package models;

import components.*;
import org.codelibs.fess.suggest.Suggester;
import org.codelibs.fess.suggest.exception.SuggesterException;
import org.codelibs.fess.suggest.index.contents.document.DocumentReader;
import org.codelibs.fess.suggest.index.contents.document.ESSourceReader;
import org.codelibs.fess.suggest.request.suggest.SuggestResponse;

public class SuggestIndex {
    public SuggestResponse suggest(String query) {

import org.apache.maven.api.annotations.Nonnull;
import org.apache.maven.api.model.Model;

/**
 * Provides the super POM that all models implicitly inherit from.
 *
 * @since 4.0.0
 */
@Experimental
public interface SuperPomProvider extends Service {

    /**
     * Gets the super POM for the specified model version.
     *
     * @param version The model version to retrieve the super POM for (e.g. "4.0.0"), must not be {@code null}.

      <plugin>
        <groupId>org.codehaus.modello</groupId>
        <artifactId>modello-maven-plugin</artifactId>
        <configuration>
          <version>1.1.0</version>
          <basedir>${project.basedir}/../../api/maven-api-toolchain</basedir>
          <velocityBasedir>${project.basedir}/../../src/mdo</velocityBasedir>
          <models>
            <model>src/main/mdo/toolchains.mdo</model>
          </models>
        </configuration>

```Python hl_lines="1  9  12"
{!../../docs_src/response_change_status_code/tutorial001.py!}
```

Y luego puedes retornar cualquier objeto que necesites, como normalmente lo harías (un `dict`, un modelo de base de datos, etc).

Y si declaraste un `response_model`, aún se usará para filtrar y convertir el objeto que retornaste.

 */
package org.apache.maven.model.superpom;

import org.apache.maven.model.Model;

/**
 * Provides the super POM that all models implicitly inherit from.
 *
 * @deprecated use {@link org.apache.maven.api.services.ModelBuilder} instead
 */
@Deprecated(since = "4.0.0")
public interface SuperPomProvider {

    /**

        DefaultModelProblem pb2 =
                new DefaultModelProblem("message2", ModelProblem.Severity.ERROR, null, "source", 0, 0, "modelId", null);
        String msg = ModelBuildingException.toMessage("modelId", Arrays.asList(pb1, pb2));
        assertEquals(
                "2 problems were encountered while building the effective model for modelId" + System.lineSeparator()

 * under the License.
 */
package org.apache.maven.model.building;

import java.util.function.Supplier;

import org.apache.maven.building.Source;

/**
 * Caches auxiliary data used during model building like already processed raw/effective models. The data in the cache
 * is meant for exclusive consumption by the model builder and is opaque to the cache implementation. The cache key is

En utilisant cette même astuce, vous pouvez utiliser un modèle Pydantic pour définir le schéma JSON qui est ensuite inclus dans la section de schéma OpenAPI personnalisée pour le *chemin* concerné.

Et vous pouvez le faire même si le type de données dans la requête n'est pas au format JSON.

```Python hl_lines="1  10-13  21-24"
{!../../docs_src/sql_databases/sql_app/models.py!}
```

### ✍ 💛

🔜 ✍ 💛.

👉, 👥 ⚙️ `relationship` 🚚 🇸🇲 🐜.

👉 🔜 ▶️️, 🌅 ⚖️ 🌘, "🎱" 🔢 👈 🔜 🔌 💲 ⚪️➡️ 🎏 🏓 🔗 👉 1️⃣.

```Python hl_lines="2  15  26"
{!../../docs_src/sql_databases/sql_app/models.py!}
```

from typing import Optional

from fastapi.openapi.models import OpenIdConnect as OpenIdConnectModel
from fastapi.security.base import SecurityBase
from starlette.exceptions import HTTPException
from starlette.requests import Request
from starlette.status import HTTP_403_FORBIDDEN
from typing_extensions import Annotated, Doc


class OpenIdConnect(SecurityBase):
    """
    OpenID Connect authentication class. An instance of it would be used as a