fix(ai): preserve OpenAI message phases

packages/ai/src/protocols/openai-responses.ts

@@ -62,6 +62,9 @@ const OpenAIResponsesOutputText = Schema.Struct({
   text: Schema.String,
 })
 
+const OpenAIResponsesMessagePhase = Schema.Literals(["commentary", "final_answer"])
+type OpenAIResponsesMessagePhase = Schema.Schema.Type<typeof OpenAIResponsesMessagePhase>
+
 const OpenAIResponsesReasoningSummaryText = Schema.Struct({
   type: Schema.tag("summary_text"),
   text: Schema.String,
@@ -96,7 +99,11 @@ const OpenAIResponsesFunctionCallOutput = Schema.Union([
 const OpenAIResponsesInputItem = Schema.Union([
   Schema.Struct({ role: Schema.tag("system"), content: Schema.String }),
   Schema.Struct({ role: Schema.tag("user"), content: Schema.Array(OpenAIResponsesInputContent) }),
-  Schema.Struct({ role: Schema.tag("assistant"), content: Schema.Array(OpenAIResponsesOutputText) }),
+  Schema.Struct({
+    role: Schema.tag("assistant"),
+    content: Schema.Array(OpenAIResponsesOutputText),
+    phase: optionalNull(OpenAIResponsesMessagePhase),
+  }),
   OpenAIResponsesReasoningItem,
   OpenAIResponsesItemReference,
   Schema.Struct({
@@ -216,6 +223,7 @@ const OpenAIResponsesStreamItem = Schema.Struct({
   // call's typed input portion and round-trip the full result payload without
   // hand-rolling a per-tool schema.
   status: Schema.optional(Schema.String),
+  phase: optionalNull(OpenAIResponsesMessagePhase),
   action: Schema.optional(Schema.Unknown),
   queries: Schema.optional(Schema.Unknown),
   results: Schema.optional(Schema.Unknown),
@@ -271,6 +279,7 @@ interface ParserState {
   readonly tools: ToolStream.State<string>
   readonly hasFunctionCall: boolean
   readonly lifecycle: Lifecycle.State
+  readonly textItems: Readonly<Record<string, ProviderMetadata>>
   readonly reasoningItems: Readonly<Record<string, ReasoningStreamItem>>
   readonly store: boolean | undefined
 }
@@ -395,10 +404,7 @@ const lowerToolResultContentItem = Effect.fn("OpenAIResponses.lowerToolResultCon
   provider: string,
 ) {
   if (item.type === "text") return { type: "input_text" as const, text: item.text }
-  return yield* lowerMedia(
+  return yield* lowerMedia({ type: "media", mediaType: item.mime, data: item.uri, filename: item.name }, provider)
-    { type: "media", mediaType: item.mime, data: item.uri, filename: item.name },
-    provider,
-  )
 })
 
 const lowerToolResultOutput = Effect.fn("OpenAIResponses.lowerToolResultOutput")(function* (
@@ -442,16 +448,29 @@ const lowerMessages = Effect.fn("OpenAIResponses.lowerMessages")(function* (requ
 
     if (message.role === "assistant") {
       const content: TextPart[] = []
+      let phase: OpenAIResponsesMessagePhase | undefined
       const reasoningItems: Record<string, OpenAIResponsesReasoningReplay> = {}
       const reasoningReferences = new Set<string>()
       const hostedToolReferences = new Set<string>()
       const flushText = () => {
         if (content.length === 0) return
-        input.push({ role: "assistant", content: content.map((part) => ({ type: "output_text", text: part.text })) })
+        input.push({
+          role: "assistant",
+          content: content.map((part) => ({ type: "output_text", text: part.text })),
+          ...(phase === undefined ? {} : { phase }),
+        })
         content.splice(0, content.length)
+        phase = undefined
       }
       for (const part of message.content) {
         if (part.type === "text") {
+          const openai = part.providerMetadata?.openai
+          const nextPhase =
+            ProviderShared.isRecord(openai) && (openai.phase === "commentary" || openai.phase === "final_answer")
+              ? openai.phase
+              : undefined
+          if (content.length > 0 && phase !== nextPhase) flushText()
+          phase = nextPhase
           content.push(part)
           continue
         }
@@ -709,15 +728,28 @@ const TERMINAL_TYPES = new Set(["response.completed", "response.incomplete", "re
 const onOutputTextDelta = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {
   if (!event.delta) return [state, NO_EVENTS]
   const events: LLMEvent[] = []
+  const itemID = event.item_id ?? "text-0"
   return [
-    { ...state, lifecycle: Lifecycle.textDelta(state.lifecycle, events, event.item_id ?? "text-0", event.delta) },
+    {
+      ...state,
+      lifecycle: Lifecycle.textDelta(state.lifecycle, events, itemID, event.delta, state.textItems[itemID]),
+    },
     events,
   ]
 }
 
