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

# parsing_auto()

> Automatically select an appropriate parser based on detected file types

Automatically select an appropriate parser based on detected file types. Documents with unrecognizable formats won't
be processed and will generate an error in the `ai.vectorizer_errors` table.

The parser selection examines file extensions and content types:

* **PDF files, images, Office documents** (DOCX, XLSX, etc.): Uses Docling
* **EPUB and MOBI** (e-book formats): Uses PyMuPDF
* **Text formats** (TXT, MD, etc.): No parser used (content read directly)

## Samples

### Use automatic parser selection

```sql theme={"dark"}
SELECT ai.create_vectorizer(
    'documents'::regclass,
    loading => ai.loading_uri('file_path'),
    parsing => ai.parsing_auto(),
    embedding => ai.embedding_openai('text-embedding-3-small', 768)
);
```

## Arguments

This function takes no arguments.

## Returns

A JSON configuration object for use in [`create_vectorizer()`][create_vectorizer].

## Related functions

* [`parsing_none()`][parsing_none]: skip parsing for textual data
* [`parsing_docling()`][parsing_docling]: explicitly use Docling parser
* [`parsing_pymupdf()`][parsing_pymupdf]: explicitly use PyMuPDF parser
* [`loading_uri()`][loading_uri]: load data from file URIs

[create_vectorizer]: /api-reference/pgai/vectorizer/create_vectorizer

[loading_uri]: /api-reference/pgai/vectorizer/loading_uri

[parsing_docling]: /api-reference/pgai/vectorizer/parsing_docling

[parsing_none]: /api-reference/pgai/vectorizer/parsing_none

[parsing_pymupdf]: /api-reference/pgai/vectorizer/parsing_pymupdf