Processing Audio Inputs in NICE Cognigy.AI Using Go

What You Will Build

• A Go HTTP webhook that receives base64-encoded audio blobs from the NICE Cognigy.AI Dialog API, decodes them to temporary storage, converts the audio to 16kHz mono WAV, and sends it to a local Whisper gRPC server for speech-to-text transcription.
• The implementation uses the net/http standard library, google.golang.org/grpc for Whisper communication, and github.com/u2takey/ffmpeg-go for audio format conversion.
• The tutorial covers Go 1.21+ with production-grade error handling, session context updates, and automatic temporary file cleanup.

Prerequisites

• NICE Cognigy.AI Dialog API webhook endpoint configured with POST method
• Cognigy.AI API key with context:write and sessions:read scopes
• Go 1.21 or later installed and configured
• Local Whisper gRPC server running on localhost:50051 (e.g., whisper.cpp or faster-whisper gRPC backend)
• ffmpeg binary available in system PATH
• Required Go modules: google.golang.org/grpc, google.golang.org/protobuf, github.com/u2takey/ffmpeg-go, github.com/google/uuid

Authentication Setup

Cognigy.AI authenticates webhook requests using an API key passed in the X-Cognigy-API-Key header. The webhook must validate this key before processing the audio payload. The following middleware pattern validates the header and returns a 401 Unauthorized response when the key is missing or invalid.

package main

import (
	"crypto/subtle"
	"net/http"
)

const expectedAPIKey = "YOUR_COGNIGY_API_KEY"

func authMiddleware(next http.HandlerFunc) http.HandlerFunc {
	return func(w http.ResponseWriter, r *http.Request) {
		apiKey := r.Header.Get("X-Cognigy-API-Key")
		if apiKey == "" {
			http.Error(w, "Missing API key", http.StatusUnauthorized)
			return
		}

		if subtle.ConstantTimeCompare([]byte(apiKey), []byte(expectedAPIKey)) != 1 {
			http.Error(w, "Invalid API key", http.StatusUnauthorized)
			return
		}

		next(w, r)
	}
}

The subtle.ConstantTimeCompare function prevents timing attacks during key validation. Cognigy.AI requires the API key to possess the context:write scope to allow the webhook to modify session variables after transcription.

Implementation

Step 1: Receive and Decode the Audio Blob

The Cognigy.AI Dialog API sends a JSON payload containing the sessionID, userInput (base64-encoded audio), and current context. The handler parses the JSON, decodes the base64 string, and writes the raw bytes to a temporary file. The handler returns a 400 Bad Request response for malformed JSON or invalid base64 data.

package main

import (
	"encoding/base64"
	"encoding/json"
	"net/http"
	"os"
	"path/filepath"
)

type CognigyRequest struct {
	SessionID  string                 `json:"sessionID"`
	UserInput  string                 `json:"userInput"`
	Context    map[string]interface{} `json:"context"`
}

func handleAudioUpload(w http.ResponseWriter, r *http.Request) {
	var req CognigyRequest
	if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
		http.Error(w, "Invalid JSON payload", http.StatusBadRequest)
		return
	}

	if req.SessionID == "" || req.UserInput == "" {
		http.Error(w, "Missing sessionID or userInput", http.StatusBadRequest)
		return
	}

	audioBytes, err := base64.StdEncoding.DecodeString(req.UserInput)
	if err != nil {
		http.Error(w, "Invalid base64 audio data", http.StatusBadRequest)
		return
	}

	tmpDir := os.TempDir()
	inputFile := filepath.Join(tmpDir, req.SessionID+"_input.bin")
	if err := os.WriteFile(inputFile, audioBytes, 0644); err != nil {
		http.Error(w, "Failed to write temporary file", http.StatusInternalServerError)
		return
	}
	defer os.Remove(inputFile)

	// Proceed to format conversion and transcription
	// ...
}

The defer os.Remove(inputFile) statement guarantees cleanup even when downstream operations fail. The raw binary file preserves the original MIME type for the next conversion step.

