3.0.0 • Published 5 years ago

@datafire/google_firebaseml v3.0.0

Weekly downloads
1
License
MIT
Repository
github
Last release
5 years ago

@datafire/google_firebaseml

Client library for Firebase ML API

Installation and Usage

npm install --save @datafire/google_firebaseml
let google_firebaseml = require('@datafire/google_firebaseml').create({
  access_token: "",
  refresh_token: "",
  client_id: "",
  client_secret: "",
  redirect_uri: ""
});

.then(data => {
  console.log(data);
});

Description

Access custom machine learning models hosted via Firebase ML.

Actions

oauthCallback

Exchange the code passed to your redirect URI for an access_token

google_firebaseml.oauthCallback({
  "code": ""
}, context)

Input

  • input object
    • code required string

Output

  • output object
    • access_token string
    • refresh_token string
    • token_type string
    • scope string
    • expiration string

oauthRefresh

Exchange a refresh_token for an access_token

google_firebaseml.oauthRefresh(null, context)

Input

This action has no parameters

Output

  • output object
    • access_token string
    • refresh_token string
    • token_type string
    • scope string
    • expiration string

firebaseml.projects.models.delete

Deletes a model

google_firebaseml.firebaseml.projects.models.delete({
  "name": ""
}, context)

Input

  • input object
    • name required string: Required. The name of the model to delete. The name must have the form projects/{project_id}/models/{model_id}
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key string: API key. Your API key identifies your project and provides you with API access, quota, and reports. Required unless you provide an OAuth 2.0 token.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: Available to use for quota purposes for server-side applications. Can be any arbitrary string assigned to a user, but should not exceed 40 characters.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

firebaseml.projects.operations.get

Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.

google_firebaseml.firebaseml.projects.operations.get({
  "name": ""
}, context)

Input

  • input object
    • name required string: The name of the operation resource.
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key string: API key. Your API key identifies your project and provides you with API access, quota, and reports. Required unless you provide an OAuth 2.0 token.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: Available to use for quota purposes for server-side applications. Can be any arbitrary string assigned to a user, but should not exceed 40 characters.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

firebaseml.projects.models.patch

Updates a model. The longrunning operation will eventually return a Model.

google_firebaseml.firebaseml.projects.models.patch({
  "name": ""
}, context)

Input

  • input object
    • name required string: The resource name of the Model. Model names have the form projects/{project_id}/models/{model_id} The name is ignored when creating a model.
    • updateMask string: The update mask
    • body Model
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key string: API key. Your API key identifies your project and provides you with API access, quota, and reports. Required unless you provide an OAuth 2.0 token.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: Available to use for quota purposes for server-side applications. Can be any arbitrary string assigned to a user, but should not exceed 40 characters.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

firebaseml.projects.models.list

Lists the models

google_firebaseml.firebaseml.projects.models.list({
  "parent": ""
}, context)

Input

  • input object
    • parent required string: Required. The name of the parent to list models for. The parent must have the form `projects/{project_id}'
    • filter string: A filter for the list e.g. 'tags: abc' to list models which are tagged with "abc"
    • pageSize integer: The maximum number of items to return
    • pageToken string: The next_page_token value returned from a previous List request, if any.
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key string: API key. Your API key identifies your project and provides you with API access, quota, and reports. Required unless you provide an OAuth 2.0 token.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: Available to use for quota purposes for server-side applications. Can be any arbitrary string assigned to a user, but should not exceed 40 characters.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

firebaseml.projects.models.create

Creates a model in Firebase ML. The longrunning operation will eventually return a Model

google_firebaseml.firebaseml.projects.models.create({
  "parent": ""
}, context)

Input

  • input object
    • parent required string: Required. The parent project resource where the model is to be created. The parent must have the form projects/{project_id}
    • body Model
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key string: API key. Your API key identifies your project and provides you with API access, quota, and reports. Required unless you provide an OAuth 2.0 token.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: Available to use for quota purposes for server-side applications. Can be any arbitrary string assigned to a user, but should not exceed 40 characters.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

Definitions

Empty

  • Empty object: A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for Empty is empty JSON object {}.

ListModelsResponse

  • ListModelsResponse object: The response for list models
    • models array: The list of models
    • nextPageToken string: Token to retrieve the next page of results, or empty if there are no more results in the list.

Model

  • Model object: An ML model hosted in Firebase ML
    • tags array: User defined tags which can be used to group/filter models during listing
      • items string
    • activeOperations array: Output only. Lists operation ids associated with this model whose status is NOT done.
    • createTime string: Output only. Timestamp when this model was created in Firebase ML.
    • displayName string: Required. The name of the model to create. The name can be up to 32 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscores(_) and ASCII digits 0-9. It must start with a letter.
    • etag string: Output only. See RFC7232 https://tools.ietf.org/html/rfc7232#section-2.3
    • modelHash string: Output only. The model_hash will change if a new file is available for download.
    • name string: The resource name of the Model. Model names have the form projects/{project_id}/models/{model_id} The name is ignored when creating a model.
    • state ModelState
    • tfliteModel TfLiteModel
    • updateTime string: Output only. Timestamp when this model was updated in Firebase ML.

ModelOperationMetadata

  • ModelOperationMetadata object: This is returned in the longrunning operations for create/update.
    • basicOperationStatus string (values: BASIC_OPERATION_STATUS_UNSPECIFIED, BASIC_OPERATION_STATUS_UPLOADING, BASIC_OPERATION_STATUS_VERIFYING)
    • name string: The name of the model we are creating/updating The name must have the form projects/{project_id}/models/{model_id}

ModelState

  • ModelState object: State common to all model types. Includes publishing and validation information.
    • published boolean: Indicates if this model has been published.
    • validationError Status

Operation

  • Operation object: This resource represents a long-running operation that is the result of a network API call.
    • done boolean: If the value is false, it means the operation is still in progress. If true, the operation is completed, and either error or response is available.
    • error Status
    • metadata object: Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
    • name string: The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the name should be a resource name ending with operations/{unique_id}.
    • response object: The normal response of the operation in case of success. If the original method returns no data on success, such as Delete, the response is google.protobuf.Empty. If the original method is standard Get/Create/Update, the response should be the resource. For other methods, the response should have the type XxxResponse, where Xxx is the original method name. For example, if the original method name is TakeSnapshot(), the inferred response type is TakeSnapshotResponse.

Status

  • Status object: The Status type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by gRPC. Each Status message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the API Design Guide.
    • code integer: The status code, which should be an enum value of google.rpc.Code.
    • details array: A list of messages that carry the error details. There is a common set of message types for APIs to use.
      • items object
    • message string: A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.

TfLiteModel

  • TfLiteModel object: Information that is specific to TfLite models.
    • automlModel string: The AutoML model id referencing a model you created with the AutoML API. The name should have format 'projects//locations//models/' (This is the model resource name returned from the AutoML API)
    • gcsTfliteUri string: The TfLite file containing the model. (Stored in Google Cloud). The gcs_tflite_uri should have form: gs://some-bucket/some-model.tflite Note: If you update the file in the original location, it is necessary to call UpdateModel for ML to pick up and validate the updated file.
    • sizeBytes string: Output only. The size of the TFLite model
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3.0.0

5 years ago