| layout | default |
|---|---|
| title | Chapter 2: Realtime API Fundamentals |
| nav_order | 2 |
| parent | OpenAI Realtime Agents Tutorial |
Welcome to Chapter 2: Realtime API Fundamentals. In this part of OpenAI Realtime Agents Tutorial: Voice-First AI Systems, you will build an intuitive mental model first, then move into concrete implementation details and practical production tradeoffs.
Realtime systems are event systems first and model systems second. Reliability comes from mastering session state and event flow.
By the end of this chapter, you should be able to:
- map session lifecycle states clearly
- choose the right transport for your product constraints
- debug event-ordering and reconnect issues
- plan around current GA and deprecation timelines
A practical lifecycle looks like this:
- client requests short-lived session credentials
- client opens realtime transport
- session configuration is set (modalities, instructions, tool policy)
- user input is committed to conversation
- responses and tool events stream continuously
- session is gracefully closed or resumed after reconnect
| Transport | Best For | Tradeoff |
|---|---|---|
| WebRTC | browser voice UX and low-latency media | more moving parts in signaling/media handling |
| WebSocket | server-side pipelines and custom clients | you own more media/runtime behavior |
- treat every event as observable and traceable
- avoid relying on undocumented ordering assumptions
- make unknown events non-fatal in client handlers
- keep event handlers idempotent when possible
OpenAI deprecation docs currently list February 27, 2026 as the Realtime beta interface shutdown date. New builds should target GA semantics and avoid beta-only behavior.
When issues occur, classify first:
- connection issue (transport/session establishment)
- protocol issue (event ordering/invalid payload)
- model issue (quality/content)
- tool/runtime issue (external dependency failures)
This prevents wasting time tuning prompts for transport bugs.
- schema validation for incoming/outgoing events
- reconnect strategy with bounded retries
- timeout and cancellation behavior for long operations
- structured logging for session, event type, and outcome
You now understand the realtime lifecycle and have a framework for protocol-level debugging and migration-safe implementation.
Next: Chapter 3: Voice Input Processing
The GuardrailResultType interface in src/app/types.ts handles a key part of this chapter's functionality:
export type AllAgentConfigsType = Record<string, AgentConfig[]>;
export interface GuardrailResultType {
status: "IN_PROGRESS" | "DONE";
testText?: string;
category?: ModerationCategory;
rationale?: string;
}
export interface TranscriptItem {
itemId: string;
type: "MESSAGE" | "BREADCRUMB";
role?: "user" | "assistant";
title?: string;
data?: Record<string, any>;
expanded: boolean;
timestamp: string;
createdAtMs: number;
status: "IN_PROGRESS" | "DONE";
isHidden: boolean;
guardrailResult?: GuardrailResultType;
}
export interface Log {
id: number;
timestamp: string;
direction: string;
eventName: string;
data: any;
expanded: boolean;
type: string;
}This interface is important because it defines how OpenAI Realtime Agents Tutorial: Voice-First AI Systems implements the patterns covered in this chapter.
The TranscriptItem interface in src/app/types.ts handles a key part of this chapter's functionality:
toolLogic?: Record<
string,
(args: any, transcriptLogsFiltered: TranscriptItem[], addTranscriptBreadcrumb?: (title: string, data?: any) => void) => Promise<any> | any
>;
// addTranscriptBreadcrumb is a param in case we want to add additional breadcrumbs, e.g. for nested tool calls from a supervisor agent.
downstreamAgents?:
| AgentConfig[]
| { name: string; publicDescription: string }[];
}
export type AllAgentConfigsType = Record<string, AgentConfig[]>;
export interface GuardrailResultType {
status: "IN_PROGRESS" | "DONE";
testText?: string;
category?: ModerationCategory;
rationale?: string;
}
export interface TranscriptItem {
itemId: string;
type: "MESSAGE" | "BREADCRUMB";
role?: "user" | "assistant";
title?: string;
data?: Record<string, any>;
expanded: boolean;
timestamp: string;
createdAtMs: number;
status: "IN_PROGRESS" | "DONE";
isHidden: boolean;
guardrailResult?: GuardrailResultType;
}This interface is important because it defines how OpenAI Realtime Agents Tutorial: Voice-First AI Systems implements the patterns covered in this chapter.
The Log interface in src/app/types.ts handles a key part of this chapter's functionality:
instructions: string;
tools: Tool[];
toolLogic?: Record<
string,
(args: any, transcriptLogsFiltered: TranscriptItem[], addTranscriptBreadcrumb?: (title: string, data?: any) => void) => Promise<any> | any
>;
// addTranscriptBreadcrumb is a param in case we want to add additional breadcrumbs, e.g. for nested tool calls from a supervisor agent.
downstreamAgents?:
| AgentConfig[]
| { name: string; publicDescription: string }[];
}
export type AllAgentConfigsType = Record<string, AgentConfig[]>;
export interface GuardrailResultType {
status: "IN_PROGRESS" | "DONE";
testText?: string;
category?: ModerationCategory;
rationale?: string;
}
export interface TranscriptItem {
itemId: string;
type: "MESSAGE" | "BREADCRUMB";
role?: "user" | "assistant";
title?: string;
data?: Record<string, any>;
expanded: boolean;
timestamp: string;
createdAtMs: number;
status: "IN_PROGRESS" | "DONE";
isHidden: boolean;This interface is important because it defines how OpenAI Realtime Agents Tutorial: Voice-First AI Systems implements the patterns covered in this chapter.
The ServerEvent interface in src/app/types.ts handles a key part of this chapter's functionality:
}
export interface ServerEvent {
type: string;
event_id?: string;
item_id?: string;
transcript?: string;
delta?: string;
session?: {
id?: string;
};
item?: {
id?: string;
object?: string;
type?: string;
status?: string;
name?: string;
arguments?: string;
role?: "user" | "assistant";
content?: {
type?: string;
transcript?: string | null;
text?: string;
}[];
};
response?: {
output?: {
id: string;
type?: string;
name?: string;
arguments?: any;
call_id?: string;This interface is important because it defines how OpenAI Realtime Agents Tutorial: Voice-First AI Systems implements the patterns covered in this chapter.
flowchart TD
A[GuardrailResultType]
B[TranscriptItem]
C[Log]
D[ServerEvent]
E[LoggedEvent]
A --> B
B --> C
C --> D
D --> E