579 lines
17 KiB
Go
579 lines
17 KiB
Go
package agent
|
||
|
||
import (
|
||
"context"
|
||
"encoding/json"
|
||
"fmt"
|
||
"sort"
|
||
"strconv"
|
||
"strings"
|
||
"sync"
|
||
"time"
|
||
|
||
"laodingbot/internal/knowledge"
|
||
"laodingbot/internal/llm"
|
||
"laodingbot/internal/logger"
|
||
"laodingbot/internal/memory"
|
||
"laodingbot/internal/tools"
|
||
)
|
||
|
||
type Orchestrator struct {
|
||
llm llm.Client
|
||
store *memory.SQLiteStore
|
||
tools *tools.Registry
|
||
soul string
|
||
skills []knowledge.Skill
|
||
skillsDir string
|
||
autoSkillDir string
|
||
gapDraftTriggerCount int
|
||
gapLookbackDuration time.Duration
|
||
reactMaxStep int
|
||
enableCapabilityGap bool
|
||
log *logger.Logger
|
||
skillsMu sync.RWMutex
|
||
}
|
||
|
||
func NewOrchestrator(
|
||
llmClient llm.Client,
|
||
store *memory.SQLiteStore,
|
||
registry *tools.Registry,
|
||
soul string,
|
||
skills []knowledge.Skill,
|
||
skillsDir string,
|
||
reactMaxStep int,
|
||
enableCapabilityGap bool,
|
||
autoSkillDir string,
|
||
gapDraftTriggerCount int,
|
||
gapLookbackDuration time.Duration,
|
||
log *logger.Logger,
|
||
) *Orchestrator {
|
||
if reactMaxStep <= 0 {
|
||
reactMaxStep = 4
|
||
}
|
||
if gapDraftTriggerCount <= 0 {
|
||
gapDraftTriggerCount = 3
|
||
}
|
||
if gapLookbackDuration <= 0 {
|
||
gapLookbackDuration = 7 * 24 * time.Hour
|
||
}
|
||
if strings.TrimSpace(autoSkillDir) == "" {
|
||
autoSkillDir = skillsDir
|
||
}
|
||
return &Orchestrator{
|
||
llm: llmClient,
|
||
store: store,
|
||
tools: registry,
|
||
soul: soul,
|
||
skills: skills,
|
||
skillsDir: skillsDir,
|
||
autoSkillDir: autoSkillDir,
|
||
gapDraftTriggerCount: gapDraftTriggerCount,
|
||
gapLookbackDuration: gapLookbackDuration,
|
||
reactMaxStep: reactMaxStep,
|
||
enableCapabilityGap: enableCapabilityGap,
|
||
log: log,
|
||
}
|
||
}
|
||
|
||
func (o *Orchestrator) HandleMessage(ctx context.Context, chatID, userID, text string) (string, error) {
|
||
traceID := logger.NewTraceID()
|
||
ctx = logger.WithTraceID(ctx, traceID)
|
||
traceLogPrefix := "trace_id=" + traceID
|
||
if o.log != nil {
|
||
o.log.Infof("%s handle message chat_id=%s user_id=%s text_len=%d", traceLogPrefix, chatID, userID, len(text))
|
||
o.log.Debugf("%s handle message text=%q", traceLogPrefix, text)
|
||
}
|
||
if strings.EqualFold(strings.TrimSpace(text), "/reload_skills") {
|
||
if err := o.ReloadSkills(); err != nil {
|
||
return "技能热加载失败: " + err.Error(), nil
|
||
}
|
||
return "技能已热加载完成。", nil
|
||
}
|
||
if strings.EqualFold(strings.TrimSpace(text), "/capability_gaps") {
|
||
report, err := o.BuildCapabilityGapReport(10)
|
||
if err != nil {
|
||
return "缺口报告生成失败: " + err.Error(), nil
|
||
}
|
||
return report, nil
|
||
}
|
||
if err := o.store.SaveMessage(chatID, userID, "user", text); err != nil {
|
||
if o.log != nil {
|
||
o.log.Errorf("%s save user message failed chat_id=%s err=%v", traceLogPrefix, chatID, err)
|
||
}
|
||
return "", err
|
||
}
|
||
|
||
recent, err := o.store.LoadRecent(chatID, 16)
|
||
if err != nil {
|
||
