Refactor LLM route-first provider API (#28523)

2026-05-20 20:15:52 -04:00
parent 5381795844
commit 41f6daf96a
87 changed files with 2450 additions and 1520 deletions
--- a/packages/llm/example/call-sites.md
+++ b/packages/llm/example/call-sites.md
@@ -0,0 +1,591 @@
+# LLM Call Site Sketches
+
+Scratchpad for examples first, abstractions second. Current direction: routes
+execute, provider facades organize configured route sets, and models carry route
+values directly.
+
+## Conversation Summary
+
+Kit and Aidan want provider-specific LLM behavior to move out of opencode's AI
+SDK transform path and into `packages/llm` where possible. The goal is not a big
+generic transform layer; the goal is small composable route definitions backed by
+recorded golden tests.
+
+Things to keep testing against:
+
+- Cache placement: `cache: "auto"`, manual cache breakpoints, provider cache usage.
+- Images: golden image tests for providers/protocols that claim image support.
+- Reasoning: canonical reasoning parts/events versus provider-native knobs.
+- Auth: bearer, custom headers, multiple credentials, query auth, SigV4, OAuth, no auth.
+- OpenAI-compatible providers: DeepSeek, Together, Groq, Alibaba/DashScope, custom routers.
+- Provider switching: stale signatures, encrypted reasoning, provider metadata, incompatible parts.
+- Error quality: typed errors instead of generic SDK/server failures.
+
+## Final Guide: Routes Execute, Providers Organize
+
+Do not introduce a first-class `Deployment` abstraction unless it gains real
+semantics. Provider facades are ergonomic configured route groups, not execution
+registries. The executable/composable thing is still a route. Do not make route
+construction publish to a global registry; models should carry their route value
+directly.
+
+Keep durable identity separate from runtime capability:
+
+- Durable identity is small serializable data like `{ providerID, modelID }` for
+  config, sessions, logs, and catalogs.
+- Runtime capability is a `Model` with a route value, protocol, transport, auth,
+  and defaults. It is allowed to contain functions and schemas.
+- If persisted identity needs to become executable, resolve it through an app
+  boundary first. Do not make `LLMRequest` recover behavior from a global route
+  side table.
+
+Keep unconfigured behavior values as values, not factories. A transport like
+`HttpTransport.sseJson` should be a reusable immutable value. Use a function only
+when the caller supplies options or when construction needs fresh state.
+
+Use constants to remove repetition before inventing abstractions. Provider ids
+are branded once per provider facade and reused across routes; a plain exported
+object is enough for the provider-facing API unless a helper earns its keep by
+removing repeated route projection.
+
+Expose default configured provider instances, and put provider-specific setup on
+`.configure(...)`. Model selectors stay pure: `model(id)`, `responses(id)`,
+`chat(id)`, etc. Endpoint/auth/resource/api-version configuration happens before
+model selection, not as a second argument to model selection.
+
+Use provider/product facades consistently:
+
+- One coherent provider/product config surface gets one top-level facade.
+- APIs/model kinds that share that config are methods on the facade.
+- Different products with different required config get separate top-level
+  facades, not a shared namespace with unrelated children.
+- Default facades are exposed only when concrete defaults or lazy env/credential
+  defaults make the facade valid.
+
+Examples:
+
+```ts
+OpenAI.responses("gpt-4o")
+OpenAI.chat("gpt-4o")
+OpenAI.responsesWebSocket("gpt-4o")
+
+Azure.configure({ resourceName, apiKey }).responses("my-deployment")
+AmazonBedrock.configure({ region, credentials }).model("anthropic.claude-3-5-sonnet-20241022-v2:0")
+
+CloudflareAIGateway.configure({ accountId, gatewayId, gatewayApiKey, apiKey }).model("openai/gpt-4o")
+CloudflareWorkersAI.configure({ accountId, apiKey }).model("@cf/meta/llama-3.1-8b-instruct")
+
+OpenAICompatible.configure({
+  provider: "custom",
+  baseURL: "https://custom.example/v1",
+  auth: Auth.bearer(apiKey),
+}).model("custom-model")
+```
+
+Standardize the provider facade contract before abstracting construction. A
+plain object is enough at first; add a helper only if repeated route projection
+starts hiding the real provider-specific config.
