mirror of
https://gitcode.com/JianFeeeee/HomeAgent.git
synced 2026-09-21 01:18:08 +00:00
2ebbdadcd6
设计：docs/zh/resident-subagent-design.md §6/§7/§8/§9/§10。
## N3 生命周期（resident.go）
- `SpawnResident`：主库**受限句柄** + 自己的 temp 实例（`LightMemory`）⇒ 子的轻量内核；
划入 inputch（登记归属）、授权输出通道、注入任务提示词；为父登记 `child/<id>` 入站 inputch；
建独立 `IOManager`（共享通道登记表）；启动子。
- `DestroyResident`：停子内核、归还划入的 inputch（回到未分配）、丢弃 temp 目录、出登记表。
- `Stop()` → `StopResidents()`：**父退出必须销毁全部子、不留孤儿**（设计 §10 硬约束）。
- `Residents()` 登记表快照；`ResidentTable(id)` 父 pull 子的处理表（不打断）。
## N4 跨 agent 投递
- 子→父：`notify_parent` → 投进父的 `child/<id>` inputch，优先级 **L3**。
- 父→子：`SendToResident` → 投进子的 inputch，优先级 **L4**；
`isKernelLevelSource` 泛化为"该 agent 的上级"（`AgentConfig.KernelSource`）⇒
只有父能在子的阶梯上产生 L4（子内部一律 ≤L3）。
- 子的 contextfull → 父侧 `raiseKernelInterrupt`（内核级事件，带子标识，父侧 L4）。
## N5 inputch 处理表
- 子持有；`inputch_note` 主动写**优先**，轮末 `autoRecordInputch` 兜底 ⇒ 每轮必有记录。
- 压缩时清表（表记的是被压掉那段窗口的逐轮处理）。
## N6 contextfull（判据修正）
❗初版判据是"拼好的 `f.Msgs` 估算 > 90% 窗口"，**结构上永不成立**：
`buildMessages` 拿到的 `budget.ContextTokens` 由 `targetUsage = 0.8 × 窗口` 推出，
时间线**在拼进消息之前就被预算裁过**，`f.Msgs` 封顶在 ~80% 窗口。
（初版测试用一个比系统提示词还小的窗口才勉强越线 —— 那等于什么都没测。）
现判据 = **未裁剪的积累上下文**（`a.context.Recent(0)`）超过窗口 90%：
它超过就说明下一轮必须丢事件，这正是"上下文满"。
三处置：`CompressResident`（保留语义：`TrimKeepRecent` 保留最近 N 条 + 清表）/
`ReclaimResident`（取消语义：`ExportTriples` 读 temp → 父选出要保留的 → `Commit` 进 main → 取消该子）/
`DestroyResident`（立刻销毁并移除）。
## 工具面
`resident_agents`（父，单工具多动作：list/create/send/inspect/compress/reclaim/destroy）、
`notify_parent` + `inputch_note`（子）。声明条件式：父才有前者，子才有后两者。
## 验收
`resident_test.go` 五项：生命周期与不留孤儿、双向投递（含"子的主动消息不得以 L4 出现"）、
处理表（自动写 vs 主动写优先）、contextfull + 三处置、
**压力 8 子 × 12 轮（父→子 L4 与普通输入各半）+ 双向汇报 + 父退出清理**。
全仓 go test ./... 37 包 ok / 0 FAIL；`-race`（agent/memory/plugin）干净；
压力 `-race -count=3` 通过。
794 lines
34 KiB
Go
794 lines
34 KiB
Go
package core
|
||
|
||
import (
|
||
"fmt"
|
||
"strings"
|
||
|
||
agentIO "gitcode.com/JianFeeeee/HomeAgent/internal/agent/io"
|
||
)
|
||
|
||
func (a *Agent) buildMemoryContext(input string, maxTokens int) string {
|
||
if a.indexer == nil {
|
||
return ""
|
||
}
|
||
injected := a.indexer.BuildContext(input)
|
||
s := a.indexer.FormatContext(injected)
|
||
|
||
// 图库召回命中的实体若关联着带媒体的句子，把媒体说明一并注入。
|
||
//
|
||
// 不做这一步的后果：媒体描述进了 L3，agent 却拿不出来。图库句子里
|
||
// 写着 [image/png a1b2c3d4e5f6] 这样的短标记，但没有任何东西告诉
|
||
// 模型那份内容是否还在、能否重新查看——描述永存而 blob 可能已被
|
||
// 删除，两者状态不同，必须显式告知。
|
||
//
|
||
// 注意不能直接用 injected.Relations：BuildContext 刻意把它置为 nil
