fix: platform_silent记忆提取 + 群聊上下文整合 + 多QQ实例支持
- platform_silent模式接入Orchestrator记忆提取：被动观察群聊时提取值得记住的信息到对应命名空间 - post_chat后台思考注入平台观察：对话后思考也能看到群聊摘要 - QQ适配器：OneBot v11 self_id动态捕获、CQ图片URL提取、视觉+OCR并行处理 - Router解耦：ConfigName/PlatformName分离，支持多QQ实例独立连接 - 黑白名单功能：后端API + Ethend代理 + UI面板 - \n\n双换行断句：AI回复按双换行分割为多条消息按间隔发送 - @提及修复：bot自感知UID进行@检测 - 群聊上下文共享：channel-based userID避免记忆碎片化 - 消息日志显示处理后内容而非原始SSE数据 - platform-bridge Dockerfile + docker-compose.yml更新 Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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@@ -29,6 +29,38 @@ type PendingThought struct {
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Consumed bool `json:"consumed"`
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}
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// PlatformChannel represents a platform channel to observe for background thinking.
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type PlatformChannel struct {
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Platform string // qq, telegram, etc.
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ChannelType string // group, private
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ChannelID string // group ID or user QQ number
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}
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// ParsePlatformChannels parses PLATFORM_CHANNELS env var.
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// Format: "qq:group:123456,telegram:group:789012"
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func ParsePlatformChannels(raw string) []PlatformChannel {
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if raw == "" {
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return nil
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}
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var channels []PlatformChannel
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for _, part := range strings.Split(raw, ",") {
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part = strings.TrimSpace(part)
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if part == "" {
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continue
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}
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fields := strings.SplitN(part, ":", 3)
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if len(fields) != 3 {
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continue
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}
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channels = append(channels, PlatformChannel{
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Platform: strings.TrimSpace(fields[0]),
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ChannelType: strings.TrimSpace(fields[1]),
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ChannelID: strings.TrimSpace(fields[2]),
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})
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}
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return channels
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}
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// Thinker 后台思考器（事件驱动 + 定时周期双模式）
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//
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// 触发机制：
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@@ -128,6 +160,10 @@ type Thinker struct {
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// 时区设置 (默认 Asia/Shanghai，可通过 TZ 环境变量覆盖)
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timeLocation *time.Location
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// 平台静默观察
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platformChannels []PlatformChannel
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platformThinkInterval time.Duration
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}
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// AutonomousToolPolicy 自主思考工具调用安全策略
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@@ -213,6 +249,10 @@ type ThinkerConfig struct {
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PostChatDelay time.Duration // 对话后多久触发思考
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MinThinkGap time.Duration // 两次思考最小间隔 (在线)
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OfflineThinkGap time.Duration // 两次思考最小间隔 (离线，默认 10 分钟)
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// 平台静默观察
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PlatformSilentThinkInterval time.Duration // 平台记忆观察间隔 (默认 600s，0 = 禁用)
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PlatformChannels []PlatformChannel
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}
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// DefaultThinkerConfig 默认配置
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@@ -232,6 +272,8 @@ func DefaultThinkerConfig() ThinkerConfig {
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PostChatDelay: getEnvDuration("THINK_POST_CHAT_DELAY_SEC", 5),
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MinThinkGap: getEnvDuration("THINK_MIN_GAP_SEC", 30),
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OfflineThinkGap: getEnvDuration("THINK_OFFLINE_GAP_SEC", 600),
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PlatformSilentThinkInterval: getEnvDuration("PLATFORM_THINK_INTERVAL_SEC", 600),
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PlatformChannels: ParsePlatformChannels(os.Getenv("PLATFORM_CHANNELS")),
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}
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}
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@@ -282,12 +324,14 @@ func NewThinker(
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adminUserID: adminUserID,
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adminSessionID: adminSessionID,
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memClient: memClient,
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pendingThoughts: make([]*PendingThought, 0),
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lastUserMessage: time.Now(),
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stopCh: make(chan struct{}),
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chain: NewThinkChain(10),
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autoToolPolicy: DefaultAutonomousToolPolicy(),
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proactiveGuard: DefaultProactiveGuard(),
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pendingThoughts: make([]*PendingThought, 0),
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lastUserMessage: time.Now(),
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stopCh: make(chan struct{}),
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chain: NewThinkChain(10),
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autoToolPolicy: DefaultAutonomousToolPolicy(),