+
+`Route.with(...)` patch semantics should be boring and explicit:
+
+- Omitted fields inherit from the original route.
+- `endpoint` patches merge with the existing endpoint, so overriding `baseURL`
+  keeps the existing `path`.
+- `endpoint.query` merges by default; later values win.
+- `auth` replaces.
+- `headers` merge by default; undefined values are omitted.
+- `id` is optional in patches. Route ids are diagnostic/provider API labels, not
+  global runtime registry keys.
+
+1. **Route**
+   - route id
+   - provider id
+   - protocol
+   - body schema
+   - body builder
+   - stream event schema
+   - parser/state machine
+   - transport
+     - method / IO shape
+     - framing
+     - request preparation
+     - constants when unconfigured; functions only when configured
+   - endpoint
+     - base URL
+     - static path
+     - body/model-derived path
+     - query params
+   - auth
+     - bearer
+     - custom header
+     - multiple credentials
+     - SigV4
+     - none
+   - defaults
+     - headers
+     - generation defaults
+     - provider options
+     - limits
+2. **Provider Facade**
+   - default configured provider instance
+   - provider-specific `.configure(...)`
+   - plain object/function facade over one or more routes
+   - top-level export only when it represents one coherent config surface
+   - no passive `Provider.make(...)` wrapper unless it gains runtime behavior
+3. **Model Selector**
+   - route/provider-owned selector
+   - accepts model id only
+   - returns executable models
+   - does not accept endpoint/auth/deployment overrides
+4. **Model**
+   - model id
+   - route value
+   - provider id
+   - configured route value at selection time
+5. **LLM Request**
+   - model
+   - messages/tools
+   - generation/cache/reasoning/response-format options
+   - request-level HTTP overlays for per-request headers/query/body additions,
+     not provider endpoint/auth reconfiguration
+6. **Compile**
+   - read route from model
+   - merge route defaults and request overrides
+   - build final URL from route endpoint
+   - apply auth from the configured route
+   - build body with protocol
+   - execute with transport and parse with protocol
+
+## Provider Facade Shape
+
+The provider abstraction is a facade over configured routes, not the runtime
+execution mechanism:
+
+```ts
+type ProviderFacade<APIs, Config> = {
+  readonly id: ProviderID
+  readonly model: (id: string) => Model
+  readonly configure: (input?: Config) => ProviderFacade<APIs, Config>
+} & APIs
+```
+
+Manual construction is fine and should be the default until duplication earns a
+helper:
+
+```ts
+export const OpenAI = {
+  id: openAIProvider,
+  model: openAIResponses.model,
+  responses: openAIResponses.model,
+  chat: openAIChat.model,
+  configure: configureOpenAI,
+} satisfies ProviderFacade<
+  {
+    responses: (id: string) => Model
+    chat: (id: string) => Model
+  },
+  OpenAIConfig
+>
+```
+
+If several providers repeat the same projection from route values to model
+methods, the helper can stay deliberately tiny:
+
+```ts
+const configureOpenAI = (input: OpenAIConfig = {}) =>
+  Provider.define({
+    id: openAIProvider,
+    routes: {
+      responses: openAIResponses.with(openAIConfig(input)),
+      chat: openAIChat.with(openAIConfig(input)),
+    },
+    default: "responses",
+    configure: configureOpenAI,
+  })
+
+export const OpenAI = configureOpenAI()
+```
+
+`Provider.define(...)` would only project route methods and preserve types:
+
+```ts
+OpenAI.model("gpt-4o")
+OpenAI.responses("gpt-4o")
+OpenAI.chat("gpt-4o")
+OpenAI.configure({ apiKey }).responses("gpt-4o")
+```
+
+It must not register routes, select routes dynamically, or participate in
+execution. Execution still reads the route value carried by the model.
