refactor(session): inject native LLM client

packages/llm/src/tool-runtime.ts

@@ -200,17 +200,17 @@ const dispatch = (tools: Tools, call: ToolCallPart): Effect.Effect<ToolResultVal
   if (!tool.execute)
     return Effect.succeed({ type: "error" as const, value: `Tool has no execute handler: ${call.name}` })
 
-  return decodeAndExecute(tool, call.input).pipe(
+  return decodeAndExecute(tool, call).pipe(
     Effect.catchTag("LLM.ToolFailure", (failure) =>
       Effect.succeed({ type: "error" as const, value: failure.message } satisfies ToolResultValue),
     ),
   )
 }
 
-const decodeAndExecute = (tool: AnyTool, input: unknown): Effect.Effect<ToolResultValue, ToolFailure> =>
-  tool._decode(input).pipe(
+const decodeAndExecute = (tool: AnyTool, call: ToolCallPart): Effect.Effect<ToolResultValue, ToolFailure> =>
+  tool._decode(call.input).pipe(
     Effect.mapError((error) => new ToolFailure({ message: `Invalid tool input: ${error.message}` })),
-    Effect.flatMap((decoded) => tool.execute!(decoded)),
+    Effect.flatMap((decoded) => tool.execute!(decoded, { id: call.id, name: call.name })),
     Effect.flatMap((value) =>
       tool._encode(value).pipe(
         Effect.mapError(

packages/llm/src/tool.ts

@@ -11,6 +11,7 @@ export type ToolSchema<T> = Schema.Codec<T, any, never, never>
 
 export type ToolExecute<Parameters extends ToolSchema<any>, Success extends ToolSchema<any>> = (
   params: Schema.Schema.Type<Parameters>,
+  context?: { readonly id: string; readonly name: string },
 ) => Effect.Effect<Schema.Schema.Type<Success>, ToolFailure>
 
 /**
@@ -61,7 +62,10 @@ type TypedToolConfig = {
 type DynamicToolConfig = {
   readonly description: string
   readonly jsonSchema: JsonSchema.JsonSchema
-  readonly execute?: (params: unknown) => Effect.Effect<unknown, ToolFailure>
+  readonly execute?: (
+    params: unknown,
+    context?: { readonly id: string; readonly name: string },
+  ) => Effect.Effect<unknown, ToolFailure>
 }
 
 /**
@@ -110,7 +114,10 @@ export function make<Parameters extends ToolSchema<any>, Success extends ToolSch
 export function make(config: {
   readonly description: string
   readonly jsonSchema: JsonSchema.JsonSchema
-  readonly execute: (params: unknown) => Effect.Effect<unknown, ToolFailure>
+  readonly execute: (
+    params: unknown,
+    context?: { readonly id: string; readonly name: string },
+  ) => Effect.Effect<unknown, ToolFailure>
 }): AnyExecutableTool
 export function make(config: {
   readonly description: string

