Files
HomeAgent/internal/agent/core/toolcall.go
JianFeeeee d4f9a12db0 feat(memory): 场景从「声明」改为「涌现」——场面指纹自己长成场景
上一版场景是声明/派生的:调用方写 scene="chan:qq",或由通道机械派生。
那不是涌现,是贴标签——标签谁定、怎么定全靠人。按「像人一样:干了什么事,
后续类似场面自动唤起对应记忆」的要求重做。

机制(全部取自运行时可观察量,无需模型配合、无需人工标注):

- **场面指纹 Situation**:每轮采集 `chan:xx / peer:xx / peer_group:xx /
  tool:xx / topic:xx / part:xx`。权重按种类:通道与对象最强(1.0),
  工具次之(0.8),话题是软信号(0.4),时段最弱(0.2)。
- **归属判定用加权 Jaccard**(不是字符串相等):共享特征权重和 / 并集权重和。
  加权是必须的——`chan:qq` 与 `topic:排班` 的证据力差 2.5 倍,不加权会让
  一次偶然的话题重合把两个不同场面并成一个。
- **涌现**:同类指纹重复到 minSceneEvidence=2 次才长出场景
  (首次只登记 situation_evidence 足迹)。一次性的交互不是「场面」,
  给它建场景会让库被一次性事件撑满、之后每次路过都召回一堆只发生过一次的事。
- **强化**:场景每次重现 strength+1、并入新特征。
- **唤起**:RecallBySituation 按**相似度**取回(阈值 0.35,比归属阈值 0.5 低
  ——想不起来是损失,多想起一条只是多几行上下文),与措辞无关。
- **遗忘**:DecaySceneRefs 按半衰期让久未重现的关联淡出,低于 floor 直接删;
  已接进 archive 心跳(半衰期 30 天,比「这个月没做过这类事」更久)。

三个必须讲清的边界:
1. 一轮只解析一次场景(TaskFrame 缓存)——多解析一次就多记一次强度,
   「工具调得多」会被误读成「这个场面更常出现」。
2. 声明与涌现**并存**:声明是「我知道这是哪个场面」(插件注入点最清楚),
   涌现是「这轮看起来像哪个场面」。两者都进召回。
3. 记忆挂载全自动:memory_commit 没写 scene 时落到本轮涌现场景,
   模型不需要知道场景这回事。

验证:go build/vet 干净,go test -count=1 ./... 全绿。
新增用例(核心证据):
- TestSceneEmergesFromRepetition:首次不建场景 → 第 2 次同类场面长出场景 →
  同场面**不同话题**仍并入同一场景 → 换通道的场面自己长出独立场景(共 2 个)→
  强度随重现增长、特征多条。全程没有任何人声明过场景键。
- TestSceneRecallsBySituationNotWording:场面里写下的规则,换措辞后仍被
  自动唤起(含原句),无关场面不唤起。
- TestSceneRefDecay:一个半衰期权重减半、第二个半衰期低于 floor 被清掉,
  仍在重现的场景不受影响。
- TestSituationFeaturesFor:指纹维度齐全、归一化、数值 group_id 转换、nil 安全。
2026-09-15 09:27:39 +08:00

684 lines
23 KiB
Go
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

package core
import (
"fmt"
"log"
"runtime/debug"
"strings"
"time"
agentAPI "gitcode.com/JianFeeeee/HomeAgent/internal/agent/api"
"gitcode.com/JianFeeeee/HomeAgent/internal/memory"
"gitcode.com/JianFeeeee/HomeAgent/internal/memory/document"
"gitcode.com/JianFeeeee/HomeAgent/internal/memory/text"
)
func (a *Agent) executeToolCall(tc agentAPI.ToolCall, channel string, turnScene ...string) (ret string) {
defer func() {
if r := recover(); r != nil {
stack := debug.Stack()
log.Printf("[agent] tool %s panic: %v\n%s", tc.Name, r, stack)
if pluginName := a.resolveToolPlugin(tc.Name); pluginName != "" {
if a.pluginHealth.recordCrash(pluginName) {
log.Printf("[agent] plugin %s exceeded crash threshold, scheduling reload", pluginName)
}
}
ret = fmt.Sprintf("工具 %s 执行崩溃: %v", tc.Name, r)
}
}()
done := make(chan string, 1)
go func() {
done <- a.executeToolCallInner(tc, channel, firstOr(turnScene))
}()
select {
case result := <-done:
return result
case <-time.After(60 * time.Second):
log.Printf("[agent] tool %s timed out after 60s", tc.Name)
return fmt.Sprintf("工具 %s 执行超时60秒已取消", tc.Name)
}
}
// firstOr 取可选参数的首个值(工具执行路径只有调用方知道本轮场景,
// 用变参是为了不让「不关心场景」的调用点spawn/测试)被迫传空串)。
func firstOr(v []string) string {
if len(v) == 0 {
return ""
}
return v[0]
}
