View Source API Reference google_api_contact_center_insights v0.13.0
Modules
API client metadata for GoogleApi.ContactCenterInsights.V1.
API calls for all endpoints tagged Projects.
Handle Tesla connections for GoogleApi.ContactCenterInsights.V1.
The analysis resource.
The result of an analysis.
Call-specific metadata created during analysis.
The CCAI Insights project wide analysis rule. This rule will be applied to all conversations that match the filter defined in the rule. For a conversation matches the filter, the annotators specified in the rule will be run. If a conversation matches multiple rules, a union of all the annotators will be run. One project can have multiple analysis rules.
A point in a conversation that marks the start or the end of an annotation.
Selector of all available annotators and phrase matchers to run.
Configuration for the QA feature.
Container for a list of scorecards.
Configuration for summarization.
The feedback that the customer has about a certain answer in the conversation.
Agent Assist Article Suggestion data.
The metadata for a bulk analyze conversations operation.
The request to analyze conversations in bulk.
The response for a bulk analyze conversations operation.
The metadata for a bulk delete conversations operation.
The request to delete conversations in bulk.
The response for a bulk delete conversations operation.
Metadata for the BulkDownloadFeedbackLabel endpoint.
Statistics for BulkDownloadFeedbackLabels operation.
Request for the BulkDownloadFeedbackLabel endpoint.
Google Cloud Storage Object details to write the feedback labels to.
Response for the BulkDownloadFeedbackLabel endpoint.
The request for bulk uploading feedback labels.
Google Cloud Storage Object details to get the feedback label file from.
Response of querying an issue model's statistics.
The response for calculating conversation statistics.
A time series representing conversations over time.
A single interval in a time series.
A piece of metadata that applies to a window of a call.
The conversation resource.
Call-specific metadata.
The conversation source, which is a combination of transcript and audio.
One channel of conversation-level sentiment data.
Conversation-level silence data.
The call participant speaking for a given utterance.
Conversation metadata related to quality management.
Information about an agent involved in the conversation.
Conversation summarization suggestion data.
A message representing the transcript of a conversation.
A segment of a full transcript.
Metadata from Dialogflow relating to the current transcript segment.
Word-level info for words in a transcript.
Metadata for a create analysis operation.
Metadata for creating an issue model.
The request to create an issue model.
Metadata for deleting an issue model.
The request to delete an issue model.
Metadata for deploying an issue model.
The request to deploy an issue model.
The response to deploy an issue model.
The request to deploy a QaScorecardRevision
The data for a Dialogflow intent. Represents a detected intent in the conversation, e.g. MAKES_PROMISE.
Dialogflow interaction data.
A Dialogflow source of conversation data.
A dimension determines the grouping key for the query. In SQL terms, these would be part of both the "SELECT" and "GROUP BY" clauses.
Metadata about the agent dimension.
Metadata about the issue dimension.
Metadata about the QA question-answer dimension. This is useful for showing the answer distribution for questions for a given scorecard.
Metadata about the QA question dimension.
A customer-managed encryption key specification that can be applied to all created resources (e.g. Conversation).
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.
The data for an entity mention annotation. This represents a mention of an Entity in the conversation.
Exact match configuration.
Metadata for an export insights operation.
The request to export insights.
A BigQuery Table Reference.
Response for an export insights operation.
Metadata used for export issue model.
Request to export an issue model.
Google Cloud Storage Object URI to save the issue model to.
Response from export issue model
Agent Assist frequently-asked-question answer data.
Represents a conversation, resource, and label provided by the user.
A Cloud Storage source of conversation data.
The data for a hold annotation.
Metadata used for import issue model.
Request to import an issue model.
Google Cloud Storage Object URI to get the issue model file from.
Response from import issue model
The metadata for an IngestConversations operation.
Statistics for IngestConversations operation.
The request to ingest conversations.
Configuration that applies to all conversations.
Configuration for Cloud Storage bucket sources.
Configuration for processing transcript objects.
The response to an IngestConversations operation.
Metadata for initializing a location-level encryption specification.
The request to initialize a location-level encryption specification.
The response to initialize a location-level encryption specification.
The data for an intent. Represents a detected intent in the conversation, for example MAKES_PROMISE.
