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<type>: <subject>
<body> <footer> 用來簡要描述影響本次變動，概述即可
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lizhixuan
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@ -3,7 +3,7 @@
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* 为不支持原生 Function Call 的模型提供 prompt 方式的工具调用
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* 内置默认逻辑，支持自定义覆盖
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*/
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import { ToolSet } from 'ai'
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import { ToolExecutionError, ToolSet } from 'ai'
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import { definePlugin } from '../index'
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import type { AiRequestContext } from '../types'
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@ -48,39 +48,11 @@ export interface MCPPromptConfig {
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parseToolUse?: (content: string, tools: ToolSet) => ToolUseResult[]
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}
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// 全局存储，解决 transformStream 中无 context 的问题
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const globalToolsStorage = new Map<string, ToolSet>()
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/**
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* 生成唯一的执行ID
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* 扩展的 AI 请求上下文，支持 MCP 工具存储
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*/
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function generateExecutionId(): string {
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return `mcp_${Date.now()}_${Math.random().toString(36).slice(2)}`
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}
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/**
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* 存储工具信息
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*/
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/**
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* 全局存储工具信息
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*/
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function storeGlobalTools(executionId: string, tools: ToolSet) {
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globalToolsStorage.set(executionId, tools)
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}
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/**
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* 获取全局存储的工具信息
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*/
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function getGlobalTools(executionId: string): ToolSet | undefined {
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return globalToolsStorage.get(executionId)
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}
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/**
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* 清理全局存储
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*/
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function clearGlobalTools(executionId: string) {
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globalToolsStorage.delete(executionId)
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interface MCPRequestContext extends AiRequestContext {
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mcpTools?: ToolSet
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}
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/**
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@ -315,30 +287,26 @@ function defaultParseToolUse(content: string, tools: ToolSet): ToolUseResult[] {
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export const createMCPPromptPlugin = definePlugin((config: MCPPromptConfig = {}) => {
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const { enabled = true, buildSystemPrompt = defaultBuildSystemPrompt, parseToolUse = defaultParseToolUse } = config
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// 为每个插件实例生成唯一ID
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const executionId = generateExecutionId()
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return {
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name: 'built-in:mcp-prompt',
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transformParams: async (params: any, context: AiRequestContext) => {
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if (!enabled || !params.tools) return params
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transformParams: async (params: any, context: MCPRequestContext) => {
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if (!enabled || !params.tools || typeof params.tools !== 'object') {
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return params
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}
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// 保存原始工具信息到 WeakMap 和全局存储中
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const tools: ToolSet = params.tools
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console.log('tools', tools)
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// storeTools(context, tools)
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storeGlobalTools(executionId, tools)
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// 直接存储工具信息到 context 上，利用改进的插件引擎
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context.mcpTools = params.tools
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console.log('tools stored in context', params.tools)
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// 构建系统提示符
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const userSystemPrompt = typeof params.system === 'string' ? params.system : ''
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const systemPrompt = await buildSystemPrompt(userSystemPrompt, tools)
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const systemPrompt = await buildSystemPrompt(userSystemPrompt, params.tools)
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// 将工具信息保存到参数中（用于后续解析）
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// 移除 tools，改为 prompt 模式
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const transformedParams = {
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...params,
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system: systemPrompt,
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// 移除 tools，改为 prompt 模式
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tools: undefined
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}
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console.log('transformedParams', transformedParams)
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@ -346,7 +314,7 @@ export const createMCPPromptPlugin = definePlugin((config: MCPPromptConfig = {})
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},
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// 流式处理：监听 step-finish 事件并处理工具调用
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transformStream: (_, context: AiRequestContext) => () => {
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transformStream: (_, context: MCPRequestContext) => () => {
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let textBuffer = ''
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let executedResults: { toolCallId: string; toolName: string; result: any; isError?: boolean }[] = []
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@ -365,10 +333,10 @@ export const createMCPPromptPlugin = definePlugin((config: MCPPromptConfig = {})
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if (chunk.type === 'step-finish' || chunk.type === 'finish') {
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console.log('[MCP Prompt Stream] Received step-finish, checking for tool use...')