+
+## Ideal Call Sites
+
+Define concrete routes for a native provider, then project them through a
+provider facade:
+
+```ts
+const openAIProvider = ProviderID.make("openai")
+
+const openAIResponses = Route.make({
+  id: "openai-responses",
+  provider: openAIProvider,
+  protocol: OpenAIResponses.protocol,
+  transport: HttpTransport.sseJson,
+  endpoint: {
+    baseURL: "https://api.openai.com/v1",
+    path: "/responses",
+  },
+  auth: Auth.envBearer("OPENAI_API_KEY"),
+})
+
+const openAIChat = Route.make({
+  id: "openai-chat",
+  provider: openAIProvider,
+  protocol: OpenAIChat.protocol,
+  transport: HttpTransport.sseJson,
+  endpoint: {
+    baseURL: "https://api.openai.com/v1",
+    path: "/chat/completions",
+  },
+  auth: Auth.envBearer("OPENAI_API_KEY"),
+})
+
+const openAIResponsesWebSocket = openAIResponses.with({
+  id: "openai-responses-websocket",
+  transport: WebSocketTransport.json,
+})
+
+const openAIConfig = (input: OpenAIConfig) => ({
+  endpoint: input.endpoint,
+  auth: input.auth ?? (input.apiKey ? Auth.bearer(input.apiKey) : undefined),
+  headers: {
+    "OpenAI-Organization": input.organization,
+    "OpenAI-Project": input.project,
+  },
+})
+
+const configureOpenAI = (input: OpenAIConfig = {}) => {
+  const responses = openAIResponses.with(openAIConfig(input))
+  const responsesWebSocket = openAIResponsesWebSocket.with(openAIConfig(input))
+  const chat = openAIChat.with(openAIConfig(input))
+
+  return {
+    id: openAIProvider,
+    responses: responses.model,
+    responsesWebSocket: responsesWebSocket.model,
+    chat: chat.model,
+    model: responses.model,
+    configure: configureOpenAI,
+  }
+}
+
+export const OpenAI = configureOpenAI()
+```
+
+Specialize it functionally for concrete providers:
+
+```ts
+const deepSeekProvider = ProviderID.make("deepseek")
+
+const deepseekChat = openAIChat.with({
+  id: "deepseek-chat",
+  provider: deepSeekProvider,
+  endpoint: {
+    baseURL: "https://api.deepseek.com/v1",
+  },
+  auth: Auth.envBearer("DEEPSEEK_API_KEY"),
+})
+
+const configureDeepSeek = (input: OpenAICompatibleConfig = {}) => {
+  const route = deepseekChat.with({
+    endpoint: input.endpoint,
+    auth: input.auth ?? (input.apiKey ? Auth.bearer(input.apiKey) : undefined),
+  })
+
+  return {
+    id: deepSeekProvider,
+    model: route.model,
+    configure: configureDeepSeek,
+  }
+}
+
+export const DeepSeek = {
+  id: deepSeekProvider,
+  model: deepseekChat.model,
+  configure: configureDeepSeek,
+}
+```
+
+Provider-specific configuration happens before model selection:
+
+```ts
+const deepseek = DeepSeek.configure({
+  endpoint: {
+    baseURL: "https://proxy.example.com/v1",
+  },
+  auth: Auth.bearer(apiKey),
+})
+
+const model = deepseek.model("deepseek-chat")
+```
+
+Final request call site stays boring:
+
+```ts
+const response =
+  yield *
+  LLM.generate(
+    LLM.request({
+      model: DeepSeek.model("deepseek-chat"),
+      prompt: "Hello.",
+    }),
+  )
+```
+
+HTTP versus WebSocket is represented as named route selectors, not as model or
+request overrides. Same protocol, different transport, different route:
+
+```ts
+OpenAI.responses("gpt-4o")
+OpenAI.responsesWebSocket("gpt-4o")
+```
+
+The client should not require a different public layer just because a selected
+route uses WebSocket. Use one `LLMClient.layer` with HTTP and WebSocket runtime
+capabilities available; routes that do not need WebSocket simply never touch it.
