Returns the analysisRules Resource.
Returns the assessmentRules Resource.
Returns the authorizedViewSets Resource.
Returns the autoLabelingRules Resource.
Returns the conversations Resource.
Returns the dashboards Resource.
Returns the datasets Resource.
Returns the encryptionSpec Resource.
Returns the insightsdata Resource.
Returns the issueModels Resource.
Returns the operations Resource.
Returns the phraseMatchers Resource.
Returns the qaQuestionTags Resource.
Returns the qaScorecards Resource.
Returns the views Resource.
bulkDeleteFeedbackLabels(parent, body=None, x__xgafv=None)
Delete feedback labels in bulk using a filter.
bulkDownloadFeedbackLabels(parent, body=None, x__xgafv=None)
Download feedback labels in bulk from an external source. Currently supports exporting Quality AI example conversations with transcripts and question bodies.
bulkUploadFeedbackLabels(parent, body=None, x__xgafv=None)
Upload feedback labels from an external source in bulk. Currently supports labeling Quality AI example conversations.
Close httplib2 connections.
generativeInsights(location, body=None, x__xgafv=None)
Natural language based Insights which powers the next generation of dashboards in Insights. Next generation of QueryMetrics.
getCorrelationConfig(name, x__xgafv=None)
Gets correlation config.
getEncryptionSpec(name, x__xgafv=None)
Gets location-level encryption key specification.
getSettings(name, x__xgafv=None)
Gets project-level settings.
listAllFeedbackLabels(parent, filter=None, pageSize=None, pageToken=None, x__xgafv=None)
List all feedback labels by project number.
Retrieves the next page of results.
queryMetrics(location, body=None, x__xgafv=None)
Query metrics.
queryPerformanceOverview(parent, body=None, x__xgafv=None)
Generates a summary of predefined performance metrics for a set of conversations. Conversations can be specified by specifying a time window and an agent id, for now. The summary includes a comparison of metrics computed for conversations in the previous time period, and also a comparison with peers in the same time period.
testCorrelationConfig(location, body=None, x__xgafv=None)
Tests correlation config on a conversation.
updateCorrelationConfig(name, body=None, updateMask=None, x__xgafv=None)
Updates correlation config.
updateSettings(name, body=None, updateMask=None, x__xgafv=None)
Updates project-level settings.
bulkDeleteFeedbackLabels(parent, body=None, x__xgafv=None)
Delete feedback labels in bulk using a filter.
Args:
parent: string, Required. The parent resource for new feedback labels. (required)
body: object, The request body.
The object takes the form of:
{ # Request for the BulkDeleteFeedbackLabels endpoint.
"filter": "A String", # Optional. A filter to reduce results to a specific subset. Supports disjunctions (OR) and conjunctions (AND). Supported fields: * `issue_model_id` * `qa_question_id` * `qa_scorecard_id` * `min_create_time` * `max_create_time` * `min_update_time` * `max_update_time` * `feedback_label_type`: QUALITY_AI, TOPIC_MODELING
"parent": "A String", # Required. The parent resource for new feedback labels.
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # 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": { # 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](https://github.com/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](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A 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.
},
"metadata": { # 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.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A 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": { # The normal, successful response of the operation. 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`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}
bulkDownloadFeedbackLabels(parent, body=None, x__xgafv=None)
Download feedback labels in bulk from an external source. Currently supports exporting Quality AI example conversations with transcripts and question bodies.
Args:
parent: string, Required. The parent resource for new feedback labels. (required)
body: object, The request body.
The object takes the form of:
{ # Request for the BulkDownloadFeedbackLabel endpoint.
"conversationFilter": "A String", # Optional. Filter parent conversations to download feedback labels for. When specified, the feedback labels will be downloaded for the conversations that match the filter. If `template_qa_scorecard_id` is set, all the conversations that match the filter will be paired with the questions under the scorecard for labeling.
"feedbackLabelType": "A String", # Optional. The type of feedback labels that will be downloaded.
"filter": "A String", # Optional. A filter to reduce results to a specific subset. Supports disjunctions (OR) and conjunctions (AND). Supported fields: * `issue_model_id` * `qa_question_id` * `qa_scorecard_id` * `min_create_time` * `max_create_time` * `min_update_time` * `max_update_time` * `feedback_label_type`: QUALITY_AI, TOPIC_MODELING
"gcsDestination": { # Google Cloud Storage Object details to write the feedback labels to. # A cloud storage bucket destination.
"addWhitespace": True or False, # Optional. Add whitespace to the JSON file. Makes easier to read, but increases file size. Only applicable for JSON format.
"alwaysPrintEmptyFields": True or False, # Optional. Always print fields with no presence. This is useful for printing fields that are not set, like implicit 0 value or empty lists/maps. Only applicable for JSON format.
"format": "A String", # Required. File format in which the labels will be exported.
"objectUri": "A String", # Required. The Google Cloud Storage URI to write the feedback labels to. The file name will be used as a prefix for the files written to the bucket if the output needs to be split across multiple files, otherwise it will be used as is. The file extension will be appended to the file name based on the format selected. E.g. `gs://bucket_name/object_uri_prefix`
"recordsPerFileCount": "A String", # Optional. The number of records per file. Applicable for either format.
},
"maxDownloadCount": 42, # Optional. Limits the maximum number of feedback labels that will be downloaded. The first `N` feedback labels will be downloaded.
"parent": "A String", # Required. The parent resource for new feedback labels.
"sheetsDestination": { # Google Sheets document details to write the feedback labels to. # A sheets document destination.
"sheetTitle": "A String", # Optional. The title of the new sheet to write the feedback labels to.
"spreadsheetUri": "A String", # Required. The Google Sheets document to write the feedback labels to. Retrieved from Google Sheets URI. E.g. `https://docs.google.com/spreadsheets/d/1234567890` The spreadsheet must be shared with the Insights P4SA. The spreadsheet ID written to will be returned as `file_names` in the BulkDownloadFeedbackLabelsMetadata.
},
"templateQaScorecardId": [ # Optional. If set, a template for labeling conversations and scorecard questions will be created from the conversation_filter and the questions under the scorecard(s). The feedback label `filter` will be ignored.
"A String",
],
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # 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": { # 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](https://github.com/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](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A 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.
},
"metadata": { # 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.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A 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": { # The normal, successful response of the operation. 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`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}
bulkUploadFeedbackLabels(parent, body=None, x__xgafv=None)
Upload feedback labels from an external source in bulk. Currently supports labeling Quality AI example conversations.
Args:
parent: string, Required. The parent resource for new feedback labels. (required)
body: object, The request body.
The object takes the form of:
{ # The request for bulk uploading feedback labels.
"gcsSource": { # Google Cloud Storage Object details to get the feedback label file from. # A cloud storage bucket source.
"format": "A String", # Required. File format which will be ingested.
"objectUri": "A String", # Required. The Google Cloud Storage URI of the file to import. Format: `gs://bucket_name/object_name`
},
"sheetsSource": { # Google Sheets document details to get the feedback label file from. # A sheets document source.
"spreadsheetUri": "A String", # Required. The Google Sheets document to write the feedback labels to. Retrieved from Google Sheets URI. E.g. `https://docs.google.com/spreadsheets/d/1234567890` The spreadsheet must be shared with the Insights P4SA.
},
"validateOnly": True or False, # Optional. If set, upload will not happen and the labels will be validated. If not set, then default behavior will be to upload the labels after validation is complete.
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # 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": { # 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](https://github.com/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](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A 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.
},
"metadata": { # 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.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A 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": { # The normal, successful response of the operation. 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`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}
close()
Close httplib2 connections.
generativeInsights(location, body=None, x__xgafv=None)
Natural language based Insights which powers the next generation of dashboards in Insights. Next generation of QueryMetrics.
Args:
location: string, Required. The location of the data. "projects/{project}/locations/{location}" (required)
body: object, The request body.
The object takes the form of:
{ # The request for generative insights.
"chart": "A String", # The full name of the chart resource this request corresponds to. Format: projects/{project}/locations/{location}/dashboards/{dashboard}/charts/{chart}
"comparisonFilter": "A String", # Optional. Filter for the data that can be specified in addition to the natural language query. This `filter` is specifically used for charts where comparisons are possible. For example, "compare to last month" or "compare to previous quarter".
"filter": "A String", # Filter for the data that can be specified in addition to the natural language query. Users are encouraged to use this field to populate time-windows.
"naturalLanguageQuery": "A String", # The natural language query specified by the user. If this field is specified, `sql_query` will be ignored.
"revisionId": "A String", # Optional. The revision id that maps to the state of the chart state revision. When specified, the backend will reload the chart with the sql and visual spec from that revision.
"sessionId": "A String", # Optional. The session id of the conversation. If the session id is not specified, backend will generate a random session id. If the session id is specified, will associate user-provided user_query with the provided session id.
"sqlComparisonKey": "A String", # Optional. For charts with comparison, this key will determine the metric that will be compared between the current and another dataset.
"sqlQuery": "A String", # Optional. The SQL query specified by the user. This query must be in BigQuery SQL dialect. The `filter` field will also be ignored, as it is assumed that any filtering is already included in the SQL query.
"userProvidedChartSpec": { # Optional. The user provided chart spec for the chart. This will be used to override the visual spec generated by the LLM.
"a_key": "", # Properties of the object.
},
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # 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": { # 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](https://github.com/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](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A 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.
},
"metadata": { # 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.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A 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": { # The normal, successful response of the operation. 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`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}
getCorrelationConfig(name, x__xgafv=None)
Gets correlation config.