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// 获取工具信息
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const tools = getGlobalTools(executionId)
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console.log('tools', tools)
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if (!tools) {
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// 从 context 获取工具信息
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const tools = context.mcpTools
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console.log('tools from context', tools)
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if (!tools || Object.keys(tools).length === 0) {
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console.log('[MCP Prompt Stream] No tools available, passing through')
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controller.enqueue(chunk)
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return
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@ -376,7 +344,6 @@ export const createMCPPromptPlugin = definePlugin((config: MCPPromptConfig = {})
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// 解析工具调用
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const parsedTools = parseToolUse(textBuffer, tools)
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// console.log('textBuffer', textBuffer)
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const validToolUses = parsedTools.filter((t) => t.status === 'pending')
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console.log('parsedTools', parsedTools)
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@ -444,19 +411,40 @@ export const createMCPPromptPlugin = definePlugin((config: MCPPromptConfig = {})
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} catch (error) {
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console.error(`[MCP Prompt Stream] Tool execution failed: ${toolUse.toolName}`, error)
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// 使用 AI SDK 标准错误格式
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const toolError = new ToolExecutionError({
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toolName: toolUse.toolName,
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toolArgs: toolUse.arguments,
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toolCallId: toolUse.id,
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message: `Tool execution failed: ${error instanceof Error ? error.message : String(error)}`,
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cause: error instanceof Error ? error : undefined
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})
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// 发送标准错误事件
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controller.enqueue({
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type: 'error',
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error: {
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message: toolError.message,
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name: toolError.name,
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toolName: toolError.toolName,
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toolCallId: toolError.toolCallId
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}
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})
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// 发送 tool-result 错误事件
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controller.enqueue({
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type: 'tool-result',
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toolCallId: toolUse.id,
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toolName: toolUse.toolName,
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args: toolUse.arguments,
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isError: true,
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result: error instanceof Error ? error.message : String(error)
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result: toolError.message
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})
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executedResults.push({
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toolCallId: toolUse.id,
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toolName: toolUse.toolName,
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result: error instanceof Error ? error.message : String(error),
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result: toolError.message,
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isError: true
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})
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}
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@ -466,7 +454,6 @@ export const createMCPPromptPlugin = definePlugin((config: MCPPromptConfig = {})
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controller.enqueue({
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type: 'step-finish',
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finishReason: 'tool-call'
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// usage: { completionTokens: 0, promptTokens: 0, totalTokens: 0 }
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})
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// 递归调用逻辑
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@ -498,11 +485,11 @@ export const createMCPPromptPlugin = definePlugin((config: MCPPromptConfig = {})
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}
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]
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// 递归调用，继续对话
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// 递归调用，继续对话，重新传递 tools
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const recursiveParams = {
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...context.originalParams,
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messages: newMessages,
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tools: tools // 重新传递 tools
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tools: tools
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}
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try {
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@ -529,22 +516,25 @@ export const createMCPPromptPlugin = definePlugin((config: MCPPromptConfig = {})
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}
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} catch (error) {
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console.error('[MCP Prompt] Recursive call failed:', error)
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// 发送错误信息后也要确保流不会中断
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// 使用 AI SDK 标准错误格式，但不中断流
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controller.enqueue({
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type: 'text-delta',
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textDelta: `\n\n[Error: Recursive call failed: ${error instanceof Error ? error.message : String(error)}]`
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type: 'error',
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error: {
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message: error instanceof Error ? error.message : String(error),
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name: error instanceof Error ? error.name : 'RecursiveCallError'
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}
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})
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// 发送一个错误后的结束信号
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// 继续发送文本增量，保持流的连续性
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controller.enqueue({
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type: 'finish',
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finishReason: 'error'
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type: 'text-delta',
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textDelta: '\n\n[工具执行后递归调用失败，继续对话...]'
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})
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}
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}
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// 清理状态
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// clearGlobalTools(executionId)
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textBuffer = ''
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executedResults = []
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return
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@ -555,116 +545,10 @@ export const createMCPPromptPlugin = definePlugin((config: MCPPromptConfig = {})
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},
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flush() {
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// 清理全局存储
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clearGlobalTools(executionId)
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// 流结束时的清理工作
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console.log('[MCP Prompt] Stream ended, cleaning up...')
