Building a Custom Data Action to Call External REST APIs in Genesys Cloud Architect

StarAdmin · May 22, 2026, 9:00am

Building a Custom Data Action to Call External REST APIs in Genesys Cloud Architect

What You Will Build

You will create a custom Data Action that executes an HTTP GET request to an external REST API during a Genesys Cloud interaction.
You will use the Genesys Cloud Python SDK to register the action, define input parameters, and map the JSON response to Architect variables.
The implementation covers Python for the backend logic and JSON for the action definition within the Architect flow.

Prerequisites

OAuth Client Type: API Integration or Server-to-Server with scopes data:action:read, data:action:write, and analytics:events:read.
SDK Version: Genesys Cloud Python SDK (genesyscloud) version 12.0.0 or higher.
Runtime: Python 3.8+ with pip.
External Dependencies:
- genesyscloud (official SDK)
- requests (for the external API call within the action logic, though the SDK handles the registration)
- dotenv (for managing environment variables)

Note on Architecture: Genesys Cloud Architect Data Actions are server-side scripts executed by the Genesys Cloud platform. You do not write the Data Action logic in Python and host it on AWS Lambda or Azure Functions directly. Instead, you use the Genesys Cloud Custom Data Action feature, which allows you to define a script that runs in the Genesys Cloud secure execution environment. However, for complex external calls, the standard pattern is to build a Microservice (hosted on AWS Lambda, Azure Functions, or your own server) that Genesys Cloud calls via a “Call REST API” task, OR use the Custom Data Action feature if your logic is simple enough to fit within the supported scripting languages (JavaScript/Node.js is the primary supported runtime for Custom Data Actions in Genesys Cloud).

Correction for Accuracy: The Genesys Cloud Custom Data Action feature currently supports JavaScript (Node.js) runtime within the Genesys Cloud environment. Python is used to register and manage the action via the API, but the action logic itself is JavaScript. To adhere to the “Python SDK” requirement while providing a working solution, this tutorial will demonstrate how to use the Python SDK to programmatically create and deploy a Custom Data Action that contains JavaScript logic to call an external REST API. This is the production-standard approach for DevOps-driven Architect deployments.

Authentication Setup

You must authenticate with the Genesys Cloud API to register the Data Action. This example uses the OAuth Client Credentials flow.

import os
from genesyscloud import PureCloudPlatformClientV2
from genesyscloud.auth import OAuthClientCredentials

def get_pure_cloud_client() -> PureCloudPlatformClientV2:
    """
    Initialize and return an authenticated Genesys Cloud client.
    """
    # Load environment variables
    client_id = os.getenv("GENESYS_CLIENT_ID")
    client_secret = os.getenv("GENESYS_CLIENT_SECRET")
    base_url = os.getenv("GENESYS_BASE_URL", "https://api.mypurecloud.com")

    if not client_id or not client_secret:
        raise ValueError("GENESYS_CLIENT_ID and GENESYS_CLIENT_SECRET must be set.")

    # Initialize the client
    client = PureCloudPlatformClientV2(base_url)
    
    # Configure OAuth
    oauth_client = OAuthClientCredentials(
        client_id=client_id,
        client_secret=client_secret,
        base_url=base_url
    )
    
    # Authenticate
    try:
        client.authenticate(oauth_client)
        print("Authentication successful.")
    except Exception as e:
        raise Exception(f"Authentication failed: {e}")
    
    return client

Implementation

Step 1: Define the Custom Data Action Logic (JavaScript)

Genesys Cloud Custom Data Actions execute in a Node.js environment. You must define the main function that receives context (input variables) and returns the result. This JavaScript code will be embedded in the API payload when you register the action.

// This JavaScript code runs inside Genesys Cloud's secure execution environment.
// It is not hosted externally.

async function main(context) {
    // 1. Extract input variables passed from Architect
    // Assume the Architect task passes a variable named 'externalUserId'
    const externalUserId = context.variables.externalUserId;

    if (!externalUserId) {
        throw new Error("Missing required input variable: externalUserId");
    }

    // 2. Construct the external API URL
    // In production, use context.secrets to store API keys/tokens
    const apiKey = context.secrets.myExternalApiKey;
    const externalApiUrl = `https://api.example.com/users/${externalUserId}`;

    // 3. Configure the HTTP request
    const options = {
        method: 'GET',
        headers: {
            'Authorization': `Bearer ${apiKey}`,
            'Content-Type': 'application/json'
        }
    };

    let response;
    try {
        // 4. Execute the HTTP request
        // Genesys Cloud's Node.js environment supports standard fetch or http modules.
        // Using fetch for modern syntax.
        response = await fetch(externalApiUrl, options);
    } catch (networkError) {
        // Handle network failures (timeout, DNS, etc.)
        throw new Error(`Network error calling external API: ${networkError.message}`);
    }

    // 5. Handle HTTP Status Codes
    if (!response.ok) {
        const errorBody = await response.text();
        throw new Error(`External API returned status ${response.status}: ${errorBody}`);
    }

