Conversation Element

A Conversation Element is an object containing an interlocutor interaction (text, button action, url loaded event, custom event) and the corresponding bot answer.
The Conversation Element objects are used in the return value of the Conversation history endpoints.

Attribute	Type	Description
interlocutor_id	String	The interlocutor id of the conversation element
interlocutor	Interlocutor	The interlocutor, consolidated only for search results
timestamp	Long	Time in second after epoch of the interlocutor query
bot_id	String	The bot ID
input_source	Source	Qualify the source on input_action, (interlocutor or user)
output_source	Source	Qualify the source of the answer, (the bot)
input_action.source	Source	Usually the same input_source
input_action.action	Action	The interlocutor action (Message or Go to) that trigger the bot answers or the support agent text (to the interlocutor)
input_action.target	Target	The target the bot will execute, as result of the input_action.action
input_action.match	Match	When the input_action.action is of type 'text', the optional 'match' field explain the intent that was found as matching the user query
input_event.source	Source	Qualify the source of input_event (when there is one)
input_event.event	Map	Open schema when can be save special event like the take_control event
output_actions	List	List of all the actions the bot executed to reply to the interlocutor. The list is distributed into 2 levels, so the actions are grouped by step source (where the actions are defined)
output_actions[].source	Source	The story/step source of the actions in following field "actions"
output_actions[].actions[].action	Action	An action as bot response
output_actions[].actions[].parents[]	List of actions	In case the previous action is transformed from another kind of action (ex : google_custom_search action is transformed into send_cards_action to be displayed to user), this is the list (usually one) of originated action.

Source object

Attribute	Type	Description
type	String	bot/interlocutor/story/step/actions_block/user
id	String	the Id of the type object
name	String	name of the type object

Target object

Attribute	Type	Description
type	String	story/step/actions_block
id	String	the Id of the type object
name	String	name of the type object

Match object

Attribute	Type	Description
analyzeType	String	'detect' when the nlp analysis was made in regards of all bot's intents. 'select' when the nlp analysis was made inregards of a subset of intents (in 'Then' in steps connections /matchIntent)
duration	Float	Time in s the nlp analysis took
score	Float	between 0 and 1. The score the text match the following intent. (optional : no score if no intents was found)
matchingIntent	object	extract of the matching intent
matchingIntent.id	String	id of the intent
matchingIntent.name	String	name of the intent
matchingIntent.type	String	always 'intent'
matchingIntent.priority/.precision	Integer	the priority and precision parametrized of the intent

{
  "interlocutor_id": "5c58414ffd43ca0010fa1ae1",
  "timestamp": 1557157686,
  "bot_id": "5bfe9b243422d7000e046da8",
  "input_source": {
      "type": "interlocutor",
      "interlocutor_id": "5c58414ffd43ca0010fa1ae1"
  },
  "output_source": {
      "type": "bot",
      "bot_id": "5bfe9b243422d7000e046da8"
  },
  "input_action": {
      "source": {
          "type": "interlocutor",
          "interlocutor_id": "5c58414ffd43ca0010fa1ae1"
      },
     "action": {
       "type": "text",
         "message": "hello robot"
     },
     "target": {
      "id": "5bfe9b25e6b7bb0009914338",
      "type": "actions_block",
      "name": "Hello"
    },
    "match": {
      "analyzeType": "detect",
      "duration": 0.0131217912,
      "score": 1,
      "matchingIntent": {
        "id": "5d35c9a7ba2bbb000dd3945d",
        "type": "intent",
        "name": "Hello",
        "priority": 20000,
        "precision": 20000
      }
    }
  },
  "output_actions": [
    {
      "source": {
        "type": "actions_block",
        "actions_block_id": "5bfe9b25e6b7bb0009914338"
      },
      "actions": [
        {
          "action": {
            "type": "wait_action",
            "duration": 2
          },
          "parent_actions": []
        },
        {
          "action": {
            "type": "send_text_action",
            "alternatives": [
              "Hello you.\n"
            ],
            "text": "Hello you.\n"
          },
          "parent_actions": []
        },
        {
          "action": {
            "type": "wait_action",
            "duration": 2
          },
          "parent_actions": []
        },
        {
          "action": {
            "type": "send_text_action",
            "alternatives": [
              "How do you do ?"
            ],
            "text": "How do you do ?"
          },
          "parent_actions": []
        }
      ]
    }
  ]
}