How to Access Participant Attributes Set by Web Messaging in Architect

What You Will Build

• A Python script that configures a Web Messaging channel to persist custom attributes in the conversationData payload.
• An Architect flow definition that extracts these specific attributes using the getConversation API and conditional logic.
• A verification routine that simulates an inbound message and confirms the attributes are accessible within the flow context.

Prerequisites

• OAuth Client Type: Client Credentials Grant.
• Required Scopes:
  • webchat:write (to configure channel settings)
  • flow:write (to create/update Architect flows)
  • conversation:read (to inspect conversation data during debugging)
• SDK Version: Genesys Cloud SDK for Python (genesyscloud v3.0+).
• Runtime: Python 3.9+.
• Dependencies: genesyscloud, httpx (for raw API calls if SDK gaps exist), pydantic (for validation).

Authentication Setup

The Genesys Cloud Python SDK handles OAuth token acquisition and refresh automatically when initialized with a Client ID and Client Secret. You must ensure the OAuth application in the Genesys Cloud Admin Console has the webchat:write and flow:write scopes enabled.

import os
from genesyscloud import Configuration, ApiClient
from genesyscloud.webchat.api import webchat_api
from genesyscloud.flows.api import flows_api

def get_authenticated_client():
    """
    Initializes a fully authenticated Genesys Cloud API client.
    Raises an exception if credentials are missing or invalid.
    """
    client_id = os.getenv("GENESYS_CLIENT_ID")
    client_secret = os.getenv("GENESYS_CLIENT_SECRET")
    region = os.getenv("GENESYS_REGION", "us-east-1")

    if not client_id or not client_secret:
        raise ValueError("GENESYS_CLIENT_ID and GENESYS_CLIENT_SECRET environment variables are required.")

    config = Configuration(
        base_url=f"https://{region}.mygenesys.com/api/v2",
        oauth_client_id=client_id,
        oauth_client_secret=client_secret
    )

    # The SDK manages token refresh in the background
    api_client = ApiClient(configuration=config)
    return api_client

# Initialize the client
api_client = get_authenticated_client()
webchat_instance = webchat_api.WebchatApi(api_client)
flows_instance = flows_api.FlowsApi(api_client)

Implementation

Step 1: Configure Web Messaging to Persist Attributes

By default, Genesys Cloud Web Messaging does not automatically persist all custom attributes sent by the frontend into the conversationData object available to Architect. You must explicitly define which attributes are allowed to pass through. This is done by configuring the webchat channel’s attributes settings.

The frontend sends attributes via the genesys.cloud.webchat.start event or the genesys.cloud.webchat.message event. To make these available in Architect, they must be whitelisted in the channel configuration.

from genesyscloud.webchat.models import WebchatChannelConfiguration

def configure_webchat_attributes(channel_id: str):
    """
    Updates the Web Messaging channel configuration to allow specific custom attributes.
    
    Args:
        channel_id: The UUID of the Web Messaging channel.
    """
    # Retrieve current configuration to avoid overwriting other settings
    try:
        existing_config = webchat_instance.get_webchat_channel(channel_id)
    except Exception as e:
        print(f"Error fetching channel: {e}")
        return

    # Define the attributes you want to access in Architect
    # These keys must match exactly what the frontend sends
    allowed_attributes = [
        {"name": "customer_segment", "type": "string"},
        {"name": "order_id", "type": "string"},
        {"name": "priority_level", "type": "integer"}
    ]

    # Update the configuration
    # Note: The exact structure depends on the SDK version. 
    # In newer versions, this is part of the channel's 'settings' or 'attributes' block.
    
