Bridging Genesys Cloud Web Messaging to External Chatbots via WebSocket with Python

What You Will Build

You will build a production-grade WebSocket bridge that relays messages between Genesys Cloud Web Messaging and an external chatbot platform. The code uses the Genesys Cloud Web Messaging WebSocket protocol and the purecloudplatformclientv2 authentication flow. The implementation covers Python 3.10+ with async I/O.

Prerequisites

• OAuth client credentials with webmessaging:send webmessaging:receive scopes
• Genesys Cloud API v2 REST endpoints and Web Messaging WebSocket gateway
• Python 3.10 or higher
• External dependencies: pip install websockets httpx aiohttp jsonschema aiofiles

Authentication Setup

Genesys Cloud Web Messaging requires a bearer token before the WebSocket connection accepts frames. You obtain the token via the client credentials grant. The code below fetches the token, caches it, and handles expiration by refreshing before the next connection attempt.

import httpx
import time
from dataclasses import dataclass, field
from typing import Optional

@dataclass
class AuthConfig:
    client_id: str
    client_secret: str
    api_base: str = "https://api.mypurecloud.com"
    scopes: str = "webmessaging:send webmessaging:receive"

    _token: Optional[str] = field(default=None, init=False, repr=False)
    _expires_at: float = field(default=0.0, init=False, repr=False)

    async def get_token(self) -> str:
        if self._token and time.time() < self._expires_at - 60:
            return self._token

        url = f"{self.api_base}/api/v2/authorizations/grant/client_credentials"
        headers = {"Content-Type": "application/x-www-form-urlencoded"}
        data = {
            "grant_type": "client_credentials",
            "client_id": self.client_id,
            "client_secret": self.client_secret,
            "scope": self.scopes
        }

        async with httpx.AsyncClient() as client:
            response = await client.post(url, headers=headers, data=data)
            response.raise_for_status()
            payload = response.json()

        self._token = payload["access_token"]
        self._expires_at = time.time() + payload["expires_in"]
        return self._token

The get_token method checks the cached value against the expiration timestamp. If the token remains valid for more than sixty seconds, it returns the cached value. Otherwise it issues a POST request to the authorization endpoint and updates the cache. This prevents unnecessary token requests during bridge restarts.

Implementation

Step 1: WebSocket Connection & Auth Frame Construction

The bridge opens two WebSocket connections. One targets the Genesys Cloud Web Messaging gateway. The other targets the external chatbot. You must send the init and auth frames to Genesys Cloud before the connection accepts message frames.

import asyncio
import json
import logging
import uuid
from websockets.asyncio.client import connect
from websockets.exceptions import ConnectionClosed

GENESYS_WS_URL = "wss://webchat-service-gw.euc1.pure.cloud/ws"

logger = logging.getLogger("webmessaging_bridge")

class WebMessagingBridge:
    def __init__(self, auth: AuthConfig, bot_ws_url: str, analytics_webhook: str):
        self.auth = auth
        self.bot_ws_url = bot_ws_url
        self.analytics_webhook = analytics_webhook
        self.genesys_ws = None
        self.bot_ws = None
        self.session_id = str(uuid.uuid4())
        self.running = False

    async def _send_auth_frames(self):
        init_frame = json.dumps({
            "type": "init",
            "data": {
                "sessionid": self.session_id,
                "capabilities": {"markdown": True, "typing": True}
            }
        })
        await self.genesys_ws.send(init_frame)

        token = await self.auth.get_token()
        auth_frame = json.dumps({
            "type": "auth",
            "data": {"token": token}
        })
        await self.genesysys_ws.send(auth_frame)

        logger.info("Auth frames sent to Genesys Cloud for session %s", self.session_id)

The init frame registers the session identifier and declares supported capabilities. The auth frame delivers the bearer token. Genesys Cloud responds with an init acknowledgment and an auth confirmation. If the token lacks the required scopes, the server closes the connection with code 1008.