func (a *Agent) executeToolCallInner(tc agentAPI.ToolCall, channel string, scene string) string {
switch {
case tc.Name == "persona_set":
return a.executePersonaTool(tc)
case strings.HasPrefix(tc.Name, "memory_"):
return a.executeMemoryTool(tc, scene)
case strings.HasPrefix(tc.Name, "social_"):
return a.executeSocialTool(tc)
case strings.HasPrefix(tc.Name, "knowledge_"):
return a.executeKnowledgeTool(tc)
case strings.HasPrefix(tc.Name, "doc_"):
return a.executeDocTool(tc)
case strings.HasPrefix(tc.Name, "output_send__") && strings.HasSuffix(tc.Name, "_help"):
return a.executeOutputSendHelp(tc)
case strings.HasPrefix(tc.Name, "output_send__"):
return a.executeOutputSendTool(tc)
case tc.Name == "output_list_channels":
return a.executeOutputListChannels()
case tc.Name == "input_channels":
return a.executeInputChannels(tc)
case tc.Name == "resident_agents":
return a.executeResidentAgents(tc)
case tc.Name == "notify_parent":
return a.executeNotifyParent(tc)
case tc.Name == "inputch_note":
return a.executeInputchNote(tc)
case tc.Name == "plgreload":
return a.executePluginReload()
case tc.Name == "get_plugin_tools":
pluginName, _ := tc.Arguments["plugin_name"].(string)
return a.executeGetPluginTools(pluginName)
case tc.Name == "spawn_child":
return a.executeSpawnChild(tc, channel)
case tc.Name == "child_result":
return a.executeChildResultTool(tc)
case strings.HasPrefix(tc.Name, "llm_"):
return a.executeLLMTool(tc)
case tc.Name == "describe_image":
return a.executeDescribeImage(tc)
case tc.Name == "transcribe_audio":
return a.executeTranscribeAudio(tc)
case tc.Name == "ocr_image":
return a.executeOCRImage(tc)
}
if a.stageHost != nil {
if result, err := a.stageHost.ExecuteTool(tc.Name, tc.Arguments); err == nil {
return fmt.Sprintf("%v", result)
} else if !strings.Contains(err.Error(), "not found in any plugin") {
return fmt.Sprintf("工具 %s 执行失败: %v", tc.Name, err)
}
}
// 设备类工具的**授权闸**(最小授权的缺口在这里)。
//
// 设备指令类工具device_ctl_cmdrun/screensee/computeruse/...)走的是工具面,
// 而 AllowedOutputs 只作用于 output_send__<通道> —— 于是"授权"对指令类工具完全无效:
// 驻留子只要拿到 device_ctl_cmdrun 就能指挥**任意**设备。
// 这里按目标设备的通道名 device/<id> 查同一道闸:父授权了哪台设备,才允许指挥哪台。
if _, isDeviceTool := a.io.DeviceOfTool(tc.Name); isDeviceTool {
if id, _ := tc.Arguments["device_id"].(string); id != "" && !a.IsOutputAllowed("device/"+id) {
return fmt.Sprintf("设备 [%s] 未授权给本 agent可用设备见 output_list_channels 的 device/<id> 通道,或 devicedetect", id)
}
}
if a.tracker != nil {
a.tracker.PreAction(tc.Name)
}
result, err := a.io.ExecuteTool(tc.Name, tc.Arguments)
if a.tracker != nil {
if cs := a.tracker.PostAction(tc.Name); cs != nil && len(cs.Files) > 0 {
log.Printf("[agent] tool %s changed %d files (changeset: %s)", tc.Name, len(cs.Files), cs.ID)
}
}
if err != nil {
return fmt.Sprintf("工具 %s 执行失败: %v", tc.Name, err)
}
return fmt.Sprintf("%v", result)
}
func (a *Agent) executeMemoryTool(tc agentAPI.ToolCall, turnScene string) string {
g := a.graphMem()