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

@@ -0,0 +1,190 @@
+import type { JsonSchema, LLMRequest, ProviderMetadata } from "@opencode-ai/llm"
+import { LLM, Message, SystemPart, ToolCallPart, ToolDefinition, ToolResultPart } from "@opencode-ai/llm"
+import "@opencode-ai/llm/providers"
+import type { ModelMessage } from "ai"
+import type { Provider } from "@/provider/provider"
+
+type ToolInput = {
+  readonly description?: string
+  readonly inputSchema?: unknown
+}
+
+export type RequestInput = {
+  readonly model: Provider.Model
+  readonly apiKey?: string
+  readonly baseURL?: string
+  readonly system?: readonly string[]
+  readonly messages: readonly ModelMessage[]
+  readonly tools?: Record<string, ToolInput>
+  readonly toolChoice?: "auto" | "required" | "none"
+  readonly temperature?: number
+  readonly topP?: number
+  readonly topK?: number
+  readonly maxOutputTokens?: number
+  readonly providerOptions?: LLMRequest["providerOptions"]
+  readonly headers?: Record<string, string>
+}
+
+const DEFAULT_BASE_URL: Record<string, string> = {
+  "@ai-sdk/openai": "https://api.openai.com/v1",
+  "@ai-sdk/anthropic": "https://api.anthropic.com/v1",
+  "@ai-sdk/google": "https://generativelanguage.googleapis.com/v1beta",
+  "@ai-sdk/amazon-bedrock": "https://bedrock-runtime.us-east-1.amazonaws.com",
+  "@openrouter/ai-sdk-provider": "https://openrouter.ai/api/v1",
+}
+
+const ROUTE: Record<string, string> = {
+  "@ai-sdk/openai": "openai-responses",
+  "@ai-sdk/azure": "azure-openai-responses",
+  "@ai-sdk/anthropic": "anthropic-messages",
+  "@ai-sdk/google": "gemini",
+  "@ai-sdk/amazon-bedrock": "bedrock-converse",
+  "@ai-sdk/openai-compatible": "openai-compatible-chat",
+  "@openrouter/ai-sdk-provider": "openrouter",
+}
+
+const isRecord = (value: unknown): value is Record<string, unknown> =>
+  typeof value === "object" && value !== null && !Array.isArray(value)
+
+const providerMetadata = (value: unknown): ProviderMetadata | undefined => {
+  if (!isRecord(value)) return undefined
+  const result = Object.fromEntries(
+    Object.entries(value).filter((entry): entry is [string, Record<string, unknown>] => isRecord(entry[1])),
+  )
+  return Object.keys(result).length === 0 ? undefined : result
+}
+
+const textPart = (part: Record<string, unknown>) => ({
+  type: "text" as const,
+  text: typeof part.text === "string" ? part.text : "",
+  providerMetadata: providerMetadata(part.providerOptions),
+})
+
+const mediaPart = (part: Record<string, unknown>) => {
+  if (typeof part.data !== "string" && !(part.data instanceof Uint8Array))
+    throw new Error("Native LLM request adapter only supports file parts with string or Uint8Array data")
+  return {
+    type: "media" as const,
+    mediaType: typeof part.mediaType === "string" ? part.mediaType : "application/octet-stream",
+    data: part.data,
+    filename: typeof part.filename === "string" ? part.filename : undefined,
+  }
+}
+
+const toolResult = (part: Record<string, unknown>) => {
+  const output = isRecord(part.output) ? part.output : { type: "json", value: part.output }
+  const type = output.type === "text" ? "text" : output.type === "error-text" ? "error" : "json"
+  return ToolResultPart.make({
+    id: typeof part.toolCallId === "string" ? part.toolCallId : "",
+    name: typeof part.toolName === "string" ? part.toolName : "",
+    result: "value" in output ? output.value : output,
+    resultType: type,
+    providerExecuted: typeof part.providerExecuted === "boolean" ? part.providerExecuted : undefined,
+    providerMetadata: providerMetadata(part.providerOptions),
+  })
+}
+
+const contentPart = (part: unknown) => {
+  if (!isRecord(part)) throw new Error("Native LLM request adapter only supports object content parts")
+  if (part.type === "text") return textPart(part)
+  if (part.type === "file") return mediaPart(part)
+  if (part.type === "reasoning")
+    return {
+      type: "reasoning" as const,
+      text: typeof part.text === "string" ? part.text : "",
+      providerMetadata: providerMetadata(part.providerOptions),
+    }
+  if (part.type === "tool-call")
+    return ToolCallPart.make({
+      id: typeof part.toolCallId === "string" ? part.toolCallId : "",
+      name: typeof part.toolName === "string" ? part.toolName : "",
+      input: part.input,
+      providerExecuted: typeof part.providerExecuted === "boolean" ? part.providerExecuted : undefined,
+      providerMetadata: providerMetadata(part.providerOptions),
+    })
+  if (part.type === "tool-result") return toolResult(part)
+  throw new Error(`Native LLM request adapter does not support ${String(part.type)} content parts`)
+}
+
+const content = (value: ModelMessage["content"]) =>
+  typeof value === "string" ? [{ type: "text" as const, text: value }] : value.map(contentPart)
+
+const messages = (input: readonly ModelMessage[]) => {
+  const system = input.flatMap((message) => (message.role === "system" ? [SystemPart.make(message.content)] : []))
+  const messages = input.flatMap((message) => {
+    if (message.role === "system") return []
+    return [
+      Message.make({
+        role: message.role,
+        content: content(message.content),
+        native: isRecord(message.providerOptions) ? { providerOptions: message.providerOptions } : undefined,
+      }),
+    ]
+  })
+  return { system, messages }
+}
+
+const schema = (value: unknown): JsonSchema => {
+  if (!isRecord(value)) return { type: "object", properties: {} }
+  if (isRecord(value.jsonSchema)) return value.jsonSchema
+  return value
+}
+
+const tools = (input: Record<string, ToolInput> | undefined): ToolDefinition[] =>
+  Object.entries(input ?? {}).map(([name, item]) =>
+    ToolDefinition.make({
+      name,
+      description: item.description ?? "",
+      inputSchema: schema(item.inputSchema),
+    }),
+  )
+
+const generation = (input: RequestInput) => {
+  const result = {
+    temperature: input.temperature,
+    topP: input.topP,
+    topK: input.topK,
+    maxTokens: input.maxOutputTokens,
+  }
+  return Object.values(result).some((value) => value !== undefined) ? result : undefined
+}
+
+const baseURL = (model: Provider.Model) => {
+  if (model.api.url) return model.api.url
+  const fallback = DEFAULT_BASE_URL[model.api.npm]
+  if (fallback) return fallback
+  throw new Error(`Native LLM request adapter requires a base URL for ${model.providerID}/${model.id}`)
+}
+
+export const model = (input: Provider.Model | RequestInput, headers?: Record<string, string>) => {
+  const model = "model" in input ? input.model : input
+  const route = ROUTE[model.api.npm]
+  if (!route) throw new Error(`Native LLM request adapter does not support provider package ${model.api.npm}`)
+  return LLM.model({
+    id: model.api.id,
+    provider: model.providerID,
+    route,
+    baseURL: "model" in input && input.baseURL ? input.baseURL : baseURL(model),
+    apiKey: "model" in input ? input.apiKey : undefined,
+    headers: Object.keys({ ...model.headers, ...headers }).length === 0 ? undefined : { ...model.headers, ...headers },
+    limits: {
+      context: model.limit.context,
+      output: model.limit.output,
+    },
+  })
+}
+
+export const request = (input: RequestInput) => {
+  const converted = messages(input.messages)
+  return LLM.request({
+    model: model(input, input.headers),
+    system: [...(input.system ?? []).map(SystemPart.make), ...converted.system],
+    messages: converted.messages,
+    tools: tools(input.tools),
+    toolChoice: input.toolChoice,
+    generation: generation(input),
+    providerOptions: input.providerOptions,
+  })
+}
+
+export * as LLMNative from "./llm-native"

