> ## 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.

# User Feedback (Structured Questions)

> Pause a trip-planning agent with UserFeedbackTools and collect answers to multiple-choice questions.

```python user_feedback.py theme={null}
"""
User Feedback (Structured Questions)
=====================================

Human-in-the-Loop: Presenting structured questions with predefined options.
Uses UserFeedbackTools to pause the agent and collect user selections.
"""

from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIResponses
from agno.tools.user_feedback import UserFeedbackTools
from agno.utils import pprint

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    tools=[UserFeedbackTools()],
    instructions=[
        "You are a helpful travel assistant.",
        "When the user asks you to plan a trip, use the ask_user tool to clarify their preferences.",
    ],
    markdown=True,
    db=SqliteDb(db_file="tmp/user_feedback.db"),
)

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    run_response = agent.run("Help me plan a vacation")

    while run_response.is_paused:
        for requirement in run_response.active_requirements:
            if requirement.needs_user_feedback:
                feedback_schema = requirement.user_feedback_schema
                if not feedback_schema:
                    continue

                selections = {}
                for question in feedback_schema:
                    print(f"\n{question.header or 'Question'}: {question.question}")
                    if question.options:
                        for i, opt in enumerate(question.options, 1):
                            desc = f" - {opt.description}" if opt.description else ""
                            print(f"  {i}. {opt.label}{desc}")

                    if question.multi_select:
                        raw = input("Select options (comma-separated numbers): ")
                        indices = [
                            int(x.strip()) - 1
                            for x in raw.split(",")
                            if x.strip().isdigit()
                        ]
                        selected = [
                            question.options[i].label
                            for i in indices
                            if question.options and 0 <= i < len(question.options)
                        ]
                    else:
                        raw = input("Select an option (number): ")
                        idx = int(raw.strip()) - 1 if raw.strip().isdigit() else -1
                        selected = (
                            [question.options[idx].label]
                            if question.options and 0 <= idx < len(question.options)
                            else []
                        )

                    selections[question.question] = selected
                    print(f"  -> Selected: {selected}")

                requirement.provide_user_feedback(selections)

        run_response = agent.continue_run(
            run_id=run_response.run_id,
            requirements=run_response.requirements,
        )

        if not run_response.is_paused:
            pprint.pprint_run_response(run_response)
```

## Run the Example

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

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

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

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

Full source: [cookbook/02\_agents/10\_human\_in\_the\_loop/user\_feedback.py](https://github.com/agno-agi/agno/blob/main/cookbook/02_agents/10_human_in_the_loop/user_feedback.py)