feat: enable stemming (#1356)

Added the ability to specify tokenizer_name, when creating a full text
search index using tantivy. This enables the use of language specific
stemming.

Also updated the [guide on full text
search](https://lancedb.github.io/lancedb/fts/) with a short section on
choosing tokenizer.

Fixes #1315

docs/src/fts.md

@@ -54,6 +54,16 @@ This returns the result as a list of dictionaries as follows.
 !!! note
     LanceDB automatically searches on the existing FTS index if the input to the search is of type `str`. If you provide a vector as input, LanceDB will search the ANN index instead.
 
+## Tokenization
+By default the text is tokenized by splitting on punctuation and whitespaces and then removing tokens that are longer than 40 chars. For more language specific tokenization then provide the argument tokenizer_name with the 2 letter language code followed by "_stem". So for english it would be "en_stem".
+
+```python
+table.create_fts_index("text", tokenizer_name="en_stem")
+```
+
+The following [languages](https://docs.rs/tantivy/latest/tantivy/tokenizer/enum.Language.html) are currently supported.
+
+
 ## Index multiple columns
 
 If you have multiple string columns to index, there's no need to combine them manually -- simply pass them all as a list to `create_fts_index`:
@@ -139,6 +149,7 @@ is treated as a phrase query.
 In general, a query that's declared as a phrase query will be wrapped in double quotes during parsing, with nested
 double quotes replaced by single quotes.
 
+
 ## Configurations
 
 By default, LanceDB configures a 1GB heap size limit for creating the index. You can