Accessing Web Messaging Participant Attributes in Genesys Cloud Architect

What You Will Build

• You will build a Python script that retrieves the raw JSON payload of a Web Messaging conversation, extracts custom participant attributes, and maps them to Architect variables for use in inbound message flows.
• This tutorial uses the Genesys Cloud Python SDK (genesyscloud) and the REST API for Analytics/Conversations.
• The programming language covered is Python 3.9+.

Prerequisites

• OAuth Client Type: A Service Account with the following scopes:
  • conversation:webchat:read (to access web messaging conversation details)
  • analytics:conversation:read (optional, if using analytics endpoints for historical data)
  • user:read (if you need to resolve user IDs)
• SDK Version: genesyscloud >= 12.0.0
• Language/Runtime: Python 3.9+
• External Dependencies:

  pip install genesyscloud
  

Authentication Setup

Genesys Cloud uses OAuth 2.0. For server-to-server communication (like this tutorial), you must use the Client Credentials flow.

Step 1: Configure Environment Variables

Create a .env file in your project root. Do not hardcode credentials.

GENESYS_REGION=us-east-1.aws
GENESYS_CLIENT_ID=your-client-id-here
GENESYS_CLIENT_SECRET=your-client-secret-here

Step 2: Initialize the Client

The Genesys Cloud SDK handles token acquisition and caching automatically. You initialize the client once, and subsequent API calls reuse the token until it expires.

import os
from dotenv import load_dotenv
from genesyscloud import PlatformClient, Configuration
import json

load_dotenv()

def get_platform_client():
    """
    Initializes the Genesys Cloud Platform Client.
    """
    config = Configuration(
        region=os.getenv("GENESYS_REGION"),
        client_id=os.getenv("GENESYS_CLIENT_ID"),
        client_secret=os.getenv("GENESYS_CLIENT_SECRET")
    )
    
    client = PlatformClient(config)
    return client

# Initialize global client
client = get_platform_client()

Error Handling: If your client ID or secret is invalid, the SDK will raise an UnauthorizedException (401) on the first API call. If the region is incorrect, you will receive a ConnectionError or a 404. Ensure the region string matches your environment (e.g., us-east-1.aws, eu-west-1.aws).

Implementation

Step 1: Capture the Conversation ID

In an Architect flow, you typically trigger an API action when a message is received. The trigger provides the conversationId. For this tutorial, we will simulate having a conversationId.

If you are testing manually, you can find a recent Web Messaging conversation ID using the Analytics API or by checking the Genesys Cloud Admin Console under Conversations > Web Messaging.

Step 2: Retrieve Conversation Details via SDK

To access participant attributes, you must fetch the full conversation object. The GET /api/v2/conversations/webchat/{conversationId} endpoint returns the conversation metadata, including the participants array.

Each participant in this array has an attributes field. This is where Web Messaging custom data resides.

from genesyscloud import ConversationWebchatApi
from genesyscloud.exceptions import ApiClientException

def get_webchat_conversation(conversation_id: str) -> dict:
    """
    Fetches the full Web Messaging conversation object.
    
    Args:
        conversation_id: The UUID of the webchat conversation.
        
    Returns:
        The conversation object as a dictionary.
    """
    webchat_api = ConversationWebchatApi(client)
    
    try:
        # The SDK method for GET /api/v2/conversations/webchat/{conversationId}
        response = webchat_api.get_conversation_webchat(conversation_id=conversation_id)
        return response.to_dict()
    except ApiClientException as e:
        print(f"Error fetching conversation {conversation_id}: {e.status_code} - {e.reason}")
        if e.status_code == 404:
            print("Conversation not found. Ensure it is a Web Messaging conversation.")
        elif e.status_code == 401:
            print("Authentication failed. Check OAuth scopes: conversation:webchat:read")
        raise

Step 3: Extract Participant Attributes

The response structure for a Web Messaging conversation looks like this:

{
  "id": "12345678-1234-1234-1234-123456789abc",
  "type": "webchat",
  "participants": [
    {
      "id": "participant-uuid-customer",
      "name": "Customer Name",
      "address": "webchat:customer:uuid",
      "role": "customer",
      "attributes": {
        "custom_field_1": "value1",
        "source_url": "https://example.com/support",
        "pre_chat_form_data": {
          "email": "user@example.com",
          "subject": "Billing Issue"
        }
      }
    },
    {
      "id": "participant-uuid-agent",
      "name": "Agent Name",
      "address": "user:uuid",
      "role": "agent",
      "attributes": {}
    }
  ]
}

You must iterate through the participants array to find the customer (role customer) and extract their attributes.

def extract_customer_attributes(conversation_data: dict) -> dict:
    """
    Parses the conversation object to find customer attributes.
    
