feat(ai): round-trip Anthropic redacted thinking blocks

packages/ai/src/protocols/anthropic-messages.ts

@@ -75,6 +75,15 @@ const AnthropicThinkingBlock = Schema.Struct({
   cache_control: Schema.optional(AnthropicCacheControl),
 })
 
+// Safety-filtered thinking arrives as an opaque encrypted `data` payload with
+// no visible text. It must round-trip verbatim so multi-turn thinking + tool
+// use conversations keep their reasoning continuity.
+const AnthropicRedactedThinkingBlock = Schema.Struct({
+  type: Schema.tag("redacted_thinking"),
+  data: Schema.String,
+  cache_control: Schema.optional(AnthropicCacheControl),
+})
+
 const AnthropicToolUseBlock = Schema.Struct({
   type: Schema.tag("tool_use"),
   id: Schema.String,
@@ -136,6 +145,7 @@ type AnthropicUserBlock = Schema.Schema.Type<typeof AnthropicUserBlock>
 const AnthropicAssistantBlock = Schema.Union([
   AnthropicTextBlock,
   AnthropicThinkingBlock,
+  AnthropicRedactedThinkingBlock,
   AnthropicToolUseBlock,
   AnthropicServerToolUseBlock,
   AnthropicServerToolResultBlock,
@@ -214,6 +224,9 @@ const AnthropicStreamBlock = Schema.Struct({
   text: Schema.optional(Schema.String),
   thinking: Schema.optional(Schema.String),
   signature: Schema.optional(Schema.String),
+  // redacted_thinking blocks arrive whole in content_block_start with the
+  // encrypted payload in `data`; there is no streaming delta sequence.
+  data: Schema.optional(Schema.String),
   input: Schema.optional(Schema.Unknown),
   // *_tool_result blocks arrive whole as content_block_start (no streaming
   // delta) with the structured payload in `content` and the originating
@@ -287,6 +300,12 @@ const signatureFromMetadata = (metadata: ProviderMetadata | undefined): string |
   return typeof anthropic.signature === "string" ? anthropic.signature : undefined
 }
 
+const redactedDataFromMetadata = (metadata: ProviderMetadata | undefined): string | undefined => {
+  const anthropic = metadata?.anthropic
+  if (!ProviderShared.isRecord(anthropic)) return undefined
+  return typeof anthropic.redactedData === "string" ? anthropic.redactedData : undefined
+}
+
 const lowerTool = (breakpoints: Cache.Breakpoints, tool: ToolDefinition, inputSchema: JsonSchema): AnthropicTool => ({
   name: tool.name,
   description: tool.description,
@@ -472,11 +491,16 @@ const lowerMessages = Effect.fn("AnthropicMessages.lowerMessages")(function* (
           continue
         }
         if (part.type === "reasoning") {
-          content.push({
-            type: "thinking",
-            thinking: part.text,
-            signature: part.encrypted ?? signatureFromMetadata(part.providerMetadata),
-          })
+          // Mirrors Vercel's @ai-sdk/anthropic: a signature marks visible
+          // thinking; only signature-less parts carrying redactedData
+          // round-trip as opaque redacted_thinking blocks.
+          const signature = part.encrypted ?? signatureFromMetadata(part.providerMetadata)
+          const redactedData = redactedDataFromMetadata(part.providerMetadata)
+          if (signature === undefined && redactedData !== undefined) {
+            content.push({ type: "redacted_thinking", data: redactedData })
+            continue
+          }
+          content.push({ type: "thinking", thinking: part.text, signature })
           continue
         }
         if (part.type === "tool-call") {
@@ -747,6 +771,25 @@ const onContentBlockStart = (state: ParserState, event: AnthropicEvent): StepRes
     ]
   }
 
+  // Redacted thinking surfaces as an empty reasoning part carrying the opaque
+  // payload as `redactedData` metadata (same model as Vercel's
+  // @ai-sdk/anthropic). The existing content_block_stop closes the part.
+  if (block.type === "redacted_thinking" && block.data) {
+    const events: LLMEvent[] = []
+    return [
+      {
+        ...state,
+        lifecycle: Lifecycle.reasoningStart(
+          state.lifecycle,
+          events,
+          `reasoning-${event.index ?? 0}`,
+          anthropicMetadata({ redactedData: block.data }),
+        ),
+      },
+      events,
+    ]
+  }
+
   const result = serverToolResultEvent(block)
   if (!result) return [state, NO_EVENTS]
   const events: LLMEvent[] = []

packages/ai/test/provider/anthropic-messages.test.ts

@@ -409,6 +409,34 @@ describe("Anthropic Messages route", () => {
     }),
   )
 
