final String vaultToken = System.getenv('VAULT_TOKEN') ?: new Vault(
  new VaultConfig()
    .address(System.env.VAULT_ADDR)
    .engineVersion(1)
    .build()
)
  .withRetries(5, 1000)
  .auth()
  .loginByAppRole("approle", System.env.VAULT_ROLE_ID, System.env.VAULT_SECRET_ID)
  .getAuthClientToken()

final Vault vault = new Vault(
  new VaultConfig()
    .address(System.env.VAULT_ADDR)
    .engineVersion(1)
    .token(vaultToken)

name: Label Approved

on:
  schedule:
    - cron: "0 12 * * *"
  workflow_dispatch:

permissions:
  pull-requests: write

env:
  UV_SYSTEM_PYTHON: 1

jobs:
  label-approved:
    if: github.repository_owner == 'fastapi'
    runs-on: ubuntu-latest
    steps:
    - name: Dump GitHub context
      env:
        GITHUB_CONTEXT: ${{ toJson(github) }}
      run: echo "$GITHUB_CONTEXT"
    - uses: actions/checkout@v6

-   If all looks good, the reviewer will approve the PR.
-   If a change is needed, the contributor is requested to make the suggested
    change.
-   You make the change and submit it for the review again.
-   This cycle repeats itself until the PR gets approved.
-   Note: As a friendly reminder, we may reach out to you if the PR is awaiting
    your response for more than 2 weeks.

**4. Approved**

	<Loggers>
		<Logger name="org.codelibs" additivity="false" level="${log.level}">
			<AppenderRef ref="AppFile" />
		</Logger>
		<Logger name="org.dbflute" additivity="false" level="${log.level}">
			<AppenderRef ref="AppFile" />
		</Logger>
		<Logger name="org.lastaflute" additivity="false" level="${log.level}">
			<AppenderRef ref="AppFile" />
		</Logger>
		<Logger name="fess.log.crawler.stats" additivity="false" level="info">

Once a native speaker comes, reviews the PR, and approves it, the GitHub Action will come and remove the `awaiting-review` label, and add the `approved-1` label.

This way, we can notice when there are new translations ready, because they have the `approved-1` label.

## Merge Translation PRs

			<AppenderRef ref="AppFile" />
		</Logger>
		<Logger name="org.dbflute" additivity="false" level="${log.level}">
			<AppenderRef ref="AppFile" />
		</Logger>
		<Logger name="org.lastaflute" additivity="false" level="${log.level}">
			<AppenderRef ref="AppFile" />
		</Logger>
		<Logger name="org.opensearch.bootstrap" additivity="false" level="error">
			<AppenderRef ref="AppFile" />
		</Logger>

		</RollingFile>
	</Appenders>

	<Loggers>
		<Logger name="org.codelibs.fess" additivity="false" level="${log.level}">
			<AppenderRef ref="AppFile" />
		</Logger>
		<Root level="${root.log.level}">
			<AppenderRef ref="AppFile" />
		</Root>
	</Loggers>

		</RollingFile>
	</Appenders>

	<Loggers>
		<Logger name="org.codelibs.fess" additivity="false" level="${log.level}">
			<AppenderRef ref="AppFile" />
		</Logger>
		<Root level="${root.log.level}">
			<AppenderRef ref="AppFile" />
		</Root>
	</Loggers>

        assertNotNull(response);
    }

    @Test
    public void test_addRole() throws Exception {
        indexItems();

        SuggestResponse response = suggester.suggest().setQuery("test").addRole(SuggestConstants.DEFAULT_ROLE).execute().getResponse();

        assertNotNull(response);
        assertEquals(1, response.getNum());
    }

    @Test
    public void test_addField() throws Exception {

    * Cependant il nous apporte les outils pour construire une application web simple, avec un routage basé sur des chemins, etc.
    * Si on compare Starlette, il faut le comparer à d'autres frameworks web (ou micorframework) comme Sanic, Flask, Django, etc.
* **FastAPI** :
    * Comme Starlette, FastAPI utilise Uvicorn et ne peut donc pas être plus rapide que ce dernier.