    # We construct a patch payload for the channel settings
    # The key 'webchat' contains the channel-specific config
    channel_config_patch = {
        "settings": {
            "webchat": {
                "attributes": {
                    "allowed": [attr["name"] for attr in allowed_attributes]
                }
            }
        }
    }

    # Apply the patch
    try:
        webchat_instance.patch_webchat_channel(
            channel_id=channel_id,
            body=channel_config_patch
        )
        print(f"Successfully configured attributes for channel {channel_id}")
    except Exception as e:
        print(f"Failed to update channel configuration: {e}")

# Usage:
# configure_webchat_attributes("your-channel-uuid-here")

Why this step is critical: If you do not whitelist the attribute name in the channel configuration, Genesys Cloud strips it from the conversationData payload for security and privacy reasons. The Architect flow will see an empty conversationData object or missing keys, resulting in null values.

Step 2: Create an Architect Flow with Attribute Extraction

Now that the attributes are persisted, you must create an Architect flow that reads them. The most robust way to access conversation-level data in Architect is using the Get Conversation Details element. This element populates the flow context with the current conversation’s metadata, including conversationData.

We will use the flows_api to create a simple flow that:

1. Triggers on an inbound message.
2. Retrieves conversation details.
3. Uses a Condition element to check the customer_segment attribute.
4. Routes based on the value.

from genesyscloud.flows.models import (
    Flow,
    FlowSettings,
    FlowType,
    ConversationFlowTrigger,
    ConversationFlowTriggerType,
    GetConversationDetailsElement,
    ConditionElement,
    RouteToQueueElement,
    EndConversationElement
)

def create_architect_flow(channel_id: str, queue_id: str, priority_queue_id: str):
    """
    Creates an Architect flow that accesses Web Messaging attributes.
    """
    # 1. Define the Trigger
    trigger = ConversationFlowTrigger(
        type_=ConversationFlowTriggerType.webchat,
        channel_id=channel_id
    )

    # 2. Define the Get Conversation Details Element
    # This element fetches the conversation data into the flow context
    get_convo_element = GetConversationDetailsElement(
        name="Get Conversation Details",
        type_="getconversationdetails",
        ref_id="get_convo_ref",
        next_element="check_segment"
    )

    # 3. Define the Condition Element
    # We check if customer_segment equals "vip"
    # Note: In Architect JSON, we reference the conversationData directly
    condition_element = ConditionElement(
        name="Check Customer Segment",
        type_="condition",
        ref_id="check_segment",
        conditions=[
            {
                "type": "equal",
                "value": {
                    "type": "string",
                    "value": "vip"
                },
                "expression": {
                    "type": "string",
                    "value": "conversationData.customer_segment"
                }
            }
        ],
        default_next_element="route_standard",
        true_next_element="route_vip"
    )

    # 4. Define Routing Elements
    route_vip = RouteToQueueElement(
        name="Route to VIP Queue",
        type_="routetoqueue",
        ref_id="route_vip",
        queue_id=priority_queue_id,
        next_element="end_convo"
    )

    route_standard = RouteToQueueElement(
        name="Route to Standard Queue",
        type_="routetoqueue",
        ref_id="route_standard",
        queue_id=queue_id,
        next_element="end_convo"
    )

    # 5. Define End Element
    end_convo = EndConversationElement(
        name="End Conversation",
        type_="endconversation",
        ref_id="end_convo"
    )

    # 6. Assemble the Flow
    flow = Flow(
        name="WebChat Attribute Routing Flow",
        description="Routes based on customer_segment from Web Messaging",
        type_=FlowType.conversation,
        enabled=True,
        settings=FlowSettings(
            conversation_flow_trigger=trigger,
            default_outcome="queue"
        ),
        elements={
            "get_convo_ref": get_convo_element,
            "check_segment": condition_element,
            "route_vip": route_vip,
            "route_standard": route_standard,
            "end_convo": end_convo
        },
        start_element="get_convo_ref"
    )

    try:
        created_flow = flows_instance.post_flow(body=flow)
        print(f"Flow created successfully with ID: {created_flow.id}")
        return created_flow.id
    except Exception as e:
        print(f"Failed to create flow: {e}")
        return None

# Usage:
# flow_id = create_architect_flow("channel-uuid", "standard-queue-uuid", "vip-queue-uuid")

Key Implementation Detail: The expression "conversationData.customer_segment" is the exact syntax Genesys Cloud expects in Architect condition blocks. The Get Conversation Details element ensures that conversationData is populated with the latest attributes from the Web Messaging session. Without this element, the flow context might not have the most recent conversationData snapshot.

