### `Body` com vários `examples`

Alternativamente ao único `example`, você pode passar `examples` usando um `dict` com **vários examples**, cada um com informações extras que serão adicionadas no **OpenAPI** também.

As chaves do `dict` identificam cada exemplo, e cada valor é outro `dict`.

Cada `dict` de exemplo específico em `examples` pode conter:

* `summary`: Pequena descrição do exemplo.

Sie würden diese Editor-Unterstützung nicht erhalten, wenn Sie direkt mit `dict`, statt mit Pydantic-Modellen arbeiten würden.

Aber Sie müssen sich auch nicht weiter um die Modelle kümmern, hereinkommende Dicts werden automatisch in sie konvertiert. Und was Sie zurückgeben, wird automatisch nach JSON konvertiert.

## Bodys mit beliebigen `dict`s

Sie können einen Body auch als `dict` deklarieren, mit Schlüsseln eines Typs und Werten eines anderen Typs.

    <jsp:include page="/WEB-INF/view/common/admin/sidebar.jsp">
        <jsp:param name="menuCategoryType" value="system"/>
        <jsp:param name="menuType" value="dict"/>
    </jsp:include>
    <div class="content-wrapper">
        <div class="content-header">
            <div class="container-fluid">
                <div class="row mb-2">
                    <div class="col-sm-6">

    <jsp:include page="/WEB-INF/view/common/admin/sidebar.jsp">
        <jsp:param name="menuCategoryType" value="system"/>
        <jsp:param name="menuType" value="dict"/>
    </jsp:include>
    <div class="content-wrapper">
        <div class="content-header">
            <div class="container-fluid">
                <div class="row mb-2">
                    <div class="col-sm-6">

        if read_with_orm_mode:
            # Let from_orm extract the data from this model instead of converting
            # it now to a dict.
            # Otherwise, there's no way to extract lazy data that requires attribute
            # access instead of dict iteration, e.g. lazy relationships.
            return res
        return _model_dump(
            res,
            by_alias=True,

from typing import Dict

from fastapi import FastAPI

app = FastAPI()


@app.post("/index-weights/")
async def create_index_weights(weights: Dict[int, float]):

import org.codelibs.fess.Constants;
import org.codelibs.fess.app.pager.KuromojiPager;
import org.codelibs.fess.dict.DictionaryFile.PagingList;
import org.codelibs.fess.dict.DictionaryManager;
import org.codelibs.fess.dict.kuromoji.KuromojiFile;
import org.codelibs.fess.dict.kuromoji.KuromojiItem;
import org.codelibs.fess.mylasta.direction.FessConfig;
import org.dbflute.optional.OptionalEntity;

 * governing permissions and limitations under the License.
 */
package org.codelibs.fess.dict.protwords;

import java.util.Date;

import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
import org.codelibs.fess.dict.DictionaryCreator;
import org.codelibs.fess.dict.DictionaryFile;
import org.codelibs.fess.dict.DictionaryItem;

import jakarta.annotation.PostConstruct;

 * governing permissions and limitations under the License.
 */
package org.codelibs.fess.dict.synonym;

import java.util.Date;

import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
import org.codelibs.fess.dict.DictionaryCreator;
import org.codelibs.fess.dict.DictionaryFile;
import org.codelibs.fess.dict.DictionaryItem;

import jakarta.annotation.PostConstruct;

from typing import Dict

from fastapi import FastAPI

app = FastAPI()


@app.get("/keyword-weights/", response_model=Dict[str, float])
async def read_keyword_weights():