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articles/ai-services/openai/how-to/realtime-audio.md

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## Supported models
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The GPT 4o realtime models are available for global deployments in [East US 2 and Sweden Central regions](../concepts/models.md#global-standard-model-availability).
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The GPT 4o real-time models are available for global deployments in [East US 2 and Sweden Central regions](../concepts/models.md#global-standard-model-availability).
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- `gpt-4o-realtime-preview` (2024-12-17)
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- `gpt-4o-realtime-preview` (2024-10-01)
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```
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When the server responds with a [`response.done`](../realtime-audio-reference.md#realtimeservereventresponsecreated) event, the response will contain the metadata you provided. You can identify the corresponding response for the client-sent event via the `response.metadata` field.
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When the server responds with a [`response.done`](../realtime-audio-reference.md#realtimeservereventresponsecreated) event, the response contains the metadata you provided. You can identify the corresponding response for the client-sent event via the `response.metadata` field.
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> [!IMPORTANT]
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> If you create any responses outside the default conversation, be sure to always check the `response.metadata` field to help you identify the corresponding response for the client-sent event. You should even check the `response.metadata` field for responses that are part of the default conversation. That way, you can ensure that you're handling the correct response for the client-sent event.
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### Custom context for out-of-band responses
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You can also construct a custom context that the model will use outside of the session's default conversation. To create a response with custom context, set the `conversation` field to `none` and provide the custom context in the `input` array. The `input` array can contain new inputs or references to existing conversation items.
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You can also construct a custom context that the model uses outside of the session's default conversation. To create a response with custom context, set the `conversation` field to `none` and provide the custom context in the `input` array. The `input` array can contain new inputs or references to existing conversation items.
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```json
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{
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## Voice activity detection (VAD) and the audio buffer
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The server maintains an input audio buffer containing client-provided audio that has not yet been committed to the conversation state.
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The server maintains an input audio buffer containing client-provided audio that hasn't yet been committed to the conversation state.
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One of the key [session-wide](#session-configuration) settings is `turn_detection`, which controls how data flow is handled between the caller and model. The `turn_detection` setting can be set to `none` or `server_vad` (to use [server-side voice activity detection](#server-decision-mode)).
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### VAD without automatic response generation
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You can use server-side voice activity detection (VAD) without automatic response generation. This can be useful when you want to implement some degree of moderation.
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You can use server-side voice activity detection (VAD) without automatic response generation. This approach can be useful when you want to implement some degree of moderation.
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Set [`turn_detection.create_response`](../realtime-audio-reference.md#realtimeturndetection) to `false` via the [session.update](../realtime-audio-reference.md#realtimeclienteventsessionupdate) event. VAD will detect the end of speech but the server won't generate a response until you send a [`response.create`](../realtime-audio-reference.md#realtimeclienteventresponsecreate) event.
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Set [`turn_detection.create_response`](../realtime-audio-reference.md#realtimeturndetection) to `false` via the [session.update](../realtime-audio-reference.md#realtimeclienteventsessionupdate) event. VAD detects the end of speech but the server doesn't generate a response until you send a [`response.create`](../realtime-audio-reference.md#realtimeclienteventresponsecreate) event.
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```json
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## Conversation and response generation
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The Realtime API is designed to handle real-time, low-latency conversational interactions. The API is built on a series of events that allow the client to send and receive messages, control the flow of the conversation, and manage the state of the session.
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The GPT-4o real-time audio models are designed for real-time, low-latency conversational interactions. The API is built on a series of events that allow the client to send and receive messages, control the flow of the conversation, and manage the state of the session.
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### Conversation sequence and items
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