memory

type Config struct {
	MaxRecentRounds   int // 保留最近几轮讨论，默认 3
	MaxKeyFacts       int // 最大关键事实数，默认 20
	MaxSummaryLength  int // 摘要最大字数，默认 300
	CompressThreshold int // 触发压缩的轮次数，默认 5
}

type DiscussionInput struct {
	AgentName string
	Role      string
	Content   string
}

type EntryType string

type FileStorage struct {
	// contains filtered or unexported fields
}

type GseTokenizer struct {
	// contains filtered or unexported fields
}

type LLMSummarizer struct {
	// contains filtered or unexported fields
}

type Manager struct {
	// contains filtered or unexported fields
}

type MemoryEntry struct {
	ID        string    `json:"id"`
	Type      EntryType `json:"type"`
	Content   string    `json:"content"`
	Source    string    `json:"source"`   // 来源 Agent
	Keywords  []string  `json:"keywords"` // 关键词（用于文本匹配）
	Timestamp int64     `json:"timestamp"`
	Weight    float64   `json:"weight"` // 重要性权重 0-1
}

type Relevance struct {
	// contains filtered or unexported fields
}

type RoundMemory struct {
	Round     int      `json:"round"`
	Query     string   `json:"query"`      // 用户问题
	Consensus string   `json:"consensus"`  // 本轮结论
	KeyPoints []string `json:"key_points"` // 要点
	Timestamp int64    `json:"timestamp"`
}

type ScoredEntry struct {
	Entry MemoryEntry
	Score float64
}

type StockMemory struct {
	StockCode    string        `json:"stock_code"`
	StockName    string        `json:"stock_name"`
	Summary      string        `json:"summary"`       // 历史摘要
	KeyFacts     []MemoryEntry `json:"key_facts"`     // 关键事实
	RecentRounds []RoundMemory `json:"recent_rounds"` // 最近几轮讨论
	TotalRounds  int           `json:"total_rounds"`  // 总讨论轮次
	CreatedAt    int64         `json:"created_at"`
	UpdatedAt    int64         `json:"updated_at"`
}

type Storage interface {
	Load(stockCode string) (*StockMemory, error)
	Save(mem *StockMemory) error
	Delete(stockCode string) error
	List() ([]string, error)
}

type Summarizer interface {
	SummarizeRounds(ctx context.Context, rounds []RoundMemory) (string, error)
	ExtractFacts(ctx context.Context, content, agentName string) ([]MemoryEntry, error)
	ExtractKeyPoints(ctx context.Context, discussions []DiscussionInput) ([]string, error)
}

type Tokenizer interface {
	Extract(text string, topK int) []string
	Cut(text string) []string
}