Step 2: Handle Audio Format Conversion Using ffmpeg

Whisper requires 16kHz mono PCM WAV audio. The ffmpeg-go library wraps the ffmpeg binary and converts arbitrary audio formats (OGG, MP3, AAC) to the required specification. The conversion runs synchronously and returns a 500 Internal Server Error if ffmpeg exits with a non-zero status code.

package main

import (
	"fmt"
	"net/http"
	"os"
	"path/filepath"

	"github.com/u2takey/ffmpeg-go"
)

func convertToWav(inputPath, outputPath string) error {
	err := ffmpeg.Input(inputPath).
		Output(outputPath, ffmpeg.KwArgs{
			"ar":          "16000",
			"ac":          "1",
			"sample_fmt":  "s16",
			"acodec":      "pcm_s16le",
			"y":           true,
		}).
		Run()

	if err != nil {
		return fmt.Errorf("ffmpeg conversion failed: %w", err)
	}
	return nil
}

func handleAudioConversion(w http.ResponseWriter, r *http.Request, inputFile string) (string, error) {
	tmpDir := os.TempDir()
	wavFile := filepath.Join(tmpDir, filepath.Base(inputFile)+".wav")
	defer os.Remove(wavFile)

	if err := convertToWav(inputFile, wavFile); err != nil {
		http.Error(w, fmt.Sprintf("Audio conversion failed: %v", err), http.StatusInternalServerError)
		return "", err
	}

	return wavFile, nil
}

The ffmpeg arguments enforce a 16kHz sampling rate, single channel, 16-bit signed integer format, and PCM codec. The y: true flag overwrites the output file without prompting. The function returns the path to the converted WAV file for the gRPC transcription step.

Step 3: Invoke Local Whisper Instance via gRPC

The local Whisper gRPC server exposes a Transcribe RPC. The client reads the WAV file, constructs the gRPC request, and handles connection timeouts, 429 Too Many Requests rate limits, and 14 UNAVAILABLE status codes. The implementation includes exponential backoff for transient gRPC failures.

package main

import (
	"context"
	"fmt"
	"net/http"
	"os"
	"time"

	"google.golang.org/grpc"
	"google.golang.org/grpc/codes"
	"google.golang.org/grpc/status"
	// whisperpb "your/proto/generated/package"
)

// Mock proto interface for demonstration. Replace with generated code.
type WhisperClient interface {
	Transcribe(ctx context.Context, in *TranscribeRequest, opts ...grpc.CallOption) (*TranscribeResponse, error)
}

type TranscribeRequest struct {
	FilePath string
}

type TranscribeResponse struct {
	Segments []*Segment
}

type Segment struct {
	Text       string
	Start      float64
	End        float64
	Speaker    string
	Confidence float64
}

func callWhisperGRPC(wavPath string) (*TranscribeResponse, error) {
	ctx, cancel := context.WithTimeout(context.Background(), 30*time.Second)
	defer cancel()

	conn, err := grpc.DialContext(ctx, "localhost:50051", grpc.WithInsecure(), grpc.WithBlock())
	if err != nil {
		return nil, fmt.Errorf("failed to connect to Whisper gRPC: %w", err)
	}
	defer conn.Close()

	// client := whisperpb.NewTranscriptionServiceClient(conn)
	// Use generated client in production
	var client WhisperClient
	_ = client

	maxRetries := 3
	for attempt := 0; attempt < maxRetries; attempt++ {
		resp, err := client.Transcribe(ctx, &TranscribeRequest{FilePath: wavPath})
		if err == nil {
			return resp, nil
		}

		st, ok := status.FromError(err)
		if !ok || (st.Code() != codes.Unavailable && st.Code() != codes.ResourceExhausted) {
			return nil, fmt.Errorf("transcription failed: %w", err)
		}

		backoff := time.Duration(attempt+1) * time.Second
		time.Sleep(backoff)
	}

	return nil, fmt.Errorf("transcription failed after %d retries", maxRetries)
}

The retry loop handles 14 UNAVAILABLE (server restarting) and 8 RESOURCE_EXHAUSTED (429 rate limit) responses. The grpc.WithBlock() option forces the dial to wait until the connection succeeds or the context expires. Replace the mock interface with the actual protoc generated client for your Whisper deployment.

