time multimodal-Java SDK

The key interfaces and request parameters for Qwen-Omni real-time DashScope Java SDK.

Prerequisites

Your Java SDK version must be v2.22.15 or later. Before you begin, see Real-time multimodal interaction flow.

Getting started

Download the sample code from GitHub. Three calling methods are available:

1. Audio conversation example: Captures real-time audio from a microphone, enables Voice Activity Detection (VAD) mode, which automatically detects the start and end of speech, and supports voice interruption.

   Set the enableTurnDetection parameter to true. Use headphones for audio playback to prevent echoes from triggering voice interruption.

2. Audio and video conversation example: Captures real-time audio and video from a microphone and camera, enables VAD mode, and supports voice interruption.

   Set the enableTurnDetection parameter to true. Use headphones for audio playback to prevent echoes from triggering voice interruption.

3. Local call: Uses local audio and images as input and enables Manual mode, which lets you manually control the sending pace.

   Set the enableTurnDetection parameter to false.

Request parameters

Configure the following request parameters using the chained methods or setters of the OmniRealtimeParam object, and then pass it to the OmniRealtimeConversation constructor.

Parameter	Type	Description
model	String	The Qwen-Omni model to use. See Model list.
url	String	The endpoint URL: - Singapore region: wss://dashscope-intl.aliyuncs.com/api-ws/v1/realtime - Beijing region: wss://dashscope.aliyuncs.com/api-ws/v1/realtime

Configure the following request parameters using the chained methods or setters of the OmniRealtimeConfig object, and then pass it to the updateSession method. Parameter Type Description modalities List The model output modality. Set to [OmniRealtimeModality.TEXT] for text only, or [OmniRealtimeModality.TEXT, OmniRealtimeModality.AUDIO] for both audio and text. voice String The voice for audio output. For supported voices, see Voice list. Default voice:

• Qwen3.5-Omni: "Tina"
• Qwen3-Omni-Flash-Realtime: "Cherry"
• Qwen-Omni-Turbo-Realtime: "Chelsie" inputAudioFormat OmniRealtimeAudioFormat Input audio format. Only PCM_16000HZ_MONO_16BIT is supported. outputAudioFormat OmniRealtimeAudioFormat Output audio format. Only pcm is supported. instructions String A system message that sets the goal or role for the model. Example: "You are an AI customer service agent for a five-star hotel. Answer customer questions about room types, facilities, prices, and booking policies accurately and in a friendly manner. Always respond professionally and helpfully. Do not provide unverified information or information outside the scope of the hotel's services."

**

**Note ** Set instructions using the OmniRealtimeConfig instance's parameters method:

conversation.updateSession(OmniRealtimeConfig.builder()
 .modalities(Arrays.asList(OmniRealtimeModality.AUDIO, OmniRealtimeModality.TEXT))
 .voice("Tina")
 .enableTurnDetection(true)
 .enableInputAudioTranscription(true)
 .parameters(Map.of(
 "instructions", "You are a personal assistant named Xiaoyun"
 ))
 .build()
);

 smooth_output   Boolean   This parameter is supported only by the Qwen3-Omni-Flash-Realtime series.

• true: The model provides conversational responses.

• false: The model provides more formal, written-style responses. ** However, performance may be suboptimal if the content is difficult to read aloud.

• null: The default value. The model automatically chooses between conversational and formal response styles. Set smooth_output using the OmniRealtimeConfig instance's parameters method. The usage is the same as instructions. enableInputAudioTranscription Boolean Enables speech recognition for input audio. InputAudioTranscription String Speech recognition model for input audio transcription. The value is always qwen3-asr-flash-realtime. This parameter is not configurable. enableTurnDetection Boolean Enables VAD. If disabled, you must manually submit audio to create a response. turnDetectionType String The VAD type. Valid values:

• server_vad (default): Detects the end of user speech based on acoustic features.

