fix(llm): split OpenAI reasoning summary blocks (#29000)

packages/opencode/test/provider/transform.test.ts

@@ -271,6 +271,7 @@ describe("ProviderTransform.options - gpt-5 textVerbosity", () => {
     const model = createGpt5Model("gpt-5.2")
     const result = ProviderTransform.options({ model, sessionID, providerOptions: {} })
     expect(result.textVerbosity).toBe("low")
+    expect(result.include).toEqual(["reasoning.encrypted_content"])
   })
 
   test("gpt-5.1 should have textVerbosity set to low", () => {

packages/opencode/test/session/llm-native-recorded.test.ts

@@ -336,10 +336,25 @@ const weatherTool = tool({
 })
 
 const toolRoundtrip = (
+  events: ReadonlyArray<LLMEvent>,
   call: { readonly id: string; readonly name: string; readonly input: unknown },
   result: JSONValue,
 ): ModelMessage[] => [
-  { role: "assistant", content: [{ type: "tool-call", toolCallId: call.id, toolName: call.name, input: call.input }] },
+  {
+    role: "assistant",
+    content: [
+      ...events.filter(LLMEvent.is.reasoningEnd).map((part) => ({
+        type: "reasoning" as const,
+        text: events
+          .filter(LLMEvent.is.reasoningDelta)
+          .filter((event) => event.id === part.id)
+          .map((event) => event.text)
+          .join(""),
+        providerMetadata: part.providerMetadata,
+      })),
+      { type: "tool-call", toolCallId: call.id, toolName: call.name, input: call.input },
+    ],
+  },
   {
     role: "tool",
     content: [
@@ -395,7 +410,7 @@ const driveToolLoop = (scenario: RecordedScenario) =>
 
     const turn2 = yield* collect({
       ...base,
-      messages: [userMessage, ...toolRoundtrip(toolCall!, WEATHER_RESULT)],
+      messages: [userMessage, ...toolRoundtrip(turn1, toolCall!, WEATHER_RESULT)],
     })
 
     expect(LLMResponse.text({ events: turn2 })).toMatch(/Paris is sunny/i)

packages/opencode/test/session/llm-native.test.ts

@@ -591,7 +591,7 @@ describe("session.llm-native.request", () => {
         ]),
         storedSession.user("Summarize it."),
       ],
-      providerOptions: { openai: { store: false, includeEncryptedReasoning: true } },
+      providerOptions: { openai: { store: false, include: ["reasoning.encrypted_content"] } },
       expectedBody: {
         input: [
           openAIResponses.user("What changed?"),
@@ -608,6 +608,45 @@ describe("session.llm-native.request", () => {
     }),
   )
 
+  it.effect("preserves empty encrypted OpenAI reasoning items before tool output", () =>
+    expectOpenAIResponsesRequest({
+      history: [
+        storedSession.assistant([
+          storedSession.openaiReasoning("", {
+            storedAs: "providerMetadata",
+            itemId: "rs_1",
+            encryptedContent: "encrypted-state",
+          }),
+        ]),
+      ],
+      providerOptions: { openai: { store: false, include: ["reasoning.encrypted_content"] } },
+      expectedBody: {
+        input: [{ type: "reasoning", id: "rs_1", summary: [], encrypted_content: "encrypted-state" }],
+        include: ["reasoning.encrypted_content"],
+        store: false,
+      },
+    }),
+  )
+
+  it.effect("references stored OpenAI reasoning items by id", () =>
+    expectOpenAIResponsesRequest({
+      history: [
+        storedSession.assistant([
+          storedSession.openaiReasoning("Checked the previous diff.", {
+            storedAs: "providerMetadata",
+            itemId: "rs_1",
+            encryptedContent: null,
+          }),
+        ]),
+      ],
+      providerOptions: { openai: { store: true } },
+      expectedBody: {
+        input: [{ type: "item_reference", id: "rs_1" }],
+        store: true,
+      },
+    }),
+  )
+
   it.effect("uses provider fetch override for native OpenAI OAuth requests", () =>
     Effect.gen(function* () {
       const captures: Array<{ url: string; body: unknown }> = []

packages/opencode/test/session/llm.test.ts

@@ -1166,6 +1166,7 @@ describe("session.llm.stream", () => {
         expect(capture.body.model).toBe(model.id)
         expect(capture.body.stream).toBe(true)
         expect((capture.body.reasoning as { effort?: string } | undefined)?.effort).toBe("high")
+        expect(capture.body.include).toEqual(["reasoning.encrypted_content"])
         expect(JSON.stringify(capture.body.input)).toContain("You are a helpful assistant.")
         expect(capture.body.input).toContainEqual({ role: "user", content: [{ type: "input_text", text: "Hello" }] })
       }),