> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Agent with Followup Suggestions

> Generate followup prompts after agent responses.

Set `followups=True` to generate prompt suggestions when a run returns content. Agno makes a second model call using the user input and response.

**1. Create a Python file**

```python followup_suggestions.py theme={null}
from agno.agent import Agent
from agno.models.openai import OpenAIResponses

agent = Agent(
    model=OpenAIResponses(id="gpt-5.4-mini"),
    followups=True,
    num_followups=3,
)

response = agent.run("What is quantum computing?")

print(response.content)
print("\nFollowup suggestions:")
for i, suggestion in enumerate(response.followups or [], 1):
    print(f"  {i}. {suggestion}")
```

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

**2. Install dependencies**

```bash theme={null}
uv pip install -U agno openai
```

**3. Export your OpenAI API key**

```bash Mac/Linux theme={null}
export OPENAI_API_KEY="your_openai_api_key_here"
```

```powershell Windows theme={null}
$Env:OPENAI_API_KEY="your_openai_api_key_here"
```

**4. Run Agent**

```bash theme={null}
python followup_suggestions.py
```

## Options

| Parameter | Type | Default | Description |
| - | - | - | - |
| `followups` | `bool` | `False` | Enable followup suggestion generation |
| `num_followups` | `int` | `3` | Number of suggestions to generate (minimum 1) |
| `followup_model` | `Model \| str` | `None` | Model used for followups. `None` reuses the agent's model. |

## Streaming

Followup suggestions are available via events when streaming. The `FollowupsCompleted` event carries the suggestions after the main response finishes.

```python followup_suggestions_streaming.py theme={null}
import asyncio

from agno.agent import Agent, RunEvent
from agno.models.openai import OpenAIResponses

agent = Agent(
    model=OpenAIResponses(id="gpt-5.4-mini"),
    followups=True,
    num_followups=3,
)


async def main():
    async for event in agent.arun(
        "What is quantum computing?",
        stream=True,
        stream_events=True,
    ):
        if event.event == RunEvent.run_content and event.content:
            print(event.content, end="", flush=True)

        if event.event == RunEvent.followups_completed:
            print("\n\nFollowup suggestions:")
            for i, suggestion in enumerate(event.followups or [], 1):
                print(f"  {i}. {suggestion}")


asyncio.run(main())
```

## Using a separate model

Use `followup_model` to run followup generation with a separate model.

```python theme={null}
from agno.agent import Agent
from agno.models.openai import OpenAIResponses

agent = Agent(
    model=OpenAIResponses(id="gpt-5.4-mini"),
    followups=True,
    num_followups=3,
    followup_model=OpenAIResponses(id="gpt-4o-mini"),
)
```

## Developer Resources

* [Agent reference](https://agno-v2.mintlify.site/reference/agents/agent.md)
* [RunOutput reference](https://agno-v2.mintlify.site/reference/agents/run-response.md)


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