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rasa命令行介绍

article 2025/1/11 10:01:55

rasa命令行介绍

命令注释
rasa init使用示例训练数据、操作和配置文件创建新项目。
rasa train使用 NLU 数据和故事训练模型，将训练好的模型保存在 中。./models
rasa interactive启动交互式学习会话，通过与助手聊天来创建新的训练数据。
rasa shell加载经过训练的模型，并允许您在命令行上与助手交谈。
rasa run使用已训练的模型启动服务器。
rasa run actions使用 Rasa SDK 启动操作服务器。
rasa visualize生成故事的可视化表示形式。
rasa test在以test_开头的任何文件上测试经过训练的 Rasa 模型。
rasa data split nlu对 NLU 训练数据执行 80/20 拆分。
rasa data convert在不同格式之间转换训练数据。
rasa data migrate将 2.0 域迁移到 3.0 格式。
rasa data validate检查域、NLU 和会话数据是否存在不一致。
rasa export将对话从跟踪器存储导出到事件代理。
rasa evaluate markers从现有跟踪器存储中提取标记。
rasa -h显示所有可用的命令。

rasa init

它创建以下文件：

.
├── actions
│   ├── __init__.py
│   └── actions.py
├── config.yml
├── credentials.yml
├── data
│   ├── nlu.yml
│   └── stories.yml
├── domain.yml
├── endpoints.yml
├── models
│   └── <timestamp>.tar.gz
└── tests
   └── test_stories.yml

它会询问您是否要使用此数据训练初始模型。 如果回答“否”，则目录将为空。models

任何默认的 CLI 命令都需要此项目设置，因此这是最好的开始方式。您可以运行rasa train rasa shell rasa test ，无需任何其他配置。

rasa train

该命令可训练 Rasa 模型

如果您的目录中有现有模型（默认情况下在models/ 下），则仅模型中已更改的部分将被重新训练。例如，如果您编辑您的 NLU 训练数据仅此而已，只会训练 NLU 部分。

如果要单独训练 NLU 或对话模型，可以运行 rasa train nlu或rasa train core 。如果仅提供其中一个的训练数据 默认情况下，这些rasa train命令将回退到这些命令之一。

rasa train默认情况下，将训练好的模型存储在 定义的目录中。 默认情况下--out, models/ 模型的名称为<timestamp>.tar.gz 。如果要以不同的方式命名模型， 您可以使用--fixed-model-name标志指定名称。

以下参数可用于配置训练过程：

usage: rasa train [-h] [-v] [-vv] [--quiet]
                  [--logging-config-file LOGGING_CONFIG_FILE]
                  [--data DATA [DATA ...]] [-c CONFIG] [-d DOMAIN] [--out OUT]
                  [--dry-run] [--augmentation AUGMENTATION] [--debug-plots]
                  [--num-threads NUM_THREADS]
                  [--fixed-model-name FIXED_MODEL_NAME] [--persist-nlu-data]
                  [--force] [--finetune [FINETUNE]]
                  [--epoch-fraction EPOCH_FRACTION] [--endpoints ENDPOINTS]
                  {core,nlu} ...

positional arguments:
  {core,nlu}
    core                Trains a Rasa Core model using your stories.
    nlu                 Trains a Rasa NLU model using your NLU data.

