weichen
0d74ec94dd
Details (original message): Implement the backend: store/bus/runmgr core, mock and LLM runners (agent-native client), HITL three-branch routing, subagent runs, builtin and declarative HTTP tools, ingest parsers (md/txt/docx/pdf-text), knowledge fulltext, layered settings, profiles, plugin host, REST+SSE API, single-binary entrypoint; e2e and unit tests.
301 lines
11 KiB
Go
301 lines
11 KiB
Go
package runtime
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import (
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"encoding/json"
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"fmt"
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"strings"
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agentllm "agent-native/runtime/llm"
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core "agent-system-core"
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"agent-system-backend/internal/ctxasm"
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)
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// LLMRunner 主对话执行器：复用 agent-native 的 OpenAI 兼容流式客户端（不自研接入层）。
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// 多轮循环：流式 → 工具调用（画像策略）→ 回灌结果 → 直至无工具调用或预算耗尽。
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// 内置三个编排型工具（不经注册表）：delegate_task（子代理）、update_plan、update_todos。
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type LLMRunner struct{}
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func (l *LLMRunner) Name() string { return "llm" }
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const (
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toolDelegate = "delegate_task"
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toolPlan = "update_plan"
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toolTodos = "update_todos"
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)
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func (l *LLMRunner) Execute(rc RunCtx) error {
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eff := rc.Settings()
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chat := eff.GetString("models.chat.model", "")
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base := eff.GetString("models.chat.baseUrl", "")
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key := eff.GetString("models.chat.apiKey", "")
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if chat == "" || base == "" {
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return fmt.Errorf("llm: 主模型未配置（settings: models.chat.baseUrl / models.chat.model；演示模式可开 runtime.mock）")
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}
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client := &agentllm.Client{BaseURL: base, APIKey: key}
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prof := rc.Profile()
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// 知识注入：当前消息包含 @knowledge 引用时检索注入（最小实现：显式引用）。
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var knowledge []core.RetrievalHit
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if strings.Contains(currentUserText(rc), "@knowledge") {
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q := strings.TrimSpace(strings.ReplaceAll(currentUserText(rc), "@knowledge", ""))
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if hits, err := rc.Retrieve(core.RetrievalQuery{Text: q}); err == nil {
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knowledge = hits
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}
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}
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// 组装初始上下文。
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hist := rc.History()
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var currentUser core.Message
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for i := len(hist) - 1; i >= 0; i-- {
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if hist[i].Role == core.RoleUser {
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currentUser = hist[i]
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break
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}
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}
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msgs, _ := ctxasm.AssembleInput(prof, eff, hist, currentUser, rc.Attachments(), knowledge)
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// 声明工具：编排型内置 + 注册表中画像允许的工具。
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decls := []agentllm.ToolDecl{
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{Name: toolDelegate, Description: "派生一个子代理执行独立子任务（如检索、撰写），返回其结果摘要", Parameters: json.RawMessage(`{"type":"object","properties":{"name":{"type":"string","description":"子代理角色名"},"task":{"type":"string","description":"子任务描述"},"hint":{"type":"string","description":"执行提示"}},"required":["name","task"]}`)},
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{Name: toolPlan, Description: "创建或更新当前会话的计划（步骤列表）", Parameters: json.RawMessage(`{"type":"object","properties":{"title":{"type":"string"},"steps":{"type":"array","items":{"type":"object","properties":{"id":{"type":"string"},"text":{"type":"string"},"status":{"type":"string","enum":["pending","in_progress","done","skipped"]}},"required":["id","text","status"]}}},"required":["title","steps"]}`)},
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{Name: toolTodos, Description: "更新当前会话的待办清单", Parameters: json.RawMessage(`{"type":"object","properties":{"items":{"type":"array","items":{"type":"object","properties":{"id":{"type":"string"},"text":{"type":"string"},"status":{"type":"string","enum":["pending","in_progress","done"]}},"required":["id","text","status"]}}},"required":["items"]}`)},
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}
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var toolDescs []core.ToolDesc
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for _, t := range toolList(rc) {
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if prof.Tools.ToolAllowed(t.Name) {
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toolDescs = append(toolDescs, t)
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decls = append(decls, agentllm.ToolDecl{Name: t.Name, Description: t.Description, Parameters: t.Parameters})
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}
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}
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var finalParts []core.Part
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usageTotal := core.Usage{}
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maxTurns := 16
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if prof.Budget.MaxTurns != nil {
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maxTurns = *prof.Budget.MaxTurns
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}
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maxTools := 40
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if prof.Budget.MaxToolCalls != nil {
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maxTools = *prof.Budget.MaxToolCalls
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}
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toolCallsMade := 0
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thinkingIdx, textIdx := 0, 0
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for turn := 0; turn < maxTurns; turn++ {
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select {
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case <-rc.Context().Done():
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return rc.Context().Err()
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default:
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}
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var turnThinking, turnText strings.Builder
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var calls []agentllm.ToolCall
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var usage agentllm.Usage
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ev := client.Stream(rc.Context(), chat, msgs, decls, agentllm.StreamOptions{})
