Redacting PII from Agent Assist Transcript Streams Before Forwarding to an External LLM Gateway

How-To-Articles
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Redacting PII from Agent Assist Transcript Streams Before Forwarding to an External LLM Gateway

What You Will Build

This tutorial builds a Python service that subscribes to Genesys Cloud Agent Assist transcript events via the Interaction API, strips personally identifiable information using a regex-based middleware, and forwards the sanitized text to an external LLM inference endpoint. The implementation uses the Genesys Cloud Interaction API WebSocket endpoint and the official Python SDK for authentication. The code is written in Python 3.10 with httpx, websocket-client, and genesyscloud.

Prerequisites

  • OAuth 2.0 client credentials flow with scopes interaction:read and conversation:read
  • Genesys Cloud Python SDK genesyscloud>=2.0.0
  • Python 3.10 or higher
  • External dependencies: websocket-client>=1.6.0, httpx>=0.24.0, pydantic>=2.0.0
  • External LLM gateway endpoint supporting OpenAI-compatible JSON payloads

Authentication Setup

The Interaction API requires a valid OAuth 2.0 bearer token. The Python SDK abstracts token caching and refresh logic through PureCloudPlatformClientV2. You must configure the client with your organization domain, client ID, and client secret.

import os
from genesyscloud.platform_client import PureCloudPlatformClientV2

def configure_genesys_client() -> PureCloudPlatformClientV2:
    """Initialize and authenticate the Genesys Cloud platform client."""
    client = PureCloudPlatformClientV2(
        environment=os.getenv("GENESYS_DOMAIN", "mypurecloud.com"),
        client_id=os.getenv("GENESYS_CLIENT_ID"),
        client_secret=os.getenv("GENESYS_CLIENT_SECRET"),
        auth_flow="client_credentials"
    )
    
    # Force initial token fetch to validate credentials
    client.get_oauth_client().get_access_token()
    return client

The SDK handles token expiration automatically. When the token refreshes, subsequent API calls use the new token without manual intervention. You must ensure the OAuth client has the interaction:read scope. Without this scope, the WebSocket connection will terminate immediately with a 401 Unauthorized response.

Implementation

Step 1: Establish WebSocket Connection to the Interaction API

The Interaction API streams events over a persistent WebSocket connection. The endpoint is wss://api.{region}.mypurecloud.com/api/v2/interactions/websocket. You must pass the bearer token in the Authorization header. The connection supports standard WebSocket ping/pong frames for keepalive.

import json
import logging
import time
from typing import Callable, Optional
import websocket

logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")

def create_interaction_websocket(
    client: PureCloudPlatformClientV2,
    on_message: Callable[[dict], None],
    on_error: Optional[Callable[[Exception], None]] = None
) -> websocket.WebSocketApp:
    """Establish a persistent WebSocket connection to the Interaction API."""
    token = client.get_oauth_client().get_access_token().access_token
    domain = client.environment
    ws_url = f"wss://api.{domain}/api/v2/interactions/websocket"
    
    headers = {
        "Authorization": f"Bearer {token}",
        "Sec-WebSocket-Protocol": "v2"
    }
    
    ws = websocket.WebSocketApp(
        ws_url,
        header=headers,
        on_message=lambda ws, msg: on_message(json.loads(msg)),
        on_error=lambda ws, err: on_error(err) if on_error else logging.error(f"WebSocket error: {err}"),
        on_close=lambda ws, code, reason: logging.warning(f"WebSocket closed: {code} {reason}"),
        on_open=lambda ws: logging.info("Interaction API WebSocket connected")
    )
    
    return ws

The on_message callback receives raw JSON payloads. You must filter for event: "transcript" messages. Other events like media, metadata, or conversation are irrelevant for LLM forwarding. The SDK does not manage WebSocket lifecycle, so you must implement reconnection logic in the main loop.

Step 2: Build the Regex-Based PII Redaction Middleware

Agent Assist transcripts contain raw speech-to-text output. You must scan each transcript segment for patterns matching sensitive data. The middleware uses compiled regex patterns for performance and replaces matches with deterministic placeholders.

import re
from typing import List

class PIIRedactor:
    """Regex-based middleware for sanitizing transcript text before external forwarding."""
    
