Dialogflow API . projects . conversations . messages

close()

Close httplib2 connections.

list(parent, filter=None, pageSize=None, pageToken=None, x__xgafv=None)

Lists messages that belong to a given conversation. `messages` are ordered by `create_time` in descending order. To fetch updates without duplication, send request with filter `create_time_epoch_microseconds > [first item's create_time of previous request]` and empty page_token.

Args:
  parent: string, Required. The name of the conversation to list messages for. Format: `projects//locations//conversations/` (required)
  filter: string, Optional. Filter on message fields. Currently predicates on `create_time` and `create_time_epoch_microseconds` are supported. `create_time` only support milliseconds accuracy. E.g., `create_time_epoch_microseconds > 1551790877964485` or `create_time > 2017-01-15T01:30:15.01Z`. For more information about filtering, see [API Filtering](https://aip.dev/160).
  pageSize: integer, Optional. The maximum number of items to return in a single page. By default 100 and at most 1000.
  pageToken: string, Optional. The next_page_token value returned from a previous list request.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # The response message for Conversations.ListMessages.
  "messages": [ # The list of messages. There will be a maximum number of items returned based on the page_size field in the request. `messages` is sorted by `create_time` in descending order.
    { # Represents a message posted into a conversation.
      "content": "A String", # Required. The message content.
      "createTime": "A String", # Output only. The time when the message was created in Contact Center AI.
      "languageCode": "A String", # Optional. The message language. This should be a [BCP-47](https://www.rfc-editor.org/rfc/bcp/bcp47.txt) language tag. Example: "en-US".
      "messageAnnotation": { # Represents the result of annotation for the message. # Output only. The annotation for the message.
        "containEntities": True or False, # Indicates whether the text message contains entities.
        "parts": [ # The collection of annotated message parts ordered by their position in the message. You can recover the annotated message by concatenating [AnnotatedMessagePart.text].
          { # Represents a part of a message possibly annotated with an entity. The part can be an entity or purely a part of the message between two entities or message start/end.
            "entityType": "A String", # The [Dialogflow system entity type](https://cloud.google.com/dialogflow/docs/reference/system-entities) of this message part. If this is empty, Dialogflow could not annotate the phrase part with a system entity.
            "formattedValue": "", # The [Dialogflow system entity formatted value ](https://cloud.google.com/dialogflow/docs/reference/system-entities) of this message part. For example for a system entity of type `@sys.unit-currency`, this may contain: { "amount": 5, "currency": "USD" }
            "text": "A String", # A part of a message possibly annotated with an entity.
          },
        ],
      },
      "name": "A String", # Optional. The unique identifier of the message. Format: `projects//locations//conversations//messages/`.
      "participant": "A String", # Output only. The participant that sends this message.
      "participantRole": "A String", # Output only. The role of the participant.
      "sendTime": "A String", # Optional. The time when the message was sent.
      "sentimentAnalysis": { # The result of sentiment analysis. Sentiment analysis inspects user input and identifies the prevailing subjective opinion, especially to determine a user's attitude as positive, negative, or neutral. For DetectIntent, it needs to be configured in DetectIntentRequest.query_params. For StreamingDetectIntent, it needs to be configured in StreamingDetectIntentRequest.query_params. And for Participants.AnalyzeContent and Participants.StreamingAnalyzeContent, it needs to be configured in ConversationProfile.human_agent_assistant_config # Output only. The sentiment analysis result for the message.
        "queryTextSentiment": { # The sentiment, such as positive/negative feeling or association, for a unit of analysis, such as the query text. See: https://cloud.google.com/natural-language/docs/basics#interpreting_sentiment_analysis_values for how to interpret the result. # The sentiment analysis result for `query_text`.
          "magnitude": 3.14, # A non-negative number in the [0, +inf) range, which represents the absolute magnitude of sentiment, regardless of score (positive or negative).
          "score": 3.14, # Sentiment score between -1.0 (negative sentiment) and 1.0 (positive sentiment).
        },
      },
    },
  ],
  "nextPageToken": "A String", # Token to retrieve the next page of results, or empty if there are no more results in the list.
}

list_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.