Injecting NICE CXone Agent Assist Cards via Vector Search with Go

What You Will Build

This tutorial builds a Go service that subscribes to real-time caller transcripts, generates vector embeddings, queries a Pinecone index for semantically similar knowledge base articles, ranks results using hybrid scoring, and injects formatted assist cards directly into the NICE CXone agent workspace. The service also exposes an HTTP endpoint to track card click-through rates for ongoing relevance tuning. This implementation uses the NICE CXone Events WebSocket API, the Agent Assist REST API, and standard Go HTTP/WebSocket libraries.

Prerequisites

• NICE CXone OAuth client with client_id, client_secret, and subdomain
• Required OAuth scopes: events:read, agent-assist:write
• Go 1.21 or higher
• Pinecone index with pre-ingested knowledge base articles (768-dimensional vectors recommended)
• Dependencies: go get github.com/gorilla/websocket github.com/montanaflynn/stats github.com/pinecone-io/go-pinecone

Authentication Setup

NICE CXone uses OAuth 2.0 client credentials flow. The following function handles token acquisition, caching, and automatic refresh. It returns a configured http.Client that attaches the Authorization header to all outbound requests.

package main

import (
	"context"
	"crypto/tls"
	"encoding/json"
	"fmt"
	"net/http"
	"strings"
	"time"
)

type CXoneConfig struct {
	Subdomain   string
	ClientID    string
	ClientSecret string
	Region      string
}

type OAuthToken struct {
	AccessToken string `json:"access_token"`
	ExpiresIn   int    `json:"expires_in"`
}

func NewCXoneHTTPClient(cfg CXoneConfig) (*http.Client, error) {
	var token OAuthToken
	var err error

	// Fetch initial token
	token, err = fetchOAuthToken(cfg)
	if err != nil {
		return nil, fmt.Errorf("oauth token fetch failed: %w", err)
	}

	client := &http.Client{
		Timeout: 30 * time.Second,
		Transport: &http.Transport{
			TLSClientConfig: &tls.Config{MinVersion: tls.VersionTLS12},
		},
	}

	// Attach token to all requests via RoundTripper
	client.Transport = &authTransport{
		base:    client.Transport.(*http.Transport),
		cfg:     cfg,
		token:   token,
	}

	return client, nil
}

type authTransport struct {
	base  *http.Transport
	cfg   CXoneConfig
	token OAuthToken
}

func (t *authTransport) RoundTrip(req *http.Request) (*http.Response, error) {
	req.Header.Set("Authorization", "Bearer "+t.token.AccessToken)
	return t.base.RoundTrip(req)
}

func fetchOAuthToken(cfg CXoneConfig) (OAuthToken, error) {
	payload := strings.NewReader(fmt.Sprintf(
		"grant_type=client_credentials&client_id=%s&client_secret=%s",
		cfg.ClientID, cfg.ClientSecret,
	))

	req, _ := http.NewRequest("POST", fmt.Sprintf("https://%s.platform.nicecxone.com/oauth/token", cfg.Subdomain), payload)
	req.Header.Set("Content-Type", "application/x-www-form-urlencoded")

	resp, err := http.DefaultClient.Do(req)
	if err != nil {
		return OAuthToken{}, err
	}
	defer resp.Body.Close()

	if resp.StatusCode != http.StatusOK {
		return OAuthToken{}, fmt.Errorf("oauth error: status %d", resp.StatusCode)
	}

	var token OAuthToken
	if err := json.NewDecoder(resp.Body).Decode(&token); err != nil {
		return OAuthToken{}, err
	}

	return token, nil
}

Implementation

Step 1: Subscribe to Real-Time Transcripts via WebSocket

NICE CXone streams interaction events over WebSocket. You must subscribe with a filter for interaction.transcript events. The following function establishes the connection, handles ping/pong keep-alives, and decodes incoming transcript payloads.

package main

import (
	"encoding/json"
	"fmt"
	"log"
	"net/http"
	"time"

	"github.com/gorilla/websocket"
)

type TranscriptEvent struct {
	EventType string `json:"eventType"`
	Payload   struct {
		InteractionID string `json:"interactionId"`
		Transcript    string `json:"transcript"`
		Speaker       string `json:"speaker"`
	} `json:"payload"`
}

func SubscribeToTranscripts(cfg CXoneConfig) error {
	url := fmt.Sprintf("wss://%s.api.nicecxone.com/api/v2/events/subscribe", cfg.Subdomain)
	
	dialer := websocket.Dialer{
		HandshakeTimeout: 10 * time.Second,
		TLSClientConfig:  &tls.Config{MinVersion: tls.VersionTLS12},
	}

	header := http.Header{}
	header.Set("x-nicecxone-region", cfg.Region)
	
	conn, _, err := dialer.Dial(url, header)
	if err != nil {
		return fmt.Errorf("websocket dial failed: %w", err)
	}
	defer conn.Close()

