安装和运行文本分析容器Install and run Text Analytics containers


  • 用于情绪分析和语言检测的容器现已正式发布。The container for Sentiment Analysis and language detection are now Generally Available. 关键短语提取容器以非封闭公共预览版的形式提供。The key phrase extraction container is available as an ungated public preview.
  • 实体链接和 NER 当前不可用作容器。Entity linking and NER are not currently available as a container.
  • 容器映像位置最近可能已更改。The container image locations may have recently changed. 阅读本文以查看此容器的更新位置。Read this article to see the updated location for this container.

容器使你能够在自己的环境中运行文本分析 API,最适合特定安全性和数据管理要求。Containers enable you to run the Text Analytic APIs in your own environment and are great for your specific security and data governance requirements. 文本分析容器提供对原始文本的高级自然语言处理,并且包含三项主要功能:情绪分析、关键短语提取和语言检测。The Text Analytics containers provide advanced natural language processing over raw text, and include three main functions: sentiment analysis, key phrase extraction, and language detection.

如果没有 Azure 订阅,可在开始前创建一个试用帐户If you don't have an Azure subscription, create a Trial before you begin.


试用版限制为每月 5000 个事务,并且仅“免费”和“标准” 定价层对于容器有效。The Trial is limited to 5,000 transactions per month and only the Free and Standard pricing tiers are valid for containers. 有关事务请求费率的更多信息,请参阅数据限制For more information on transaction request rates, see Data Limits.


若要运行任何文本分析容器,必须具有主计算机和容器环境。To run any of the Text Analytics containers, you must have the host computer and container environments.


使用文本分析容器之前,必须满足以下先决条件:You must meet the following prerequisites before using Text Analytics containers:

必须Required 目的Purpose
Docker 引擎Docker Engine 需要在主计算机上安装 Docker 引擎。You need the Docker Engine installed on a host computer. Docker 提供用于在 macOSWindowsLinux 上配置 Docker 环境的包。Docker provides packages that configure the Docker environment on macOS, Windows, and Linux. 有关 Docker 和容器的基础知识,请参阅 Docker 概述For a primer on Docker and container basics, see the Docker overview.

必须将 Docker 配置为允许容器连接 Azure 并向其发送账单数据。Docker must be configured to allow the containers to connect with and send billing data to Azure.

在 Windows 上,还必须将 Docker 配置为支持 Linux 容器。On Windows, Docker must also be configured to support Linux containers.

熟悉 DockerFamiliarity with Docker 应对 Docker 概念有基本的了解,例如注册表、存储库、容器和容器映像,以及基本的 docker 命令的知识。You should have a basic understanding of Docker concepts, like registries, repositories, containers, and container images, as well as knowledge of basic docker commands.
文本分析资源Text Analytics resource 若要使用容器,必须具有:In order to use the container, you must have:

使用免费 (F0) 或标准 (S) 定价层的 Azure 文本分析资源An Azure Text Analytics resource with the free (F0) or standard (S) pricing tier. 你将需要通过导航到 Azure 门户中资源的“密钥和终结点”页来获取关联的 API 密钥和终结点 URI。You will need to get the associated API key and endpoint URI by navigating to your resource's Key and endpoint page in the Azure portal.

{API_KEY}:两个可用资源密钥之一。{API_KEY}: One of the two available resource keys.

{ENDPOINT_URI}:资源的终结点。{ENDPOINT_URI}: The endpoint for your resource.

收集必需参数Gathering required parameters

对于所有认知服务的容器来说,有三种主要参数是必需的。There are three primary parameters for all Cognitive Services' containers that are required. 最终用户许可协议 (EULA) 的值必须为 acceptThe end-user license agreement (EULA) must be present with a value of accept. 此外还需要终结点 URL 和 API 密钥。Additionally, both an Endpoint URL and API Key are needed.


在相应的认知服务资源的 Azure 门户“概览” 页上提供终结点 URI 值。The Endpoint URI value is available on the Azure portal Overview page of the corresponding Cognitive Service resource. 导航到“概览” 页,将鼠标悬停在“终结点”上就会显示一个 Copy to clipboard 图标。Navigate to the Overview page, hover over the Endpoint, and a Copy to clipboard icon will appear. 复制后在需要时使用。Copy and use where needed.

收集终结点 URI 供以后使用

密钥 {API_KEY}Keys {API_KEY}

此密钥用于启动容器,可以从相应认知服务资源的 Azure 门户的“密钥”页获取。This key is used to start the container, and is available on the Azure portal's Keys page of the corresponding Cognitive Service resource. 导航到“密钥”页并单击 Copy to clipboard 图标。 Navigate to the Keys page, and click on the Copy to clipboard icon.