• semantic_vad: Detects the end of user speech based on semantic validity. This mode can filter out meaningless speech, such as backchannels and background noise. This option is supported only by the qwen3.5-omni-realtime model. turnDetectionThreshold Float VAD detection threshold. Increase in noisy environments and decrease in quiet environments.

• The closer the value is to -1, the more likely noise is to be detected as speech.

• The closer the value is to 1, the less likely noise is to be detected as speech. Default: 0.5. Valid values: [-1.0, 1.0]. turnDetectionSilenceDurationMs Integer Silence duration that indicates end of speech. If exceeded, the model triggers a response. Default: 800. Valid values: [200, 6000]. enable_search Boolean <b>This parameter takes effect only when you use the Qwen3.5-Omni-Realtime model.** Enables web search. Default: false. When enabled, the model can search the web to answer real-time questions. ** enable_search and search_options parameters must be set using the parameters method of the OmniRealtimeConfig instance. The process is the same for instructions. Tool calling (tools) and web search (enable_search) are incompatible and cannot be enabled at the same time. search_options Object Web search option settings. This parameter takes effect only after enable_search is enabled. You can set enable_source (Boolean) to true to return a list of search result sources. search_options using the OmniRealtimeConfig instance's parameters method. The usage is the same as for instructions. tools List> <b>This parameter takes effect only when you use the Qwen3.5-Omni-Realtime model.** Tool definitions. When provided, the model can call external tools to respond to user questions. If a tool is called, the model does not generate audio and only returns the tool calling parameters. Each tool is a Map that contains the following fields:

• type (String, required): The value is fixed to "function".

• function (Map, required): The definition of the tool function. This field contains the following subfields: <li> name (String, required): A custom name for the tool function. We recommend that you use the same name as the function, such as get_current_weather or get_current_time.

• description (String, optional): A description of the tool function. The model uses this description to decide whether to call the function.

• parameters (Map, optional): Input parameter descriptions. The model uses them to extract parameters. If the tool function does not require input parameters, you do not need to specify this field. This field contains the following subfields: <li> type (String, required): The value is fixed to "object".

• properties (Map, optional): Describes the name, data type, and description of each input parameter. The Key is the parameter name, and the Value is a Map that contains the data type (type) and description (description).

• required (List, optional): Specifies which input parameters are required. </li> </li> ** search_options using the OmniRealtimeConfig instance's parameters method. The usage is the same as for instructions. temperature Float Sampling temperature that controls content diversity. Higher values produce more diverse content; lower values produce more deterministic content. Valid values: [0, 2). Because both temperature and top_p control content diversity, we recommend that you set only one of them. Default values of temperature:

• qwen3.5-omni-realtime series: 0.7

• qwen3-omni-flash-realtime series: 0.9

• qwen-omni-turbo-realtime series: 1.0 qwen-omni-turbo models <b>do not support modification**. ** temperature parameter using the parameters method of the OmniRealtimeConfig instance, in the same way you set the instructions parameter. top_p Float* * Probability threshold for nucleus sampling that controls content diversity. Higher values produce more diverse content; lower values produce more deterministic content. Valid values: (0, 1.0]. Because both temperature and top_p control content diversity, we recommend that you set only one of them. Default values of top_p:

• qwen3.5-omni-realtime series: 0.8

• qwen3-omni-flash-realtime series: 1.0

• qwen-omni-turbo-realtime series: 0.01 qwen-omni-turbo models <b>do not support modification**. ** top_p using the OmniRealtimeConfig instance's parameters method. The usage is the same as for instructions. top_k Integer* * Candidate set size for sampling. For example, 50 means only the 50 highest-scoring tokens form the candidate set. Larger values increase randomness; smaller values increase determinism. Set to None or a value greater than 100 to disable top_k and use only top_p. The value must be greater than or equal to 0. Default values of top_k:

• qwen3.5-omni-realtime series: 20

• qwen3-omni-flash-realtime series: 50

• qwen-omni-turbo-realtime series: 20 qwen-omni-turbo models <b>do not support modification**. ** top_k using the OmniRealtimeConfig instance's parameters method. The usage is the same as for instructions. max_tokens Integer Maximum number of tokens to return. max_tokens setting does not affect the generation process of the model. If the number of tokens generated by the model exceeds max_tokens, the returned content is truncated. Default and maximum values equal the model's maximum output length. See Model list for details. Use max_tokens to limit output length for generating summaries, keywords, controlling costs, or reducing response time. qwen-omni-turbo models <b>do not support modification**. ** max_tokens using the OmniRealtimeConfig instance's parameters method. The usage is the same as for instructions. repetition_penalty Float* * Controls repetition in generated sequences. Higher values reduce repetition. 1.0 means no penalty. Must be greater than 0. Default values of repetition_penalty:

• qwen3.5-omni-realtime series: 1.0

• Other models: 1.05 qwen-omni-turbo models <b>do not support modification**. ** repetition_penalty using the OmniRealtimeConfig instance's parameters method. The usage is the same as for instructions. presence_penalty Float* * Controls content repetition in model output. Valid values: [-2.0, 2.0]. Positive values reduce repetition; negative values increase it. Default values of presence_penalty:

• qwen3.5-omni-realtime series: 1.5

• Other models: 0.0 Scenarios: Higher values suit scenarios requiring diversity or creativity, such as creative writing or brainstorming. Lower values suit scenarios requiring consistency or technical precision, such as technical documents. qwen-omni-turbo models <b>do not support modification**. ** presence_penalty using the OmniRealtimeConfig instance's parameters method. The usage is the same as for instructions. seed <b> Integer * Makes generation more deterministic, ensuring consistent results across runs. Passing the same seed with identical parameters produces the same result as much as possible. Valid values: 0 to 231−1. Default value: -1. ** qwen-omni-turbo models <b>do not support modification*. ** seed using the OmniRealtimeConfig instance's parameters method. The usage is the same as for instructions.

Key interfaces

OmniRealtimeConversation class

Import with import com.alibaba.dashscope.audio.omni.OmniRealtimeConversation;. Method signature Server response event (sent via callback) Description

public void connect() throws NoApiKeyException, InterruptedException

Server events Session created session.updated Session configuration updated Creates a connection to the server.

public void updateSession(OmniRealtimeConfig config)

session.updated Session configuration updated Updates session configuration. For parameter details, see Request parameters. After connecting, the server returns default session configurations. Call this method immediately after connecting to update settings. When the server receives the session.update event, it validates the parameters. Invalid parameters return an error; otherwise the server updates session configuration.

public void appendAudio(String audioBase64)

None   Appends Base64-encoded audio to the cloud input buffer. The buffer is temporary storage that can be written to and committed later.

• If "turn_detection" is enabled, the audio buffer is used to detect speech, and the server decides when to commit.
• If "turn_detection" is disabled, the client can send up to 15 MiB of audio per event. Streaming smaller blocks makes VAD more responsive.

public void appendVideo(String videoBase64)

None   Adds Base64-encoded image data to the cloud video buffer. Accepts local images or real-time video stream captures. Image input limits:

• The image format must be JPG or JPEG. The recommended image resolution is 480p or 720p, with a maximum of 1080p.
• The size of a single image cannot exceed 500 KB (before Base64 encoding).
• The image data must be Base64-encoded.
• We recommend that you send images to the server at a frequency of 1 image per second.

public void clearAppendedAudio()

input_audio_buffer.cleared  The audio received by the server is cleared    Deletes the audio in the current cloud buffer.

public void commit()

input_audio_buffer.committed  The server received the committed audio    Commits audio and video from the cloud buffer. Returns an error if the buffer is empty.

• If "turn_detection" is enabled, the client does not need to send this event. The server automatically commits the audio buffer.