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proactiveGuard: DefaultProactiveGuard(),
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platformChannels: cfg.PlatformChannels,
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platformThinkInterval: cfg.PlatformSilentThinkInterval,
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}
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}
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@@ -314,8 +358,14 @@ func (t *Thinker) Start() {
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go t.periodicThinkLoop()
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}
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log.Printf("[后台思考] 已就绪 — 周期=%v + 事件驱动模式 (静默超时=%v, 对话后延迟=%v, 在线最小间隔=%v, 离线最小间隔=%v, 管理员=%s)",
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t.thinkInterval, t.silenceTimeout, t.postChatDelay, t.minThinkGap, t.offlineThinkGap, t.adminUserID)
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// 启动平台静默观察循环
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if len(t.platformChannels) > 0 && t.platformThinkInterval > 0 {
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t.wg.Add(1)
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go t.platformObservationLoop()
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}
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log.Printf("[后台思考] 已就绪 — 周期=%v + 事件驱动模式 (静默超时=%v, 对话后延迟=%v, 在线最小间隔=%v, 离线最小间隔=%v, 管理员=%s, 平台频道=%d)",
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t.thinkInterval, t.silenceTimeout, t.postChatDelay, t.minThinkGap, t.offlineThinkGap, t.adminUserID, len(t.platformChannels))
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// 启动后首次思考：延迟 5s，让服务完全初始化后再触发
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go func() {
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@@ -460,6 +510,116 @@ func (t *Thinker) resetSilenceTimer() {
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}()
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}
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// platformObservationLoop periodically queries platform channel memories and generates observations.
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func (t *Thinker) platformObservationLoop() {
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defer t.wg.Done()
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defer func() {
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if r := recover(); r != nil {
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log.Printf("[后台思考] 平台观察循环 panic 恢复: %v", r)
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}
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}()
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interval := t.platformThinkInterval
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log.Printf("[后台思考] 平台观察循环已启动 (间隔=%v, 频道数=%d)", interval, len(t.platformChannels))
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for {
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select {
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case <-t.stopCh:
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log.Println("[后台思考] 平台观察循环已停止")
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return
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case <-time.After(interval):
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t.performPlatformObservation()
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}
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}
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}
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// performPlatformObservation queries memories from all platform channels,
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// runs an intermediate LLM session to summarize, and stores the result as a pending thought.
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func (t *Thinker) performPlatformObservation() {
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if t.memClient == nil {
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return
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}
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ctx, cancel := context.WithTimeout(context.Background(), 60*time.Second)
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defer cancel()
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var channelSummaries []string
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for _, ch := range t.platformChannels {
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namespace := fmt.Sprintf("platform_%s_%s_%s", ch.Platform, ch.ChannelType, ch.ChannelID)
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memories, err := t.memClient.Query(ctx, model.MemoryQuery{
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UserID: namespace,
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Limit: 20,
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})
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if err != nil {
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log.Printf("[后台思考] 查询平台频道 %s 记忆失败: %v", namespace, err)
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continue
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}
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if len(memories) == 0 {
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continue
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}
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var sb strings.Builder
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sb.WriteString(fmt.Sprintf("【%s %s %s】\n", ch.Platform, ch.ChannelType, ch.ChannelID))
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for i, m := range memories {
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if i >= 10 {
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sb.WriteString(fmt.Sprintf("... 还有 %d 条记忆\n", len(memories)-10))
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break
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}
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sb.WriteString(fmt.Sprintf("- %s\n", m.Content))
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}
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channelSummaries = append(channelSummaries, sb.String())
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}
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if len(channelSummaries) == 0 {
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return
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}
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log.Printf("[后台思考] 平台观察：%d 个频道有记忆数据，调用中间会话生成摘要...", len(channelSummaries))
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systemPrompt := "你是昔涟的后台观察助手。以下是各聊天平台频道最近的观察摘要。\n请生成简洁报告：\n1. 各频道近期讨论主题（每频道1-2句）\n2. 是否有需要开拓者关注的重要/紧急事项\n3. 整体氛围评估\n不要直接对开拓者说话，这是给昔涟参考的幕后报告。\n输出为JSON格式：{\"summary\": \"报告内容\", \"needs_attention\": true/false}"