+If a WebSocket route is selected in an environment without WebSocket support,
+fail with a typed transport configuration error.
+
+Azure is a route specialization with auth/path/default changes plus input
+mapping. The public API configures the Azure resource once, then selects
+deployment ids with pure model selectors:
+
+```ts
+const azureProvider = ProviderID.make("azure")
+
+const azureResponses = openAIResponses.with({
+  id: "azure-openai-responses",
+  provider: azureProvider,
+  auth: Auth.envHeader("api-key", "AZURE_OPENAI_API_KEY"),
+})
+
+const configureAzure = (input: AzureConfig = {}) => {
+  const route = azureResponses.with({
+    endpoint: {
+      baseURL:
+        input.baseURL ??
+        Endpoint.envBaseURL(
+          "AZURE_RESOURCE_NAME",
+          (resourceName) => `https://${resourceName}.openai.azure.com/openai/v1`,
+        ),
+      query: { "api-version": input.apiVersion ?? "v1" },
+    },
+    auth: input.apiKey ? Auth.header("api-key", input.apiKey) : Auth.envHeader("api-key", "AZURE_OPENAI_API_KEY"),
+  })
+
+  return {
+    id: azureProvider,
+    model: route.model,
+    responses: route.model,
+    configure: configureAzure,
+  }
+}
+
+export const Azure = configureAzure()
+
+const azure = Azure.configure({
+  resourceName: "my-resource",
+  apiVersion: "v1",
+})
+
+const model = azure.responses("my-deployment")
+```
+
+Default provider facades are only valid when required configuration has a lazy
+default source. `Azure.responses("my-deployment")` can be valid if endpoint
+resolution reads `AZURE_RESOURCE_NAME` lazily and fails with a typed
+configuration error when missing. If a provider has no sensible lazy default,
+do not expose a default model selector; expose only a configured entrypoint.
+
+Cloudflare AI Gateway and Workers AI are separate product facades because their
+configuration surfaces differ. Do not make a root `Cloudflare.configure(...)`
+pretend there is one coherent Cloudflare provider configuration:
+
+```ts
+const cloudflareProvider = ProviderID.make("cloudflare-ai-gateway")
+
+const cloudflareOpenAIChat = openAIChat.with({
+  id: "cloudflare-ai-gateway-openai-chat",
+  provider: cloudflareProvider,
+  auth: Auth.bearerHeader("cf-aig-authorization").andThen(Auth.bearer()),
+})
+
+const configureCloudflareAIGateway = (input: CloudflareAIGatewayConfig) => {
+  const route = cloudflareOpenAIChat.with({
+    endpoint: {
+      baseURL: `https://gateway.ai.cloudflare.com/v1/${input.accountId}/${input.gatewayId}/openai`,
+    },
+    auth: Auth.bearerHeader("cf-aig-authorization", input.gatewayApiKey).andThen(Auth.bearer(input.apiKey)),
+  })
+
+  return {
+    id: cloudflareProvider,
+    model: (modelID: string) => route.model({ id: modelID }),
+    configure: configureCloudflareAIGateway,
+  }
+}
+
+export const CloudflareAIGateway = {
+  id: cloudflareProvider,
+  configure: configureCloudflareAIGateway,
+}
+
+const gateway = CloudflareAIGateway.configure({
+  accountId: "account",
+  gatewayId: "gateway",
+  gatewayApiKey,
+  apiKey,
+})
+
+const model = gateway.model("openai/gpt-4o")
+```
+
+If a Cloudflare product gains a full lazy env default, it can expose a direct
+selector too. Until then, omitting `CloudflareAIGateway.model(...)` makes missing
+account/gateway configuration unrepresentable.