Args:
name: string, Required. The name of the correlation config resource to get. Format: projects/{project}/locations/{location}/correlationConfig (required)
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # A configuration that defines how to correlate conversations for a given a given project.
"createTime": "A String", # Output only. The time at which the correlation config was created.
"fullConversationConfig": { # A list of correlation rules for a given correlation type. # The correlation type config for full conversations.
"correlationRules": [ # A list of correlation rules to be evaluated for correlation.
{ # A correlation rule that defines how to join conversations for a given correlation type.
"active": True or False, # Optional. Whether the config is active to be evaluated.
"constraintExpression": "A String", # Optional. A cel expression (go/cel) to be evaluated as a boolean value. Two variables conversation_a and conversation_b will be available for evaluation. This expression should evaluate to true if conversation_a and conversation_b should be joined. This is used as an extra constraint on top of the join_key_expression to further refine the group of conversations that are joined together and will be evaluated in both directions. for two conversations c1 and c2 and the result will be OR'd. We will evaluate: f(c1, c2) OR f(c2, c1)
"joinKeyExpression": "A String", # Optional. A cel expression (go/cel) to be evaluated as a string value. This string value will be used as the join key for the correlation.
"ruleId": "A String", # Required. The unique identifier of the rule.
},
],
},
"name": "A String", # Immutable. Identifier. The resource name of the correlation config. Format: projects/{project}/locations/{location}/correlationConfig
"updateTime": "A String", # Output only. The time at which the correlation config was last updated.
}
getEncryptionSpec(name, x__xgafv=None)
Gets location-level encryption key specification.
Args:
name: string, Required. The name of the encryption spec resource to get. (required)
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # A customer-managed encryption key specification that can be applied to all created resources (e.g. `Conversation`).
"kmsKey": "A String", # Required. The name of customer-managed encryption key that is used to secure a resource and its sub-resources. If empty, the resource is secured by our default encryption key. Only the key in the same location as this resource is allowed to be used for encryption. Format: `projects/{project}/locations/{location}/keyRings/{keyRing}/cryptoKeys/{key}`
"name": "A String", # Immutable. The resource name of the encryption key specification resource. Format: projects/{project}/locations/{location}/encryptionSpec
}
getSettings(name, x__xgafv=None)
Gets project-level settings.
Args:
name: string, Required. The name of the settings resource to get. (required)
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # The CCAI Insights project wide settings. Use these settings to configure the behavior of Insights. View these settings with [`getsettings`](https://cloud.google.com/contact-center/insights/docs/reference/rest/v1/projects.locations/getSettings) and change the settings with [`updateSettings`](https://cloud.google.com/contact-center/insights/docs/reference/rest/v1/projects.locations/updateSettings).
"analysisConfig": { # Default configuration when creating Analyses in Insights. # Default analysis settings.
"annotatorSelector": { # Selector of all available annotators and phrase matchers to run. # To select the annotators to run and the phrase matchers to use (if any). If not specified, all annotators will be run.
"issueModels": [ # The issue model to run. If not provided, the most recently deployed topic model will be used. The provided issue model will only be used for inference if the issue model is deployed and if run_issue_model_annotator is set to true. If more than one issue model is provided, only the first provided issue model will be used for inference.
"A String",
],
"phraseMatchers": [ # The list of phrase matchers to run. If not provided, all active phrase matchers will be used. If inactive phrase matchers are provided, they will not be used. Phrase matchers will be run only if run_phrase_matcher_annotator is set to true. Format: projects/{project}/locations/{location}/phraseMatchers/{phrase_matcher}
"A String",
],
"qaConfig": { # Configuration for the QA feature. # Configuration for the QA annotator.
"scorecardList": { # Container for a list of scorecards. # A manual list of scorecards to score.
"qaScorecardRevisions": [ # List of QaScorecardRevisions.
"A String",
],
},
},
"runEntityAnnotator": True or False, # Whether to run the entity annotator.
"runIntentAnnotator": True or False, # Whether to run the intent annotator.
"runInterruptionAnnotator": True or False, # Whether to run the interruption annotator.
"runIssueModelAnnotator": True or False, # Whether to run the issue model annotator. A model should have already been deployed for this to take effect.
"runPhraseMatcherAnnotator": True or False, # Whether to run the active phrase matcher annotator(s).
"runQaAnnotator": True or False, # Whether to run the QA annotator.
"runSentimentAnnotator": True or False, # Whether to run the sentiment annotator.
"runSilenceAnnotator": True or False, # Whether to run the silence annotator.
"runSummarizationAnnotator": True or False, # Whether to run the summarization annotator.
"summarizationConfig": { # Configuration for summarization. # Configuration for the summarization annotator.
"conversationProfile": "A String", # Resource name of the Dialogflow conversation profile. Format: projects/{project}/locations/{location}/conversationProfiles/{conversation_profile}
"generator": "A String", # The resource name of the existing created generator. Format: projects//locations//generators/
"summarizationModel": "A String", # Default summarization model to be used.
},
},
"runtimeIntegrationAnalysisPercentage": 3.14, # Percentage of conversations created using Dialogflow runtime integration to analyze automatically, between [0, 100].
"uploadConversationAnalysisPercentage": 3.14, # Percentage of conversations created using the UploadConversation endpoint to analyze automatically, between [0, 100].
},
"conversationTtl": "A String", # The default TTL for newly-created conversations. If a conversation has a specified expiration, that value will be used instead. Changing this value will not change the expiration of existing conversations. Conversations with no expire time persist until they are deleted.
"createTime": "A String", # Output only. The time at which the settings was created.
"languageCode": "A String", # A language code to be applied to each transcript segment unless the segment already specifies a language code. Language code defaults to "en-US" if it is neither specified on the segment nor here.
"name": "A String", # Immutable. The resource name of the settings resource. Format: projects/{project}/locations/{location}/settings
"pubsubNotificationSettings": { # A map that maps a notification trigger to a Pub/Sub topic. Each time a specified trigger occurs, Insights will notify the corresponding Pub/Sub topic. Keys are notification triggers. Supported keys are: * "all-triggers": Notify each time any of the supported triggers occurs. * "create-analysis": Notify each time an analysis is created. * "create-conversation": Notify each time a conversation is created. * "export-insights-data": Notify each time an export is complete. * "ingest-conversations": Notify each time an IngestConversations LRO is complete. * "update-conversation": Notify each time a conversation is updated via UpdateConversation. * "upload-conversation": Notify when an UploadConversation LRO is complete. * "update-or-analyze-conversation": Notify when an analysis for a conversation is completed or when the conversation is updated. The message will contain the conversation with transcript, analysis and other metadata. Values are Pub/Sub topics. The format of each Pub/Sub topic is: projects/{project}/topics/{topic}
"a_key": "A String",
},
"redactionConfig": { # DLP resources used for redaction while ingesting conversations. DLP settings are applied to conversations ingested from the `UploadConversation` and `IngestConversations` endpoints, including conversation coming from CCAI Platform. They are not applied to conversations ingested from the `CreateConversation` endpoint or the Dialogflow / Agent Assist runtime integrations. When using Dialogflow / Agent Assist runtime integrations, redaction should be performed in Dialogflow / Agent Assist. # Default DLP redaction resources to be applied while ingesting conversations. This applies to conversations ingested from the `UploadConversation` and `IngestConversations` endpoints, including conversations coming from CCAI Platform.
"deidentifyTemplate": "A String", # The fully-qualified DLP deidentify template resource name. Format: `projects/{project}/deidentifyTemplates/{template}`
"inspectTemplate": "A String", # The fully-qualified DLP inspect template resource name. Format: `projects/{project}/locations/{location}/inspectTemplates/{template}`
},
"screenRecordingBucketUri": "A String", # Optional. The path to a Cloud Storage bucket containing conversation screen recordings. If provided, Insights will search in the bucket for a screen recording file matching the conversation data source object name prefix. If matches are found, these file URIs will be stored in the conversation screen recordings field.
"speechConfig": { # Speech-to-Text configuration. Speech-to-Text settings are applied to conversations ingested from the `UploadConversation` and `IngestConversations` endpoints, including conversation coming from CCAI Platform. They are not applied to conversations ingested from the `CreateConversation` endpoint. # Optional. Default Speech-to-Text resources to use while ingesting audio files. Optional, CCAI Insights will create a default if not provided. This applies to conversations ingested from the `UploadConversation` and `IngestConversations` endpoints, including conversations coming from CCAI Platform.
"disableWordTimeOffsets": True or False, # Whether to disable word time offsets. If true, the `enable_word_time_offsets` field in the recognition config will be set to false.
"speechRecognizer": "A String", # The fully-qualified Speech Recognizer resource name. Format: `projects/{project_id}/locations/{location}/recognizer/{recognizer}`
},
"updateTime": "A String", # Output only. The time at which the settings were last updated.
}
listAllFeedbackLabels(parent, filter=None, pageSize=None, pageToken=None, x__xgafv=None)
List all feedback labels by project number.
Args:
parent: string, Required. The parent resource of all feedback labels per project. (required)
filter: string, Optional. A filter to reduce results to a specific subset in the entire project. Supports disjunctions (OR) and conjunctions (AND). Supported fields: * `issue_model_id` * `qa_question_id` * `min_create_time` * `max_create_time` * `min_update_time` * `max_update_time` * `feedback_label_type`: QUALITY_AI, TOPIC_MODELING
pageSize: integer, Optional. The maximum number of feedback labels to return in the response. A valid page size ranges from 0 to 100,000 inclusive. If the page size is zero or unspecified, a default page size of 100 will be chosen. Note that a call might return fewer results than the requested page size.
pageToken: string, Optional. The value returned by the last `ListAllFeedbackLabelsResponse`. This value indicates that this is a continuation of a prior `ListAllFeedbackLabels` call and that the system should return the next page of data.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # The response for listing all feedback labels.