 const onOutputTextDone = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {
   const events: LLMEvent[] = []
-  return [{ ...state, lifecycle: Lifecycle.textEnd(state.lifecycle, events, event.item_id ?? "text-0") }, events]
+  const itemID = event.item_id ?? "text-0"
+  const { [itemID]: _completed, ...textItems } = state.textItems
+  return [
+    {
+      ...state,
+      lifecycle: Lifecycle.textEnd(state.lifecycle, events, itemID, state.textItems[itemID]),
+      textItems,
+    },
+    events,
+  ]
 }
 
 const onReasoningDelta = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {
@@ -754,6 +786,21 @@ const reasoningMetadata = (item: OpenAIResponsesStreamItem & { id: string }) =>
 // best-effort, not guaranteed.
 const onOutputItemAdded = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {
   const item = event.item
+  if (item?.type === "message" && item.id) {
+    return [
+      {
+        ...state,
+        textItems: {
+          ...state.textItems,
+          [item.id]: openaiMetadata({
+            itemId: item.id,
+            ...(item.phase === undefined || item.phase === null ? {} : { phase: item.phase }),
+          }),
+        },
+      },
+      NO_EVENTS,
+    ]
+  }
   if (item && isReasoningItem(item)) {
     const events: LLMEvent[] = []
     return [
@@ -1063,6 +1110,7 @@ export const protocol = Protocol.make({
       hasFunctionCall: false,
       tools: ToolStream.empty<string>(),
       lifecycle: Lifecycle.initial(),
+      textItems: {},
       reasoningItems: {},
       store: OpenAIOptions.store(request),
     }),

packages/ai/src/protocols/utils/lifecycle.ts

@@ -14,16 +14,25 @@ export const stepStart = (state: State, events: LLMEvent[]): State => {
   return { ...state, stepStarted: true }
 }
 
-export const textDelta = (state: State, events: LLMEvent[], id: string, text: string): State => {
+export const textStart = (state: State, events: LLMEvent[], id: string, providerMetadata?: ProviderMetadata): State => {
+  if (state.text.has(id)) return state
   const stepped = stepStart(state, events)
-  if (stepped.text.has(id)) {
+  events.push(LLMEvent.textStart({ id, providerMetadata }))
-    events.push(LLMEvent.textDelta({ id, text }))
-    return stepped
-  }
-  events.push(LLMEvent.textStart({ id }), LLMEvent.textDelta({ id, text }))
   return { ...stepped, text: new Set([...stepped.text, id]) }
 }
 
+export const textDelta = (
+  state: State,
+  events: LLMEvent[],
+  id: string,
+  text: string,
+  providerMetadata?: ProviderMetadata,
+): State => {
+  const started = textStart(state, events, id, providerMetadata)
+  events.push(LLMEvent.textDelta({ id, text, providerMetadata }))
+  return started
+}
+
 export const reasoningStart = (
   state: State,
   events: LLMEvent[],

packages/ai/test/provider/openai-responses.test.ts

@@ -899,6 +899,66 @@ describe("OpenAI Responses route", () => {
     }),
   )
 
+  it.effect("preserves output message phases in follow-up requests", () =>
+    Effect.gen(function* () {
+      const response = yield* LLMClient.generate(request).pipe(
+        Effect.provide(
+          fixedResponse(
+            sseEvents(
+              {
+                type: "response.output_item.added",
+                item: { type: "message", id: "msg_commentary", phase: "commentary" },
+              },
+              { type: "response.output_text.delta", item_id: "msg_commentary", delta: "Checking." },
+              { type: "response.output_text.done", item_id: "msg_commentary" },
+              {
+                type: "response.output_item.added",
+                item: { type: "message", id: "msg_final", phase: "final_answer" },
+              },
+              { type: "response.output_text.delta", item_id: "msg_final", delta: "Done." },
+              { type: "response.output_text.done", item_id: "msg_final" },
+              { type: "response.completed", response: { id: "resp_1" } },
+            ),
+          ),
+        ),
+      )
+
+      expect(response.message.content).toEqual([
+        {
+          type: "text",
+          text: "Checking.",
+          providerMetadata: { openai: { itemId: "msg_commentary", phase: "commentary" } },
+        },
+        {
+          type: "text",
+          text: "Done.",
+          providerMetadata: { openai: { itemId: "msg_final", phase: "final_answer" } },
+        },
+      ])
+
+      const followUp = yield* LLMClient.prepare<OpenAIResponses.OpenAIResponsesBody>(
+        LLM.request({
+          model,
+          messages: [Message.user("Start"), response.message, Message.user("Continue")],
+        }),
+      )
+      expect(followUp.body.input).toEqual([
+        { role: "user", content: [{ type: "input_text", text: "Start" }] },
+        {
+          role: "assistant",
+          phase: "commentary",
+          content: [{ type: "output_text", text: "Checking." }],
+        },
+        {
+          role: "assistant",
+          phase: "final_answer",
+          content: [{ type: "output_text", text: "Done." }],
+        },
+        { role: "user", content: [{ type: "input_text", text: "Continue" }] },
+      ])
+    }),
+  )
+
   it.effect("parses reasoning summary stream fixtures", () =>
     Effect.gen(function* () {
       const body = sseEvents(