+
+opencode's dynamic runtime should construct executable models at its app
+boundary instead of exposing a giant unstructured public model constructor or a
+generic dynamic resolver:
+
+```ts
+const model =
+  providerID === "azure"
+    ? Azure.configure(resolvedAzureConfig).responses(apiModelID)
+    : endpoint.websocket
+      ? OpenAI.responsesWebSocket(apiModelID)
+      : OpenAI.responses(apiModelID)
+```
+
+That boundary can branch on durable config/catalog metadata and call typed
+provider APIs directly. Transport selection belongs there too: map metadata like
+`endpoint.websocket` to `OpenAI.responsesWebSocket(apiModelID)`; otherwise use
+the normal `OpenAI.responses(apiModelID)` route. The client runtime only executes
+the route carried by the model.
+
+## Competitive Shape
+
+This follows the strongest parts of adjacent libraries:
+
+- AI SDK: configured provider instances expose provider-specific model methods.
+- Effect AI: executable models carry provider requirements and can be resolved by
+  an app boundary.
+- LiteLLM/opencode config: dynamic `providerID/modelID` branching belongs at the
+  app boundary, not in the typed public provider API or a global runtime
+  resolver.
+- LangChain/LlamaIndex: constructor-style config plus model id is convenient,
+  but we avoid making model selection also configure endpoint/auth.
+
+The chosen split is:
+
+```txt
+Route = execution mechanics
+Provider facade = configured route group
+Model = selected executable model carrying route value
+App boundary = explicit durable-config -> typed-provider call
+```
+
+## What This Removes
+
+- No `Provider.make(...)` as a core abstraction.
+- No `Provider.make(...)` wrapper just to bind an id to model functions. Use a
+  branded provider id constant and a plain exported provider facade.
+- No `Deployment.define(...)` unless future examples force it.
+- No global route registry as the normal execution path.
+- No import side effects required before a model can execute.
+- No duplicate `provider.id` object when selected models already carry provider
+  id.
+- No `model(id, overrides)` escape hatch. Model selection takes the model id;
+  endpoint/auth/deployment customization happens by configuring the route first.
+- No transport override on model/request. HTTP SSE versus WebSocket is a named
+  route selector such as `responses` versus `responsesWebSocket`.
+- No separate public `LLMClient.layerWithWebSocket`. The runtime should expose one
+  client layer with the available transport capabilities.
+- No executable `ModelRef`. The executable handle is `Model`; durable model
+  identity stays separate and cannot execute on its own.
+
+## Implementation Todo
+
+- [x] Replace the current executable `ModelRef` with `Model`.
+- [x] Change `Model.route` to carry a route value, not a `RouteID` string.
+- [ ] Keep a separate durable model identity type for persisted/session/catalog
+      data, likely `{ providerID, modelID }`, and make it clear that it cannot
+      execute without resolver context.
+- [x] Change route model selectors so `route.model(id)` returns an executable
+      model with the route value attached, not a globally registered route id.
+- [x] Remove the standalone `Route.model(route, defaults, mapInput)` helper;
+      configured route instances own model selection.
+- [x] Remove endpoint/auth escape hatches from route model selection; callers must
+      configure endpoint/auth through `route.with(...)` or provider facades before
+      calling `.model(...)`.
+- [x] Remove request-shaping defaults from `Model`; selected models now carry only
+      id, provider, and configured route while defaults live on routes or requests.
+- [x] Rework `LLMClient.prepare` / `stream` / `generate` to read
+      `request.model.route` directly instead of calling `registeredRoute(...)`.
+- [x] Remove `Route.make(...)` global registration from the normal execution
+      path; keep route ids only as diagnostics/provider API labels.
+- [x] Model endpoint as `{ baseURL, path, query }` on routes, then remove the
+      current split where host/query live on the model and path lives in route
+      transport setup.
+- [x] Define `Route.with(...)` with explicit patch semantics for endpoint merge,
+      query merge, header merge, auth replacement, and optional diagnostic id.
