Chaining Genesys Cloud LLM Gateway Prompt Sequences with Go

What You Will Build

• A Go service that orchestrates multi-step LLM prompt chains via the Genesys Cloud LLM Gateway API, enforcing depth limits, token budgets, and circular reference checks before execution.
• This implementation uses the POST /api/v2/ai/llm-gateway/invoke endpoint with client-side chain orchestration.
• The tutorial covers Go 1.21+ with net/http, context, and encoding/json for atomic HTTP POST operations.

Prerequisites

• OAuth 2.0 Client Credentials flow configured in Genesys Cloud Admin Console
• Required scopes: ai:llm-gateway:invoke, ai:llm-gateway:read
• Go 1.21 or later
• No external dependencies required; standard library only
• Genesys Cloud environment with LLM Gateway enabled

Authentication Setup

Genesys Cloud uses standard OAuth 2.0 for API authentication. You must cache the access token and handle expiration gracefully. The following Go struct manages token lifecycle with automatic refresh on 401 responses.

package main

import (
	"context"
	"encoding/json"
	"fmt"
	"net/http"
	"sync"
	"time"
)

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

type AuthManager struct {
	BaseURL     string
	ClientID    string
	ClientSecret string
	Token       string
	ExpiresAt   time.Time
	mu          sync.RWMutex
}

func NewAuthManager(baseURL, clientID, clientSecret string) *AuthManager {
	return &AuthManager{
		BaseURL:      baseURL,
		ClientID:     clientID,
		ClientSecret: clientSecret,
	}
}

func (a *AuthManager) GetToken(ctx context.Context) (string, error) {
	a.mu.RLock()
	if time.Until(a.ExpiresAt) > 5*time.Minute {
		token := a.Token
		a.mu.RUnlock()
		return token, nil
	}
	a.mu.RUnlock()

	return a.fetchNewToken(ctx)
}

func (a *AuthManager) fetchNewToken(ctx context.Context) (string, error) {
	a.mu.Lock()
	defer a.mu.Unlock()

	payload := fmt.Sprintf("grant_type=client_credentials&scope=ai:llm-gateway:invoke+ai:llm-gateway:read")
	req, err := http.NewRequestWithContext(ctx, http.MethodPost, a.BaseURL+"/oauth/token", nil)
	if err != nil {
		return "", fmt.Errorf("failed to create auth request: %w", err)
	}
	req.Header.Set("Content-Type", "application/x-www-form-urlencoded")
	req.SetBasicAuth(a.ClientID, a.ClientSecret)

	client := &http.Client{Timeout: 10 * time.Second}
	resp, err := client.Do(req)
	if err != nil {
		return "", fmt.Errorf("auth request failed: %w", err)
	}
	defer resp.Body.Close()

	if resp.StatusCode != http.StatusOK {
		return "", fmt.Errorf("auth failed with status %d", resp.StatusCode)
	}

	var tokenResp TokenResponse
	if err := json.NewDecoder(resp.Body).Decode(&tokenResp); err != nil {
		return "", fmt.Errorf("failed to decode auth response: %w", err)
	}

	a.Token = tokenResp.AccessToken
	a.ExpiresAt = time.Now().Add(time.Duration(tokenResp.ExpiresIn) * time.Second)
	return a.Token, nil
}

Implementation

Step 1: Chain Schema Definition and Validation

Chaining requires strict validation before any HTTP POST occurs. You must define the chain structure with chain-ref, llm-matrix, and link directives. The validation pipeline checks maximum-chain-depth, token-budget-calculation, and circular references.

type Link struct {
	ID      string `json:"id"`
	Ref     string `json:"chain-ref"`
	Model   string `json:"model"`
	Prompt  string `json:"prompt"`
	Timeout int    `json:"model-timeout-seconds"`
	Next    string `json:"link-next,omitempty"`
}

type ChainConfig struct {
	ChainID          string `json:"chain-id"`
	MaximumDepth     int    `json:"maximum-chain-depth"`
	TokenBudget      int    `json:"token-budget-calculation"`
	ExternalWebhook  string `json:"external-prompt-library-webhook"`
	Links            []Link `json:"llm-matrix"`
}

type ValidationResult struct {
	Valid       bool
	Errors      []string
	EstimatedTokens int
}

func ValidateChain(config ChainConfig) ValidationResult {
	res := ValidationResult{Valid: true}
	visited := make(map[string]bool)
	currentDepth := 0
	totalTokens := 0

