deer-flow/backend/packages/harness/deerflow/agents/memory/storage.py

"""Memory storage providers."""

import abc
import json
import logging
import threading
from datetime import UTC, datetime
from pathlib import Path
from typing import Any

from deerflow.config.agents_config import AGENT_NAME_PATTERN
from deerflow.config.memory_config import MemoryConfig
from deerflow.config.paths import get_paths

logger = logging.getLogger(__name__)


def utc_now_iso_z() -> str:
    """Current UTC time as ISO-8601 with ``Z`` suffix (matches prior naive-UTC output)."""
    return datetime.now(UTC).isoformat().removesuffix("+00:00") + "Z"


def create_empty_memory() -> dict[str, Any]:
    """Create an empty memory structure."""
    return {
        "version": "1.0",
        "lastUpdated": utc_now_iso_z(),
        "user": {
            "workContext": {"summary": "", "updatedAt": ""},
            "personalContext": {"summary": "", "updatedAt": ""},
            "topOfMind": {"summary": "", "updatedAt": ""},
        },
        "history": {
            "recentMonths": {"summary": "", "updatedAt": ""},
            "earlierContext": {"summary": "", "updatedAt": ""},
            "longTermBackground": {"summary": "", "updatedAt": ""},
        },
        "facts": [],
    }


class MemoryStorage(abc.ABC):
    """Abstract base class for memory storage providers."""

    @abc.abstractmethod
    def load(self, agent_name: str | None = None, *, user_id: str | None = None) -> dict[str, Any]:
        """Load memory data for the given agent."""
        pass

    @abc.abstractmethod
    def reload(self, agent_name: str | None = None, *, user_id: str | None = None) -> dict[str, Any]:
        """Force reload memory data for the given agent."""
        pass

    @abc.abstractmethod
    def save(self, memory_data: dict[str, Any], agent_name: str | None = None, *, user_id: str | None = None) -> bool:
        """Save memory data for the given agent."""
        pass


class FileMemoryStorage(MemoryStorage):
    """File-based memory storage provider."""

    def __init__(self, memory_config: MemoryConfig):
        """Initialize the file memory storage.

        Args:
            memory_config: Memory configuration (storage_path etc.). Stored on
                the instance so per-request lookups don't need to reach for
                ambient state.
        """
        self._memory_config = memory_config
        # Per-user/agent memory cache: keyed by (user_id, agent_name) tuple (None = global)
        # Value: (memory_data, file_mtime)
        self._memory_cache: dict[tuple[str | None, str | None], tuple[dict[str, Any], float | None]] = {}

    def _validate_agent_name(self, agent_name: str) -> None:
        """Validate that the agent name is safe to use in filesystem paths.

        Uses the repository's established AGENT_NAME_PATTERN to ensure consistency
        across the codebase and prevent path traversal or other problematic characters.
        """
        if not agent_name:
            raise ValueError("Agent name must be a non-empty string.")
        if not AGENT_NAME_PATTERN.match(agent_name):
            raise ValueError(f"Invalid agent name {agent_name!r}: names must match {AGENT_NAME_PATTERN.pattern}")

    def _get_memory_file_path(self, agent_name: str | None = None, *, user_id: str | None = None) -> Path:
        """Get the path to the memory file."""
        config = self._memory_config
        if user_id is not None:
            if agent_name is not None:
                self._validate_agent_name(agent_name)
                return get_paths().user_agent_memory_file(user_id, agent_name)
            if config.storage_path and Path(config.storage_path).is_absolute():
                return Path(config.storage_path)
            return get_paths().user_memory_file(user_id)
        # Legacy: no user_id
        if agent_name is not None:
            self._validate_agent_name(agent_name)
            return get_paths().agent_memory_file(agent_name)
        if config.storage_path:
            p = Path(config.storage_path)
            return p if p.is_absolute() else get_paths().base_dir / p
        return get_paths().memory_file

    def _load_memory_from_file(self, agent_name: str | None = None, *, user_id: str | None = None) -> dict[str, Any]:
        """Load memory data from file."""
        file_path = self._get_memory_file_path(agent_name, user_id=user_id)

        if not file_path.exists():
            return create_empty_memory()

