ConnectContactLens ****************** Client ====== class ConnectContactLens.Client A low-level client representing Amazon Connect Contact Lens * Contact Lens actions * Contact Lens data types Amazon Connect Contact Lens enables you to analyze conversations between customer and agents, by using speech transcription, natural language processing, and intelligent search capabilities. It performs sentiment analysis, detects issues, and enables you to automatically categorize contacts. Amazon Connect Contact Lens provides both real-time and post-call analytics of customer-agent conversations. For more information, see Analyze conversations using speech analytics in the *Amazon Connect Administrator Guide*. import boto3 client = boto3.client('connect-contact-lens') These are the available methods: * can_paginate * close * get_paginator * get_waiter * list_realtime_contact_analysis_segments ConnectContactLens / Client / get_paginator get_paginator ************* ConnectContactLens.Client.get_paginator(operation_name) Create a paginator for an operation. Parameters: **operation_name** (*string*) -- The operation name. This is the same name as the method name on the client. For example, if the method name is "create_foo", and you'd normally invoke the operation as "client.create_foo(**kwargs)", if the "create_foo" operation can be paginated, you can use the call "client.get_paginator("create_foo")". Raises: **OperationNotPageableError** -- Raised if the operation is not pageable. You can use the "client.can_paginate" method to check if an operation is pageable. Return type: "botocore.paginate.Paginator" Returns: A paginator object. ConnectContactLens / Client / can_paginate can_paginate ************ ConnectContactLens.Client.can_paginate(operation_name) Check if an operation can be paginated. Parameters: **operation_name** (*string*) -- The operation name. This is the same name as the method name on the client. For example, if the method name is "create_foo", and you'd normally invoke the operation as "client.create_foo(**kwargs)", if the "create_foo" operation can be paginated, you can use the call "client.get_paginator("create_foo")". Returns: "True" if the operation can be paginated, "False" otherwise. ConnectContactLens / Client / get_waiter get_waiter ********** ConnectContactLens.Client.get_waiter(waiter_name) Returns an object that can wait for some condition. Parameters: **waiter_name** (*str*) -- The name of the waiter to get. See the waiters section of the service docs for a list of available waiters. Returns: The specified waiter object. Return type: "botocore.waiter.Waiter" ConnectContactLens / Client / list_realtime_contact_analysis_segments list_realtime_contact_analysis_segments *************************************** ConnectContactLens.Client.list_realtime_contact_analysis_segments(**kwargs) Provides a list of analysis segments for a real-time analysis session. See also: AWS API Documentation **Request Syntax** response = client.list_realtime_contact_analysis_segments( InstanceId='string', ContactId='string', MaxResults=123, NextToken='string' ) Parameters: * **InstanceId** (*string*) -- **[REQUIRED]** The identifier of the Amazon Connect instance. * **ContactId** (*string*) -- **[REQUIRED]** The identifier of the contact. * **MaxResults** (*integer*) -- The maximum number of results to return per page. * **NextToken** (*string*) -- The token for the next set of results. Use the value returned in the previous response in the next request to retrieve the next set of results. Return type: dict Returns: **Response Syntax** { 'Segments': [ { 'Transcript': { 'Id': 'string', 'ParticipantId': 'string', 'ParticipantRole': 'string', 'Content': 'string', 'BeginOffsetMillis': 123, 'EndOffsetMillis': 123, 'Sentiment': 'POSITIVE'|'NEUTRAL'|'NEGATIVE', 'IssuesDetected': [ { 'CharacterOffsets': { 'BeginOffsetChar': 123, 'EndOffsetChar': 123 } }, ] }, 'Categories': { 'MatchedCategories': [ 'string', ], 'MatchedDetails': { 'string': { 'PointsOfInterest': [ { 'BeginOffsetMillis': 123, 'EndOffsetMillis': 123 }, ] } } }, 'PostContactSummary': { 'Content': 'string', 'Status': 'FAILED'|'COMPLETED', 