    Args:
        conversation_data: The dictionary response from get_webchat_conversation.
        
    Returns:
        A dictionary of customer attributes, or empty dict if none found.
    """
    participants = conversation_data.get("participants", [])
    
    for participant in participants:
        # Identify the customer participant
        if participant.get("role") == "customer":
            attributes = participant.get("attributes", {})
            return attributes
            
    return {}

Step 4: Map Attributes to Architect Variables

In Genesys Cloud Architect, you cannot directly inject a complex JSON object into a simple variable. You must flatten the attributes or pass them as a JSON string that Architect can parse.

The most robust method is to set Conversation Attributes via the API. These attributes become available in Architect as sys.conversation.attributes.your_key.

from genesyscloud import ConversationApi

def set_conversation_attributes(conversation_id: str, attributes: dict):
    """
    Updates the conversation with custom attributes.
    These attributes will be available in Architect flows.
    
    Args:
        conversation_id: The UUID of the conversation.
        attributes: A dictionary of key-value pairs to set.
    """
    # We need to patch the conversation. 
    # Note: ConversationApi is generic, but for webchat, we often use the specific type API.
    # However, setting attributes is often done via the generic Conversation API 
    # or by updating the participant. 
    # The most reliable way to persist data for Architect is to update the 
    # conversation's 'attributes' field directly if supported, or use 
    # the 'patch' method on the conversation.
    
    # For Web Messaging, updating participant attributes is also an option, 
    # but conversation-level attributes are easier to access in Architect.
    
    conversation_api = ConversationApi(client)
    
    # Prepare the patch body
    # The body must be a ConversationPatchRequest
    patch_body = {
        "attributes": attributes
    }
    
    try:
        # PUT /api/v2/conversations/webchat/{conversationId}
        # Note: Some attribute updates require a PATCH, but the SDK often maps 
        # update operations to PUT for the full object or specific patch endpoints.
        # For simplicity in this tutorial, we use the ConversationWebchatApi update.
        
        # Re-initialize specific API for the update
        webchat_api = ConversationWebchatApi(client)
        
        # We must fetch the current object, modify it, and PUT it back,
        # OR use the patch endpoint if available in the SDK version.
        # The SDK provides `update_conversation_webchat`
        
        # Fetch current to preserve other fields
        current_conv = webchat_api.get_conversation_webchat(conversation_id=conversation_id)
        
        # Convert to dict to modify
        conv_dict = current_conv.to_dict()
        
        # Merge attributes
        if "attributes" not in conv_dict:
            conv_dict["attributes"] = {}
        
        conv_dict["attributes"].update(attributes)
        
        # Update the object
        updated_conv = ConversationWebchatApi.construct_from_object(conv_dict)
        
        # Perform the update
        webchat_api.update_conversation_webchat(
            conversation_id=conversation_id,
            body=updated_conv
        )
        
        print(f"Successfully set attributes for conversation {conversation_id}")
        
    except ApiClientException as e:
        print(f"Failed to update conversation: {e.status_code} - {e.reason}")
        raise

Step 5: Integrate into an Architect Flow

In Architect, you will create an API Action that calls your external service (or use a Genesys Cloud API Action if you host the logic within a Genesys Cloud integration).

1. Trigger: Inbound Web Messaging Message.
2. API Action: Call your endpoint (or use the Genesys Cloud API action to call /api/v2/conversations/webchat/{sys.conversation.id}).
3. Response Handler: Parse the JSON response.
4. Set Variable: Extract the specific attribute you need (e.g., response.attributes.pre_chat_form_data.email).
5. Use Variable: Use this variable in subsequent nodes (e.g., routing, IVR, or agent transfer).

If you are using the Genesys Cloud API Action directly within Architect (no external server):

1. Add an API Action node.
2. Set Method to GET.
3. Set Path to /api/v2/conversations/webchat/{sys.conversation.id}.
4. In the Response tab, map $.participants[?(@.role=='customer')].attributes to a flow variable customerAttributes.
5. Use customerAttributes.pre_chat_form_data.email in your flow.

