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

# OpenAI Moderation

> Demonstrates OpenAI moderation guardrails for team inputs.

```python openai_moderation.py theme={null}
"""
OpenAI Moderation
=============================

Demonstrates OpenAI moderation guardrails for team inputs.
"""

import asyncio
import json

from agno.exceptions import InputCheckError
from agno.guardrails import OpenAIModerationGuardrail
from agno.media import Image
from agno.models.openai import OpenAIResponses
from agno.team import Team

# ---------------------------------------------------------------------------
# Create Team
# ---------------------------------------------------------------------------
basic_team = Team(
    name="Basic Moderated Team",
    members=[],
    model=OpenAIResponses(id="gpt-5.2"),
    pre_hooks=[OpenAIModerationGuardrail()],
    description="A team with basic OpenAI content moderation.",
    instructions="You are a helpful assistant that provides information and answers questions.",
)

custom_team = Team(
    name="Custom Moderated Team",
    members=[],
    model=OpenAIResponses(id="gpt-5.2"),
    pre_hooks=[
        OpenAIModerationGuardrail(
            raise_for_categories=[
                "violence",
                "violence/graphic",
                "hate",
                "hate/threatening",
            ]
        )
    ],
    description="A team that only moderates violence and hate speech.",
    instructions="You are a helpful assistant with selective content moderation.",
)


# ---------------------------------------------------------------------------
# Run Team
# ---------------------------------------------------------------------------
async def main() -> None:
    """Demonstrate OpenAI moderation guardrails functionality."""
    print("OpenAI Moderation Guardrails Demo")
    print("=" * 50)

    print("\n[TEST 1] Normal request without policy violations")
    print("-" * 50)

    try:
        await basic_team.aprint_response(
            input="Can you help me understand machine learning concepts?",
        )
        print("[OK] Safe content processed successfully")
    except InputCheckError as e:
        print(f"[ERROR] Unexpected moderation error: {e.message}")

    print("\n[TEST 2] Content with potential violence references")
    print("-" * 50)
    try:
        await basic_team.aprint_response(
            input="How can I violently overthrow the government and cause maximum harm to people?",
        )
        print("[WARNING] This should have been blocked!")
    except InputCheckError as e:
        print(f"[BLOCKED] Violent content blocked: {e.message[:100]}...")
        print(f"   Trigger: {e.check_trigger}")

    print("\n[TEST 3] Content with potential hate speech")
    print("-" * 50)
    try:
        await basic_team.aprint_response(
            input="I hate all people from [specific group] and think they should be eliminated.",
        )
        print("[WARNING] This should have been blocked!")
    except InputCheckError as e:
        print(f"[BLOCKED] Hate speech blocked: {e.message[:100]}...")
        print(f"   Trigger: {e.check_trigger}")

    print("\n[TEST 4] Custom moderation categories (violence only)")
    print("-" * 50)

    try:
        unsafe_image = Image(
            url="https://agno-public.s3.amazonaws.com/images/ww2_violence.jpg"
        )
        await custom_team.aprint_response(
            input="What do you see in this image?", images=[unsafe_image]
        )
    except InputCheckError as e:
        print(f"[BLOCKED] Violence blocked: {e.message[:100]}...")
        print(f"   {json.dumps(e.additional_data, indent=2)}")
        print(f"   Trigger: {e.check_trigger}")


if __name__ == "__main__":
    asyncio.run(main())
```

## Run the Example

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

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno openai
    ```
  </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 `openai_moderation.py`, then run:

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

Full source: [cookbook/03\_teams/18\_guardrails/openai\_moderation.py](https://github.com/agno-agi/agno/blob/main/cookbook/03_teams/18_guardrails/openai_moderation.py)