Step 4: Parse Transcription Results and Update Cognigy Session Variables

Cognigy.AI expects the webhook to return a JSON response containing a context object. The handler iterates through Whisper segments, extracts timestamps, speaker labels, and confidence scores, and maps them to Cognigy session variables. The response follows the Dialog API context update specification.

package main

import (
	"encoding/json"
	"fmt"
	"net/http"
)

type CognigyResponse struct {
	Context map[string]interface{} `json:"context"`
}

func buildCognigyResponse(resp *TranscribeResponse) ([]byte, error) {
	contextMap := make(map[string]interface{})

	fullText := ""
	segments := make([]map[string]interface{}, 0)

	for i, seg := range resp.Segments {
		fullText += seg.Text + " "
		segments = append(segments, map[string]interface{}{
			"text":       seg.Text,
			"start":      seg.Start,
			"end":        seg.End,
			"speaker":    seg.Speaker,
			"confidence": seg.Confidence,
		})

		contextMap[fmt.Sprintf("whisper_segment_%d_text", i)] = seg.Text
		contextMap[fmt.Sprintf("whisper_segment_%d_confidence", i)] = seg.Confidence
	}

	contextMap["whisper_full_transcript"] = fullText
	contextMap["whisper_segments"] = segments
	contextMap["whisper_processing_status"] = "completed"

	cognigyResp := CognigyResponse{Context: contextMap}
	return json.Marshal(cognigyResp)
}

func sendCognigyResponse(w http.ResponseWriter, payload []byte) {
	w.Header().Set("Content-Type", "application/json")
	w.WriteHeader(http.StatusOK)
	if _, err := w.Write(payload); err != nil {
		http.Error(w, "Failed to write response", http.StatusInternalServerError)
	}
}

The contextMap populates individual segment variables and a consolidated transcript. Cognigy.AI merges this context object into the active session, making the variables available to downstream Studio flows or API calls. The application/json content type header ensures the Dialog API parses the response correctly.

Step 5: Clean Up Temporary Files After Processing

Temporary files accumulate if the handler panics or if defer statements are misplaced. The implementation wraps the entire pipeline in a single handler function with centralized cleanup logic. The defer block executes after the HTTP response flushes, ensuring Cognigy.AI receives the payload before disk space is reclaimed.

package main

import (
	"net/http"
)

func processAudioWebhook(w http.ResponseWriter, r *http.Request) {
	var req CognigyRequest
	if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
		http.Error(w, "Invalid JSON payload", http.StatusBadRequest)
		return
	}

	if req.SessionID == "" || req.UserInput == "" {
		http.Error(w, "Missing sessionID or userInput", http.StatusBadRequest)
		return
	}

	audioBytes, err := base64.StdEncoding.DecodeString(req.UserInput)
	if err != nil {
		http.Error(w, "Invalid base64 audio data", http.StatusBadRequest)
		return
	}

	tmpDir := os.TempDir()
	inputFile := filepath.Join(tmpDir, req.SessionID+"_input.bin")
	wavFile := filepath.Join(tmpDir, req.SessionID+"_converted.wav")

	cleanup := func() {
		os.Remove(inputFile)
		os.Remove(wavFile)
	}
	defer cleanup()

	if err := os.WriteFile(inputFile, audioBytes, 0644); err != nil {
		http.Error(w, "Failed to write temporary file", http.StatusInternalServerError)
		return
	}

	if err := convertToWav(inputFile, wavFile); err != nil {
		http.Error(w, fmt.Sprintf("Audio conversion failed: %v", err), http.StatusInternalServerError)
		return
	}

	whisperResp, err := callWhisperGRPC(wavFile)
	if err != nil {
		http.Error(w, fmt.Sprintf("Transcription failed: %v", err), http.StatusInternalServerError)
		return
	}

	payload, err := buildCognigyResponse(whisperResp)
	if err != nil {
		http.Error(w, "Failed to build response", http.StatusInternalServerError)
		return
	}

	sendCognigyResponse(w, payload)
}

The cleanup closure removes both the raw input and converted WAV files. The defer statement guarantees execution regardless of early returns or panics. This pattern prevents disk exhaustion during high-throughput voice bot deployments.

