Handling Genesys Cloud Webchat File Uploads via WebSocket with Node.js
What You Will Build
- A Node.js service that streams files to Genesys Cloud Webchat via WebSocket, validates MIME types and malware signatures, chunks binary data with checksum verification, tracks latency, and syncs completion events to an external document management system.
- This uses the Genesys Cloud Webchat WebSocket protocol and the
wslibrary for streaming. - The tutorial covers JavaScript with modern async/await patterns and JSDoc type annotations.
Prerequisites
- OAuth client type: Confidential client (client credentials flow) or Webchat deployment token. Required scopes:
webchat:write,conversation:read. - SDK/API version: Genesys Cloud Webchat WebSocket protocol v2, Node.js
wsv8.16+,axiosv1.6+ - Runtime: Node.js 18 LTS or newer
- External dependencies:
ws,axios,mime-types,crypto(built-in),uuid(v9) - Environment variables:
GENESYS_OAUTH_CLIENT_ID,GENESYS_OAUTH_CLIENT_SECRET,GENESYS_ORGANIZATION_ID,GENESYS_DEPLOYMENT_ID,GENESYS_REGION(e.g.,mypurecloud.com)
Authentication Setup
Genesys Cloud Webchat requires a JWT token for the initial auth message. You obtain this token via the OAuth2 client credentials flow. The following code implements token acquisition with exponential backoff for 429 rate-limit responses and automatic caching with refresh logic.
import axios from 'axios';
import { setTimeout } from 'timers/promises';
/**
* @typedef {Object} OAuthConfig
* @property {string} clientId
* @property {string} clientSecret
* @property {string} region
*/
/**
* Manages OAuth2 token lifecycle with 429 retry logic
*/
class TokenManager {
/**
* @param {OAuthConfig} config
*/
constructor(config) {
this.config = config;
this.token = null;
this.expiresAt = 0;
this.retryAttempts = 0;
this.maxRetries = 3;
}
/**
* Fetches or refreshes the OAuth token
* @returns {Promise<string>}
*/
async getToken() {
if (this.token && Date.now() < this.expiresAt) {
return this.token;
}
const url = `https://api.${this.config.region}/api/v2/oauth/token`;
const headers = {
'Content-Type': 'application/x-www-form-urlencoded',
'Authorization': 'Basic ' + Buffer.from(`${this.config.clientId}:${this.config.clientSecret}`).toString('base64')
};
const body = new URLSearchParams({
grant_type: 'client_credentials',
scope: 'webchat:write conversation:read'
}).toString();
try {
const response = await axios.post(url, body, { headers });
this.token = response.data.access_token;
this.expiresAt = Date.now() + (response.data.expires_in * 1000) - 5000; // 5s buffer
this.retryAttempts = 0;
return this.token;
} catch (error) {
if (error.response?.status === 429) {
const retryAfter = parseInt(error.response.headers['retry-after'], 10) || Math.pow(2, this.retryAttempts);
console.warn(`[TokenManager] 429 Rate limited. Retrying in ${retryAfter}s (attempt ${this.retryAttempts + 1}/${this.maxRetries})`);
if (this.retryAttempts >= this.maxRetries) throw new Error('Max 429 retries exceeded for OAuth token fetch');
this.retryAttempts++;
await setTimeout(retryAfter * 1000);
return this.getToken();
}
throw new Error(`OAuth token fetch failed: ${error.message}`);
}
}
}
Implementation
Step 1: Initialize WebSocket Connection and Auth Handshake
Genesys Cloud Webchat uses a persistent WebSocket connection. You must send an auth message immediately after connection. The message requires your organizationId, deploymentId, and the JWT from Step 0. The server responds with an auth acknowledgment containing the assigned conversationId.