if g == nil {
if tc.Name == "memory_document_query" {
return a.executeDocTool(tc)
}
return "图记忆系统不可用"
}
// 整理类工具需要**完整内核**的记忆整理面(块/媒体/结构操作)。
// 轻量内核(驻留子)只有图记忆共同面 ⇒ 这些操作明确不可用,不静默降级。
requireFull := func() string {
if a.memory == nil {
return "本 agent 是轻量内核:只能读写图记忆,记忆整理(合并/删除/清理/编辑/统计)不可用"
}
return ""
}
switch tc.Name {
case "memory_recall":
query, _ := tc.Arguments["query_intent"].(string)
depth, _ := tc.Arguments["depth"].(float64)
if depth <= 0 {
depth = 2
}
if query == "" {
return "请输入查询关键词"
}
// 关键词提取:支持逗号分隔和自然语言
keywords := strings.Split(query, ",")
if len(keywords) == 1 {
keywords = memory.ExtractKeywords(query)
}
result, err := g.Recall(keywords, nil, int(depth), "")
if err != nil {
return fmt.Sprintf("记忆检索失败: %v", err)
}
if len(result.Entities) == 0 && len(result.Relations) == 0 {
return "未找到相关记忆"
}
if a.indexer != nil {
names := make([]string, len(result.Entities))
for i, e := range result.Entities {
names[i] = e.Name
}
a.indexer.MarkRecalled(names...)
}
var parts []string
parts = append(parts, fmt.Sprintf("找到 %d 个相关实体:", len(result.Entities)))
for _, e := range result.Entities {
parts = append(parts, fmt.Sprintf("- %s (提及%d次, 类型:%s)", e.Name, e.MentionCount, e.Type))
}
parts = append(parts, fmt.Sprintf("找到 %d 条关系:", len(result.Relations)))
parts = append(parts, formatRecallRelations(result.Relations, 10)...)
// 命中的关系若挂着媒体块,把媒体说明附在结果末尾。
//
// 关系行只有实体名和关系类型,看不出"这条记忆当时还带了一张图"。
// 媒体块以结构边与句子相连,需经关系→句子反查。
// 不附上的后果agent 显式查了图记忆,却仍然不知道有图。
if mc := a.mediaContextForRelations(result.Relations); mc != "" {
parts = append(parts, "", "关联媒体:", mc)
}
return strings.Join(parts, "\n")
case "memory_block_merge":
if msg := requireFull(); msg != "" {
return msg
}
entityA, _ := tc.Arguments["entity_a"].(string)
entityB, _ := tc.Arguments["entity_b"].(string)
rounds, _ := tc.Arguments["rounds"].(float64)
if entityA == "" || entityB == "" || rounds <= 0 {
return "entity_a、entity_b 和 rounds 不能为空"
}
if entityA > entityB {
entityA, entityB = entityB, entityA
}
key := entityA + "||" + entityB
a.noMergeMu.Lock()
a.noMergeMarkers[key] = int(rounds)
a.noMergeMu.Unlock()
return fmt.Sprintf("已标记「%s」与「%s」在 %d 轮内不合并", entityA, entityB, int(rounds))
case "memory_commit":
triplesData, ok := tc.Arguments["triples"].([]interface{})
if !ok {
return "参数格式错误,需要 triples 数组"
}
// 场景键模型可以在三元组里逐条给scene 字段),也可以在工具参数
// 顶层给一次scene 参数),后者作为本批次的默认场景。
// 两条路都为空则这条记忆不参与场景召回——不做猜测:猜错的场景会把
// 无关记忆钉死,之后每次进入该场面都会被注入,比漏标更难发现。
batchScene := getString(tc.Arguments, "scene")
// 没有显式声明时,落到本轮**涌现**出来的场景上:模型不需要知道场景
// 这回事,记忆也会因为「是在什么场面里写下的」而自动获得唤起入口。
if batchScene == "" {
batchScene = turnScene
}
var triples []memory.Triple
for _, td := range triplesData {
if m, ok := td.(map[string]interface{}); ok {
t := memory.Triple{
Subject: getString(m, "subject"),
Relation: getString(m, "relation"),
Object: getString(m, "object"),
SentenceText: getString(m, "sentence_text"),