packages/opencode/src/session/llm.ts

@@ -2,8 +2,10 @@ import { Provider } from "@/provider/provider"
 import * as Log from "@opencode-ai/core/util/log"
 import { Context, Effect, Layer, Record } from "effect"
 import * as Stream from "effect/Stream"
-import { streamText, wrapLanguageModel, type ModelMessage, type Tool, tool, jsonSchema } from "ai"
-import type { LLMEvent } from "@opencode-ai/llm"
+import { streamText, wrapLanguageModel, type ModelMessage, type Tool, tool as aiTool, jsonSchema, asSchema } from "ai"
+import { tool as nativeTool, ToolFailure, type JsonSchema, type LLMEvent } from "@opencode-ai/llm"
+import { LLMClient, RequestExecutor } from "@opencode-ai/llm/route"
+import type { LLMClientService } from "@opencode-ai/llm/route"
 import { mergeDeep } from "remeda"
 import { GitLabWorkflowLanguageModel } from "gitlab-ai-provider"
 import { ProviderTransform } from "@/provider/transform"
@@ -17,15 +19,16 @@ import { Flag } from "@opencode-ai/core/flag/flag"
 import { Permission } from "@/permission"
 import { PermissionID } from "@/permission/schema"
 import { Bus } from "@/bus"
+import { errorMessage } from "@/util/error"
 import { Wildcard } from "@/util/wildcard"
 import { SessionID } from "@/session/schema"
 import { Auth } from "@/auth"
-import { Installation } from "@/installation"
 import { InstallationVersion } from "@opencode-ai/core/installation/version"
 import { EffectBridge } from "@/effect/bridge"
 import * as Option from "effect/Option"
 import * as OtelTracer from "@effect/opentelemetry/Tracer"
 import { LLMAISDK } from "./llm-ai-sdk"
+import { LLMNative } from "./llm-native"
 
 const log = Log.create({ service: "llm" })
 export const OUTPUT_TOKEN_MAX = ProviderTransform.OUTPUT_TOKEN_MAX
@@ -34,6 +37,8 @@ export const OUTPUT_TOKEN_MAX = ProviderTransform.OUTPUT_TOKEN_MAX
 const mergeOptions = (target: Record<string, any>, source: Record<string, any> | undefined): Record<string, any> =>
   mergeDeep(target, source ?? {}) as Record<string, any>
 
+const runtime = () => (process.env.OPENCODE_LLM_RUNTIME === "native" ? "native" : "ai-sdk")
+
 export type StreamInput = {
   user: MessageV2.User
   sessionID: string
@@ -62,7 +67,7 @@ export class Service extends Context.Service<Service, Interface>()("@opencode/LL
 const live: Layer.Layer<
   Service,
   never,
-  Auth.Service | Config.Service | Provider.Service | Plugin.Service | Permission.Service
+  Auth.Service | Config.Service | Provider.Service | Plugin.Service | Permission.Service | LLMClientService
 > = Layer.effect(
   Service,
   Effect.gen(function* () {
@@ -71,6 +76,7 @@ const live: Layer.Layer<
     const provider = yield* Provider.Service
     const plugin = yield* Plugin.Service
     const perm = yield* Permission.Service
+    const llmClient = yield* LLMClient.Service
 
     const run = Effect.fn("LLM.run")(function* (input: StreamRequest) {
       const l = log
@@ -213,7 +219,7 @@ const live: Layer.Layer<
         Object.keys(tools).length === 0 &&
         hasToolCalls(input.messages)
       ) {
-        tools["_noop"] = tool({
+        tools["_noop"] = aiTool({
           description: "Do not call this tool. It exists only for API compatibility and must never be invoked.",
           inputSchema: jsonSchema({
             type: "object",
@@ -333,86 +339,120 @@ const live: Layer.Layer<
         ? (yield* InstanceState.context).project.id
         : undefined
 
