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eaidc

v1.0.2

Published

Einstein.ai plugin

Downloads

32

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Maintainers

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Keywords

sfdx-plugin

Readme

eai

Einstein.ai plugin

Version CircleCI Appveyor CI Codecov Greenkeeper Known Vulnerabilities Downloads/week License

$ npm install -g eaidc
$ sfdx COMMAND
running command...
$ sfdx (-v|--version|version)
eaidc/1.0.1 darwin-x64 node-v13.12.0
$ sfdx --help [COMMAND]
USAGE
  $ sfdx COMMAND
...

sfdx eai:apiusage [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

Returns prediction usage on a monthly basis for the current calendar month and future months.

USAGE
  $ sfdx eai:apiusage [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:apiusage

  API Usage Summary
  Period Start  Period End  Remaining  Used  Maximum
  ────────────  ──────────  ─────────  ────  ───────
  March/2020    April/2020  1990       10    2000

See code: lib/commands/eai/apiusage.js

sfdx eai:auth:gettoken [-c] [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

USAGE
  $ sfdx eai:auth:gettoken [-c] [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -c, --toclipboard                                                                 add token to clipboard without
                                                                                    displaying in terminal

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:auth:gettoke
     Successfully obtained auth token

See code: lib/commands/eai/auth/gettoken.js

sfdx eai:auth:login -n <string> -f <string> [-e <number>] [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

download an OAuth token for your account

USAGE
  $ sfdx eai:auth:login -n <string> -f <string> [-e <number>] [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -e, --expiration=expiration
      [default: 1] number of minutes until token expires

  -f, --pemlocation=pemlocation
      (required) Local path to your Einsten private key certificat (<something>.pem)

  -n, --name=name
      (required) Your Einstein Platform Services username. You can find your username in the welcome email you receive 
      after you get an account. If you signed up using Salesforce, your username is the email address associated with the 
      org you signed up with.

  --json
      format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)
      [default: warn] logging level for this command invocation

EXAMPLE
  $ sfdx eai:auth:login -n [email protected] -f einstein_platform.pem -e 1
     Successfully obtained auth token for [email protected]

See code: lib/commands/eai/auth/login.js

sfdx eai:language:datasets [-i <string>] [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

get a list of all your datasets, or provide an Id to get the details of a specific dataset

USAGE
  $ sfdx eai:language:datasets [-i <string>] [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -i, --datasetid=datasetid                                                         id of dataset to retrieve, if
                                                                                    missing all datasets are returned

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:language:datasets
  Successfully retrieved language datasets
  Id       Name         Created                Updated                Type         Examples  Labels  Status
  ───────  ───────────  ─────────────────────  ─────────────────────  ───────────  ────────  ──────  ─────────
  1xx3663  atis.csv     3/25/2020, 2:35:18 PM  3/25/2020, 2:35:20 PM  text-intent  763       8       SUCCEEDED
  1xx9106  sampleLDS    5/5/2020, 3:53:21 PM   5/5/2020, 3:53:21 PM   text-intent  150       5       SUCCEEDED
  1xx1357  weather.csv  5/11/2020, 3:47:28 PM  5/11/2020, 3:47:28 PM  text-intent  73        3       SUCCEEDED

See code: lib/commands/eai/language/datasets.js

sfdx eai:language:datasets:create -t <string> [-d <string> | -p <string>] [-l <string>] [-n <string>] [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

create a new dataset

USAGE
  $ sfdx eai:language:datasets:create -t <string> [-d <string> | -p <string>] [-l <string>] [-n <string>] [--json] 
  [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -d, --data=data                                                                   URL of the .zip file. The maximum
                                                                                    .zip file size you can upload from a
                                                                                    web location is 50 MB.

  -l, --language=language                                                           [default: N/A] Dataset language.
                                                                                    Optional. Default is N/A. Reserved
                                                                                    for future use.

