> ## Documentation Index
> Fetch the complete documentation index at: https://docs.agno.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Custom Function Step Confirmation

> Test script demonstrating Step-level Human-In-The-Loop (HITL) functionality.

```python custom_function_step_confirmation.py theme={null}
"""
Test script demonstrating Step-level Human-In-The-Loop (HITL) functionality.

This example shows a blog post workflow where:
1. Research agent gathers information (no confirmation)
2. Custom function processes the research (HITL via @pause decorator)
3. Writer agent creates the final post (no confirmation)

Two approaches for HITL:
1. Flag-based: Using requires_confirmation=True on Step
2. Decorator-based: Using @pause decorator on custom functions
"""

from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.openai import OpenAIResponses
from agno.workflow.decorators import pause
from agno.workflow.step import Step
from agno.workflow.types import StepInput, StepOutput
from agno.workflow.workflow import Workflow

db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"


# ============================================================
# Step 1: Research Agent (no confirmation needed)
# ============================================================
research_agent = Agent(
    name="Researcher",
    model=OpenAIResponses(id="gpt-5.4"),
    instructions=[
        "You are a research assistant.",
        "Given a topic, provide 3 key points about it in a concise bullet list.",
        "Keep each point to one sentence.",
    ],
)


# ============================================================
# Step 2: Process research (requires confirmation via @pause decorator)
# ============================================================
@pause(
    name="Process Research",
    requires_confirmation=True,
    confirmation_message="Research complete. Ready to generate blog post. Proceed?",
)
def process_research(step_input: StepInput) -> StepOutput:
    """Process the research data before writing."""
    research = step_input.previous_step_content or "No research available"
    return StepOutput(
        content=f"PROCESSED RESEARCH:\n{research}\n\nReady for blog post generation."
    )


# ============================================================
# Step 3: Writer Agent (no confirmation needed)
# ============================================================
writer_agent = Agent(
    name="Writer",
    model=OpenAIResponses(id="gpt-5.4"),
    instructions=[
        "You are a blog writer.",
        "Given processed research, write a short 2-paragraph blog post.",
        "Keep it concise and engaging.",
    ],
)


# Define steps
research_step = Step(name="research", agent=research_agent)
process_step = Step(
    name="process_research", executor=process_research
)  # @pause auto-detected
write_step = Step(name="write_post", agent=writer_agent)

# Create workflow
workflow = Workflow(
    name="blog_post_workflow",
    db=PostgresDb(db_url=db_url),
    steps=[research_step, process_step, write_step],
)

if __name__ == "__main__":
    print("Starting blog post workflow...")
    print("=" * 50)

    run_output = workflow.run("Benefits of morning exercise")

    # Handle HITL pause
    while run_output.is_paused:
        for requirement in run_output.steps_requiring_confirmation:
            print(f"\n[HITL] Step '{requirement.step_name}' requires confirmation")
            print(f"[HITL] {requirement.confirmation_message}")

            user_input = input("\nContinue? (yes/no): ").strip().lower()

            if user_input in ("yes", "y"):
                requirement.confirm()
                print("[HITL] Confirmed - continuing workflow...")
            else:
                requirement.reject()
                print("[HITL] Rejected - cancelling workflow...")

        run_output = workflow.continue_run(run_output)

    print("\n" + "=" * 50)
    print(f"Status: {run_output.status}")
    print(f"Output:\n{run_output.content}")
```

## Run the Example

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno fastapi openai psycopg-binary sqlalchemy
    ```
  </Step>

  <Step title="Export your OpenAI API key">
    <CodeGroup>
      ```bash Mac/Linux theme={null}
      export OPENAI_API_KEY="your_openai_api_key_here"
      ```

      ```bash Windows theme={null}
      $Env:OPENAI_API_KEY="your_openai_api_key_here"
      ```
    </CodeGroup>
  </Step>

  <Snippet file="run-pgvector-step.mdx" />

  <Step title="Run the example">
    Save the code above as `custom_function_step_confirmation.py`, then run:

    ```bash theme={null}
    python custom_function_step_confirmation.py
    ```
  </Step>
</Steps>

Full source: [cookbook/04\_workflows/08\_human\_in\_the\_loop/confirmation/02\_custom\_function\_step\_confirmation.py](https://github.com/agno-agi/agno/blob/main/cookbook/04_workflows/08_human_in_the_loop/confirmation/02_custom_function_step_confirmation.py)