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.
The data for an interruption annotation.
The issue resource.
Information about the issue.
The data for an issue match annotation.
The issue model resource.
Configs for the input data used to create the issue model.
Aggregated statistics about an issue model.
Aggregated statistics about an issue.
Issue Modeling result on a conversation.
The response for listing all feedback labels.
The response to list analyses.
The response of listing views.
The response of listing conversations.
The response for listing feedback labels.
The response of listing issue models.
The response of listing issues.
The response of listing phrase matchers.
The response from a ListQaQuestions request.
The response from a ListQaScorecardRevisions request.
The response from a ListQaScorecards request.
The response of listing views.
The data for a matched phrase matcher. Represents information identifying a phrase matcher for a given match.
The data for a phrase match rule.
Configuration information of a phrase match rule.
A message representing a rule in the phrase matcher.
The phrase matcher resource.
An answer to a QaQuestion.
A question may have multiple answers from varying sources, one of which becomes the "main" answer above. AnswerSource represents each individual answer.
Message for holding the value of a QaAnswer. QaQuestion.AnswerChoice defines the possible answer values for a question.
A single question to be scored by the Insights QA feature.
Message representing a possible answer to the question.
A wrapper representing metrics calculated against a test-set on a LLM that was fine tuned for this question.
Metadata about the tuning operation for the question. Will only be set if a scorecard containing this question has been tuned.
A QaScorecard represents a collection of questions to be scored during analysis.
The results of scoring a single conversation against a QaScorecard. Contains a collection of QaAnswers and aggregate score.
Tags and their corresponding results.
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.
A revision of a QaScorecard. Modifying published scorecard fields would invalidate existing scorecard results — the questions may have changed, or the score weighting will make existing scores impossible to understand. So changes must create a new revision, rather than modifying the existing resource.
The metadata from querying metrics.
The request for querying metrics.
The response for querying metrics.
A slice contains a total and (if the request specified a time granularity) a time series of metric values. Each slice contains a unique combination of the cardinality of dimensions from the request. For example, if the request specifies a single ISSUE dimension and it has a cardinality of 2 (i.e. the data used to compute the metrics has 2 issues in total), the response will have 2 slices: Slice 1 -> dimensions=[Issue 1] Slice 2 -> dimensions=[Issue 2]
A data point contains the metric values mapped to an interval.
The measure related to conversations.
Average QA normalized score for the tag.
A time series of metric values.
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.
An annotation that was generated during the customer and agent interaction.
Explicit input used for generating the answer
The data for a sentiment annotation.
The CCAI Insights project wide settings. Use these settings to configure the behavior of Insights. View these settings with getsettings and change the settings with updateSettings.
Default configuration when creating Analyses in Insights.
The data for a silence annotation.
Agent Assist Smart Compose suggestion data.
Agent Assist Smart Reply data.
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.
Request for TuneQaScorecardRevision endpoint.
Metadata for undeploying an issue model.
The request to undeploy an issue model.
The response to undeploy an issue model.
The request to undeploy a QaScorecardRevision
The metadata for an UploadConversation operation.
Request to upload a conversation.
The analysis resource.
The result of an analysis.
Call-specific metadata created during analysis.
A point in a conversation that marks the start or the end of an annotation.
Selector of all available annotators and phrase matchers to run.
Configuration for the QA feature.
Container for a list of scorecards.
Configuration for summarization.
The feedback that the customer has about a certain answer in the conversation.
Agent Assist Article Suggestion data.
The metadata for a bulk analyze conversations operation.
The request to analyze conversations in bulk.
The response for a bulk analyze conversations operation.
The metadata for a bulk delete conversations operation.
The request to delete conversations in bulk.
The response for a bulk delete conversations operation.
A piece of metadata that applies to a window of a call.
The conversation resource.
Call-specific metadata.
The conversation source, which is a combination of transcript and audio.
One channel of conversation-level sentiment data.
Conversation-level silence data.
The call participant speaking for a given utterance.
Conversation metadata related to quality management.
Information about an agent involved in the conversation.
Conversation summarization suggestion data.
A message representing the transcript of a conversation.
A segment of a full transcript.
Metadata from Dialogflow relating to the current transcript segment.
