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August 27, 2025

Additional Observation Types for More Meaningful Span Context

Nimar Blume

New observation types including Agent, Tool, Chain, Retriever, Evaluator, Embedding, and Guardrail provide semantic meaning to your traces.

We’ve expanded the supported observation types to bring more meaning to your spans. Now, you can easily identify the type of action an observation represents, such as tool calls, embeddings or agents.

For most integrations with agent frameworks the observation types are automatically detected. You can also manually set them via the Langfuse SDK as explained in the docs.

Full List of Available Observation Types:

• event is the basic building block. An event is used to track discrete events in a trace.
• span represents durations of units of work in a trace.
• generation logs generations of AI models incl. prompts, token usage and costs.
• agent decides on the application flow and can for example use tools with the guidance of a LLM.
• tool represents a tool call, for example to a weather API.
• chain is a link between different application steps, like passing context from a retriever to a LLM call.
• retriever represents data retrieval steps, such as a call to a vector store or a database.
• evaluator represents functions that assess relevance/correctness/helpfulness of a LLM’s outputs.
• embedding is a call to a LLM to generate embeddings and can include model, token usage and costs
• guardrail is a component that protects against malicious content or jailbreaks.

Learn more