if o.log != nil {
|
||
o.log.Errorf("%s load recent failed chat_id=%s err=%v", traceLogPrefix, chatID, err)
|
||
}
|
||
return "", err
|
||
}
|
||
compressed := memory.CompressForPrompt(recent, 6000)
|
||
if o.log != nil {
|
||
o.log.Debugf("%s prompt context prepared chat_id=%s recent_count=%d compressed_len=%d", traceLogPrefix, chatID, len(recent), len(compressed))
|
||
}
|
||
|
||
matchedSkills := o.matchSkills(ctx, compressed, text)
|
||
if len(matchedSkills) == 0 {
|
||
if bootstrap, ok := o.findSkillByKeyword("创建skill", "skill builder", "skill 创建", "构建技能"); ok {
|
||
matchedSkills = []knowledge.Skill{bootstrap}
|
||
if o.log != nil {
|
||
o.log.Infof("%s fallback bootstrap skill selected name=%s", traceLogPrefix, bootstrap.Name)
|
||
}
|
||
}
|
||
}
|
||
|
||
var response string
|
||
if len(matchedSkills) == 0 {
|
||
if o.log != nil {
|
||
o.log.Infof("%s no skill matched; use direct llm chat_id=%s", traceLogPrefix, chatID)
|
||
}
|
||
o.emitCapabilityGap(chatID, userID, text, "no_skill_matched")
|
||
response, err = o.runDirectLLM(ctx, compressed, text)
|
||
} else {
|
||
if o.log != nil {
|
||
names := make([]string, 0, len(matchedSkills))
|
||
for _, s := range matchedSkills {
|
||
names = append(names, s.Name)
|
||
o.log.Infof("%s skill selected name=%s source=%s", traceLogPrefix, s.Name, s.Source)
|
||
o.log.Debugf("%s skill selected content name=%s content=%q", traceLogPrefix, s.Name, s.Content)
|
||
}
|
||
o.log.Infof("%s skills matched chat_id=%s skills=%s", traceLogPrefix, chatID, strings.Join(names, ","))
|
||
}
|
||
response, err = o.runReAct(ctx, chatID, userID, compressed, text, matchedSkills)
|
||
}
|
||
if err != nil {
|
||
if o.log != nil {
|
||
o.log.Errorf("%s message generation failed chat_id=%s err=%v", traceLogPrefix, chatID, err)
|
||
}
|
||
return "", err
|
||
}
|
||
|
||
if err := o.store.SaveMessage(chatID, userID, "assistant", response); err != nil {
|
||
if o.log != nil {
|
||
o.log.Errorf("%s save assistant response failed chat_id=%s err=%v", traceLogPrefix, chatID, err)
|
||
}
|
||
return "", err
|
||
}
|
||
if o.log != nil {
|
||
o.log.Infof("%s message handled chat_id=%s response_len=%d", traceLogPrefix, chatID, len(response))
|
||
}
|
||
return response, nil
|
||
}
|
||
|
||
func (o *Orchestrator) runDirectLLM(ctx context.Context, compressedContext, userInput string) (string, error) {
|
||
systemPrompt := strings.Join([]string{
|
||
"你是一个个人自动化助手,必须遵循如下人格设定并保持一致:",
|
||
o.soul,
|
||
"",
|
||
"如果当前问题没有匹配到已定义技能,请直接回答用户。",
|
||
"当你判断必须依赖外部工具结果才能可靠回答时,请明确告知用户需要进一步操作信息。",
|
||
}, "\n")
|
||
|
||
userPrompt := strings.Join([]string{
|
||
"历史上下文:",
|
||
compressedContext,
|
||
"",
|
||
"用户问题:",
|
||
userInput,
|
||
}, "\n")
|
||
|
||
return o.llm.Generate(ctx, systemPrompt, userPrompt)
|
||
}
|
||
|
||
type reactDecision struct {
|
||
Thought string `json:"thought"`
|
||
Action string `json:"action"`
|
||
ActionInput string `json:"action_input"`
|
||
Final string `json:"final"`
|
||
}
|
||
|
||
