Class SessionExperimental

constructor

• new Session(conn: WebSocket, apiClient: ApiClient): Session
  Experimental

  Parameters

  • conn: WebSocket
  • apiClient: ApiClient

  Returns Session

Readonly Experimentalconn

close

• close(): void
  Experimental

  Terminates the WebSocket connection.

  Returns void

  Example

  const session = await ai.live.connect({
    model: 'gemini-2.0-flash-exp',
    config: {
      responseModalities: [Modality.AUDIO],
    }
  });
  
  session.close();
  Copy

sendClientContent

• sendClientContent(params: SessionSendClientContentParameters): void
  Experimental

  Send a message over the established connection.

  Parameters

  • params: SessionSendClientContentParameters

    Contains two optional properties, turns and turnComplete.

    • turns will be converted to a Content[]
    • turnComplete: true indicates that you are done sending content and expect a response.

  Returns void

  Remanks

  There are two ways to send messages to the live API: sendClientContent and sendRealtimeInput.

  sendClientContent messages are added to the model context in order. Having a conversation using sendClientContent messages is roughly equivalent to using the Chat.sendMessageStream, except that the state of the chat history is stored on the API server instead of locally.

  Because of sendClientContent's order guarantee, the model cannot respons as quickly to sendClientContent messages as to sendRealtimeInput messages. This makes the biggest difference when sending objects that have significant preprocessing time (typically images).

  The sendClientContent message sends a Content[] which has more options than the Blob sent by sendRealtimeInput.

  So the main use-cases for sendClientContent over sendRealtimeInput are:

  • Sending anything that can't be represented as a Blob (text, sendClientContent({turns="Hello?"})).
  • Managing turns when not using audio input and voice activity detection. (sendClientContent({turnComplete:true}) or the short form sendClientContent())
  • Prefilling a conversation context

    sendClientContent({
        turns: [
          Content({role:user, parts:...}),
          Content({role:user, parts:...}),
          ...
        ]
    })
    Copy

sendRealtimeInput

• sendRealtimeInput(params: SessionSendRealtimeInputParameters): void
  Experimental

  Send a realtime message over the established connection.

  Parameters

  • params: SessionSendRealtimeInputParameters

    Contains one property, media.

    • media will be converted to a Blob

  Returns void

  Remanks

  Use sendRealtimeInput for realtime audio chunks and video frames (images).

  With sendRealtimeInput the api will respond to audio automatically based on voice activity detection (VAD).

  sendRealtimeInput is optimized for responsivness at the expense of deterministic ordering guarantees. Audio and video tokens are to the context when they become available.

  Note: The Call signature expects a Blob object, but only a subset of audio and image mimetypes are allowed.

sendToolResponse

• sendToolResponse(params: SessionSendToolResponseParameters): void
  Experimental

  Send a function response message over the established connection.

  Parameters

  • params: SessionSendToolResponseParameters

    Contains property functionResponses.

    • functionResponses will be converted to a functionResponses[]

  Returns void

  Remanks

  Use sendFunctionResponse to reply to LiveServerToolCall from the server.

  Use LiveConnectConfig#tools to configure the callable functions.