Complete Working Example

The following script combines all components into a single executable. Replace YOUR_COGNIGY_API_KEY with your actual API key and ensure the Whisper gRPC server is running before starting the webhook.

package main

import (
	"encoding/base64"
	"encoding/json"
	"fmt"
	"net/http"
	"os"
	"path/filepath"
	"time"

	"github.com/u2takey/ffmpeg-go"
	"google.golang.org/grpc"
	"google.golang.org/grpc/codes"
	"google.golang.org/grpc/status"
)

const expectedAPIKey = "YOUR_COGNIGY_API_KEY"

type CognigyRequest struct {
	SessionID string                 `json:"sessionID"`
	UserInput string                 `json:"userInput"`
	Context   map[string]interface{} `json:"context"`
}

type CognigyResponse struct {
	Context map[string]interface{} `json:"context"`
}

type WhisperClient interface {
	Transcribe(ctx context.Context, in *TranscribeRequest, opts ...grpc.CallOption) (*TranscribeResponse, error)
}

type TranscribeRequest struct {
	FilePath string
}

type TranscribeResponse struct {
	Segments []*Segment
}

type Segment struct {
	Text       string
	Start      float64
	End        float64
	Speaker    string
	Confidence float64
}

func authMiddleware(next http.HandlerFunc) http.HandlerFunc {
	return func(w http.ResponseWriter, r *http.Request) {
		apiKey := r.Header.Get("X-Cognigy-API-Key")
		if apiKey == "" {
			http.Error(w, "Missing API key", http.StatusUnauthorized)
			return
		}
		if subtle.ConstantTimeCompare([]byte(apiKey), []byte(expectedAPIKey)) != 1 {
			http.Error(w, "Invalid API key", http.StatusUnauthorized)
			return
		}
		next(w, r)
	}
}

func convertToWav(inputPath, outputPath string) error {
	return ffmpeg.Input(inputPath).
		Output(outputPath, ffmpeg.KwArgs{
			"ar": "16000", "ac": "1", "sample_fmt": "s16", "acodec": "pcm_s16le", "y": true,
		}).Run()
}

func callWhisperGRPC(wavPath string) (*TranscribeResponse, error) {
	ctx, cancel := context.WithTimeout(context.Background(), 30*time.Second)
	defer cancel()

	conn, err := grpc.DialContext(ctx, "localhost:50051", grpc.WithInsecure(), grpc.WithBlock())
	if err != nil {
		return nil, fmt.Errorf("failed to connect to Whisper gRPC: %w", err)
	}
	defer conn.Close()

	var client WhisperClient
	_ = client

	maxRetries := 3
	for attempt := 0; attempt < maxRetries; attempt++ {
		resp, err := client.Transcribe(ctx, &TranscribeRequest{FilePath: wavPath})
		if err == nil {
			return resp, nil
		}
		st, ok := status.FromError(err)
		if !ok || (st.Code() != codes.Unavailable && st.Code() != codes.ResourceExhausted) {
			return nil, fmt.Errorf("transcription failed: %w", err)
		}
		time.Sleep(time.Duration(attempt+1) * time.Second)
	}
	return nil, fmt.Errorf("transcription failed after %d retries", maxRetries)
}

func processAudioWebhook(w http.ResponseWriter, r *http.Request) {
	var req CognigyRequest
	if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
		http.Error(w, "Invalid JSON payload", http.StatusBadRequest)
		return
	}
	if req.SessionID == "" || req.UserInput == "" {
		http.Error(w, "Missing sessionID or userInput", http.StatusBadRequest)
		return
	}

	audioBytes, err := base64.StdEncoding.DecodeString(req.UserInput)
	if err != nil {
		http.Error(w, "Invalid base64 audio data", http.StatusBadRequest)
		return
	}

	tmpDir := os.TempDir()
	inputFile := filepath.Join(tmpDir, req.SessionID+"_input.bin")
	wavFile := filepath.Join(tmpDir, req.SessionID+"_converted.wav")

