"""记忆模块跨层共享的数据契约。

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、
Milvus 或 Neo4j 的实现细节。
"""

from __future__ import annotations

from datetime import datetime
from enum import StrEnum
from typing import Any

from pydantic import BaseModel, ConfigDict, Field


class MemoryType(StrEnum):
    """客服记忆可以保存的业务类型。"""

    PROFILE_FACT = "PROFILE_FACT"
    PROFILE_CANDIDATE = "PROFILE_CANDIDATE"
    CUSTOMER_PREFERENCE = "CUSTOMER_PREFERENCE"
    INVESTMENT_GOAL = "INVESTMENT_GOAL"
    SERVICE_FACT = "SERVICE_FACT"
    CUSTOMER_RELATION = "CUSTOMER_RELATION"


class MemoryStatus(StrEnum):
    """记忆生命周期状态。"""

    CANDIDATE = "candidate"
    CONFIRMED = "confirmed"
    EXPIRED = "expired"
    REJECTED = "rejected"
    ARCHIVED = "archived"


class MemorySource(StrEnum):
    """客服对话形成记忆的证据来源。"""

    DIALOGUE_CONFIRMED = "dialogue_confirmed"
    DIALOGUE_STATED = "dialogue_stated"
    DIALOGUE_INFERRED = "dialogue_inferred"


class ShortTermMessage(BaseModel):
    """Redis 短期会话中的一条消息。"""

    model_config = ConfigDict(extra="forbid")

    message_id: str = Field(min_length=1, max_length=64)
    session_id: str = Field(min_length=1, max_length=64)
    role: str = Field(min_length=1, max_length=16)
    content: str = Field(min_length=1)
    token_count: int = Field(default=0, ge=0)
    agent_run_id: str | None = Field(default=None, max_length=64)
    tool_calls: list[dict[str, Any]] = Field(default_factory=list)
    create_time: datetime | None = None


class MemoryUnitDTO(BaseModel):
    """统一表示一条客户记忆，供写入、召回和重排使用。"""

    model_config = ConfigDict(extra="forbid")

    id: int | None = None
    customer_id: int
    session_id: str | None = Field(default=None, max_length=64)
    agent_run_id: str | None = Field(default=None, max_length=64)
    memory_type: MemoryType
    tag: str = Field(min_length=1, max_length=64)
    content: str = Field(min_length=1, max_length=512)
    info_type: str = Field(default="FACT", min_length=1, max_length=8)
    source: MemorySource
    evidence_ref: list[dict[str, Any]] = Field(default_factory=list)
    source_confidence: float = Field(default=0.2, ge=0.0, le=1.0)
    confidence: float = Field(default=0.2, ge=0.0, le=1.0)
    historical_accuracy: float = Field(default=0.5, ge=0.0, le=1.0)
    confidence_version: str | None = Field(default=None, max_length=32)
    confidence_reason: str | None = Field(default=None, max_length=255)
    confidence_update_time: datetime | None = None
    final_score: float | None = Field(default=None, ge=0.0, le=1.0)
    semantic_similarity: float | None = Field(default=None, ge=0.0, le=1.0)
    evidence_count: int = Field(default=0, ge=0)
    recall_count: int = Field(default=0, ge=0)
    status: MemoryStatus = MemoryStatus.CANDIDATE
    valid_from: datetime | None = None
    valid_until: datetime | None = None
    last_verified_at: datetime | None = None
    milvus_id: str | None = Field(default=None, max_length=128)
    graph_node_id: str | None = Field(default=None, max_length=128)


class CustomerMemoryContext(BaseModel):
    """客服 Agent 每轮请求可使用的统一记忆上下文。"""

    model_config = ConfigDict(extra="forbid")

    customer_id: int
    session_id: str
    short_term_messages: list[ShortTermMessage] = Field(default_factory=list)
    customer_profile: dict[str, Any] | None = None
    work_orders: list[dict[str, Any]] = Field(default_factory=list)
    long_term_memories: list[MemoryUnitDTO] = Field(default_factory=list)
    customer_relations: list[dict[str, Any]] = Field(default_factory=list)
    customer_products: list[dict[str, Any]] = Field(default_factory=list)
    warnings: list[str] = Field(default_factory=list)