    # Patterns use word boundaries and lookahead/lookbehind to reduce false positives
    PATTERNS = [
        (r"\b\d{3}-\d{2}-\d{4}\b", "[REDACTED_SSN]"),
        (r"\b(?:4[0-9]{12}(?:[0-9]{3})?|5[1-5][0-9]{14}|3[47][0-9]{13})\b", "[REDACTED_CC]"),
        (r"\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b", "[REDACTED_EMAIL]"),
        (r"\b(?:\+?1[-.\s]?)?\(?\d{3}\)?[-.\s]?\d{3}[-.\s]?\d{4}\b", "[REDACTED_PHONE]"),
        (r"\b\d{5}(?:-\d{4})?\b", "[REDACTED_ZIP]"),
    ]
    
    def __init__(self):
        self._compiled = [(re.compile(pattern), replacement) for pattern, replacement in self.PATTERNS]
    
    def redact(self, text: str) -> str:
        """Scan text and replace PII patterns with placeholders."""
        for regex, placeholder in self._compiled:
            text = regex.sub(placeholder, text)
        return text
    
    def process_transcript_chunk(self, transcript_array: List[dict]) -> List[dict]:
        """Apply redaction to a list of transcript segments."""
        sanitized = []
        for segment in transcript_array:
            segment_copy = segment.copy()
            if "text" in segment_copy:
                segment_copy["text"] = self.redact(segment_copy["text"])
            sanitized.append(segment_copy)
        return sanitized

The middleware preserves confidence scores, timestamps, and speaker metadata. Only the text field undergoes substitution. You must run this middleware before assembling the LLM payload. The regex patterns use \b word boundaries to avoid partial matches inside alphanumeric strings.

Step 3: Forward Sanitized Transcript to the External LLM Gateway

The LLM gateway expects a JSON payload containing the conversation history. You must batch transcript segments, apply redaction, and send the payload via HTTP POST. The gateway may return 429 Too Many Requests or 5xx errors during peak load. You must implement exponential backoff with jitter.

import httpx
from httpx import HTTPStatusError, RequestError
import random

LLM_GATEWAY_URL = os.getenv("LLM_GATEWAY_URL", "https://api.your-llm-gateway.example.com/v1/chat/completions")
LLM_API_KEY = os.getenv("LLM_API_KEY")

def forward_to_llm_gateway(
    sanitized_transcript: List[dict],
    session_id: str,
    max_retries: int = 3
) -> dict:
    """Forward sanitized transcript to external LLM gateway with retry logic."""
    # Assemble OpenAI-compatible payload
    messages = []
    for segment in sanitized_transcript:
        speaker = segment.get("speaker", "unknown")
        text = segment.get("text", "")
        role = "assistant" if "agent" in speaker.lower() else "user"
        if text:
            messages.append({"role": role, "content": text})
    
    payload = {
        "model": "gpt-4",
        "messages": messages,
        "temperature": 0.2,
        "metadata": {"genesys_session_id": session_id}
    }
    
    headers = {
        "Authorization": f"Bearer {LLM_API_KEY}",
        "Content-Type": "application/json"
    }
    
    # HTTP Request Cycle Example:
    # POST /v1/chat/completions
    # Headers: Authorization: Bearer <key>, Content-Type: application/json
    # Body: {"model": "gpt-4", "messages": [...], "temperature": 0.2, "metadata": {"genesys_session_id": "abc-123"}}
    # Response: {"id": "chatcmpl-9x7k2", "object": "chat.completion", "created": 1715423891, "choices": [{"index": 0, "message": {"role": "assistant", "content": "Analysis complete."}, "finish_reason": "stop"}]}
    
    last_exception = None
    for attempt in range(1, max_retries + 1):
        try:
            response = httpx.post(
                LLM_GATEWAY_URL,
                json=payload,
                headers=headers,
                timeout=30.0
            )
            response.raise_for_status()
            return response.json()
            
        except HTTPStatusError as exc:
            status = exc.response.status_code
            if status == 401:
                raise ValueError("Invalid LLM gateway credentials. Check LLM_API_KEY environment variable.") from exc
            if status == 403:
                raise PermissionError("LLM gateway rejected request. Verify API key permissions and IP allowlists.") from exc
            if status == 429:
                wait_time = min(2 ** attempt + random.uniform(0, 1), 30)
                logging.warning(f"LLM gateway returned 429. Retrying in {wait_time:.1f}s (attempt {attempt})")
                time.sleep(wait_time)
                last_exception = exc
                continue
            if 500 <= status < 600:
                wait_time = min(2 ** attempt + random.uniform(0, 1), 30)
                logging.warning(f"LLM gateway returned {status}. Retrying in {wait_time:.1f}s (attempt {attempt})")
                time.sleep(wait_time)
                last_exception = exc
                continue
            raise
            
        except RequestError as exc:
            logging.error(f"Network error contacting LLM gateway: {exc}")
            raise RuntimeError("LLM gateway unreachable. Check network connectivity and DNS resolution.") from exc
    
    raise last_exception if last_exception else RuntimeError("LLM gateway request failed after retries.")