options:
  -h, --help            show this help message and exit
  --data DATA [DATA ...]
                        Paths to the Core and NLU data files. (default:
                        ['data'])
  -c CONFIG, --config CONFIG
                        The policy and NLU pipeline configuration of your bot.
                        (default: config.yml)
  -d DOMAIN, --domain DOMAIN
                        Domain specification. This can be a single YAML file,
                        or a directory that contains several files with domain
                        specifications in it. The content of these files will
                        be read and merged together. (default: domain.yml)
  --out OUT             Directory where your models should be stored.
                        (default: models)
  --dry-run             If enabled, no actual training will be performed.
                        Instead, it will be determined whether a model should
                        be re-trained and this information will be printed as
                        the output. The return code is a 4-bit bitmask that
                        can also be used to determine what exactly needs to be
                        retrained: - 0 means that no extensive training is
                        required (note that the responses still might require
                        updating by running 'rasa train'). - 1 means the model
                        needs to be retrained - 8 means the training was
                        forced (--force argument is specified) (default:
                        False)
  --augmentation AUGMENTATION
                        How much data augmentation to use during training.
                        (default: 50)
  --debug-plots         If enabled, will create plots showing checkpoints and
                        their connections between story blocks in a file
                        called `story_blocks_connections.html`. (default:
                        False)
  --num-threads NUM_THREADS
                        Maximum amount of threads to use when training.
                        (default: None)
  --fixed-model-name FIXED_MODEL_NAME
                        If set, the name of the model file/directory will be
                        set to the given name. (default: None)
  --persist-nlu-data    Persist the NLU training data in the saved model.
                        (default: False)
  --force               Force a model training even if the data has not
                        changed. (default: False)
  --finetune [FINETUNE]
                        Fine-tune a previously trained model. If no model path
                        is provided, Rasa Open Source will try to finetune the
                        latest trained model from the model directory
                        specified via '--out'. (default: None)
  --epoch-fraction EPOCH_FRACTION
                        Fraction of epochs which are currently specified in
                        the model configuration which should be used when
                        finetuning a model. (default: None)
  --endpoints ENDPOINTS
                        Configuration file for the connectors as a yml file.
                        (default: endpoints.yml)

Python Logging Options:
  You can control level of log messages printed. In addition to these
  arguments, a more fine grained configuration can be achieved with
  environment variables. See online documentation for more info.

  -v, --verbose         Be verbose. Sets logging level to INFO. (default:
                        None)
  -vv, --debug          Print lots of debugging statements. Sets logging level
                        to DEBUG. (default: None)
  --quiet               Be quiet! Sets logging level to WARNING. (default:
                        None)
  --logging-config-file LOGGING_CONFIG_FILE
                        If set, the name of the logging configuration file
                        will be set to the given name. (default: None)

rasa interactive

启动交互式学习会话

这将首先训练模型，然后启动交互式 shell 会话。 然后，您可以在与助手交谈时更正助手的预测。 如果 UnexpecTEDIntentPolicy 包含在管道中，action_unlikely_intent可以在任何对话轮次触发。随后，将显示以下消息：

 The bot wants to run 'action_unlikely_intent' to indicate that the last user message was unexpected
 at this point in the conversation. Check out UnexpecTEDIntentPolicy docs to learn more.

如消息所述，这表明您已探索对话路径 根据当前的培训故事集，这是出乎意料的，因此添加了这个 建议使用培训故事的路径。与其他机器人操作一样，您可以选择确认或拒绝运行此操作。

如果使用--model参数提供经过训练的模型，则会跳过训练 并且将改为加载该模型。

在互动学习过程中，Rasa将绘制当前对话 以及来自训练数据的一些类似对话来帮助您 跟踪您的位置。您可以查看可视化效果 在 http://localhost:5005/visualization.html 一旦会话开始。生成此图可能需要一些时间。 要跳过可视化效果，请运行 rasa interactive --skip-visualization

以下参数可用于配置交互式学习会话：

usage: rasa interactive [-h] [-v] [-vv] [--quiet]
                        [--logging-config-file LOGGING_CONFIG_FILE] [--e2e]
                        [-p PORT] [-m MODEL] [--data DATA [DATA ...]]
                        [--skip-visualization]
                        [--conversation-id CONVERSATION_ID]
                        [--endpoints ENDPOINTS] [-c CONFIG] [-d DOMAIN]
                        [--out OUT] [--augmentation AUGMENTATION]
                        [--debug-plots] [--finetune [FINETUNE]]
                        [--epoch-fraction EPOCH_FRACTION] [--force]
                        [--persist-nlu-data]
                        {core} ... [model-as-positional-argument]

