feat: 品牌替换 + 启动优化 + AGENTS.md 模板定制
- 品牌替换：OpenCode/opencode → AirCoding/aircoding（16+ 文件） - Logo ASCII art：修复 left/right 行数不匹配导致的启动崩溃 - 启动诊断：添加 OPENCODE_PRINT_TIMING 计时探针 - dev 模式默认 --pure 跳过外部插件加载 - AGENTS.md 模板：追加 AirCoding 多 Agent 专项段落 - architect prompt + plugin：强化 AGENTS.md 产出验证
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airlongdian
186
packages/llm/src/llm.ts
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186
packages/llm/src/llm.ts
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import { Effect, JsonSchema, Schema } from "effect"
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import { LLMClient } from "./route/client"
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import {
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GenerationOptions,
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HttpOptions,
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InvalidProviderOutputReason,
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LLMError,
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LLMEvent,
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LLMRequest,
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LLMResponse,
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Message,
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type ModelInput as SchemaModelInput,
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SystemPart,
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ToolChoice,
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ToolDefinition,
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type ContentPart,
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ToolResultPart,
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} from "./schema"
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import { make as makeTool, toDefinitions, type ToolSchema } from "./tool"
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export type ModelInput = SchemaModelInput
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export type MessageInput = Message.Input
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export type ToolChoiceInput = ToolChoice.Input
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export type ToolChoiceMode = ToolChoice.Mode
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export type ToolResultInput = Parameters<typeof ToolResultPart.make>[0]
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/** Input accepted by `LLM.request`, normalized into the canonical `LLMRequest` class. */
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export type RequestInput = Omit<
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ConstructorParameters<typeof LLMRequest>[0],
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"system" | "messages" | "tools" | "toolChoice" | "generation" | "http" | "providerOptions"
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> & {
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readonly system?: string | SystemPart | ReadonlyArray<SystemPart>
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readonly prompt?: string | ContentPart | ReadonlyArray<ContentPart>
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readonly messages?: ReadonlyArray<Message | MessageInput>
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readonly tools?: ReadonlyArray<ToolDefinition.Input>
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readonly toolChoice?: ToolChoiceInput
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readonly generation?: GenerationOptions.Input
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readonly providerOptions?: ConstructorParameters<typeof LLMRequest>[0]["providerOptions"]
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readonly http?: HttpOptions.Input
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}
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export const generate = LLMClient.generate
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export const stream = LLMClient.stream
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export const requestInput = (input: LLMRequest): RequestInput => ({
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...LLMRequest.input(input),
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})
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export const request = (input: RequestInput) => {
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const {
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system: requestSystem,
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prompt,
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messages,
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tools,
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toolChoice: requestToolChoice,
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generation: requestGeneration,
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providerOptions: requestProviderOptions,
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http: requestHttp,
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...rest
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} = input
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return new LLMRequest({
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...rest,
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system: SystemPart.content(requestSystem),
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messages: [...(messages?.map(Message.make) ?? []), ...(prompt === undefined ? [] : [Message.user(prompt)])],
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tools: tools?.map(ToolDefinition.make) ?? [],
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toolChoice: requestToolChoice ? ToolChoice.make(requestToolChoice) : undefined,
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generation: requestGeneration === undefined ? undefined : GenerationOptions.make(requestGeneration),
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providerOptions: requestProviderOptions,
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http: requestHttp === undefined ? undefined : HttpOptions.make(requestHttp),
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})
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}
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export const updateRequest = (input: LLMRequest, patch: Partial<RequestInput>) =>
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request({ ...requestInput(input), ...patch })
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const GENERATE_OBJECT_TOOL_NAME = "generate_object"
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const GENERATE_OBJECT_TOOL_DESCRIPTION = "Return the structured result by calling this tool."
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type GenerateObjectBase = Omit<RequestInput, "tools" | "toolChoice" | "responseFormat">
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export class GenerateObjectResponse<T> {
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constructor(
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readonly object: T,
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readonly response: LLMResponse,
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) {}
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get events() {
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return this.response.events
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}
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get usage() {
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return this.response.usage
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}
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}
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export interface GenerateObjectOptions<S extends ToolSchema<any>> extends GenerateObjectBase {
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readonly schema: S
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}
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export interface GenerateObjectDynamicOptions extends GenerateObjectBase {
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/** Raw JSON Schema object describing the expected output shape. */
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readonly jsonSchema: JsonSchema.JsonSchema
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}
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const runGenerateObject = Effect.fn("LLM.generateObject")(function* (
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options: GenerateObjectBase,
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tool: ReturnType<typeof makeTool>,
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) {
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const baseRequest = request(options)
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const generateRequest = LLMRequest.update(baseRequest, {
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tools: toDefinitions({ [GENERATE_OBJECT_TOOL_NAME]: tool }),
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toolChoice: ToolChoice.named(GENERATE_OBJECT_TOOL_NAME),
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})
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const response = yield* LLMClient.generate(generateRequest)
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const call = response.toolCalls.find(
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(event) => LLMEvent.is.toolCall(event) && event.name === GENERATE_OBJECT_TOOL_NAME,
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)
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if (!call || !LLMEvent.is.toolCall(call))
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return yield* new LLMError({
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module: "LLM",
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method: "generateObject",
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reason: new InvalidProviderOutputReason({
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message: `generateObject: model did not call the forced \`${GENERATE_OBJECT_TOOL_NAME}\` tool`,
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}),
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})
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const object = yield* tool._decode(call.input).pipe(
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Effect.mapError(
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(error) =>
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new LLMError({
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module: "LLM",
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method: "generateObject",
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reason: new InvalidProviderOutputReason({
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message: `generateObject: tool input failed schema decode: ${error.message}`,
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}),
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}),
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),
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)
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return new GenerateObjectResponse(object, response)
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})
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/**
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* Run a model and decode its output against `schema`. Works on every protocol
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* because it forces a synthetic tool call internally — provider-native JSON
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* modes are intentionally avoided so behaviour is uniform.
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*
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* Two input modes:
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*
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* 1. `schema: EffectSchema<T>` — `.object` is decoded and typed as `T`.
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* Decode failures surface as `LLMError`.
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* 2. `jsonSchema: JsonSchema.JsonSchema` — `.object` is `unknown`. Use when
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* the schema is only available at runtime (MCP, plugin manifests). Caller validates.
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*/
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export function generateObject<S extends ToolSchema<any>>(
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options: GenerateObjectOptions<S>,
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): Effect.Effect<GenerateObjectResponse<Schema.Schema.Type<S>>, LLMError>
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export function generateObject(
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options: GenerateObjectDynamicOptions,
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): Effect.Effect<GenerateObjectResponse<unknown>, LLMError>
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export function generateObject(options: GenerateObjectOptions<ToolSchema<any>> | GenerateObjectDynamicOptions) {
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if ("schema" in options) {
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const { schema, ...rest } = options
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return runGenerateObject(
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rest,
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makeTool({
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description: GENERATE_OBJECT_TOOL_DESCRIPTION,
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parameters: schema,
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success: Schema.Unknown as ToolSchema<unknown>,
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execute: () => Effect.void,
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}),
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)
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}
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const { jsonSchema, ...rest } = options
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return runGenerateObject(
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rest,
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makeTool({
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description: GENERATE_OBJECT_TOOL_DESCRIPTION,
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jsonSchema,
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execute: () => Effect.void,
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}),
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)
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}
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