|
||
//（自动注入只给实体索引以省 token，细节留给 memory_recall）。
|
||
// 因此这里用命中的实体名再查一次关系，只为拿到 sentence_id。
|
||
if mc := a.mediaContextForInjectedEntities(injected); mc != "" {
|
||
if s != "" {
|
||
s += "\n"
|
||
}
|
||
s += "【关联媒体】\n" + mc
|
||
}
|
||
|
||
if maxTokens > 0 {
|
||
s = TruncateByTokens(s, maxTokens)
|
||
}
|
||
return s
|
||
}
|
||
|
||
func (a *Agent) buildSystemPrompt(memContext string, userInput string) string {
|
||
prompt := a.systemPrompt
|
||
if prompt == "" {
|
||
prompt = "你是小宅，HomeAgent 的看板娘，一个家政型 AI 管家助手。绝不用 Unicode emoji，只用颜文字表达情感，句尾带语气词。WebUI 概览页展示你的立绘。"
|
||
}
|
||
|
||
// 驻留子：在**固定提示词之上**注入任务提示词（设计 §7「创建」）。
|
||
if a.taskPrompt != "" {
|
||
prompt += "\n\n【任务】" + a.taskPrompt
|
||
}
|
||
|
||
if a.personality != nil {
|
||
if pp := a.personality.InjectPrompt(); pp != "" {
|
||
prompt += "\n\n" + pp
|
||
}
|
||
}
|
||
|
||
if memContext != "" {
|
||
prompt += "\n\n" + memContext
|
||
}
|
||
|
||
prompt += "\n\n【记忆清理指令】当用户要求整理或清理记忆时，你必须实际调用 memory_ 工具执行操作，不能只回复文本。先用 memory_introspect 查看概况，再用 memory_recall 获取详情。有同义实体则用 memory_merge 合并（source 会被彻底删除），有无用噪音实体则用 memory_delete_entity 直接删除，也可用 memory_purge 批量清理，用 memory_edit 修正错误，用 memory_block_merge 标记不合并。如果工具执行成功，把结果告知用户；不要只描述计划而不执行。"
|
||
|
||
// 跨模态召回：文本路（fastText/TF-IDF 文档层，媒体描述文本已随记忆进入）
|
||
// + 视觉路（多模态文本编码 → 媒体库坐标）两路归一化融合。
|
||
// 未配置多模态空间时视觉路为空，等价旧的 docStore.Query。
|
||
if a.docStore != nil {
|
||
hits := a.retrieveCrossModal(userInput, 3, a.fusionCfg)
|
||
if md := a.crossModalMarkdown(hits); md != "" {
|
||
prompt += "\n\n" + md
|
||
}
|
||
}
|
||
|
||
prompt += "\n\n【中断消息】长任务执行期间，工具/插件/定时器等会通过中断机制向你发送提醒（如 QQ 新消息、终端输出到达、定时器到点等）。中断消息以 system 角色注入，内容带 [中断消息] 前缀，**不是用户发言，但也必须认真处理**：优先停下当前长任务，针对中断内容作出响应或决定继续执行。不要忽略带 [中断消息] 前缀的 system 消息。"
|
||
|
||
prompt += "\n\n【输出规则】消息不会自动发送到对话来源通道，你必须自己决定如何回复：\n"
|
||
prompt += "- **不要假设当前通道是某个固定值**：同一会话里可能同时有多个来源（多设备、多通道、子任务）。\n"
|
||
prompt += " 先看这条消息本身与上下文里的来源信息，再决定往哪里回；不确定有哪些通道时先调 output_list_channels。\n"
|
||
prompt += "- 同步通道（webui / cli / 终端）：直接返回纯文本，内核会把文本交给等待方显示，无需调用工具。\n"
|
||
prompt += "- 异步通道（qq / wechat / 群聊等）：返回纯文本**【不会】**自动送达用户，必须调用 output_send__{通道名} 工具（注意 meta 里带上正确的 user_id 或 group_id）才能真正把消息发出去。\n"
|
||
prompt += "- 不确定当前通道的发送方式时，先用 output_send__{通道名}_help 查看该通道的 meta 格式和 type 枚举，再决定。\n"
|
||
prompt += "- 每轮对话**通常只需调用一次** output_send__{通道名} 即可完成回复。仅在内容确实超过单条消息长度上限（如 >4000 字）时才拆分为多条；拆分时每条应是完整段落，不要碎片化。\n"
|
||
prompt += "- 需要多步执行的长任务：**必须先**向当前对话通道发一条确认消息告诉用户已收到（异步通道用输出门工具，同步通道直接返回文本），**然后再**执行具体排查工具。确认消息不代表任务完成，发出后仍需继续执行实际工具并最终汇报结果。\n"
