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Launch HN: Langfuse (YC W23) – OSS Tracing and Workflows to Improve LLM Apps

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Re: Launch HN: Langfuse (YC W23) – OSS Tracing and Workflows to Improve LLM Apps

#11

Post by marcklingen »

extr wrote: post #10

Very timely post/update, was just checking out your product. IMO it is one of the best solutions I've looked at. Appreciate your dedication to self hosting, for us it's not really practical to have traces with potentially sensitive customer data sitting around on some external company's server somewhere (no offense).

Thank you for the kind words! Let us know if you have any questions or feedback regarding the self-hosting documentation and experience. We collaborate with many teams that have diverse security needs, including HIPAA, PCI, and on-premises deployments on bare metal without internet access.

Re: Launch HN: Langfuse (YC W23) – OSS Tracing and Workflows to Improve LLM Apps

#13

Post by marcklingen »

mathiasn wrote: post #6
mfdupuis wrote: post #4

This is actually one of the more interesting LLM observability platforms I've seen. Beyond addressing scaling issues, where do you see yourself going next?

What are other potential platforms?

This is a good long-list of projects, although it is not narrowly scoped to tracing/evals/prompt-management: https://github.com/tensorchord/Awesome-LLMOps?tab=readme-ov-...

Re: Launch HN: Langfuse (YC W23) – OSS Tracing and Workflows to Improve LLM Apps

#14

Post by jondwillis »

I promise this isn’t astroturfing ;)

I happened to have been triaging LLM observability, dataset, and eval solutions yesterday at the day job, and congratulations, Langfuse was the second solution that I tried, and simple enough to get set up locally with my existing stack for me to stop looking (ye olde time constraints, and I know good-enough when I see it!)

Thanks for your and your team’s work.

Re: Launch HN: Langfuse (YC W23) – OSS Tracing and Workflows to Improve LLM Apps

#15

Post by clemo_ra »

jondwillis wrote: post #14

I promise this isn’t astroturfing ;) I happened to have been triaging LLM observability, dataset, and eval solutions yesterday at the day job, and congratulations, Langfuse was the second solution that I tried, and simple enough to get set up locally with my existing stack for me to stop looking (ye olde time constraints, and I know good-enough when I see it!) Thanks for your and your team’s work.

thank you, that is genuinely nice to hear and motivating for our team.

we're available if you ever run into any issues (github, email etc.)

Re: Launch HN: Langfuse (YC W23) – OSS Tracing and Workflows to Improve LLM Apps

#18

Post by calebkaiser »

mathiasn wrote: post #6
mfdupuis wrote: post #4

This is actually one of the more interesting LLM observability platforms I've seen. Beyond addressing scaling issues, where do you see yourself going next?

What are other potential platforms?

I'm a maintainer of Opik, an open source LLM evaluation and observability platform. We only launched a few months ago, but we're growing rapidly: https://github.com/comet-ml/opik

Re: Launch HN: Langfuse (YC W23) – OSS Tracing and Workflows to Improve LLM Apps

#19

Post by kappamax »

Congrats Marc! We've been using Langfuse for about 6-months for our LLMOps tooling. While its SDKs are limited to python and typescript, their openapi specification is pretty easy to implement in any language.

The team behind it is amazing, and their product being OSS is one of the reasons we chose it. But it just keeps getting better.

We're incidentally only using part of the product because we've implemented most of these new features, prompt caching, execution etc in our app. But with the API you can decide what parts are core to your business logic and outsource the parts you don't want to deal with to Langfuse.

I appreciate that its not an opionated product.

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