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

packages/llm/test/tool-runtime.test.ts

@@ -4,6 +4,7 @@ import { GenerationOptions, LLM, LLMEvent, LLMRequest, LLMResponse, ToolChoice }
 import { Auth, LLMClient } from "../src/route"
 import * as AnthropicMessages from "../src/protocols/anthropic-messages"
 import * as OpenAIChat from "../src/protocols/openai-chat"
+import * as OpenAIResponses from "../src/protocols/openai-responses"
 import { tool, ToolFailure, type ToolExecuteContext } from "../src/tool"
 import { ToolRuntime } from "../src/tool-runtime"
 import { it } from "./lib/effect"
@@ -309,6 +310,71 @@ describe("LLMClient tools", () => {
     }),
   )
 
+  it.effect("replays encrypted OpenAI reasoning items with tool outputs", () =>
+    Effect.gen(function* () {
+      const bodies: unknown[] = []
+      const layer = dynamicResponse((input) =>
+        Effect.sync(() => {
+          bodies.push(decodeJson(input.text))
+          return input.respond(
+            bodies.length === 1
+              ? sseEvents(
+                  { type: "response.output_item.added", item: { type: "reasoning", id: "rs_1", encrypted_content: null } },
+                  { type: "response.reasoning_summary_part.added", item_id: "rs_1", summary_index: 0 },
+                  { type: "response.reasoning_summary_part.done", item_id: "rs_1", summary_index: 0 },
+                  {
+                    type: "response.output_item.done",
+                    item: { type: "reasoning", id: "rs_1", encrypted_content: "encrypted-state" },
+                  },
+                  {
+                    type: "response.output_item.added",
+                    item: { type: "function_call", id: "item_1", call_id: "call_1", name: "get_weather", arguments: "" },
+                  },
+                  { type: "response.function_call_arguments.delta", item_id: "item_1", delta: '{"city":"Paris"}' },
+                  {
+                    type: "response.output_item.done",
+                    item: {
+                      type: "function_call",
+                      id: "item_1",
+                      call_id: "call_1",
+                      name: "get_weather",
+                      arguments: '{"city":"Paris"}',
+                    },
+                  },
+                  { type: "response.completed", response: {} },
+                )
+              : sseEvents(
+                  { type: "response.output_text.delta", item_id: "msg_1", delta: "Done." },
+                  { type: "response.completed", response: {} },
+                ),
+            { headers: { "content-type": "text/event-stream" } },
+          )
+        }),
+      )
+
+      yield* TestToolRuntime.runTools({
+        request: LLM.request({
+          model: OpenAIResponses.route
+            .with({ endpoint: { baseURL: "https://api.openai.test/v1/" }, auth: Auth.bearer("test") })
+            .model({ id: "gpt-5.5" }),
+          prompt: "Use the tool.",
+          providerOptions: { openai: { store: false, include: ["reasoning.encrypted_content"] } },
+        }),
+        tools: { get_weather },
+      }).pipe(Stream.runCollect, Effect.provide(layer))
+
+      expect(bodies[1]).toMatchObject({
+        include: ["reasoning.encrypted_content"],
+        input: [
+          { role: "user" },
+          { type: "reasoning", id: "rs_1", summary: [], encrypted_content: "encrypted-state" },
+          { type: "function_call", call_id: "call_1", name: "get_weather" },
+          { type: "function_call_output", call_id: "call_1" },
+        ],
+      })
+    }),
+  )
+
   it.effect("emits tool-error for unknown tools so the model can self-correct", () =>
     Effect.gen(function* () {
       const layer = scriptedResponses([