Workflow History & Continuous Execution

Build conversational workflows that maintain context across multiple executions, creating truly intelligent and natural interactions.

Workflow History enables your Agno workflows to remember and reference previous conversations, transforming isolated executions into continuous, context-aware interactions.

Instead of starting fresh each time, with Workflow History you can:

• Build on previous interactions - Reference the context of past interactions
• Avoid repetitive questions - Avoid requesting previously provided information
• Maintain context continuity - Create a conversational experience
• Learn from patterns - Analyze historical data to make better decisions

Note that this feature is different from add_history_to_context. This does not add the history of a particular agent or team, but the full workflow history to either all or some steps.

How It Works

When workflow history is enabled, previous messages are automatically injected into agent/team inputs as structured context:

<workflow_history_context>
[run-1]
input: Create content about AI in healthcare
response: # AI in Healthcare: Transforming Patient Care...

[run-2] 
input: Make it more family-focused
response: # AI in Family Healthcare: A Parent's Guide...
</workflow_history_context>

Your current input goes here...

Along with this, in using Steps with custom functions, you can access this history in the following ways:

1. As a formatted context string as shown above
2. In a structured format as well for more control

[
    (<workflow input from run 1>)(<workflow output from run 1>),
    (<workflow input from run 2>)(<workflow output from run 2>),
]

A database is required to use Workflow history. Runs across different executions will be persisted there.

Example-

def custom_function(step_input: StepInput) -> StepOutput:
    # Option 1: Structured data for analysis
    history_tuples = step_input.get_workflow_history(num_runs=3)
    for user_input, workflow_output in history_tuples:
        # Process each conversation turn

    # Option 2: Formatted context for agents  
    context_string = step_input.get_workflow_history_context(num_runs=3)

    return StepOutput(content="Analysis complete")

You can use these helper functions to access the history:

• step_input.get_workflow_history(num_runs=3)
• step_input.get_workflow_history_context(num_runs=3)

Refer to StepInput reference for more details.

Control Levels

You can be specific about which Steps to add the history to:

Workflow-Level History

Add workflow history to all steps in the workflow:

workflow = Workflow(
    steps=[research_step, analysis_step, writing_step],
    add_workflow_history_to_steps=True  # All steps get history
)

Step-Level History

Add workflow history to specific steps only:

Step(
    name="Content Creator", 
    agent=content_agent,
    add_workflow_history=True  # Only this step gets history
)

You can also put add_workflow_history=False to disable history for a specific step.

Precedence Logic

Step-level settings always take precedence over workflow-level settings:

workflow = Workflow(
    steps=[
        Step("Research", agent=research_agent),                              # None → inherits workflow setting
        Step("Analysis", agent=analysis_agent, add_workflow_history=False),  # False → overrides workflow  
        Step("Writing", agent=writing_agent, add_workflow_history=True),     # True → overrides workflow
    ],
    add_workflow_history_to_steps=True  # Default for all steps
)

History Length Control

By default, all available history is included (no limit). It is recommended to use a fixed history run limit to avoid bloating the LLM context window.

You can control this at both levels:

# Workflow-level: limit history for all steps
workflow = Workflow(
    add_workflow_history_to_steps=True,
    num_history_runs=5  # Only last 5 runs
)

# Step-level: override for specific steps
Step("Analysis", agent=analysis_agent, 
     add_workflow_history=True,
     num_history_runs=3  # Only last 3 runs for this step
)

Developer Resources

Explore the different examples in Workflow History Examples for more details.