Input Transformer - Cognigy Documentation

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In Cognigy.AI 2025.25.0, transformers will start using the axios library for handling HTTP requests internally instead of request-promise. This change occurs to improve security and maintainability. The following HTTP request options will still be supported:

If you use other HTTP request options, review your transformer code to ensure it is compatible with the axios library before the release of Cognigy.AI 2025.25.0.

The Input Transformer converts the user input after it’s sent to an Endpoint. This allows you to manipulate the user input data before it is sent to the Flow, for example, to communicate with external systems, to implement integrations with a custom channel, and much more. You can configure the input transformer in the handleInput function in the Endpoint settings or via CLI.

Restrictions

Transformer Function Arguments

Depending on the Endpoint type in which you want to use the transformer, the function arguments vary:

Argument Description
endpoint The configuration object for the Endpoint.
request The Express request object with a JSON-parsed body.
response The Express response object.
Argument Description
endpoint The configuration object for the Endpoint.
payload The payload object contains the userId, sessionId, text, and data that was sent through the socket. The payload also contains the channel of the client.

Endpoint Configuration Object

endpoint Object Properties

Property Type Description
_id string The Endpoint’s Reference ID.
channel string The Endpoint’s channel.
URLToken string The URL Token, found in the Input object.
name string The Endpoint’s name.
flowId string The Reference ID of the specified Flow to which the Endpoint points to.
entrypoint string The Entrypoint of the Endpoint.
active boolean The flag to activate or deactivate the Endpoint.
nluConnectorId string ID of the selected NLU connector for the Endpoint.
useAnalytics boolean The flag to collect analytics data for the Endpoint.
storeDataPayload boolean The flag to store data payloads into analytics for the Endpoint.
useConversations boolean The flag to collect conversations history for the Endpoint.
maskIPAddress boolean The flag to mask sensitive IP addresses in input object and analytics data.
maskAnalytics boolean The flag to mask sensitive data in analytics for the Endpoint.
maskLogging boolean The flag to mask sensitive data in logs for the Endpoint.
useContactProfiles boolean The flag to use Contact Profiles for the Endpoint.
useDashbotAnalytics boolean The flag to use Dashbot for collecting analytics data.
dashbotApikey string The API key of the Dashbot bot for analytics collection.
dashbotPlatform string The selected platform of the Dashbot bot for analytics collection.
settings object Optional Endpoint-specific settings. For example, Facebook Page token.
handoverSettings object Settings to configure a handover provider.
createdAt number Unix timestamp when the Endpoint was created.
lastChanged number Unix timestamp when the Endpoint was last modified.
createdBy string Email of the user who created the Endpoint.
lastChangedBy string Email of the user who last modified the Endpoint.

Return Values

The input transformer returns the user ID, session ID, text, and data, which are subsequently sent to the Flow. These values are extracted from the Endpoint payload. The payload format is specific to the Endpoint type you use, for example, Alexa or Facebook (Meta) Messenger. Read the documentation of the specific Endpoint to know how to format the payload.

Example of Transformer Return Values

return {
    userId: payload.userId,
    sessionId: payload.sessionId,
    text: payload.text,
    data: { "test": 1 }
};

Undefined Return Values

If the transformer returns undefined for userId, sessionId, text, or data, this means that the transformer uses the value from the Endpoint.

Example of Undefined Return Values

The following example overwrites text and data, but uses the userId and sessionId from the Endpoint:

return {
    userId: undefined,
    sessionId: undefined,
    text: payload.text,
    data: { "test": 1 }
};

Endpoints Event Messages

The Webchat and the Socket.IO Endpoints output event messages that indicate user activity, such as whether the user is connected (user-connected) or disconnected (user-disconnected). These event messages neither trigger Flows nor are counted. The event messages inform handover providers about user activity, allowing human agents to determine if the user is still engaged in the conversation. You can access the event messages with the data._cognigy.event property in the return value of the input transformer.

Example of Return Values with Event Messages

return {
    "userId": payload.userId,
    "sessionId": payload.sessionId,
    "text": payload.text,
    "data": {
        "_cognigy": {
              "event": {
                "type": "user-connected"
            }
        }
    }
}

If you want to access event messages in the input transformer, don’t modify them. The event messages are only recognized if their data payload follows a specific format. The following code snippet shows how to use event messages in the input transformer:

Example of Input Transformer with Event Messages

{
handleInput: async ({ payload, endpoint }) => {
  if (!!payload.data?._cognigy?.event) {
// pass on "event messages" without modification
      return payload;
    }

// rest of your input transformer code
  }
}

Transformers and Conversation Counts

Conversations in Cognigy.AI are counted if the input transformer returns any result but falsy.

Last modified on April 21, 2026