Enabling Event-Streaming Operations

Server-sent events (SSE) is a core web feature that provides servers with a low overhead solution to push real-time events to the client when they become available. SSE can be used to stream chat completions from a large language model, real-time stock prices, and sensor readings to clients.

SSE is similar to WebSockets in that it uses a persistent connection but differs in that it is unidirectional - only the server sends events. SSE is simpler to implement in many existing backend HTTP frameworks.

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INFO

Speakeasy makes it easy to build SSE into generated SDKs without vendor extensions or heuristics. Leverage SSE by modeling SSE streams as text/event-stream responses with pure OpenAPI.

Here’s a short example of using an SDK to chat with an LLM and read its response as a stream:

import { SDK } from '@speakeasy/sdk';
const sdk = new SDK()
const response = await sdk.chat.create({
prompt: "What are the top 3 French cheeses by consumption?"
})
for await (const event of response.chatStream) {
process.stdout.write(event.data);
}
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INFO

The SSE feature is currently supported in TypeScript, Python, Go, and Java. Let us know if you’d like to see support for other languages.

Modeling SSE in OpenAPI

To implement SSE in a generated SDKs, model an API endpoint that serves an event stream in an OpenAPI document. Each server-sent event can contain up to four types of fields: id, event, data, and retry.

Basic Implementation

The example below illustrates an operation that streams events containing only a data field that holds string content:

paths:
/chat:
post:
summary: Create a chat completion from a prompt
operationId: create
tags: [chat]
requestBody:
required: true
content:
application/json:
schema:
$ref: "#/components/schemas/ChatRequest"
responses:
"200":
description: Chat completion created
content:
text/event-stream:
schema:
$ref: "#/components/schemas/ChatStream"
components:
schemas:
ChatRequest:
type: object
required: [prompt]
properties:
prompt:
type: string
ChatStream:
description: A server-sent event containing chat completion content
type: object
required: [data]
properties:
data:
type: string

When data is a JSON Object

SSE implementation isn’t limited to string data. If data is specified as an object instead of a string, then SDKs will assume the field will contain JSON content. Raw data received from the server will be deserialized into an object for the application code to consume.

components:
schemas:
ChatStream:
description: A server-sent event containing chat completion content
type: object
required: [data]
properties:
data:
type: object
properties:
content:
type: string
model:
type: string
enum: ["foo-gpt-tiny", "foo-gpt-small"]
created:
type: integer

The Speakeasy-generated TypeScript SDK for the example above will allow users to access this object:

for await (const event of response.chatStream) {
const { content, model, created } = event.data;
process.stdout.write(content);
}

Handling Multiple Event Types

Other streaming APIs send multiple types of events with the id and event fields. These event types can be described as a union (oneOf) with the event field acting as a discriminator:

components:
schemas:
ChatStream:
oneOf:
- $ref: "#/components/schemas/HeartbeatEvent"
- $ref: "#/components/schemas/ChatEvent"
discriminator:
propertyName: event
mapping:
ping: "#/components/schemas/HeartbeatEvent"
completion: "#/components/schemas/ChatEvent"
HeartbeatEvent:
description: A server-sent event indicating that the server is still processing the request
type: object
required: [event]
properties:
event:
type: string
const: "ping"
ChatEvent:
description: A server-sent event containing chat completion content
type: object
required: [id, event, data]
properties:
id:
type: string
event:
type: string
const: completion
data:
type: object
required: [content]
properties:
content:
type: string

Endpoints with Multiple Response Types

For APIs that handle both JSON responses and streaming events, use URL fragments to define separate paths for each response type. Each fragment maps to a specific behavior—either returning a complete JSON response or streaming data. This approach allows Speakeasy to generate distinct SDK methods with clear return types while maintaining API flexibility.

paths:
/chat:
post:
summary: >
Create a chat completion from a prompt. The entire response is
returned as a single JSON object.
operationId: create
tags: [chat]
requestBody:
required: true
content:
application/json:
schema:
$ref: "#/components/schemas/ChatRequestJson"
responses:
"200":
description: Chat completion created
content:
application/json:
schema:
$ref: "#/components/schemas/ChatResponse"
/chat#streamed:
post:
summary: >
Create a chat completion from a prompt. The response is streamed in
chunks as it is generated.
operationId: createStreamed
tags: [chat]
requestBody:
required: true
content:
application/json:
schema:
$ref: "#/components/schemas/ChatRequestStream"
responses:
"200":
description: Chat completion created
content:
text/event-stream:
schema:
$ref: "#/components/schemas/ChatStream"
components:
schemas:
ChatRequest:
# ...
ChatRequestJson:
allOf:
- $ref: "#/components/schemas/ChatRequest"
- type: object
properties:
stream:
type: boolean
enum: [false]
default: false
ChatRequestStream:
allOf:
- $ref: "#/components/schemas/ChatRequest"
- type: object
properties:
stream:
type: boolean
enum: [true]
default: true
ChatResponse:
# ...
ChatStream:
# ...
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IMPORTANT

The stream properties in the ChatRequestJson and ChatRequestStream schemas are treated as constants, ensuring that each request type always has a fixed stream value (false for JSON responses and true for streamed responses). In OpenAPI 3.0, this is achieved using single-value enums. For OpenAPI 3.1, simplify schema by using the const field instead of enum, which explicitly defines the property as having a constant value. This makes the specification more concise and easier to maintain.

See the Speakeasy OpenAPI reference on enums for more information.

Use chat for the non-streaming endpoint and chatStreamed for the streaming endpoint:

import { SDK } from '@speakeasy/sdk';
const sdk = new SDK()
// Non-streaming method
const jsonResponse = await sdk.chat.create({
prompt: "What are the top 3 French cheeses by consumption?"
});
console.log(jsonResponse.content);
// Streaming method
const stream = await sdk.chat.createStreamed({
prompt: "What are the top 3 French cheeses by consumption?"
});
for await (const event of response.chatStream) {
process.stdout.write(event.data);
}
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NOTE

Accross all of these examples, the schema for the events only ever specifies one or more of the four recognized fields. Adding other fields will trigger a validation error when generating an SDK with the Speakeasy CLI or GitHub action.

Sentinel events

Some SSE APIs will terminate the stream by sending a final, special event. This sentinel event is only used to signal that there are no more events and is not intended for application code to handle.

In the example below, the final data: [DONE] event is the sentinel event:

HTTP/1.1 200 OK
Content-Type: text/event-stream; charset=utf-8
Date: Fri, 12 Jul 2024 14:29:22 GMT
Keep-Alive: timeout=5, max=1000
Connection: Keep-Alive
data: {"content": "there"}
data: {"content": "are 7"}
data: {"content": "continents in the world"}
data: [DONE]

To hide this final event in generated SDK methods, use the x-speakeasy-sse-sentinel: <string> extension on a text/event-stream media object:

paths:
/chat:
post:
summary: Create a chat completion from a prompt
operationId: create
tags: [chat]
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/ChatRequest'
responses:
'200':
description: Chat completion created
content:
text/event-stream:
+ x-speakeasy-sse-sentinel: '[DONE]'
schema:
$ref: '#/components/schemas/ChatEvent'
components:
schemas:
ChatEvent:
description: A server-sent event containing chat completion content
type: object
required: [data]
properties:
data:
type: object
required: [content]
properties:
content:
type: string

Application code like the following TypeScript sample will behave as expected. The async iteration loop will finish when the sentinel event is encountered:

const llm = new LLM();
const stream = await llm.chat.create({
prompt: "How many continents are there?",
});
for await (const event of stream) {
// ^? ChatEvent
process.stdout.write(event.data.content);
}