Initial commit: sage：TypeScript AI Agent 框架 monorepo（llm / memory / tui 三包）
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{
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"name": "@sage/llm",
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"version": "0.1.0",
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"private": true,
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"type": "module",
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"exports": { ".": "./src/index.ts" },
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"dependencies": {
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"@sage/core": "*",
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"ai": "^4.3.0",
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"@ai-sdk/anthropic": "^1.0.0",
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"@ai-sdk/openai": "^1.0.0",
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"@ai-sdk/google": "^1.0.0",
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"zod": "^3.24.0"
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},
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"devDependencies": {
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"@types/node": "^22.0.0",
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"typescript": "^5.8.0"
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}
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}
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import { streamText, tool, type CoreMessage, type CoreTool, type TextStreamPart } from "ai"
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import { z } from "zod"
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import type { SageConfig, AnyToolDef, ToolContext } from "@sage/core"
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import { ALL_TOOLS, getTool, addMessage, updateMessage } from "@sage/core"
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import { getLanguageModel, type ProviderID } from "./providers/index.js"
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import type { LLMEventEmitter } from "./types.js"
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const SYSTEM_PROMPT = `You are Sage, an expert AI coding assistant. You help users write, debug, and understand code.
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You have access to tools to read/write files, run shell commands, search code, and more.
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Always prefer using tools to gather information before answering.
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When editing files, use the edit tool for small changes and write for large rewrites.
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Be concise but complete. Show your reasoning when working through complex problems.`
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export interface RunOptions {
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sessionId: string
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messages: CoreMessage[]
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model: string
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provider: string
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cwd: string
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config: SageConfig
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memoryContext?: string
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onEvent: LLMEventEmitter
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signal?: AbortSignal
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}
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export async function runLLM(opts: RunOptions): Promise<void> {
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const { sessionId, messages, model, provider, cwd, config, onEvent, signal } = opts
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const toolContext: ToolContext = {
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sessionId,
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cwd,
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onProgress: (text) => {
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/* incremental tool output — currently unused at this level */
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},
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}
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const aiTools: Record<string, CoreTool> = {}
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for (const t of ALL_TOOLS) {
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aiTools[t.name] = tool({
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description: t.description,
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parameters: t.inputSchema as z.ZodType<Record<string, unknown>>,
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execute: async (input) => {
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const result = await t.execute(input as Record<string, unknown>, toolContext)
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return result
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},
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})
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}
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const systemParts: string[] = [SYSTEM_PROMPT]
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if (opts.memoryContext) {
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systemParts.push(`\n## Recalled Memories\n${opts.memoryContext}`)
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}
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systemParts.push(`\nCurrent working directory: ${cwd}`)
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const lm = getLanguageModel(provider as ProviderID, model, config)
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const currentMessages = [...messages]
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let assistantMsgId: string | null = null
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let accText = ""
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const stream = streamText({
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model: lm,
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system: systemParts.join("\n"),
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messages: currentMessages,
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tools: aiTools,
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maxSteps: 20,
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abortSignal: signal,
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})
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for await (const part of stream.fullStream) {
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if (signal?.aborted) break
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switch (part.type) {
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case "text-delta": {
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if (!assistantMsgId) {
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const msg = await addMessage({
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sessionId,
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role: "assistant",
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content: "",
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})
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assistantMsgId = msg.id
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}
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accText += part.textDelta
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await updateMessage(assistantMsgId, { content: accText })
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onEvent({ type: "text-delta", delta: part.textDelta })
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break
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}
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case "tool-call": {
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onEvent({
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type: "tool-call",
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toolCall: {
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id: part.toolCallId,
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name: part.toolName,
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input: part.args as Record<string, unknown>,
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},
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})
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break
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}
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case "tool-result": {
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const output = typeof part.result === "string"
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? part.result
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: JSON.stringify(part.result, null, 2)
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await addMessage({
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sessionId,
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role: "tool",
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content: output,
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toolCallId: part.toolCallId,
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})
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onEvent({
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type: "tool-result",
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toolResult: {
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toolCallId: part.toolCallId,
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toolName: part.toolName,
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output,
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},
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})
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break
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}
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case "finish": {
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const usage = part.usage
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if (assistantMsgId && usage) {
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await updateMessage(assistantMsgId, {
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tokensInput: usage.promptTokens,
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tokensOutput: usage.completionTokens,