|
||
prompt += "- 用户从其他渠道发来「在哪里/怎么样了」这类追问时，先回忆上次任务的通道与上下文，再回同一通道。"
|
||
|
||
if a.indexer != nil {
|
||
prompt += "\n\n" + a.indexer.BuildToolPrompt()
|
||
}
|
||
|
||
// 技能索引（方案B）：轻量注入已加载技能列表，LLM 匹配到场景时
|
||
// 主动 skill_info 拉取全文按文档执行
|
||
if a.skillIndex != nil {
|
||
if idx := a.skillIndex.SkillIndex(); idx != "" {
|
||
prompt += "\n\n【可用技能】以下是已安装的原生技能。当用户请求与某技能描述匹配时，\n先用 skill_info(\"技能名\") 拉取全文，再严格按文档步骤执行：\n" + idx
|
||
}
|
||
}
|
||
|
||
// 首启人格门禁（跨通道唯一闸口）：人格未确认时，要求模型主动询问用户。
|
||
// 系统提示词每轮重建，因此 WebUI / QQ / CLI / ACP / 邮件等所有通道都会带上它；
|
||
// 模型调用 persona_set（或用户在 WebUI 向导里选）落地后，标记置位，本段消失。
|
||
if a.personaStore != nil && !a.personaStore.PersonaInitialized() {
|
||
prompt += "\n\n【首启人格设定】你的**人格设定尚未确认**。请在本轮回复里先问用户一句：" +
|
||
"要用默认人格，还是自定义一个？拿到明确答复后**必须调用 persona_set 工具**落库：" +
|
||
"用户选默认 → mode=default；自定义 → mode=custom 且把内容写进 content；" +
|
||
"用户说以后再说 → mode=later。用户答复前不要假设已设置，也不要反复追问同一件事。"
|
||
}
|
||
|
||
prompt += a.buildToolCatalog()
|
||
|
||
return prompt
|
||
}
|
||
|
||
func cleanParams(params map[string]interface{}) map[string]interface{} {
|
||
if params == nil {
|
||
return nil
|
||
}
|
||
cleaned := make(map[string]interface{}, len(params))
|
||
for k, v := range params {
|
||
cleaned[k] = v
|
||
}
|
||
if req, ok := cleaned["required"]; ok {
|
||
switch v := req.(type) {
|
||
case []interface{}:
|
||
if len(v) == 0 {
|
||
delete(cleaned, "required")
|
||
}
|
||
case []string:
|
||
if len(v) == 0 {
|
||
delete(cleaned, "required")
|
||
}
|
||
}
|
||
}
|
||
return cleaned
|
||
}
|
||
|
||
func (a *Agent) buildToolCatalog() string {
|
||
defs := a.buildToolDefs()
|
||
if len(defs) == 0 {
|
||
return ""
|
||
}
|
||
// 仅注入插件/通道能力摘要，避免全量工具定义污染 system prompt。
|
||
// 每个插件列：名称 + 能力描述 + 工具数。完整工具定义由 get_plugin_tools 按需拉取。
|
||
byPlugin := map[string]int{} // plugin -> 工具数
|
||
pluginDesc := map[string]string{} // plugin -> 首个工具描述(作能力概览)
|
||
var order []string
|
||
for _, t := range defs {
|
||
fn, ok := t.(map[string]interface{})["function"].(map[string]interface{})
|
||
if !ok {
|
||
continue
|
||
}
|
||
name, _ := fn["name"].(string)
|
||
if name == "" {
|
||
continue
|
||
}
|
||
plg := a.resolveToolPlugin(name)
|
||
if _, seen := byPlugin[plg]; !seen {
|
||
order = append(order, plg)
|
||
}
|
||
byPlugin[plg]++
|
||
if pluginDesc[plg] == "" {
|
||
desc, _ := fn["description"].(string)
|
||
if len(desc) > 60 {
|
||
desc = desc[:60] + "..."