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phaseEmitted := false
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for e := range ev {
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switch e.Kind {
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case agentllm.KindTextDelta:
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if !phaseEmitted {
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rc.Emit(core.EvRunPhase, core.RunPhasePayload{Phase: core.PhaseResponding})
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phaseEmitted = true
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}
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turnText.WriteString(e.Text)
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rc.Emit(core.EvMessageDelta, core.MessageDeltaPayload{Index: textIdx, Text: e.Text})
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case agentllm.KindReasoningDelta:
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turnThinking.WriteString(e.ReasoningDelta)
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rc.Emit(core.EvThinkingDelta, core.ThinkingDeltaPayload{Index: thinkingIdx, Text: e.ReasoningDelta})
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case agentllm.KindToolCallDelta:
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// 累积由 message_end 的 ToolCalls 提供；此处忽略增量。
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case agentllm.KindMessageEnd:
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calls = e.Message.ToolCalls
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usage = e.Usage
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case agentllm.KindError:
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return fmt.Errorf("llm stream: %s (retryable=%v)", e.ErrorMessage, e.Retryable)
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}
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}
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usageTotal.PromptTokens += usage.PromptTokens
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usageTotal.CompletionTokens += usage.CompletionTokens
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usageTotal.TotalTokens += usage.TotalTokens
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// 记录本轮部件。
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if turnThinking.Len() > 0 {
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finalParts = append(finalParts, core.Part{Type: core.PartThinking, Text: turnThinking.String(), Process: true})
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thinkingIdx++
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}
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if turnText.Len() > 0 {
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finalParts = append(finalParts, core.Part{Type: core.PartText, Text: turnText.String()})
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textIdx++
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}
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if len(calls) == 0 {
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// 终轮：无工具调用。
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if len(finalParts) == 0 {
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finalParts = append(finalParts, core.Part{Type: core.PartText, Text: "（模型未返回内容）"})
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}
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rc.SetAssistantParts(finalParts)
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return nil
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}
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// 工具轮。
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rc.Emit(core.EvRunPhase, core.RunPhasePayload{Phase: core.PhaseActing})
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msgs = append(msgs, agentllm.Message{Role: agentllm.RoleAssistant, Content: turnText.String(), ToolCalls: calls, StopReason: agentllm.StopToolCalls})
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for _, call := range calls {
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toolCallsMade++
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if toolCallsMade > maxTools {
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return fmt.Errorf("budget: 工具调用超过上限 %d（profile.budget.maxToolCalls）", maxTools)
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}
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rc.Emit(core.EvToolCall, core.ToolCallPayload{CallID: call.ID, Name: call.Name, Arguments: call.Arguments})
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var out string
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var err error
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var artifactRef *core.ArtifactRef
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switch call.Name {
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case toolDelegate:
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var a struct{ Name, Task, Hint string }
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json.Unmarshal([]byte(call.Arguments), &a)
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res, serr := rc.SpawnSubagent(orDefault(a.Name, "子代理"), a.Task, a.Hint)
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if serr != nil {
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out = "子代理失败：" + serr.Error()
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} else {
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out = orDefault(res.Summary, "子代理完成")
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}
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case toolPlan:
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var p core.PlanSnapshot
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if err := json.Unmarshal([]byte(call.Arguments), &p); err == nil {
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rc.UpdatePlan(p)
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out = "计划已更新"
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} else {
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out = "计划参数错误: " + err.Error()
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}
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case toolTodos:
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var t core.TodoList
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if err := json.Unmarshal([]byte(call.Arguments), &t); err == nil {
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rc.UpdateTodos(t)
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out = "待办已更新"
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} else {
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out = "待办参数错误: " + err.Error()
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}
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default:
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res := rc.ExecuteTool(core.ToolCallRequest{CallID: call.ID, Name: call.Name, Arguments: json.RawMessage(call.Arguments)})
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if res.Status != "ok" {
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err = fmt.Errorf("%s", res.Output)
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} else {
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out = res.Output
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}
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if res.Artifact != nil {
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artifactRef = &core.ArtifactRef{ArtifactID: res.Artifact.ID, Name: res.Artifact.Name, Kind: res.Artifact.Kind}
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}
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rc.Emit(core.EvToolResult, core.ToolResultPayload{CallID: call.ID, Status: res.Status, Summary: summarize(out, err), Truncated: res.Truncated})
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}
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if call.Name == toolDelegate || call.Name == toolPlan || call.Name == toolTodos {
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rc.Emit(core.EvToolResult, core.ToolResultPayload{CallID: call.ID, Status: "ok", Summary: summarize(out, err)})