Complete Working Example

This script demonstrates the full flow: authenticate, fetch conversation, extract attributes, and update the conversation with flattened attributes for easy Architect access.

import os
import json
import sys
from dotenv import load_dotenv
from genesyscloud import PlatformClient, Configuration, ConversationWebchatApi, ConversationApi
from genesyscloud.exceptions import ApiClientException

load_dotenv()

def main():
    # 1. Initialize Client
    config = Configuration(
        region=os.getenv("GENESYS_REGION"),
        client_id=os.getenv("GENESYS_CLIENT_ID"),
        client_secret=os.getenv("GENESYS_CLIENT_SECRET")
    )
    client = PlatformClient(config)
    webchat_api = ConversationWebchatApi(client)

    # 2. Define Conversation ID (Replace with actual ID or pass via CLI)
    conversation_id = sys.argv[1] if len(sys.argv) > 1 else os.getenv("TEST_CONVERSATION_ID")
    
    if not conversation_id:
        print("Error: No conversation ID provided.")
        print("Usage: python script.py <conversation_id>")
        sys.exit(1)

    print(f"Fetching conversation: {conversation_id}")

    try:
        # 3. Fetch Conversation
        response = webchat_api.get_conversation_webchat(conversation_id=conversation_id)
        conv_data = response.to_dict()

        # 4. Extract Customer Attributes
        participants = conv_data.get("participants", [])
        customer_attrs = {}
        
        for p in participants:
            if p.get("role") == "customer":
                customer_attrs = p.get("attributes", {})
                break
        
        if not customer_attrs:
            print("No customer attributes found.")
            return

        print("Raw Customer Attributes:")
        print(json.dumps(customer_attrs, indent=2))

        # 5. Flatten and Set Conversation Attributes for Architect
        # Architect can access these via sys.conversation.attributes.key
        new_attrs = {}
        
        # Example: Flatten nested pre_chat_form_data
        if "pre_chat_form_data" in customer_attrs:
            pre_chat = customer_attrs["pre_chat_form_data"]
            for key, value in pre_chat.items():
                # Create a namespaced key to avoid collisions
                new_attrs[f"prechat_{key}"] = value
        
        # Add other top-level attributes
        for key, value in customer_attrs.items():
            if key not in ["pre_chat_form_data"]:
                new_attrs[key] = value

        if new_attrs:
            # Update the conversation object
            # We must use the current object to avoid overwriting other fields
            current_conv = webchat_api.get_conversation_webchat(conversation_id=conversation_id)
            conv_dict = current_conv.to_dict()
            
            if "attributes" not in conv_dict:
                conv_dict["attributes"] = {}
            
            conv_dict["attributes"].update(new_attrs)
            
            # Convert back to SDK object
            updated_conv = ConversationWebchatApi.construct_from_object(conv_dict)
            
            # Perform Update
            webchat_api.update_conversation_webchat(
                conversation_id=conversation_id,
                body=updated_conv
            )
            
            print("\nSuccessfully updated conversation attributes.")
            print("In Architect, access these via:")
            for k in new_attrs:
                print(f"  sys.conversation.attributes.{k}")
        else:
            print("No new attributes to set.")

    except ApiClientException as e:
        print(f"API Error: {e.status_code} - {e.reason}")
        if e.status_code == 401:
            print("Check your OAuth scopes. Required: conversation:webchat:read, conversation:webchat:write")
    except Exception as e:
        print(f"Unexpected error: {e}")

if __name__ == "__main__":
    main()

Common Errors & Debugging

Error: 401 Unauthorized

• Cause: The OAuth token is invalid, expired, or missing required scopes.
• Fix: Verify GENESYS_CLIENT_ID and GENESYS_CLIENT_SECRET. Ensure the Service Account has the conversation:webchat:read scope. If you are updating attributes, ensure conversation:webchat:write is also included.

Error: 404 Not Found

• Cause: The conversationId is invalid or does not exist.
• Fix: Verify the conversation ID is a valid UUID. Ensure it is a Web Messaging conversation (type webchat). If you pass a Chat or Voice conversation ID to the Web Messaging API, it will return 404.

Error: 403 Forbidden

• Cause: The Service Account does not have permission to access the conversation.
• Fix: Ensure the Service Account has the correct security profile. Web Messaging conversations are often tied to specific queues. The Service Account must have visibility into those queues or the conversation itself.

Error: Attributes Not Visible in Architect

• Cause: You updated the participant attributes but not the conversation attributes, or you used the wrong variable reference.
• Fix: In Architect, participant attributes are accessed via sys.participant.attributes. Conversation attributes are accessed via sys.conversation.attributes. The tutorial above updates conversation attributes for broader accessibility. If you update participant attributes, ensure you reference the correct participant ID in Architect.

Error: Nested JSON Parsing Issues in Architect

• Cause: Architect does not automatically flatten deep JSON structures.
• Fix: Use the “Parse JSON” action in Architect or flatten the data in your API call (as shown in the Complete Working Example) before passing it to the flow.

Official References

• Genesys Cloud Python SDK Documentation
• Web Messaging API Reference
• Architect Flow Variables Reference
• OAuth 2.0 Client Credentials Flow