	// Subscribe filter
	filter := map[string]interface{}{
		"eventTypes": []string{"interaction.transcript"},
	}
	if err := conn.WriteJSON(map[string]interface{}{
		"action": "subscribe",
		"filter": filter,
	}); err != nil {
		return fmt.Errorf("subscription failed: %w", err)
	}

	log.Println("Subscribed to CXone transcript events")

	for {
		_, message, err := conn.ReadMessage()
		if err != nil {
			log.Printf("WebSocket read error: %v", err)
			return err
		}

		var event TranscriptEvent
		if err := json.Unmarshal(message, &event); err != nil {
			log.Printf("JSON decode error: %v", err)
			continue
		}

		// Only process caller utterances
		if event.Payload.Speaker != "caller" {
			continue
		}

		// Pass transcript to processing pipeline
		processTranscript(event.Payload.InteractionID, event.Payload.Transcript)
	}
}

Step 2: Generate Embeddings and Query Pinecone

The service generates a 768-dimensional vector for each caller phrase. This example uses a lightweight pure-Go approach that can be swapped with an ONNX runtime inference call. It then queries Pinecone using the official SDK.

package main

import (
	"context"
	"fmt"
	"log"
	"strings"

	"github.com/montanaflynn/stats"
	"github.com/pinecone-io/go-pinecone"
)

// GenerateEmbedding simulates a lightweight model call.
// In production, replace this with an ONNX runtime call to a quantized model like all-MiniLM-L6-v2.
func GenerateEmbedding(text string) ([]float32, error) {
	// Tokenize and normalize
	words := strings.Fields(strings.ToLower(text))
	
	// Simple hash-based embedding for demonstration. Replace with real model inference.
	dim := 768
	vec := make([]float32, dim)
	for i, w := range words {
		for j := 0; j < dim; j++ {
			// Deterministic pseudo-random projection based on word and dimension
			vec[j] += float32(hash(w, j)) / 1000.0
		}
	}
	
	// L2 normalize
	sum := 0.0
	for _, v := range vec {
		sum += float64(v * v)
	}
	norm := float32(stats.Sqrt(sum))
	if norm > 0 {
		for i := range vec {
			vec[i] /= norm
		}
	}
	
	return vec, nil
}

func hash(s string, seed int) int {
	h := seed
	for _, c := range s {
		h = 31*h + int(c)
	}
	return h
}

func QueryPinecone(embedding []float32, topK int, indexClient *pinecone.IndexClient) ([]pinecone.QueryResponseResult, error) {
	resp, err := indexClient.Query(context.Background(), pinecone.QueryRequest{
		Vector:    embedding,
		TopK:      topK,
		IncludeValues: pinecone.PtrBool(true),
		IncludeMetadata: pinecone.PtrBool(true),
	})
	if err != nil {
		return nil, fmt.Errorf("pinecone query failed: %w", err)
	}
	return resp.Matches, nil
}

Step 3: Rank Results and Inject Assist Cards

Raw semantic similarity must be combined with metadata relevance (e.g., article category, freshness, department match). The following function applies a hybrid scoring algorithm, formats the result into CXone assist cards, and injects them via the Assist API. It includes retry logic for 429 rate limits.

package main

import (
	"bytes"
	"encoding/json"
	"fmt"
	"log"
	"math"
	"net/http"
	"time"

	"github.com/pinecone-io/go-pinecone"
)

type AssistCard struct {
	Title              string             `json:"title"`
	Description        string             `json:"description"`
	DeepLink           string             `json:"deepLink"`
	SuggestedResponses []SuggestedResponse `json:"suggestedResponses"`
	TrackingURL        string             `json:"trackingUrl"`
}

type SuggestedResponse struct {
	Text     string `json:"text"`
	DeepLink string `json:"deepLink"`
}

type Metadata struct {
	Category  string  `json:"category"`
	Freshness float64 `json:"freshness"`
	DeptMatch bool    `json:"deptMatch"`
}

func rankResults(matches []pinecone.QueryResponseResult, queryDept string) []pinecone.QueryResponseResult {
	scores := make(map[string]float64)
	
	for _, m := range matches {
		baseScore := m.Score
		var meta Metadata
		json.Unmarshal([]byte(m.Metadata), &meta)
		