Word-level info for words in a transcript.
Metadata for a create analysis operation.
Metadata for creating an issue model.
The request to create an issue model.
Metadata for deleting an issue model.
The request to delete an issue model.
Metadata for deploying an issue model.
The request to deploy an issue model.
The response to deploy an issue model.
The data for a Dialogflow intent. Represents a detected intent in the conversation, e.g. MAKES_PROMISE.
Dialogflow interaction data.
A Dialogflow source of conversation data.
A dimension determines the grouping key for the query. In SQL terms, these would be part of both the "SELECT" and "GROUP BY" clauses.
Metadata about the agent dimension.
Metadata about the issue dimension.
Metadata about the QA question-answer dimension. This is useful for showing the answer distribution for questions for a given scorecard.
Metadata about the QA question dimension.
A customer-managed encryption key specification that can be applied to all created resources (e.g. Conversation).
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.
The data for an entity mention annotation. This represents a mention of an Entity in the conversation.
Metadata for an export insights operation.
The request to export insights.
A BigQuery Table Reference.
Response for an export insights operation.
Metadata used for export issue model.
Request to export an issue model.
Google Cloud Storage Object URI to save the issue model to.
Response from export issue model
Agent Assist frequently-asked-question answer data.
Represents a conversation, resource, and label provided by the user.
A Cloud Storage source of conversation data.
The data for a hold annotation.
Metadata used for import issue model.
Request to import an issue model.
Google Cloud Storage Object URI to get the issue model file from.
Response from import issue model
The metadata for an IngestConversations operation.
Statistics for IngestConversations operation.
The request to ingest conversations.
Configuration that applies to all conversations.
Configuration for Cloud Storage bucket sources.
Configuration for processing transcript objects.
The response to an IngestConversations operation.
Metadata for initializing a location-level encryption specification.
The request to initialize a location-level encryption specification.
The response to initialize a location-level encryption specification.
The data for an intent. Represents a detected intent in the conversation, for example MAKES_PROMISE.
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.
The data for an interruption annotation.
Information about the issue.
The data for an issue match annotation.
The issue model resource.
Configs for the input data used to create the issue model.
Aggregated statistics about an issue model.
Aggregated statistics about an issue.
Issue Modeling result on a conversation.
The response for listing all feedback labels.
The response for listing feedback labels.
The data for a matched phrase matcher. Represents information identifying a phrase matcher for a given match.
An answer to a QaQuestion.
A question may have multiple answers from varying sources, one of which becomes the "main" answer above. AnswerSource represents each individual answer.
Message for holding the value of a QaAnswer. QaQuestion.AnswerChoice defines the possible answer values for a question.
The results of scoring a single conversation against a QaScorecard. Contains a collection of QaAnswers and aggregate score.
Tags and their corresponding results.
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.
The metadata from querying metrics.
The response for querying metrics.
A slice contains a total and (if the request specified a time granularity) a time series of metric values. Each slice contains a unique combination of the cardinality of dimensions from the request. For example, if the request specifies a single ISSUE dimension and it has a cardinality of 2 (i.e. the data used to compute the metrics has 2 issues in total), the response will have 2 slices: Slice 1 -> dimensions=[Issue 1] Slice 2 -> dimensions=[Issue 2]
A data point contains the metric values mapped to an interval.
The measure related to conversations.
Average QA normalized score for the tag.
A time series of metric values.
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.
An annotation that was generated during the customer and agent interaction.
Explicit input used for generating the answer
The data for a sentiment annotation.
The data for a silence annotation.
Agent Assist Smart Compose suggestion data.
Agent Assist Smart Reply data.
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.
Metadata for undeploying an issue model.
The request to undeploy an issue model.
The response to undeploy an issue model.
The metadata for an UploadConversation operation.
Request to upload a conversation.
The response message for Operations.ListOperations.
This resource represents a long-running operation that is the result of a network API call.
A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }
The Status type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by gRPC. Each Status message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the API Design Guide.
Represents a time interval, encoded as a Timestamp start (inclusive) and a Timestamp end (exclusive). The start must be less than or equal to the end. When the start equals the end, the interval is empty (matches no time). When both start and end are unspecified, the interval matches any time.