|
||
}
|
||
pluginDesc[plg] = desc
|
||
}
|
||
}
|
||
var sb strings.Builder
|
||
sb.WriteString("\n\n【可用工具能力】\n")
|
||
sb.WriteString("工具按插件分组注册。需要某个插件的具体工具时，调用 get_plugin_tools(\"{插件名}\") 获取该插件的完整工具定义（名称/参数/用途）。\n")
|
||
for _, plg := range order {
|
||
sb.WriteString(fmt.Sprintf("- %s (%d 个工具)", plg, byPlugin[plg]))
|
||
if d := pluginDesc[plg]; d != "" {
|
||
sb.WriteString(": " + d)
|
||
}
|
||
sb.WriteString("\n")
|
||
}
|
||
return sb.String()
|
||
}
|
||
|
||
func (a *Agent) buildToolDefs() []interface{} {
|
||
var tools []interface{}
|
||
|
||
if a.io != nil {
|
||
for _, td := range a.io.GetAllTools() {
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": td.Name,
|
||
"description": td.Description,
|
||
"parameters": cleanParams(td.Parameters),
|
||
},
|
||
})
|
||
}
|
||
}
|
||
|
||
if a.stageHost != nil {
|
||
for _, td := range a.stageHost.GetToolDefs() {
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": td.Name,
|
||
"description": td.Description,
|
||
"parameters": cleanParams(td.Parameters),
|
||
},
|
||
})
|
||
}
|
||
}
|
||
|
||
if a.indexer != nil {
|
||
for _, td := range a.indexer.GetToolDefinitions() {
|
||
tools = append(tools, td)
|
||
}
|
||
}
|
||
|
||
if a.personaStore != nil {
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "persona_set",
|
||
"description": "【首启人格】落地用户的人格选择并记录「已经问过」。仅在用户明确答复后调用：默认用 mode=default；自定义用 mode=custom 并把人格内容放进 content；用户说以后再说用 mode=later。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"mode": map[string]interface{}{"type": "string", "description": "default | custom | later"},
|
||
"content": map[string]interface{}{"type": "string", "description": "自定义人格内容（mode=custom 时必填）"},
|
||
},
|
||
"required": []string{"mode"},
|
||
},
|
||
},
|
||
})
|
||
}
|
||
|
||
if a.memory != nil {
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "memory_merge",
|
||
"description": "【记忆清理】合并两个同义实体。将所有关系从 source 重定向到 target，然后彻底删除 source。注意：实体删除后不可恢复，合并前请确认语义一致。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"source": map[string]interface{}{"type": "string", "description": "被合并的实体名（合并后消失）"},
|
||
"target": map[string]interface{}{"type": "string", "description": "保留的实体名"},
|
||
},
|
||
"required": []string{"source", "target"},
|
||
},
|
||
},
|
||
})
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "memory_delete_entity",
|
||
"description": "【记忆清理】彻底删除指定实体及其所有关联关系。用于清理无用的噪音实体，如 mentionCount=0 的孤立实体、distiller 自动产生的垃圾节点、确认无用的旧数据。此操作不可恢复。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"name": map[string]interface{}{"type": "string", "description": "要删除的实体名称"},
|
||
},
|
||
"required": []string{"name"},
|
||
},
|
||
},
|
||
})
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "memory_block_merge",
|
||
"description": "【记忆清理】标记两个实体在指定轮次内不尝试合并，用于阻止误判。当 LLM 判断两个实体虽然相似但不是同一事物时，使用此工具阻止后续心跳自动推送合并候选。每次心跳扫描双方计数各减一，归零后恢复候选资格。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"entity_a": map[string]interface{}{"type": "string", "description": "第一个实体名"},
|
||
"entity_b": map[string]interface{}{"type": "string", "description": "第二个实体名"},
|
||
"rounds": map[string]interface{}{"type": "integer", "description": "阻止轮次数（每次心跳各减一，归零后恢复）"},
|
||
},
|
||
"required": []string{"entity_a", "entity_b", "rounds"},
|
||
},
|
||
},
|
||
})
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "memory_purge",
|
||
"description": "【记忆清理】删除记忆库中符合条件的垃圾关系和数据。当用户要求整理记忆时，用 memory_introspect 发现低质量实体后，用此工具批量删除。如 @merged 后缀的残留实体、mentionCount=0 的孤立实体、distiller 自动生成的噪音关系等。支持软删（soft）和物理删除（hard）。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"subject_contains": map[string]interface{}{"type": "string", "description": "主体名包含的关键词，如 '@merged' 可清理已合并残留"},