+- [x] Make unconfigured transports reusable constants such as
+      `HttpTransport.sseJson`; keep transport functions only for configured/fresh
+      state construction.
+- [x] Collapse the public WebSocket runtime split so one `LLMClient.layer`
+      exposes available transport capabilities and selected routes fail with typed
+      transport config errors when a required capability is missing.
+- [x] Convert OpenAI provider APIs to provider-facade shape:
+      `OpenAI.configure(config).responses(id)`, `.chat(id)`, and
+      `.responsesWebSocket(id)`.
+- [x] Convert Azure to a configured facade where resource/base URL/api version
+      setup happens before selecting deployment ids.
+- [x] Split Cloudflare products into separate facades such as
+      `CloudflareAIGateway` and `CloudflareWorkersAI`; do not expose a shared root
+      config surface unless one product actually exists.
+- [x] Migrate remaining built-in provider facades one at a time so configuration
+      happens before model selection and selectors accept only ids:
+      xAI, GitHub Copilot, OpenRouter, OpenAI-compatible families, Anthropic,
+      Google/Gemini, and Amazon Bedrock now use configured facades such as
+      `Provider.configure(options).model(id)` with named selectors where needed.
+- [ ] Decide whether a tiny `Provider.define(...)` helper is warranted after two
+      or three provider conversions; start with plain objects if duplication is not
+      yet painful.
+- [x] Update `packages/opencode/src/session/llm/native-request.ts` to construct
+      executable models at the session boundary with explicit provider facade
+      calls, mapping catalog metadata such as `endpoint.websocket` to the correct
+      named route selector.
+- [ ] Update tests so direct route/provider tests assert route values are carried
+      by executable models, and opencode/native tests assert boundary-based route
+      selection.
+- [ ] Remove compatibility exports or stale docs only after internal call sites
+      are migrated; do not keep duplicate constructor paths without an external
+      compatibility need.
+
+## Open Questions
+
+- Default facades with required setup: should providers like Azure and Bedrock
+  expose default model selectors only when all required setup has lazy env or
+  credential-chain defaults? If not, omit the default selector so missing config
+  is impossible at the type/API level.
+- Lazy endpoint/auth values: should `Endpoint.envBaseURL(...)` and env-backed
+  auth produce typed configuration/authentication errors at compile/prepare time
+  or only when executing the transport?
+- `Route.with(...)` clearing semantics: endpoint/query/header patches merge by
+  default, but what is the explicit way to remove an inherited value?
+- Provider facade helper: keep plain objects until duplication hurts, or add a
+  tiny `Provider.define(...)` immediately to enforce shape and method projection?
+- Auth shape: should auth stay as today's composable `Auth`, or split into an
+  auth placement/strategy and credential sources?
+- Naming: is `baseURL` still the right endpoint field name, or should it be
+  `origin` / `urlPrefix` to clarify that route `path` is appended?
--- a/packages/llm/example/tutorial.ts
+++ b/packages/llm/example/tutorial.ts
@@ -1,6 +1,6 @@
 import { Config, Effect, Formatter, Layer, Schema, Stream } from "effect"
-import { LLM, LLMClient, Provider, ProviderID, Tool, type ProviderModelOptions } from "@opencode-ai/llm"
-import { Route, Auth, Endpoint, Framing, Protocol, RequestExecutor } from "@opencode-ai/llm/route"
+import { LLM, LLMClient, ProviderID, Tool } from "@opencode-ai/llm"
+import { Route, Auth, Endpoint, Framing, Protocol, RequestExecutor, WebSocketExecutor } from "@opencode-ai/llm/route"
 import { OpenAI } from "@opencode-ai/llm/providers"

 /**
@@ -18,18 +18,18 @@ const apiKey = Config.redacted("OPENAI_API_KEY")

 // 1. Pick a model. The provider helper records provider identity, protocol
 // choice, capabilities, deployment options, authentication, and defaults.
