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feat(ai): preserve streamed refusals as text (#43343)

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This commit is contained in:
Aiden Cline
2026-08-20 00:47:18 -05:00
committed by GitHub
parent 99490f289b
commit 5b1e8450e7
5 changed files with 249 additions and 2 deletions
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packages/ai/src/protocols/open-responses.ts
+22
View File
@@ -298,6 +298,20 @@ export const Event = Schema.StructWithRest(
)
export type Event = Schema.Schema.Type<typeof Event>
const RefusalEvent = Schema.Union([
Schema.Struct({
type: Schema.tag("response.refusal.delta"),
item_id: Schema.String,
delta: Schema.String,
}),
Schema.Struct({
type: Schema.tag("response.refusal.done"),
item_id: Schema.String,
refusal: Schema.String,
}),
])
const isRefusalEvent = Schema.is(RefusalEvent)
export interface Extension {
readonly id: string
readonly name: string
@@ -1073,6 +1087,14 @@ export const step = (state: ParserState, event: Event) => {
: onOutputTextDone(state, event, event.item_id),
)
}
if (event.type === "response.refusal.delta" || event.type === "response.refusal.done") {
if (!isRefusalEvent(event)) return ProviderShared.eventError(state.id, `${event.type} is malformed`)
return Effect.succeed(
event.type === "response.refusal.delta"
? onOutputTextDelta(state, event, event.item_id)
: onOutputTextDone(state, { ...event, text: event.refusal }, event.item_id),
)
}
if (event.type === "response.reasoning.delta" || event.type === "response.reasoning_summary_text.delta") {
if (!event.item_id) return ProviderShared.eventError(state.id, `${event.type} is missing item_id`)
return Effect.succeed(onReasoningDelta(state, event, event.item_id))
packages/ai/src/protocols/openai-chat.ts
+14 -2
View File
@@ -28,7 +28,7 @@ import { ToolSchemaProjection } from "./utils/tool-schema.js"
import { ToolStream } from "./utils/tool-stream.js"
const ADAPTER = "openai-chat"
const RESERVED_REASONING_FIELDS = new Set(["role", "content", "tool_calls"])
const RESERVED_REASONING_FIELDS = new Set(["role", "content", "refusal", "tool_calls"])
export const DEFAULT_BASE_URL = "https://api.openai.com/v1"
export const PATH = "/chat/completions"
@@ -194,6 +194,7 @@ type OpenAIChatToolCallDelta = Schema.Schema.Type<typeof OpenAIChatToolCallDelta
const OpenAIChatDelta = Schema.StructWithRest(
Schema.Struct({
content: optionalNull(Schema.String),
refusal: optionalNull(Schema.String),
reasoning_content: optionalNull(Schema.String),
reasoning: optionalNull(Schema.String),
reasoning_text: optionalNull(Schema.String),
@@ -709,6 +710,7 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
const reasoning = reasoningDelta(delta, state.reasoningField)
const hasLateContent =
Boolean(delta?.content) ||
Boolean(delta?.refusal) ||
reasoning !== undefined ||
(Array.isArray(delta?.reasoning_details) && delta.reasoning_details.length > 0) ||
toolDeltas.some((tool) => Boolean(tool.id) || Boolean(tool.function?.name) || Boolean(tool.function?.arguments))
@@ -728,7 +730,7 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
else if (
reasoningDetailsObserved &&
!lifecycle.reasoning.has("reasoning-0") &&
(Boolean(delta?.content) || toolDeltas.length > 0)
(Boolean(delta?.content) || Boolean(delta?.refusal) || toolDeltas.length > 0)
)
lifecycle = Lifecycle.reasoningStart(lifecycle, events, "reasoning-0", deltaMetadata)
const reasoningEmitted = state.reasoningEmitted || lifecycle.reasoning.has("reasoning-0")
@@ -743,6 +745,16 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
lifecycle = Lifecycle.textDelta(lifecycle, events, "text-0", delta.content)
}
if (delta?.refusal) {
lifecycle = Lifecycle.reasoningEnd(
lifecycle,
events,
"reasoning-0",
reasoningMetadata(reasoningField, reasoningDetailsObserved ? state.reasoningDetails : undefined),
)
lifecycle = Lifecycle.textDelta(lifecycle, events, "text-0", delta.refusal)
}
// Compatible providers may omit indexes. Prefer durable identity, then use
// batch position for parallel deltas or the latest call for sparse chunks.
for (const [position, tool] of toolDeltas.entries()) {
packages/ai/test/provider/openai-chat.test.ts
+68
View File
@@ -664,6 +664,74 @@ describe("OpenAI Chat route", () => {
}),
)
it.effect("preserves streamed refusals as ordinary assistant text", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(request).pipe(
Effect.provide(
fixedResponse(
sseEvents(
deltaChunk({ role: "assistant", refusal: "I can't" }),
deltaChunk({ refusal: " help with that." }),
deltaChunk({}, "stop"),
),
),
),
)
expect(response.text).toBe("I can't help with that.")
