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refactor: output channel interface (payload/meta/type) + memory fixes

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- Redesign output_send__ tools: content JSON string -> structured
  payload/meta/type params for LLM reliability
- executeOutputSendTool: route by type with capability check
- executeOutputSendHelp: show meta format + type enum
- Updated system prompt rules for new interface
- docToTriples: use jieba exact mode adjacent co-occurrence
- Unify vector space: Doc.Vector field, ContextToDoc vectorizer,
  ReindexWithVectorizer on startup
This commit is contained in:
root
2026-07-19 10:29:21 +08:00
parent 9b3a751d98
commit 8ae1d19869
10 changed files with 453 additions and 109 deletions
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192
internal/agent/core/agent.go
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@ -165,9 +165,16 @@ func New(cfg AgentConfig) *Agent {
if cfg.MaxContextSize <= 0 {
cfg.MaxContextSize = 30
}
embedder := memory.NewStaticEmbedder(strings.Split(cfg.EmbeddingModelPath, ",")...)
if cfg.DocStore != nil {
cfg.DocStore.SetVectorizer(embedder)
cfg.DocStore.ReindexWithVectorizer(embedder)
}
return &Agent{
id: cfg.ID,
startTime: time.Now(),
startTime: time.Now(),
provider: cfg.Provider,
providerManager: cfg.ProviderManager,
io: cfg.IO,
@ -175,7 +182,7 @@ func New(cfg AgentConfig) *Agent {
indexer: cfg.Indexer,
skills: cfg.Skills,
tracker: cfg.Tracker,
context: NewRelevanceContext(cfg.ContextSavePath, memory.NewStaticEmbedder(strings.Split(cfg.EmbeddingModelPath, ",")...)),
context: NewRelevanceContext(cfg.ContextSavePath, embedder),
systemPrompt: cfg.SystemPrompt,
ctx: ctx,
cancel: cancel,
@ -734,6 +741,10 @@ func (a *Agent) process(input string, stageCtx *sdk.StageContext) (response stri
break
}
if errors.Is(llmErr, context.Canceled) {
// 打断不是 provider 故障，不标记不可用，直接让外层循环重试
break
}
var pe *agentAPI.ProviderError
if errors.As(llmErr, &pe) && (pe.StatusCode == 401 || pe.StatusCode == 403) {
a.providerManager.ReportStatus(fbProvider.Name(), pe.StatusCode)
@ -1612,8 +1623,8 @@ func (a *Agent) buildSystemPrompt(memContext string, userInput string) string {
// 输出指令：使用 output_send__{channel} 作为回复手段
prompt += "\n\n【输出规则】你有多组输出门工具（type=output），每个对应一个输出通道。回复用户时必须调用对应的 output_send__{通道名} 工具。\n"
prompt += "- content 参数是 JSON 字符串，包含要发送的内容。具体格式因通道而异，用 output_send__{通道名}_help 查看每个通道的 JSON 格式说明。\n"
prompt += "- output_send__{通道名}_help 是普通 function 类型工具，调用后返回该通道的 JSON 格式详情和示例。\n"
prompt += "- payload 参数是消息载荷（文本直接填文字），type 指定载荷类型（text/voice/image/file），meta 是 JSON 发送元数据（群号/用户号等）。\n"
prompt += "- 用 output_send__{通道名}_help 查看该通道的 meta 格式和 type 枚举。\n"
prompt += "- 同一轮对话中可多次调用输出门工具。长消息应当分多次发出，而不是一口气发完。\n"
prompt += "- 直接返回纯文本不会到达任何用户端。"
@ -2081,16 +2092,24 @@ func (a *Agent) buildToolDefs() []interface{} {
"type": "function",
"function": map[string]interface{}{
"name": "output_send__" + ch.Name,
"description": desc + "。能力: " + capStr + "。content 参数为 JSON 字符串，具体格式请调用 output_send__" + ch.Name + "_help 查看。",
"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{}{
"content": map[string]interface{}{
"payload": map[string]interface{}{
"type": "string",