Scene: getString(m, "scene"),
}
if t.Scene == "" {
t.Scene = batchScene
}
// 模型显式关联的媒体:结构化字段随三元组一起提交,
// 由 commitTriplesWithMedia 变成 L3 一等块并与句子建边——
// 不再把 marker 写进句子文本。
if digests := getStringSlice(m, "media_digests"); len(digests) > 0 {
t.MediaDigests = a.resolveMediaDigests(digests)
// 块边需要句子作端点。模型没给原句时用三元组本身拼一句
// 自然语言——不能造一段 marker 文本,那正是被废弃的东西。
if t.SentenceText == "" && len(t.MediaDigests) > 0 {
t.SentenceText = fmt.Sprintf("%s%s%s。", t.Subject, t.Relation, t.Object)
}
}
if t.Subject != "" && t.Relation != "" && t.Object != "" {
triples = append(triples, t)
}
}
}
if len(triples) == 0 {
return "没有有效的三元组"
}
// remember 工具是用户/模型显式写入,不涉及归档删除,
// 因此不需要 mediaBound——没有旧引用要释放。
ec, rc, mb, err := a.commitTriplesWithMedia(triples, string(a.id), 0, nil)
if err != nil {
return fmt.Sprintf("记忆写入失败: %v", err)
}
if mb > 0 {
return fmt.Sprintf("已写入 %d 个实体和 %d 条关系,关联 %d 份媒体", ec, rc, mb)
}
return fmt.Sprintf("已写入 %d 个实体和 %d 条关系", ec, rc)
case "memory_introspect":
if msg := requireFull(); msg != "" {
return msg
}
stats, err := a.memory.Introspect()
if err != nil {
return fmt.Sprintf("查询失败: %v", err)
}
return fmt.Sprintf("记忆统计: %v", stats)
case "memory_document_query":
return a.executeDocTool(tc)
case "memory_merge":
if msg := requireFull(); msg != "" {
return msg
}
source, _ := tc.Arguments["source"].(string)
target, _ := tc.Arguments["target"].(string)
if source == "" || target == "" {
return "source 和 target 不能为空"
}
count, err := a.memory.MergeEntities(source, target)
if err != nil {
return fmt.Sprintf("合并失败: %v", err)
}
return fmt.Sprintf("已将「%s」合并到「%s」source 已彻底删除,%d 条关系已重定向", source, target, count)
case "memory_delete_entity":
if msg := requireFull(); msg != "" {
return msg
}
name, _ := tc.Arguments["name"].(string)
if name == "" {
return "name 不能为空"
}
if err := a.memory.DeleteEntity(name); err != nil {
return fmt.Sprintf("删除失败: %v", err)
}
return fmt.Sprintf("已彻底删除实体「%s」及其所有关联关系", name)
case "memory_purge":
if msg := requireFull(); msg != "" {
return msg
}
criteria := make(map[string]string)
if v, ok := tc.Arguments["subject_contains"].(string); ok && v != "" {
criteria["subject_contains"] = v
}
if v, ok := tc.Arguments["relation_type"].(string); ok && v != "" {
criteria["relation_type"] = v
}
if v, ok := tc.Arguments["target_contains"].(string); ok && v != "" {
criteria["target_contains"] = v
}
mode, _ := tc.Arguments["mode"].(string)
if mode == "" {
mode = "soft"
}
n, err := a.memory.Purge(criteria, mode)
if err != nil {
return fmt.Sprintf("删除图记忆失败: %v", err)
}
textRemoved := 0
if a.textMem != nil {
if subj, ok := criteria["subject_contains"]; ok && subj != "" {
textRemoved, _ = a.textMem.PurgeByFilter(func(evt text.Event) bool {
return strings.Contains(evt.Source, subj) || strings.Contains(evt.Input, subj) || strings.Contains(evt.Response, subj)
})
}
}
parts := []string{fmt.Sprintf("已%s删除 %d 条图记忆关系", mode, n)}
