65 lines
2.1 KiB
Python

"""Configuration for memory mechanism."""
from pydantic import BaseModel, ConfigDict, Field
class MemoryConfig(BaseModel):
"""Configuration for global memory mechanism."""
model_config = ConfigDict(frozen=True)
enabled: bool = Field(
default=True,
description="Whether to enable memory mechanism",
)
storage_path: str = Field(
default="",
description=(
"Path to store memory data. "
"If empty, defaults to per-user memory at `{base_dir}/users/{user_id}/memory.json`. "
"Absolute paths are used as-is and opt out of per-user isolation "
"(all users share the same file). "
"Relative paths are resolved against `Paths.base_dir` "
"(not the backend working directory). "
"Note: if you previously set this to `.deer-flow/memory.json`, "
"the file will now be resolved as `{base_dir}/.deer-flow/memory.json`; "
"migrate existing data or use an absolute path to preserve the old location."
),
)
storage_class: str = Field(
default="deerflow.agents.memory.storage.FileMemoryStorage",
description="The class path for memory storage provider",
)
debounce_seconds: int = Field(
default=30,
ge=1,
le=300,
description="Seconds to wait before processing queued updates (debounce)",
)
model_name: str | None = Field(
default=None,
description="Model name to use for memory updates (None = use default model)",
)
max_facts: int = Field(
default=100,
ge=10,
le=500,
description="Maximum number of facts to store",
)
fact_confidence_threshold: float = Field(
default=0.7,
ge=0.0,
le=1.0,
description="Minimum confidence threshold for storing facts",
)
injection_enabled: bool = Field(
default=True,
description="Whether to inject memory into system prompt",
)
max_injection_tokens: int = Field(
default=2000,
ge=100,
le=8000,
description="Maximum tokens to use for memory injection",
)