import WebSocket from 'ws';
import { v4 as uuidv4 } from 'uuid';
/**
* @typedef {Object} WebchatAuthResponse
* @property {string} conversationId
* @property {string} deploymentId
*/
export class WebchatConnection {
/**
* @param {string} region
* @param {TokenManager} tokenManager
* @param {string} organizationId
* @param {string} deploymentId
*/
constructor(region, tokenManager, organizationId, deploymentId) {
this.wsUrl = `wss://webchat.${region}`;
this.tokenManager = tokenManager;
this.organizationId = organizationId;
this.deploymentId = deploymentId;
this.ws = null;
this.conversationId = null;
this.isConnected = false;
}
/**
* Establishes WebSocket connection and completes auth handshake
* @returns {Promise<WebchatAuthResponse>}
*/
async connect() {
return new Promise((resolve, reject) => {
this.ws = new WebSocket(this.wsUrl);
this.ws.on('open', async () => {
try {
const token = await this.tokenManager.getToken();
const authMessage = {
type: 'auth',
id: uuidv4(),
organizationId: this.organizationId,
deploymentId: this.deploymentId,
token: token,
version: '2'
};
this.ws.send(JSON.stringify(authMessage));
} catch (err) {
reject(new Error(`Auth handshake failed: ${err.message}`));
this.ws.close();
}
});
this.ws.on('message', (data) => {
const msg = JSON.parse(data.toString());
if (msg.type === 'auth' && msg.success) {
this.conversationId = msg.conversationId;
this.isConnected = true;
resolve({ conversationId: this.conversationId, deploymentId: this.deploymentId });
} else if (msg.type === 'error') {
reject(new Error(`Webchat auth error: ${msg.message}`));
}
});
this.ws.on('error', (err) => reject(new Error(`WebSocket connection error: ${err.message}`)));
this.ws.on('close', () => { this.isConnected = false; });
});
}
/**
* Sends a raw WebSocket message
* @param {Object} payload
*/
send(payload) {
if (!this.isConnected || !this.ws?.readyState) {
throw new Error('WebSocket is not connected');
}
this.ws.send(JSON.stringify(payload));
}
}
Step 2: Validate File Schema, MIME Type, and Malware Signatures
Genesys Cloud enforces strict file constraints. You must validate the file before streaming. The maximum allowed size is 25 MB. Allowed MIME types are restricted to safe document formats. You must also run a malware signature scan. The following validator implements MIME checking, size limits, and a pluggable scanner pipeline.
import { readFileSync, statSync } from 'fs';
import { createHash, createReadStream } from 'crypto';
import { lookup as lookupMimeType } from 'mime-types';
/**
* @typedef {Object} ValidationResult
* @property {boolean} valid
* @property {string[]} errors
* @property {string} checksum
* @property {string} mimeType
* @property {number} fileSize
*/
/**
* Validates file constraints and runs security checks
*/
export class FileValidator {
/**
* @param {Object} scanner - Must implement async scan(filePath) -> { clean: boolean }
*/
constructor(scanner) {
this.scanner = scanner;
this.maxSizeBytes = 25 * 1024 * 1024; // 25MB
this.allowedMimeTypes = [
'application/pdf',
'image/jpeg', 'image/png', 'image/gif', 'image/webp',
'text/plain', 'text/csv',
'application/zip', 'application/x-rar-compressed'
];
}
/**
* Computes MD5 checksum of a file
* @param {string} filePath
* @returns {Promise<string>}
*/
async computeChecksum(filePath) {
return new Promise((resolve, reject) => {
const hash = createHash('md5');
const stream = createReadStream(filePath);
stream.on('data', chunk => hash.update(chunk));
stream.on('end', () => resolve(hash.digest('hex')));
stream.on('error', reject);
});
}
/**
* Validates file against Genesys constraints and security pipeline
* @param {string} filePath
* @returns {Promise<ValidationResult>}
*/
async validate(filePath) {
const errors = [];
const fileSize = statSync(filePath).size;
const mimeType = lookupMimeType(filePath) || 'application/octet-stream';
if (fileSize > this.maxSizeBytes) {
errors.push(`File exceeds 25MB limit (${fileSize} bytes)`);
}
if (!this.allowedMimeTypes.includes(mimeType)) {
errors.push(`Unsupported MIME type: ${mimeType}`);
}
if (errors.length > 0) {
return { valid: false, errors, checksum: '', mimeType, fileSize };
}
const checksum = await this.computeChecksum(filePath);
try {
const scanResult = await this.scanner.scan(filePath);
if (!scanResult.clean) {
errors.push('Malware signature detected during scanning pipeline');
}
} catch (scanErr) {
errors.push(`Malware scanner failure: ${scanErr.message}`);
}
return { valid: errors.length === 0, errors, checksum, mimeType, fileSize };
}
}
Step 3: Construct Chunk Matrices and Stream Upload Payloads
Genesys Cloud expects file uploads to be split into base64-encoded chunks. You construct a chunk matrix that tracks indices, calculate the checksum upfront, and push atomic fileUploadChunk messages. The platform automatically triggers reassembly buffers upon receiving fileUploadEnd.