positional arguments:
  {core}
    core                Starts an interactive learning session model to create
                        new training data for a Rasa Core model by chatting.
                        Uses the 'RegexMessageHandler', i.e. `/<intent>` input
                        format.
  model-as-positional-argument
                        Path to a trained Rasa model. If a directory is
                        specified, it will use the latest model in this
                        directory. (default: None)

options:
  -h, --help            show this help message and exit
  --e2e                 Save story files in e2e format. In this format user
                        messages will be included in the stories. (default:
                        False)
  -p PORT, --port PORT  Port to run the server at. (default: 5005)
  -m MODEL, --model MODEL
                        Path to a trained Rasa model. If a directory is
                        specified, it will use the latest model in this
                        directory. (default: None)
  --data DATA [DATA ...]
                        Paths to the Core and NLU data files. (default:
                        ['data'])
  --skip-visualization  Disable plotting the visualization during interactive
                        learning. (default: False)
  --conversation-id CONVERSATION_ID
                        Specify the id of the conversation the messages are
                        in. Defaults to a UUID that will be randomly
                        generated. (default: 875709465b4e42399d8fd60d91038bc1)
  --endpoints ENDPOINTS
                        Configuration file for the model server and the
                        connectors as a yml file. (default: endpoints.yml)

Python Logging Options:
  You can control level of log messages printed. In addition to these
  arguments, a more fine grained configuration can be achieved with
  environment variables. See online documentation for more info.

  -v, --verbose         Be verbose. Sets logging level to INFO. (default:
                        None)
  -vv, --debug          Print lots of debugging statements. Sets logging level
                        to DEBUG. (default: None)
  --quiet               Be quiet! Sets logging level to WARNING. (default:
                        None)
  --logging-config-file LOGGING_CONFIG_FILE
                        If set, the name of the logging configuration file
                        will be set to the given name. (default: None)

Train Arguments:
  -c CONFIG, --config CONFIG
                        The policy and NLU pipeline configuration of your bot.
                        (default: config.yml)
  -d DOMAIN, --domain DOMAIN
                        Domain specification. This can be a single YAML file,
                        or a directory that contains several files with domain
                        specifications in it. The content of these files will
                        be read and merged together. (default: domain.yml)
  --out OUT             Directory where your models should be stored.
                        (default: models)
  --augmentation AUGMENTATION
                        How much data augmentation to use during training.
                        (default: 50)
  --debug-plots         If enabled, will create plots showing checkpoints and
                        their connections between story blocks in a file
                        called `story_blocks_connections.html`. (default:
                        False)
  --finetune [FINETUNE]
                        Fine-tune a previously trained model. If no model path
                        is provided, Rasa Open Source will try to finetune the
                        latest trained model from the model directory
                        specified via '--out'. (default: None)
  --epoch-fraction EPOCH_FRACTION
                        Fraction of epochs which are currently specified in
                        the model configuration which should be used when
                        finetuning a model. (default: None)
  --force               Force a model training even if the data has not
                        changed. (default: False)
  --persist-nlu-data    Persist the NLU training data in the saved model.
                        (default: False)

rasa shell

启动聊天会话

默认情况下，这将加载最新的训练模型。 您可以使用标志指定要加载的--model其他模型。

如果使用仅 NLU 模型启动 shell，rasa shell将输出为您输入的任何消息预测的意图和实体。

如果您已经训练了组合的Rasa模型，但只想查看您的模型 从文本中提取为意图和实体，您可以使用命令 rasa shell nlu

若要提高用于调试的日志记录级别，请运行：

rasa shell --debug

以下参数可用于配置命令。 大多数参数与 rasa run重叠;有关这些参数的详细信息，请参阅以下部分。

请注意，--connector参数将始终设置为 cmdline运行rasa shell时 。 这意味着您的凭证文件中的所有凭证都将被忽略， 如果您为--connector参数提供自己的值，它也将被忽略。

