chore: generate
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1 changed files with 154 additions and 145 deletions
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@ -176,7 +176,7 @@ const request = LLM.request({
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})
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// Current API: this performs one provider turn, despite the broad name.
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const response = yield* LLM.generate(request)
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const response = yield * LLM.generate(request)
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// Current API: execution also needs LLMClient.layer and RequestExecutor services.
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```
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@ -242,14 +242,15 @@ executable tools. Call-level values override model defaults.
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Provider-specific options are inferred from the concrete model:
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```ts
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yield* LLM.generate({
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yield *
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LLM.generate({
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model: OpenAI.model("gpt-4.1-mini"),
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prompt: "Hello",
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provider: {
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store: false,
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// OpenAI-specific autocomplete here; no `{ openai: ... }` nesting.
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},
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})
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})
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```
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Code choosing between providers dynamically must narrow the model before using
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@ -278,12 +279,14 @@ provider.
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### Inline input
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```ts
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const result = yield* LLM.generate({
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const result =
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yield *
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LLM.generate({
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model,
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system: "You are concise.",
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prompt: "Summarize this pull request.",
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generation: { maxTokens: 500 },
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})
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})
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```
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### Reusable portable request
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@ -296,7 +299,7 @@ const request = LLM.request({
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})
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// Bind process-local execution behavior only when running.
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const result = yield* LLM.generate({ model, request })
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const result = yield * LLM.generate({ model, request })
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```
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`LLM.request(...)` returns a plain immutable object. Use ordinary object spread
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@ -362,11 +365,13 @@ const tools = {
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}),
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}
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const result = yield* LLM.generate({
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const result =
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yield *
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LLM.generate({
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model,
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prompt: "What is the weather in London?",
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tools,
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})
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})
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// The runtime advertises definitions, dispatches calls, records results, and
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// continues provider turns automatically.
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@ -387,15 +392,14 @@ successful result with `stopReason: "max-turns"`, not an Effect failure.
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### Custom stopping
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```ts
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const result = yield* LLM.generate({
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const result =
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yield *
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LLM.generate({
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model,
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prompt,
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tools,
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stopWhen: StopWhen.any(
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StopWhen.turnCount(8),
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StopWhen.hasToolCall("finalize"),
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),
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})
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stopWhen: StopWhen.any(StopWhen.turnCount(8), StopWhen.hasToolCall("finalize")),
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})
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```
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`stopWhen` accepts one predicate. Composition is explicit through combinators
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@ -427,17 +431,13 @@ const request = LLM.request({
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tools: Tool.toDefinitions(tools),
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})
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const events = yield* LLM.stream(request).pipe(Stream.runCollect)
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const events = yield * LLM.stream(request).pipe(Stream.runCollect)
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const call = Array.from(events).find(LLMEvent.is.toolCall)
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if (call && !call.providerExecuted) {
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const dispatched = yield* ToolRuntime.dispatch(tools, call)
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const dispatched = yield * ToolRuntime.dispatch(tools, call)
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const followUp = LLM.updateRequest(request, {
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messages: [
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...request.messages,
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Message.assistant([call]),
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Message.tool({ ...call, result: dispatched.result }),
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],
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messages: [...request.messages, Message.assistant([call]), Message.tool({ ...call, result: dispatched.result })],
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})
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// Caller must invoke the provider again and repeat the loop.
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}
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@ -452,7 +452,9 @@ OpenCode and other durable runtimes need to own persistence, tool settlement,
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and continuation. They use the explicit turn API:
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```ts
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const result = yield* LLM.generateTurn({
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const result =
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yield *
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LLM.generateTurn({
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model,
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request,
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// Definitions only. generateTurn never dispatches local handlers.
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@ -462,7 +464,7 @@ const result = yield* LLM.generateTurn({
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parameters: WeatherInput,
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}),
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},
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})
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})
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// Persist the TurnResult and settle calls durably before the next turn.
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for (const call of result.toolCalls) {
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@ -494,7 +496,9 @@ const request = LLM.request({
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},
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})
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const result = yield* LLM.generate({
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const result =
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yield *
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LLM.generate({
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model,
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request,
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tools: {
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@ -506,7 +510,7 @@ const result = yield* LLM.generate({
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formatError,
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}),
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},
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})
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})
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```
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Definitions and handlers match by record key. Before the first provider call,
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@ -516,13 +520,15 @@ binding. Missing or incompatible bindings fail with a typed tool-binding error.