"feedbackLabels": [ # The feedback labels that match the request.
{ # Represents a conversation, resource, and label provided by the user. Can take the form of a string label or a QaAnswer label. QaAnswer labels are used for Quality AI example conversations. String labels are used for Topic Modeling. AgentAssistSummary labels are used for Agent Assist Summarization.
"createTime": "A String", # Output only. Create time of the label.
"label": "A String", # String label used for Topic Modeling.
"labeledResource": "A String", # Name of the resource to be labeled. Supported resources are: * `projects/{project}/locations/{location}/qaScorecards/{scorecard}/revisions/{revision}/qaQuestions/{question}` * `projects/{project}/locations/{location}/issueModels/{issue_model}` * `projects/{project}/locations/{location}/generators/{generator_id}`
"name": "A String", # Immutable. Resource name of the FeedbackLabel. Format: projects/{project}/locations/{location}/conversations/{conversation}/feedbackLabels/{feedback_label}
"qaAnswerLabel": { # Message for holding the value of a QaAnswer. QaQuestion.AnswerChoice defines the possible answer values for a question. # QaAnswer label used for Quality AI example conversations.
"boolValue": True or False, # Boolean value.
"key": "A String", # A short string used as an identifier. Matches the value used in QaQuestion.AnswerChoice.key.
"naValue": True or False, # A value of "Not Applicable (N/A)". Should only ever be `true`.
"normalizedScore": 3.14, # Output only. Normalized score of the questions. Calculated as score / potential_score.
"numValue": 3.14, # Numerical value.
"potentialScore": 3.14, # Output only. The maximum potential score of the question.
"score": 3.14, # Output only. Numerical score of the answer.
"skipValue": True or False, # Output only. A value of "Skip". If provided, this field may only be set to `true`. If a question receives this answer, it will be excluded from any score calculations. This would mean that the question was not evaluated.
"strValue": "A String", # String value.
},
"updateTime": "A String", # Output only. Update time of the label.
},
],
"nextPageToken": "A String", # A token, which can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no subsequent pages.
}
listAllFeedbackLabels_next()
Retrieves the next page of results.
Args:
previous_request: The request for the previous page. (required)
previous_response: The response from the request for the previous page. (required)
Returns:
A request object that you can call 'execute()' on to request the next
page. Returns None if there are no more items in the collection.
queryMetrics(location, body=None, x__xgafv=None)
Query metrics.
Args:
location: string, Required. The location of the data. "projects/{project}/locations/{location}" (required)
body: object, The request body.
The object takes the form of:
{ # The request for querying metrics.
"dimensions": [ # The dimensions that determine the grouping key for the query. Defaults to no dimension if this field is unspecified. If a dimension is specified, its key must also be specified. Each dimension's key must be unique. If a time granularity is also specified, metric values in the dimension will be bucketed by this granularity. Up to one dimension is supported for now.
{ # A dimension determines the grouping key for the query. In SQL terms, these would be part of both the "SELECT" and "GROUP BY" clauses.
"agentDimensionMetadata": { # Metadata about the agent dimension. # Output only. Metadata about the agent dimension.
"agentDeploymentDisplayName": "A String", # Optional. The agent's deployment display name. Only applicable to automated agents. This will be populated for AGENT_DEPLOYMENT_ID dimensions.
"agentDeploymentId": "A String", # Optional. The agent's deployment ID. Only applicable to automated agents. This will be populated for AGENT and AGENT_DEPLOYMENT_ID dimensions.
"agentDisplayName": "A String", # Optional. The agent's name This will be populated for AGENT, AGENT_TEAM, AGENT_VERSION_ID, and AGENT_DEPLOYMENT_ID dimensions.
"agentId": "A String", # Optional. A user-specified string representing the agent. This will be populated for AGENT, AGENT_TEAM, AGENT_VERSION_ID, and AGENT_DEPLOYMENT_ID dimensions.
"agentTeam": "A String", # Optional. A user-specified string representing the agent's team.
"agentVersionDisplayName": "A String", # Optional. The agent's version display name. Only applicable to automated agents. This will be populated for AGENT_VERSION_ID, and AGENT_DEPLOYMENT_ID dimensions.
"agentVersionId": "A String", # Optional. The agent's version ID. Only applicable to automated agents. This will be populated for AGENT_VERSION_ID, and AGENT_DEPLOYMENT_ID dimensions.
},
"clientSentimentCategoryDimensionMetadata": { # Metadata about the client sentiment category dimension. # Output only. Metadata about the client sentiment category dimension.
"sentimentCategory": "A String", # Optional. The client sentiment category.
},
"conversationProfileDimensionMetadata": { # Metadata about the conversation profile dimension. # Output only. Metadata about the conversation profile dimension.
"conversationProfileId": "A String", # Optional. The conversation profile ID.
},
"conversationalAgentsPlaybookDimensionMetadata": { # Metadata about the Conversational Agents playbook dimension. # Output only. Metadata about the Conversational Agents playbook dimension.
"playbookDisplayName": "A String", # Optional. The dialogflow playbook display name.
"playbookId": "A String", # Optional. The dialogflow playbook ID.
},
"conversationalAgentsToolDimensionMetadata": { # Metadata about the Conversational Agents tool dimension. # Output only. Metadata about the Conversational Agents tool dimension.
"toolDisplayName": "A String", # Optional. The dialogflow tool display name.
"toolId": "A String", # Optional. The dialogflow tool ID.
},
"dimensionKey": "A String", # The key of the dimension.
"issueDimensionMetadata": { # Metadata about the issue dimension. # Output only. Metadata about the issue dimension.
"issueDisplayName": "A String", # The issue display name.
"issueId": "A String", # The issue ID.
"issueModelId": "A String", # The parent issue model ID.
},
"labelDimensionMetadata": { # Metadata about conversation labels. # Output only. Metadata about conversation labels.
"labelKey": "A String", # Optional. The label key.
"labelValue": "A String", # Optional. The label value.
},
"mediumDimensionMetadata": { # Metadata about the conversation medium dimension. # Output only. Metadata about the conversation medium dimension.
"medium": "A String", # Optional. The conversation medium. Currently supports : PHONE_CALL, CHAT.
},
"qaQuestionAnswerDimensionMetadata": { # Metadata about the QA question-answer dimension. This is useful for showing the answer distribution for questions for a given scorecard. # Output only. Metadata about the QA question-answer dimension.
"answerValue": "A String", # Optional. The full body of the question.
"qaQuestionId": "A String", # Optional. The QA question ID.
"qaScorecardId": "A String", # Optional. The QA scorecard ID.
"questionBody": "A String", # Optional. The full body of the question.
},
"qaQuestionDimensionMetadata": { # Metadata about the QA question dimension. # Output only. Metadata about the QA question dimension.
"qaQuestionId": "A String", # Optional. The QA question ID.
"qaScorecardId": "A String", # Optional. The QA scorecard ID.
"questionBody": "A String", # Optional. The full body of the question.
},
"qaScorecardDimensionMetadata": { # Metadata about the QA scorecard dimension. # Output only. Metadata about the QA scorecard dimension.
"qaScorecardId": "A String", # Optional. The QA scorecard ID.
},
},
],
"filter": "A String", # Required. Filter to select a subset of conversations to compute the metrics. Must specify a window of the conversation create time to compute the metrics. The returned metrics will be from the range [DATE(starting create time), DATE(ending create time)).
"measureMask": "A String", # Measures to return. Defaults to all measures if this field is unspecified. A valid mask should traverse from the `measure` field from the response. For example, a path from a measure mask to get the conversation count is "conversation_measure.count".
"timeGranularity": "A String", # The time granularity of each data point in the time series. Defaults to NONE if this field is unspecified.
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # 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": { # 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](https://github.com/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](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A 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.
},
"metadata": { # 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.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A 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": { # The normal, successful response of the operation. 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`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}
queryPerformanceOverview(parent, body=None, x__xgafv=None)
Generates a summary of predefined performance metrics for a set of conversations. Conversations can be specified by specifying a time window and an agent id, for now. The summary includes a comparison of metrics computed for conversations in the previous time period, and also a comparison with peers in the same time period.
Args:
parent: string, Required. The parent resource of the conversations to derive performance stats from. "projects/{project}/locations/{location}" (required)
body: object, The request body.
The object takes the form of:
{ # The request for summarizing performance according to different metrics for conversations over a specified time window.
"agentPerformanceSource": { # The entity whose performance is being queried is a single agent. # Conversations are from a single agent.
"agentId": "A String", # Required. Agent id to query performance overview for.
},
"comparisonQueryInterval": { # A time window for querying conversations. # The time window of the conversations to compare the performance to.
"endTime": "A String", # Required. The end time of the time window.
"startTime": "A String", # Required. The start time of the time window.
},
"filter": "A String", # Optional. Filter to select a subset of conversations to compute the performance overview. Supports the same filters as the filter field in QueryMetricsRequest. The source and query interval/comparison query interval should not be included here.
"queryInterval": { # A time window for querying conversations. # Required. The time window of the conversations to derive performance stats from.
"endTime": "A String", # Required. The end time of the time window.
"startTime": "A String", # Required. The start time of the time window.
},
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # 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": { # 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](https://github.com/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](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A 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.
},
"metadata": { # 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.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A 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": { # The normal, successful response of the operation. 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`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}
testCorrelationConfig(location, body=None, x__xgafv=None)
Tests correlation config on a conversation.
Args:
location: string, Required. The location to test correlation config. Format: projects/{project}/locations/{location} (required)
body: object, The request body.