usage: rasa shell [-h] [-v] [-vv] [--quiet]
                  [--logging-config-file LOGGING_CONFIG_FILE]
                  [--conversation-id CONVERSATION_ID] [-m MODEL]
                  [--log-file LOG_FILE] [--use-syslog]
                  [--syslog-address SYSLOG_ADDRESS]
                  [--syslog-port SYSLOG_PORT]
                  [--syslog-protocol SYSLOG_PROTOCOL] [--endpoints ENDPOINTS]
                  [-i INTERFACE] [-p PORT] [-t AUTH_TOKEN] [--cors [CORS ...]]
                  [--enable-api] [--response-timeout RESPONSE_TIMEOUT]
                  [--request-timeout REQUEST_TIMEOUT]
                  [--remote-storage REMOTE_STORAGE]
                  [--ssl-certificate SSL_CERTIFICATE]
                  [--ssl-keyfile SSL_KEYFILE] [--ssl-ca-file SSL_CA_FILE]
                  [--ssl-password SSL_PASSWORD] [--credentials CREDENTIALS]
                  [--connector CONNECTOR] [--jwt-secret JWT_SECRET]
                  [--jwt-method JWT_METHOD]
                  [--jwt-private-key JWT_PRIVATE_KEY]
                  {nlu} ... [model-as-positional-argument]

positional arguments:
  {nlu}
    nlu                 Interprets messages on the command line using your NLU
                        model.
  model-as-positional-argument
                        Path to a trained Rasa model. If a directory is
                        specified, it will use the latest model in this
                        directory. (default: None)

options:
  -h, --help            show this help message and exit
  --conversation-id CONVERSATION_ID
                        Set the conversation ID. (default:
                        ba0603d9db404c6db19051ffc3da5d6f)
  -m MODEL, --model MODEL
                        Path to a trained Rasa model. If a directory is
                        specified, it will use the latest model in this
                        directory. (default: models)
  --log-file LOG_FILE   Store logs in specified file. (default: None)
  --use-syslog          Add syslog as a log handler (default: False)
  --syslog-address SYSLOG_ADDRESS
                        Address of the syslog server. --use-sylog flag is
                        required (default: localhost)
  --syslog-port SYSLOG_PORT
                        Port of the syslog server. --use-sylog flag is
                        required (default: 514)
  --syslog-protocol SYSLOG_PROTOCOL
                        Protocol used with the syslog server. Can be UDP
                        (default) or TCP (default: UDP)
  --endpoints ENDPOINTS
                        Configuration file for the model server and the
                        connectors as a yml file. (default: endpoints.yml)

Python Logging Options:
  You can control level of log messages printed. In addition to these
  arguments, a more fine grained configuration can be achieved with
  environment variables. See online documentation for more info.

  -v, --verbose         Be verbose. Sets logging level to INFO. (default:
                        None)
  -vv, --debug          Print lots of debugging statements. Sets logging level
                        to DEBUG. (default: None)
  --quiet               Be quiet! Sets logging level to WARNING. (default:
                        None)
  --logging-config-file LOGGING_CONFIG_FILE
                        If set, the name of the logging configuration file
                        will be set to the given name. (default: None)

Server Settings:
  -i INTERFACE, --interface INTERFACE
                        Network interface to run the server on. (default:
                        0.0.0.0)
  -p PORT, --port PORT  Port to run the server at. (default: 5005)
  -t AUTH_TOKEN, --auth-token AUTH_TOKEN
                        Enable token based authentication. Requests need to
                        provide the token to be accepted. (default: None)
  --cors [CORS ...]     Enable CORS for the passed origin. Use * to whitelist
                        all origins. (default: None)
  --enable-api          Start the web server API in addition to the input
                        channel. (default: False)
  --response-timeout RESPONSE_TIMEOUT
                        Maximum time a response can take to process (sec).
                        (default: 3600)
  --request-timeout REQUEST_TIMEOUT
                        Maximum time a request can take to process (sec).
                        (default: 300)
  --remote-storage REMOTE_STORAGE
                        Set the remote location where your Rasa model is
                        stored, e.g. on AWS. (default: None)
  --ssl-certificate SSL_CERTIFICATE
                        Set the SSL Certificate to create a TLS secured
                        server. (default: None)
  --ssl-keyfile SSL_KEYFILE
                        Set the SSL Keyfile to create a TLS secured server.
                        (default: None)
  --ssl-ca-file SSL_CA_FILE
                        If your SSL certificate needs to be verified, you can
                        specify the CA file using this parameter. (default:
                        None)
  --ssl-password SSL_PASSWORD
                        If your ssl-keyfile is protected by a password, you
                        can specify it using this paramer. (default: None)

