Langfuse

Langfuse

Open Source LLM Engineering Platform
31 reviews1 shoutout
2K followers

What is Langfuse?

Langfuse is the open source LLM Engineering Platform. It provides observability, metrics, evals, prompt management and a playground and to debug and improve LLM apps. Langfuse is open. It works with any model, any framework, allows for complex nesting and has open APIs to build downstream use cases. Docs: langfuse.com/docs Github: github.com/langfuse/langfuse

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Review Langfuse?

5/5 based on 31 reviews
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Maker reviews of Langfuse

cognee
Boris Arzentar
used this to buildcogneecognee
(362 points)
Langfuse is our choice when observability and tracing are the key. Our clients love their tool and we do too!
Lingo.dev
Max Prilutskiy
used this to buildLingo.dev
(1,102 points)
Extremely relilable LLM Engineering Platform.
Lamatic.ai
Aman Sharma
used this to buildLamatic 2.0Lamatic.ai
(394 points)
Built in integration for the best LLM observability out there.
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Reviews

Rajtilak Bhattacharjee
50 reviews

Awesome!!! First, congratulations on the launch. Making LLM apps cost-effective is one of the priorities for the service that I am working on. This should help. Just a quick question, can this be used in tandem with Langsmith?

Nikhil Kulkarni
4 reviews

We use Langfuse to monitor our GPT usage - specifically to watch for token usage, monitor hallucinations, and trace through request history when things go wrong. Great product and even greater team! Highly recommend trying Langfuse!

David
4 reviews

So excited to see Langfuse go live — we've been a happy user for 4 weeks now. Most detailed latency and analytics in the market. Highly recommend for anyone using complex chains or with user-facing chat applications, where latency becomes crucial. Congrats, Clemens, Marc, and Max!

Collin Schneider
1 review

This is awesome, congrats on the launch guys! LLMs always felt like such a black box for me, Langfuse seems to address these concerns. This is a huge win for the LLM space in general, I'm super excited to build on it!

Ishwar Jha
37 reviews

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.

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