106 lines
3.7 KiB
Python
106 lines
3.7 KiB
Python
"""记忆模块跨层共享的数据契约。
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这些模型只描述记忆模块与客服 Agent 之间的输入输出，不绑定 Redis、MySQL、
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Milvus 或 Neo4j 的实现细节。
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"""
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from __future__ import annotations
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from datetime import datetime
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from enum import StrEnum
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from typing import Any
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from pydantic import BaseModel, ConfigDict, Field
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class MemoryType(StrEnum):
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"""客服记忆可以保存的业务类型。"""
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PROFILE_FACT = "PROFILE_FACT"
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PROFILE_CANDIDATE = "PROFILE_CANDIDATE"
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CUSTOMER_PREFERENCE = "CUSTOMER_PREFERENCE"
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INVESTMENT_GOAL = "INVESTMENT_GOAL"
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SERVICE_FACT = "SERVICE_FACT"
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CUSTOMER_RELATION = "CUSTOMER_RELATION"
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class MemoryStatus(StrEnum):
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"""记忆生命周期状态。"""
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CANDIDATE = "candidate"
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CONFIRMED = "confirmed"
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EXPIRED = "expired"
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REJECTED = "rejected"
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ARCHIVED = "archived"
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class MemorySource(StrEnum):
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"""客服对话形成记忆的证据来源。"""
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DIALOGUE_CONFIRMED = "dialogue_confirmed"
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DIALOGUE_STATED = "dialogue_stated"
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DIALOGUE_INFERRED = "dialogue_inferred"
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class ShortTermMessage(BaseModel):
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"""Redis 短期会话中的一条消息。"""
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model_config = ConfigDict(extra="forbid")
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message_id: str = Field(min_length=1, max_length=64)
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session_id: str = Field(min_length=1, max_length=64)
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role: str = Field(min_length=1, max_length=16)
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content: str = Field(min_length=1)
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token_count: int = Field(default=0, ge=0)
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agent_run_id: str | None = Field(default=None, max_length=64)
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tool_calls: list[dict[str, Any]] = Field(default_factory=list)
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create_time: datetime | None = None
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class MemoryUnitDTO(BaseModel):
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"""统一表示一条客户记忆，供写入、召回和重排使用。"""
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model_config = ConfigDict(extra="forbid")
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id: int | None = None
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customer_id: int
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session_id: str | None = Field(default=None, max_length=64)
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agent_run_id: str | None = Field(default=None, max_length=64)
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memory_type: MemoryType
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tag: str = Field(min_length=1, max_length=64)
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content: str = Field(min_length=1, max_length=512)
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info_type: str = Field(default="FACT", min_length=1, max_length=8)
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source: MemorySource
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evidence_ref: list[dict[str, Any]] = Field(default_factory=list)
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source_confidence: float = Field(default=0.2, ge=0.0, le=1.0)
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confidence: float = Field(default=0.2, ge=0.0, le=1.0)
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historical_accuracy: float = Field(default=0.5, ge=0.0, le=1.0)
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confidence_version: str | None = Field(default=None, max_length=32)
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confidence_reason: str | None = Field(default=None, max_length=255)
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confidence_update_time: datetime | None = None
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final_score: float | None = Field(default=None, ge=0.0, le=1.0)
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evidence_count: int = Field(default=0, ge=0)
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recall_count: int = Field(default=0, ge=0)
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status: MemoryStatus = MemoryStatus.CANDIDATE
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valid_from: datetime | None = None
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valid_until: datetime | None = None
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last_verified_at: datetime | None = None
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milvus_id: str | None = Field(default=None, max_length=128)
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graph_node_id: str | None = Field(default=None, max_length=128)
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class CustomerMemoryContext(BaseModel):
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"""客服 Agent 每轮请求可使用的统一记忆上下文。"""
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model_config = ConfigDict(extra="forbid")
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customer_id: int
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session_id: str
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short_term_messages: list[ShortTermMessage] = Field(default_factory=list)
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customer_profile: dict[str, Any] | None = None
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work_orders: list[dict[str, Any]] = Field(default_factory=list)
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long_term_memories: list[MemoryUnitDTO] = Field(default_factory=list)
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customer_relations: list[dict[str, Any]] = Field(default_factory=list)
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customer_products: list[dict[str, Any]] = Field(default_factory=list)
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warnings: list[str] = Field(default_factory=list)
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