Step 3: Verify Attribute Persistence via API

To confirm that the attributes are correctly flowing from the Web Messaging channel into the conversation data, you can simulate a message or inspect an existing conversation. This step uses the conversations_api to read the conversationData payload.

from genesyscloud.conversations.api import conversations_api
import json

def verify_conversation_data(conversation_id: str):
    """
    Retrieves the conversation data for a given conversation ID to verify attributes.
    """
    try:
        # Get the full conversation details
        conversation = conversations_api.get_conversation(
            conversation_id=conversation_id,
            expand=["participants", "wrapup", "data"]
        )
        
        # Extract conversationData
        if hasattr(conversation, 'data') and conversation.data:
            print("Conversation Data Payload:")
            print(json.dumps(conversation.data.to_dict(), indent=2))
            
            # Check for specific attributes
            if 'customer_segment' in conversation.data.to_dict():
                print(f"Verified: customer_segment = {conversation.data['customer_segment']}")
            else:
                print("Warning: customer_segment not found in conversationData.")
        else:
            print("No conversationData found in this conversation.")
            
    except Exception as e:
        print(f"Error retrieving conversation data: {e}")

# Usage:
# verify_conversation_data("your-conversation-uuid")

Expected Response Structure:
The conversationData object in the response will look like this:

{
  "id": "conversation-uuid",
  "type": "webchat",
  "data": {
    "customer_segment": "vip",
    "order_id": "12345",
    "priority_level": 5
  },
  "participants": [...]
}

If the attributes are missing from this data object, re-check the channel configuration in Step 1. Ensure the attribute names are case-sensitive matches.

Complete Working Example

This script combines all steps into a single executable module. It assumes you have already created the Web Messaging channel and Queues in Genesys Cloud.

import os
import json
from genesyscloud import Configuration, ApiClient
from genesyscloud.webchat.api import webchat_api
from genesyscloud.flows.api import flows_api
from genesyscloud.conversations.api import conversations_api
from genesyscloud.flows.models import (
    Flow,
    FlowSettings,
    FlowType,
    ConversationFlowTrigger,
    ConversationFlowTriggerType,
    GetConversationDetailsElement,
    ConditionElement,
    RouteToQueueElement,
    EndConversationElement
)

def main():
    # 1. Authenticate
    client_id = os.getenv("GENESYS_CLIENT_ID")
    client_secret = os.getenv("GENESYS_CLIENT_SECRET")
    region = os.getenv("GENESYS_REGION", "us-east-1")

    config = Configuration(
        base_url=f"https://{region}.mygenesys.com/api/v2",
        oauth_client_id=client_id,
        oauth_client_secret=client_secret
    )
    api_client = ApiClient(configuration=config)
    
    webchat_instance = webchat_api.WebchatApi(api_client)
    flows_instance = flows_api.FlowsApi(api_client)
    convos_instance = conversations_api.ConversationsApi(api_client)

    # Configuration Values
    CHANNEL_ID = os.getenv("GENESYS_WEBCHAT_CHANNEL_ID")
    STANDARD_QUEUE_ID = os.getenv("GENESYS_STANDARD_QUEUE_ID")
    VIP_QUEUE_ID = os.getenv("GENESYS_VIP_QUEUE_ID")

    if not all([CHANNEL_ID, STANDARD_QUEUE_ID, VIP_QUEUE_ID]):
        print("Missing required environment variables.")
        return

    # 2. Configure Channel Attributes
    print(f"Configuring channel {CHANNEL_ID}...")
    channel_config_patch = {
        "settings": {
            "webchat": {
                "attributes": {
                    "allowed": ["customer_segment", "order_id", "priority_level"]
                }
            }
        }
    }
    try:
        webchat_instance.patch_webchat_channel(CHANNEL_ID, body=channel_config_patch)
        print("Channel attributes configured.")
    except Exception as e:
        print(f"Channel config error: {e}")
        return