if textRemoved > 0 {
parts = append(parts, fmt.Sprintf("清理 %d 条文本记忆日志", textRemoved))
}
return strings.Join(parts, "")
case "memory_edit":
if msg := requireFull(); msg != "" {
return msg
}
oldSubject, _ := tc.Arguments["old_subject"].(string)
oldRelation, _ := tc.Arguments["old_relation"].(string)
oldObject, _ := tc.Arguments["old_object"].(string)
if oldSubject == "" || oldRelation == "" || oldObject == "" {
return "old_subject、old_relation、old_object 不能为空"
}
newSubject, _ := tc.Arguments["new_subject"].(string)
newRelation, _ := tc.Arguments["new_relation"].(string)
newObject, _ := tc.Arguments["new_object"].(string)
if newSubject == "" && newRelation == "" && newObject == "" {
return "至少提供一个新值new_subject / new_relation / new_object"
}
if newSubject == "" {
newSubject = oldSubject
}
if newRelation == "" {
newRelation = oldRelation
}
if newObject == "" {
newObject = oldObject
}
// 编辑前先精确取回旧关系Purge 是「删旧写新」,中间那一步会把
// 置信度、场景引用、原句一起丢掉。复审心跳reviewLoop正是走这条路
// 于是每次复审都把置信度重置成默认 1.0、把场景钉死的记忆打散成无场景,
// 而且没有任何日志——这类「静默降级」比报错难查得多。
var carriedConf float64
var carriedSentence, carriedScene string
if olds, ferr := a.memory.FindRelations(oldSubject, oldRelation, oldObject); ferr == nil && len(olds) > 0 {
carriedConf = olds[0].Confidence
carriedSentence = olds[0].SentenceText
if keys, serr := a.memory.ScenesOfRelation(olds[0].ID); serr == nil && len(keys) > 0 {
carriedScene = keys[0]
}
}
n, err := a.memory.Purge(map[string]string{
"subject_contains": oldSubject,
"relation_type": oldRelation,
"target_contains": oldObject,
}, "hard")
if err != nil {
return fmt.Sprintf("编辑图记忆失败(删除旧记录): %v", err)
}
triples := []memory.Triple{{
Subject: newSubject,
Relation: newRelation,
Object: newObject,
Confidence: carriedConf,
SentenceText: carriedSentence,
Scene: carriedScene,
}}
ec, rc, err := a.memory.Commit(triples, string(a.id), 0)
if err != nil {
return fmt.Sprintf("编辑图记忆失败(写入新记录): %v", err)
}
textReplaced := 0
if a.textMem != nil && oldSubject != "" {
textReplaced, _ = a.textMem.ReplaceByFilter(
func(evt text.Event) bool {
return strings.Contains(evt.Input, oldSubject) || strings.Contains(evt.Response, oldSubject)
},
func(evt text.Event) text.Event {
evt.Input = strings.ReplaceAll(evt.Input, oldSubject, newSubject)
evt.Response = strings.ReplaceAll(evt.Response, oldSubject, newSubject)
return evt
},
)
}
result := fmt.Sprintf("已编辑记忆:删除 %d 条旧关系,写入 %d 个实体 + %d 条新关系", n, ec, rc)
if textReplaced > 0 {
result += fmt.Sprintf(",更新 %d 条文本记忆日志", textReplaced)
}
return result
default:
return fmt.Sprintf("未知的记忆工具: %s", tc.Name)
}
}
func (a *Agent) executeSocialTool(tc agentAPI.ToolCall) string {
if a.social == nil {
return "人物关系网不可用social store 未初始化)"
}
switch tc.Name {
case "person_query":
name, _ := tc.Arguments["name"].(string)
if name == "" {
return "请输入人物名称"
}
profile, err := a.social.GetPerson(name)
if err != nil {
return fmt.Sprintf("查询人物失败: %v", err)
}