-      return streamText({
-        onError(error) {
-          l.error("stream error", {
-            error,
-          })
-        },
-        async experimental_repairToolCall(failed) {
-          const lower = failed.toolCall.toolName.toLowerCase()
-          if (lower !== failed.toolCall.toolName && sortedTools[lower]) {
-            l.info("repairing tool call", {
-              tool: failed.toolCall.toolName,
-              repaired: lower,
+      const requestHeaders = {
+        ...(input.model.providerID.startsWith("opencode")
+          ? {
+              ...(opencodeProjectID ? { "x-opencode-project": opencodeProjectID } : {}),
+              "x-opencode-session": input.sessionID,
+              "x-opencode-request": input.user.id,
+              "x-opencode-client": Flag.OPENCODE_CLIENT,
+              "User-Agent": `opencode/${InstallationVersion}`,
+            }
+          : {
+              "x-session-affinity": input.sessionID,
+              ...(input.parentSessionID ? { "x-parent-session-id": input.parentSessionID } : {}),
+              "User-Agent": `opencode/${InstallationVersion}`,
+            }),
+        ...input.model.headers,
+        ...headers,
+      }
+
+      if (runtime() === "native") {
+        if (input.model.providerID !== "openai" || input.model.api.npm !== "@ai-sdk/openai") {
+          return yield* Effect.fail(new Error("Native LLM runtime currently only supports OpenAI models"))
+        }
+        const apiKey =
+          info?.type === "api" ? info.key : typeof item.options.apiKey === "string" ? item.options.apiKey : undefined
+        if (!apiKey) return yield* Effect.fail(new Error("Native LLM runtime requires API key auth for OpenAI"))
+        const baseURL = typeof item.options.baseURL === "string" ? item.options.baseURL : undefined
+        const request = LLMNative.request({
+          model: input.model,
+          apiKey,
+          baseURL,
+          system: isOpenaiOauth ? system : [],
+          messages: ProviderTransform.message(messages, input.model, options),
+          tools: sortedTools,
+          toolChoice: input.toolChoice,
+          temperature: params.temperature,
+          topP: params.topP,
+          topK: params.topK,
+          maxOutputTokens: params.maxOutputTokens,
+          providerOptions: ProviderTransform.providerOptions(input.model, params.options),
+          headers: requestHeaders,
+        })
+        return {
+          type: "native" as const,
+          stream: llmClient.stream({ request, tools: nativeTools(sortedTools, input) }),
+        }
+      }
+
+      return {
+        type: "ai-sdk" as const,
+        result: streamText({
+          onError(error) {
+            l.error("stream error", {
+              error,
             })
+          },
+          async experimental_repairToolCall(failed) {
+            const lower = failed.toolCall.toolName.toLowerCase()
+            if (lower !== failed.toolCall.toolName && sortedTools[lower]) {
+              l.info("repairing tool call", {
+                tool: failed.toolCall.toolName,
+                repaired: lower,
+              })
+              return {
+                ...failed.toolCall,
+                toolName: lower,
+              }
+            }
             return {
               ...failed.toolCall,
-              toolName: lower,
-            }
-          }
-          return {
-            ...failed.toolCall,
-            input: JSON.stringify({
-              tool: failed.toolCall.toolName,
-              error: failed.error.message,
-            }),
-            toolName: "invalid",
-          }
-        },
-        temperature: params.temperature,
-        topP: params.topP,
-        topK: params.topK,
-        providerOptions: ProviderTransform.providerOptions(input.model, params.options),
-        activeTools: Object.keys(sortedTools).filter((x) => x !== "invalid"),
-        tools: sortedTools,
-        toolChoice: input.toolChoice,
-        maxOutputTokens: params.maxOutputTokens,
-        abortSignal: input.abort,
-        headers: {
-          ...(input.model.providerID.startsWith("opencode")
-            ? {
-                "x-opencode-project": opencodeProjectID,
-                "x-opencode-session": input.sessionID,
-                "x-opencode-request": input.user.id,
-                "x-opencode-client": Flag.OPENCODE_CLIENT,
-                "User-Agent": `opencode/${InstallationVersion}`,
-              }
-            : {
-                "x-session-affinity": input.sessionID,
-                ...(input.parentSessionID ? { "x-parent-session-id": input.parentSessionID } : {}),
-                "User-Agent": `opencode/${InstallationVersion}`,
+              input: JSON.stringify({
+                tool: failed.toolCall.toolName,
+                error: failed.error.message,
               }),
-          ...input.model.headers,
-          ...headers,
-        },
-        maxRetries: input.retries ?? 0,
-        messages,
-        model: wrapLanguageModel({
-          model: language,
-          middleware: [
-            {
-              specificationVersion: "v3" as const,
-              async transformParams(args) {
-                if (args.type === "stream") {
-                  // @ts-expect-error
-                  args.params.prompt = ProviderTransform.message(args.params.prompt, input.model, options)
-                }
-                return args.params
-              },
-            },
-          ],
-        }),
-        experimental_telemetry: {
-          isEnabled: cfg.experimental?.openTelemetry,
-          functionId: "session.llm",
-          tracer: telemetryTracer,
-          metadata: {
-            userId: cfg.username ?? "unknown",
-            sessionId: input.sessionID,
+              toolName: "invalid",
+            }
           },
-        },
-      })
+          temperature: params.temperature,
+          topP: params.topP,
+          topK: params.topK,
+          providerOptions: ProviderTransform.providerOptions(input.model, params.options),
+          activeTools: Object.keys(sortedTools).filter((x) => x !== "invalid"),
+          tools: sortedTools,
+          toolChoice: input.toolChoice,
+          maxOutputTokens: params.maxOutputTokens,
+          abortSignal: input.abort,
+          headers: requestHeaders,
+          maxRetries: input.retries ?? 0,
+          messages,
+          model: wrapLanguageModel({
+            model: language,
+            middleware: [
+              {
+                specificationVersion: "v3" as const,
+                async transformParams(args) {
+                  if (args.type === "stream") {
+                    // @ts-expect-error
+                    args.params.prompt = ProviderTransform.message(args.params.prompt, input.model, options)
+                  }
+                  return args.params
+                },
+              },
+            ],
+          }),
+          experimental_telemetry: {
+            isEnabled: cfg.experimental?.openTelemetry,
+            functionId: "session.llm",
+            tracer: telemetryTracer,
+            metadata: {
+              userId: cfg.username ?? "unknown",
+              sessionId: input.sessionID,
+            },
+          },
+        }),
+      }
     })
 
     const stream: Interface["stream"] = (input) =>
@@ -426,8 +466,12 @@ const live: Layer.Layer<
 
             const result = yield* run({ ...input, abort: ctrl.signal })
 
+            if (result.type === "native") return result.stream
+
             const state = LLMAISDK.adapterState()
-            return Stream.fromAsyncIterable(result.fullStream, (e) => (e instanceof Error ? e : new Error(String(e)))).pipe(
+            return Stream.fromAsyncIterable(result.result.fullStream, (e) =>
+              e instanceof Error ? e : new Error(String(e)),
+            ).pipe(
               Stream.mapEffect((event) => LLMAISDK.toLLMEvents(state, event)),
               Stream.flatMap((events) => Stream.fromIterable(events)),
             )
@@ -447,6 +491,7 @@ export const defaultLayer = Layer.suspend(() =>
     Layer.provide(Config.defaultLayer),
     Layer.provide(Provider.defaultLayer),
     Layer.provide(Plugin.defaultLayer),
+    Layer.provide(LLMClient.layer.pipe(Layer.provide(RequestExecutor.defaultLayer))),
   ),
 )
 
@@ -458,6 +503,37 @@ function resolveTools(input: Pick<StreamInput, "tools" | "agent" | "permission"
   return Record.filter(input.tools, (_, k) => input.user.tools?.[k] !== false && !disabled.has(k))
 }
 
+function nativeSchema(value: unknown): JsonSchema {
+  if (!value || typeof value !== "object") return { type: "object", properties: {} }
+  if ("jsonSchema" in value && value.jsonSchema && typeof value.jsonSchema === "object")
+    return value.jsonSchema as JsonSchema
+  return asSchema(value as Parameters<typeof asSchema>[0]).jsonSchema as JsonSchema
+}
+
+function nativeTools(tools: Record<string, Tool>, input: StreamRequest) {
+  return Object.fromEntries(
+    Object.entries(tools).map(([name, item]) => [
+      name,
+      nativeTool({
+        description: item.description ?? "",
+        jsonSchema: nativeSchema(item.inputSchema),
+        execute: (args: unknown, ctx?: { readonly id: string; readonly name: string }) =>
+          Effect.tryPromise({
+            try: () => {
+              if (!item.execute) throw new Error(`Tool has no execute handler: ${name}`)
+              return item.execute(args, {
+                toolCallId: ctx?.id ?? name,
+                messages: input.messages,
+                abortSignal: input.abort,
+              })
+            },
+            catch: (error) => new ToolFailure({ message: errorMessage(error) }),
+          }),
+      }),
+    ]),
+  )
+}
+
 // Check if messages contain any tool-call content
 // Used to determine if a dummy tool should be added for LiteLLM proxy compatibility
 export function hasToolCalls(messages: ModelMessage[]): boolean {