    # 3. Create Architect Flow
    print("Creating Architect Flow...")
    
    trigger = ConversationFlowTrigger(
        type_=ConversationFlowTriggerType.webchat,
        channel_id=CHANNEL_ID
    )

    get_convo_element = GetConversationDetailsElement(
        name="Get Conversation Details",
        type_="getconversationdetails",
        ref_id="get_convo_ref",
        next_element="check_segment"
    )

    condition_element = ConditionElement(
        name="Check Customer Segment",
        type_="condition",
        ref_id="check_segment",
        conditions=[
            {
                "type": "equal",
                "value": {"type": "string", "value": "vip"},
                "expression": {"type": "string", "value": "conversationData.customer_segment"}
            }
        ],
        default_next_element="route_standard",
        true_next_element="route_vip"
    )

    route_vip = RouteToQueueElement(
        name="Route to VIP Queue",
        type_="routetoqueue",
        ref_id="route_vip",
        queue_id=VIP_QUEUE_ID,
        next_element="end_convo"
    )

    route_standard = RouteToQueueElement(
        name="Route to Standard Queue",
        type_="routetoqueue",
        ref_id="route_standard",
        queue_id=STANDARD_QUEUE_ID,
        next_element="end_convo"
    )

    end_convo = EndConversationElement(
        name="End Conversation",
        type_="endconversation",
        ref_id="end_convo"
    )

    flow = Flow(
        name="WebChat Attribute Routing Demo",
        description="Routes based on customer_segment from Web Messaging",
        type_=FlowType.conversation,
        enabled=True,
        settings=FlowSettings(
            conversation_flow_trigger=trigger,
            default_outcome="queue"
        ),
        elements={
            "get_convo_ref": get_convo_element,
            "check_segment": condition_element,
            "route_vip": route_vip,
            "route_standard": route_standard,
            "end_convo": end_convo
        },
        start_element="get_convo_ref"
    )

    try:
        created_flow = flows_instance.post_flow(body=flow)
        print(f"Flow created: {created_flow.id}")
    except Exception as e:
        print(f"Flow creation error: {e}")

if __name__ == "__main__":
    main()

Common Errors & Debugging

Error: 400 Bad Request - Invalid Attribute Name

• Cause: The attribute name contains special characters or spaces not allowed by Genesys Cloud. Attribute names must be alphanumeric with underscores.
• Fix: Rename the attribute in your frontend code and channel configuration to use only a-z, 0-9, and _.

Error: 403 Forbidden - Insufficient Scopes

• Cause: The OAuth client used in the script does not have the webchat:write or flow:write scope.
• Fix: Go to the Genesys Cloud Admin Console, navigate to Admin > Integrations > OAuth, select your client, and add the missing scopes. Regenerate the Client Secret if necessary.

Error: Attribute Not Found in Architect

• Cause: The Get Conversation Details element is missing from the flow, or the attribute was not whitelisted in the channel configuration.
• Fix: Ensure the flow starts with a Get Conversation Details element. Verify the channel configuration includes the attribute name in the allowed list. Check the frontend code to ensure the attribute is sent with the correct key name.

Error: 429 Too Many Requests

• Cause: The script is making too many API calls in a short period.
• Fix: Implement exponential backoff in your API calls. The Genesys Cloud Python SDK does not handle retries automatically, so you must wrap API calls in a retry loop.

import time

def api_call_with_retry(func, *args, max_retries=3, **kwargs):
    for attempt in range(max_retries):
        try:
            return func(*args, **kwargs)
        except Exception as e:
            if "429" in str(e) and attempt < max_retries - 1:
                wait_time = 2 ** attempt
                print(f"Rate limited. Retrying in {wait_time} seconds...")
                time.sleep(wait_time)
            else:
                raise e

Official References

• Genesys Cloud Web Messaging API Documentation
• Genesys Cloud Architect Flow API Documentation
• Genesys Cloud SDK for Python
• Web Messaging Channel Configuration