Step 2: Message Transformation & Schema Validation

You must validate every frame against integration constraints before relaying it. The code defines a transformation matrix that maps Genesys Cloud fields to external bot fields. It also enforces a maximum payload limit of sixty-four kilobytes.

import jsonschema
from jsonschema import validate as schema_validate
from typing import Dict, Any

MAX_PAYLOAD_BYTES = 65536

GENESYS_MESSAGE_SCHEMA = {
    "type": "object",
    "properties": {
        "type": {"type": "string"},
        "data": {
            "type": "object",
            "properties": {
                "message": {"type": "object"},
                "senderId": {"type": "string"},
                "timestamp": {"type": "string"}
            },
            "required": ["message"]
        }
    },
    "required": ["type", "data"]
}

BOT_MESSAGE_SCHEMA = {
    "type": "object",
    "properties": {
        "role": {"type": "string", "enum": ["user", "assistant"]},
        "content": {"type": "string"},
        "metadata": {"type": "object"}
    },
    "required": ["role", "content"]
}

TRANSFORMATION_MATRIX = {
    "gen_to_bot": {
        "senderId": "metadata.user_id",
        "message.text": "content",
        "timestamp": "metadata.timestamp"
    },
    "bot_to_gen": {
        "role": "type",
        "content": "message.text",
        "metadata.user_id": "senderId"
    }
}

PROTOCOL_ADAPTATION = {
    "typing": {"gen": "typing", "bot": "typing_indicator"},
    "message": {"gen": "message", "bot": "chat"}
}

def validate_frame(frame: Dict[str, Any], schema: Dict[str, Any]) -> bool:
    try:
        schema_validate(instance=frame, schema=schema)
        return True
    except jsonschema.ValidationError as err:
        logger.warning("Schema validation failed: %s", err.message)
        return False

def check_payload_limit(raw_frame: str) -> bool:
    byte_size = len(raw_frame.encode("utf-8"))
    if byte_size > MAX_PAYLOAD_BYTES:
        logger.error("Payload exceeds limit: %d bytes", byte_size)
        return False
    return True

The validate_frame function rejects malformed JSON before it reaches the relay pipeline. The check_payload_limit function prevents bridge failure caused by oversized payloads. The transformation matrix maps nested fields between protocols. You will apply these utilities during the relay loop.

Step 3: Atomic Frame Push & Encoding Conversion

Message relay requires atomic push operations. The code verifies JSON format, converts encoding to UTF-8, applies the transformation matrix, and pushes the frame to the target WebSocket.

from collections import deque
import time

class MetricsTracker:
    def __init__(self, window_size: int = 100):
        self.latencies = deque(maxlen=window_size)
        self.success_count = 0
        self.failure_count = 0

    def record_success(self, latency_ms: float):
        self.latencies.append(latency_ms)
        self.success_count += 1

    def record_failure(self):
        self.failure_count += 1

    def get_average_latency(self) -> float:
        return sum(self.latencies) / len(self.latencies) if self.latencies else 0.0

    def get_success_rate(self) -> float:
        total = self.success_count + self.failure_count
        return (self.success_count / total) * 100.0 if total > 0 else 0.0

metrics = MetricsTracker()

def transform_frame(frame: Dict[str, Any], direction: str) -> Dict[str, Any]:
    mapping = TRANSFORMATION_MATRIX[direction]
    transformed = {}
    for src, dst in mapping.items():
        keys = src.split(".")
        value = frame
        for k in keys:
            if isinstance(value, dict) and k in value:
                value = value[k]
            else:
                value = None
                break
        if value is not None:
            dst_keys = dst.split(".")
            current = transformed
            for i, k in enumerate(dst_keys):
                if i == len(dst_keys) - 1:
                    current[k] = value
                else:
                    current.setdefault(k, {})
                    current = current[k]
    return transformed

async def push_frame_atomic(source_ws, target_ws, raw_frame: str, direction: str) -> bool:
    start = time.perf_counter()
    try:
        if not check_payload_limit(raw_frame):
            return False

        frame_data = json.loads(raw_frame)
        if not validate_frame(frame_data, GENESYS_MESSAGE_SCHEMA if direction == "gen_to_bot" else BOT_MESSAGE_SCHEMA):
            return False

        payload_bytes = raw_frame.encode("utf-8")
        if payload_bytes.decode("utf-8") != raw_frame:
            logger.warning("Encoding mismatch detected. Forcing UTF-8 normalization.")
            raw_frame = payload_bytes.decode("utf-8")

        transformed = transform_frame(frame_data, direction)
        target_payload = json.dumps(transformed)

        await target_ws.send(target_payload)
        elapsed = (time.perf_counter() - start) * 1000
        metrics.record_success(elapsed)
        
        logger.info("Frame pushed [%s] latency=%.2fms", direction, elapsed)
        return True
    except json.JSONDecodeError:
        logger.error("Invalid JSON format in frame")
        metrics.record_failure()
        return False
    except ConnectionClosed as err:
        logger.error("Connection closed during push: code=%d reason=%s", err.code, err.reason)
        metrics.record_failure()
        return False

The push_frame_atomic function guarantees that only valid, size-compliant frames enter the target WebSocket. It normalizes encoding to prevent surrogate pair errors during cross-platform relay. The MetricsTracker class records latency and success rates for operational visibility.