var parts []string
parts = append(parts, fmt.Sprintf("▎%s 的档案", name))
if len(profile.Traits) > 0 {
parts = append(parts, "【特质】")
for k, v := range profile.Traits {
parts = append(parts, fmt.Sprintf(" %s: %s", k, v))
}
}
if len(profile.Relations) > 0 {
parts = append(parts, "【社交关系】")
for _, r := range profile.Relations {
parts = append(parts, fmt.Sprintf(" %s —(%s)—→ %s", name, r.Relation, r.Person))
}
}
if len(profile.Traits) == 0 && len(profile.Relations) == 0 {
parts = append(parts, " (尚无记录)")
}
return strings.Join(parts, "\n")
case "person_set_trait":
name, _ := tc.Arguments["name"].(string)
trait, _ := tc.Arguments["trait"].(string)
value, _ := tc.Arguments["value"].(string)
if name == "" || trait == "" || value == "" {
return "name、trait、value 都不能为空"
}
if err := a.social.SetTrait(name, trait, value); err != nil {
return fmt.Sprintf("设置特质失败: %v", err)
}
return fmt.Sprintf("已记录:%s 的 %s = %s", name, trait, value)
case "person_relate":
personA, _ := tc.Arguments["person_a"].(string)
relation, _ := tc.Arguments["relation"].(string)
personB, _ := tc.Arguments["person_b"].(string)
if personA == "" || relation == "" || personB == "" {
return "person_a、relation、person_b 都不能为空"
}
if err := a.social.AddRelation(personA, relation, personB); err != nil {
return fmt.Sprintf("建立关系失败: %v", err)
}
return fmt.Sprintf("已记录:%s —(%s)—→ %s", personA, relation, personB)
case "person_network":
name, _ := tc.Arguments["name"].(string)
depth := int(getFloat(tc.Arguments, "depth"))
if depth <= 0 {
depth = 2
}
if name == "" {
return "请输入人物名称"
}
profiles, err := a.social.GetNetwork(name, depth)
if err != nil {
return fmt.Sprintf("查询社交网络失败: %v", err)
}
if len(profiles) == 0 {
return fmt.Sprintf("未找到 %s 的社交网络", name)
}
var parts []string
parts = append(parts, fmt.Sprintf("▎%s 的社交网络(%d 度)", name, depth))
for _, p := range profiles {
if p.Name == name {
continue
}
parts = append(parts, fmt.Sprintf(" · %s", p.Name))
for k, v := range p.Traits {
parts = append(parts, fmt.Sprintf(" %s: %s", k, v))
}
for _, r := range p.Relations {
if r.Person != name {
parts = append(parts, fmt.Sprintf(" —(%s)—→ %s", r.Relation, r.Person))
}
}
}
return strings.Join(parts, "\n")
default:
return fmt.Sprintf("未知的人物工具: %s", tc.Name)
}
}
func (a *Agent) executeKnowledgeTool(tc agentAPI.ToolCall) string {
if a.knowledge == nil {
return "知识库不可用"
}
switch tc.Name {
case "knowledge_search":
query, _ := tc.Arguments["query"].(string)
topK := int(getFloat(tc.Arguments, "top_k"))
if topK <= 0 {
topK = 5
}
if query == "" {
return "请输入查询关键词"
}
results := a.knowledge.Search(query, topK)
if len(results) == 0 {
return "未找到相关知识"
}
var parts []string
for i, k := range results {
if i >= topK {
break
}
label := k.Name
if k.Category != "" {
label = k.Category + "/" + k.Name
}
parts = append(parts, fmt.Sprintf("[%s]\n%s", label, truncateStr(k.Content, 200)))
}
return strings.Join(parts, "\n---\n")