The object takes the form of:
{ # The request to test correlation config.
"conversations": { # Wrapper for a list of conversations. # Optional. A list of conversations to test against.
"conversations": [ # Optional. The conversations.
{ # The conversation resource.
"agentId": "A String", # An opaque, user-specified string representing the human agent who handled the conversation.
"callMetadata": { # Call-specific metadata. # Call-specific metadata.
"agentChannel": 42, # The audio channel that contains the agent.
"customerChannel": 42, # The audio channel that contains the customer.
},
"correlationInfo": { # Info for correlating across conversations. # Output only. Info for correlating across conversations.
"correlationTypes": [ # Output only. The correlation types of this conversation. A single conversation can have multiple correlation types. For example a conversation that only has a single segment is both a SEGMENT and a FULL_CONVERSATION.
"A String",
],
"fullConversationCorrelationId": "A String", # Output only. The full conversation correlation id this conversation is a segment of.
"mergedFullConversationCorrelationId": "A String", # Output only. The full conversation correlation id this conversation is a merged conversation of.
},
"createTime": "A String", # Output only. The time at which the conversation was created.
"dataSource": { # The conversation source, which is a combination of transcript and audio. # The source of the audio and transcription for the conversation.
"dialogflowSource": { # A Dialogflow source of conversation data. # The source when the conversation comes from Dialogflow.
"audioUri": "A String", # Cloud Storage URI that points to a file that contains the conversation audio.
"dialogflowConversation": "A String", # Output only. The name of the Dialogflow conversation that this conversation resource is derived from. Format: projects/{project}/locations/{location}/conversations/{conversation}
},
"gcsSource": { # A Cloud Storage source of conversation data. # A Cloud Storage location specification for the audio and transcript.
"audioUri": "A String", # Cloud Storage URI that points to a file that contains the conversation audio.
"transcriptUri": "A String", # Immutable. Cloud Storage URI that points to a file that contains the conversation transcript.
},
"metadataUri": "A String", # Cloud Storage URI that points to a file that contains the conversation metadata.
},
"dialogflowIntents": { # Output only. All the matched Dialogflow intents in the call. The key corresponds to a Dialogflow intent, format: projects/{project}/agent/{agent}/intents/{intent}
"a_key": { # The data for a Dialogflow intent. Represents a detected intent in the conversation, e.g. MAKES_PROMISE.
"displayName": "A String", # The human-readable name of the intent.
},
},
"duration": "A String", # Output only. The duration of the conversation.
"expireTime": "A String", # The time at which this conversation should expire. After this time, the conversation data and any associated analyses will be deleted.
"labels": { # A map for the user to specify any custom fields. A maximum of 100 labels per conversation is allowed, with a maximum of 256 characters per entry.
"a_key": "A String",
},
"languageCode": "A String", # A user-specified language code for the conversation.
"latestAnalysis": { # The analysis resource. # Output only. The conversation's latest analysis, if one exists.
"analysisResult": { # The result of an analysis. # Output only. The result of the analysis, which is populated when the analysis finishes.
"callAnalysisMetadata": { # Call-specific metadata created during analysis. # Call-specific metadata created by the analysis.
"annotations": [ # A list of call annotations that apply to this call.
{ # A piece of metadata that applies to a window of a call.
"annotationEndBoundary": { # A point in a conversation that marks the start or the end of an annotation. # The boundary in the conversation where the annotation ends, inclusive.
"transcriptIndex": 42, # The index in the sequence of transcribed pieces of the conversation where the boundary is located. This index starts at zero.
"wordIndex": 42, # The word index of this boundary with respect to the first word in the transcript piece. This index starts at zero.
},
"annotationStartBoundary": { # A point in a conversation that marks the start or the end of an annotation. # The boundary in the conversation where the annotation starts, inclusive.
"transcriptIndex": 42, # The index in the sequence of transcribed pieces of the conversation where the boundary is located. This index starts at zero.
"wordIndex": 42, # The word index of this boundary with respect to the first word in the transcript piece. This index starts at zero.
},
"channelTag": 42, # The channel of the audio where the annotation occurs. For single-channel audio, this field is not populated.
"entityMentionData": { # The data for an entity mention annotation. This represents a mention of an `Entity` in the conversation. # Data specifying an entity mention.
"entityUniqueId": "A String", # The key of this entity in conversation entities. Can be used to retrieve the exact `Entity` this mention is attached to.
"sentiment": { # The data for a sentiment annotation. # Sentiment expressed for this mention of the entity.
"magnitude": 3.14, # A non-negative number from 0 to infinity which represents the absolute magnitude of sentiment regardless of score.
"score": 3.14, # The sentiment score between -1.0 (negative) and 1.0 (positive).
},
"type": "A String", # The type of the entity mention.
},
"holdData": { # The data for a hold annotation. # Data specifying a hold.
},
"intentMatchData": { # The data for an intent match. Represents an intent match for a text segment in the conversation. A text segment can be part of a sentence, a complete sentence, or an utterance with multiple sentences. # Data specifying an intent match.
"intentUniqueId": "A String", # The id of the matched intent. Can be used to retrieve the corresponding intent information.
},
"interruptionData": { # The data for an interruption annotation. # Data specifying an interruption.
},
"issueMatchData": { # The data for an issue match annotation. # Data specifying an issue match.
"issueAssignment": { # Information about the issue. # Information about the issue's assignment.
"displayName": "A String", # Immutable. Display name of the assigned issue. This field is set at time of analysis and immutable since then.
"issue": "A String", # Resource name of the assigned issue.
"score": 3.14, # Score indicating the likelihood of the issue assignment. currently bounded on [0,1].
},
},
"phraseMatchData": { # The data for a matched phrase matcher. Represents information identifying a phrase matcher for a given match. # Data specifying a phrase match.
"displayName": "A String", # The human-readable name of the phrase matcher.
"phraseMatcher": "A String", # The unique identifier (the resource name) of the phrase matcher.
},
"sentimentData": { # The data for a sentiment annotation. # Data specifying sentiment.
"magnitude": 3.14, # A non-negative number from 0 to infinity which represents the absolute magnitude of sentiment regardless of score.
"score": 3.14, # The sentiment score between -1.0 (negative) and 1.0 (positive).
},
"silenceData": { # The data for a silence annotation. # Data specifying silence.
},
},
],
"entities": { # All the entities in the call.
"a_key": { # The data for an entity annotation. Represents a phrase in the conversation that is a known entity, such as a person, an organization, or location.
"displayName": "A String", # The representative name for the entity.
"metadata": { # Metadata associated with the entity. For most entity types, the metadata is a Wikipedia URL (`wikipedia_url`) and Knowledge Graph MID (`mid`), if they are available. For the metadata associated with other entity types, see the Type table below.
"a_key": "A String",
},
"salience": 3.14, # The salience score associated with the entity in the [0, 1.0] range. The salience score for an entity provides information about the importance or centrality of that entity to the entire document text. Scores closer to 0 are less salient, while scores closer to 1.0 are highly salient.
"sentiment": { # The data for a sentiment annotation. # The aggregate sentiment expressed for this entity in the conversation.
"magnitude": 3.14, # A non-negative number from 0 to infinity which represents the absolute magnitude of sentiment regardless of score.
"score": 3.14, # The sentiment score between -1.0 (negative) and 1.0 (positive).
},
"type": "A String", # The entity type.
},
},
"intents": { # All the matched intents in the call.
"a_key": { # The data for an intent. Represents a detected intent in the conversation, for example MAKES_PROMISE.
"displayName": "A String", # The human-readable name of the intent.
"id": "A String", # The unique identifier of the intent.
},
},
"issueModelResult": { # Issue Modeling result on a conversation. # Overall conversation-level issue modeling result.
"issueModel": "A String", # Issue model that generates the result. Format: projects/{project}/locations/{location}/issueModels/{issue_model}
"issues": [ # All the matched issues.
{ # Information about the issue.
"displayName": "A String", # Immutable. Display name of the assigned issue. This field is set at time of analysis and immutable since then.
"issue": "A String", # Resource name of the assigned issue.
"score": 3.14, # Score indicating the likelihood of the issue assignment. currently bounded on [0,1].
},
],
},
"phraseMatchers": { # All the matched phrase matchers in the call.
"a_key": { # The data for a matched phrase matcher. Represents information identifying a phrase matcher for a given match.
"displayName": "A String", # The human-readable name of the phrase matcher.
"phraseMatcher": "A String", # The unique identifier (the resource name) of the phrase matcher.
},
},
"qaScorecardResults": [ # Results of scoring QaScorecards.
{ # The results of scoring a single conversation against a QaScorecard. Contains a collection of QaAnswers and aggregate score.
"agentId": "A String", # ID of the agent that handled the conversation.
"conversation": "A String", # The conversation scored by this result.
"createTime": "A String", # Output only. The timestamp that the revision was created.
"name": "A String", # Identifier. The name of the scorecard result. Format: projects/{project}/locations/{location}/qaScorecardResults/{qa_scorecard_result}
"normalizedScore": 3.14, # The normalized score, which is the score divided by the potential score. Any manual edits are included if they exist.
"potentialScore": 3.14, # The maximum potential overall score of the scorecard. Any questions answered using `na_value` are excluded from this calculation.
"qaAnswers": [ # Set of QaAnswers represented in the result.
{ # An answer to a QaQuestion.
"answerSources": [ # Lists all answer sources containing one or more answer values of a specific source type, e.g., all system-generated answer sources, or all manual edit answer sources.
{ # A question may have multiple answers from varying sources, one of which becomes the "main" answer above. AnswerSource represents each individual answer.
