us in leveraging LLMs. Its detailed tracing provides unrivaled clarity, streamlining our debug times and offering insights into both LLM and non-LLM actions. With seamless integrations, from Langchain to their SDKs, and insightful analytics on cost, feedback, and latency, it's the must-have tool for anyone in the LLM space. A bonus: their commitment to open source means flexibility for developers and is in line with the decentralized nature we love in crypto. Kudos to the Langfuse team!