import { readFileSync } from 'fs';
import { v4 as uuidv4 } from 'uuid';
/**
* @typedef {Object} UploadConfig
* @property {string} filePath
* @property {string} fileName
* @property {string} mimeType
* @property {string} checksum
* @property {number} fileSize
* @property {number} chunkSizeBytes
*/
/**
* Handles chunk generation and WebSocket streaming
*/
export class FileStreamer {
/**
* @param {WebchatConnection} connection
* @param {UploadConfig} config
*/
constructor(connection, config) {
this.connection = connection;
this.config = config;
this.totalChunks = Math.ceil(config.fileSize / config.chunkSizeBytes);
this.uploadedChunks = 0;
this.startTime = 0;
}
/**
* Generates base64 chunk matrix and streams to Genesys
* @returns {Promise<void>}
*/
async stream() {
this.startTime = Date.now();
const fileBuffer = readFileSync(this.config.filePath);
// Send initial fileUpload metadata
this.connection.send({
type: 'fileUpload',
id: uuidv4(),
conversationId: this.connection.conversationId,
fileName: this.config.fileName,
fileSize: this.config.fileSize,
mimeType: this.config.mimeType,
checksum: this.config.checksum,
chunkSize: this.config.chunkSizeBytes,
totalChunks: this.totalChunks
});
// Stream chunks sequentially
for (let i = 0; i < this.totalChunks; i++) {
const start = i * this.config.chunkSizeBytes;
const end = Math.min(start + this.config.chunkSizeBytes, this.config.fileSize);
const chunkBuffer = fileBuffer.slice(start, end);
const base64Data = chunkBuffer.toString('base64');
this.connection.send({
type: 'fileUploadChunk',
id: uuidv4(),
conversationId: this.connection.conversationId,
chunkIndex: i,
data: base64Data
});
this.uploadedChunks++;
}
// Trigger server-side reassembly buffer
this.connection.send({
type: 'fileUploadEnd',
id: uuidv4(),
conversationId: this.connection.conversationId
});
}
/**
* Calculates transfer metrics
* @returns {{ latencyMs: number, throughputMbps: number }}
*/
getMetrics() {
const endTime = Date.now();
const latencyMs = endTime - this.startTime;
const bytesTransferred = this.config.fileSize;
const throughputMbps = (bytesTransferred * 8) / (latencyMs / 1000) / 1_000_000;
return { latencyMs, throughputMbps: Number(throughputMbps.toFixed(3)) };
}
}
Step 4: Process Completion, Calculate Metrics, and Sync to External DMS
You must track upload completion, generate audit logs, and invoke external document management system callbacks. The following orchestrator ties validation, streaming, metrics, and DMS synchronization together.
/**
* @callback DMSyncHandler
* @param {Object} uploadRecord
* @returns {Promise<void>}
*/
export class UploadOrchestrator {
/**
* @param {WebchatConnection} connection
* @param {FileValidator} validator
* @param {DMSyncHandler} dmsHandler
*/
constructor(connection, validator, dmsHandler) {
this.connection = connection;
this.validator = validator;
this.dmsHandler = dmsHandler;
}
/**
* Executes the complete upload pipeline
* @param {string} filePath
* @param {string} fileName
* @returns {Promise<Object>}
*/
async upload(filePath, fileName) {
const validation = await this.validator.validate(filePath);
if (!validation.valid) {
const auditLog = this.generateAuditLog(fileName, validation, 'FAILED_VALIDATION');
console.error(JSON.stringify(auditLog));
throw new Error(`Upload rejected: ${validation.errors.join(', ')}`);
}
const streamer = new FileStreamer(this.connection, {
filePath,
fileName,
mimeType: validation.mimeType,
checksum: validation.checksum,
fileSize: validation.fileSize,
chunkSizeBytes: 16384 // 16KB chunks
});
await streamer.stream();
const metrics = streamer.getMetrics();
const auditLog = this.generateAuditLog(fileName, validation, 'SUCCESS', metrics);
console.log(JSON.stringify(auditLog));
// Sync to external DMS
await this.dmsHandler({
fileName,
conversationId: this.connection.conversationId,
checksum: validation.checksum,
mimeType: validation.mimeType,
sizeBytes: validation.fileSize,
uploadTimestamp: new Date().toISOString(),
metrics
});
return auditLog;
}
/**
* Generates structured audit log for content governance
* @param {string} fileName
* @param {ValidationResult} validation
* @param {string} status
* @param {Object} [metrics]
* @returns {Object}
*/
generateAuditLog(fileName, validation, status, metrics) {
return {
timestamp: new Date().toISOString(),
event: 'webchat_file_upload',
status,
fileName,
fileSize: validation.fileSize,
mimeType: validation.mimeType,
checksum: validation.checksum,
conversationId: this.connection.conversationId,
metrics: metrics || null,
validationErrors: validation.errors
};
}
}
Complete Working Example
The following script combines all components into a runnable module. Replace the mock scanner with your enterprise malware scanning service in production.