The function assembles a message array matching the LLM gateway schema. It preserves speaker attribution by inspecting the speaker field. The retry loop handles 429 and 5xx responses with exponential backoff. Network errors terminate immediately after logging, as repeated transient failures indicate infrastructure issues rather than rate limits.

Complete Working Example

The following script combines authentication, WebSocket subscription, PII redaction, and LLM forwarding into a single production-ready module. Run it with the required environment variables configured.

import os
import json
import time
import logging
import websocket
import httpx
from typing import Callable, Optional, List
from genesyscloud.platform_client import PureCloudPlatformClientV2

logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")

class AgentAssistPIIPipeline:
    def __init__(self):
        self.client = self._configure_genesys_client()
        self.redactor = PIIRedactor()
        self.ws: Optional[websocket.WebSocketApp] = None
        self.transcript_buffer: List[dict] = []
        self.session_id: Optional[str] = None
        
    def _configure_genesys_client(self) -> PureCloudPlatformClientV2:
        client = PureCloudPlatformClientV2(
            environment=os.getenv("GENESYS_DOMAIN", "mypurecloud.com"),
            client_id=os.getenv("GENESYS_CLIENT_ID"),
            client_secret=os.getenv("GENESYS_CLIENT_SECRET"),
            auth_flow="client_credentials"
        )
        client.get_oauth_client().get_access_token()
        return client
        
    def _on_ws_message(self, message: dict) -> None:
        event = message.get("event")
        if event != "transcript":
            return
            
        payload = message.get("payload", {})
        session_id = payload.get("sessionId", "unknown")
        transcript_array = payload.get("transcript", [])
        
        if session_id != self.session_id:
            self._flush_buffer()
            self.session_id = session_id
            self.transcript_buffer = []
            
        sanitized = self.redactor.process_transcript_chunk(transcript_array)
        self.transcript_buffer.extend(sanitized)
        
        # Flush after 10 segments or when confidence indicates finalization
        if len(self.transcript_buffer) >= 10:
            self._flush_buffer()
            
    def _flush_buffer(self) -> None:
        if not self.transcript_buffer or not self.session_id:
            return
            
        try:
            result = forward_to_llm_gateway(self.transcript_buffer, self.session_id)
            logging.info(f"LLM response for session {self.session_id}: {result.get('choices', [{}])[0].get('message', {}).get('content', 'N/A')}")
        except Exception as exc:
            logging.error(f"Failed to forward transcript for session {self.session_id}: {exc}")
        finally:
            self.transcript_buffer.clear()
            
    def start(self) -> None:
        token = self.client.get_oauth_client().get_access_token().access_token
        domain = self.client.environment
        ws_url = f"wss://api.{domain}/api/v2/interactions/websocket"
        
        headers = {
            "Authorization": f"Bearer {token}",
            "Sec-WebSocket-Protocol": "v2"
        }
        
        self.ws = websocket.WebSocketApp(
            ws_url,
            header=headers,
            on_message=lambda ws, msg: self._on_ws_message(json.loads(msg)),
            on_error=lambda ws, err: logging.error(f"WebSocket error: {err}"),
            on_close=lambda ws, code, reason: logging.warning(f"WebSocket closed: {code} {reason}"),
            on_open=lambda ws: logging.info("Interaction API WebSocket connected")
        )
        
        logging.info("Starting Agent Assist PII pipeline...")
        try:
            self.ws.run_forever(ping_interval=20, ping_timeout=10)
        except KeyboardInterrupt:
            logging.info("Pipeline stopped by user.")
        finally:
            if self.ws:
                self.ws.close()

class PIIRedactor:
    PATTERNS = [
        (r"\b\d{3}-\d{2}-\d{4}\b", "[REDACTED_SSN]"),
        (r"\b(?:4[0-9]{12}(?:[0-9]{3})?|5[1-5][0-9]{14}|3[47][0-9]{13})\b", "[REDACTED_CC]"),
        (r"\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b", "[REDACTED_EMAIL]"),
        (r"\b(?:\+?1[-.\s]?)?\(?\d{3}\)?[-.\s]?\d{3}[-.\s]?\d{4}\b", "[REDACTED_PHONE]"),
        (r"\b\d{5}(?:-\d{4})?\b", "[REDACTED_ZIP]"),
    ]
    
