feat: Phase 1+2 架构进化 — 连续思考链/主动消息决策/情感状态机/离线自主思考 (86文件)

Phase 1 (基础设施): - ThinkChain 思考链连续性 + 差异化思考提示词 (persistent) - AutonomousToolPolicy 工具安全策略 (safe/unsafe/conditional) - MessageScheduler 自适应消息节奏 (Idle/Available/Busy) - SessionEnrichmentStore 渐进式上下文丰富 (5层) - ConversationBus 事件总线 + ResponseCache (dedup) - pkg/logger 统一日志 + 所有 handler 替换 fmt.Printf - NPE 守卫/链路优化/数据库表修复/Go workspace Phase 2 (人格交互): - EmotionState/EmotionTracker 情感状态机 (5种心情, 情绪衰减) - ProactiveGuard 主动消息多维决策 (静默时段/紧急度/频率/校验) - Gateway↔ai-core 在线状态感知链路 (presence notification) - 离线思考频率控制 + 重连问候 + 离线消息排队 Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-23 15:25:12 +08:00
parent b123a36aae
commit 87214b9441
86 changed files with 3085 additions and 582 deletions
@@ -0,0 +1,165 @@
+package background
+
+import (
+	"crypto/rand"
+	"fmt"
+	"strings"
+	"sync"
+	"time"
+)
+
+// ThinkRecord is a single thinking session's result.
+type ThinkRecord struct {
+	ID          string    `json:"id"`
+	Content     string    `json:"content"`
+	Conclusions []string  `json:"conclusions"` // key takeaways
+	FollowUps   []string  `json:"follow_ups"`  // questions to continue
+	ToolCalls   int       `json:"tool_calls"`
+	Trigger     string    `json:"trigger"` // post_chat, silence, periodic
+	Timestamp   time.Time `json:"timestamp"`
+}
+
+// ThinkChain stores linked thinking records so each round
+// can build on previous conclusions.
+type ThinkChain struct {
+	mu      sync.Mutex
+	records []ThinkRecord
+	maxSize int
+}
+
+// NewThinkChain creates a think chain with the given max size.
+func NewThinkChain(maxSize int) *ThinkChain {
+	if maxSize <= 0 {
+		maxSize = 10
+	}
+	return &ThinkChain{
+		records: make([]ThinkRecord, 0, maxSize),
+		maxSize: maxSize,
+	}
+}
+
+// Add appends a new think record, evicting oldest if at capacity.
+func (c *ThinkChain) Add(r ThinkRecord) {
+	c.mu.Lock()
+	defer c.mu.Unlock()
+	if len(c.records) >= c.maxSize {
+		c.records = c.records[1:]
+	}
+	c.records = append(c.records, r)
+}
+
+// LastConclusions returns conclusions from the most recent N records.
+func (c *ThinkChain) LastConclusions(n int) []string {
+	c.mu.Lock()
+	defer c.mu.Unlock()
+	var result []string
+	start := len(c.records) - n
+	if start < 0 {
+		start = 0
+	}
+	for _, r := range c.records[start:] {
+		result = append(result, r.Conclusions...)
+	}
+	return result
+}
+
+// LastFollowUps returns follow-up questions from the single most recent record.
+func (c *ThinkChain) LastFollowUps() []string {
+	c.mu.Lock()
+	defer c.mu.Unlock()
+	if len(c.records) == 0 {
+		return nil
+	}
+	return c.records[len(c.records)-1].FollowUps
+}
+
+// LastTopic attempts to infer a topic from recent conclusions.
+func (c *ThinkChain) LastTopic() string {
+	c.mu.Lock()
+	defer c.mu.Unlock()
+	if len(c.records) == 0 {
+		return ""
+	}
+	// Use first conclusion line of the most recent record as topic
+	for _, r := range c.records {
+		for _, c := range r.Conclusions {
+			if c != "" {
+				runes := []rune(c)
+				if len(runes) > 50 {
+					return string(runes[:50]) + "..."
+				}
+				return c
+			}
+		}
+	}
+	return ""
+}
+
+// Size returns the current number of records in the chain.
+func (c *ThinkChain) Size() int {
+	c.mu.Lock()
+	defer c.mu.Unlock()
+	return len(c.records)
+}
+
+// extractConclusions parses the LLM thinking output to find conclusions and follow-ups.
+// Looks for "结论" / "后续" markers in the content.
+func extractConclusions(content string) (conclusions []string, followUps []string) {
+	lines := strings.Split(content, "\n")
+	inConclusions := false
+	inFollowUps := false
+
+	for _, line := range lines {
+		line = strings.TrimSpace(line)
+
+		if strings.Contains(line, "结论") && (strings.Contains(line, "💭") || strings.Contains(line, "📝") || strings.HasPrefix(line, "-")) {
+			// Heuristic: this line starts a conclusions section
+		}
+
+		// Match bullet-point conclusions: lines starting with - or •
+		if (strings.HasPrefix(line, "- ") || strings.HasPrefix(line, "• ")) && !inFollowUps {
+			text := strings.TrimPrefix(line, "- ")
+			text = strings.TrimPrefix(text, "• ")
+			text = strings.TrimSpace(text)
+			if text != "" && len([]rune(text)) > 2 {
+				if inConclusions {
+					conclusions = append(conclusions, text)
+				} else {
+					// Without explicit marker, treat all bullets as conclusions
+					conclusions = append(conclusions, text)
+				}
+			}
+			continue
+		}
+
+		// Detect section transitions
+		if strings.Contains(line, "后续") || strings.Contains(line, "继续思考") || strings.Contains(line, "下次") {
+			inFollowUps = true
+			inConclusions = false
+			continue
+		}
+		if strings.Contains(line, "结论") || strings.Contains(line, "观察") || strings.Contains(line, "记忆") {
+			inConclusions = true
+			inFollowUps = false
+			continue
+		}
+	}
+
+	// If no structured markers found, treat the whole content as a single conclusion
+	if len(conclusions) == 0 {
+		runes := []rune(content)
+		if len(runes) > 200 {
+			content = string(runes[:200]) + "..."
+		}
+		conclusions = []string{content}
+	}
+
+	return conclusions, followUps
+}
+
+// generateID generates a short random ID.
+func generateID() string {
+	b := make([]byte, 6)
+	rand.Read(b)
+	return fmt.Sprintf("th-%x", b)
+}