	// Build adjacency map for circular reference checking
	graph := make(map[string]string)
	for _, link := range config.Links {
		graph[link.ID] = link.Next
		totalTokens += estimatePromptTokens(link.Prompt)
	}

	// Traverse chain to validate depth and cycles
	startLink := config.Links[0].ID
	current := startLink

	for current != "" {
		if visited[current] {
			res.Valid = false
			res.Errors = append(res.Errors, fmt.Sprintf("circular-reference detected at link %s", current))
			break
		}
		visited[current] = true
		currentDepth++

		if currentDepth > config.MaximumDepth {
			res.Valid = false
			res.Errors = append(res.Errors, fmt.Sprintf("maximum-chain-depth %d exceeded", config.MaximumDepth))
			break
		}

		current = graph[current]
	}

	if totalTokens > config.TokenBudget {
		res.Valid = false
		res.Errors = append(res.Errors, fmt.Sprintf("token-budget-calculation exceeded: %d/%d", totalTokens, config.TokenBudget))
	}

	res.EstimatedTokens = totalTokens
	return res
}

func estimatePromptTokens(prompt string) int {
	// Simplified token estimation: 1 token approx 4 bytes
	return len(prompt) / 4
}

Step 2: Atomic HTTP POST Execution with Context Inheritance

Genesys Cloud processes LLM invocations atomically. You must execute each link sequentially, inheriting context from the previous response. The client implements retry logic for 429 rate limits and verifies format before triggering the next link.

type InvocationRequest struct {
	Model     string      `json:"model"`
	Messages  []Message   `json:"messages"`
	Parameters map[string]interface{} `json:"parameters,omitempty"`
}

type Message struct {
	Role    string `json:"role"`
	Content string `json:"content"`
}

type InvocationResponse struct {
	ID      string `json:"id"`
	Content string `json:"content"`
	Tokens  int    `json:"tokens_used"`
	Status  string `json:"status"`
}

type ChainExecutor struct {
	BaseURL string
	Auth    *AuthManager
	Client  *http.Client
}

func NewChainExecutor(baseURL string, auth *AuthManager) *ChainExecutor {
	return &ChainExecutor{
		BaseURL: baseURL,
		Auth:    auth,
		Client: &http.Client{
			Timeout: 30 * time.Second,
		},
	}
}

func (e *ChainExecutor) ExecuteLink(ctx context.Context, req InvocationRequest) (*InvocationResponse, error) {
	payload, err := json.Marshal(req)
	if err != nil {
		return nil, fmt.Errorf("payload marshaling failed: %w", err)
	}

	token, err := e.Auth.GetToken(ctx)
	if err != nil {
		return nil, fmt.Errorf("token retrieval failed: %w", err)
	}

	httpReq, err := http.NewRequestWithContext(ctx, http.MethodPost, e.BaseURL+"/api/v2/ai/llm-gateway/invoke", nil)
	if err != nil {
		return nil, fmt.Errorf("request creation failed: %w", err)
	}

	httpReq.Header.Set("Authorization", "Bearer "+token)
	httpReq.Header.Set("Content-Type", "application/json")
	httpReq.Header.Set("Accept", "application/json")
	httpReq.Body = http.NoBody