"answerValue": { # Message for holding the value of a QaAnswer. QaQuestion.AnswerChoice defines the possible answer values for a question. # The answer value from this source. This field is populated by default, unless the question has a selection strategy configured to return multiple answer values, in which case `answer_values` will be populated instead.
"boolValue": True or False, # Boolean value.
"key": "A String", # A short string used as an identifier. Matches the value used in QaQuestion.AnswerChoice.key.
"naValue": True or False, # A value of "Not Applicable (N/A)". Should only ever be `true`.
"normalizedScore": 3.14, # Output only. Normalized score of the questions. Calculated as score / potential_score.
"numValue": 3.14, # Numerical value.
"potentialScore": 3.14, # Output only. The maximum potential score of the question.
"score": 3.14, # Output only. Numerical score of the answer.
"skipValue": True or False, # Output only. A value of "Skip". If provided, this field may only be set to `true`. If a question receives this answer, it will be excluded from any score calculations. This would mean that the question was not evaluated.
"strValue": "A String", # String value.
},
"sourceType": "A String", # What created the answer.
},
],
"answerValue": { # Message for holding the value of a QaAnswer. QaQuestion.AnswerChoice defines the possible answer values for a question. # The answer value from this source. This field is populated by default, unless the question has a selection strategy configured to return multiple answer values, in which case `answer_values` will be populated instead.
"boolValue": True or False, # Boolean value.
"key": "A String", # A short string used as an identifier. Matches the value used in QaQuestion.AnswerChoice.key.
"naValue": True or False, # A value of "Not Applicable (N/A)". Should only ever be `true`.
"normalizedScore": 3.14, # Output only. Normalized score of the questions. Calculated as score / potential_score.
"numValue": 3.14, # Numerical value.
"potentialScore": 3.14, # Output only. The maximum potential score of the question.
"score": 3.14, # Output only. Numerical score of the answer.
"skipValue": True or False, # Output only. A value of "Skip". If provided, this field may only be set to `true`. If a question receives this answer, it will be excluded from any score calculations. This would mean that the question was not evaluated.
"strValue": "A String", # String value.
},
"conversation": "A String", # The conversation the answer applies to.
"qaQuestion": "A String", # The QaQuestion answered by this answer.
"questionBody": "A String", # Question text. E.g., "Did the agent greet the customer?"
"tags": [ # User-defined list of arbitrary tags. Matches the value from QaScorecard.ScorecardQuestion.tags. Used for grouping/organization and for weighting the score of each answer.
"A String",
],
},
],
"qaScorecardRevision": "A String", # The QaScorecardRevision scored by this result.
"qaTagResults": [ # Collection of tags and their scores.
{ # Tags and their corresponding results.
"normalizedScore": 3.14, # The normalized score the tag applies to.
"potentialScore": 3.14, # The potential score the tag applies to.
"score": 3.14, # The score the tag applies to.
"tag": "A String", # The tag the score applies to.
},
],
"score": 3.14, # The overall numerical score of the result, incorporating any manual edits if they exist.
"scoreSources": [ # List of all individual score sets.
{ # A scorecard result may have multiple sets of scores from varying sources, one of which becomes the "main" answer above. A ScoreSource represents each individual set of scores.
"normalizedScore": 3.14, # The normalized score, which is the score divided by the potential score.
"potentialScore": 3.14, # The maximum potential overall score of the scorecard. Any questions answered using `na_value` are excluded from this calculation.
"qaTagResults": [ # Collection of tags and their scores.
{ # Tags and their corresponding results.
"normalizedScore": 3.14, # The normalized score the tag applies to.
"potentialScore": 3.14, # The potential score the tag applies to.
"score": 3.14, # The score the tag applies to.
"tag": "A String", # The tag the score applies to.
},
],
"score": 3.14, # The overall numerical score of the result.
"sourceType": "A String", # What created the score.
},
],
},
],
"sentiments": [ # Overall conversation-level sentiment for each channel of the call.
{ # One channel of conversation-level sentiment data.
"channelTag": 42, # The channel of the audio that the data applies to.
"sentimentData": { # The data for a sentiment annotation. # Data specifying sentiment.
"magnitude": 3.14, # A non-negative number from 0 to infinity which represents the absolute magnitude of sentiment regardless of score.
"score": 3.14, # The sentiment score between -1.0 (negative) and 1.0 (positive).
},
},
],
"silence": { # Conversation-level silence data. # Overall conversation-level silence during the call.
"silenceDuration": "A String", # Amount of time calculated to be in silence.
"silencePercentage": 3.14, # Percentage of the total conversation spent in silence.
},
},
"endTime": "A String", # The time at which the analysis ended.
},
"annotatorSelector": { # Selector of all available annotators and phrase matchers to run. # To select the annotators to run and the phrase matchers to use (if any). If not specified, all annotators will be run.
"issueModels": [ # The issue model to run. If not provided, the most recently deployed topic model will be used. The provided issue model will only be used for inference if the issue model is deployed and if run_issue_model_annotator is set to true. If more than one issue model is provided, only the first provided issue model will be used for inference.
"A String",
],
"phraseMatchers": [ # The list of phrase matchers to run. If not provided, all active phrase matchers will be used. If inactive phrase matchers are provided, they will not be used. Phrase matchers will be run only if run_phrase_matcher_annotator is set to true. Format: projects/{project}/locations/{location}/phraseMatchers/{phrase_matcher}
"A String",
],
"qaConfig": { # Configuration for the QA feature. # Configuration for the QA annotator.
"scorecardList": { # Container for a list of scorecards. # A manual list of scorecards to score.
"qaScorecardRevisions": [ # List of QaScorecardRevisions.
"A String",
],
},
},
"runEntityAnnotator": True or False, # Whether to run the entity annotator.
"runIntentAnnotator": True or False, # Whether to run the intent annotator.
"runInterruptionAnnotator": True or False, # Whether to run the interruption annotator.
"runIssueModelAnnotator": True or False, # Whether to run the issue model annotator. A model should have already been deployed for this to take effect.
"runPhraseMatcherAnnotator": True or False, # Whether to run the active phrase matcher annotator(s).
"runQaAnnotator": True or False, # Whether to run the QA annotator.
"runSentimentAnnotator": True or False, # Whether to run the sentiment annotator.
"runSilenceAnnotator": True or False, # Whether to run the silence annotator.
"runSummarizationAnnotator": True or False, # Whether to run the summarization annotator.
"summarizationConfig": { # Configuration for summarization. # Configuration for the summarization annotator.
"conversationProfile": "A String", # Resource name of the Dialogflow conversation profile. Format: projects/{project}/locations/{location}/conversationProfiles/{conversation_profile}
"generator": "A String", # The resource name of the existing created generator. Format: projects//locations//generators/
"summarizationModel": "A String", # Default summarization model to be used.
},
},
"createTime": "A String", # Output only. The time at which the analysis was created, which occurs when the long-running operation completes.
"name": "A String", # Immutable. The resource name of the analysis. Format: projects/{project}/locations/{location}/conversations/{conversation}/analyses/{analysis}
"requestTime": "A String", # Output only. The time at which the analysis was requested.
},
"latestSummary": { # Conversation summarization suggestion data. # Output only. Latest summary of the conversation.
"answerRecord": "A String", # The name of the answer record. Format: projects/{project}/locations/{location}/answerRecords/{answer_record}
"confidence": 3.14, # The confidence score of the summarization.
"conversationModel": "A String", # The name of the model that generates this summary. Format: projects/{project}/locations/{location}/conversationModels/{conversation_model}
"generatorId": "A String", # Agent Assist generator ID.
"metadata": { # A map that contains metadata about the summarization and the document from which it originates.
"a_key": "A String",
},
"text": "A String", # The summarization content that is concatenated into one string.
"textSections": { # The summarization content that is divided into sections. The key is the section's name and the value is the section's content. There is no specific format for the key or value.
"a_key": "A String",
},
},
"medium": "A String", # Immutable. The conversation medium.
"metadataJson": "A String", # Input only. JSON metadata encoded as a string. This field is primarily used by Insights integrations with various telephony systems and must be in one of Insight's supported formats.
"name": "A String", # Immutable. The resource name of the conversation. Format: projects/{project}/locations/{location}/conversations/{conversation}
"obfuscatedUserId": "A String", # Obfuscated user ID which the customer sent to us.
"qualityMetadata": { # Conversation metadata related to quality management. # Conversation metadata related to quality management.
"agentInfo": [ # Information about agents involved in the call.
{ # Information about an agent involved in the conversation.
"agentId": "A String", # A user-specified string representing the agent.
"agentType": "A String", # The agent type, e.g. HUMAN_AGENT.
"deploymentDisplayName": "A String", # The agent's deployment display name. Only applicable to automated agents.
"deploymentId": "A String", # The agent's deployment ID. Only applicable to automated agents.
"displayName": "A String", # The agent's name.
"dispositionCode": "A String", # A user-provided string indicating the outcome of the agent's segment of the call.
"location": "A String", # The agent's location.
"team": "A String", # A user-specified string representing the agent's team. Deprecated in favor of the `teams` field.
"teams": [ # User-specified strings representing the agent's teams.
"A String",
],
"versionDisplayName": "A String", # The agent's version display name. Only applicable to automated agents.
"versionId": "A String", # The agent's version ID. Only applicable to automated agents.
},
],
"customerSatisfactionRating": 42, # An arbitrary integer value indicating the customer's satisfaction rating.
"feedbackLabels": [ # Input only. The feedback labels associated with the conversation.