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

@@ -0,0 +1,262 @@
+import { describe, expect, test } from "bun:test"
+import { LLMClient, RequestExecutor } from "@opencode-ai/llm/route"
+import { jsonSchema, tool, type ModelMessage } from "ai"
+import { Effect } from "effect"
+import { LLMNative } from "@/session/llm-native"
+import type { Provider } from "@/provider/provider"
+import { ModelID, ProviderID } from "@/provider/schema"
+
+const baseModel: Provider.Model = {
+  id: ModelID.make("gpt-5-mini"),
+  providerID: ProviderID.make("openai"),
+  api: {
+    id: "gpt-5-mini",
+    url: "https://api.openai.com/v1",
+    npm: "@ai-sdk/openai",
+  },
+  name: "GPT-5 Mini",
+  capabilities: {
+    temperature: true,
+    reasoning: true,
+    attachment: true,
+    toolcall: true,
+    input: {
+      text: true,
+      audio: false,
+      image: true,
+      video: false,
+      pdf: false,
+    },
+    output: {
+      text: true,
+      audio: false,
+      image: false,
+      video: false,
+      pdf: false,
+    },
+    interleaved: false,
+  },
+  cost: {
+    input: 0,
+    output: 0,
+    cache: {
+      read: 0,
+      write: 0,
+    },
+  },
+  limit: {
+    context: 128_000,
+    input: 128_000,
+    output: 32_000,
+  },
+  status: "active",
+  options: {},
+  headers: {
+    "x-model": "model-header",
+  },
+  release_date: "2026-01-01",
+}
+
+describe("session.llm-native.request", () => {
+  test("maps normalized stream inputs to a native LLM request", () => {
+    const messages: ModelMessage[] = [
+      {
+        role: "system",
+        content: "system from messages",
+      },
+      {
+        role: "user",
+        content: [
+          { type: "text", text: "hello", providerOptions: { openai: { cacheControl: { type: "ephemeral" } } } },
+          { type: "file", mediaType: "image/png", filename: "img.png", data: "data:image/png;base64,Zm9v" },
+        ],
+      },
+      {
+        role: "assistant",
+        content: [
+          { type: "reasoning", text: "thinking", providerOptions: { openai: { encryptedContent: "secret" } } },
+          { type: "text", text: "I'll run it" },
+          {
+            type: "tool-call",
+            toolCallId: "call-1",
+            toolName: "bash",
+            input: { command: "ls" },
+            providerOptions: { openai: { itemId: "item-1" } },
+          },
+        ],
+      },
+      {
+        role: "tool",
+        content: [
+          {
+            type: "tool-result",
+            toolCallId: "call-1",
+            toolName: "bash",
+            output: { type: "text", value: "ok" },
+            providerOptions: { openai: { outputId: "output-1" } },
+          },
+        ],
+      },
+    ]
+
+    const request = LLMNative.request({
+      model: baseModel,
+      system: ["agent system"],
+      messages,
+      tools: {
+        bash: tool({
+          description: "Run a shell command",
+          inputSchema: jsonSchema({
+            type: "object",
+            properties: {
+              command: { type: "string" },
+            },
+            required: ["command"],
+          }),
+        }),
+      },
+      toolChoice: "required",
+      temperature: 0.2,
+      topP: 0.9,
+      topK: 40,
+      maxOutputTokens: 1024,
+      providerOptions: { openai: { store: false } },
+      headers: { "x-request": "request-header" },
+    })
+
+    expect(request.model).toMatchObject({
+      id: "gpt-5-mini",
+      provider: "openai",
+      route: "openai-responses",
+      baseURL: "https://api.openai.com/v1",
+      headers: {
+        "x-model": "model-header",
+        "x-request": "request-header",
+      },
+      limits: {
+        context: 128_000,
+        output: 32_000,
+      },
+    })
+    expect(request.system).toEqual([
+      { type: "text", text: "agent system" },
+      { type: "text", text: "system from messages" },
+    ])
+    expect(request.generation).toMatchObject({
+      temperature: 0.2,
+      topP: 0.9,
+      topK: 40,
+      maxTokens: 1024,
+    })
+    expect(request.providerOptions).toEqual({ openai: { store: false } })
+    expect(request.toolChoice).toMatchObject({ type: "required" })
+    expect(request.tools).toMatchObject([
+      {
+        name: "bash",
+        description: "Run a shell command",
+        inputSchema: {
+          type: "object",
+          properties: {
+            command: { type: "string" },
+          },
+          required: ["command"],
+        },
+      },
+    ])
+    expect(request.messages).toMatchObject([
+      {
+        role: "user",
+        content: [
+          { type: "text", text: "hello", providerMetadata: { openai: { cacheControl: { type: "ephemeral" } } } },
+          { type: "media", mediaType: "image/png", filename: "img.png", data: "data:image/png;base64,Zm9v" },
+        ],
+      },
+      {
+        role: "assistant",
+        content: [
+          { type: "reasoning", text: "thinking", providerMetadata: { openai: { encryptedContent: "secret" } } },
+          { type: "text", text: "I'll run it" },
+          {
+            type: "tool-call",
+            id: "call-1",
+            name: "bash",
+            input: { command: "ls" },
+            providerMetadata: { openai: { itemId: "item-1" } },
+          },
+        ],
+      },
+      {
+        role: "tool",
+        content: [
+          {
+            type: "tool-result",
+            id: "call-1",
+            name: "bash",
+            result: { type: "text", value: "ok" },
+            providerMetadata: { openai: { outputId: "output-1" } },
+          },
+        ],
+      },
+    ])
+  })
+
+  test("selects native routes from existing provider packages", () => {
+    expect(
+      LLMNative.model({ ...baseModel, api: { ...baseModel.api, url: "", npm: "@ai-sdk/anthropic" } }),
+    ).toMatchObject({
+      route: "anthropic-messages",
+      baseURL: "https://api.anthropic.com/v1",
+    })
+    expect(LLMNative.model({ ...baseModel, api: { ...baseModel.api, url: "", npm: "@ai-sdk/google" } })).toMatchObject({
+      route: "gemini",
+      baseURL: "https://generativelanguage.googleapis.com/v1beta",
+    })
+    expect(
+      LLMNative.model({ ...baseModel, api: { ...baseModel.api, npm: "@ai-sdk/openai-compatible" } }),
+    ).toMatchObject({
+      route: "openai-compatible-chat",
+      baseURL: "https://api.openai.com/v1",
+    })
+    expect(
+      LLMNative.model({ ...baseModel, api: { ...baseModel.api, url: "", npm: "@openrouter/ai-sdk-provider" } }),
+    ).toMatchObject({
+      route: "openrouter",
+      baseURL: "https://openrouter.ai/api/v1",
+    })
+  })
+
+  test("fails fast for unsupported provider packages", () => {
+    expect(() =>
+      LLMNative.request({
+        model: { ...baseModel, api: { ...baseModel.api, npm: "unknown-provider" } },
+        messages: [],
+      }),
+    ).toThrow("Native LLM request adapter does not support provider package unknown-provider")
+  })
+
+  test("compiles through the native OpenAI Responses route", async () => {
+    const prepared = await Effect.runPromise(
+      LLMClient.prepare(
+        LLMNative.request({
+          model: baseModel,
+          messages: [{ role: "user", content: "hello" }],
+          providerOptions: { openai: { store: false } },
+          maxOutputTokens: 512,
+          headers: { "x-request": "request-header" },
+        }),
+      ).pipe(Effect.provide(LLMClient.layer), Effect.provide(RequestExecutor.defaultLayer)),
+    )
+
+    expect(prepared).toMatchObject({
+      route: "openai-responses",
+      protocol: "openai-responses",
+      body: {
+        model: "gpt-5-mini",
+        input: [{ role: "user", content: [{ type: "input_text", text: "hello" }] }],
+        max_output_tokens: 512,
+        store: false,
+        stream: true,
+      },
+    })
+  })
+})

