Langfuse is the leading open-source LLMOps platform, designed to help teams collaboratively develop, monitor, evaluate, and debug AI applications. With Langfuse, teams can self-host the platform in just a few minutes. It’s battle-tested, reliable, and trusted by thousands of users—from YC startups to major companies like Khan Academy and Twilio—who use it in production every day. Developers can trace any Large Language Model (LLM) or framework using our Python and JS/TS SDKs, open API, or native integrations with platforms like OpenAI, Langchain, Llama-Index, and the Vercel AI SDK. Beyond tracing, Langfuse offers powerful tools like Langfuse Prompt Management, open APIs, and testing and evaluation pipelines to enhance the quality of AI applications. Product managers can analyze, evaluate, and debug AI products with detailed metrics on costs, latencies, and user feedback, all available through the Langfuse Dashboard. They can also engage human annotators with customized workflows to score and improve the application. Langfuse provides a full suite of tools for managing security risks, including security frameworks and evaluation pipelines to ensure robust, secure AI deployments.

Langfuse is a comprehensive platform designed to enhance the management and observability of large language models (LLMs). It offers a suite of tools that allow users to monitor, analyze, and improve the performance of their LLM applications. Key features include a Prompt Playground, where users can experiment with and optimize prompts to achieve better results from their models. This feature supports integration with models from providers like OpenAI and Anthropic, allowing for comparison and customization of model parameters.

Langfuse also provides tracing and scoring capabilities, enabling users to capture detailed traces of LLM interactions and evaluate their outputs using model-based evaluations. This includes the ability to use LLMs as judges to assess aspects like hallucination, helpfulness, and relevance. The platform supports integration with frameworks such as LangChain, facilitating seamless observability and monitoring.

In addition to its cloud offerings, Langfuse is self-hostable, allowing users to deploy it on their own infrastructure for enhanced control over data privacy and costs. The platform's architecture includes multiple components like Postgres, Clickhouse, Redis, and S3/Blob storage, ensuring high performance and reliability. Overall, Langfuse is designed to help developers and organizations optimize their LLM applications through better management, analysis, and evaluation tools.

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Website: langfuse.com

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