func (o *Orchestrator) runReAct(ctx context.Context, chatID, userID, compressedContext, userInput string, selectedSkills []knowledge.Skill) (string, error) {
|
||
traceID := logger.TraceIDFromContext(ctx)
|
||
traceLogPrefix := "trace_id=" + traceID
|
||
selectedSkillsDoc := formatSkills(selectedSkills)
|
||
toolDoc := o.formatToolDoc()
|
||
if o.log != nil {
|
||
names := make([]string, 0, len(selectedSkills))
|
||
for _, s := range selectedSkills {
|
||
names = append(names, s.Name)
|
||
}
|
||
o.log.Infof("%s react start steps=%d skills=%s", traceLogPrefix, o.reactMaxStep, strings.Join(names, ","))
|
||
o.log.Debugf("%s react selected_skills_doc=%q", traceLogPrefix, selectedSkillsDoc)
|
||
o.log.Debugf("%s react tools_doc=%q", traceLogPrefix, toolDoc)
|
||
}
|
||
|
||
systemPrompt := strings.Join([]string{
|
||
"你是一个个人自动化助手,必须遵循如下人格设定并保持一致:",
|
||
o.soul,
|
||
"",
|
||
"已匹配到的 skills(只可按下列技能执行):",
|
||
selectedSkillsDoc,
|
||
"",
|
||
"可用工具:",
|
||
toolDoc,
|
||
"",
|
||
"你必须使用 ReAct 模式做决策。",
|
||
"只有当技能明确需要工具能力时才调用工具。",
|
||
"如果问题可直接回答,不要调用工具。",
|
||
"你的输出必须是 JSON,对象字段为 thought, action, action_input, final。",
|
||
"规则:",
|
||
"1) 当需要调工具时:final 置空,action 必须是可用工具之一,action_input 为工具输入。",
|
||
"2) 当可以最终回答时:action 置 none,action_input 置空,final 填最终回复。",
|
||
"3) 不要输出 JSON 之外内容。",
|
||
}, "\n")
|
||
|
||
scratchpad := ""
|
||
for step := 1; step <= o.reactMaxStep; step++ {
|
||
if o.log != nil {
|
||
o.log.Infof("%s react step start step=%d/%d", traceLogPrefix, step, o.reactMaxStep)
|
||
o.log.Debugf("%s react scratchpad_before step=%d content=%q", traceLogPrefix, step, scratchpad)
|
||
}
|
||
prompt := strings.Join([]string{
|
||
"历史上下文:",
|
||
compressedContext,
|
||
"",
|
||
"用户问题:",
|
||
userInput,
|
||
"",
|
||
"当前推理记录(按时间顺序):",
|
||
scratchpad,
|
||
"",
|
||
fmt.Sprintf("请输出下一步 JSON 决策。当前步骤: %d/%d", step, o.reactMaxStep),
|
||
}, "\n")
|
||
|
||
raw, err := o.llm.Generate(ctx, systemPrompt, prompt)
|
||
if err != nil {
|
||
return "", err
|
||
}
|
||
if o.log != nil {
|
||
o.log.Infof("%s react step llm output step=%d raw=%q", traceLogPrefix, step, raw)
|
||
}
|
||
decision, err := parseDecision(raw)
|
||
if err != nil {
|
||
if o.log != nil {
|
||
o.log.Warnf("%s react parse failed, fallback to direct llm err=%v", traceLogPrefix, err)
|
||
}
|
||
o.emitCapabilityGap(chatID, userID, userInput, "react_parse_failed")
|
||
return o.runDirectLLM(ctx, compressedContext, userInput)
|
||
}
|
||
if o.log != nil {
|
||
o.log.Infof("%s react step decision step=%d thought=%q action=%q action_input=%q final=%q", traceLogPrefix, step, decision.Thought, decision.Action, decision.ActionInput, decision.Final)
|
||
}
|
||
|
||
action := strings.ToLower(strings.TrimSpace(decision.Action))
|
||
if action == "" {
|
||
action = "none"
|
||
}
|
||
|
||
if action == "none" {
|
||
finalText := strings.TrimSpace(decision.Final)
|
||
if finalText == "" {
|
||
finalText = "我已完成思考,但当前没有足够信息给出稳定结论。"
|
||
}
|
||
if o.log != nil {
|
||
o.log.Infof("%s react final step=%d final=%q", traceLogPrefix, step, finalText)
|
||
}
|
||
return finalText, nil
|
||
}
|
||
|
||
tool, ok := o.tools.Get(action)