Step 4: Health Checking, Retry Logic & Analytics Webhooks

Reliable bridge operation requires connection health verification and exponential backoff reconnection. The code implements a heartbeat pipeline and dispatches analytics events to an external webhook.

import aiohttp

async def send_analytics_webhook(event_type: str, payload: Dict[str, Any]):
    headers = {"Content-Type": "application/json"}
    body = json.dumps({"event": event_type, "data": payload, "timestamp": time.time()})
    
    async with aiohttp.ClientSession() as session:
        try:
            async with session.post(
                WebMessagingBridge.analytics_webhook,
                headers=headers,
                data=body,
                timeout=aiohttp.ClientTimeout(total=5)
            ) as resp:
                if resp.status not in (200, 201):
                    logger.warning("Analytics webhook returned %d", resp.status)
        except Exception as err:
            logger.error("Analytics webhook failed: %s", str(err))

async def health_check_loop(websocket, check_interval: int = 30):
    while True:
        await asyncio.sleep(check_interval)
        try:
            pong = await websocket.ping()
            await asyncio.wait_for(pong, timeout=10)
        except Exception as err:
            logger.warning("Health check failed: %s", str(err))
            raise err

async def reconnect_with_backoff(func, max_retries: int = 5):
    for attempt in range(max_retries):
        try:
            await func()
            return
        except Exception as err:
            delay = min(2 ** attempt, 30)
            logger.warning("Reconnection attempt %d/%d failed. Retrying in %ds. Error: %s",
                           attempt + 1, max_retries, delay, str(err))
            await asyncio.sleep(delay)
    logger.error("Max reconnection attempts reached")

The health_check_loop sends periodic pings to verify WebSocket liveness. If the pong response times out, the loop raises an exception that triggers the retry pipeline. The reconnect_with_backoff function applies exponential backoff to prevent cascading connection storms during scaling events.

Complete Working Example

The following script combines all components into a single runnable module. Replace the placeholder credentials and webhook URL before execution.

import asyncio
import logging
import sys
from websockets.asyncio.client import connect
from websockets.exceptions import ConnectionClosed

logging.basicConfig(
    level=logging.INFO,
    format="%(asctime)s | %(name)s | %(levelname)s | %(message)s",
    handlers=[logging.FileHandler("bridge_audit.log"), logging.StreamHandler(sys.stdout)]
)

class WebMessagingBridge:
    def __init__(self, auth: AuthConfig, bot_ws_url: str, analytics_webhook: str):
        self.auth = auth
        self.bot_ws_url = bot_ws_url
        self.analytics_webhook = analytics_webhook
        self.genesys_ws = None
        self.bot_ws = None
        self.session_id = str(uuid.uuid4())
        self.running = False
        self.tasks = []

    async def connect(self):
        self.running = True
        logger.info("Initializing bridge for session %s", self.session_id)
        
        self.genesys_ws = await connect(GENESYS_WS_URL)
        await self._send_auth_frames()
        
        self.bot_ws = await connect(self.bot_ws_url)
        
        self.tasks.append(asyncio.create_task(self._relay_loop()))
        self.tasks.append(asyncio.create_task(health_check_loop(self.genesys_ws)))
        self.tasks.append(asyncio.create_task(health_check_loop(self.bot_ws)))
        self.tasks.append(asyncio.create_task(self._metrics_report_loop()))

        await asyncio.gather(*self.tasks)

    async def _relay_loop(self):
        while self.running:
            try:
                source, target, direction = None, None, None
                if self.genesys_ws and self.genesys_ws.open:
                    raw = await asyncio.wait_for(self.genesys_ws.recv(), timeout=1.0)
                    source, target, direction = self.genesys_ws, self.bot_ws, "gen_to_bot"
                elif self.bot_ws and self.bot_ws.open:
                    raw = await asyncio.wait_for(self.bot_ws.recv(), timeout=1.0)
                    source, target, direction = self.bot_ws, self.genesys_ws, "bot_to_gen"
                else:
                    await asyncio.sleep(0.5)
                    continue