+  it.effect("round-trips redacted thinking as redacted_thinking blocks", () =>
+    Effect.gen(function* () {
+      const prepared = yield* LLMClient.prepare(
+        LLM.request({
+          model,
+          messages: [
+            Message.assistant([
+              { type: "reasoning", text: "", providerMetadata: { anthropic: { redactedData: "opaque_1" } } },
+              { type: "reasoning", text: "visible", providerMetadata: { anthropic: { signature: "sig_1" } } },
+            ]),
+          ],
+        }),
+      )
+
+      expect(prepared.body).toMatchObject({
+        messages: [
+          {
+            role: "assistant",
+            content: [
+              { type: "redacted_thinking", data: "opaque_1" },
+              { type: "thinking", thinking: "visible", signature: "sig_1" },
+            ],
+          },
+        ],
+      })
+    }),
+  )
+
   it.effect("parses text, reasoning, and usage stream fixtures", () =>
     Effect.gen(function* () {
       const body = sseEvents(
@@ -454,6 +482,105 @@ describe("Anthropic Messages route", () => {
     }),
   )
 
+  it.effect("parses redacted thinking into empty reasoning with redactedData metadata", () =>
+    Effect.gen(function* () {
+      const body = sseEvents(
+        { type: "message_start", message: { usage: { input_tokens: 5 } } },
+        { type: "content_block_start", index: 0, content_block: { type: "redacted_thinking", data: "opaque_1" } },
+        { type: "content_block_stop", index: 0 },
+        { type: "content_block_start", index: 1, content_block: { type: "text", text: "" } },
+        { type: "content_block_delta", index: 1, delta: { type: "text_delta", text: "Hello" } },
+        { type: "content_block_stop", index: 1 },
+        { type: "message_delta", delta: { stop_reason: "end_turn" }, usage: { output_tokens: 2 } },
+        { type: "message_stop" },
+      )
+      const response = yield* LLMClient.generate(request).pipe(Effect.provide(fixedResponse(body)))
+
+      expect(response.events.find((event) => event.type === "reasoning-start")).toMatchObject({
+        providerMetadata: { anthropic: { redactedData: "opaque_1" } },
+      })
+      expect(response.message.content).toEqual([
+        { type: "reasoning", text: "", providerMetadata: { anthropic: { redactedData: "opaque_1" } } },
+        { type: "text", text: "Hello" },
+      ])
+    }),
+  )
+
+  it.effect("round-trips streamed redacted thinking with tool use into a continuation request", () =>
+    Effect.gen(function* () {
+      // Anthropic types `redacted_thinking.data` as an opaque string. Its
+      // contents are provider-owned and must be replayed without inspection.
+      const redactedData = "cmVkYWN0ZWQtdGhpbmtpbmc="
+      const response = yield* LLMClient.generate(
+        LLM.updateRequest(request, {
+          tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
+        }),
+      ).pipe(
+        Effect.provide(
+          fixedResponse(
+            sseEvents(
+              { type: "message_start", message: { usage: { input_tokens: 5 } } },
+              {
+                type: "content_block_start",
+                index: 0,
+                content_block: { type: "redacted_thinking", data: redactedData },
+              },
+              { type: "content_block_stop", index: 0 },
+              {
+                type: "content_block_start",
+                index: 1,
+                content_block: { type: "tool_use", id: "call_1", name: "lookup" },
+              },
+              {
+                type: "content_block_delta",
+                index: 1,
+                delta: { type: "input_json_delta", partial_json: '{"query":"weather"}' },
+              },
+              { type: "content_block_stop", index: 1 },
+              { type: "message_delta", delta: { stop_reason: "tool_use" }, usage: { output_tokens: 1 } },
+              { type: "message_stop" },
+            ),
+          ),
+        ),
+      )
+      const prepared = yield* LLMClient.prepare<AnthropicMessages.AnthropicMessagesBody>(
+        LLM.request({
+          model,
+          messages: [
+            Message.user("Say hello."),
+            response.message,
+            Message.tool({ id: "call_1", name: "lookup", result: "sunny", resultType: "text" }),
+          ],
+          tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
+          cache: "none",
+        }),
+      )
+
+      expect(prepared.body.messages).toEqual([
+        { role: "user", content: [{ type: "text", text: "Say hello." }] },
+        {
+          role: "assistant",
+          content: [
+            { type: "redacted_thinking", data: redactedData },
+            { type: "tool_use", id: "call_1", name: "lookup", input: { query: "weather" } },
+          ],
+        },
+        {
+          role: "user",
+          content: [
+            {
+              type: "tool_result",
+              tool_use_id: "call_1",
+              content: "sunny",
+              is_error: undefined,
+              cache_control: undefined,
+            },
+          ],
+        },
+      ])
+    }),
+  )
+
   it.effect("maps context-window truncation to length", () =>
     Effect.gen(function* () {
       const response = yield* LLMClient.generate(request).pipe(