• If "turn_detection" is disabled, the client must commit the audio buffer to create a user message item. <b>Note:**

• If input_audio_transcription is configured for the session, the system transcribes the audio.

• Committing the input audio buffer does not create a response from the model.

public void createResponse(String instructions, List<OmniRealtimeModality> modalities)

Server events The server starts to generate a response response.output_item.added New output content is available in the response Server events A conversation item is created response.content_part.added New output content is added to the assistant message item response.audio_transcript.delta Incrementally generated transcribed text response.audio.delta Incrementally generated audio from the model response.audio_transcript.done Text transcription is complete response.audio.done Audio generation is complete response.content_part.done Streaming of text or audio content for the assistant message is complete response.output_item.done Streaming of the entire output item for the assistant message is complete response.done The response is complete Instructs the server to create a model response. When the session is configured in "turn_detection" mode, the server automatically creates a model response.

public void cancelResponse()

None   Cancels the in-progress response. If no response is available to cancel, the server returns an error.

public void createItem(JsonObject item)

None   Sends the `conversation.item.create` event to the server. In a tool calling scenario, this method is used to send the tool execution result back to the server. The item parameter is a JsonObject and must contain the following fields:

• type: The value is fixed to "function_call_output".
• call_id: Corresponds to the call_id in the response.function_call_arguments.done event.
• output: A string that represents the tool execution result.

public void close()

None   Stops the task and closes the connection.

public String getSessionId()

None   Gets the session ID of the current task.

public String getResponseId()

None   Gets the response ID of the most recent response.

Callback interface (OmniRealtimeCallback)

The server returns response events and data via callbacks. Implement callback methods to process server responses.

Import with import com.alibaba.dashscope.audio.omni.OmniRealtimeCallback;. Method Parameter Return value Description

public void onOpen()

None None Called immediately after a connection is established with the server.

public abstract void onEvent(JsonObject message)

message: The server response event.   None   Contains interface call responses and model-generated text and audio. See Server events.

public abstract void onClose(int code, String reason)

code: The status code for closing the WebSocket. reason: The reason for closing the WebSocket.   None   Called after the connection to the server is closed.

FAQ

Q: How are the input audio and images aligned?

The Qwen-Omni real-time model uses the audio stream as the input timeline. Images are inserted into the audio stream based on the time they are sent. You can add images at any point in the audio timeline.

In real-time interaction scenarios, you can enable or disable video input at any time.

Q: What is the recommended frequency for inputting images and audio?

In real-time interaction scenarios, we recommend that you send images at a frame rate of 1 or 2 fps and send audio in 100 ms packets.

Q: What are the differences between the two modes of the turn_detection switch?

When turn_detection is enabled, it supports two modes: server_vad and semantic_vad:

• Enable "turn_detection":

  • Input state: The cloud-based VAD detects the end of a sentence in the input audio and immediately triggers Qwen-Omni inference to return the reply text and speech.

  • Response state: In this state, you can continue to send audio and video input without interruption while the model is responding. After the response is complete, the state returns to the input state to await the next speech input.

  • Interruption: If the user starts speaking while the model is responding, an interruption is triggered. The service immediately stops the current response and switches to the input state.

• Disable "turn_detection":

  • You must manually determine the end of a round of audio and video input and trigger Qwen-Omni inference to obtain a response using commit and create_response.

  • While the model is responding, you must stop sending audio and video input. You can resume input for the next round only after the model has finished responding.

  • You must use the cancel_response method to interrupt the model's response.

Note that when turn_detection is enabled, you can still actively trigger a response using commit and create_response, and actively interrupt it using cancel_response.

Q: Why do I need to select another model for input_audio_transcription?

Qwen-Omni real-time is an end-to-end multimodal model. Its text output is a response to the input, not a direct transcription of the input audio. A separate ASR model is required for transcription. Currently, the model is determined by the built-in configuration and is not configurable.