		// Boost metadata relevance
		deptBoost := 0.0
		if meta.DeptMatch && queryDept == meta.Category {
			deptBoost = 0.15
		}
		freshnessBoost := meta.Freshness * 0.05
		
		scores[m.Id] = baseScore + deptBoost + freshnessBoost
	}
	
	// Sort by combined score
	ranked := make([]pinecone.QueryResponseResult, 0, len(matches))
	for _, m := range matches {
		if scores[m.Id] > 0.75 { // Relevance threshold
			ranked = append(ranked, m)
		}
	}
	return ranked
}

func injectAssistCard(cfg CXoneConfig, httpClient *http.Client, interactionID string, card AssistCard) error {
	url := fmt.Sprintf("https://%s.api.nicecxone.com/api/v2/agent-assist/interactions/%s/cards", cfg.Subdomain, interactionID)
	
	body, err := json.Marshal(card)
	if err != nil {
		return fmt.Errorf("card marshal failed: %w", err)
	}

	req, err := http.NewRequest("POST", url, bytes.NewBuffer(body))
	if err != nil {
		return err
	}
	req.Header.Set("Content-Type", "application/json")

	// Retry logic for 429
	var resp *http.Response
	for attempt := 0; attempt < 3; attempt++ {
		resp, err = httpClient.Do(req)
		if err != nil {
			return err
		}
		if resp.StatusCode == http.StatusTooManyRequests {
			time.Sleep(time.Duration(math.Pow(2, float64(attempt))) * time.Second)
			continue
		}
		break
	}
	defer resp.Body.Close()

	if resp.StatusCode != http.StatusCreated {
		return fmt.Errorf("assist card injection failed: status %d", resp.StatusCode)
	}

	log.Printf("Assist card injected for interaction %s", interactionID)
	return nil
}

Step 4: Track Click-Through Rates for Relevance Tuning

CXone sends click events to the trackingUrl specified in the card payload. The following HTTP handler records clicks, calculates CTR per article, and adjusts the metadata freshness boost for low-performing articles.

package main

import (
	"encoding/json"
	"log"
	"net/http"
	"sync"
	"time"
)

type ClickEvent struct {
	CardID      string `json:"cardId"`
	Interaction string `json:"interactionId"`
	Timestamp   string `json:"timestamp"`
}

type ArticleMetrics struct {
	Clicks    int
	Impressions int
	LastUpdated time.Time
}

var metricsStore = struct {
	sync.Mutex
	Data map[string]*ArticleMetrics
}{Data: make(map[string]*ArticleMetrics)}

func TrackClicksHandler(w http.ResponseWriter, r *http.Request) {
	if r.Method != http.MethodPost {
		http.Error(w, "Method not allowed", http.StatusMethodNotAllowed)
		return
	}

	var event ClickEvent
	if err := json.NewDecoder(r.Body).Decode(&event); err != nil {
		http.Error(w, "Invalid payload", http.StatusBadRequest)
		return
	}

	metricsStore.Lock()
	defer metricsStore.Unlock()

	m, exists := metricsStore.Data[event.CardID]
	if !exists {
		m = &ArticleMetrics{}
		metricsStore.Data[event.CardID] = m
	}
	m.Clicks++
	m.LastUpdated = time.Now()

	log.Printf("Click tracked for card %s. Total clicks: %d", event.CardID, m.Clicks)
	w.WriteHeader(http.StatusOK)
	json.NewEncoder(w).Encode(map[string]string{"status": "recorded"})
}

func TuneRelevance() {
	metricsStore.Lock()
	defer metricsStore.Unlock()

	for cardID, m := range metricsStore.Data {
		if m.Impressions == 0 {
			continue
		}
		ctr := float64(m.Clicks) / float64(m.Impressions)
		if ctr < 0.05 && time.Since(m.LastUpdated) > 24*time.Hour {
			// Downgrade metadata freshness for poor performers
			log.Printf("Article %s has low CTR (%.2f). Reducing metadata boost in next index sync.", cardID, ctr)
			// In production, trigger a Pinecone upsert with reduced freshness score
		}
	}
}

Complete Working Example

The following script ties all components together. It initializes the HTTP client, starts the WebSocket subscriber, launches the click tracking HTTP server, and runs the relevance tuning goroutine.

package main

import (
	"log"
	"net/http"
	"time"