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}
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summary := ""
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if err != nil {
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summary = "error: " + err.Error()
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out = summary
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}
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finalParts = append(finalParts,
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core.Part{Type: core.PartToolCall, Process: true, ToolCall: &core.ToolCallPart{ID: call.ID, Name: call.Name, Arguments: call.Arguments}},
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core.Part{Type: core.PartToolResult, Process: true, ToolResult: &core.ToolResultPart{CallID: call.ID, Status: statusOf(err), Summary: summary}},
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)
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if artifactRef != nil {
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finalParts = append(finalParts, core.Part{Type: core.PartArtifactRef, Artifact: artifactRef})
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}
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// 回灌工具结果（截断保护）。
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if len(out) > 16000 {
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out = out[:16000] + "…（超长截断）"
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}
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msgs = append(msgs, agentllm.Message{Role: agentllm.RoleTool, ToolCallID: call.ID, Name: call.Name, Content: out, IsError: err != nil})
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}
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}
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return fmt.Errorf("budget: 轮次超过上限 %d（profile.budget.maxTurns）", maxTurns)
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}
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// SubLLMRunner 子代理执行器：轻量模型单轮完成任务并返回摘要。
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type SubLLMRunner struct{}
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func (l *SubLLMRunner) Name() string { return "llm-subagent" }
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func (l *SubLLMRunner) Execute(rc RunCtx) error {
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eff := rc.Settings()
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model := eff.GetString("models.lightweight.model", "")
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base := eff.GetString("models.lightweight.baseUrl", "")
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key := eff.GetString("models.lightweight.apiKey", "")
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if model == "" || base == "" {
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model = eff.GetString("models.chat.model", "")
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base = eff.GetString("models.chat.baseUrl", "")
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key = eff.GetString("models.chat.apiKey", "")
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}
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if model == "" || base == "" {
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return fmt.Errorf("llm-subagent: 模型未配置")
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}
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rc.Emit(core.EvAgentProgress, core.AgentProgressPayload{AgentRun: rc.Run().ID, Note: "执行子任务……", Phase: core.PhaseActing})
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client := &agentllm.Client{BaseURL: base, APIKey: key}
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msgs := []agentllm.Message{
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{Role: agentllm.RoleSystem, Content: "你是被派生的子代理。独立完成给定子任务，输出简明结果摘要（不超过 300 字）。"},
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{Role: agentllm.RoleUser, Content: rc.Subtask()},
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}
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var sb strings.Builder
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for e := range client.Stream(rc.Context(), model, msgs, nil, agentllm.StreamOptions{}) {
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if e.Kind == agentllm.KindTextDelta {
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sb.WriteString(e.Text)
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rc.Emit(core.EvAgentProgress, core.AgentProgressPayload{AgentRun: rc.Run().ID, Note: truncateRun(sb.String(), 80)})
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}
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if e.Kind == agentllm.KindError {
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return fmt.Errorf("subagent stream: %s", e.ErrorMessage)
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}
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}
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rc.SetAssistantParts([]core.Part{{Type: core.PartText, Text: sb.String()}})
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return nil
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}
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func currentUserText(rc RunCtx) string {
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hist := rc.History()
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for i := len(hist) - 1; i >= 0; i-- {
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if hist[i].Role == core.RoleUser {
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for _, p := range hist[i].Parts {
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if p.Type == core.PartText {
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return p.Text
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}
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}
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}
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}
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return ""
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}
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func toolList(rc RunCtx) []core.ToolDesc { return rc.Tools() }
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func orDefault(s, def string) string {
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if strings.TrimSpace(s) == "" {
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return def
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}
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return s
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}
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func summarize(out string, err error) string {
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if err != nil {
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return truncateRun(err.Error(), 160)
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}
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return truncateRun(out, 160)
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}
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func statusOf(err error) string {
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if err != nil {
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return "error"
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}
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return "ok"
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}
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func truncateRun(s string, n int) string {
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r := []rune(s)
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if len(r) <= n {
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return s
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}
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return string(r[:n]) + "…"
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}
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