case "knowledge_create":
name, _ := tc.Arguments["name"].(string)
content, _ := tc.Arguments["content"].(string)
if name == "" || content == "" {
return "name 和 content 不能为空"
}
if err := a.knowledge.Add(name, content); err != nil {
return fmt.Sprintf("知识创建失败: %v", err)
}
return fmt.Sprintf("知识「%s」已创建并向量化索引%d 字符)", name, len(content))
case "knowledge_list":
tree := a.knowledge.BuildTree()
return formatTree(tree, 0)
case "knowledge_delete":
name, _ := tc.Arguments["name"].(string)
if name == "" {
return "name 不能为空"
}
if err := a.knowledge.Remove(name); err != nil {
return fmt.Sprintf("知识删除失败: %v", err)
}
return fmt.Sprintf("知识「%s」已删除", name)
default:
return fmt.Sprintf("未知的知识工具: %s", tc.Name)
}
}
func (a *Agent) executeDocTool(tc agentAPI.ToolCall) string {
if a.docStore == nil {
return "文档记忆不可用"
}
switch tc.Name {
case "doc_query":
query, _ := tc.Arguments["query"].(string)
topK := int(getFloat(tc.Arguments, "top_k"))
if topK <= 0 {
topK = 3
}
if query == "" {
return "请输入查询内容"
}
docs := a.docStore.Consume(query, topK)
if len(docs) == 0 {
return "未找到相关文档记忆"
}
var parts []string
var refs []string
for i, d := range docs {
parts = append(parts, fmt.Sprintf("[%d] %s (来源: %s)", i+1, d.Summary, d.Source))
if len(d.Tags) > 0 {
parts = append(parts, " 标签: "+strings.Join(d.Tags, ", "))
}
content := d.Content
if len(content) > 2000 {
content = content[:2000] + "..."
}
// 媒体块标签单独一行进冷存事件:正文可能被上面的 2000 字截断,
// 截掉之后模型就不知道这篇文档带过图。
if labels := a.blockLabelsForDoc(d); labels != "" {
content = content + "\n关联媒体: " + labels
}
a.context.InsertByTimestamp(ContextEvent{
Timestamp: d.CreatedAt,
Source: "cold_storage",
Input: fmt.Sprintf("加载文档记忆: %s", query),
Response: content,
})
refs = append(refs, fmt.Sprintf("#%d(%s)", i+1, d.Summary))
}
return fmt.Sprintf("已加载 %d 篇文档记忆: %s\n(完整内容参见对话时序中 cold_storage 事件)",
len(docs), strings.Join(refs, ", "))
case "doc_commit":
content, _ := tc.Arguments["content"].(string)
summary, _ := tc.Arguments["summary"].(string)
if content == "" {
return "content 不能为空"
}
if summary == "" {
summary = truncateStr(content, 100)
}
tagsRaw, _ := tc.Arguments["tags"].([]interface{})
var tags []string
for _, t := range tagsRaw {
if s, ok := t.(string); ok {
tags = append(tags, s)
}
}
doc := &document.Doc{
Summary: summary,
Content: content,
Tags: tags,
Source: "manual",
}
// 模型显式关联的媒体:直接变成文档持有的一等块。
// 不再往正文写 marker——文档向量会融合这些块的媒体向量
// 图片按自己的向量被检索。
for _, d := range a.resolveMediaDigests(getStringSlice(tc.Arguments, "media_digests")) {
if b, ok := a.blockFromDigest(d); ok {
doc.Blocks = append(doc.Blocks, b)
}
}
if err := a.docStore.Insert(doc); err != nil {
return fmt.Sprintf("文档写入失败: %v", err)
}
if n := len(doc.Blocks); n > 0 {
return fmt.Sprintf("文档已提交 (id: %s, 摘要: %s, 关联 %d 份媒体)", doc.ID, summary, n)
}
return fmt.Sprintf("文档已提交 (id: %s, 摘要: %s)", doc.ID, summary)
default:
return fmt.Sprintf("未知的文档工具: %s", tc.Name)
}
}