memory

type Chunk struct {
	// FileID identifies the source file (relative path).
	FileID string

	// Index is the chunk position within the file (0-based).
	Index int

	// Text is the chunk content.
	Text string

	// Hash is the SHA-256 hex digest of the chunk text.
	Hash string
}

type ChunkConfig struct {
	// MaxTokens is the approximate max tokens per chunk (default: 500).
	// Uses ~4 chars/token heuristic.
	MaxTokens int

	// Overlap is the number of characters to overlap between chunks (default: 100).
	Overlap int
}

type EmbeddingConfig struct {
	// Provider is the embedding provider ("openai", "gemini", "voyage", "mistral", "auto", "none").
	Provider string `yaml:"provider"`

	// Model is the embedding model name (e.g. "text-embedding-3-small").
	Model string `yaml:"model"`

	// Dimensions is the output vector dimensionality (default: auto from model).
	Dimensions int `yaml:"dimensions"`

	// APIKey is the API key for the embedding provider. If empty, falls back to
	// the main LLM API key or provider-specific env vars.
	APIKey string `yaml:"api_key"`

	// BaseURL is the API base URL. If empty, uses the provider default.
	BaseURL string `yaml:"base_url"`

	// Cache enables embedding caching in SQLite (default: true).
	Cache bool `yaml:"cache"`

	// Fallback is the fallback provider when the primary fails ("openai", "gemini", etc., or "none").
	Fallback string `yaml:"fallback"`

	// FallbackAPIKey is the API key for the fallback provider.
	FallbackAPIKey string `yaml:"fallback_api_key"`

	// FallbackBaseURL is the base URL for the fallback provider.
	FallbackBaseURL string `yaml:"fallback_base_url"`

	// FallbackModel is the model for the fallback provider.
	FallbackModel string `yaml:"fallback_model"`
}

type EmbeddingProvider interface {
	// Embed generates embeddings for a batch of texts.
	// Returns one float32 vector per input text.
	Embed(ctx context.Context, texts []string) ([][]float32, error)

	// Dimensions returns the dimensionality of the output vectors.
	Dimensions() int

	// Name returns the provider name (for cache key derivation).
	Name() string

	// Model returns the model name (for cache key derivation).
	Model() string
}

type Entry struct {
	Content   string    `json:"content"`
	Source    string    `json:"source"`   // "user", "agent", "system"
	Category  string    `json:"category"` // "fact", "preference", "event", "summary"
	Timestamp time.Time `json:"timestamp"`
}

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

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

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

type MMRConfig struct {
	Enabled bool
	Lambda  float64
}

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

type NullEmbedder struct{}

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

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

type SearchResult struct {
	FileID string
	Text   string
	Score  float64
}

type Store interface {
	// Save persists a new memory entry.
	Save(entry Entry) error

	// Search returns entries matching the query, limited to maxResults.
	Search(query string, maxResults int) ([]Entry, error)

	// GetRecent returns the most recent entries up to limit.
	GetRecent(limit int) ([]Entry, error)

	// GetByDate returns entries for a specific date.
	GetByDate(date time.Time) ([]Entry, error)

	// GetAll returns all stored entries.
	GetAll() ([]Entry, error)

	// SaveDailyLog appends a summary to the daily log file.
	SaveDailyLog(date time.Time, content string) error
}

type TemporalDecayConfig struct {
	Enabled      bool
	HalfLifeDays float64
}

type TranscriptEntry struct {
	Role    string // "user" or "assistant"
	Content string
}

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