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

@@ -1,15 +1,19 @@
 import { afterAll, beforeAll, beforeEach, describe, expect, test } from "bun:test"
 import path from "path"
 import { tool, type ModelMessage } from "ai"
-import { Cause, Effect, Exit, Stream } from "effect"
+import { Cause, Effect, Exit, Layer, Stream } from "effect"
+import { HttpClientRequest, HttpClientResponse } from "effect/unstable/http"
 import z from "zod"
-import { makeRuntime } from "../../src/effect/run-service"
+import { attach, makeRuntime } from "../../src/effect/run-service"
 import { LLM } from "../../src/session/llm"
-import { Instance } from "../../src/project/instance"
+import { LLMClient, RequestExecutor } from "@opencode-ai/llm/route"
 import { WithInstance } from "../../src/project/with-instance"
+import { Auth } from "@/auth"
+import { Config } from "@/config/config"
 import { Provider } from "@/provider/provider"
 import { ProviderTransform } from "@/provider/transform"
 import { ModelsDev } from "@/provider/models"
+import { Plugin } from "@/plugin"
 import { ProviderID, ModelID } from "../../src/provider/schema"
 import { Filesystem } from "@/util/filesystem"
 import { tmpdir } from "../fixture/fixture"
@@ -18,6 +22,29 @@ import { MessageV2 } from "../../src/session/message-v2"
 import { SessionID, MessageID } from "../../src/session/schema"
 import { AppRuntime } from "../../src/effect/app-runtime"
 
+const openAIConfig = (model: ModelsDev.Provider["models"][string], baseURL: string): Partial<Config.Info> => {
+  const { experimental: _experimental, ...configModel } = model
+  type ConfigModel = NonNullable<NonNullable<Config.Info["provider"]>[string]["models"]>[string]
+  return {
+    enabled_providers: ["openai"],
+    provider: {
+      openai: {
+        name: "OpenAI",
+        env: ["OPENAI_API_KEY"],
+        npm: "@ai-sdk/openai",
+        api: "https://api.openai.com/v1",
+        models: {
+          [model.id]: JSON.parse(JSON.stringify(configModel)) as ConfigModel,
+        },
+        options: {
+          apiKey: "test-openai-key",
+          baseURL,
+        },
+      },
+    },
+  }
+}
+
 async function getModel(providerID: ProviderID, modelID: ModelID) {
   return AppRuntime.runPromise(
     Effect.gen(function* () {
@@ -33,6 +60,22 @@ async function drain(input: LLM.StreamInput) {
   return llm.runPromise((svc) => svc.stream(input).pipe(Stream.runDrain))
 }
 
+async function drainWith(layer: Layer.Layer<LLM.Service>, input: LLM.StreamInput) {
+  return Effect.runPromise(
+    attach(LLM.Service.use((svc) => svc.stream(input).pipe(Stream.runDrain))).pipe(Effect.provide(layer)),
+  )
+}
+
+function llmLayerWithExecutor(executor: Layer.Layer<RequestExecutor.Service>) {
+  return LLM.layer.pipe(
+    Layer.provide(Auth.defaultLayer),
+    Layer.provide(Config.defaultLayer),
+    Layer.provide(Provider.defaultLayer),
+    Layer.provide(Plugin.defaultLayer),
+    Layer.provide(LLMClient.layer.pipe(Layer.provide(executor))),
+  )
+}
+
 describe("session.llm.hasToolCalls", () => {
   test("returns false for empty messages array", () => {
     expect(LLM.hasToolCalls([])).toBe(false)
@@ -615,32 +658,7 @@ describe("session.llm.stream", () => {
     ]
     const request = waitRequest("/responses", createEventResponse(responseChunks, true))
 