'FailureCode': 'QUOTA_EXCEEDED'|'INSUFFICIENT_CONVERSATION_CONTENT'|'FAILED_SAFETY_GUIDELINES'|'INVALID_ANALYSIS_CONFIGURATION'|'INTERNAL_ERROR' } }, ], 'NextToken': 'string' } **Response Structure** * *(dict) --* * **Segments** *(list) --* An analyzed transcript or category. * *(dict) --* An analyzed segment for a real-time analysis session. * **Transcript** *(dict) --* The analyzed transcript. * **Id** *(string) --* The identifier of the transcript. * **ParticipantId** *(string) --* The identifier of the participant. Valid values are CUSTOMER or AGENT. * **ParticipantRole** *(string) --* The role of participant. For example, is it a customer, agent, or system. * **Content** *(string) --* The content of the transcript. * **BeginOffsetMillis** *(integer) --* The beginning offset in the contact for this transcript. * **EndOffsetMillis** *(integer) --* The end offset in the contact for this transcript. * **Sentiment** *(string) --* The sentiment detected for this piece of transcript. * **IssuesDetected** *(list) --* List of positions where issues were detected on the transcript. * *(dict) --* Potential issues that are detected based on an artificial intelligence analysis of each turn in the conversation. * **CharacterOffsets** *(dict) --* The offset for when the issue was detected in the segment. * **BeginOffsetChar** *(integer) --* The beginning of the issue. * **EndOffsetChar** *(integer) --* The end of the issue. * **Categories** *(dict) --* The matched category rules. * **MatchedCategories** *(list) --* The category rules that have been matched in the analyzed segment. * *(string) --* * **MatchedDetails** *(dict) --* The category rule that was matched and when it occurred in the transcript. * *(string) --* * *(dict) --* Provides information about the category rule that was matched. * **PointsOfInterest** *(list) --* The section of audio where the category rule was detected. * *(dict) --* The section of the contact audio where that category rule was detected. * **BeginOffsetMillis** *(integer) --* The beginning offset in milliseconds where the category rule was detected. * **EndOffsetMillis** *(integer) --* The ending offset in milliseconds where the category rule was detected. * **PostContactSummary** *(dict) --* Information about the post-contact summary. * **Content** *(string) --* The content of the summary. * **Status** *(string) --* Whether the summary was successfully COMPLETED or FAILED to be generated. * **FailureCode** *(string) --* If the summary failed to be generated, one of the following failure codes occurs: * "QUOTA_EXCEEDED": The number of concurrent analytics jobs reached your service quota. * "INSUFFICIENT_CONVERSATION_CONTENT": The conversation needs to have at least one turn from both the participants in order to generate the summary. * "FAILED_SAFETY_GUIDELINES": The generated summary cannot be provided because it failed to meet system safety guidelines. * "INVALID_ANALYSIS_CONFIGURATION": This code occurs when, for example, you're using a language that isn't supported by generative AI-powered post- contact summaries. * "INTERNAL_ERROR": Internal system error. * **NextToken** *(string) --* If there are additional results, this is the token for the next set of results. If response includes "nextToken" there are two possible scenarios: * There are more segments so another call is required to get them. * There are no more segments at this time, but more may be available later (real-time analysis is in progress) so the client should call the operation again to get new segments. If response does not include "nextToken", the analysis is completed (successfully or failed) and there are no more segments to retrieve. **Exceptions** * "ConnectContactLens.Client.exceptions.InvalidRequestException" * "ConnectContactLens.Client.exceptions.AccessDeniedException" * "ConnectContactLens.Client.exceptions.ResourceNotFoundException" * "ConnectContactLens.Client.exceptions.InternalServiceException" * "ConnectContactLens.Client.exceptions.ThrottlingException" ConnectContactLens / Client / close close ***** ConnectContactLens.Client.close() Closes underlying endpoint connections.