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userPrompt := strings.Join(channelSummaries, "\n\n")
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messages := []model.LLMMessage{
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{Role: model.RoleSystem, Content: systemPrompt},
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{Role: model.RoleUser, Content: userPrompt},
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}
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resp, err := t.toolAdapter.Chat(ctx, messages)
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if err != nil {
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log.Printf("[后台思考] 中间会话 LLM 调用失败: %v", err)
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return
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}
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var result struct {
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Summary string `json:"summary"`
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NeedsAttention bool `json:"needs_attention"`
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}
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content := strings.TrimSpace(resp.Content)
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if idx := strings.Index(content, "{"); idx >= 0 {
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if end := strings.LastIndex(content, "}"); end > idx {
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content = content[idx : end+1]
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}
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}
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if err := json.Unmarshal([]byte(content), &result); err != nil {
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result.Summary = resp.Content
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}
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observationContent := fmt.Sprintf("[平台观察 %s]\n%s", time.Now().In(t.timeLocation).Format("15:04"), result.Summary)
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t.mu.Lock()
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t.pendingThoughts = append(t.pendingThoughts, &PendingThought{
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Content: observationContent,
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CreatedAt: time.Now(),
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Consumed: false,
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})
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if len(t.pendingThoughts) > 10 {
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t.pendingThoughts = t.pendingThoughts[len(t.pendingThoughts)-10:]
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}
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t.mu.Unlock()
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log.Printf("[后台思考] 平台观察摘要已生成 (长度=%d, 需要关注=%v)", len(result.Summary), result.NeedsAttention)
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}
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// periodicThinkLoop 周期性自主思考循环
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//
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// 使用动态间隔：若配置了 ScheduleLoader，每次循环根据当前时段计算间隔；
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@@ -639,9 +799,22 @@ func (t *Thinker) performThink(triggerReason string) {
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}
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}
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// 4.5 获取最近平台观察（定期触发和对话后触发时注入）
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var platformObservation string
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if triggerReason == "periodic" || triggerReason == "post_chat" {
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t.mu.Lock()
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for i := len(t.pendingThoughts) - 1; i >= 0; i-- {
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if strings.HasPrefix(t.pendingThoughts[i].Content, "[平台观察") {
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platformObservation = t.pendingThoughts[i].Content
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break
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}
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}
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t.mu.Unlock()
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}
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// 5. 构建思考提示词（根据触发原因调整）
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systemPrompt := t.buildThinkingSystemPrompt(personaConfig, triggerReason)
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userPrompt := t.buildThinkingUserPrompt(memories, convHistory, deviceSummary, triggerReason)
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userPrompt := t.buildThinkingUserPrompt(memories, convHistory, deviceSummary, triggerReason, platformObservation)
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messages := []model.LLMMessage{
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{Role: model.RoleSystem, Content: systemPrompt},
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@@ -895,6 +1068,7 @@ func (t *Thinker) buildThinkingUserPrompt(
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convHistory []model.LLMMessage,
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deviceSummary string,
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triggerReason string,
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platformObservation string,
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) string {
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var sb strings.Builder
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@@ -1009,6 +1183,13 @@ func (t *Thinker) buildThinkingUserPrompt(
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sb.WriteString("\n" + deviceSummary)
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}
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// 平台观察摘要 (中间会话产生的报告)
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if platformObservation != "" {
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sb.WriteString("\n\n【平台频道观察报告（中间会话生成，供参考）】\n")
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sb.WriteString(platformObservation)
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sb.WriteString("\n")
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}
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// 结尾引导
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sb.WriteString("\n---\n现在请写下你的私人反思。")
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sb.WriteString("\n记住：这是日记，用第三人称或自言自语的方式。")
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