|
||
if !ok {
|
||
if o.log != nil {
|
||
o.log.Warnf("%s react step tool missing step=%d tool=%s", traceLogPrefix, step, action)
|
||
}
|
||
scratchpad += "Step " + strconv.Itoa(step) + " Thought: " + decision.Thought + "\n"
|
||
scratchpad += "Step " + strconv.Itoa(step) + " Observation: " + formatToolErrorObservation("TOOL_NOT_FOUND", action, "tool not found") + "\n"
|
||
o.emitCapabilityGap(chatID, userID, userInput, "tool_not_found:"+action)
|
||
continue
|
||
}
|
||
|
||
toolOut, toolErr := tool.Call(ctx, decision.ActionInput)
|
||
if o.log != nil {
|
||
o.log.Infof("%s react step tool call step=%d tool=%s input=%q", traceLogPrefix, step, action, decision.ActionInput)
|
||
}
|
||
obs := strings.TrimSpace(toolOut)
|
||
if obs == "" {
|
||
obs = "(empty output)"
|
||
}
|
||
if toolErr != nil {
|
||
obs = formatToolErrorObservation("TOOL_EXEC_ERROR", action, toolErr.Error()) + "\nOUTPUT:\n" + obs
|
||
o.emitCapabilityGap(chatID, userID, userInput, "tool_call_failed:"+action)
|
||
}
|
||
if o.log != nil {
|
||
o.log.Infof("%s react step observation step=%d tool=%s observation=%q", traceLogPrefix, step, action, obs)
|
||
}
|
||
if len(obs) > 2000 {
|
||
obs = obs[:2000]
|
||
}
|
||
scratchpad += "Step " + strconv.Itoa(step) + " Thought: " + decision.Thought + "\n"
|
||
scratchpad += "Step " + strconv.Itoa(step) + " Action: " + action + "\n"
|
||
scratchpad += "Step " + strconv.Itoa(step) + " ActionInput: " + decision.ActionInput + "\n"
|
||
scratchpad += "Step " + strconv.Itoa(step) + " Observation: " + obs + "\n"
|
||
}
|
||
|
||
o.emitCapabilityGap(chatID, userID, userInput, "react_step_exhausted")
|
||
return "我尝试了多轮思考与工具调用,但仍未得到稳定结论。请给我更具体的约束或允许我继续尝试。", nil
|
||
}
|
||
|
||
func (o *Orchestrator) matchSkills(ctx context.Context, compressedContext, userInput string) []knowledge.Skill {
|
||
skills := o.getSkillsSnapshot()
|
||
if len(skills) == 0 {
|
||
return nil
|
||
}
|
||
|
||
type skillChoice struct {
|
||
Skills []string `json:"skills"`
|
||
}
|
||
|
||
systemPrompt := strings.Join([]string{
|
||
"你是技能路由器。",
|
||
"任务:根据用户问题,从候选技能中选择 0-2 个最相关技能名称。",
|
||
"输出必须是 JSON:{\"skills\":[\"name1\",\"name2\"]}",
|
||
"如果没有匹配技能,返回 {\"skills\":[]}。",
|
||
"不要输出 JSON 之外内容。",
|
||
}, "\n")
|
||
|
||
userPrompt := strings.Join([]string{
|
||
"候选技能:",
|
||
formatSkillCatalog(skills),
|
||
"",
|
||
"历史上下文:",
|
||
compressedContext,
|
||
"",
|
||
"用户问题:",
|
||
userInput,
|
||
}, "\n")
|
||
|
||
raw, err := o.llm.Generate(ctx, systemPrompt, userPrompt)
|
||
if err != nil {
|
||
if o.log != nil {
|
||
o.log.Warnf("skill match llm failed err=%v", err)
|
||
}
|
||
return nil
|
||
}
|
||
if o.log != nil {
|
||
o.log.Infof("skill router output raw=%q", raw)
|
||
}
|
||
|
||
raw = normalizeJSON(raw)
|
||
choice := skillChoice{}
|
||
if err := json.Unmarshal([]byte(raw), &choice); err != nil {
|
||
if o.log != nil {
|
||
o.log.Warnf("skill match parse failed err=%v", err)
|
||
}
|
||
return nil
|
||
}
|
||
|
||
picked := make([]knowledge.Skill, 0, 2)
|
||
seen := map[string]struct{}{}
|
||