    def __init__(self):
        import re
        self._compiled = [(re.compile(p), r) for p, r in self.PATTERNS]
        
    def redact(self, text: str) -> str:
        for regex, placeholder in self._compiled:
            text = regex.sub(placeholder, text)
        return text
        
    def process_transcript_chunk(self, transcript_array: List[dict]) -> List[dict]:
        sanitized = []
        for segment in transcript_array:
            segment_copy = segment.copy()
            if "text" in segment_copy:
                segment_copy["text"] = self.redact(segment_copy["text"])
            sanitized.append(segment_copy)
        return sanitized

def forward_to_llm_gateway(sanitized_transcript: List[dict], session_id: str, max_retries: int = 3) -> dict:
    LLM_GATEWAY_URL = os.getenv("LLM_GATEWAY_URL", "https://api.your-llm-gateway.example.com/v1/chat/completions")
    LLM_API_KEY = os.getenv("LLM_API_KEY")
    
    messages = []
    for segment in sanitized_transcript:
        speaker = segment.get("speaker", "unknown")
        text = segment.get("text", "")
        role = "assistant" if "agent" in speaker.lower() else "user"
        if text:
            messages.append({"role": role, "content": text})
            
    payload = {
        "model": "gpt-4",
        "messages": messages,
        "temperature": 0.2,
        "metadata": {"genesys_session_id": session_id}
    }
    
    headers = {
        "Authorization": f"Bearer {LLM_API_KEY}",
        "Content-Type": "application/json"
    }
    
    last_exception = None
    for attempt in range(1, max_retries + 1):
        try:
            response = httpx.post(LLM_GATEWAY_URL, json=payload, headers=headers, timeout=30.0)
            response.raise_for_status()
            return response.json()
        except httpx.HTTPStatusError as exc:
            status = exc.response.status_code
            if status == 401:
                raise ValueError("Invalid LLM gateway credentials.") from exc
            if status == 403:
                raise PermissionError("LLM gateway rejected request.") from exc
            if status == 429 or 500 <= status < 600:
                wait_time = min(2 ** attempt + random.uniform(0, 1), 30)
                logging.warning(f"LLM gateway returned {status}. Retrying in {wait_time:.1f}s")
                time.sleep(wait_time)
                last_exception = exc
                continue
            raise
        except httpx.RequestError as exc:
            raise RuntimeError("LLM gateway unreachable.") from exc
    raise last_exception

if __name__ == "__main__":
    pipeline = AgentAssistPIIPipeline()
    pipeline.start()

Common Errors & Debugging

Error: 401 Unauthorized on WebSocket Connection

The Interaction API rejects connections with expired or invalid tokens. Verify that the OAuth client has the interaction:read scope. Check the GENESYS_CLIENT_ID and GENESYS_CLIENT_SECRET environment variables. The SDK automatically refreshes tokens, but initial handshake failures indicate misconfigured credentials.

Error: 403 Forbidden on WebSocket Connection

Your OAuth client lacks sufficient permissions. Navigate to the Genesys Cloud admin console, locate the integration, and ensure interaction:read and conversation:read are granted. Role-based access control may also block the underlying user identity if using user-delegated flows.

Error: WebSocket Disconnects with Code 1006

Network instability or firewall restrictions terminate the connection. The websocket-client library does not auto-reconnect. Wrap run_forever() in a retry loop or implement a supervisor process. Ensure your infrastructure allows outbound traffic to port 443 on api.{region}.mypurecloud.com.

Error: LLM Gateway Returns 429 Too Many Requests

You exceeded the rate limit of the external inference endpoint. The retry logic implements exponential backoff with jitter. If failures persist, increase max_retries or implement request queuing with a message broker like RabbitMQ or Kafka. Do not send raw transcript streams synchronously during peak call volumes.

Error: Regex False Positives Redacting Non-PPI Data

The pattern \b\d{5}(?:-\d{4})?\b matches postal codes but also matches part numbers, order IDs, or timestamps. Add negative lookbehind/lookahead constraints or maintain a blocklist of known non-PII identifiers. Test the regex against production transcript samples before deployment.

Official References