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Langfuse is an open-source LLM engineering platform designed to streamline the development, monitoring, and testing of LLM-based applications. It addresses the unique challenges posed by LLMs, such as complex control flows, non-deterministic outputs, and mixed user intents, by offering robust tools for tracing, debugging, and evaluating these applications. With Langfuse, teams can collaboratively debug, analyze, and iterate on their LLM applications, making it easier to track all relevant logic, manage prompts, and monitor the performance and quality of their models over time.

Core features of Langfuse include observability through detailed tracing of all LLM calls and relevant application logic, along with integrations for popular tools like OpenAI SDK, Langchain, and others. The platform provides a UI for inspecting and debugging logs, managing prompts, and conducting experiments to test application behavior before deployment. Additionally, Langfuse offers powerful analytics and evaluation tools to monitor LLM performance, track metrics like cost and latency, and gather user feedback, all of which contribute to a deeper understanding of application quality and user behavior.

Langfuse's open-source nature, model and framework agnosticism, and incremental adoptability make it ideal for teams building complex LLM applications. By capturing the full context of LLM executions and providing tools to classify and analyze user inputs, Langfuse helps developers maintain control over their applications, ensuring they can effectively manage and improve the performance and quality of their LLM systems.