expect(response.finishReason).toEqual({ normalized: "stop", raw: "stop" })
expect(response.message.content).toEqual([{ type: "text", text: "I can't help with that." }])
const replay = yield* compileRequest(LLM.request({ model, messages: [response.message] }))
expect(replay.body.messages).toEqual([{ role: "assistant", content: "I can't help with that." }])
}),
)
it.effect("orders metadata-only reasoning before refusal output", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(request).pipe(
Effect.provide(
fixedResponse(
sseEvents(
{ choices: [{ delta: { reasoning_details: [] } }] },
deltaChunk({ refusal: "I can't help with that." }),
deltaChunk({}, "stop"),
),
),
),
)
expect(response.message.content).toEqual([
{ type: "reasoning", text: "", providerMetadata: { openai: { reasoningDetails: [] } } },
{
type: "text",
text: "I can't help with that.",
},
])
}),
)
it.effect("joins content and refusal deltas into ordinary assistant text", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(request).pipe(
Effect.provide(
fixedResponse(
sseEvents(
deltaChunk({ refusal: "No." }),
deltaChunk({ content: " Alternative." }),
deltaChunk({ refusal: " Still no." }),
deltaChunk({}, "stop"),
),
),
),
)
expect(response.text).toBe("No. Alternative. Still no.")
expect(response.events.filter(LLMEvent.is.textStart).map((event) => event.id)).toEqual(["text-0"])
expect(response.events.filter(LLMEvent.is.textEnd).map((event) => event.id)).toEqual(["text-0"])
}),
)
it.effect("parses and replays OpenAI-compatible reasoning fields", () =>
Effect.gen(function* () {
const fields = ["reasoning_content", "reasoning", "reasoning_text"] as const
packages/ai/test/provider/openai-compatible-responses.test.ts
+45
View File
@@ -118,6 +118,51 @@ describe("Open Responses-compatible route", () => {
}),
)
it.effect("preserves standard refusal content as ordinary assistant text", () =>
Effect.gen(function* () {
const model = configure({
apiKey: "test-key",
baseURL: "https://responses.example.test/v1",
provider: "example",
}).model("example-model")
const response = yield* LLMClient.generate(LLM.request({ model, prompt: "Unsafe request" })).pipe(
Effect.provide(
fixedResponse(
sseEvents(
{
type: "response.output_item.added",
output_index: 0,
item: { type: "message", id: "msg_refusal", content: [] },
},
{
type: "response.refusal.done",
item_id: "msg_refusal",
refusal: "I can't help with that.",
},
{
type: "response.output_item.done",
output_index: 0,
item: {
type: "message",
id: "msg_refusal",
content: [{ type: "refusal", refusal: "I can't help with that." }],
},
},
{ type: "response.completed", response: { id: "resp_1" } },
),
),
),
)
expect(response.message.content).toEqual([{ type: "text", text: "I can't help with that." }])
const prepared = yield* compileRequest(LLM.request({ model, messages: [response.message] }))
expect(prepared.body.input).toEqual([
{ role: "assistant", content: [{ type: "output_text", text: "I can't help with that." }] },
])
}),
)
it.effect("reads standard Open Responses options", () =>
Effect.gen(function* () {
const model = configure({
packages/ai/test/provider/openai-responses.test.ts
+100
View File
@@ -1505,6 +1505,106 @@ describe("OpenAI Responses route", () => {
}),
)
it.effect("preserves standard refusal content as ordinary assistant text", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(request).pipe(
Effect.provide(
fixedResponse(
sseEvents(
{
type: "response.output_item.added",
output_index: 0,
item: { type: "message", id: "msg_refusal", content: [] },
},
{
type: "response.content_part.added",
item_id: "msg_refusal",
output_index: 0,
content_index: 0,
part: { type: "refusal", refusal: "" },
},
{
type: "response.refusal.delta",
item_id: "msg_refusal",
output_index: 0,
content_index: 0,
delta: "I can't",
},
{
type: "response.refusal.delta",
item_id: "msg_refusal",
output_index: 0,
content_index: 0,
delta: " help with that.",
},
{
type: "response.refusal.done",
item_id: "msg_refusal",
output_index: 0,
content_index: 0,
refusal: "I can't help with that.",
},
{
type: "response.content_part.done",
item_id: "msg_refusal",
output_index: 0,
content_index: 0,
part: { type: "refusal", refusal: "I can't help with that." },
},
{
type: "response.output_item.done",
output_index: 0,
item: {
type: "message",
id: "msg_refusal",
phase: "final_answer",
content: [{ type: "refusal", refusal: "I can't help with that." }],
},
},
{ type: "response.completed", response: { id: "resp_1" } },
),
),
),
)
expect(response.text).toBe("I can't help with that.")
expect(response.finishReason).toEqual({ normalized: "stop", raw: undefined })
expect(response.message.content).toEqual([
{
type: "text",
text: "I can't help with that.",
providerMetadata: { openai: { phase: "final_answer" } },
},
])
const prepared = yield* compileRequest(LLM.request({ model, messages: [response.message] }))
expect(prepared.body.input).toEqual([
{
role: "assistant",
content: [{ type: "output_text", text: "I can't help with that." }],
phase: "final_answer",
},
])
}),
)
it.effect("rejects malformed refusal events", () =>
Effect.gen(function* () {
const events = [
{ type: "response.refusal.delta", output_index: 0, content_index: 0, delta: "missing item" },
{ type: "response.refusal.delta", item_id: "msg_1", output_index: 0, content_index: 0 },
{ type: "response.refusal.done", item_id: "msg_1", output_index: 0, content_index: 0 },
]
for (const event of events) {
const error = yield* LLMClient.generate(request).pipe(
Effect.provide(fixedResponse(sseEvents(event))),
Effect.flip,
)
expect(error.reason._tag).toBe("InvalidProviderOutput")
}
}),
)
it.effect("preserves and replays assistant message phases", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(request).pipe(