feat(ai): send min_p on xAI Responses (#58889)

Author: rekram1-node

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

@@ -31,9 +31,15 @@ const XAIResponsesHostedToolItem = Schema.Union([
   ),
 ])
 
+const Options = Schema.Struct({
+  minP: Schema.optional(Schema.Number),
+})
+export type OptionsInput = typeof Options.Type
+
 const Body = Schema.Struct({
   ...OpenResponses.OpenResponsesBody.fields,
   top_k: Schema.optional(Schema.Number),
+  min_p: Schema.optional(Schema.Number),
 })
 
 const adapter = {
@@ -58,13 +64,15 @@ const fromRequest = Effect.fn("XAIResponses.fromRequest")(function* (request: LL
       message:
         "xAI requires explicit compaction through LLMClient.compact; automatic context management is not supported",
     })
+  const options = yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(Options))(request.providerOptions ?? {})
   const body = yield* OpenResponses.fromRequestWithAdapter(request, adapter)
   // xAI Responses does not support penalties (they are ignored), but does support top_k.
   return {
     ...body,
     presence_penalty: undefined,
     frequency_penalty: undefined,
     top_k: request.generation?.topK,
+    min_p: options.minP,
   }
 })
 

packages/ai/src/providers/xai.ts

@@ -14,7 +14,8 @@ import type { ProviderPackage } from "../provider-package.js"
 export const id = ProviderID.make("xai")
 const baseURL = "https://api.x.ai/v1"
 
-export type XAIProviderOptionsInput = OpenAIOptionsInput & { readonly contextManagement?: never }
+export type XAIProviderOptionsInput = OpenAIOptionsInput &
+  XAIResponses.OptionsInput & { readonly contextManagement?: never }
 
 export type LanguageModelOptions = Omit<RouteDefaultsInput, "providerOptions"> &
   ProviderAuthOption<"optional"> & {

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

@@ -89,6 +89,14 @@ describe("xAI Responses route", () => {
     }),
   )
 
+  it.effect("sends min_p from provider options", () =>
+    Effect.gen(function* () {
+      const prepared = yield* compileRequest(LLM.request({ model, prompt: "Hello", providerOptions: { minP: 0.1 } }))
+
+      expect(prepared.body.min_p).toBe(0.1)
+    }),
+  )
+
   it.effect("parses xAI reasoning summaries", () =>
     Effect.gen(function* () {
       const response = yield* LLMClient.generate(LLM.request({ model, prompt: "Think" })).pipe(