Azure Communication Callautomation Java

Azure Communication Call Automation (Java)

Build server-side call automation workflows including IVR systems, call routing, recording, and AI-powered interactions.

Installation

<dependency>
    <groupId>com.azure</groupId>
    <artifactId>azure-communication-callautomation</artifactId>
    <version>1.6.0</version>
</dependency>

Client Creation

import com.azure.communication.callautomation.CallAutomationClient;
import com.azure.communication.callautomation.CallAutomationClientBuilder;
import com.azure.identity.DefaultAzureCredentialBuilder;

// With DefaultAzureCredential
CallAutomationClient client = new CallAutomationClientBuilder()
    .endpoint("https://<resource>.communication.azure.com")
    .credential(new DefaultAzureCredentialBuilder().build())
    .buildClient();

// With connection string
CallAutomationClient client = new CallAutomationClientBuilder()
    .connectionString("<connection-string>")
    .buildClient();

Key Concepts

Create Outbound Call

import com.azure.communication.callautomation.models.*;
import com.azure.communication.common.CommunicationUserIdentifier;
import com.azure.communication.common.PhoneNumberIdentifier;

// Call to PSTN number
PhoneNumberIdentifier target = new PhoneNumberIdentifier("+14255551234");
PhoneNumberIdentifier caller = new PhoneNumberIdentifier("+14255550100");

CreateCallOptions options = new CreateCallOptions(
    new CommunicationUserIdentifier("<user-id>"),  // Source
    List.of(target))                                // Targets
    .setSourceCallerId(caller)
    .setCallbackUrl("https://your-app.com/api/callbacks");

CreateCallResult result = client.createCall(options);
String callConnectionId = result.getCallConnectionProperties().getCallConnectionId();

Answer Incoming Call

// From Event Grid webhook - IncomingCall event
String incomingCallContext = "<incoming-call-context-from-event>";

AnswerCallOptions options = new AnswerCallOptions(
    incomingCallContext,
    "https://your-app.com/api/callbacks");

AnswerCallResult result = client.answerCall(options);
CallConnection callConnection = result.getCallConnection();

Play Audio (Text-to-Speech)

CallConnection callConnection = client.getCallConnection(callConnectionId);
CallMedia callMedia = callConnection.getCallMedia();

// Play text-to-speech
TextSource textSource = new TextSource()
    .setText("Welcome to Contoso. Press 1 for sales, 2 for support.")
    .setVoiceName("en-US-JennyNeural");

PlayOptions playOptions = new PlayOptions(
    List.of(textSource),
    List.of(new CommunicationUserIdentifier("<target-user>")));

callMedia.play(playOptions);

// Play audio file
FileSource fileSource = new FileSource()
    .setUrl("https://storage.blob.core.windows.net/audio/greeting.wav");

callMedia.play(new PlayOptions(List.of(fileSource), List.of(target)));

Recognize DTMF Input

// Recognize DTMF tones
DtmfTone stopTones = DtmfTone.POUND;

CallMediaRecognizeDtmfOptions recognizeOptions = new CallMediaRecognizeDtmfOptions(
    new CommunicationUserIdentifier("<target-user>"),
    5)  // Max tones to collect
    .setInterToneTimeout(Duration.ofSeconds(5))
    .setStopTones(List.of(stopTones))
    .setInitialSilenceTimeout(Duration.ofSeconds(15))
    .setPlayPrompt(new TextSource().setText("Enter your account number followed by pound."));

callMedia.startRecognizing(recognizeOptions);

Recognize Speech

// Speech recognition with AI
CallMediaRecognizeSpeechOptions speechOptions = new CallMediaRecognizeSpeechOptions(
    new CommunicationUserIdentifier("<target-user>"))
    .setEndSilenceTimeout(Duration.ofSeconds(2))
    .setSpeechLanguage("en-US")
    .setPlayPrompt(new TextSource().setText("How can I help you today?"));

callMedia.startRecognizing(speechOptions);

Call Recording

CallRecording callRecording = client.getCallRecording();

// Start recording
StartRecordingOptions recordingOptions = new StartRecordingOptions(
    new ServerCallLocator("<server-call-id>"))
    .setRecordingChannel(RecordingChannel.MIXED)
    .setRecordingContent(RecordingContent.AUDIO_VIDEO)
    .setRecordingFormat(RecordingFormat.MP4);