  -n, --name=name                                                                   Name of the dataset. Maximum length
                                                                                    is 180 characters.

  -p, --path=path                                                                   URL of the .zip file. The maximum
                                                                                    .zip file size you can upload from a
                                                                                    web location is 50 MB.

  -t, --type=type                                                                   (required) Type of dataset data.
                                                                                    Valid values are text-intent and
                                                                                    text-sentiment. Available in
                                                                                    Einstein Vision API version 2.0 and
                                                                                    later.

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:language:datasets:create --type text-intent --data /mylocaldatapath.csv

See code: lib/commands/eai/language/datasets/create.js

sfdx eai:language:datasets:delete -i <string> [-c] [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

request that a dataset be deleted

USAGE
  $ sfdx eai:language:datasets:delete -i <string> [-c] [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -c, --clipboard                                                                   places the dataset delete status
                                                                                    command in your clipboard

  -i, --datasetid=datasetid                                                         (required) dataset id to retrieve,
                                                                                    if not specified all datasets are
                                                                                    retrieved

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:language:datasets:delete --datasetid 12345
     successfully queued dataset 12345 for deletion
     You can check the status of the delete requestio by entering the command below
     sfdx eai.language:datasets:delete:status --datsetid 123345

See code: lib/commands/eai/language/datasets/delete.js

sfdx eai:language:datasets:delete:status -i <string> [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

get the status of a dataset delete request

USAGE
  $ sfdx eai:language:datasets:delete:status -i <string> [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -i, --deletrequestid=deletrequestid                                               (required) dataset id to retrieve
                                                                                    deletion status for

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:language:datasets:delete:status --deleterequestid
     Successfully retrieved language dataset delete status
     id:              XSBIYHY6LOJOBQVNNVRAODOYOU
     type:            DATASET
     status:          QUEUED
     deletedObjectId: 1186961

See code: lib/commands/eai/language/datasets/delete/status.js

sfdx eai:language:datasets:retrain -i <string> [-e <integer>] [-r <number>] [-p <string>] [-c] [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

request to retrain a dataset, optionally with new params

USAGE
  $ sfdx eai:language:datasets:retrain -i <string> [-e <integer>] [-r <number>] [-p <string>] [-c] [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -c, --clipboard
      places the dataset retrain status command in your clipboard

  -e, --epochs=epochs
      Number of training iterations for the neural network. Optional. Valid values are 1–1,000.

  -i, --modelid=modelid
      (required) Id of the model to be retrained

  -p, --trainparams=trainparams
      JSON that contains parameters that specify how the model is created.

  -r, --learningrate=learningrate
      Specifies how much the gradient affects the optimization of the model at each time step. Optional. Use this 
      parameter to tune your model. Valid values are between 0.0001 and 0.01. If not specified, the default is 0.0001. We 
      recommend keeping this value between 0.0001 and 0.001.    This parameter isn't used when training a detection 
      dataset.

  --json
      format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)
      [default: warn] logging level for this command invocation

EXAMPLE
  $ sfdx eai:language:datasets:retrain --modelid 57
     Successfully requested to retrain the model with id: TDD3UH52XGFRUMC2D63R24H4KM
     datasetId:        1187599
     modelId:          HQSIQO6FMPTONEJ6R3T6LE2TAI
     name:             new model
     status:           QUEUED
     progress:         0
     createdAt:        2020-04-05T22:21:17.000+0000
     You can check the status of the training by entering the command below
     sfdx eai:language:datasets:train:status -i HQSIQO6FMPTONEJ6R3T6LE2TAI

See code: lib/commands/eai/language/datasets/retrain.js

sfdx eai:language:datasets:train -i <string> -n <string> [-e <integer>] [-r <number>] [-p <string>] [-c] [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

request that a dataset begin a training run

USAGE
  $ sfdx eai:language:datasets:train -i <string> -n <string> [-e <integer>] [-r <number>] [-p <string>] [-c] [--json] 
  [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -c, --clipboard
      places the dataset train status command in your clipboard

  -e, --epochs=epochs
      Number of training iterations for the neural network. Optional. Valid values are 1–1,000.

