"type": "mapping",
          "mappings_path": "${fess.dictionary.path}fa/mapping.txt"
        },
        "mapping_ja_filter": {
          "type": "mapping",
          "mappings_path": "${fess.dictionary.path}ja/mapping.txt"
        },
        "mapping_filter": {
          "type": "mapping",
          "mappings_path": "${fess.dictionary.path}mapping.txt"
        },
        "traditional_chinese_convert": {

        "keywords_path": "${fess.dictionary.path}da/protwords.txt"
      },
      "danish_stemmer": {
        "type":       "stemmer",
        "language":   "danish"
      },
      "dutch_stop": {
        "type":       "stop",
        "stopwords":  "_dutch_"
      },
      "dutch_keywords": {
        "type":       "keyword_marker",
        "keywords_path": "${fess.dictionary.path}nl/protwords.txt"
      },

```

## Metadata for tags

You can also add additional metadata for the different tags used to group your path operations with the parameter `openapi_tags`.

It takes a list containing one dictionary for each tag.

Each dictionary can contain:

* `name` (**required**): a `str` with the same tag name you use in the `tags` parameter in your *path operations* and `APIRouter`s.

        String[] values = CSVUtil.parse(rule);
        if (dup.add(values[0]) == false) {
            throw new IllegalArgumentException("Found duplicate term [" + values[0] + "] in user dictionary.");
        }
        return rule;
    }

    public static UserDictionary getUserDictionary(Environment env, Settings settings) {

        {
            "detail": [
                {
                    "type": "model_attributes_type",
                    "loc": ["body"],
                    "msg": "Input should be a valid dictionary or object to extract fields from",
                    "input": "name=Foo&price=50.5",
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {

        {
            "detail": [
                {
                    "type": "model_attributes_type",
                    "loc": ["body"],
                    "msg": "Input should be a valid dictionary or object to extract fields from",
                    "input": "name=Foo&price=50.5",
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {

                        userFSTReaderField.set(tokenizer, userFst.getBytesReader());
                        @SuppressWarnings("unchecked")
                        final EnumMap<Type, Dictionary> dictionaryMap = (EnumMap<Type, Dictionary>) dictionaryMapField.get(tokenizer);
                        dictionaryMap.put(Type.USER, userDictionary);
                    } catch (final Exception e) {

            throw new SuggestSettingsException("Failed to create mappings.");
        }
    }

    protected String loadIndexSettings() throws IOException {
        final String dictionaryPath = System.getProperty("fess.dictionary.path", StringUtil.EMPTY);
        final StringBuilder sb = new StringBuilder();
        try (BufferedReader br = new BufferedReader(new InputStreamReader(

        return tuples;
    }

    protected String loadIndexSettings() throws IOException {
        final String dictionaryPath = System.getProperty("fess.dictionary.path", StringUtil.EMPTY);
        final StringBuilder sb = new StringBuilder();
        try (BufferedReader br = new BufferedReader(

* Declare a `Request` parameter in the *path operation* that will return a template.
* Use the `templates` you created to render and return a `TemplateResponse`, pass the name of the template, the request object, and a "context" dictionary with key-value pairs to be used inside of the Jinja2 template.

```Python hl_lines="4  11  15-18"
{!../../docs_src/templates/tutorial001.py!}
```

/// note