RecordingStateResult recordingResult = callRecording.start(recordingOptions);
String recordingId = recordingResult.getRecordingId();

// Pause/resume/stop
callRecording.pause(recordingId);
callRecording.resume(recordingId);
callRecording.stop(recordingId);

// Download recording (after RecordingFileStatusUpdated event)
callRecording.downloadTo(recordingUrl, Paths.get("recording.mp4"));

Add Participant to Call

CallConnection callConnection = client.getCallConnection(callConnectionId);

CommunicationUserIdentifier participant = new CommunicationUserIdentifier("<user-id>");
AddParticipantOptions addOptions = new AddParticipantOptions(participant)
    .setInvitationTimeout(Duration.ofSeconds(30));

AddParticipantResult result = callConnection.addParticipant(addOptions);

Transfer Call

// Blind transfer
PhoneNumberIdentifier transferTarget = new PhoneNumberIdentifier("+14255559999");
TransferCallToParticipantResult result = callConnection.transferCallToParticipant(transferTarget);

Handle Events (Webhook)

import com.azure.communication.callautomation.CallAutomationEventParser;
import com.azure.communication.callautomation.models.events.*;

// In your webhook endpoint
public void handleCallback(String requestBody) {
    List<CallAutomationEventBase> events = CallAutomationEventParser.parseEvents(requestBody);
    
    for (CallAutomationEventBase event : events) {
        if (event instanceof CallConnected) {
            CallConnected connected = (CallConnected) event;
            System.out.println("Call connected: " + connected.getCallConnectionId());
        } else if (event instanceof RecognizeCompleted) {
            RecognizeCompleted recognized = (RecognizeCompleted) event;
            // Handle DTMF or speech recognition result
            DtmfResult dtmfResult = (DtmfResult) recognized.getRecognizeResult();
            String tones = dtmfResult.getTones().stream()
                .map(DtmfTone::toString)
                .collect(Collectors.joining());
            System.out.println("DTMF received: " + tones);
        } else if (event instanceof PlayCompleted) {
            System.out.println("Audio playback completed");
        } else if (event instanceof CallDisconnected) {
            System.out.println("Call ended");
        }
    }
}

Hang Up Call

// Hang up for all participants
callConnection.hangUp(true);

// Hang up only this leg
callConnection.hangUp(false);

Error Handling

import com.azure.core.exception.HttpResponseException;

try {
    client.answerCall(options);
} catch (HttpResponseException e) {
    if (e.getResponse().getStatusCode() == 404) {
        System.out.println("Call not found or already ended");
    } else if (e.getResponse().getStatusCode() == 400) {
        System.out.println("Invalid request: " + e.getMessage());
    }
}

Environment Variables

AZURE_COMMUNICATION_ENDPOINT=https://<resource>.communication.azure.com
AZURE_COMMUNICATION_CONNECTION_STRING=endpoint=https://...;accesskey=...
CALLBACK_BASE_URL=https://your-app.com/api/callbacks

Trigger Phrases

• "call automation Java", "IVR Java", "interactive voice response"
• "call recording Java", "DTMF recognition Java"
• "text to speech call", "speech recognition call"
• "answer incoming call", "transfer call Java"
• "Azure Communication Services call automation"

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

AGI Framework Integration

Adapted for @techwavedev/agi-agent-kit Original source: antigravity-awesome-skills

Memory-First Protocol

Cache workflow configurations and automation patterns. Retrieve prior pipeline designs to avoid re-building similar flows from scratch.

# Check for prior workflow/automation context before starting
python3 execution/memory_manager.py auto --query "automation patterns and workflow configurations for Azure Communication Callautomation Java"

Storing Results

After completing work, store workflow/automation decisions for future sessions:

python3 execution/memory_manager.py store \
  --content "Workflow: automated data pipeline with retry logic, dead-letter queue, and Slack alerts on failure" \
  --type technical --project <project> \
  --tags azure-communication-callautomation-java workflow

Multi-Agent Collaboration

Share workflow state with other agents so they can trigger, monitor, or extend the automation.

python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Workflow automation deployed — pipeline processing 1000+ events/day with 99.9% success rate" \
  --project <project>

Playbook Engine

Combine this skill with others using the Playbook Engine (execution/workflow_engine.py) for guided multi-step automation with progress tracking.

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