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

# Edge Ngram

> Generates prefix n-grams per word, ideal for search-as-you-type

The edge ngram tokenizer first splits text into words at character-class boundaries, then generates n-grams anchored
to the **beginning** of each word. This makes it ideal for "search-as-you-type" functionality, where users find matches
as they type partial words.

The tokenizer takes two required arguments: the minimum and maximum gram length. For each word, it emits prefix tokens
from `min_gram` to `max_gram` characters long (clamped to the word length). Words shorter than `min_gram` are skipped.

```sql theme={null}
CREATE INDEX search_idx ON mock_items
USING bm25 (id, (description::pdb.edge_ngram(2,5)))
WITH (key_field='id');
```

To get a feel for this tokenizer, run the following command and replace the text with your own:

```sql theme={null}
SELECT 'Quick Fox'::pdb.edge_ngram(2,5)::text[];
```

```ini Expected Response theme={null}
            text
-----------------------------
 {qu,qui,quic,quick,fo,fox}
(1 row)
```

## Token Chars

By default, the edge ngram tokenizer treats letters and digits as token content and everything else (spaces,
punctuation, symbols) as word delimiters. You can customize this with `token_chars`, which accepts a comma-separated
list of character classes: `letter`, `digit`, `whitespace`, `punctuation`, `symbol`. Character classification uses
Unicode general categories, matching Elasticsearch's behavior.

For example, including `punctuation` keeps hyphens as part of words:

```sql theme={null}
SELECT 'Quick-Fox'::pdb.edge_ngram(2,5,'token_chars=letter,digit,punctuation')::text[];
```

```ini Expected Response theme={null}
          text
-------------------------
 {qu,qui,quic,quick}
(1 row)
```