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

# Google Gemini

> Generate documents with Gemini's structured output

# Google Gemini

Gemini supports structured output via `response_schema`. Use `GEMINI_DOCUMENT_SCHEMA` which omits `additionalProperties` (unsupported by Gemini).

```python theme={null}
from surfacedocs import SurfaceDocs, GEMINI_DOCUMENT_SCHEMA, SYSTEM_PROMPT
import google.generativeai as genai

genai.configure(api_key="...")
docs = SurfaceDocs()

model = genai.GenerativeModel(
    model_name="gemini-2.0-flash",
    system_instruction=SYSTEM_PROMPT,
    generation_config=genai.GenerationConfig(
        response_mime_type="application/json",
        response_schema=GEMINI_DOCUMENT_SCHEMA,
    ),
)

response = model.generate_content("Write documentation for user authentication")
result = docs.save(response.text)
print(f"Saved: {result.url}")
```

<Note>
  `GEMINI_DOCUMENT_SCHEMA` is specifically designed for Gemini — it removes `additionalProperties` fields that Gemini doesn't support and uses explicit metadata property definitions.
</Note>

## Why a separate schema?

Gemini's structured output has different constraints than OpenAI:

| Feature                | OpenAI                       | Gemini        |
| ---------------------- | ---------------------------- | ------------- |
| `additionalProperties` | Required for strict mode     | Not supported |
| Nullable types         | `"type": ["string", "null"]` | Not needed    |
| All fields required    | Yes (strict mode)            | No            |

The `GEMINI_DOCUMENT_SCHEMA` handles these differences so you don't have to.