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

# SearchResultContent

# SearchResultContent

Search result content for grounding LLM responses with web search data.

```python theme={null}
from adaline_api.models.search_result_content import SearchResultContent
```

***

## Fields

<ParamField body="modality" type="str" required>
  Must be `"search-result"`.
</ParamField>

<ParamField body="value" type="SearchResultGoogleContentValue" required>
  Google search result value with `type`, `references`, and `responses`.
</ParamField>

***

## Example

```python theme={null}
from adaline_api.models.search_result_content import SearchResultContent
from adaline_api.models.search_result_google_content_value import SearchResultGoogleContentValue
from adaline_api.models.message_content import MessageContent

search_result = SearchResultContent(
    modality="search-result",
    value=SearchResultGoogleContentValue.from_dict({
        "type": "google",
        "references": [
            {"title": "Example", "url": "https://example.com", "snippet": "..."}
        ],
        "responses": [
            {"text": "Search grounding result..."}
        ]
    })
)

content = MessageContent(actual_instance=search_result)
```

**JSON**:

```json theme={null}
{
  "modality": "search-result",
  "value": {
    "type": "google",
    "references": [
      { "title": "Example", "url": "https://example.com", "snippet": "..." }
    ],
    "responses": [
      { "text": "Search grounding result..." }
    ]
  }
}
```

***

## Related

* [MessageContent](/docs/reference/sdk/v2/python/types/MessageContent) — union wrapper for all content types
* [PromptMessage](/docs/reference/sdk/v2/python/types/PromptMessage) — chat message containing content arrays