langfuse/langfuse-python

What it solves

It provides a comprehensive toolkit for developers to monitor, evaluate, and manage their LLM applications. It addresses the need for visibility into how LLM calls are performing, the ability to to test prompt and model changes without breaking existing functionality, and the way prompts are managed across different environments.

How it works

The SDK integrates into Python applications to capture traces and spans (using OpenTelemetry standards) to track the flow of LLM interactions. It allows developers to create datasets for offline evaluation and regression testing, implement LLM-as-a-judge scoring, and manage prompts via a dedicated management system. It also provides a full REST API client for programmatic access to the platform.

Who it’s for

Developers building LLM-powered applications who need professional observability, systematic evaluation, and prompt management tools.

Highlights

• Observability and Tracing: OpenTelemetry-based tracing with built-in integrations for OpenAI and LangChain.
• Datasets and Experiments: Support for offline evaluation and regression testing of prompt/model changes, including CI integration via GitHub Actions.
• Evaluation: Tools for custom scores and LLM-as-a-judge evaluations.
• Prompt Management: Centralized management of prompts used in applications.