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55 lines
1.9 KiB
Python
55 lines
1.9 KiB
Python
import datetime
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from typing import Dict, List
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from pydantic import Field, BaseModel
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from memory_scope.utils.tool_functions import md5_hash
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class MemoryNode(BaseModel):
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memory_id: str = Field("", description="unique id for memory")
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user_name: str = Field("", description="the user who owns the memory")
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target_name: str = Field("", description="target name described by the memory")
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meta_data: Dict[str, str] = Field({}, description="meta data infos")
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content: str = Field("", description="memory content")
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key: str = Field("", description="memory key")
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value: str = Field("", description="memory value")
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score_similar: float = Field(0, description="es similar score")
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score_rank: float = Field(0, description="rank model score")
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score_rerank: float = Field(0, description="rerank score")
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memory_type: str = Field("", description="conversation/observation/insight...")
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status: str = Field("active", description="active or expired")
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vector: List[float] = Field([], description="content embedding result, return empty")
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timestamp: int = Field(int(datetime.datetime.now().timestamp()), description="timestamp of the memory node")
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dt: str = Field("", description="dt of the memory node")
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obs_reflected: bool = Field(False, description="if the observation is reflected")
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obs_updated: bool = Field(False, description="if the observation has updated user profile or insight")
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def __init__(self, **kwargs):
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super().__init__(**kwargs)
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self.memory_id = f"{self.user_name}_{self.target_name}_{self.timestamp}_{md5_hash(self.content)[:8]}"
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self.dt = datetime.datetime.fromtimestamp(self.timestamp).strftime("%Y%m%d")
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@property
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def node_keys(self):
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return list(self.model_json_schema()["properties"].keys())
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def __getitem__(self, key: str):
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return self.model_dump().get(key)
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