  -i, --datasetid=datasetid
      (required) Id of the dataset to be trained

  -n, --name=name
      (required) Name of the model. Maximum length is 180 characters

  -p, --trainparams=trainparams
      JSON that contains parameters that specify how the model is created.

  -r, --learningrate=learningrate
      Specifies how much the gradient affects the optimization of the model at each time step. Optional. Use this 
      parameter to tune your model. Valid values are between 0.0001 and 0.01. If not specified, the default is 0.0001. We 
      recommend keeping this value between 0.0001 and 0.001.    This parameter isn"t used when training a detection 
      dataset.

  --json
      format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)
      [default: warn] logging level for this command invocation

EXAMPLE
  $ sfdx eai:language:datasets:train --datasetid 57
     Successfully requested dataset '1187599' be trained, status is 'QUEUED'
     You can check the status of the training by entering the command below
       sfdx eai:language:datasets:train:status -i HQSIQO6FMPTONEJ6R3T6LE2TAI

See code: lib/commands/eai/language/datasets/train.js

sfdx eai:language:datasets:train:status -i <string> [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

retrieve the progress of a dataset train request

USAGE
  $ sfdx eai:language:datasets:train:status -i <string> [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -i, --modelid=modelid                                                             (required) language model id to
                                                                                    retrieve training status for

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:language:dataset:train:status --modelid TDD3UH52XGFRUMC2D63R24H4KM
     Successfully retrieved training status
     name:             Simple Model
     status:           RUNNING
     modelId:          TDD3UH52XGFRUMC2D63R24H4KM
     modelType:        text-intent
     updatedAt:        2020-04-05T21:20:10.000+0000

See code: lib/commands/eai/language/datasets/train/status.js

sfdx eai:language:examples [-i <string> | -l <string>] [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

adds examples from a .csv, .tsv, or .json file to a dataset.

USAGE
  $ sfdx eai:language:examples [-i <string> | -l <string>] [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -i, --datasetid=datasetid                                                         language dataset id to retrieve
                                                                                    examples for, if not specified all
                                                                                    examples are retrieved

  -l, --labelid=labelid                                                             label id to retrieve examples for,
                                                                                    if not specified all examples are
                                                                                    retrieved

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:language:datasets:examples --datasetid 3454453

See code: lib/commands/eai/language/examples.js

sfdx eai:language:examples:create -i <string> [-d <string> | -p <string>] [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

create a new dataset

USAGE
  $ sfdx eai:language:examples:create -i <string> [-d <string> | -p <string>] [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -d, --data=data                                                                   local path to the .zip file. The
                                                                                    maximum .zip file size you can
                                                                                    upload from a web location is 50 MB.

  -i, --datasetid=datasetid                                                         (required) dataset id to add the
                                                                                    examples to

  -p, --path=path                                                                   URL of the .zip file. The maximum
                                                                                    .zip file size you can upload from a
                                                                                    web location is 50 MB.

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:language:examples:create --datasetid 1187600 --path =http://einstein.ai/text/weather_update.csv

See code: lib/commands/eai/language/examples/create.js

sfdx eai:language:feedback:create -d <string> -l <string> -i <string> [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

create a feedback for label

USAGE
  $ sfdx eai:language:feedback:create -d <string> -l <string> -i <string> [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -d, --document=document                                                           (required) Intent or sentiment
                                                                                    string to add to the dataset.

  -i, --modelid=modelid                                                             (required) model id to add the
                                                                                    feedback to

  -l, --expectedlabel=expectedlabel                                                 (required) Correct label for the
                                                                                    example. Must be a label that exists
                                                                                    in the dataset.

