<font color="#4E9A06">INFO</font>:     Started server process [<font color="#06989A">2265873</font>]
<font color="#4E9A06">INFO</font>:     Waiting for application startup.
<font color="#4E9A06">INFO</font>:     Application startup complete.
```

</div>

Програма командного рядка `fastapi` це **FastAPI CLI**.

    protected static Response deleteMethod(final String path) {
        return given().contentType("application/json").header("Authorization", getTestToken()).delete(path);
    }

    protected static void deleteDocuments(final String queryString) {
        List<String> docIds = new ArrayList<>();
        Response response = given().contentType("application/json")
                .param("scroll", "1m")
                .param("q", queryString)

worker_processes  auto;

error_log  /var/log/nginx/error.log warn;
pid        /var/run/nginx.pid;

events {
    worker_connections  4096;
}

http {
    include       /etc/nginx/mime.types;
    default_type  application/octet-stream;

    log_format  main  '$remote_addr - $remote_user [$time_local] "$request" '
                      '$status $body_bytes_sent "$http_referer" '
                      '"$http_user_agent" "$http_x_forwarded_for"';

Los contenidos que devuelvas desde tu *path operation function* se colocarán dentro de esa `Response`.

Y si ese `Response` tiene un media type JSON (`application/json`), como es el caso con `JSONResponse` y `UJSONResponse`, los datos que devuelvas se convertirán automáticamente (y serán filtrados) con cualquier `response_model` de Pydantic que hayas declarado en el *path operation decorator*.

# Deploy FastAPI on Cloud Providers { #deploy-fastapi-on-cloud-providers }

You can use virtually **any cloud provider** to deploy your FastAPI application.

In most of the cases, the main cloud providers have guides to deploy FastAPI with them.

## Cloud Providers - Sponsors { #cloud-providers-sponsors }

import org.opensearch.monitor.jvm.JvmInfo;
import org.opensearch.monitor.os.OsProbe;
import org.opensearch.monitor.process.ProcessProbe;

import jakarta.annotation.Resource;

/**
 * This class is a command-line application for creating and managing the suggest index.
 * It provides functionality to index words from documents and search logs, as well as
 * to purge old suggest data.
 */
public class SuggestCreator {

    /**

## OpenAPI supplémentaire

Lorsque vous déclarez un *chemin* dans votre application, **FastAPI** génère automatiquement les métadonnées concernant ce *chemin* à inclure dans le schéma OpenAPI.

/// note | Détails techniques

worker_processes  auto;

error_log  /var/log/nginx/error.log warn;
pid        /var/run/nginx.pid;

events {
    worker_connections  4096;
}

http {
    include       /etc/nginx/mime.types;
    default_type  application/octet-stream;

    log_format  main  '$remote_addr - $remote_user [$time_local] "$request" '
                      '$status $body_bytes_sent "$http_referer" '
                      '"$http_user_agent" "$http_x_forwarded_for"';

/**
 * Abstract base class for search-related actions in the Fess search application.
 * Provides common functionality for search operations, including search form handling,
 * label management, user authentication, and search result processing.
 *
 * This class extends FessBaseAction and serves as the foundation for all search-related
 * web actions in the application.
 */
public abstract class FessSearchAction extends FessBaseAction {

<span style="color: green;">INFO</span>:     Started server process [28722]
<span style="color: green;">INFO</span>:     Waiting for application startup.
<span style="color: green;">INFO</span>:     Application startup complete.
```

</div>

/// note | 참고

`uvicorn main:app` 명령은 다음을 의미합니다:

* `main`: 파일 `main.py` (파이썬 "모듈").