zhuyongxin
f75d0c49ae
将 ReAct 循环从单阶段升级为 Thinking + Action 双阶段架构： - Phase 1：剥夺工具访问权，强制模型先输出纯文本推理规划 - Phase 2：恢复工具挂载，模型按推理结果精准执行 - 新增 EnableThinking 开关，兼容旧模式
128 lines
4.7 KiB
Go
128 lines
4.7 KiB
Go
package engine
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import (
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"context"
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"fmt"
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"log"
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"go-tiny-claw/internal/provider"
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"go-tiny-claw/internal/schema"
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"go-tiny-claw/internal/tools"
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)
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// AgentEngine 是微型 OS 的核心驱动
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type AgentEngine struct {
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provider provider.LLMProvider
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registry tools.Registry
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// WorkDir (工作区): 借鉴 OpenClaw 的理念，Agent 必须有一个明确的物理边界
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WorkDir string
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EnableThinking bool // 【新增】慢思考模式开关
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}
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func NewAgentEngine(p provider.LLMProvider, r tools.Registry, workDir string, enableThinking bool) *AgentEngine {
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return &AgentEngine{
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provider: p,
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registry: r,
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WorkDir: workDir,
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EnableThinking: enableThinking,
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}
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}
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// internal/engine/loop.go (续)
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func (e *AgentEngine) Run(ctx context.Context, userPrompt string) error {
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log.Printf("[Engine] 引擎启动，锁定工作区: %s\n", e.WorkDir)
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log.Printf("[Engine] 慢思考模式 (Thinking Phase): %v\n", e.EnableThinking)
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contextHistory := []schema.Message{
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{
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Role: schema.RoleSystem,
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Content: "You are go-tiny-claw, an expert coding assistant. You have full access to tools in the workspace.",
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},
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{
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Role: schema.RoleUser,
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Content: userPrompt,
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},
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}
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turnCount := 0
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for {
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turnCount++
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log.Printf("\n========== [Turn %d] 开始 ==========\n", turnCount)
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// 获取当前挂载的所有工具定义
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availableTools := e.registry.GetAvailableTools()
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// ====================================================================
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// Phase 1: 慢思考阶段 (Thinking) - 剥夺工具，强制规划
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// ====================================================================
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if e.EnableThinking {
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log.Println("[Engine][Phase 1] 剥夺工具访问权，强制进入慢思考与规划阶段...")
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// 核心机制：传入的 availableTools 为 nil！
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// 大模型看不到任何 JSON Schema，被迫只能输出纯文本的思考过程。
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thinkResp, err := e.provider.Generate(ctx, contextHistory, nil)
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if err != nil {
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return fmt.Errorf("Thinking 阶段生成失败: %w", err)
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}
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// 如果模型输出了思考过程，我们将其作为 Assistant 消息追加到上下文中
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if thinkResp.Content != "" {
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fmt.Printf("🧠 [内部思考 Trace]: %s\n", thinkResp.Content)
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contextHistory = append(contextHistory, *thinkResp)
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}
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}
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// ====================================================================
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// Phase 2: 行动阶段 (Action) - 恢复工具，顺着规划执行
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// ====================================================================
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log.Println("[Engine][Phase 2] 恢复工具挂载，等待模型采取行动...")
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// 此时的 contextHistory 中已经包含了上一阶段模型自己的 Thinking Trace。
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// 模型会顺着自己的逻辑，结合恢复的 availableTools 发起精准的工具调用。
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actionResp, err := e.provider.Generate(ctx, contextHistory, availableTools)
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if err != nil {
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return fmt.Errorf("Action 阶段生成失败: %w", err)
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}
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contextHistory = append(contextHistory, *actionResp)
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if actionResp.Content != "" {
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fmt.Printf("🤖 [对外回复]: %s\n", actionResp.Content)
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}
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// ====================================================================
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// 退出与执行逻辑 (与上一讲保持一致)
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// ====================================================================
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if len(actionResp.ToolCalls) == 0 {
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log.Println("[Engine] 模型未请求调用工具，任务宣告完成。")
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break
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}
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log.Printf("[Engine] 模型请求调用 %d 个工具...\n", len(actionResp.ToolCalls))
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for _, toolCall := range actionResp.ToolCalls {
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log.Printf(" -> 🛠️ 执行工具: %s, 参数: %s\n", toolCall.Name, string(toolCall.Arguments))
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result := e.registry.Execute(ctx, toolCall)
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if result.IsError {
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log.Printf(" -> ❌ 工具执行报错: %s\n", result.Output)
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} else {
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log.Printf(" -> ✅ 工具执行成功 (返回 %d 字节)\n", len(result.Output))
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}
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// 将工具执行的观察结果追加到 Context，准备进入下一轮
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observationMsg := schema.Message{
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Role: schema.RoleUser,
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Content: result.Output,
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ToolCallID: toolCall.ID,
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}
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contextHistory = append(contextHistory, observationMsg)
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}
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}
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return nil
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}
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