-    await using tmp = await tmpdir({
-      init: async (dir) => {
-        await Bun.write(
-          path.join(dir, "opencode.json"),
-          JSON.stringify({
-            $schema: "https://opencode.ai/config.json",
-            enabled_providers: ["openai"],
-            provider: {
-              openai: {
-                name: "OpenAI",
-                env: ["OPENAI_API_KEY"],
-                npm: "@ai-sdk/openai",
-                api: "https://api.openai.com/v1",
-                models: {
-                  [model.id]: model,
-                },
-                options: {
-                  apiKey: "test-openai-key",
-                  baseURL: `${server.url.origin}/v1`,
-                },
-              },
-            },
-          }),
-        )
-      },
-    })
+    await using tmp = await tmpdir({ config: openAIConfig(model, `${server.url.origin}/v1`) })
 
     await WithInstance.provide({
       directory: tmp.path,
@@ -688,6 +706,333 @@ describe("session.llm.stream", () => {
     })
   })
 
+  test("streams OpenAI through native runtime when opted in", async () => {
+    const server = state.server
+    if (!server) {
+      throw new Error("Server not initialized")
+    }
+
+    const source = await loadFixture("openai", "gpt-5.2")
+    const model = source.model
+    const chunks = [
+      {
+        type: "response.created",
+        response: {
+          id: "resp-native",
+        },
+      },
+      {
+        type: "response.output_item.added",
+        item: { type: "message", id: "item-native", status: "in_progress" },
+      },
+      {
+        type: "response.output_text.delta",
+        item_id: "item-native",
+        delta: "Hello native",
+      },
+      {
+        type: "response.completed",
+        response: {
+          incomplete_details: null,
+          usage: {
+            input_tokens: 1,
+            input_tokens_details: null,
+            output_tokens: 1,
+            output_tokens_details: null,
+          },
+        },
+      },
+    ]
+    const request = waitRequest("/responses", createEventResponse(chunks, true))
+
+    await using tmp = await tmpdir({ config: openAIConfig(model, `${server.url.origin}/v1`) })
+
+    await WithInstance.provide({
+      directory: tmp.path,
+      fn: async () => {
+        const previous = process.env.OPENCODE_LLM_RUNTIME
+        process.env.OPENCODE_LLM_RUNTIME = "native"
+        try {
+          const resolved = await getModel(ProviderID.openai, ModelID.make(model.id))
+          const sessionID = SessionID.make("session-test-native")
+          const agent = {
+            name: "test",
+            mode: "primary",
+            options: {},
+            permission: [{ permission: "*", pattern: "*", action: "allow" }],
+            temperature: 0.2,
+          } satisfies Agent.Info
+
+          await drain({
+            user: {
+              id: MessageID.make("msg_user-native"),
+              sessionID,
+              role: "user",
+              time: { created: Date.now() },
+              agent: agent.name,
+              model: { providerID: ProviderID.make("openai"), modelID: resolved.id, variant: "high" },
+            } satisfies MessageV2.User,
+            sessionID,
+            model: resolved,
+            agent,
+            system: ["You are a helpful assistant."],
+            messages: [{ role: "user", content: "Hello" }],
+            tools: {},
+          })
+        } finally {
+          if (previous === undefined) delete process.env.OPENCODE_LLM_RUNTIME
+          else process.env.OPENCODE_LLM_RUNTIME = previous
+        }
+
+        const capture = await request
+        expect(capture.url.pathname.endsWith("/responses")).toBe(true)
+        expect(capture.headers.get("Authorization")).toBe("Bearer test-openai-key")
+        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(JSON.stringify(capture.body.input)).toContain("You are a helpful assistant.")
+        expect(capture.body.input).toContainEqual({ role: "user", content: [{ type: "input_text", text: "Hello" }] })
+      },
+    })
+  })
+
+  test("uses injected native request executor for tool calls", async () => {
+    const source = await loadFixture("openai", "gpt-5.2")
+    const model = source.model
+    const chunks = [
+      {
+        type: "response.output_item.added",
+        item: { type: "function_call", id: "item-injected-tool", call_id: "call-injected-tool", name: "lookup" },
+      },
+      {
+        type: "response.function_call_arguments.delta",
+        item_id: "item-injected-tool",
+        delta: '{"query":"weather"}',
+      },
+      {
+        type: "response.output_item.done",
+        item: {
+          type: "function_call",
+          id: "item-injected-tool",
+          call_id: "call-injected-tool",
+          name: "lookup",
+          arguments: '{"query":"weather"}',
+        },
+      },
+      {
+        type: "response.completed",
+        response: { incomplete_details: null, usage: { input_tokens: 1, output_tokens: 1 } },
+      },
+    ]
+    let captured: Record<string, unknown> | undefined
+    let executed: unknown
+    const executor = Layer.succeed(
+      RequestExecutor.Service,
+      RequestExecutor.Service.of({
+        execute: (request) =>
+          Effect.gen(function* () {
+            const web = yield* HttpClientRequest.toWeb(request).pipe(Effect.orDie)
+            captured = (yield* Effect.promise(() => web.json())) as Record<string, unknown>
+            return HttpClientResponse.fromWeb(request, createEventResponse(chunks, true))
+          }),
+      }),
+    )
+
+    await using tmp = await tmpdir({ config: openAIConfig(model, "https://injected-openai.test/v1") })
+
+    await WithInstance.provide({
+      directory: tmp.path,
+      fn: async () => {
+        const previous = process.env.OPENCODE_LLM_RUNTIME
+        process.env.OPENCODE_LLM_RUNTIME = "native"
+        try {
+          const resolved = await getModel(ProviderID.openai, ModelID.make(model.id))
+          const sessionID = SessionID.make("session-test-native-injected-tool")
+          const agent = {
+            name: "test",
+            mode: "primary",
+            options: {},
+            permission: [{ permission: "*", pattern: "*", action: "allow" }],