"description": "JSON 字符串，包含要发送的内容和路由信息。格式因通道而异，用 _help 工具查看详情。",
"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{"content"},
"required": []string{"payload", "type"},
},
},
})
@ -2100,7 +2119,7 @@ func (a *Agent) buildToolDefs() []interface{} {
"type": "function",
"function": map[string]interface{}{
"name": "output_send__" + ch.Name + "_help",
"description": "查看 " + ch.Name + " 输出通道的 JSON 格式说明和示例",
"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{}{},
@ -2425,12 +2444,16 @@ func (a *Agent) evaluateGraphQuality() {
// 选出低质量候选：generic 关系（如 distiller 自动生成的泛化关系）
var lowQuality []string
for _, r := range result.Relations {
// 自动蒸馏生成的 (用户, 提及, ...) 和 (AI, 回应, ...) 通常是噪音
// 自动蒸馏生成的 (用户, 提及, ...), (AI, 回应, ...) 和 jieba 共现 (..., 关联, ...) 通常是噪音
if (r.SourceName == "用户" || r.SourceName == "AI") &&
(r.RelationType == "提及" || r.RelationType == "回应") {
lowQuality = append(lowQuality, fmt.Sprintf("「%s」-「%s」→「%s」", r.SourceName, r.RelationType, r.TargetName))
continue
}
if r.RelationType == "关联" {
lowQuality = append(lowQuality, fmt.Sprintf("「%s」-「%s」→「%s」(jieba 共现)", r.SourceName, r.RelationType, r.TargetName))
continue
}
// 极低 mention 的实体+generic 关系
if r.Confidence < 0.3 && r.RelationType != "" {
lowQuality = append(lowQuality, fmt.Sprintf("「%s」-「%s」→「%s」(confidence=%.1f)", r.SourceName, r.RelationType, r.TargetName, r.Confidence))
@ -2518,32 +2541,42 @@ func docToTriples(doc *document.Doc) []memory.Triple {
}
triples = append(triples, memory.Triple{
Subject: "文档",
Relation: "包含内容",
Object: doc.Summary,
Subject: "文档",
SubjectType: "Concept",
Relation: "主题",
Object: doc.Summary,
ObjectType: "Topic",
Confidence: 1.0,
})
for _, entity := range doc.Entities {
triples = append(triples, memory.Triple{
Subject: "文档",
Relation: "提及实体",
Object: entity,
})
}
for _, tag := range doc.Tags {
triples = append(triples, memory.Triple{
Subject: "文档",
Relation: "标签",
Object: tag,
})
// 用 jieba 精确模式逐句分词 → 相邻词共现三元组
lines := strings.Split(doc.Content, "\n")
for _, line := range lines {
line = strings.TrimSpace(line)
if line == "" {
continue
}
terms := memory.CutExact(line)
for i := 0; i < len(terms)-1; i++ {
triples = append(triples, memory.Triple{
Subject: terms[i],
SubjectType: "Concept",
Relation: "关联",
Object: terms[i+1],
ObjectType: "Concept",
Confidence: 0.8,
})
}
}
if doc.Source != "" {
triples = append(triples, memory.Triple{
Subject: "文档",
Relation: "来源",
Object: doc.Source,
Subject: "文档",
SubjectType: "Concept",
Relation: "来源",
Object: doc.Source,
ObjectType: "Source",
Confidence: 1.0,
})
}
@ -2601,55 +2634,77 @@ func (a *Agent) processConsolidation(evt *agentIO.InputEvent, input string) {
// executeOutputSendTool — AI 通过指定通道发送消息（校验通道能力）
func (a *Agent) executeOutputSendTool(tc agentAPI.ToolCall) string {
// tool name is "output_send__{channel}"
channel := strings.TrimPrefix(tc.Name, "output_send__")
content, _ := tc.Arguments["content"].(string)
if channel == "" || content == "" {
return "工具名称格式: output_send__{channel}，content 不能为空"
payload, _ := tc.Arguments["payload"].(string)
rawType, _ := tc.Arguments["type"].(string)
if channel == "" || payload == "" || rawType == "" {
return "工具名称格式: output_send__{channel}，payload 和 type 不能为空"
}
// content 是一个 JSON 字符串，插件通过解析它确定如何发送消息