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})
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}
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onEvent({
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type: "finish",
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usage: usage
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? { inputTokens: usage.promptTokens, outputTokens: usage.completionTokens }
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: undefined,
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})
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break
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}
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case "error": {
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onEvent({ type: "error", error: part.error as Error })
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break
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}
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}
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}
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}
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@@ -0,0 +1,3 @@
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export * from "./client.js"
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export * from "./providers/index.js"
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export * from "./types.js"
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@@ -0,0 +1,75 @@
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import { createAnthropic } from "@ai-sdk/anthropic"
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import { createOpenAI } from "@ai-sdk/openai"
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import { createGoogleGenerativeAI } from "@ai-sdk/google"
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import type { LanguageModelV1 } from "ai"
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import type { SageConfig } from "@sage/core"
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export type ProviderID = "anthropic" | "openai" | "google" | "openrouter"
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export interface ProviderModel {
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id: string
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name: string
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contextWindow: number
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supportsTools: boolean
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}
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export const PROVIDER_MODELS: Record<ProviderID, ProviderModel[]> = {
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anthropic: [
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{ id: "claude-opus-4-8", name: "Claude Opus 4.8", contextWindow: 200_000, supportsTools: true },
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{ id: "claude-sonnet-4-6", name: "Claude Sonnet 4.6", contextWindow: 200_000, supportsTools: true },
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{ id: "claude-haiku-4-5-20251001", name: "Claude Haiku 4.5", contextWindow: 200_000, supportsTools: true },
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],
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openai: [
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{ id: "gpt-4o", name: "GPT-4o", contextWindow: 128_000, supportsTools: true },
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{ id: "gpt-4o-mini", name: "GPT-4o Mini", contextWindow: 128_000, supportsTools: true },
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{ id: "o3", name: "o3", contextWindow: 200_000, supportsTools: true },
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],
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google: [
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{ id: "gemini-2.5-pro", name: "Gemini 2.5 Pro", contextWindow: 1_000_000, supportsTools: true },
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{ id: "gemini-2.5-flash", name: "Gemini 2.5 Flash", contextWindow: 1_000_000, supportsTools: true },
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],
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openrouter: [
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{ id: "anthropic/claude-sonnet-4-6", name: "Claude Sonnet 4.6 (OR)", contextWindow: 200_000, supportsTools: true },
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{ id: "openai/gpt-4o", name: "GPT-4o (OR)", contextWindow: 128_000, supportsTools: true },
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{ id: "google/gemini-2.5-pro", name: "Gemini 2.5 Pro (OR)", contextWindow: 1_000_000, supportsTools: true },
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{ id: "deepseek/deepseek-r1", name: "DeepSeek R1 (OR)", contextWindow: 64_000, supportsTools: true },
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],
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}
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export function getLanguageModel(provider: ProviderID, modelId: string, config: SageConfig): LanguageModelV1 {
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const providerCfg = config.providers[provider] ?? {}
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switch (provider) {
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case "anthropic": {
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const apiKey = (providerCfg as { apiKey?: string }).apiKey ?? process.env.ANTHROPIC_API_KEY
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const client = createAnthropic({ apiKey })
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return client(modelId) as LanguageModelV1
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}
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case "openai": {
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const cfg = providerCfg as { apiKey?: string; baseUrl?: string }
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const apiKey = cfg.apiKey ?? process.env.OPENAI_API_KEY
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const client = createOpenAI({ apiKey, baseURL: cfg.baseUrl })
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return client(modelId) as LanguageModelV1
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}
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case "google": {
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const apiKey = (providerCfg as { apiKey?: string }).apiKey ?? process.env.GOOGLE_API_KEY
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const client = createGoogleGenerativeAI({ apiKey })
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return client(modelId) as LanguageModelV1
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}
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case "openrouter": {
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const apiKey = (providerCfg as { apiKey?: string }).apiKey ?? process.env.OPENROUTER_API_KEY
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const client = createOpenAI({
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apiKey,
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baseURL: "https://openrouter.ai/api/v1",
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headers: { "HTTP-Referer": "https://github.com/sage-ai", "X-Title": "Sage" },
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})
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return client(modelId) as LanguageModelV1
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}
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default:
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throw new Error(`Unknown provider: ${provider}`)
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}
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}
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export function listProviders(): ProviderID[] {
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return ["anthropic", "openai", "google", "openrouter"]
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}
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@@ -0,0 +1,22 @@
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import type { CoreMessage, CoreTool, StreamTextResult } from "ai"
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import type { ToolCall, ToolResult } from "@sage/core"
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export interface LLMRequest {
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messages: CoreMessage[]
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tools?: Record<string, CoreTool>
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model: string
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provider: string
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maxSteps?: number
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systemPrompt?: string
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}
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export interface LLMStreamEvent {
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type: "text-delta" | "tool-call" | "tool-result" | "finish" | "error"
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delta?: string
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toolCall?: { id: string; name: string; input: Record<string, unknown> }
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toolResult?: ToolResult
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usage?: { inputTokens: number; outputTokens: number }
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error?: Error
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}
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export type LLMEventEmitter = (event: LLMStreamEvent) => void
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@@ -0,0 +1,8 @@
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{
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"extends": "../../tsconfig.json",
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"compilerOptions": {
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"outDir": "dist",
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"rootDir": "src"
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},
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"include": ["src"]
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}
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