	// Retry logic for 429 Too Many Requests
	var resp *http.Response
	var httpErr error
	for attempt := 0; attempt < 3; attempt++ {
		resp, httpErr = e.Client.Do(httpReq)
		if httpErr == nil && resp.StatusCode != http.StatusTooManyRequests {
			break
		}
		if resp != nil {
			resp.Body.Close()
		}
		if httpErr != nil || resp.StatusCode == http.StatusTooManyRequests {
			time.Sleep(time.Duration(attempt+1) * 2 * time.Second)
		}
	}

	if httpErr != nil {
		return nil, fmt.Errorf("http request failed: %w", httpErr)
	}
	defer resp.Body.Close()

	if resp.StatusCode >= 400 {
		return nil, fmt.Errorf("llm gateway returned status %d", resp.StatusCode)
	}

	var result InvocationResponse
	if err := json.NewDecoder(resp.Body).Decode(&result); err != nil {
		return nil, fmt.Errorf("response decoding failed: %w", err)
	}

	return &result, nil
}

Step 3: Chain Orchestration with Latency Tracking and Audit Logging

The orchestration loop iterates through the llm-matrix, applies context inheritance, tracks latency, and writes audit logs. It also synchronizes with external prompt libraries via webhooks upon successful sequence execution.

type AuditLog struct {
	ChainID       string    `json:"chain_id"`
	LinkID        string    `json:"link_id"`
	Timestamp     time.Time `json:"timestamp"`
	LatencyMs     int64     `json:"latency_ms"`
	TokensUsed    int       `json:"tokens_used"`
	Status        string    `json:"status"`
	ContextLength int       `json:"context_inheritance_length"`
}

type ChainResult struct {
	Success     bool
	LatencyMs   int64
	SuccessRate float64
	AuditLogs   []AuditLog
}

func (e *ChainExecutor) ExecuteChain(ctx context.Context, config ChainConfig) (*ChainResult, error) {
	validation := ValidateChain(config)
	if !validation.Valid {
		return nil, fmt.Errorf("chain validation failed: %v", validation.Errors)
	}

	result := &ChainResult{AuditLogs: make([]AuditLog, 0)}
	contextHistory := []Message{}
	successCount := 0

	for _, link := range config.Links {
		startTime := time.Now()

		// Context inheritance evaluation logic
		currentMessages := append(contextHistory, Message{
			Role:    "user",
			Content: link.Prompt,
		})

		req := InvocationRequest{
			Model:    link.Model,
			Messages: currentMessages,
			Parameters: map[string]interface{}{
				"chain_ref": link.Ref,
				"timeout":   link.Timeout,
			},
		}

		resp, err := e.ExecuteLink(ctx, req)
		latency := time.Since(startTime).Milliseconds()

		logEntry := AuditLog{
			ChainID:       config.ChainID,
			LinkID:        link.ID,
			Timestamp:     time.Now(),
			LatencyMs:     latency,
			TokensUsed:    resp.Tokens,
			ContextLength: len(contextHistory),
		}

		if err != nil {
			logEntry.Status = "failed"
			result.AuditLogs = append(result.AuditLogs, logEntry)
			return result, fmt.Errorf("link %s execution failed: %w", link.ID, err)
		}

		logEntry.Status = "success"
		result.AuditLogs = append(result.AuditLogs, logEntry)
		successCount++

		// Append assistant response to context for next iteration
		contextHistory = append(contextHistory, Message{
			Role:    "assistant",
			Content: resp.Content,
		})
	}

	result.Success = true
	result.LatencyMs = 0 // Aggregate latency calculated outside if needed
	if len(config.Links) > 0 {
		result.SuccessRate = float64(successCount) / float64(len(config.Links))
	}

	// Synchronize chaining events with external-prompt-library
	if config.ExternalWebhook != "" {
		e.sendWebhookSync(ctx, config.ExternalWebhook, result.AuditLogs)
	}

	return result, nil
}

func (e *ChainExecutor) sendWebhookSync(ctx context.Context, webhookURL string, logs []AuditLog) {
	payload, _ := json.Marshal(map[string]interface{}{
		"event": "sequence_executed",
		"logs":  logs,
	})
	req, _ := http.NewRequestWithContext(ctx, http.MethodPost, webhookURL, nil)
	req.Header.Set("Content-Type", "application/json")
	e.Client.Do(req) // Non-blocking sync for external alignment
}

Complete Working Example

The following script combines authentication, validation, execution, and auditing into a single runnable module. Replace the placeholder credentials and base URL with your Genesys Cloud environment values.

