from __future__ import annotations

from pydantic import BaseModel, Field


class KnowledgeStatusRequest(BaseModel):
    open: bool


class KnowledgeLifecycleRequest(BaseModel):
    status: str = Field(pattern="^(active|archived)$")


class KnowledgeMetadataUpdateRequest(BaseModel):
    name: str = Field(min_length=1, max_length=100)
    knowledgeType: str = Field(pattern="^(course|qa|general|fixed)$")


class KnowledgeBatchMetadataUpdateRequest(BaseModel):
    knowledgeIds: list[int] = Field(min_length=1, max_length=500)
    knowledgeType: str | None = Field(default=None, pattern="^(course|qa|general|fixed)$")


class KnowledgeBatchSyncRequest(BaseModel):
    knowledgeIds: list[int] = Field(min_length=1, max_length=500)


class AttentionUpdateRequest(BaseModel):
    status: str = Field(pattern="^(pending|processing|resolved|ignored)$")
    note: str | None = Field(default=None, max_length=2000)


class AttentionRecognitionItem(BaseModel):
    name: str = Field(min_length=1, max_length=50)
    description: str = Field(min_length=1, max_length=500)
    priority: str = Field(pattern="^(urgent|important|normal)$")
    enabled: bool = True


class AttentionConfigRequest(BaseModel):
    enabled: bool = True
    keywordEnabled: bool = True
    aiEnabled: bool = False
    knowledgeMissingEnabled: bool = True
    urgentTerms: list[str] = Field(default_factory=list, max_length=100)
    importantTerms: list[str] = Field(default_factory=list, max_length=100)
    normalTerms: list[str] = Field(default_factory=list, max_length=100)
    promptTemplate: str = Field(default="", max_length=8000)
    recognitionItems: list[AttentionRecognitionItem] = Field(default_factory=list, max_length=30)


class AttentionPreviewRequest(BaseModel):
    messageIds: list[int] = Field(min_length=1, max_length=20)
    config: AttentionConfigRequest