Channels:
  --credentials CREDENTIALS
                        Authentication credentials for the connector as a yml
                        file. (default: None)
  --connector CONNECTOR
                        Service to connect to. (default: None)

JWT Authentication:
  --jwt-secret JWT_SECRET
                        Public key for asymmetric JWT methods or shared
                        secretfor symmetric methods. Please also make sure to
                        use --jwt-method to select the method of the
                        signature, otherwise this argument will be
                        ignored.Note that this key is meant for securing the
                        HTTP API. (default: None)
  --jwt-method JWT_METHOD
                        Method used for the signature of the JWT
                        authentication payload. (default: HS256)
  --jwt-private-key JWT_PRIVATE_KEY
                        A private key used for generating web tokens,
                        dependent upon which hashing algorithm is used. It
                        must be used together with --jwt-secret for providing
                        the public key. (default: None)

rasa run

启动运行已训练模型的服务器

默认情况下，Rasa 服务器使用 HTTP 进行通信。保护与SSL的通信 并在HTTPS上运行服务器，需要提供有效的证书和相应的私钥文件。可以将这些文件指定为rasa run命令的一部分。 如果您在创建过程中使用密码加密了密钥文件， 您还需要添加--ssl-password。

rasa run --ssl-certificate myssl.crt --ssl-keyfile myssl.key --ssl-password mypassword

默认情况下，Rasa 侦听每个可用的网络接口。您可以将其限制为特定的使用命令行选项-i的网络接口。

rasa run -i 192.168.69.150

默认情况下，Rasa 将连接到凭证文件中指定的所有通道。 要连接到单个通道并忽略凭据文件中的所有其他通道， 在参数中指定通道的--connector名称。

rasa run --connector rest

以下参数可用于配置 Rasa 服务器：

usage: rasa run [-h] [-v] [-vv] [--quiet]
                [--logging-config-file LOGGING_CONFIG_FILE] [-m MODEL]
                [--log-file LOG_FILE] [--use-syslog]
                [--syslog-address SYSLOG_ADDRESS] [--syslog-port SYSLOG_PORT]
                [--syslog-protocol SYSLOG_PROTOCOL] [--endpoints ENDPOINTS]
                [-i INTERFACE] [-p PORT] [-t AUTH_TOKEN] [--cors [CORS ...]]
                [--enable-api] [--response-timeout RESPONSE_TIMEOUT]
                [--request-timeout REQUEST_TIMEOUT]
                [--remote-storage REMOTE_STORAGE]
                [--ssl-certificate SSL_CERTIFICATE]
                [--ssl-keyfile SSL_KEYFILE] [--ssl-ca-file SSL_CA_FILE]
                [--ssl-password SSL_PASSWORD] [--credentials CREDENTIALS]
                [--connector CONNECTOR] [--jwt-secret JWT_SECRET]
                [--jwt-method JWT_METHOD] [--jwt-private-key JWT_PRIVATE_KEY]
                {actions} ... [model-as-positional-argument]

positional arguments:
  {actions}
    actions             Runs the action server.
  model-as-positional-argument
                        Path to a trained Rasa model. If a directory is
                        specified, it will use the latest model in this
                        directory. (default: None)