for _, name := range choice.Skills {
|
||
name = strings.TrimSpace(strings.ToLower(name))
|
||
if name == "" {
|
||
continue
|
||
}
|
||
if _, ok := seen[name]; ok {
|
||
continue
|
||
}
|
||
for _, skill := range skills {
|
||
if strings.ToLower(strings.TrimSpace(skill.Name)) == name {
|
||
picked = append(picked, skill)
|
||
seen[name] = struct{}{}
|
||
break
|
||
}
|
||
}
|
||
if len(picked) >= 2 {
|
||
break
|
||
}
|
||
}
|
||
if o.log != nil {
|
||
names := make([]string, 0, len(picked))
|
||
for _, s := range picked {
|
||
names = append(names, s.Name)
|
||
}
|
||
o.log.Infof("skill router selected skills=%s", strings.Join(names, ","))
|
||
}
|
||
|
||
return picked
|
||
}
|
||
|
||
func (o *Orchestrator) emitCapabilityGap(chatID, userID, intent, reason string) {
|
||
if !o.enableCapabilityGap {
|
||
return
|
||
}
|
||
intent = strings.TrimSpace(intent)
|
||
reason = strings.TrimSpace(reason)
|
||
if intent == "" || reason == "" {
|
||
return
|
||
}
|
||
if len(intent) > 1000 {
|
||
intent = intent[:1000]
|
||
}
|
||
if len(reason) > 240 {
|
||
reason = reason[:240]
|
||
}
|
||
if err := o.store.SaveCapabilityGap(chatID, userID, intent, reason); err != nil && o.log != nil {
|
||
o.log.Warnf("save capability gap failed chat_id=%s user_id=%s err=%v", chatID, userID, err)
|
||
return
|
||
}
|
||
|
||
clusters, err := o.store.TopCapabilityGapClusters(20, time.Now().UTC().Add(-o.gapLookbackDuration))
|
||
if err != nil {
|
||
if o.log != nil {
|
||
o.log.Warnf("query capability gap clusters failed err=%v", err)
|
||
}
|
||
return
|
||
}
|
||
for _, c := range clusters {
|
||
if c.Count < o.gapDraftTriggerCount {
|
||
continue
|
||
}
|
||
path, created, draftErr := knowledge.GenerateSkillDraft(c, o.autoSkillDir)
|
||
if draftErr != nil {
|
||
if o.log != nil {
|
||
o.log.Warnf("generate skill draft failed intent_key=%s reason=%s err=%v", c.IntentKey, c.Reason, draftErr)
|
||
}
|
||
continue
|
||
}
|
||
if created && o.log != nil {
|
||
o.log.Infof("capability gap draft generated path=%s intent_key=%s reason=%s count=%d", path, c.IntentKey, c.Reason, c.Count)
|
||
}
|
||
if created {
|
||
if reloadErr := o.ReloadSkills(); reloadErr != nil && o.log != nil {
|
||
o.log.Warnf("auto reload skills failed after generation path=%s err=%v", path, reloadErr)
|
||
}
|
||
}
|
||
}
|
||
}
|
||
|
||
func (o *Orchestrator) ReloadSkills() error {
|
||
skills, err := knowledge.LoadSkillSet(o.skillsDir)
|
||
if err != nil {
|
||
return err
|
||
}
|
||
o.skillsMu.Lock()
|
||
o.skills = skills
|
||
o.skillsMu.Unlock()
|
||
if o.log != nil {
|
||
o.log.Infof("skills hot reloaded count=%d dir=%s", len(skills), o.skillsDir)
|
||
}
|
||
return nil
|
||
}
|
||
|
||
func (o *Orchestrator) getSkillsSnapshot() []knowledge.Skill {
|
||
o.skillsMu.RLock()
|
||
defer o.skillsMu.RUnlock()
|
||
out := make([]knowledge.Skill, len(o.skills))
|
||
copy(out, o.skills)
|
||
return out
|
||
}
|
||
|
||
func (o *Orchestrator) BuildCapabilityGapReport(limit int) (string, error) {
|
||
clusters, err := o.store.TopCapabilityGapClusters(limit, time.Now().UTC().Add(-o.gapLookbackDuration))