{ # Represents a conversation, resource, and label provided by the user. Can take the form of a string label or a QaAnswer label. QaAnswer labels are used for Quality AI example conversations. String labels are used for Topic Modeling. AgentAssistSummary labels are used for Agent Assist Summarization.
"createTime": "A String", # Output only. Create time of the label.
"label": "A String", # String label used for Topic Modeling.
"labeledResource": "A String", # Name of the resource to be labeled. Supported resources are: * `projects/{project}/locations/{location}/qaScorecards/{scorecard}/revisions/{revision}/qaQuestions/{question}` * `projects/{project}/locations/{location}/issueModels/{issue_model}` * `projects/{project}/locations/{location}/generators/{generator_id}`
"name": "A String", # Immutable. Resource name of the FeedbackLabel. Format: projects/{project}/locations/{location}/conversations/{conversation}/feedbackLabels/{feedback_label}
"qaAnswerLabel": { # Message for holding the value of a QaAnswer. QaQuestion.AnswerChoice defines the possible answer values for a question. # QaAnswer label used for Quality AI example conversations.
"boolValue": True or False, # Boolean value.
"key": "A String", # A short string used as an identifier. Matches the value used in QaQuestion.AnswerChoice.key.
"naValue": True or False, # A value of "Not Applicable (N/A)". Should only ever be `true`.
"normalizedScore": 3.14, # Output only. Normalized score of the questions. Calculated as score / potential_score.
"numValue": 3.14, # Numerical value.
"potentialScore": 3.14, # Output only. The maximum potential score of the question.
"score": 3.14, # Output only. Numerical score of the answer.
"skipValue": True or False, # Output only. A value of "Skip". If provided, this field may only be set to `true`. If a question receives this answer, it will be excluded from any score calculations. This would mean that the question was not evaluated.
"strValue": "A String", # String value.
},
"updateTime": "A String", # Output only. Update time of the label.
},
],
"menuPath": "A String", # An arbitrary string value specifying the menu path the customer took.
"waitDuration": "A String", # The amount of time the customer waited to connect with an agent.
},
"runtimeAnnotations": [ # Output only. The annotations that were generated during the customer and agent interaction.
{ # An annotation that was generated during the customer and agent interaction.
"annotationId": "A String", # The unique identifier of the annotation. Format: projects/{project}/locations/{location}/conversationDatasets/{dataset}/conversationDataItems/{data_item}/conversationAnnotations/{annotation}
"answerFeedback": { # The feedback that the customer has about a certain answer in the conversation. # The feedback that the customer has about the answer in `data`.
"clicked": True or False, # Indicates whether an answer or item was clicked by the human agent.
"correctnessLevel": "A String", # The correctness level of an answer.
"displayed": True or False, # Indicates whether an answer or item was displayed to the human agent in the agent desktop UI.
},
"articleSuggestion": { # Agent Assist Article Suggestion data. # Agent Assist Article Suggestion data.
"confidenceScore": 3.14, # The system's confidence score that this article is a good match for this conversation, ranging from 0.0 (completely uncertain) to 1.0 (completely certain).
"metadata": { # Map that contains metadata about the Article Suggestion and the document that it originates from.
"a_key": "A String",
},
"queryRecord": "A String", # The name of the answer record. Format: projects/{project}/locations/{location}/answerRecords/{answer_record}
"source": "A String", # The knowledge document that this answer was extracted from. Format: projects/{project}/knowledgeBases/{knowledge_base}/documents/{document}
"title": "A String", # Article title.
"uri": "A String", # Article URI.
},
"conversationSummarizationSuggestion": { # Conversation summarization suggestion data. # Conversation summarization suggestion data.
"answerRecord": "A String", # The name of the answer record. Format: projects/{project}/locations/{location}/answerRecords/{answer_record}
"confidence": 3.14, # The confidence score of the summarization.
"conversationModel": "A String", # The name of the model that generates this summary. Format: projects/{project}/locations/{location}/conversationModels/{conversation_model}
"generatorId": "A String", # Agent Assist generator ID.
"metadata": { # A map that contains metadata about the summarization and the document from which it originates.
"a_key": "A String",
},
"text": "A String", # The summarization content that is concatenated into one string.
"textSections": { # The summarization content that is divided into sections. The key is the section's name and the value is the section's content. There is no specific format for the key or value.
"a_key": "A String",
},
},
"createTime": "A String", # The time at which this annotation was created.
"dialogflowInteraction": { # Dialogflow interaction data. # Dialogflow interaction data.
"confidence": 3.14, # The confidence of the match ranging from 0.0 (completely uncertain) to 1.0 (completely certain).
"dialogflowIntentId": "A String", # The Dialogflow intent resource path. Format: projects/{project}/agent/{agent}/intents/{intent}
},
"endBoundary": { # A point in a conversation that marks the start or the end of an annotation. # The boundary in the conversation where the annotation ends, inclusive.
"transcriptIndex": 42, # The index in the sequence of transcribed pieces of the conversation where the boundary is located. This index starts at zero.
"wordIndex": 42, # The word index of this boundary with respect to the first word in the transcript piece. This index starts at zero.
},
"faqAnswer": { # Agent Assist frequently-asked-question answer data. # Agent Assist FAQ answer data.
"answer": "A String", # The piece of text from the `source` knowledge base document.
"confidenceScore": 3.14, # The system's confidence score that this answer is a good match for this conversation, ranging from 0.0 (completely uncertain) to 1.0 (completely certain).
"metadata": { # Map that contains metadata about the FAQ answer and the document that it originates from.
"a_key": "A String",
},
"queryRecord": "A String", # The name of the answer record. Format: projects/{project}/locations/{location}/answerRecords/{answer_record}
"question": "A String", # The corresponding FAQ question.
"source": "A String", # The knowledge document that this answer was extracted from. Format: projects/{project}/knowledgeBases/{knowledge_base}/documents/{document}.
},
"smartComposeSuggestion": { # Agent Assist Smart Compose suggestion data. # Agent Assist Smart Compose suggestion data.
"confidenceScore": 3.14, # The system's confidence score that this suggestion is a good match for this conversation, ranging from 0.0 (completely uncertain) to 1.0 (completely certain).
"metadata": { # Map that contains metadata about the Smart Compose suggestion and the document from which it originates.
"a_key": "A String",
},
"queryRecord": "A String", # The name of the answer record. Format: projects/{project}/locations/{location}/answerRecords/{answer_record}
"suggestion": "A String", # The content of the suggestion.
},
"smartReply": { # Agent Assist Smart Reply data. # Agent Assist Smart Reply data.
"confidenceScore": 3.14, # The system's confidence score that this reply is a good match for this conversation, ranging from 0.0 (completely uncertain) to 1.0 (completely certain).
"metadata": { # Map that contains metadata about the Smart Reply and the document from which it originates.
"a_key": "A String",
},
"queryRecord": "A String", # The name of the answer record. Format: projects/{project}/locations/{location}/answerRecords/{answer_record}
"reply": "A String", # The content of the reply.
},
"startBoundary": { # A point in a conversation that marks the start or the end of an annotation. # The boundary in the conversation where the annotation starts, inclusive.
"transcriptIndex": 42, # The index in the sequence of transcribed pieces of the conversation where the boundary is located. This index starts at zero.
"wordIndex": 42, # The word index of this boundary with respect to the first word in the transcript piece. This index starts at zero.
},
"userInput": { # Explicit input used for generating the answer # Explicit input used for generating the answer
"generatorName": "A String", # The resource name of associated generator. Format: `projects//locations//generators/`
"query": "A String", # Query text. Article Search uses this to store the input query used to generate the search results.
"querySource": "A String", # Query source for the answer.
},
},
],
"startTime": "A String", # The time at which the conversation started.
"transcript": { # A message representing the transcript of a conversation. # Output only. The conversation transcript.
"transcriptSegments": [ # A list of sequential transcript segments that comprise the conversation.
{ # A segment of a full transcript.
"channelTag": 42, # For conversations derived from multi-channel audio, this is the channel number corresponding to the audio from that channel. For audioChannelCount = N, its output values can range from '1' to 'N'. A channel tag of 0 indicates that the audio is mono.
"confidence": 3.14, # A confidence estimate between 0.0 and 1.0 of the fidelity of this segment. A default value of 0.0 indicates that the value is unset.
"dialogflowSegmentMetadata": { # Metadata from Dialogflow relating to the current transcript segment. # CCAI metadata relating to the current transcript segment.
"smartReplyAllowlistCovered": True or False, # Whether the transcript segment was covered under the configured smart reply allowlist in Agent Assist.
},
"languageCode": "A String", # The language code of this segment as a [BCP-47](https://www.rfc-editor.org/rfc/bcp/bcp47.txt) language tag. Example: "en-US".
"messageTime": "A String", # The time that the message occurred, if provided.
"segmentParticipant": { # The call participant speaking for a given utterance. # The participant of this segment.
"dialogflowParticipant": "A String", # Deprecated. Use `dialogflow_participant_name` instead. The name of the Dialogflow participant. Format: projects/{project}/locations/{location}/conversations/{conversation}/participants/{participant}
"dialogflowParticipantName": "A String", # The name of the participant provided by Dialogflow. Format: projects/{project}/locations/{location}/conversations/{conversation}/participants/{participant}
"obfuscatedExternalUserId": "A String", # Obfuscated user ID from Dialogflow.
"role": "A String", # The role of the participant.
"userId": "A String", # A user-specified ID representing the participant.
},
"sentiment": { # The data for a sentiment annotation. # The sentiment for this transcript segment.
"magnitude": 3.14, # A non-negative number from 0 to infinity which represents the absolute magnitude of sentiment regardless of score.
