> ## 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.

# Any LLM

> Use SYSTEM_PROMPT with any model that supports text output

# Any LLM

For models without native structured output support, use `SYSTEM_PROMPT` to instruct the model to return JSON in the correct format.

```python theme={null}
from surfacedocs import SurfaceDocs, SYSTEM_PROMPT

docs = SurfaceDocs()

# Use SYSTEM_PROMPT with any LLM that accepts a system message
messages = [
    {"role": "system", "content": SYSTEM_PROMPT},
    {"role": "user", "content": "Write documentation for user authentication"},
]

# Call your LLM however you normally would
response = your_llm_client.chat(messages)

# The LLM will return JSON matching the document schema
result = docs.save(response.text)
print(f"Saved: {result.url}")
```

## What SYSTEM\_PROMPT contains

The prompt instructs the LLM to:

1. Output a JSON object with `title` and `blocks`
2. Use the correct block types (`heading`, `paragraph`, `code`, `list`, `quote`, `table`, `image`, `divider`)
3. Include proper metadata (e.g., `level` for headings, `language` for code blocks)
4. Use markdown formatting within text content

## Manual documents

You can also skip the LLM entirely and build documents programmatically:

```python theme={null}
from surfacedocs import SurfaceDocs

docs = SurfaceDocs()

result = docs.save_raw(
    title="Meeting Notes",
    blocks=[
        {"type": "heading", "content": "Action Items", "metadata": {"level": 1}},
        {"type": "list", "content": "- Review PR #123\n- Update docs", "metadata": {"listType": "bullet"}},
        {"type": "divider", "content": ""},
        {"type": "paragraph", "content": "Next meeting: Monday 10am"},
    ],
    metadata={"source": "meeting-bot"},
)

print(f"Saved: {result.url}")
```