fix(ai): allow future Anthropic option values (#49835)

packages/ai/AGENTS.md

@@ -12,7 +12,7 @@
 
 Per-type constructors live on the type, not as top-level re-exports. Use `Message.system(...)`, `Message.user(...)`, `Message.assistant(...)`, `Message.tool(...)`, `LanguageModel.make(...)`, `ToolDefinition.make(...)`, `ToolCallPart.make(...)`, `ToolResultPart.make(...)`, `ToolChoice.make(...)`, `ToolChoice.named(...)`, `SystemPart.make(...)`, and `GenerationOptions.make(...)` directly. The top-level `LLM` namespace is reserved for request-shaped call APIs: `LLM.request`, `LLM.generate`, `LLM.stream`, and `LLM.generateObject`. Use `LLMRequest.update(...)` when deriving canonical request data; do not add a duplicate `LLM.updateRequest(...)` path. Two ways to construct the same thing is one too many.
 
-- Keep provider-defined string enums forward-compatible. Expose known values for autocomplete while accepting future values with `Known | (string & {})`; use `Schema.String` at runtime unless rejecting unknown values is required for correctness.
+- Prefer forward compatibility for provider-defined options that OpenCode only passes through. For pass-through string enums, expose known values for autocomplete while accepting future values with `Known | (string & {})`, and accept any string at runtime. Closed literals are appropriate when OpenCode branches on a value, transforms its associated structure, or otherwise cannot correctly handle an unknown variant. New options whose shape or behavior requires implementation remain unsupported until they are handled; do not blindly forward unknown structures.
 - Order reasoning-effort values from lowest to highest: `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, `max`. Provider-specific subsets follow the same relative order in types, schemas, option lists, and tests.
 
 ## Tests

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

@@ -83,7 +83,7 @@ const AnthropicCacheControl = Schema.Struct({
   type: Schema.tag("ephemeral"),
   ttl: Schema.optional(Schema.Literals(["5m", "1h"])),
 })
-const AnthropicServiceTier = Schema.Literals(["auto", "standard_only"])
+const AnthropicServiceTier = knownString<"auto" | "standard_only">()
 
 const AnthropicTextBlock = Schema.Struct({
   type: Schema.tag("text"),
@@ -276,7 +276,7 @@ const AnthropicThinkingBlockBinding = Schema.Struct({
 })
 
 const AnthropicThinkingFields = {
-  display: Schema.optional(Schema.Literals(["summarized", "omitted"])),
+  display: Schema.optional(knownString<"summarized" | "omitted">()),
   block_binding: Schema.optional(AnthropicThinkingBlockBinding),
 }
 const AnthropicThinkingEnabled = Schema.Struct({

packages/ai/test/provider-options/anthropic.types.ts

@@ -4,6 +4,22 @@ import { Anthropic } from "../../src/providers.js"
 const model = Anthropic.provider.model("claude-sonnet-4-5")
 
 LLM.request({ model, prompt: "Hello", providerOptions: { thinking: { type: "adaptive" } } })
+LLM.request({
+  model,
+  prompt: "Hello",
+  providerOptions: {
+    serviceTier: "future-tier",
+    thinking: { type: "adaptive", display: "future-display" },
+  },
+})
+LLM.request({
+  model,
+  prompt: "Hello",
+  providerOptions: {
+    // @ts-expect-error Anthropic cache TTL values are protocol constraints.
+    cacheControl: { type: "ephemeral", ttl: "future-ttl" },
+  },
+})
 
 LLM.request({
   model,

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

@@ -215,13 +215,31 @@ describe("Anthropic Messages route", () => {
     }),
   )
 
+  it.effect("forwards unknown values for pass-through string enums", () =>
+    Effect.gen(function* () {
+      const prepared = yield* compileRequest(
+        LLMRequest.update(request, {
+          providerOptions: {
+            service_tier: "future-tier",
+            thinking: { type: "adaptive", display: "future-display" },
+          },
+        }),
+      )
+
+      expect(prepared.body).toMatchObject({
+        service_tier: "future-tier",
+        thinking: { type: "adaptive", display: "future-display" },
+      })
+    }),
+  )
+
   it.effect("ignores unknown provider options and rejects malformed known ones", () =>
     Effect.gen(function* () {
       const prepared = yield* compileRequest(LLMRequest.update(request, { providerOptions: { unknownOption: true } }))
       const malformed = [
-        { service_tier: "fast" },
+        { service_tier: 1 },
         { metadata: { user_id: 42 } },
-        { cache_control: { type: "ephemeral", ttl: "2h" } },
+        { cache_control: { type: "ephemeral", ttl: "future-ttl" } },
         { output_config: { format: { type: "text" } } },
         { thinking: { type: "automatic" } },
       ]