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:language:feeback:create --modelid 4353445 --document "Is it snowing in Denver" --expectedlabel 
  "current-weather"

See code: lib/commands/eai/language/feedback/create.js

sfdx eai:language:intent -i <string> -d <string> [-n <integer>] [-s <string>] [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

returns an intent prediction for the given string.

USAGE
  $ sfdx eai:language:intent -i <string> -d <string> [-n <integer>] [-s <string>] [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -d, --document=document                                                           (required) the text to evaluate

  -i, --modelid=modelid                                                             (required) model id to make
                                                                                    prediction against

  -n, --numresults=numresults                                                       [default: 2] Number of probabilities
                                                                                    to return. Optional. If passed, must
                                                                                    be a number greater than zero.

  -s, --sampleid=sampleid                                                           String that you can pass in to tag
                                                                                    the prediction. Optional. Can be any
                                                                                    value, and is returned in the
                                                                                    response

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:language:intent --modelid  I3JZ7A5UJRRKU7EZGXZQLKEUZI --document "what is the weather in los angeles"
     Oauth token obtained!

See code: lib/commands/eai/language/intent.js

sfdx eai:language:models -i <string> [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

get a list of all your models for a dataset

USAGE
  $ sfdx eai:language:models -i <string> [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -i, --datasetid=datasetid                                                         (required) language dataset id to
                                                                                    retrieve models for

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:language:models --datasetid 13414123

See code: lib/commands/eai/language/models.js

sfdx eai:language:models:delete -i <string> [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

request that a dataset be deleted

USAGE
  $ sfdx eai:language:models:delete -i <string> [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -i, --modelid=modelid                                                             (required) modelset id to delete
  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:language:models:delete --modelid 4ZZEIOI4FXFWSTEYVFLZXEMOFU

See code: lib/commands/eai/language/models/delete.js

sfdx eai:language:models:metrics [-i <string>] [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

returns the metrics for a model, such as the f1 score, accuracy, and confusion matrix.

USAGE
  $ sfdx eai:language:models:metrics [-i <string>] [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -i, --modelid=modelid                                                             model id to retrieve, if not
                                                                                    specified all datasets are retrieved

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:language:models:metrics --modelid  4ZZEIOI4FXFWSTEYVFLZXEMOFU

See code: lib/commands/eai/language/models/metrics.js

sfdx eai:language:sentiment -i <string> -d <string> [-n <integer>] [-s <string>] [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

returns a sentiment prediction for the given string.

USAGE
  $ sfdx eai:language:sentiment -i <string> -d <string> [-n <integer>] [-s <string>] [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -d, --document=document                                                           (required) The image contained in a
                                                                                    base64 string

  -i, --modelid=modelid                                                             (required) model id to make
                                                                                    prediction against

  -n, --numresults=numresults                                                       [default: 2] Number of probabilities
                                                                                    to return. Optional. If passed, must
                                                                                    be a number greater than zero.

  -s, --sampleid=sampleid                                                           String that you can pass in to tag
                                                                                    the prediction. Optional. Can be any
                                                                                    value, and is returned in the
                                                                                    response

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:language:sentiment --modelid I3JZ7A5UJRRKU7EZGXZQLKEUZI --document "I can't tell you how much fun it was"

See code: lib/commands/eai/language/sentiment.js

sfdx eai:vision:datasets [-i <string>] [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

get a list of all your datasets, or provide an Id to get the details of a specific dataset

USAGE
  $ sfdx eai:vision:datasets [-i <string>] [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -i, --datasetid=datasetid                                                         dataset id to retrieve, if not
                                                                                    specified all datasets are retrieved

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:datasets:vision:get --username [email protected] --pemlocation secrets/einstein.pem
     Oauth token obtained!

