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

Overview - Langfuse

submited by

Style Pass

2024-04-17 13:00:39

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

In implementing popular LLM use cases – such as retrieval augmented generation, agents using internal tools & APIs, or background extraction/classification jobs – developers face a unique set of challenges that is different from traditional software engineering:

Tracing & Control Flow: Many valuable LLM apps rely on complex, repeated, chained or agentic calls to a foundation model. This makes debugging these applications hard as it is difficult to pinpoint the root cause of an issue in an extended control flow.

With Langfuse, it is simple to capture the full context of an LLM application. Our client SDKs and integrations are model and framework agnostic and able to capture the full context of an execution. Users commonly track LLM inference, embedding retrieval, API usage and any other interaction with internal systems that helps pinpoint problems. Users of frameworks such as Langchain benefit from automated instrumentation, otherwise the SDKs offer an ergonomic way to define the steps to be tracked by Langfuse.

Output quality: In traditional software engineering, developers are used to testing for the absence of exceptions and compliance with test cases. LLM-based applications are non-deterministic and there rarely is a hard-and-fast standard to assess quality. Understanding the quality of an application, especially at scale, and what ‘good’ evaluation looks like is a main challenge. This problem is accelerated by changes to hosted models that are outside of the user’s control.