        try:
            with open(file_path, encoding="utf-8") as f:
                data = json.load(f)
            return data
        except (json.JSONDecodeError, OSError) as e:
            logger.warning("Failed to load memory file: %s", e)
            return create_empty_memory()

    def load(self, agent_name: str | None = None, *, user_id: str | None = None) -> dict[str, Any]:
        """Load memory data (cached with file modification time check)."""
        file_path = self._get_memory_file_path(agent_name, user_id=user_id)

        try:
            current_mtime = file_path.stat().st_mtime if file_path.exists() else None
        except OSError:
            current_mtime = None

        cache_key = (user_id, agent_name)
        cached = self._memory_cache.get(cache_key)

        if cached is None or cached[1] != current_mtime:
            memory_data = self._load_memory_from_file(agent_name, user_id=user_id)
            self._memory_cache[cache_key] = (memory_data, current_mtime)
            return memory_data

        return cached[0]

    def reload(self, agent_name: str | None = None, *, user_id: str | None = None) -> dict[str, Any]:
        """Reload memory data from file, forcing cache invalidation."""
        file_path = self._get_memory_file_path(agent_name, user_id=user_id)
        memory_data = self._load_memory_from_file(agent_name, user_id=user_id)

        try:
            mtime = file_path.stat().st_mtime if file_path.exists() else None
        except OSError:
            mtime = None

        cache_key = (user_id, agent_name)
        self._memory_cache[cache_key] = (memory_data, mtime)
        return memory_data

    def save(self, memory_data: dict[str, Any], agent_name: str | None = None, *, user_id: str | None = None) -> bool:
        """Save memory data to file and update cache."""
        file_path = self._get_memory_file_path(agent_name, user_id=user_id)

        try:
            file_path.parent.mkdir(parents=True, exist_ok=True)
            memory_data["lastUpdated"] = utc_now_iso_z()

            temp_path = file_path.with_suffix(".tmp")
            with open(temp_path, "w", encoding="utf-8") as f:
                json.dump(memory_data, f, indent=2, ensure_ascii=False)

            temp_path.replace(file_path)

            try:
                mtime = file_path.stat().st_mtime
            except OSError:
                mtime = None

            cache_key = (user_id, agent_name)
            self._memory_cache[cache_key] = (memory_data, mtime)
            logger.info("Memory saved to %s", file_path)
            return True
        except OSError as e:
            logger.error("Failed to save memory file: %s", e)
            return False


# Instances keyed by (storage_class_path, id(memory_config)) so tests can
# construct isolated storages and multi-client setups with different configs
# don't collide on a single process-wide singleton.
_storage_instances: dict[tuple[str, int], MemoryStorage] = {}
_storage_lock = threading.Lock()


def get_memory_storage(memory_config: MemoryConfig) -> MemoryStorage:
    """Get the configured memory storage instance.

    Caches one instance per ``(storage_class, memory_config)`` pair. In
    single-config deployments this collapses to one instance; in multi-client
    or test scenarios each config gets its own storage.
    """
    key = (memory_config.storage_class, id(memory_config))
    existing = _storage_instances.get(key)
    if existing is not None:
        return existing

    with _storage_lock:
        existing = _storage_instances.get(key)
        if existing is not None:
            return existing

        storage_class_path = memory_config.storage_class
        try:
            module_path, class_name = storage_class_path.rsplit(".", 1)
            import importlib

            module = importlib.import_module(module_path)
            storage_class = getattr(module, class_name)

            # Validate that the configured storage is a MemoryStorage implementation
            if not isinstance(storage_class, type):
                raise TypeError(f"Configured memory storage '{storage_class_path}' is not a class: {storage_class!r}")
            if not issubclass(storage_class, MemoryStorage):
                raise TypeError(f"Configured memory storage '{storage_class_path}' is not a subclass of MemoryStorage")

            instance = storage_class(memory_config)
        except Exception as e:
            logger.error(
                "Failed to load memory storage %s, falling back to FileMemoryStorage: %s",
                storage_class_path,
                e,
            )
            instance = FileMemoryStorage(memory_config)

        _storage_instances[key] = instance
        return instance