options:
  -h, --help            show this help message and exit
  -m MODEL, --model MODEL
                        指定训练的RASA模型的路径。如果指定了目录，它将使用该目录中的最新model。
                        (default: models)
  --log-file LOG_FILE   将日志存储在指定文件中。 (default: None)
  --use-syslog          Add syslog as a log handler (default: False)
  --syslog-address SYSLOG_ADDRESS
                        Address of the syslog server. --use-sylog flag is
                        required (default: localhost)
  --syslog-port SYSLOG_PORT
                        Port of the syslog server. --use-sylog flag is
                        required (default: 514)
  --syslog-protocol SYSLOG_PROTOCOL
                        Protocol used with the syslog server. Can be UDP
                        (default) or TCP (default: UDP)
  --endpoints ENDPOINTS
                        作为YML文件的模型服务器和连接器的配置文件 (default: endpoints.yml)

Python Logging Options:
  You can control level of log messages printed. In addition to these
  arguments, a more fine grained configuration can be achieved with
  environment variables. See online documentation for more info.

  -v, --verbose         Be verbose. Sets logging level to INFO. (default:
                        None)
  -vv, --debug          Print lots of debugging statements. Sets logging level
                        to DEBUG. (default: None)
  --quiet               Be quiet! Sets logging level to WARNING. (default:
                        None)
  --logging-config-file LOGGING_CONFIG_FILE
                        If set, the name of the logging configuration file
                        will be set to the given name. (default: None)

Server Settings:
  -i INTERFACE, --interface INTERFACE
                        运行服务器的网络接口. (default:
                        0.0.0.0)
  -p PORT, --port PORT  运行服务器的端口. (default: 5005)
  -t AUTH_TOKEN, --auth-token AUTH_TOKEN
                        启用基于令牌的身份验证。请求需要提供令牌才能接受. (default: None)
  --cors [CORS ...]     为传递的原点启用CORS（跨源资源共享）。使用*将所有来源列入白名单。 
  						(default: None)
  --enable-api          除输入通道外，还启动Web服务器API. (default: False)
  --response-timeout RESPONSE_TIMEOUT
                        处理响应所需的最长时间 (sec).(default: 3600)
  --request-timeout REQUEST_TIMEOUT
                        处理请求所需的最长时间 (sec).(default: 300)
  --remote-storage REMOTE_STORAGE
                        设置存储您的RASA模型的远程位置，例如在AWS上. (default: None)
  --ssl-certificate SSL_CERTIFICATE
                        Set the SSL Certificate to create a TLS secured
                        server. (default: None)
  --ssl-keyfile SSL_KEYFILE
                        Set the SSL Keyfile to create a TLS secured server.
                        (default: None)
  --ssl-ca-file SSL_CA_FILE
                        If your SSL certificate needs to be verified, you can
                        specify the CA file using this parameter. (default:
                        None)
  --ssl-password SSL_PASSWORD
                        If your ssl-keyfile is protected by a password, you
                        can specify it using this paramer. (default: None)

Channels:
  --credentials CREDENTIALS
                        Authentication credentials for the connector as a yml
                        file. (default: None)
  --connector CONNECTOR
                        Service to connect to. (default: None)

JWT Authentication:
  --jwt-secret JWT_SECRET
                        Public key for asymmetric JWT methods or shared
                        secretfor symmetric methods. Please also make sure to
                        use --jwt-method to select the method of the
                        signature, otherwise this argument will be
                        ignored.Note that this key is meant for securing the
                        HTTP API. (default: None)
  --jwt-method JWT_METHOD
                        Method used for the signature of the JWT
                        authentication payload. (default: HS256)
  --jwt-private-key JWT_PRIVATE_KEY
                        A private key used for generating web tokens,
                        dependent upon which hashing algorithm is used. It
                        must be used together with --jwt-secret for providing
                        the public key. (default: None)

rasa run actions

使用 Rasa SDK 启动操作服务器

以下参数可用于调整服务器设置：

usage: rasa run actions [-h] [-v] [-vv] [--quiet]
                        [--logging-config-file LOGGING_CONFIG_FILE] [-p PORT]
                        [--cors [CORS ...]] [--actions ACTIONS]
                        [--ssl-keyfile SSL_KEYFILE]
                        [--ssl-certificate SSL_CERTIFICATE]
                        [--ssl-password SSL_PASSWORD] [--auto-reload]