|
||
"relation_type": map[string]interface{}{"type": "string", "description": "关系类型，如 '提及'、'回应'"},
|
||
"target_contains": map[string]interface{}{"type": "string", "description": "客体名包含的关键词"},
|
||
"mode": map[string]interface{}{"type": "string", "description": "soft（标记删除）/ hard（物理删除）", "default": "soft"},
|
||
},
|
||
},
|
||
},
|
||
})
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "memory_edit",
|
||
"description": "【记忆清理】编辑单条记忆关系：删除旧的 relation 并写入新的。用于修正错误的实体名或关系类型。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"old_subject": map[string]interface{}{"type": "string", "description": "旧主体名"},
|
||
"old_relation": map[string]interface{}{"type": "string", "description": "旧关系类型"},
|
||
"old_object": map[string]interface{}{"type": "string", "description": "旧客体名"},
|
||
"new_subject": map[string]interface{}{"type": "string", "description": "新主体名（不填则不变）"},
|
||
"new_relation": map[string]interface{}{"type": "string", "description": "新关系类型（不填则不变）"},
|
||
"new_object": map[string]interface{}{"type": "string", "description": "新客体名（不填则不变）"},
|
||
},
|
||
"required": []string{"old_subject", "old_relation", "old_object"},
|
||
},
|
||
},
|
||
})
|
||
}
|
||
|
||
if a.knowledge != nil {
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "knowledge_search",
|
||
"description": "搜索知识库。输入查询关键词，返回相关知识内容。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"query": map[string]interface{}{"type": "string", "description": "查询关键词"},
|
||
"top_k": map[string]interface{}{"type": "integer", "description": "返回数量", "default": 5},
|
||
},
|
||
"required": []string{"query"},
|
||
},
|
||
},
|
||
})
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "knowledge_list",
|
||
"description": "列出知识库中所有知识分类。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{},
|
||
},
|
||
},
|
||
})
|
||
}
|
||
|
||
if a.knowledge != nil {
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "knowledge_create",
|
||
"description": "创建新知识。将知识写入知识库（knowledge/目录），自动向量化索引。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"name": map[string]interface{}{"type": "string", "description": "知识名称（用作目录名）"},
|
||
"content": map[string]interface{}{"type": "string", "description": "知识内容，支持 Markdown"},
|
||
},
|
||
"required": []string{"name", "content"},
|
||
},
|
||
},
|
||
})
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "knowledge_delete",
|
||
"description": "删除知识库中的指定知识条目。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"name": map[string]interface{}{"type": "string", "description": "要删除的知识名称"},
|
||
},
|
||
"required": []string{"name"},
|
||
},
|
||
},
|
||
})
|
||
}
|
||
|
||
if a.docStore != nil {
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "doc_query",
|
||
"description": "查询文档记忆。输入查询内容，返回相关文档摘要。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"query": map[string]interface{}{"type": "string", "description": "查询内容"},
|
||
"top_k": map[string]interface{}{"type": "integer", "description": "返回数量", "default": 3},
|
||
},
|
||
"required": []string{"query"},
|
||
},
|
||
},
|
||
})
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "doc_commit",
|
||
"description": "提交一条文档记忆。将重要信息显式写入文档记忆层。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"content": map[string]interface{}{"type": "string", "description": "文档内容"},
|
||
"summary": map[string]interface{}{"type": "string", "description": "摘要（可选）"},
|
||
"tags": map[string]interface{}{
|
||
"type": "array",
|
||
"description": "标签列表",
|
||
"items": map[string]interface{}{"type": "string"},