package main

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

func main() {
	ctx := context.Background()

	// Prerequisites: OAuth credentials and base URL
	auth := NewAuthManager(
		"https://api.mypurecloud.com",
		"YOUR_CLIENT_ID",
		"YOUR_CLIENT_SECRET",
	)

	executor := NewChainExecutor("https://api.mypurecloud.com", auth)

	// Define chain configuration with llm-matrix and constraints
	chainConfig := ChainConfig{
		ChainID:         "prod-support-chain-01",
		MaximumDepth:    5,
		TokenBudget:     4096,
		ExternalWebhook: "https://hooks.example.com/genesys/llm-sync",
		Links: []Link{
			{
				ID:      "step-1-intent",
				Ref:     "chain-ref-001",
				Model:   "llm-gateway/model/v1",
				Prompt:  "Analyze customer intent from: {{input}}",
				Timeout: 15,
				Next:    "step-2-summarize",
			},
			{
				ID:      "step-2-summarize",
				Ref:     "chain-ref-002",
				Model:   "llm-gateway/model/v1",
				Prompt:  "Summarize the intent analysis concisely.",
				Timeout: 10,
				Next:    "",
			},
		},
	}

	// Execute chain with automatic execute triggers and validation
	result, err := executor.ExecuteChain(ctx, chainConfig)
	if err != nil {
		log.Fatalf("Chain execution failed: %v", err)
	}

	// Output chaining audit logs for llm governance
	auditJSON, _ := json.MarshalIndent(result.AuditLogs, "", "  ")
	fmt.Println("Chaining Audit Logs:")
	fmt.Println(string(auditJSON))
	fmt.Printf("Chain Success: %v | Success Rate: %.2f%% | Total Latency: %dms\n",
		result.Success, result.SuccessRate*100, result.LatencyMs)
}

Common Errors & Debugging

Error: 401 Unauthorized - Invalid OAuth Scope

• What causes it: The client credentials lack the ai:llm-gateway:invoke scope, or the token expired during chain execution.
• How to fix it: Verify the scope string in the /oauth/token request matches exactly. Ensure the AuthManager refreshes the token before each link execution.
• Code showing the fix: The GetToken method checks time.Until(a.ExpiresAt) and forces a refresh if less than 5 minutes remain, preventing mid-chain authentication failures.

Error: 429 Too Many Requests

• What causes it: Genesys Cloud enforces rate limits per tenant and per API endpoint. Rapid chain iterations trigger throttling.
• How to fix it: Implement exponential backoff. The ExecuteLink method includes a retry loop that waits 2, 4, and 6 seconds respectively before abandoning the request.
• Code showing the fix: The retry block in ExecuteLink checks resp.StatusCode == http.StatusTooManyRequests and applies time.Sleep before the next attempt.

Error: 400 Bad Request - Chain Validation Failed

• What causes it: The llm-matrix contains a circular reference, exceeds maximum-chain-depth, or violates token-budget-calculation.
• How to fix it: Review the ValidateChain output. Remove recursive Next pointers, reduce prompt length, or increase the budget. Ensure the graph traversal in validation matches your intended flow.
• Code showing the fix: The ValidateChain function returns a ValidationResult with explicit error strings. The main executor returns early if !validation.Valid, preventing malformed HTTP POSTs.

Error: 504 Gateway Timeout - Model Timeout Verification

• What causes it: The underlying LLM model takes longer than the model-timeout-seconds directive or Genesys Cloud proxy limits.
• How to fix it: Increase the Timeout field in the Link struct. Ensure the http.Client timeout matches or exceeds the model timeout. Add circuit breaker logic for repeated 504s.
• Code showing the fix: The InvocationRequest passes timeout via Parameters. The HTTP client timeout is set to 30 seconds, which should be adjusted per link requirements.

Official References

• Genesys Cloud LLM Gateway API Documentation
• OAuth 2.0 Client Credentials Flow
• Go net/http Package Reference
• Genesys Cloud Rate Limiting Guidelines