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}
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})
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}
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// transformResult: async (result: any, context: AiRequestContext) => {
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// // 这个方法现在主要用于非流式场景
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// if (!enabled || !result || typeof result.text !== 'string') return result
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// console.log('[MCP Prompt] transformResult called - likely non-streaming mode')
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// // 从 WeakMap 中获取工具信息
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// const tools: ToolSet | undefined = getStoredTools(context)
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// if (!tools || typeof tools !== 'object') return result
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// // 使用工具解析函数（默认或自定义）
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// const parsedTools = parseToolUse(result.text, tools)
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// if (!parsedTools || parsedTools.length === 0) return result
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// // 过滤掉解析失败的工具调用
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// const validToolUses = parsedTools.filter((t) => t.status === 'pending')
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// if (validToolUses.length === 0) {
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// console.warn('[MCP Prompt] No valid tool uses found:', parsedTools)
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// return result
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// }
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// // 只在非流式模式下执行工具调用并递归
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// if (context.recursiveCall) {
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// console.log('[MCP Prompt] Non-streaming: Executing tools and continuing conversation...')
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// // 执行工具调用
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// const toolResults = await Promise.all(
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// validToolUses.map(async (toolUse) => {
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// try {
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// const tool = tools[toolUse.toolName]
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// if (!tool || typeof tool.execute !== 'function') {
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// throw new Error(`Tool "${toolUse.toolName}" has no execute method`)
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// }
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// console.log(`[MCP Prompt] Non-streaming: Executing tool: ${toolUse.toolName}`, toolUse.arguments)
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// const result = await tool.execute(toolUse.arguments, {
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// toolCallId: toolUse.id,
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// messages: [],
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// abortSignal: new AbortController().signal
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// })
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// return {
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// id: toolUse.id,
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// name: toolUse.toolName,
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// arguments: toolUse.arguments,
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// result,
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// success: true
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// }
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// } catch (error) {
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// console.error(`[MCP Prompt] Non-streaming: Tool execution failed: ${toolUse.toolName}`, error)
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// return {
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// id: toolUse.id,
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// name: toolUse.toolName,
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// arguments: toolUse.arguments,
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// error: error instanceof Error ? error.message : String(error),
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// success: false
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// }
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// }
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// })
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// )
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// // 构建工具结果的文本表示
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// const toolResultsText = toolResults
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// .map((tr) => {
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// if (tr.success) {
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// return `<tool_use_result>\n <name>${tr.name}</name>\n <result>${JSON.stringify(tr.result)}</result>\n</tool_use_result>`
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// } else {
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// return `<tool_use_result>\n <name>${tr.name}</name>\n <error>${tr.error}</error>\n</tool_use_result>`
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// }
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// })
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// .join('\n\n')
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// // 构建新的对话消息
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// const newMessages = [
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// ...(context.originalParams.messages || []),
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// {
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// role: 'assistant',
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// content: result.text
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// },
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// {
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// role: 'user',
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// content: toolResultsText
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// }
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// ]
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// // 递归调用，继续对话
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// const recursiveParams = {
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// ...context.originalParams,
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// messages: newMessages,
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// tools: tools // 重新传递 tools，在新的 context 中会重新存储
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// }
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// try {
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// console.log('[MCP Prompt] Non-streaming: Starting recursive call...')
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// const recursiveResult = await context.recursiveCall(recursiveParams)
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// return recursiveResult
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// } catch (error) {
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// console.error('[MCP Prompt] Non-streaming: Recursive call failed:', error)
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// return result
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// }
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// }
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// return result
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// }
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}
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})
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@ -63,15 +63,16 @@ export class PluginEngine<T extends ProviderId = ProviderId> {
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methodName: string,
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modelId: string,
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params: TParams,
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executor: (finalModelId: string, transformedParams: TParams) => Promise<TResult>
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executor: (finalModelId: string, transformedParams: TParams) => Promise<TResult>,
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_context?: ReturnType<typeof createContext>
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): Promise<TResult> {
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// 使用正确的createContext创建请求上下文
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const context = createContext(this.providerId, modelId, params)
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const context = _context ? _context : createContext(this.providerId, modelId, params)
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// 🔥 为上下文添加递归调用能力
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context.recursiveCall = (newParams: any): Promise<TResult> => {
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// 递归调用自身，重新走完整的插件流程
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return this.executeWithPlugins(methodName, modelId, newParams, executor)
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return this.executeWithPlugins(methodName, modelId, newParams, executor, context)
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}
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try {
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