|
||
},
|
||
"media_digests": map[string]interface{}{
|
||
"type": "array",
|
||
"description": "可选：这篇文档关联的媒体 digest（对话或 memory_recall 的「关联媒体」里显示的十六进制串，短的即可）。填了以后检索到这篇文档就能看到并取回原图/音频。",
|
||
"items": map[string]interface{}{"type": "string"},
|
||
},
|
||
},
|
||
"required": []string{"content"},
|
||
},
|
||
},
|
||
})
|
||
}
|
||
|
||
if a.social != nil {
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "person_query",
|
||
"description": "查询指定人物的完整档案（特质+社交关系）。用于了解一个人的性格、喜好、背景和社交圈。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"name": map[string]interface{}{"type": "string", "description": "人物名称"},
|
||
},
|
||
"required": []string{"name"},
|
||
},
|
||
},
|
||
})
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "person_set_trait",
|
||
"description": "记录/更新一个人的特质（性格、喜好、习惯等）。例如：person_set_trait(name=\"张三\", trait=\"喜欢\", value=\"红色\")。如果该特质已存在则覆盖。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"name": map[string]interface{}{"type": "string", "description": "人物名称"},
|
||
"trait": map[string]interface{}{"type": "string", "description": "特质名称，如：喜欢、性格、职业、年龄"},
|
||
"value": map[string]interface{}{"type": "string", "description": "特质值，如：红色、开朗、工程师、25岁"},
|
||
},
|
||
"required": []string{"name", "trait", "value"},
|
||
},
|
||
},
|
||
})
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "person_relate",
|
||
"description": "记录两个人之间的社交关系。例如：person_relate(person_a=\"张三\", relation=\"朋友\", person_b=\"李四\")。关系是双向的。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"person_a": map[string]interface{}{"type": "string", "description": "人物A"},
|
||
"relation": map[string]interface{}{"type": "string", "description": "关系类型，如：朋友、家人、同事、邻居、同学"},
|
||
"person_b": map[string]interface{}{"type": "string", "description": "人物B"},
|
||
},
|
||
"required": []string{"person_a", "relation", "person_b"},
|
||
},
|
||
},
|
||
})
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "person_network",
|
||
"description": "查询某人的社交网络（多度关系）。显示该人物周围的相关人物及其关系和特质。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"name": map[string]interface{}{"type": "string", "description": "人物名称"},
|
||
"depth": map[string]interface{}{"type": "integer", "description": "关系深度（默认2）", "default": 2},
|
||
},
|
||
"required": []string{"name"},
|
||
},
|
||
},
|
||
})
|
||
}
|
||
|
||
if a.pluginReg != nil && a.pluginDir != "" {
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "plgreload",
|
||
"description": "重载 plugins/ 目录的所有插件。扫描目录变更，原子化替换 IO 设备。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{},
|
||
},
|
||
},
|
||
})
|
||
}
|
||
|
||
// 按插件动态拉取工具定义(避免全量注入提示词污染)
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "get_plugin_tools",
|
||
"description": "获取指定插件的完整工具定义(名称/参数/用途)。参数 plugin_name 传插件名(见系统提示的【可用工具能力】列表)。省略时返回全部插件的工具摘要。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"plugin_name": map[string]interface{}{"type": "string", "description": "插件名，如 qq / remotedevice / weather", "default": ""},
|
||
},
|
||
},
|
||
},
|
||
})
|
||
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "spawn_child",
|
||
"description": "启动一个异步子 Agent 执行独立任务。子 Agent 后台运行，不阻塞当前对话。完成后系统会自动通知你，届时请调用 child_result 工具查看输出。\n使用时机：多个互不依赖的子任务（如同时查三个网站、分别处理多个文件）应并行 spawn 多个子 Agent，不要自己串行逐个执行；长耗时任务（批量处理、多轮搜索）也应交给子 Agent，避免阻塞对话。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"task": map[string]interface{}{
|
||
"type": "string",
|
||
"description": "要子 Agent 完成的任务描述。请描述清晰、完整，包含所有必要背景。",
|
||
},
|
||
"max_turns": map[string]interface{}{
|
||
"type": "integer",
|
||
"description": "子 Agent 最大工具轮数（默认 5，范围 1-30）。复杂任务可调高。",
