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