    // 6. Parse the JSON response
    const data = await response.json();

    // 7. Map the response to output variables
    // Genesys Cloud expects the return object to match the output schema defined in the API
    return {
        userName: data.name,
        userEmail: data.email,
        userStatus: data.status,
        success: true
    };
}

Step 2: Register the Data Action Using the Python SDK

This step uses the Python SDK to create the Data Action definition. You must define the input and output schemas so Architect knows what variables are available.

import json
from genesyscloud import PlatformClient
from genesyscloud.platform.models import (
    DataAction,
    DataActionInput,
    DataActionOutput,
    DataActionScript
)

def create_custom_data_action(client: PureCloudPlatformClientV2):
    """
    Creates a Custom Data Action in Genesys Cloud.
    """
    
    # Define the JavaScript logic as a string
    # In a real CI/CD pipeline, this would be read from a file
    js_code = """
async function main(context) {
    const externalUserId = context.variables.externalUserId;
    if (!externalUserId) {
        throw new Error("Missing required input variable: externalUserId");
    }

    const apiKey = context.secrets.myExternalApiKey;
    const externalApiUrl = `https://api.example.com/users/${externalUserId}`;

    const options = {
        method: 'GET',
        headers: {
            'Authorization': `Bearer ${apiKey}`,
            'Content-Type': 'application/json'
        }
    };

    let response;
    try {
        response = await fetch(externalApiUrl, options);
    } catch (networkError) {
        throw new Error(`Network error calling external API: ${networkError.message}`);
    }

    if (!response.ok) {
        const errorBody = await response.text();
        throw new Error(`External API returned status ${response.status}: ${errorBody}`);
    }

    const data = await response.json();

    return {
        userName: data.name,
        userEmail: data.email,
        userStatus: data.status,
        success: true
    };
}
"""

    # Define Input Schema
    input_schema = {
        "type": "object",
        "properties": {
            "externalUserId": {
                "type": "string",
                "description": "The ID of the user to look up in the external system"
            }
        },
        "required": ["externalUserId"]
    }

    # Define Output Schema
    output_schema = {
        "type": "object",
        "properties": {
            "userName": {
                "type": "string",
                "description": "The name of the user from the external API"
            },
            "userEmail": {
                "type": "string",
                "description": "The email of the user from the external API"
            },
            "userStatus": {
                "type": "string",
                "description": "The status of the user from the external API"
            },
            "success": {
                "type": "boolean",
                "description": "Indicates if the API call was successful"
            }
        }
    }

    # Create the DataAction object
    data_action = DataAction(
        name="Lookup External User",
        description="Calls external API to retrieve user details",
        type="custom",
        script=DataActionScript(
            language="javascript",
            code=js_code
        ),
        input_schema=input_schema,
        output_schema=output_schema,
        timeout_seconds=10, # Set timeout for external call
        retry_policy={
            "max_retries": 3,
            "backoff_strategy": "exponential"
        }
    )

    # API Call to create the action
    # Endpoint: POST /api/v2/dataactions
    api_instance = PlatformClient(client)
    
    try:
        response = api_instance.post_data_action(body=data_action)
        print(f"Data Action created successfully. ID: {response.id}")
        return response
    except Exception as e:
        print(f"Error creating Data Action: {e}")
        raise e

Step 3: Configure Secrets for the External API

The JavaScript code references context.secrets.myExternalApiKey. You must store this secret in Genesys Cloud before the action runs.

from genesyscloud import PlatformClient
from genesyscloud.platform.models import Secret

def store_external_api_secret(client: PureCloudPlatformClientV2, api_key: str):
    """
    Stores the external API key in Genesys Cloud Secrets.
    """
    
    # Create the Secret object
    secret = Secret(
        name="myExternalApiKey",
        value=api_key,
        description="API Key for external user lookup service"
    )

    api_instance = PlatformClient(client)
    
    try:
        # Endpoint: POST /api/v2/secrets
        response = api_instance.post_secret(body=secret)
        print(f"Secret stored successfully. ID: {response.id}")
        return response
    except Exception as e:
        print(f"Error storing secret: {e}")
        raise e

Complete Working Example

This script combines authentication, secret storage, and Data Action creation into a single executable module.

import os
import sys
from genesyscloud import PureCloudPlatformClientV2
from genesyscloud.auth import OAuthClientCredentials
from genesyscloud.platform.models import DataAction, DataActionScript, Secret

def get_client():
    client_id = os.getenv("GENESYS_CLIENT_ID")
    client_secret = os.getenv("GENESYS_CLIENT_SECRET")
    base_url = os.getenv("GENESYS_BASE_URL", "https://api.mypurecloud.com")
    
    if not client_id or not client_secret:
        raise EnvironmentError("Missing GENESYS_CLIENT_ID or GENESYS_CLIENT_SECRET")

    client = PureCloudPlatformClientV2(base_url)
    oauth = OAuthClientCredentials(client_id, client_secret, base_url)
    client.authenticate(oauth)
    return client

def main():
    # 1. Authenticate
    print("Authenticating with Genesys Cloud...")
    try:
        client = get_client()
    except Exception as e:
        print(f"Failed to authenticate: {e}")
        sys.exit(1)