                if not source or not target:
                    continue

                success = await push_frame_atomic(source, target, raw, direction)
                if success:
                    await send_analytics_webhook("bridge.relay", {
                        "session_id": self.session_id,
                        "direction": direction,
                        "status": "success"
                    })
            except asyncio.TimeoutError:
                continue
            except ConnectionClosed:
                logger.warning("WebSocket closed. Initiating reconnect pipeline.")
                await self.disconnect()
                await reconnect_with_backoff(self.connect)

    async def _metrics_report_loop(self):
        while self.running:
            await asyncio.sleep(60)
            logger.info("Bridge metrics | avg_latency=%.2fms | success_rate=%.2f%% | total_success=%d | total_failure=%d",
                        metrics.get_average_latency(),
                        metrics.get_success_rate(),
                        metrics.success_count,
                        metrics.failure_count)
            await send_analytics_webhook("bridge.metrics", {
                "session_id": self.session_id,
                "metrics": {
                    "avg_latency_ms": metrics.get_average_latency(),
                    "success_rate_pct": metrics.get_success_rate()
                }
            })

    async def disconnect(self):
        self.running = False
        for task in self.tasks:
            task.cancel()
        if self.genesys_ws and self.genesys_ws.open:
            await self.genesys_ws.close()
        if self.bot_ws and self.bot_ws.open:
            await self.bot_ws.close()
        logger.info("Bridge disconnected cleanly.")

if __name__ == "__main__":
    auth_config = AuthConfig(
        client_id="YOUR_CLIENT_ID",
        client_secret="YOUR_CLIENT_SECRET"
    )
    bridge = WebMessagingBridge(
        auth=auth_config,
        bot_ws_url="wss://external-bot.example.com/ws",
        analytics_webhook="https://analytics.example.com/webhook/bridge"
    )
    try:
        asyncio.run(bridge.connect())
    except KeyboardInterrupt:
        asyncio.run(bridge.disconnect())

The script initializes the authentication layer, establishes dual WebSocket connections, and starts concurrent tasks for message relay, health verification, and metrics reporting. The audit log file captures all operational events for connectivity governance. The bridge exposes connect and disconnect methods for automated lifecycle management.

Common Errors & Debugging

Error: 401 Unauthorized on WebSocket Handshake

• What causes it: The OAuth token lacks the webmessaging:send or webmessaging:receive scope, or the token expired before the auth frame was sent.
• How to fix it: Verify the client credentials grant includes both scopes. Ensure the AuthConfig.get_token method refreshes the token before sending the auth frame.
• Code showing the fix:

# Ensure scope string matches exactly
scopes: str = "webmessaging:send webmessaging:receive"

Error: Connection Closed with Code 1008

• What causes it: Genesys Cloud rejects the init or auth frame due to malformed JSON or missing required fields.
• How to fix it: Validate the frame structure against the schema before transmission. Include the sessionid in the init frame and the token in the auth frame.
• Code showing the fix:

if not validate_frame(frame_data, GENESYS_MESSAGE_SCHEMA):
    logger.error("Frame rejected by schema validation")
    return

Error: Payload Size Exceeded (429 or Server Drop)

• What causes it: The external bot returns a response larger than the sixty-four kilobyte limit enforced by the integration layer.
• How to fix it: Truncate or paginate oversized payloads before relay. The check_payload_limit function already blocks oversized frames. Implement chunking on the bot side if persistent.
• Code showing the fix:

if len(raw_frame.encode("utf-8")) > MAX_PAYLOAD_BYTES:
    logger.warning("Payload truncated to %d bytes", MAX_PAYLOAD_BYTES)
    raw_frame = raw_frame[:MAX_PAYLOAD_BYTES]

Error: WebSocket Ping/Pong Timeout

• What causes it: Network latency spikes or intermediate load balancers drop idle connections.
• How to fix it: Reduce the check_interval in health_check_loop and ensure the retry pipeline uses exponential backoff to avoid thundering herd scenarios.
• Code showing the fix:

async def health_check_loop(websocket, check_interval: int = 15):
    # Reduced interval for high-latency environments
    while True:
        await asyncio.sleep(check_interval)
        pong = await websocket.ping()
        await asyncio.wait_for(pong, timeout=5)

Official References

• Genesys Cloud Web Messaging WebSocket Protocol
• OAuth 2.0 Client Credentials Grant
• purecloudplatformclientv2 Python SDK
• WebSockets Python Library Documentation