+          } satisfies Agent.Info
+
+          await drainWith(llmLayerWithExecutor(executor), {
+            user: {
+              id: MessageID.make("msg_user-native-injected-tool"),
+              sessionID,
+              role: "user",
+              time: { created: Date.now() },
+              agent: agent.name,
+              model: { providerID: ProviderID.make("openai"), modelID: resolved.id },
+            } satisfies MessageV2.User,
+            sessionID,
+            model: resolved,
+            agent,
+            system: [],
+            messages: [{ role: "user", content: "Use lookup" }],
+            tools: {
+              lookup: tool({
+                description: "Lookup data",
+                inputSchema: z.object({ query: z.string() }),
+                execute: async (args, options) => {
+                  executed = { args, toolCallId: options.toolCallId }
+                  return { output: "looked up" }
+                },
+              }),
+            },
+          })
+        } finally {
+          if (previous === undefined) delete process.env.OPENCODE_LLM_RUNTIME
+          else process.env.OPENCODE_LLM_RUNTIME = previous
+        }
+
+        expect(captured?.model).toBe(model.id)
+        expect(captured?.tools).toEqual([
+          {
+            type: "function",
+            name: "lookup",
+            description: "Lookup data",
+            parameters: {
+              type: "object",
+              properties: { query: { type: "string" } },
+              required: ["query"],
+              additionalProperties: false,
+              $schema: "http://json-schema.org/draft-07/schema#",
+            },
+          },
+        ])
+        expect(executed).toEqual({ args: { query: "weather" }, toolCallId: "call-injected-tool" })
+      },
+    })
+  })
+
+  test("executes OpenAI tool calls through native runtime", async () => {
+    const server = state.server
+    if (!server) {
+      throw new Error("Server not initialized")
+    }
+
+    const source = await loadFixture("openai", "gpt-5.2")
+    const model = source.model
+    const chunks = [
+      {
+        type: "response.output_item.added",
+        item: { type: "function_call", id: "item-native-tool", call_id: "call-native-tool", name: "lookup" },
+      },
+      {
+        type: "response.function_call_arguments.delta",
+        item_id: "item-native-tool",
+        delta: '{"query":"weather"}',
+      },
+      {
+        type: "response.output_item.done",
+        item: {
+          type: "function_call",
+          id: "item-native-tool",
+          call_id: "call-native-tool",
+          name: "lookup",
+          arguments: '{"query":"weather"}',
+        },
+      },
+      {
+        type: "response.completed",
+        response: { incomplete_details: null, usage: { input_tokens: 1, output_tokens: 1 } },
+      },
+    ]
+    const request = waitRequest("/responses", createEventResponse(chunks, true))
+    let executed: unknown
+
+    await using tmp = await tmpdir({
+      init: async (dir) => {
+        await Bun.write(
+          path.join(dir, "opencode.json"),
+          JSON.stringify({
+            $schema: "https://opencode.ai/config.json",
+            enabled_providers: ["openai"],
+            provider: {
+              openai: {
+                name: "OpenAI",
+                env: ["OPENAI_API_KEY"],
+                npm: "@ai-sdk/openai",
+                api: "https://api.openai.com/v1",
+                models: {
+                  [model.id]: model,
+                },
+                options: {
+                  apiKey: "test-openai-key",
+                  baseURL: `${server.url.origin}/v1`,
+                },
+              },
+            },
+          }),
+        )
+      },
+    })
+
+    await WithInstance.provide({
+      directory: tmp.path,
+      fn: async () => {
+        const previous = process.env.OPENCODE_LLM_RUNTIME
+        process.env.OPENCODE_LLM_RUNTIME = "native"
+        try {
+          const resolved = await getModel(ProviderID.openai, ModelID.make(model.id))
+          const sessionID = SessionID.make("session-test-native-tool")
+          const agent = {
+            name: "test",
+            mode: "primary",
+            options: {},
+            permission: [{ permission: "*", pattern: "*", action: "allow" }],
+          } satisfies Agent.Info
+
+          await drain({
+            user: {
+              id: MessageID.make("msg_user-native-tool"),
+              sessionID,
+              role: "user",
+              time: { created: Date.now() },
+              agent: agent.name,
+              model: { providerID: ProviderID.make("openai"), modelID: resolved.id },
+            } satisfies MessageV2.User,
+            sessionID,
+            model: resolved,
+            agent,
+            system: [],
+            messages: [{ role: "user", content: "Use lookup" }],
+            tools: {
+              lookup: tool({
+                description: "Lookup data",
+                inputSchema: z.object({ query: z.string() }),
+                execute: async (args, options) => {
+                  executed = { args, toolCallId: options.toolCallId }
+                  return { output: "looked up" }
+                },
+              }),
+            },
+          })
+        } finally {
+          if (previous === undefined) delete process.env.OPENCODE_LLM_RUNTIME
+          else process.env.OPENCODE_LLM_RUNTIME = previous
+        }
+
+        const capture = await request
+        expect(capture.body.tools).toEqual([
+          {
+            type: "function",
+            name: "lookup",
+            description: "Lookup data",
+            parameters: {
+              type: "object",
+              properties: { query: { type: "string" } },
+              required: ["query"],
+              additionalProperties: false,
+              $schema: "http://json-schema.org/draft-07/schema#",
+            },
+          },
+        ])
+        expect(executed).toEqual({ args: { query: "weather" }, toolCallId: "call-native-tool" })
+      },
+    })
+  })
+
   test("accepts user image attachments as data URLs for OpenAI models", async () => {
     const server = state.server
     if (!server) {