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Provider-hosted tools are distinct typed values:
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```ts
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const result = yield* LLM.generate({
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const result =
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yield *
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LLM.generate({
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model: OpenAI.model("gpt-4.1"),
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prompt: "Find today's relevant announcements.",
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tools: {
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search: OpenAI.tool.webSearch({ searchContextSize: "medium" }),
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},
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})
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})
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```
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Hosted tools do not pretend to have local handlers, and callers do not inspect a
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@ -589,11 +595,13 @@ const Weather = Schema.Struct({
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highCelsius: Schema.Number,
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})
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const result = yield* LLM.generate({
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const result =
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yield *
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LLM.generate({
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model,
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prompt: "Give me today's weather for London.",
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output: Weather,
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})
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})
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// Inferred from Weather.
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result.output.city
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@ -612,11 +620,13 @@ Advanced callers may override the strategy when exact provider semantics matter.
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```ts
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// Current API is a separate operation and always forces a synthetic tool.
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const result = yield* LLM.generateObject({
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const result =
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yield *
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LLM.generateObject({
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model,
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prompt,
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schema: Weather,
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})
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})
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```
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The proposal unifies generation and lets capabilities choose the strategy rather
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@ -679,11 +689,12 @@ cache boundaries where explicit caching is supported and does nothing on the wir
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where providers cache implicitly.
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```ts
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yield* LLM.generate({
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yield *
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LLM.generate({
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model,
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prompt,
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cache: "none", // Explicit opt-out.
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})
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})
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```
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Granular cache policy remains available as an advanced request option.
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@ -705,13 +716,14 @@ silently inherit custom retry policies.
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### Timeouts
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```ts
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yield* LLM.generate({
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yield *
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LLM.generate({
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model,
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prompt,
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timeout: "2 minutes", // Entire run, including tools.
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turnTimeout: "30 seconds", // Each provider turn.
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tools,
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})
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})
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```
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Exact Duration input spelling follows Effect conventions. Individual tools may
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@ -740,7 +752,8 @@ retry, or redirect control flow.
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```ts
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const model = OpenAI.model("gpt-4.1", {
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hooks: {
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request: (request) => Effect.succeed({
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request: (request) =>
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Effect.succeed({
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...request,
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metadata: { ...request.metadata, tenant: "acme" },
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}),
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@ -775,7 +788,8 @@ The request customization ladder is:
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5. Experimental provider-definition or protocol patching
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```ts
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yield* LLM.generate({
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yield *
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LLM.generate({
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model,
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prompt,
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http: {
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@ -783,7 +797,7 @@ yield* LLM.generate({
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query: { debug: "true" },
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body: { newlyReleasedProviderField: true },
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},
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})
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})
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```
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Raw overlays are intentional last-resort support for provider features that ship
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@ -905,7 +919,7 @@ Schemas live in a dedicated namespace/subpath instead of flooding root exports:
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```ts
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import { LLMSchema } from "@opencode-ai/ai/schema"
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const request = yield* Schema.decodeUnknown(LLMSchema.Request)(input)
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const request = yield * Schema.decodeUnknown(LLMSchema.Request)(input)
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```
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Schemas cover only serializable domain values:
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@ -928,10 +942,7 @@ Provider authoring is public but experimental.
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### Declarative provider definition
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```ts
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import {
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Provider,
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Protocol,
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} from "@opencode-ai/ai/provider"
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import { Provider, Protocol } from "@opencode-ai/ai/provider"
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export const ExampleAI = Provider.define({
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id: "example",
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@ -996,9 +1007,7 @@ SDK integrations that motivated this package.
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const PatchedResponses = OpenAIResponses.with({
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body: {
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fromRequest: (request) =>
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OpenAIResponses.body.fromRequest(request).pipe(
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Effect.map((body) => ({ ...body, custom_field: true })),
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),
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OpenAIResponses.body.fromRequest(request).pipe(Effect.map((body) => ({ ...body, custom_field: true }))),
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},
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stream: {
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step: patchResponsesStep,
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@ -1043,7 +1052,7 @@ providers, and there is no preferred all-providers barrel.
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## Defaults
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| Concern | Default |
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| --- | --- |
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| ---------------------------- | --------------------------------------------------- |
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| `LLM.generate` semantics | Complete Model Run |
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| `LLM.generateTurn` semantics | Exactly one Provider Turn |
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| Maximum turns | 20 |
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@ -1064,7 +1073,7 @@ providers, and there is no preferred all-providers barrel.
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The redesign intentionally removes or changes these current concepts:
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| Current | Proposed |
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| --- | --- |
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| --------------------------------------- | ----------------------------------------------------------- |
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| `@opencode-ai/llm` | `@opencode-ai/ai` |
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| Mandatory `LLM.request({ model, ... })` | Inline calls or model-free portable requests |
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| `LLM.generate` means one turn | `LLM.generate` means complete run |
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