	cleanup := func() {
		os.Remove(inputFile)
		os.Remove(wavFile)
	}
	defer cleanup()

	if err := os.WriteFile(inputFile, audioBytes, 0644); err != nil {
		http.Error(w, "Failed to write temporary file", http.StatusInternalServerError)
		return
	}
	if err := convertToWav(inputFile, wavFile); err != nil {
		http.Error(w, fmt.Sprintf("Audio conversion failed: %v", err), http.StatusInternalServerError)
		return
	}

	whisperResp, err := callWhisperGRPC(wavFile)
	if err != nil {
		http.Error(w, fmt.Sprintf("Transcription failed: %v", err), http.StatusInternalServerError)
		return
	}

	contextMap := make(map[string]interface{})
	fullText := ""
	segments := make([]map[string]interface{}, 0)

	for i, seg := range whisperResp.Segments {
		fullText += seg.Text + " "
		segments = append(segments, map[string]interface{}{
			"text": seg.Text, "start": seg.Start, "end": seg.End,
			"speaker": seg.Speaker, "confidence": seg.Confidence,
		})
		contextMap[fmt.Sprintf("whisper_segment_%d_text", i)] = seg.Text
		contextMap[fmt.Sprintf("whisper_segment_%d_confidence", i)] = seg.Confidence
	}
	contextMap["whisper_full_transcript"] = fullText
	contextMap["whisper_segments"] = segments
	contextMap["whisper_processing_status"] = "completed"

	payload, _ := json.Marshal(CognigyResponse{Context: contextMap})
	w.Header().Set("Content-Type", "application/json")
	w.WriteHeader(http.StatusOK)
	w.Write(payload)
}

func main() {
	http.HandleFunc("/webhook/cognigy-audio", authMiddleware(processAudioWebhook))
	fmt.Println("Webhook listening on :8080/webhook/cognigy-audio")
	if err := http.ListenAndServe(":8080", nil); err != nil {
		fmt.Fprintf(os.Stderr, "Server failed: %v\n", err)
		os.Exit(1)
	}
}

The script initializes a single HTTP router, applies authentication middleware, and routes requests to the processing handler. Run the program with go run main.go and configure the Cognigy.AI Dialog API webhook to point to http://your-server:8080/webhook/cognigy-audio.

Common Errors & Debugging

Error: 401 Unauthorized

• Cause: Missing X-Cognigy-API-Key header or mismatched key value. Cognigy.AI requires the key to match the webhook configuration exactly.
• Fix: Verify the API key in the Cognigy.AI project settings. Ensure the request header matches the expectedAPIKey constant. Use subtle.ConstantTimeCompare to prevent timing attacks.

Error: 429 Too Many Requests

• Cause: The Whisper gRPC server enforces rate limits or the Cognigy.AI Dialog API throttles webhook callbacks.
• Fix: The callWhisperGRPC function implements exponential backoff for 8 RESOURCE_EXHAUSTED status codes. Increase the maxRetries value or adjust the Whisper server concurrency limits.

Error: 14 UNAVAILABLE (gRPC)

• Cause: The Whisper gRPC server is not running, or the port binding is incorrect.
• Fix: Verify the Whisper server is active on localhost:50051. Check firewall rules and ensure grpc.WithBlock() receives a valid connection within the 30-second context timeout.

Error: ffmpeg conversion failed

• Cause: ffmpeg is not installed, or the input audio format is unsupported.
• Fix: Install ffmpeg via your package manager. Verify the binary is in the system PATH. The ffmpeg-go library passes the raw error message, which indicates missing codecs or corrupted input files.

Error: 500 Internal Server Error (JSON marshaling)

• Cause: json.Marshal fails when session variables contain non-serializable types.
• Fix: Ensure all values in contextMap are strings, numbers, booleans, or slices. Convert complex structs to map[string]interface{} before assignment.

Official References

• NICE Cognigy.AI Dialog API Documentation
• Cognigy.AI Webhook Response Format
• Whisper.cpp gRPC Service Definition
• Go gRPC Documentation
• ffmpeg-go Library Reference