|
||
},
|
||
},
|
||
"required": []string{"task"},
|
||
},
|
||
},
|
||
})
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "child_result",
|
||
"description": "查询异步子 Agent 的执行结果。当收到'子任务已完成'的通知后，调用此工具获取输出。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"task_id": map[string]interface{}{
|
||
"type": "string",
|
||
"description": "spawn_child 返回的任务 ID，如 child_1",
|
||
},
|
||
},
|
||
"required": []string{"task_id"},
|
||
},
|
||
},
|
||
})
|
||
|
||
if a.providerManager != nil {
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "llm_list_sources",
|
||
"description": "列出所有可用的 LLM 源（如 deepseek、openai、ollama），每个源有对应的 Lua 适配器和配置。如需切换 LLM 源，请使用 llm_set_source。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{},
|
||
},
|
||
},
|
||
})
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "llm_set_source",
|
||
"description": "切换当前 LLM 源到指定名称。变更立即生效，后续对话将使用新的 LLM 源。源名称可通过 llm_list_sources 查看。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"name": map[string]interface{}{
|
||
"type": "string",
|
||
"description": "LLM 源名称（如 deepseek、openai、ollama）",
|
||
},
|
||
},
|
||
"required": []string{"name"},
|
||
},
|
||
},
|
||
})
|
||
}
|
||
|
||
channels := a.io.ListChannels()
|
||
for _, ch := range channels {
|
||
if ch.Type != agentIO.DeviceOutput && ch.Type != agentIO.DeviceIO {
|
||
continue
|
||
}
|
||
// 输出通道授权（设计 §4.4/R2）：默认完整授权；父可用白名单收窄子的输出能力。
|
||
// 未授权就不生成 output_send__X —— 模型看不到它，自然不会调。
|
||
if !a.IsOutputAllowed(ch.Name) {
|
||
continue
|
||
}
|
||
capStr := a.io.GetChannelCapabilities(ch.Name).String()
|
||
desc := ch.Description
|
||
if desc == "" {
|
||
desc = ch.Name + " 输出通道"
|
||
}
|
||
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "output_send__" + ch.Name,
|
||
"description": desc + "。能力: " + capStr + "。payload 为消息载荷，meta 为 JSON 发送元数据，type 为载荷类型。用 _help 查看 meta 格式和 type 枚举。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"payload": map[string]interface{}{
|
||
"type": "string",
|
||
"description": "消息载荷。type=text 时填文字，type=file/image 时填 URL 或路径",
|
||
},
|
||
"meta": map[string]interface{}{
|
||
"type": "string",
|
||
"description": "JSON 对象，包含发送所需的元数据。用 output_send__" + ch.Name + "_help 查看 meta 格式",
|
||
},
|
||
"type": map[string]interface{}{
|
||
"type": "string",
|
||
"description": "载荷类型，用 channel._help 查看支持的枚举值",
|
||
},
|
||
},
|
||
"required": []string{"payload", "type"},
|
||
},
|
||
},
|
||
})
|
||
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "output_send__" + ch.Name + "_help",
|
||
"description": "查看 " + ch.Name + " 输出通道的 meta 格式说明和 type 枚举",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{},
|
||
},
|
||
},
|
||
})
|
||
}
|
||
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "output_list_channels",
|
||
"description": "列出所有可用输出通道及其能力（如 text/file/image/audio）和对应的输出门工具名称。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{},
|
||
},
|
||
},
|
||
})
|
||
|
||
// 父侧：驻留子控制面（单工具多动作，见设计 §7）。
|
||
if a.parentID == "" {
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "resident_agents",
|
||
"description": "管理驻留子 agent（长期派驻的下属）：list 列出 / create 创建（划入 inputch + " +
|
||
"授权输出通道 + 注入任务提示词）/ send 发送消息（对子而言是 L4 中断，取消其当前状态并插入新消息）" +
|
||
"/ inspect 查看其 inputch 处理表（不打断它）/ compress 压缩其上下文（保留语义，子继续存在）" +
|
||
"/ reclaim 回收（父选哪些纳入主记忆，然后取消该子）/ destroy 立刻销毁并移除。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"action": map[string]interface{}{
|
||
"type": "string",
|
||
"enum": []string{"list", "create", "send", "inspect", "compress", "reclaim", "destroy"},
|
||
},
|
||
"id": map[string]interface{}{"type": "string", "description": "驻留子 id"},