See code: lib/commands/eai/vision/datasets.js

sfdx eai:vision:datasets:create -n <string> -t <string> [-b <string>] [-l <string>] [-p <string>] [-d <string>] [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

create a new dataset

USAGE
  $ sfdx eai:vision:datasets:create -n <string> -t <string> [-b <string>] [-l <string>] [-p <string>] [-d <string>] 
  [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -b, --labels=labels                                                               Comma-separated list of labels.
                                                                                    Maximum number of labels per dataset
                                                                                    is 250

  -d, --data=data                                                                   local path to the .zip file. The
                                                                                    maximum .zip file size you can
                                                                                    upload is 50 MB.

  -l, --language=language                                                           [default: N/A] Dataset language.
                                                                                    Optional. Default is N/A. Reserved
                                                                                    for future use.

  -n, --name=name                                                                   (required) Name of the dataset.
                                                                                    Maximum length is 180 characters.

  -p, --path=path                                                                   URL of the .zip file. The maximum
                                                                                    .zip file size you can upload from a
                                                                                    web location is 50 MB.

  -t, --type=type                                                                   (required) Type of dataset data.
                                                                                    Valid values are image and
                                                                                    image-multi-label. Available in
                                                                                    Einstein Vision API version 2.0 and
                                                                                    later.

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:datasets:vision:create --name MyDataset --type image --path http://einstein.ai/images/mountainvsbeach.zip

See code: lib/commands/eai/vision/datasets/create.js

sfdx eai:vision:datasets:delete -i <string> [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

request that a dataset be deleted

USAGE
  $ sfdx eai:vision:datasets:delete -i <string> [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -i, --datasetid=datasetid                                                         (required) dataset id to retrieve,
                                                                                    if not specified all datasets are
                                                                                    retrieved

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:datasets:vision:get --username [email protected] --pemlocation secrets/einstein.pem
     Oauth token obtained!

See code: lib/commands/eai/vision/datasets/delete.js

sfdx eai:vision:datasets:delete:status -i <string> [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

get the status of a dataset delete request

USAGE
  $ sfdx eai:vision:datasets:delete:status -i <string> [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -i, --deleterequestid=deleterequestid                                             (required) dataset id to retrieve
                                                                                    deletion status for

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:vision:datasets:delete:status --deleterequestid RUAV4YTHOASZZH3VHJB3IROX3E

See code: lib/commands/eai/vision/datasets/delete/status.js

sfdx eai:vision:datasets:retrain -i <string> [-e <integer>] [-r <number>] [-p <string>] [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

request to retrain a dataset, optionally with new params

USAGE
  $ sfdx eai:vision:datasets:retrain -i <string> [-e <integer>] [-r <number>] [-p <string>] [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -e, --epochs=epochs
      Number of training iterations for the neural network. Optional. Valid values are 1–1,000.

  -i, --modelid=modelid
      (required) Id of the model to be retrained

  -p, --trainparams=trainparams
      JSON that contains parameters that specify how the model is created.

  -r, --learningrate=learningrate
      Specifies how much the gradient affects the optimization of the model at each time step. Optional. Use this 
      parameter to tune your model. Valid values are between 0.0001 and 0.01. If not specified, the default is 0.0001. We 
      recommend keeping this value between 0.0001 and 0.001.    This parameter isn't used when training a detection 
      dataset.

  --json
      format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)
      [default: warn] logging level for this command invocation

EXAMPLE
  $ sfdx eai:vision:datasets:retrain --modelid 57
     Oauth token obtained!

See code: lib/commands/eai/vision/datasets/retrain.js

sfdx eai:vision:datasets:train -i <string> -n <string> [-e <integer>] [-r <number>] [-p <string>] [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

request that a dataset begin a trainging run

USAGE
  $ sfdx eai:vision:datasets:train -i <string> -n <string> [-e <integer>] [-r <number>] [-p <string>] [--json] 
  [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -e, --epochs=epochs
      Number of training iterations for the neural network. Optional. Valid values are 1–1,000.

