## on_question()

When a Guava agent is asked a question that it cannot answer from its context alone, it will invoke the `on_question` callback. Your **Expert** then has the chance to answer that question, typically using a RAG system. Our examples use the provided `DocumentQA` class, but you can use any RAG system you prefer.

See our [Q&A example](https://goguava.ai/docs/inbound-rag-example) for a step-by-step walkthrough.

### Example

```python
@agent.on_question
def on_question(call: guava.Call, question: str) -> str:
    # question: natural-language question from the caller
    # return: answer to relay to caller
    ...
```

If you want the agent to answer questions immediately, use `add_info` to pre-emptively add information to the context.

- `on_question`, like all Guava callbacks, is invoked asynchronously and does not block dialog. The Guava voice agent continues to engage the caller until the question answer comes back.
- `on_question` may be invoked multiple times, for example, if a caller asks a question and then refines it. `on_question` may be invoked speculatively before a caller is done talking.
- `on_question` may be invoked simultaneously with [`on_action_request`](https://goguava.ai/docs/on-action-request-execute), as some requests can be both an "action" and a "question". For example, _"Do you have a lost and found?"_ In this case, the agent will synthesize both responses: _"Yes, we have a lost and found. Would you like me to transfer you there?"_

```python
import guava
from guava import Agent
from guava.helpers.rag import DocumentQA
from guava.examples.example_data import PROPERTY_INSURANCE_POLICY

agent = Agent(
    organization="Harper Valley Property Insurance",
    purpose="Answer questions regarding property insurance policy",
)

document_qa = DocumentQA(documents=PROPERTY_INSURANCE_POLICY)

@agent.on_question
def on_question(call: guava.Call, question: str) -> str:
    return document_qa.ask(question)
```