|
||
"task_prompt": map[string]interface{}{"type": "string", "description": "create：在固定提示词之上注入的任务提示词"},
|
||
"input_chs": map[string]interface{}{"type": "string", "description": "create：划入的 inputch（逗号分隔）"},
|
||
"allowed_outputs": map[string]interface{}{"type": "string", "description": "create：授权的输出通道（逗号分隔；留空=完整授权）"},
|
||
"capacity": map[string]interface{}{"type": "number", "description": "create：划入 inputch 的队列容量"},
|
||
"temp_path": map[string]interface{}{"type": "string", "description": "create：temp 图记忆路径（留空则用 data_dir/residents/<id>/graph.db）"},
|
||
"text": map[string]interface{}{"type": "string", "description": "send：要发给子 agent 的消息"},
|
||
},
|
||
"required": []string{"action"},
|
||
},
|
||
},
|
||
})
|
||
}
|
||
|
||
// 子侧（驻留子）：主动汇报（L3）与主动写处理表。
|
||
if a.parentID != "" {
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "notify_parent",
|
||
"description": "向主 agent 汇报（以 L3 中断投给它）。用于主动报告进展/结论，而不是等它来问。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{"text": map[string]interface{}{"type": "string", "description": "汇报内容"}},
|
||
"required": []string{"text"},
|
||
},
|
||
},
|
||
})
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "inputch_note",
|
||
"description": "为**本轮** inputch 主动写入处理信息（主 agent 会查这张表判断你的进度）。" +
|
||
"写了就不会再被系统自动记录；不写则本轮结束时系统自动写。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{"text": map[string]interface{}{"type": "string", "description": "本轮处理信息摘要"}},
|
||
"required": []string{"text"},
|
||
},
|
||
},
|
||
})
|
||
}
|
||
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "input_channels",
|
||
"description": "查看 inputch（最基本的输入路由单位）：哪些已注册、谁注册的、" +
|
||
"各自划给了哪个 agent、容量与记忆策略。单工具多视图。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"view": map[string]interface{}{
|
||
"type": "string",
|
||
"description": "all=全部已注册（默认）| mine=划给本 agent 的 | " +
|
||
"unassigned=尚未划出的 | by_agent=按归属分组的划分总览 | detail=单个详情",
|
||
"enum": []string{"all", "mine", "unassigned", "by_agent", "detail"},
|
||
},
|
||
"name": map[string]interface{}{
|
||
"type": "string",
|
||
"description": "view=detail 时必填：inputch 名",
|
||
},
|
||
},
|
||
},
|
||
},
|
||
})
|
||
|
||
if a.pendingMedia != nil {
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "describe_image",
|
||
"description": "描述当前用户上传的图片内容。使用配置的多模态模型或默认 LLM 进行识别。调用此工具后你将获得图片的详细文字描述。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"provider": map[string]interface{}{
|
||
"type": "string",
|
||
"description": "可选：用于图片描述的 LLM 源名称，不填则使用默认模型",
|
||
},
|
||
"detail": map[string]interface{}{
|
||
"type": "string",
|
||
"description": "描述详细程度: high / low / auto",
|
||
"default": "high",
|
||
},
|
||
},
|
||
},
|
||
},
|
||
})
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "transcribe_audio",
|
||
"description": "转写当前用户上传的音频内容为文字。使用配置的多模态模型或默认 LLM 进行语音识别。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"provider": map[string]interface{}{
|
||
"type": "string",
|
||
"description": "可选：用于音频转写的 LLM 源名称，不填则使用默认模型",
|
||
},
|
||
},
|
||
},
|
||
},
|
||
})
|
||
if a.inputCfg.Image.OCREnabled {
|
||
tools = append(tools, map[string]interface{}{
|
||
"type": "function",
|
||
"function": map[string]interface{}{
|
||
"name": "ocr_image",
|
||
"description": "对当前用户上传的图片执行 OCR 文字识别，提取图片中的文字内容。适用于截图、文档照片、菜单等场景。",
|
||
"parameters": map[string]interface{}{
|
||
"type": "object",
|
||
"properties": map[string]interface{}{
|
||
"language": map[string]interface{}{
|
||
"type": "string",
|
||
"description": "OCR 语言（如 chi_sim+eng），默认自动",
|
||
},
|
||
},
|
||
},
|
||
},
|
||
})
|
||
}
|
||
}
|
||
|
||
return tools
|
||
}
|