import { WebchatConnection } from './WebchatConnection.js';
import { TokenManager } from './TokenManager.js';
import { FileValidator } from './FileValidator.js';
import { UploadOrchestrator } from './UploadOrchestrator.js';
// Mock malware scanner for tutorial execution
const mockMalwareScanner = {
async scan(filePath) {
// Replace with clamav-rest or enterprise scanner integration
return new Promise((resolve) => setTimeout(() => resolve({ clean: true }), 50));
}
};
async function runUploadPipeline() {
const region = process.env.GENESYS_REGION || 'mypurecloud.com';
const tokenManager = new TokenManager({
clientId: process.env.GENESYS_OAUTH_CLIENT_ID,
clientSecret: process.env.GENESYS_OAUTH_CLIENT_SECRET,
region
});
const connection = new WebchatConnection(
region,
tokenManager,
process.env.GENESYS_ORGANIZATION_ID,
process.env.GENESYS_DEPLOYMENT_ID
);
await connection.connect();
console.log(`[Orchestrator] Connected to conversation: ${connection.conversationId}`);
const validator = new FileValidator(mockMalwareScanner);
const dmsSyncHandler = async (uploadRecord) => {
console.log(`[DMS Sync] Triggering external document storage for: ${uploadRecord.fileName}`);
// Implement REST call to SharePoint, S3, or internal DMS here
await new Promise(resolve => setTimeout(resolve, 100));
};
const orchestrator = new UploadOrchestrator(connection, validator, dmsSyncHandler);
try {
const result = await orchestrator.upload('./sample-document.pdf', 'sample-document.pdf');
console.log('[Orchestrator] Upload pipeline completed successfully.');
console.log(JSON.stringify(result, null, 2));
} catch (error) {
console.error(`[Orchestrator] Pipeline failed: ${error.message}`);
} finally {
if (connection.ws?.readyState === WebSocket.OPEN) {
connection.ws.close();
}
}
}
runUploadPipeline();
Common Errors & Debugging
Error: 401 Unauthorized on WebSocket Auth
- Cause: The JWT token expired, contains incorrect scopes, or the
organizationIddoes not match the token issuer. - Fix: Verify the OAuth2 client has
webchat:writeandconversation:readscopes. Ensure theTokenManagerrefreshes the token before sending theauthmessage. Check theexpclaim in the JWT. - Code Fix: The
TokenManageralready implements expiration tracking with a 5-second buffer. Add logging togetToken()to verify scope claims.
Error: 403 Forbidden or Invalid Deployment
- Cause: The
deploymentIdis invalid, disabled, or restricted to specific IP ranges. - Fix: Confirm the deployment ID matches an active Webchat deployment in the Genesys Cloud admin console. Verify network egress rules allow
wss://webchat.{region}.
Error: WebSocket 1006 or 429 Rate Limit Cascades
- Cause: Rapid chunk transmission triggers platform throttling, or the connection drops during large file transfers.
- Fix: Implement pacing between chunks. Genesys Cloud processes chunks asynchronously. Add a 10-50ms delay between
fileUploadChunksends if you observe 1006 drops. The provided code streams atomically; for files exceeding 10MB, insertawait setTimeout(20)inside the chunk loop. - Code Fix:
// Inside FileStreamer.stream() chunk loop
await new Promise(resolve => setTimeout(resolve, 25)); // Pacing for large files
Error: Checksum Mismatch Rejection
- Cause: The MD5 hash sent in
fileUploaddoes not match the reassembled server-side file. Base64 encoding errors or truncated chunks cause this. - Fix: Verify the
computeChecksumfunction reads the complete file buffer. EnsurefileUploadEndis sent only after all chunks are transmitted. Validate thatchunkSizeBytesdivides evenly or handles the final partial chunk correctly (the providedMath.minlogic handles this).