  -i, --datasetid=datasetid
      (required) Id of the dataset to be trained

  -n, --name=name
      (required) Name of the model. Maximum length is 180 characters

  -p, --trainparams=trainparams
      JSON that contains parameters that specify how the model is created.

  -r, --learningrate=learningrate
      Specifies how much the gradient affects the optimization of the model at each time step. Optional. Use this 
      parameter to tune your model. Valid values are between 0.0001 and 0.01. If not specified, the default is 0.0001. We 
      recommend keeping this value between 0.0001 and 0.001.    This parameter isn't used when training a detection 
      dataset.

  --json
      format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)
      [default: warn] logging level for this command invocation

EXAMPLE
  $ sfdx eai:vision:datasets:train --datasetid 57
     Oauth token obtained!

See code: lib/commands/eai/vision/datasets/train.js

sfdx eai:vision:datasets:train:status -i <string> [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

retrieve the progress of a dataset train request

USAGE
  $ sfdx eai:vision:datasets:train:status -i <string> [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -i, --modelid=modelid                                                             (required) dataset id to retrieve
                                                                                    training status for

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:vision:datasets:train --modelid FTW2B7YSTZTALH7QTNM3A7DJEY

See code: lib/commands/eai/vision/datasets/train/status.js

sfdx eai:vision:detect -i <string> [-n <integer>] [-s <string>] [-c <string> | -l <string>] [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

get a list of all your datasets, or provide an Id to get the details of a specific dataset

USAGE
  $ sfdx eai:vision:detect -i <string> [-n <integer>] [-s <string>] [-c <string> | -l <string>] [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -c, --samplecontent=samplecontent                                                 Binary content of image file

  -i, --modelid=modelid                                                             (required) model id to make
                                                                                    prediction against

  -l, --samplelocation=samplelocation                                               URL of the image file

  -n, --numresults=numresults                                                       [default: 2] Number of probabilities
                                                                                    to return. Optional. If passed, must
                                                                                    be a number greater than zero.

  -s, --sampleid=sampleid                                                           String that you can pass in to tag
                                                                                    the prediction. Optional. Can be any
                                                                                    value, and is returned in the
                                                                                    response

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:datasets:vision:get --username [email protected] --pemlocation secrets/einstein.pem
     Oauth token obtained!

See code: lib/commands/eai/vision/detect.js

sfdx eai:vision:models -i <string> [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

get a list of all your datasets, or provide an Id to get the details of a specific dataset

USAGE
  $ sfdx eai:vision:models -i <string> [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -i, --datasetid=datasetid                                                         (required) dataset id to retrieve
                                                                                    the models for

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:datasets:vision:get --username [email protected] --pemlocation secrets/einstein.pem
     Oauth token obtained!

See code: lib/commands/eai/vision/models.js

sfdx eai:vision:models:delete -i <string> [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

request that a dataset be deleted

USAGE
  $ sfdx eai:vision:models:delete -i <string> [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -i, --modelid=modelid                                                             (required) modelset id to delete
  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:vision:models:delete --username [email protected] --pemlocation secrets/einstein.pem
     Oauth token obtained!

See code: lib/commands/eai/vision/models/delete.js

sfdx eai:vision:models:learningcurve -i <string> [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

request that a dataset be deleted

USAGE
  $ sfdx eai:vision:models:learningcurve -i <string> [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -i, --modelid=modelid                                                             (required) model id to retrieve, if
                                                                                    not specified all datasets are
                                                                                    retrieved

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:datasets:vision:get --username [email protected] --pemlocation secrets/einstein.pem
     Oauth token obtained!

See code: lib/commands/eai/vision/models/learningcurve.js

sfdx eai:vision:models:metrics [-i <string>] [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

get a list of all your datasets, or provide an Id to get the details of a specific dataset

USAGE
  $ sfdx eai:vision:models:metrics [-i <string>] [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -i, --modelid=modelid                                                             model id to retrieve, if not
                                                                                    specified all datasets are retrieved

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:datasets:vision:get --username [email protected] --pemlocation secrets/einstein.pem
     Oauth token obtained!