"score": 3.14, # The sentiment score between -1.0 (negative) and 1.0 (positive).
},
"text": "A String", # The text of this segment.
"words": [ # A list of the word-specific information for each word in the segment.
{ # Word-level info for words in a transcript.
"confidence": 3.14, # A confidence estimate between 0.0 and 1.0 of the fidelity of this word. A default value of 0.0 indicates that the value is unset.
"endOffset": "A String", # Time offset of the end of this word relative to the beginning of the total conversation.
"startOffset": "A String", # Time offset of the start of this word relative to the beginning of the total conversation.
"word": "A String", # The word itself. Includes punctuation marks that surround the word.
},
],
},
],
},
"ttl": "A String", # Input only. The TTL for this resource. If specified, then this TTL will be used to calculate the expire time.
"turnCount": 42, # Output only. The number of turns in the conversation.
"updateTime": "A String", # Output only. The most recent time at which the conversation was updated.
},
],
},
"correlationConfig": { # A configuration that defines how to correlate conversations for a given a given project. # Required. The correlation config to test.
"createTime": "A String", # Output only. The time at which the correlation config was created.
"fullConversationConfig": { # A list of correlation rules for a given correlation type. # The correlation type config for full conversations.
"correlationRules": [ # A list of correlation rules to be evaluated for correlation.
{ # A correlation rule that defines how to join conversations for a given correlation type.
"active": True or False, # Optional. Whether the config is active to be evaluated.
"constraintExpression": "A String", # Optional. A cel expression (go/cel) to be evaluated as a boolean value. Two variables conversation_a and conversation_b will be available for evaluation. This expression should evaluate to true if conversation_a and conversation_b should be joined. This is used as an extra constraint on top of the join_key_expression to further refine the group of conversations that are joined together and will be evaluated in both directions. for two conversations c1 and c2 and the result will be OR'd. We will evaluate: f(c1, c2) OR f(c2, c1)
"joinKeyExpression": "A String", # Optional. A cel expression (go/cel) to be evaluated as a string value. This string value will be used as the join key for the correlation.
"ruleId": "A String", # Required. The unique identifier of the rule.
},
],
},
"name": "A String", # Immutable. Identifier. The resource name of the correlation config. Format: projects/{project}/locations/{location}/correlationConfig
"updateTime": "A String", # Output only. The time at which the correlation config was last updated.
},
"filter": "A String", # Optional. Filter to select conversations to test correlation against. Conversations matching this filter will be sampled based on start time. The most recent `max_sample_count` conversations will be selected. If no conversations match the filter, the request will fail with an `INVALID_ARGUMENT` error.
"maxSampleCount": 42, # Optional. The maximum number of conversations to sample when using the `filter`. If not set, defaults to 1000. Values greater than 1000 are coerced to 1000. This field is ignored if `conversations` is provided.
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # 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": { # 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](https://github.com/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](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A 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.
},
"metadata": { # 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.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A 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": { # The normal, successful response of the operation. 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`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}
updateCorrelationConfig(name, body=None, updateMask=None, x__xgafv=None)
Updates correlation config.
Args:
name: string, Immutable. Identifier. The resource name of the correlation config. Format: projects/{project}/locations/{location}/correlationConfig (required)
body: object, The request body.
The object takes the form of:
{ # A configuration that defines how to correlate conversations for a given a given project.
"createTime": "A String", # Output only. The time at which the correlation config was created.
"fullConversationConfig": { # A list of correlation rules for a given correlation type. # The correlation type config for full conversations.
"correlationRules": [ # A list of correlation rules to be evaluated for correlation.
{ # A correlation rule that defines how to join conversations for a given correlation type.
"active": True or False, # Optional. Whether the config is active to be evaluated.
"constraintExpression": "A String", # Optional. A cel expression (go/cel) to be evaluated as a boolean value. Two variables conversation_a and conversation_b will be available for evaluation. This expression should evaluate to true if conversation_a and conversation_b should be joined. This is used as an extra constraint on top of the join_key_expression to further refine the group of conversations that are joined together and will be evaluated in both directions. for two conversations c1 and c2 and the result will be OR'd. We will evaluate: f(c1, c2) OR f(c2, c1)
"joinKeyExpression": "A String", # Optional. A cel expression (go/cel) to be evaluated as a string value. This string value will be used as the join key for the correlation.
"ruleId": "A String", # Required. The unique identifier of the rule.
},
],
},
"name": "A String", # Immutable. Identifier. The resource name of the correlation config. Format: projects/{project}/locations/{location}/correlationConfig
"updateTime": "A String", # Output only. The time at which the correlation config was last updated.
}
updateMask: string, Optional. The list of fields to be updated.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # A configuration that defines how to correlate conversations for a given a given project.
"createTime": "A String", # Output only. The time at which the correlation config was created.
"fullConversationConfig": { # A list of correlation rules for a given correlation type. # The correlation type config for full conversations.
"correlationRules": [ # A list of correlation rules to be evaluated for correlation.
{ # A correlation rule that defines how to join conversations for a given correlation type.
"active": True or False, # Optional. Whether the config is active to be evaluated.
"constraintExpression": "A String", # Optional. A cel expression (go/cel) to be evaluated as a boolean value. Two variables conversation_a and conversation_b will be available for evaluation. This expression should evaluate to true if conversation_a and conversation_b should be joined. This is used as an extra constraint on top of the join_key_expression to further refine the group of conversations that are joined together and will be evaluated in both directions. for two conversations c1 and c2 and the result will be OR'd. We will evaluate: f(c1, c2) OR f(c2, c1)
"joinKeyExpression": "A String", # Optional. A cel expression (go/cel) to be evaluated as a string value. This string value will be used as the join key for the correlation.
"ruleId": "A String", # Required. The unique identifier of the rule.
},
],
},
"name": "A String", # Immutable. Identifier. The resource name of the correlation config. Format: projects/{project}/locations/{location}/correlationConfig
"updateTime": "A String", # Output only. The time at which the correlation config was last updated.
}
updateSettings(name, body=None, updateMask=None, x__xgafv=None)
Updates project-level settings.
Args:
name: string, Immutable. The resource name of the settings resource. Format: projects/{project}/locations/{location}/settings (required)
body: object, The request body.
The object takes the form of:
{ # The CCAI Insights project wide settings. Use these settings to configure the behavior of Insights. View these settings with [`getsettings`](https://cloud.google.com/contact-center/insights/docs/reference/rest/v1/projects.locations/getSettings) and change the settings with [`updateSettings`](https://cloud.google.com/contact-center/insights/docs/reference/rest/v1/projects.locations/updateSettings).
"analysisConfig": { # Default configuration when creating Analyses in Insights. # Default analysis settings.
"annotatorSelector": { # Selector of all available annotators and phrase matchers to run. # To select the annotators to run and the phrase matchers to use (if any). If not specified, all annotators will be run.
"issueModels": [ # The issue model to run. If not provided, the most recently deployed topic model will be used. The provided issue model will only be used for inference if the issue model is deployed and if run_issue_model_annotator is set to true. If more than one issue model is provided, only the first provided issue model will be used for inference.
"A String",
],
"phraseMatchers": [ # The list of phrase matchers to run. If not provided, all active phrase matchers will be used. If inactive phrase matchers are provided, they will not be used. Phrase matchers will be run only if run_phrase_matcher_annotator is set to true. Format: projects/{project}/locations/{location}/phraseMatchers/{phrase_matcher}
"A String",
],
"qaConfig": { # Configuration for the QA feature. # Configuration for the QA annotator.
"scorecardList": { # Container for a list of scorecards. # A manual list of scorecards to score.
"qaScorecardRevisions": [ # List of QaScorecardRevisions.
"A String",
],
},
},
"runEntityAnnotator": True or False, # Whether to run the entity annotator.
"runIntentAnnotator": True or False, # Whether to run the intent annotator.
"runInterruptionAnnotator": True or False, # Whether to run the interruption annotator.
"runIssueModelAnnotator": True or False, # Whether to run the issue model annotator. A model should have already been deployed for this to take effect.
"runPhraseMatcherAnnotator": True or False, # Whether to run the active phrase matcher annotator(s).
"runQaAnnotator": True or False, # Whether to run the QA annotator.
"runSentimentAnnotator": True or False, # Whether to run the sentiment annotator.
"runSilenceAnnotator": True or False, # Whether to run the silence annotator.
"runSummarizationAnnotator": True or False, # Whether to run the summarization annotator.
"summarizationConfig": { # Configuration for summarization. # Configuration for the summarization annotator.
"conversationProfile": "A String", # Resource name of the Dialogflow conversation profile. Format: projects/{project}/locations/{location}/conversationProfiles/{conversation_profile}
"generator": "A String", # The resource name of the existing created generator. Format: projects//locations//generators/
"summarizationModel": "A String", # Default summarization model to be used.
},
},
"runtimeIntegrationAnalysisPercentage": 3.14, # Percentage of conversations created using Dialogflow runtime integration to analyze automatically, between [0, 100].
"uploadConversationAnalysisPercentage": 3.14, # Percentage of conversations created using the UploadConversation endpoint to analyze automatically, between [0, 100].
},
"conversationTtl": "A String", # The default TTL for newly-created conversations. If a conversation has a specified expiration, that value will be used instead. Changing this value will not change the expiration of existing conversations. Conversations with no expire time persist until they are deleted.
"createTime": "A String", # Output only. The time at which the settings was created.
"languageCode": "A String", # A language code to be applied to each transcript segment unless the segment already specifies a language code. Language code defaults to "en-US" if it is neither specified on the segment nor here.