这些订阅密钥用于访问认知服务 API。These subscription keys are used to access your Cognitive Service API. 不要共享你的密钥。Do not share your keys. 以安全方式存储密钥(例如,使用 Azure Key Vault 来存储)。Store them securely, for example, using Azure Key Vault. 此外,我们建议定期重新生成这些密钥。We also recommend regenerating these keys regularly. 发出 API 调用只需一个密钥。Only one key is necessary to make an API call. 重新生成第一个密钥时,可以使用第二个密钥来持续访问服务。When regenerating the first key, you can use the second key for continued access to the service.

主计算机The host computer

主机是运行 Docker 容器且基于 x64 的计算机。The host is a x64-based computer that runs the Docker container. 它可以是本地计算机或 Azure 中的 Docker 托管服务,例如:It can be a computer on your premises or a Docker hosting service in Azure, such as:

容器要求和建议Container requirements and recommendations

下表显示了文本分析容器的最小和建议的资源规范。The following table describes the minimum and recommended specifications for the Text Analytics containers. 至少需要 2 千兆字节 (GB) 的内存,并且每个 CPU 核心必须至少为 2.6 千兆赫 (GHz) 或更快。At least 2 gigabytes (GB) of memory are required, and each CPU core must be at least 2.6 gigahertz (GHz) or faster. 还列出了可允许的每节事务数 (TPS)。The allowable Transactions Per Section (TPS) are also listed.

最小主机规格Minimum host specs 推荐主机规格Recommended host specs 最小 TPSMinimum TPS 最大 TPSMaximum TPS
语言检测、关键短语提取Language detection, key phrase extraction 1 核,2GB 内存1 core, 2GB memory 1 核,4GB 内存1 core, 4GB memory 1515 3030
情绪分析Sentiment Analysis 1 核,2GB 内存1 core, 2GB memory 4 核,8GB 内存4 cores, 8GB memory 1515 3030

CPU 核心和内存对应于 --cpus--memory 设置,用作 docker run 命令的一部分。CPU core and memory correspond to the --cpus and --memory settings, which are used as part of the docker run command.

使用 docker pull 获取容器映像Get the container image with docker pull


可以使用 docker images 命令列出下载的容器映像。You can use the docker images command to list your downloaded container images. 例如,以下命令以表格列出每个下载的容器映像的 ID、存储库和标记:For example, the following command lists the ID, repository, and tag of each downloaded container image, formatted as a table:

docker images --format "table {{.ID}}\t{{.Repository}}\t{{.Tag}}"

IMAGE ID            REPOSITORY              TAG
<image-id>       <repository-path/name>     <tag-name>

Microsoft 容器注册表中提供了文本分析的容器映像。Container images for Text Analytics are available on the Microsoft Container Registry.

适用于情绪分析 v3 容器的 Docker pullDocker pull for the Sentiment Analysis v3 container

情绪分析容器 v3 容器以多种语言提供。The sentiment analysis container v3 container is available in several languages. 若要下载英文版容器,请使用以下命令。To download the container for the English container, use the command below.

docker pull mcr.microsoft.com/azure-cognitive-services/textanalytics/sentiment:3.0-en

若要下载其他语言版的容器,请将 en 替换为以下语言代码之一。To download the container for another language, replace en with one of the language codes below.

文本分析容器Text Analytics Container 语言代码Language code
简体中文Chinese-Simplified zh-hans
繁体中文Chinese-Traditional zh-hant
荷兰语Dutch nl
英语English en
法语French fr
德语German de
HindiHindi hi
意大利语Italian it
日语Japanese ja
韩语Korean ko
挪威语(博克马尔语)Norwegian (Bokm�l) no
葡萄牙语(巴西)Portuguese (Brazil) pt-BR
葡萄牙语(葡萄牙)Portuguese (Portugal) pt-PT
西班牙语Spanish es
土耳其语Turkish tr

有关文本分析容器可用标记的完整说明,请查阅 Docker 中心For a full description of available tags for the Text Analytics containers, see Docker Hub.

如何使用容器How to use the container

一旦容器位于主计算机上,请通过以下过程使用容器。Once the container is on the host computer, use the following process to work with the container.

  1. 使用所需的计费设置运行容器Run the container, with the required billing settings.
  2. 查询容器的预测终结点Query the container's prediction endpoint.

通过 docker run 运行容器Run the container with docker run

使用 docker run 命令来运行容器。Use the docker run command to run the containers. 容器将继续运行,直到停止它。The container will continue to run until you stop it.


