Spans

Spans Overview

In AgentOps v0.4, the concept of “Events” has been replaced with “Spans” for all operation tracking. Spans represent different types of operations and are organized hierarchically. A span is a unit of work or operation in your agent workflow. Spans are created using decorators and are automatically nested to create a hierarchical trace of your agent’s execution.

Span Types

AgentOps supports several types of spans, each representing a different kind of operation:

Session Spans

Session spans serve as the root for all other spans. They represent a complete execution of your agent workflow.

from agentops.sdk.decorators import session

@session
def my_workflow():
    # Your session code here
    return result

Agent Spans

Agent spans represent operations performed by a specific agent. They are typically children of session spans.

from agentops.sdk.decorators import agent

@agent
class MyAgent:
    def __init__(self, name):
        self.name = name

Operation/Task Spans

Operation spans represent specific tasks or operations performed by an agent. They are typically children of agent spans.

from agentops.sdk.decorators import operation

@operation
def process_data(data):
    # Process the data
    return result

Workflow Spans

Workflow spans represent a sequence of operations that form a workflow. They can contain multiple operations.

from agentops.sdk.decorators import workflow

@workflow
def my_workflow(data):
    # Workflow implementation
    return result

LLM Spans

LLM spans are automatically created when you make calls to supported LLM providers. They represent interactions with language models.

Span Attributes

All spans share a set of common attributes:

Attribute	Description
span_id	A unique identifier for the span
trace_id	The ID of the trace this span belongs to
parent_id	The ID of the parent span
name	The name of the span
kind	The kind of span (session, agent, operation, etc.)
start_time	When the span started
end_time	When the span ended
attributes	Custom attributes for the span

Additionally, spans automatically capture:

Input parameters to the decorated function
Return values from the decorated function
Exceptions that occur during execution

Span Hierarchy

Spans are organized hierarchically to create a trace of your agent’s execution. The typical hierarchy is:

Session (root)
Agent
Operation/Task
Nested Operations

This hierarchy allows you to visualize the flow of your agent’s execution and understand how different operations relate to each other.

Error Handling

When an exception occurs within a decorated function, it’s automatically recorded in the span. This allows you to easily identify and debug errors in your agent workflow.

from agentops.sdk.decorators import operation

@operation
def risky_operation():
    # This exception will be recorded in the span
    raise ValueError("Something went wrong")

Getting Started

Concepts

Integrations

Usage

Other Info

Spans Overview

Span Types

Session Spans

Agent Spans

Operation/Task Spans

Workflow Spans

LLM Spans

Span Attributes

Span Hierarchy

Error Handling

​Spans Overview

​Span Types

​Session Spans

​Agent Spans

​Operation/Task Spans

​Workflow Spans

​LLM Spans

​Span Attributes

​Span Hierarchy

​Error Handling

Spans Overview

Span Types

Session Spans

Agent Spans

Operation/Task Spans

Workflow Spans

LLM Spans

Span Attributes

Span Hierarchy

Error Handling