azure-communication-callautomation-java

作者: microsoft

使用 Azure Communication Services Call Automation Java SDK 構建通話自動化工作流程。適用於實作 IVR 系統、通話路由、通話錄音、DTMF 辨識、文字轉語音或 AI 驅動的通話流程。

npx skills add https://github.com/microsoft/skills --skill 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.core.credential.TokenCredential;
import com.azure.identity.AzureIdentityEnvVars;
import com.azure.identity.DefaultAzureCredentialBuilder;
import com.azure.identity.ManagedIdentityCredentialBuilder;

// Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
TokenCredential credential = new DefaultAzureCredentialBuilder()
    .requireEnvVars(AzureIdentityEnvVars.AZURE_TOKEN_CREDENTIALS)
    .build();
// Or use a specific credential directly in production:
// See https://learn.microsoft.com/java/api/overview/azure/identity-readme?view=azure-java-stable#credential-classes
// TokenCredential credential = new ManagedIdentityCredentialBuilder().build();

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

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

Key Concepts

ClassPurpose
CallAutomationClientMake calls, answer/reject incoming calls, redirect calls
CallConnectionActions in established calls (add participants, terminate)
CallMediaMedia operations (play audio, recognize DTMF/speech)
CallRecordingStart/stop/pause recording
CallAutomationEventParserParse webhook events from ACS

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  # Required for all auth methods
AZURE_COMMUNICATION_CONNECTION_STRING=endpoint=https://...;accesskey=...  # Alternative to Entra ID auth
CALLBACK_BASE_URL=https://your-app.com/api/callbacks  # Required for webhook callbacks
AZURE_TOKEN_CREDENTIALS=prod  # Required only if DefaultAzureCredential is used in production

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"

來自 microsoft 的更多技能

oss-growth
microsoft
開源增長駭客角色
agent-framework-azure-ai-py
microsoft
使用Microsoft Agent Framework Python SDK(agent-framework-azure-ai)构建Azure AI Foundry代理。适用于使用AzureAIAgentsProvider创建持久化代理、使用托管工具(代码解释器、文件搜索、网络搜索)、集成MCP服务器、管理对话线程或实现流式响应。涵盖函数工具、结构化输出和多工具代理。
development
airunway-aks-setup
microsoft
在AKS上設定AI Runway——從裸叢集到執行模型。涵蓋叢集驗證、控制器安裝、GPU評估、供應商設定及首次部署。時機:「設定AI Runway」、「上線AKS叢集」、「安裝AI Runway」、「airunway設定」、「部署模型至AKS」、「在AKS上進行GPU推論」、「在AKS上設定KAITO」、「在AKS上執行LLM」、「在AKS上使用vLLM」、「在AKS上設定模型服務」、「AI Runway控制器」。
devops
appinsights-instrumentation
microsoft
使用Azure Application Insights檢測Web應用程式的指南。提供遙測模式、SDK設定與組態參考。適用時機:如何檢測應用程式、App Insights SDK、遙測模式、什麼是App Insights、Application Insights指南、檢測範例、APM最佳實踐。
devops
applicationinsights-web-ts
microsoft
使用Application Insights JavaScript SDK(@microsoft/applicationinsights-web)為瀏覽器/Web應用程式進行檢測。適用於真實使用者監控(RUM)——頁面檢視、點擊、AJAX/fetch依賴、例外、自訂事件,以及與後端OpenTelemetry追蹤關聯的瀏覽器端GenAI代理追蹤。涵蓋SDK載入器指令碼與npm設定、框架擴充(React、React Native、Angular)、點擊分析、遙測初始化器,以及從瀏覽器發出的代理/工具/模型span的OTel GenAI語意慣例。
devops
azure-ai-anomalydetector-java
microsoft
使用適用於 Java 的 Azure AI 異常偵測器 SDK 建置異常偵測應用程式。在實作單變量/多變量異常偵測、時間序列分析或 AI 驅動監控時使用。
development
azure-ai-language-conversations-py
microsoft
使用 azure-ai-language-conversations Python SDK 實作對話語言理解(CLU)。當使用 ConversationAnalysisClient 分析對話意圖與實體、建置 NLP 功能,或將語言理解整合至應用程式時使用。
development
azure-ai-ml-py
microsoft
Azure Machine Learning SDK v2 for Python。用於機器學習工作區、作業、模型、資料集、計算資源與管線。 觸發詞:「azure-ai-ml」、「MLClient」、「workspace」、「model registry」、「training jobs」、「datasets」。
development