# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
# Disable Docker

#   container and start fresh, run "docker rm -f tf". Removing the container
#   destroys some temporary bazel data and causes longer builds.
#
#   You will need the NVIDIA Container Toolkit for GPU testing:
#   https://github.com/NVIDIA/nvidia-container-toolkit
#
#   Note: if you interrupt a bazel command on docker (ctrl-c), you
#   will need to run `docker exec tf pkill bazel` to quit bazel.
#

### Full Stack FastAPI PostgreSQL - Özellikler

* Full **Docker** entegrasyonu (Docker based).
* Docker Swarm Mode ile deployment.
* **Docker Compose** entegrasyonu ve lokal geliştirme için optimizasyon.
* Uvicorn ve Gunicorn ile **Production ready** Python web server'ı.

TFCI_ARTIFACT_STAGING_GCS_URI=
TFCI_BAZEL_BAZELRC_ARGS=
TFCI_BAZEL_COMMON_ARGS=
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=
TFCI_BUILD_PIP_PACKAGE_ARGS=
TFCI_DOCKER_ARGS=
TFCI_DOCKER_ENABLE=
TFCI_DOCKER_IMAGE=
TFCI_DOCKER_PULL_ENABLE=
TFCI_DOCKER_REBUILD_ARGS=
TFCI_DOCKER_REBUILD_ENABLE=
TFCI_DOCKER_REBUILD_UPLOAD_ENABLE=
TFCI_GIT_DIR=
TFCI_INDEX_HTML_ENABLE=
TFCI_LIB_SUFFIX=
TFCI_MACOS_BAZEL_TEST_DIR_ENABLE=
TFCI_MACOS_BAZEL_TEST_DIR_PATH=

### Full Stack FastAPI PostgreSQL – Funktionen

* Vollständige **Docker**-Integration (Docker-basiert).
* Docker-Schwarmmodus-Deployment.
* **Docker Compose**-Integration und Optimierung für die lokale Entwicklung.
* **Produktionsbereit** Python-Webserver, verwendet Uvicorn und Gunicorn.

# despite lacking Nvidia CUDA support.
TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow"
TFCI_DOCKER_ENABLE=1
TFCI_DOCKER_IMAGE=gcr.io/tensorflow-sigs/build-arm64:tf-2-16-multi-python
TFCI_DOCKER_PULL_ENABLE=1
TFCI_DOCKER_REBUILD_ARGS="--target=tf ci/official/containers/linux_arm64"
TFCI_INDEX_HTML_ENABLE=1
TFCI_LIB_SUFFIX="-cpu-linux-arm64"
TFCI_OUTPUT_DIR=build_output

TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cpu
TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow_cpu"
TFCI_DOCKER_ENABLE=1
TFCI_DOCKER_IMAGE=tensorflow/build:2.16-python${TFCI_PYTHON_VERSION}
TFCI_DOCKER_PULL_ENABLE=1
TFCI_DOCKER_REBUILD_ARGS="--build-arg PYTHON_VERSION=python$TFCI_PYTHON_VERSION --target=devel tensorflow/tools/tf_sig_build_dockerfiles"
TFCI_INDEX_HTML_ENABLE=1

    - 🦇 Dark mode support.
- 🐋 [Docker Compose](https://www.docker.com) for development and production.
- 🔒 Secure password hashing by default.
- 🔑 JWT token authentication.
- 📫 Email based password recovery.
- ✅ Tests with [Pytest](https://pytest.org).
- 📞 [Traefik](https://traefik.io) as a reverse proxy / load balancer.

* **安全密码**，默认使用密码哈希
* **JWT 令牌**身份验证
* **SQLAlchemy** 模型（独立于 Flask 扩展，可直接用于 Celery Worker）
* 基础的用户模型（可按需修改或删除）
* **Alembic** 迁移
* **CORS**（跨域资源共享）
* **Celery** Worker 可从后端其它部分有选择地导入并使用模型和代码
* REST 后端测试基于 Pytest，并与 Docker 集成，可独立于数据库实现完整的 API 交互测试。因为是在 Docker 中运行，每次都可从头构建新的数据存储（使用 ElasticSearch、MongoDB、CouchDB 等数据库，仅测试 API 运行）
* Python 与 **Jupyter Kernels** 集成，用于远程或 Docker 容器内部开发，使用 Atom Hydrogen 或 Visual Studio Code 的 Jupyter 插件
* **Vue** 前端：

    $ ./bin/fess

For more details, see the [Installation Guide](https://fess.codelibs.org/14.12/install/index.html).

### Docker

We provide Docker images on [ghcr.io](https://github.com/orgs/codelibs/packages). We also provide a Docker Compose (YAML) file in [this repository](https://github.com/codelibs/docker-fess/tree/master/compose). 

### Browser UI

- Search UI: http://localhost:8080/