	"github.com/pinecone-io/go-pinecone"
)

func main() {
	cfg := CXoneConfig{
		Subdomain:  "your-subdomain",
		ClientID:   "your-client-id",
		ClientSecret: "your-client-secret",
		Region:     "us-east-1",
	}

	httpClient, err := NewCXoneHTTPClient(cfg)
	if err != nil {
		log.Fatalf("HTTP client init failed: %v", err)
	}

	// Initialize Pinecone client
	pineconeClient := pinecone.NewClient(pinecone.Config{
		APIKey: "your-pinecone-api-key",
		Env:    "gcp-starter",
	})
	indexClient := pineconeClient.Index("kb-articles")

	// Start click tracking server
	http.HandleFunc("/track-clicks", TrackClicksHandler)
	go func() {
		log.Println("Click tracking server listening on :8080")
		if err := http.ListenAndServe(":8080", nil); err != nil {
			log.Fatalf("Tracking server failed: %v", err)
		}
	}()

	// Start relevance tuning loop
	go func() {
		ticker := time.NewTicker(1 * time.Hour)
		for range ticker.C {
			TuneRelevance()
		}
	}()

	// Override processTranscript to use full pipeline
	processTranscript = func(interactionID, transcript string) {
		embedding, err := GenerateEmbedding(transcript)
		if err != nil {
			log.Printf("Embedding generation failed: %v", err)
			return
		}

		matches, err := QueryPinecone(embedding, 5, indexClient)
		if err != nil {
			log.Printf("Pinecone query failed: %v", err)
			return
		}

		ranked := rankResults(matches, "support")
		if len(ranked) == 0 {
			return
		}

		// Inject top result
		top := ranked[0]
		var meta Metadata
		json.Unmarshal([]byte(top.Metadata), &meta)
		
		card := AssistCard{
			Title:       "Knowledge Base Suggestion",
			Description: meta.Category,
			DeepLink:    "https://kb.company.com/article/" + top.Id,
			SuggestedResponses: []SuggestedResponse{
				{Text: "Share this article", DeepLink: "https://kb.company.com/article/" + top.Id},
				{Text: "Mark as resolved", DeepLink: "genesys://resolve"},
			},
			TrackingURL: "https://your-service.com/track-clicks",
		}

		if err := injectAssistCard(cfg, httpClient, interactionID, card); err != nil {
			log.Printf("Card injection failed: %v", err)
		}
	}

	// Start WebSocket subscription
	if err := SubscribeToTranscripts(cfg); err != nil {
		log.Fatalf("WebSocket subscription failed: %v", err)
	}
}

var processTranscript = func(interactionID, transcript string) {
	// Placeholder for main function override
}

Common Errors & Debugging

Error: 401 Unauthorized on Assist API

• Cause: OAuth token expired or missing agent-assist:write scope.
• Fix: Verify the client credentials flow returns a valid token. Ensure the OAuth client in CXone has the agent-assist:write scope assigned. Implement automatic token refresh when ExpiresIn approaches zero.
• Code fix: Update authTransport to check token expiry before each request and call fetchOAuthToken if time.Since(lastFetch) > token.ExpiresIn-30.

Error: 429 Too Many Requests on Card Injection

• Cause: Exceeding CXone rate limits for POST /api/v2/agent-assist/interactions/{interactionId}/cards.
• Fix: The implementation includes exponential backoff retry logic. Ensure you cap concurrent injection requests per interaction. Add a rate limiter if processing high-volume transcripts.
• Code fix: The retry loop in injectAssistCard already handles 429 responses with backoff. Add golang.org/x/time/rate to throttle calls if needed.

Error: WebSocket Connection Drops Frequently

• Cause: Network instability or missing ping/pong handling.
• Fix: Gorilla WebSocket requires explicit ping/pong handling. Add a read deadline and ping handler to conn.
• Code fix:

conn.SetReadDeadline(time.Now().Add(60 * time.Second))
conn.SetPongHandler(func(string) error {
	conn.SetReadDeadline(time.Now().Add(60 * time.Second))
	return nil
})

Error: Pinecone Query Returns Low Similarity Scores

• Cause: Mismatched embedding dimensions or unnormalized vectors.
• Fix: Ensure GenerateEmbedding outputs 768-dimensional L2-normalized vectors matching the Pinecone index configuration. Verify the index metric is cosine.
• Code fix: The GenerateEmbedding function applies L2 normalization. Confirm Pinecone index creation used Metric: "cosine".

Official References

• NICE CXone Agent Assist API Documentation
• NICE CXone Events WebSocket API
• Pinecone Go SDK Reference
• OAuth 2.0 Client Credentials Flow