-const model = OpenAI.model("gpt-4o-mini", {
+const model = OpenAI.configure({
  apiKey,
  generation: { maxTokens: 160 },
  providerOptions: {
    openai: { store: false },
  },
-})
+}).model("gpt-4o-mini")

 // 2. Build a provider-neutral request. This is useful when reusing one request
 // across generate and stream examples.
 //
-// Options can live on both the model and the request:
+// Options can live on both the configured route/provider facade and the request:
 //
 //   - `generation`: common controls such as max tokens, temperature, topP/topK,
 //     penalties, seed, and stop sequences.
@@ -39,7 +39,7 @@ const model = OpenAI.model("gpt-4o-mini", {
 //   - `http`: last-resort serializable overlays for final request body, headers,
 //     and query params. Prefer typed `providerOptions` when a field is stable.
 //
-// Model options are defaults. Request options override them for this call.
+// Route/provider options are defaults. Request options override them for this call.
 const request = LLM.request({
  model,
  system: "You are concise and practical.",
@@ -193,19 +193,22 @@ const FakeProtocol = Protocol.make<FakeBody, string, string, void>({
 // axes that the protocol deliberately does not know: URL, auth, and framing.
 const FakeAdapter = Route.make({
  id: "fake-echo",
+  provider: "fake-echo",
  protocol: FakeProtocol,
-  endpoint: Endpoint.path("/v1/echo"),
+  endpoint: Endpoint.path("/v1/echo", { baseURL: "https://fake.local" }),
  auth: Auth.passthrough,
  framing: Framing.sse,
 })

-// A provider module exports a Provider definition. The default `model` helper
-// sets provider identity, protocol id, and the route id resolved by the registry.
-const fakeEchoModel = Route.model(FakeAdapter, { provider: "fake-echo", baseURL: "https://fake.local" })
-const FakeEcho = Provider.make({
+// A provider module exports a configured facade. Configuration happens before
+// model selection; model selectors accept ids only.
+const FakeEcho = {
  id: ProviderID.make("fake-echo"),
-  model: (id: string, options: ProviderModelOptions = {}) => fakeEchoModel({ id, ...options }),
-})
+  configure: () => ({
+    id: ProviderID.make("fake-echo"),
+    model: (id: string) => FakeAdapter.model({ id }),
+  }),
+}

 // `LLMClient.prepare` is the lower-level inspection hook: it compiles through
 // body conversion, validation, endpoint, auth, and HTTP construction without
@@ -213,7 +216,7 @@ const FakeEcho = Provider.make({
 const inspectFakeProvider = Effect.gen(function* () {
  const prepared = yield* LLMClient.prepare(
    LLM.request({
-      model: FakeEcho.model("tiny-echo"),
+      model: FakeEcho.configure().model("tiny-echo"),
      prompt: "Show me the provider pipeline.",
    }),
  )
@@ -227,7 +230,8 @@ const inspectFakeProvider = Effect.gen(function* () {
 // enabled at a time so the tutorial can demonstrate generate, prepare, stream,
 // or tool-loop behavior without spending tokens on every example.
 const requestExecutorLayer = RequestExecutor.defaultLayer
-const llmClientLayer = LLMClient.layer.pipe(Layer.provide(requestExecutorLayer))
+const llmDeps = Layer.mergeAll(requestExecutorLayer, WebSocketExecutor.layer)
+const llmClientLayer = LLMClient.layer.pipe(Layer.provide(llmDeps))

 const program = Effect.gen(function* () {
  // yield* generateOnce
@@ -237,6 +241,6 @@ const program = Effect.gen(function* () {
  // yield* generateStructuredObject
  // yield* generateDynamicObject.pipe(Effect.andThen((response) => Effect.sync(() => console.log(response.object))))
  yield* streamWithTools
-}).pipe(Effect.provide(Layer.mergeAll(requestExecutorLayer, llmClientLayer)))
+}).pipe(Effect.provide(Layer.mergeAll(llmDeps, llmClientLayer)))

 Effect.runPromise(program)