"name": "A String", # Immutable. The resource name of the settings resource. Format: projects/{project}/locations/{location}/settings
"pubsubNotificationSettings": { # A map that maps a notification trigger to a Pub/Sub topic. Each time a specified trigger occurs, Insights will notify the corresponding Pub/Sub topic. Keys are notification triggers. Supported keys are: * "all-triggers": Notify each time any of the supported triggers occurs. * "create-analysis": Notify each time an analysis is created. * "create-conversation": Notify each time a conversation is created. * "export-insights-data": Notify each time an export is complete. * "ingest-conversations": Notify each time an IngestConversations LRO is complete. * "update-conversation": Notify each time a conversation is updated via UpdateConversation. * "upload-conversation": Notify when an UploadConversation LRO is complete. * "update-or-analyze-conversation": Notify when an analysis for a conversation is completed or when the conversation is updated. The message will contain the conversation with transcript, analysis and other metadata. Values are Pub/Sub topics. The format of each Pub/Sub topic is: projects/{project}/topics/{topic}
"a_key": "A String",
},
"redactionConfig": { # DLP resources used for redaction while ingesting conversations. DLP settings are applied to conversations ingested from the `UploadConversation` and `IngestConversations` endpoints, including conversation coming from CCAI Platform. They are not applied to conversations ingested from the `CreateConversation` endpoint or the Dialogflow / Agent Assist runtime integrations. When using Dialogflow / Agent Assist runtime integrations, redaction should be performed in Dialogflow / Agent Assist. # Default DLP redaction resources to be applied while ingesting conversations. This applies to conversations ingested from the `UploadConversation` and `IngestConversations` endpoints, including conversations coming from CCAI Platform.
"deidentifyTemplate": "A String", # The fully-qualified DLP deidentify template resource name. Format: `projects/{project}/deidentifyTemplates/{template}`
"inspectTemplate": "A String", # The fully-qualified DLP inspect template resource name. Format: `projects/{project}/locations/{location}/inspectTemplates/{template}`
},
"screenRecordingBucketUri": "A String", # Optional. The path to a Cloud Storage bucket containing conversation screen recordings. If provided, Insights will search in the bucket for a screen recording file matching the conversation data source object name prefix. If matches are found, these file URIs will be stored in the conversation screen recordings field.
"speechConfig": { # Speech-to-Text configuration. Speech-to-Text settings are applied to conversations ingested from the `UploadConversation` and `IngestConversations` endpoints, including conversation coming from CCAI Platform. They are not applied to conversations ingested from the `CreateConversation` endpoint. # Optional. Default Speech-to-Text resources to use while ingesting audio files. Optional, CCAI Insights will create a default if not provided. This applies to conversations ingested from the `UploadConversation` and `IngestConversations` endpoints, including conversations coming from CCAI Platform.
"disableWordTimeOffsets": True or False, # Whether to disable word time offsets. If true, the `enable_word_time_offsets` field in the recognition config will be set to false.
"speechRecognizer": "A String", # The fully-qualified Speech Recognizer resource name. Format: `projects/{project_id}/locations/{location}/recognizer/{recognizer}`
},
"updateTime": "A String", # Output only. The time at which the settings were last updated.
}
updateMask: string, Required. The list of fields to be updated.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # The CCAI Insights project wide settings. Use these settings to configure the behavior of Insights. View these settings with [`getsettings`](https://cloud.google.com/contact-center/insights/docs/reference/rest/v1/projects.locations/getSettings) and change the settings with [`updateSettings`](https://cloud.google.com/contact-center/insights/docs/reference/rest/v1/projects.locations/updateSettings).
"analysisConfig": { # Default configuration when creating Analyses in Insights. # Default analysis settings.
"annotatorSelector": { # Selector of all available annotators and phrase matchers to run. # To select the annotators to run and the phrase matchers to use (if any). If not specified, all annotators will be run.
"issueModels": [ # The issue model to run. If not provided, the most recently deployed topic model will be used. The provided issue model will only be used for inference if the issue model is deployed and if run_issue_model_annotator is set to true. If more than one issue model is provided, only the first provided issue model will be used for inference.
"A String",
],
"phraseMatchers": [ # The list of phrase matchers to run. If not provided, all active phrase matchers will be used. If inactive phrase matchers are provided, they will not be used. Phrase matchers will be run only if run_phrase_matcher_annotator is set to true. Format: projects/{project}/locations/{location}/phraseMatchers/{phrase_matcher}
"A String",
],
"qaConfig": { # Configuration for the QA feature. # Configuration for the QA annotator.
"scorecardList": { # Container for a list of scorecards. # A manual list of scorecards to score.
"qaScorecardRevisions": [ # List of QaScorecardRevisions.
"A String",
],
},
},
"runEntityAnnotator": True or False, # Whether to run the entity annotator.
"runIntentAnnotator": True or False, # Whether to run the intent annotator.
"runInterruptionAnnotator": True or False, # Whether to run the interruption annotator.
"runIssueModelAnnotator": True or False, # Whether to run the issue model annotator. A model should have already been deployed for this to take effect.
"runPhraseMatcherAnnotator": True or False, # Whether to run the active phrase matcher annotator(s).
"runQaAnnotator": True or False, # Whether to run the QA annotator.
"runSentimentAnnotator": True or False, # Whether to run the sentiment annotator.
"runSilenceAnnotator": True or False, # Whether to run the silence annotator.
"runSummarizationAnnotator": True or False, # Whether to run the summarization annotator.
"summarizationConfig": { # Configuration for summarization. # Configuration for the summarization annotator.
"conversationProfile": "A String", # Resource name of the Dialogflow conversation profile. Format: projects/{project}/locations/{location}/conversationProfiles/{conversation_profile}
"generator": "A String", # The resource name of the existing created generator. Format: projects//locations//generators/
"summarizationModel": "A String", # Default summarization model to be used.
},
},
"runtimeIntegrationAnalysisPercentage": 3.14, # Percentage of conversations created using Dialogflow runtime integration to analyze automatically, between [0, 100].
"uploadConversationAnalysisPercentage": 3.14, # Percentage of conversations created using the UploadConversation endpoint to analyze automatically, between [0, 100].
},
"conversationTtl": "A String", # The default TTL for newly-created conversations. If a conversation has a specified expiration, that value will be used instead. Changing this value will not change the expiration of existing conversations. Conversations with no expire time persist until they are deleted.
"createTime": "A String", # Output only. The time at which the settings was created.
"languageCode": "A String", # A language code to be applied to each transcript segment unless the segment already specifies a language code. Language code defaults to "en-US" if it is neither specified on the segment nor here.
"name": "A String", # Immutable. The resource name of the settings resource. Format: projects/{project}/locations/{location}/settings
"pubsubNotificationSettings": { # A map that maps a notification trigger to a Pub/Sub topic. Each time a specified trigger occurs, Insights will notify the corresponding Pub/Sub topic. Keys are notification triggers. Supported keys are: * "all-triggers": Notify each time any of the supported triggers occurs. * "create-analysis": Notify each time an analysis is created. * "create-conversation": Notify each time a conversation is created. * "export-insights-data": Notify each time an export is complete. * "ingest-conversations": Notify each time an IngestConversations LRO is complete. * "update-conversation": Notify each time a conversation is updated via UpdateConversation. * "upload-conversation": Notify when an UploadConversation LRO is complete. * "update-or-analyze-conversation": Notify when an analysis for a conversation is completed or when the conversation is updated. The message will contain the conversation with transcript, analysis and other metadata. Values are Pub/Sub topics. The format of each Pub/Sub topic is: projects/{project}/topics/{topic}
"a_key": "A String",
},
"redactionConfig": { # DLP resources used for redaction while ingesting conversations. DLP settings are applied to conversations ingested from the `UploadConversation` and `IngestConversations` endpoints, including conversation coming from CCAI Platform. They are not applied to conversations ingested from the `CreateConversation` endpoint or the Dialogflow / Agent Assist runtime integrations. When using Dialogflow / Agent Assist runtime integrations, redaction should be performed in Dialogflow / Agent Assist. # Default DLP redaction resources to be applied while ingesting conversations. This applies to conversations ingested from the `UploadConversation` and `IngestConversations` endpoints, including conversations coming from CCAI Platform.
"deidentifyTemplate": "A String", # The fully-qualified DLP deidentify template resource name. Format: `projects/{project}/deidentifyTemplates/{template}`
"inspectTemplate": "A String", # The fully-qualified DLP inspect template resource name. Format: `projects/{project}/locations/{location}/inspectTemplates/{template}`
},
"screenRecordingBucketUri": "A String", # Optional. The path to a Cloud Storage bucket containing conversation screen recordings. If provided, Insights will search in the bucket for a screen recording file matching the conversation data source object name prefix. If matches are found, these file URIs will be stored in the conversation screen recordings field.
"speechConfig": { # Speech-to-Text configuration. Speech-to-Text settings are applied to conversations ingested from the `UploadConversation` and `IngestConversations` endpoints, including conversation coming from CCAI Platform. They are not applied to conversations ingested from the `CreateConversation` endpoint. # Optional. Default Speech-to-Text resources to use while ingesting audio files. Optional, CCAI Insights will create a default if not provided. This applies to conversations ingested from the `UploadConversation` and `IngestConversations` endpoints, including conversations coming from CCAI Platform.
"disableWordTimeOffsets": True or False, # Whether to disable word time offsets. If true, the `enable_word_time_offsets` field in the recognition config will be set to false.
"speechRecognizer": "A String", # The fully-qualified Speech Recognizer resource name. Format: `projects/{project_id}/locations/{location}/recognizer/{recognizer}`
},
"updateTime": "A String", # Output only. The time at which the settings were last updated.
}