|
||
if err != nil {
|
||
return "", err
|
||
}
|
||
if len(clusters) == 0 {
|
||
return "最近没有采集到能力缺口记录。", nil
|
||
}
|
||
b := strings.Builder{}
|
||
b.WriteString("高频能力缺口清单:\n")
|
||
for i, c := range clusters {
|
||
line := fmt.Sprintf("%d) intent=%s | reason=%s | count=%d | last_seen=%s\n", i+1, c.IntentKey, c.Reason, c.Count, c.LastSeenAt.Format("2006-01-02 15:04:05"))
|
||
b.WriteString(line)
|
||
}
|
||
b.WriteString("\n草稿目录:")
|
||
b.WriteString(o.autoSkillDir)
|
||
b.WriteString("\n系统会在达到阈值后自动生成并热加载技能;你也可以手动发送 /reload_skills。")
|
||
return b.String(), nil
|
||
}
|
||
|
||
func (o *Orchestrator) findSkillByKeyword(keywords ...string) (knowledge.Skill, bool) {
|
||
if len(keywords) == 0 {
|
||
return knowledge.Skill{}, false
|
||
}
|
||
skills := o.getSkillsSnapshot()
|
||
for _, s := range skills {
|
||
name := strings.ToLower(strings.TrimSpace(s.Name))
|
||
content := strings.ToLower(strings.TrimSpace(s.Content))
|
||
for _, kw := range keywords {
|
||
kw = strings.ToLower(strings.TrimSpace(kw))
|
||
if kw == "" {
|
||
continue
|
||
}
|
||
if strings.Contains(name, kw) || strings.Contains(content, kw) {
|
||
return s, true
|
||
}
|
||
}
|
||
}
|
||
return knowledge.Skill{}, false
|
||
}
|
||
|
||
func formatToolErrorObservation(code, action, reason string) string {
|
||
code = strings.TrimSpace(code)
|
||
action = strings.TrimSpace(action)
|
||
reason = strings.TrimSpace(reason)
|
||
if code == "" {
|
||
code = "TOOL_EXEC_ERROR"
|
||
}
|
||
if action == "" {
|
||
action = "unknown"
|
||
}
|
||
if reason == "" {
|
||
reason = "unknown error"
|
||
}
|
||
return "ERROR_CODE=" + code + "; TOOL=" + action + "; REASON=" + reason
|
||
}
|
||
|
||
func formatSkills(skills []knowledge.Skill) string {
|
||
b := strings.Builder{}
|
||
for _, skill := range skills {
|
||
b.WriteString("## ")
|
||
b.WriteString(skill.Name)
|
||
b.WriteString("\n")
|
||
b.WriteString(skill.Content)
|
||
b.WriteString("\n\n")
|
||
}
|
||
return strings.TrimSpace(b.String())
|
||
}
|
||
|
||
func formatSkillCatalog(skills []knowledge.Skill) string {
|
||
b := strings.Builder{}
|
||
for _, skill := range skills {
|
||
summary := strings.ReplaceAll(skill.Content, "\n", " ")
|
||
summary = strings.TrimSpace(summary)
|
||
if len(summary) > 220 {
|
||
summary = summary[:220]
|
||
}
|
||
b.WriteString("- ")
|
||
b.WriteString(skill.Name)
|
||
if summary != "" {
|
||
b.WriteString(": ")
|
||
b.WriteString(summary)
|
||
}
|
||
b.WriteString("\n")
|
||
}
|
||
return strings.TrimSpace(b.String())
|
||
}
|
||
|
||
func (o *Orchestrator) formatToolDoc() string {
|
||
list := o.tools.List()
|
||
if len(list) == 0 {
|
||
return "(none)"
|
||
}
|
||
sort.Slice(list, func(i, j int) bool {
|
||
return list[i].Name() < list[j].Name()
|
||
})
|
||
b := strings.Builder{}
|
||
for _, t := range list {
|
||
b.WriteString("- ")
|
||
b.WriteString(t.Name())
|
||
b.WriteString(": ")
|
||
b.WriteString(t.Description())
|
||
b.WriteString("\n")
|
||
}
|
||
return strings.TrimSpace(b.String())
|
||
}
|