options:
  -h, --help            show this help message and exit
  -p PORT, --port PORT  运行服务器的端口 (default: 5055)
  --cors [CORS ...]     为传递的原点启用CORS。使用*将原点列入白名单 (default: None)
  --actions ACTIONS     要加载的动作包的名称 (default: None)
  --ssl-keyfile SSL_KEYFILE
                        Set the SSL certificate to create a TLS secured
                        server. (default: None)
  --ssl-certificate SSL_CERTIFICATE
                        Set the SSL certificate to create a TLS secured
                        server. (default: None)
  --ssl-password SSL_PASSWORD
                        If your ssl-keyfile is protected by a password, you
                        can specify it using this paramer. (default: None)
  --auto-reload         启用包含操作子类的模块的自动重新加载. (default: False)

Python Logging Options:
  You can control level of log messages printed. In addition to these
  arguments, a more fine grained configuration can be achieved with
  environment variables. See online documentation for more info.

  -v, --verbose         要详细。将日志记录级别设置为INFO. (default:None)
  -vv, --debug          打印大量调试语句。将日志记录级别设置为DEBUG. (default: None)
  --quiet               Be quiet! Sets logging level to WARNING. (default:
                        None)
  --logging-config-file LOGGING_CONFIG_FILE
                        If set, the name of the logging configuration file
                        will be set to the given name. (default: None)

rasa visualize

在浏览器中生成故事图表

如果您的故事位于默认位置data/以外的其他位置， 您可以使用标志--stories指定它们的位置。

以下参数可用于配置此命令：

usage: rasa visualize [-h] [-v] [-vv] [--quiet]
                      [--logging-config-file LOGGING_CONFIG_FILE] [-d DOMAIN]
                      [-s STORIES] [--out OUT] [--max-history MAX_HISTORY]
                      [-u NLU]

options:
  -h, --help            show this help message and exit
  -d DOMAIN, --domain DOMAIN
                        Domain规范。这可以是单个YAML文件，也可以是包含多个其中包含域规范的文件
                        的目录。这些文件的内容将被读取并合并在一起. 
                        (default: domain.yml)
  -s STORIES, --stories STORIES
                        包含training stories的文件或文件夹.
                        (default: data)
  --out OUT             Filename of the output path, e.g. 'graph.html'.
                        (default: graph.html)
  --max-history MAX_HISTORY
                        合并输出图中的路径时要考虑的最大历史记录. (default: 2)
  -u NLU, --nlu NLU     包含NLU数据的文件或文件夹，用于将示例消息插入图表. (default:
                        None)

Python Logging Options:
  You can control level of log messages printed. In addition to these
  arguments, a more fine grained configuration can be achieved with
  environment variables. See online documentation for more info.

  -v, --verbose         Be verbose. Sets logging level to INFO. (default:
                        None)
  -vv, --debug          Print lots of debugging statements. Sets logging level
                        to DEBUG. (default: None)
  --quiet               Be quiet! Sets logging level to WARNING. (default:
                        None)
  --logging-config-file LOGGING_CONFIG_FILE
                        If set, the name of the logging configuration file
                        will be set to the given name. (default: None)

rasa test

在测试数据上评估模型

rasa data split

创建 NLU 训练数据的训练-测试拆分

rasa data convert nlu

启动转换器

rasa data migrate

可以将 2.0 域自动迁移到 3.0 格式。

rasa data validate

验证数据。可以检查域、NLU 数据或故事数据是否存在错误和不一致之处。

rasa export

使用事件代理从跟踪器存储中导出事件

rasa evaluate markers

应用您在标记配置文件中定义的标记， 到存储在智能设备商店中的预先存在的对话框，并生成包含以下内容的文件.csv提取的标记和汇总统计信息：


http://www.kler.cn/a/5947.html

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