langfuse VS AutoChain

Langfuse is an open-source LLM engineering platform that helps teams collaboratively debug, analyze, and iterate on their LLM applications.

Congrats on the Show! How’s this different from https://github.com/langfuse/langfuse? The exports seems really interesting

Thus, we started working on Langfuse.com (GitHub) to establish an open source LLM engineering platform with tightly integrated features for tracing, prompt management, and evaluation. In the beginning we just solved our own and our friends’ problems. Today we are at over 1000 projects which rely on Langfuse, and 2.3k stars on GitHub. You can either self-host Langfuse or use the cloud instance maintained by us.

- We want to build a tool that is recommended here on HN: you can build a tool you would want to use yourself.

Please see more details here: https://langfuse.com/careers or reach out directly to me: [email protected]

[1] https://github.com/langfuse/langfuse

[2] https://create.t3.gg/

We struggled with this ourselves while building LLM-based products and then open-sourced our observability/monitoring tool [1]. Many use it to track RAG and agents in production, run custom evals on the production traces (focused on hallucination), and track how metrics are different across releases or customers. Feel free to dm if there is something specific you are looking to solve, happy to help.

[1] https://github.com/langfuse/langfuse

Visit us on Discord and Github to engage with our project.

Maybe try https://github.com/langfuse/langfuse

It was recently shared on HN

Here's the note I have on that: “For chatbot interfaces, emerging approach is to have another agent simulating the user (as opposed to a more classic approach based on token prediction probs on chat transcripts, what I think you're referencing). Then still use a model for grading. Only place I've seen this so far: https://github.com/Forethought-Technologies/AutoChain/blob/m... ” - AI Startup Founder