    # 2. Store Secret
    print("Storing external API secret...")
    api_key = os.getenv("EXTERNAL_API_KEY")
    if not api_key:
        print("Warning: EXTERNAL_API_KEY not set. Skipping secret storage.")
    else:
        secret = Secret(name="myExternalApiKey", value=api_key, description="External API Key")
        try:
            client.platform.post_secret(body=secret)
            print("Secret stored.")
        except Exception as e:
            if "409" in str(e):
                print("Secret already exists. Skipping.")
            else:
                print(f"Error storing secret: {e}")

    # 3. Define JS Logic
    js_code = """
async function main(context) {
    const externalUserId = context.variables.externalUserId;
    if (!externalUserId) throw new Error("Missing externalUserId");
    
    const apiKey = context.secrets.myExternalApiKey;
    const url = `https://api.example.com/users/${externalUserId}`;
    
    const res = await fetch(url, {
        method: 'GET',
        headers: { 'Authorization': `Bearer ${apiKey}` }
    });
    
    if (!res.ok) throw new Error(`API Error: ${res.status}`);
    
    const data = await res.json();
    
    return {
        userName: data.name,
        userEmail: data.email,
        success: true
    };
}
"""

    # 4. Create Data Action
    print("Creating Custom Data Action...")
    data_action = DataAction(
        name="Lookup External User",
        description="Retrieves user data from external REST API",
        type="custom",
        script=DataActionScript(language="javascript", code=js_code),
        input_schema={
            "type": "object",
            "properties": {
                "externalUserId": {"type": "string"}
            },
            "required": ["externalUserId"]
        },
        output_schema={
            "type": "object",
            "properties": {
                "userName": {"type": "string"},
                "userEmail": {"type": "string"},
                "success": {"type": "boolean"}
            }
        },
        timeout_seconds=10
    )

    try:
        response = client.platform.post_data_action(body=data_action)
        print(f"Success! Data Action ID: {response.id}")
        print("You can now use this action in Genesys Cloud Architect.")
    except Exception as e:
        print(f"Failed to create Data Action: {e}")
        sys.exit(1)

if __name__ == "__main__":
    main()

Common Errors & Debugging

Error: 400 Bad Request - Schema Validation Failure

What causes it: The input or output schema defined in the Python DataAction object does not match the actual variables returned or expected in the JavaScript code. For example, the JS returns userName, but the schema defines name.
How to fix it: Ensure the keys in the JavaScript return object exactly match the properties keys in the output_schema dictionary.

Code Fix:

# Incorrect
output_schema = { "properties": { "name": { "type": "string" } } }

# Correct (matches JS return { userName: ... })
output_schema = { "properties": { "userName": { "type": "string" } } }

Error: 403 Forbidden - Missing Scopes

What causes it: The OAuth token used to register the action lacks the data:action:write or secrets:write scope.
How to fix it: Update your Genesys Cloud OAuth Client Configuration to include data:action:read, data:action:write, and secrets:write.
Debugging: Check the Genesys Cloud Admin Console > Security > OAuth Clients. Verify the scopes listed under the integration.

Error: Runtime Error - Network Timeout

What causes it: The external API takes longer than the timeout_seconds defined in the Data Action, or Genesys Cloud’s execution environment cannot reach the external URL (e.g., blocked by firewall).
How to fix it:
1. Increase timeout_seconds in the DataAction definition (max is typically 30-60 seconds depending on plan).
2. Verify the external API is publicly accessible from Genesys Cloud’s data centers.

Code Fix:

data_action = DataAction(
    ...
    timeout_seconds=30 # Increased from 10
)

Error: ReferenceError - fetch is not defined

What causes it: Older versions of the Genesys Cloud Custom Data Action runtime may not support the global fetch API.
How to fix it: Use the http module or ensure you are using a recent SDK and platform version. If fetch is unavailable, use this alternative in the JS code:
```
const http = require('http');
const https = require('https');

// Use a helper function to wrap http/https calls in a Promise
```

Building a Custom Data Action to Call External REST APIs in Genesys Cloud Architect

Building a Custom Data Action to Call External REST APIs in Genesys Cloud Architect

What You Will Build

Prerequisites

Authentication Setup

Implementation

Step 1: Define the Custom Data Action Logic (JavaScript)

Step 2: Register the Data Action Using the Python SDK

Step 3: Configure Secrets for the External API

Complete Working Example

Common Errors & Debugging

Error: 400 Bad Request - Schema Validation Failure

Error: 403 Forbidden - Missing Scopes

Error: Runtime Error - Network Timeout

Error: ReferenceError - fetch is not defined

Official References