See code: lib/commands/eai/vision/models/metrics.js

sfdx eai:vision:ocr [-i <string>] [-c <string> | -l <string>] [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

get a list of all your datasets, or provide an Id to get the details of a specific dataset

USAGE
  $ sfdx eai:vision:ocr [-i <string>] [-c <string> | -l <string>] [--json] [--loglevel 
  trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -c, --samplecontent=samplecontent                                                 Path to the image file

  -i, --modelid=modelid                                                             [default: OCRModel] model id to make
                                                                                    prediction against

  -l, --samplelocation=samplelocation                                               URL of the image file

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:vision:ocr --modelid 'OCRModel' --samplelocation 
  https://www.publicdomainpictures.net/pictures/240000/velka/emergency-evacuation-route-signpost.jpg

  Probability  Label       BB MinX  BB MinY  BB MaxX  BB MaxY
  ───────────  ──────────  ───────  ───────  ───────  ───────
  0.99937266   ROUTE       582      685      1151     815
  0.99471515   EMERGENCY   361      208      1383     346
  0.99469215   EVACUATION  331      438      1401     570

See code: lib/commands/eai/vision/ocr.js

sfdx eai:vision:predict -i <string> [-n <integer>] [-b <string> | -c <string> | -l <string>] [-s <string>] [--json] [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

get a list of all your datasets, or provide an Id to get the details of a specific dataset

USAGE
  $ sfdx eai:vision:predict -i <string> [-n <integer>] [-b <string> | -c <string> | -l <string>] [-s <string>] [--json] 
  [--loglevel trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]

OPTIONS
  -b, --samplebase64content=samplebase64content                                     The image contained in a base64
                                                                                    string

  -c, --samplecontent=samplecontent                                                 Binary content of image file

  -i, --modelid=modelid                                                             (required) model id to make
                                                                                    prediction against

  -l, --samplelocation=samplelocation                                               URL of the image file

  -n, --numresults=numresults                                                       [default: 2] Number of probabilities
                                                                                    to return. Optional. If passed, must
                                                                                    be a number greater than zero.

  -s, --sampleid=sampleid                                                           String that you can pass in to tag
                                                                                    the prediction. Optional. Can be any
                                                                                    value, and is returned in the
                                                                                    response

  --json                                                                            format output as json

  --loglevel=(trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL)  [default: warn] logging level for
                                                                                    this command invocation

EXAMPLE
  $ sfdx eai:datasets:vision:get --username [email protected] --pemlocation secrets/einstein.pem
     Oauth token obtained!

See code: lib/commands/eai/vision/predict.js

Debugging your plugin

We recommend using the Visual Studio Code (VS Code) IDE for your plugin development. Included in the .vscode directory of this plugin is a launch.json config file, which allows you to attach a debugger to the node process when running your commands.

To debug the hello:org command:

  1. Start the inspector

If you linked your plugin to the sfdx cli, call your command with the dev-suspend switch:

$ sfdx hello:org -u [email protected] --dev-suspend

Alternatively, to call your command using the bin/run script, set the NODE_OPTIONS environment variable to --inspect-brk when starting the debugger:

$ NODE_OPTIONS=--inspect-brk bin/run hello:org -u [email protected]
  1. Set some breakpoints in your command code
  2. Click on the Debug icon in the Activity Bar on the side of VS Code to open up the Debug view.
  3. In the upper left hand corner of VS Code, verify that the "Attach to Remote" launch configuration has been chosen.
  4. Hit the green play button to the left of the "Attach to Remote" launch configuration window. The debugger should now be suspended on the first line of the program.
  5. Hit the green play button at the top middle of VS Code (this play button will be to the right of the play button that you clicked in step #5). Congrats, you are debugging!