  • 以下各节中的 docker 命令使用反斜杠 \ 作为行继续符。The docker commands in the following sections use the back slash, \, as a line continuation character. 根据主机操作系统的要求替换或删除字符。Replace or remove this based on your host operating system's requirements.
  • 必须指定 EulaBillingApiKey 选项运行容器;否则,该容器不会启动。The Eula, Billing, and ApiKey options must be specified to run the container; otherwise, the container won't start. 有关详细信息,请参阅计费For more information, see Billing.
  • 情绪分析和语言检测容器已正式发布。The sentiment analysis and language detection containers are generally available. 关键短语提取容器使用该 API 的 v2 版本,并且处于预览阶段。The key phrase extraction container uses v2 of the API, and is in preview.

若要运行情绪分析 v3 容器,请执行以下 docker run 命令。To run the Sentiment Analysis v3 container, execute the following docker run command. 将下面的占位符替换为你自己的值:Replace the placeholders below with your own values:

占位符Placeholder ValueValue 格式或示例Format or example
{API_KEY}{API_KEY} 文本分析资源的密钥。The key for your Text Analytics resource. 可以在 Azure 门户中资源的“密钥和终结点”页上找到此项。You can find it on your resource's Key and endpoint page, on the Azure portal. xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
{ENDPOINT_URI}{ENDPOINT_URI} 用于访问文本分析 API 的终结点。The endpoint for accessing the Text Analytics API. 可以在 Azure 门户中资源的“密钥和终结点”页上找到此项。You can find it on your resource's Key and endpoint page, on the Azure portal. https://<your-custom-subdomain>.cognitiveservices.azure.cn
docker run --rm -it -p 5000:5000 --memory 8g --cpus 1 \
mcr.microsoft.com/azure-cognitive-services/textanalytics/sentiment \
Eula=accept \
Billing={ENDPOINT_URI} \

此命令:This command:

  • 从容器映像运行情绪分析容器Runs a Sentiment Analysis container from the container image
  • 分配一个 CPU 核心和 8 GB 内存Allocates one CPU core and 8 gigabytes (GB) of memory
  • 公开 TCP 端口 5000,并为容器分配伪 TTYExposes TCP port 5000 and allocates a pseudo-TTY for the container
  • 退出后自动删除容器。Automatically removes the container after it exits. 容器映像在主计算机上仍然可用。The container image is still available on the host computer.

在同一主机上运行多个容器Run multiple containers on the same host

若要使用公开端口运行多个容器,请确保在运行每个容器时使用不同的公开端口。If you intend to run multiple containers with exposed ports, make sure to run each container with a different exposed port. 例如,在端口 5000 上运行第一个容器,在端口 5001 上运行第二个容器。For example, run the first container on port 5000 and the second container on port 5001.

可以让此容器和其他 Azure 认知服务容器一起运行在该主机上。You can have this container and a different Azure Cognitive Services container running on the HOST together. 此外,还可以让同一认知服务容器的多个容器一起运行。You also can have multiple containers of the same Cognitive Services container running.

查询容器的预测终结点Query the container's prediction endpoint

容器提供了基于 REST 的查询预测终结点 API。The container provides REST-based query prediction endpoint APIs.

为容器 API 使用主机 http://localhost:5000Use the host, http://localhost:5000, for container APIs.

验证容器是否正在运行Validate that a container is running

有几种方法可用于验证容器是否正在运行。There are several ways to validate that the container is running. 找到相关容器的外部 IP 地址和公开端口,并打开你常用的 Web 浏览器。Locate the External IP address and exposed port of the container in question, and open your favorite web browser. 使用以下各种请求 URL 验证容器是否正在运行。Use the various request URLs below to validate the container is running. 下面列出的示例请求 URL 是 http://localhost:5000,但是你的特定容器可能会有所不同。The example request URLs listed below are http://localhost:5000, but your specific container may vary. 请记住,你要依赖于容器的外部 IP 地址和公开端口。Keep in mind that you're to rely on your container's External IP address and exposed port.

请求 URLRequest URL 目的Purpose
http://localhost:5000/ 容器提供主页。The container provides a home page.
http://localhost:5000/status 使用 HTTP GET 进行请求,以便在不会导致终结点查询的情况下验证容器是否正在运行。Requested with an HTTP GET, to validate that the container is running without causing an endpoint query. 此请求可用于 Kubernetes 运行情况和就绪情况探测This request can be used for Kubernetes liveness and readiness probes.
http://localhost:5000/swagger 容器针对终结点及试用功能提供了一整套文档。The container provides a full set of documentation for the endpoints and a Try it out feature. 使用此功能可以将设置输入到基于 Web 的 HTML 表单并进行查询,而无需编写任何代码。With this feature, you can enter your settings into a web-based HTML form and make the query without having to write any code. 查询返回后,将提供示例 CURL 命令,用于演示所需的 HTTP 标头和正文格式。After the query returns, an example CURL command is provided to demonstrate the HTTP headers and body format that's required.


停止容器Stop the container

若要关闭容器,请在运行容器的命令行环境中选择 Ctrl+CTo shut down the container, in the command-line environment where the container is running, select Ctrl+C.