// === Stage: before_output — 输出前插件可审查/改写/拦截 ===
stageCtx := &sdk.StageContext{
FinalText: content,
Phase: sdk.StageBeforeOutput,
}
a.runStage(sdk.StageBeforeOutput, stageCtx)
if stageCtx.Response != nil {
return fmt.Sprintf("输出被插件拦截: %s", *stageCtx.Response)
}
content = stageCtx.FinalText
if content == "" {
return "输出被插件清空"
}
tc.Arguments["content"] = content
meta, _ := tc.Arguments["meta"].(string)
// 通道能力检查
caps := a.io.GetChannelCapabilities(channel)
if caps == 0 {
return fmt.Sprintf("通道 [%s] 不存在或不可用。可用输出工具列表见 output_list_channels", channel)
}
if !caps.Supports(agentIO.CapText) {
return fmt.Sprintf("通道 [%s] 不支持文本输出（能力: %s）", channel, caps.String())
switch rawType {
case "text":
if !caps.Supports(agentIO.CapText) {
return fmt.Sprintf("通道 [%s] 不支持文本输出（能力: %s）", channel, caps.String())
}
case "voice", "audio":
if !caps.Supports(agentIO.CapAudio) {
return fmt.Sprintf("通道 [%s] 不支持语音输出（能力: %s）", channel, caps.String())
}
case "image":
if !caps.Supports(agentIO.CapImage) {
return fmt.Sprintf("通道 [%s] 不支持图片输出（能力: %s）", channel, caps.String())
}
case "file":
if !caps.Supports(agentIO.CapFile) {
return fmt.Sprintf("通道 [%s] 不支持文件输出（能力: %s）", channel, caps.String())
}
}
// 组装参数传给设备处理器
args := map[string]interface{}{
"payload": payload,
"type": rawType,
}
if meta != "" {
args["meta"] = meta
}
// === Stage: before_output — 输出前插件可审查/改写/拦截 ===
stageCtx := &sdk.StageContext{
FinalText: payload,
Phase: sdk.StageBeforeOutput,
}
a.runStage(sdk.StageBeforeOutput, stageCtx)
if stageCtx.Response != nil {
return fmt.Sprintf("输出被插件拦截: %s", *stageCtx.Response)
}
if stageCtx.FinalText == "" {
return "输出被插件清空"
}
args["payload"] = stageCtx.FinalText
// 通过设备处理器投递
if dev := a.io.GetDevice(channel); dev != nil {
result, err := dev.Execute("output", tc.Arguments)
result, err := dev.Execute("output", args)
if err != nil {
return fmt.Sprintf("通过 [%s] 通道发送失败: %v", channel, err)
}
return fmt.Sprintf("已通过 [%s] 通道发送: %v", channel, result)
}
// 降级：发送到 outputCh（供 OutputChan 消费者）
a.io.EmitTextTo("agent_io", channel, content)
// 降级
a.io.EmitTextTo("agent_io", channel, payload)
return fmt.Sprintf("已通过 [%s] 通道发送", channel)
}
// executeOutputSendHelp — 返回指定通道的 JSON 格式说明
// executeOutputSendHelp — 返回指定通道的 meta 格式和 type 枚举
func (a *Agent) executeOutputSendHelp(tc agentAPI.ToolCall) string {
// tool name is "output_send__{channel}_help"
suffix := strings.TrimPrefix(tc.Name, "output_send__")
channel := strings.TrimSuffix(suffix, "_help")
if channel == "" {
@ -2676,13 +2731,24 @@ func (a *Agent) executeOutputSendHelp(tc agentAPI.ToolCall) string {
描述: %s
能力: %s
【content JSON 格式说明】
发送到此通道时 content 必须是 JSON 字符串，包含以下字段：
- "content": 消息正文（必填）
- 根据通道不同可能还需要路由字段（如 "group_id", "user_id" 等）
【参数说明】
payload — 消息载荷（必填）。type=text 时直接填文字，type=file/image 时填 URL 或路径
meta — JSON 对象，发送所需的元数据（可选，取决于通道是否需要路由信息）
type — 载荷类型（必填），枚举值见下方
请在通道描述中查看具体字段要求。
示例: {"content":"你好"}`, channel, desc, capStr)
【type 枚举】
- text — 文本消息
- voice — 语音消息
- image — 图片
- file — 文件
【meta JSON 格式】
由通道描述定义，通常包含：
- "group_id" 群号（群聊时必填）
- "user_id" 目标用户 QQ 号（私聊时必填）
- "reply_to" 回复某条消息 ID（可选）
示例: output_send__%s(payload="你好", meta="{\"group_id\": 123456789}", type="text")`, channel, desc, capStr, channel)
}
// executeOutputListChannels — 列出所有可用通道及其能力