如果运行启用了输出装入点和日志记录的容器,该容器会生成有助于排查启动或运行容器时发生的问题的日志文件。If you run the container with an output mount and logging enabled, the container generates log files that are helpful to troubleshoot issues that happen while starting or running the container.


如需更多的故障排除信息和指南,请参阅认知服务容器常见问题解答 (FAQ)For more troubleshooting information and guidance, see Cognitive Services containers frequently asked questions (FAQ).


文本分析容器使用 Azure 帐户中的 文本分析 资源向 Azure 发送账单信息。The Text Analytics containers send billing information to Azure, using a Text Analytics resource on your Azure account.

对该容器的查询在用于 <ApiKey> 的 Azure 资源的定价层计费。Queries to the container are billed at the pricing tier of the Azure resource that's used for the <ApiKey>.

如果未连接到计费终结点进行计量,则 Azure 认知服务容器不会被许可运行。Azure Cognitive Services containers aren't licensed to run without being connected to the billing endpoint for metering. 必须始终让容器可以向计费终结点传送计费信息。You must enable the containers to communicate billing information with the billing endpoint at all times. 认知服务容器不会将客户数据(例如,正在分析的图像或文本)发送给 Microsoft。Cognitive Services containers don't send customer data, such as the image or text that's being analyzed, to Microsoft.

连接到 AzureConnect to Azure

容器需要计费参数值才能运行。The container needs the billing argument values to run. 这些值使容器可以连接到计费终结点。These values allow the container to connect to the billing endpoint. 容器约每 10 到 15 分钟报告一次使用情况。The container reports usage about every 10 to 15 minutes. 如果容器未在允许的时间范围内连接到 Azure,容器将继续运行,但不会为查询提供服务,直到计费终结点恢复。If the container doesn't connect to Azure within the allowed time window, the container continues to run but doesn't serve queries until the billing endpoint is restored. 尝试连接按 10 到 15 分钟的相同时间间隔进行 10 次。The connection is attempted 10 times at the same time interval of 10 to 15 minutes. 如果无法在 10 次尝试内连接到计费终结点,容器将停止运行。If it can't connect to the billing endpoint within the 10 tries, the container stops running.

计费参数Billing arguments

必须使用有效值指定所有以下三个选项,才能使 docker run 命令启动容器:For the docker run command to start the container, all three of the following options must be specified with valid values:

选项Option 说明Description
ApiKey 用于跟踪计费信息的认知服务资源的 API 密钥。The API key of the Cognitive Services resource that's used to track billing information.
必须将此选项的值设置为 Billing 中指定的已预配资源的 API 密钥。The value of this option must be set to an API key for the provisioned resource that's specified in Billing.
Billing 用于跟踪计费信息的认知服务资源的终结点。The endpoint of the Cognitive Services resource that's used to track billing information.
必须将此选项的值设置为已预配的 Azure 资源的终结点 URI。The value of this option must be set to the endpoint URI of a provisioned Azure resource.
Eula 表示已接受容器的许可条款。Indicates that you accepted the license for the container.
此选项的值必须设置为 acceptThe value of this option must be set to accept.

有关这些选项的详细信息,请参阅配置容器For more information about these options, see Configure containers.


在本文中,我们已学习相关的概念,以及文本分析容器的下载、安装和运行工作流。In this article, you learned concepts and workflow for downloading, installing, and running Text Analytics containers. 综上所述:In summary:

  • 文本分析为 Docker 提供了三个 Linux 容器,其中封装了各种功能:Text Analytics provides three Linux containers for Docker, encapsulating various capabilities:
    • 情绪分析Sentiment Analysis
    • 关键短语提取(预览版)Key Phrase Extraction (preview)
    • 语言检测Language Detection
  • 容器映像可从 Microsoft 容器注册表 (MCR) 或预览版容器注册表中下载。Container images are downloaded from the Microsoft Container Registry (MCR) or preview container repository.
  • 容器映像在 Docker 中运行。Container images run in Docker.
  • 可以使用 REST API 或 SDK 通过指定容器的主机 URI 来调用文本分析容器中的操作。You can use either the REST API or SDK to call operations in Text Analytics containers by specifying the host URI of the container.
  • 必须在实例化容器时指定账单信息。You must specify billing information when instantiating a container.


如果未连接到 Azure 进行计量,则无法授权并运行认知服务容器。Cognitive Services containers are not licensed to run without being connected to Azure for metering. 客户需要始终让容器向计量服务传送账单信息。Customers need to enable the containers to communicate billing information with the metering service at all times. 认知服务容器不会向 Microsoft 发送客户数据(例如正在分析的文本)。Cognitive Services containers do not send customer data (e.g. text that is being analyzed) to Microsoft.

后续步骤Next steps