from datetime import datetime
from typing import Literal

from pydantic import BaseModel, Field, field_validator

from core.rag.index_processor.constant.index_type import IndexTechniqueType
from core.rag.retrieval.retrieval_methods import RetrievalMethod
from fields.base import ResponseModel
from libs.helper import to_timestamp
from services.data_source.entities.notion_import import NotionPageType


class NotionEstimatePagePayload(BaseModel):
    page_id: str = Field(min_length=1)
    page_type: NotionPageType = Field(alias="type")


class NotionEstimateWorkspacePayload(BaseModel):
    workspace_id: str = Field(min_length=1)
    credential_id: str = Field(min_length=1)
    pages: list[NotionEstimatePagePayload] = Field(min_length=1)


MetadataValueType = Literal["string", "number", "time"]
# Mirror models.enums.PermissionEnum / DataSourceType / DatasetRuntimeMode; response schemas do not
# import models.
DatasetPermission = Literal["only_me", "all_team_members", "partial_members"]
DatasetDataSourceType = Literal[
    "upload_file", "notion_import", "website_crawl", "local_file", "online_document", "online_drive"
]
DatasetRuntimeMode = Literal["general", "rag_pipeline"]


class DatasetMetadataResponse(ResponseModel):
    id: str
    type: MetadataValueType
    name: str


class DatasetMetadataListItemResponse(ResponseModel):
    id: str
    name: str
    type: MetadataValueType
    count: int = 0


class DatasetMetadataListResponse(ResponseModel):
    doc_metadata: list[DatasetMetadataListItemResponse]
    built_in_field_enabled: bool


class DatasetMetadataBuiltInFieldResponse(ResponseModel):
    name: str
    type: MetadataValueType


class DatasetMetadataBuiltInFieldsResponse(ResponseModel):
    fields: list[DatasetMetadataBuiltInFieldResponse]


class DatasetMetadataActionResponse(ResponseModel):
    result: str = Field(description="Operation result.")


class DatasetRerankingModelResponse(ResponseModel):
    reranking_provider_name: str | None = None
    reranking_model_name: str | None = None


class DatasetKeywordSettingResponse(ResponseModel):
    keyword_weight: float | None = None


class DatasetVectorSettingResponse(ResponseModel):
    vector_weight: float | None = None
    embedding_model_name: str | None = None
    embedding_provider_name: str | None = None


class DatasetWeightedScoreResponse(ResponseModel):
    weight_type: str | None = None
    keyword_setting: DatasetKeywordSettingResponse = Field(
        default_factory=DatasetKeywordSettingResponse,
        description="Keyword search weight settings.",
    )
    vector_setting: DatasetVectorSettingResponse = Field(
        default_factory=DatasetVectorSettingResponse,
        description="Semantic search weight settings.",
    )

    @field_validator("keyword_setting", "vector_setting", mode="before")
    @classmethod
    def _expand_null_nested(cls, value: object) -> object:
        return {} if value is None else value


class DatasetRetrievalModelResponse(ResponseModel):
    search_method: RetrievalMethod
    reranking_enable: bool
    reranking_mode: str | None = None
    reranking_model: DatasetRerankingModelResponse = Field(
        default_factory=DatasetRerankingModelResponse,
        description="Reranking model configuration.",
    )
    weights: DatasetWeightedScoreResponse | None = None
    top_k: int
    score_threshold_enabled: bool
    score_threshold: float | None = None

    @field_validator("reranking_model", mode="before")
    @classmethod
    def _expand_null_nested(cls, value: object) -> object:
        return {} if value is None else value


class DatasetSummaryIndexSettingResponse(ResponseModel):
    enable: bool | None = None
    model_name: str | None = None
    model_provider_name: str | None = None
    summary_prompt: str | None = None


class DatasetTagResponse(ResponseModel):
    id: str
    name: str
    type: str


class DatasetExternalKnowledgeInfoResponse(ResponseModel):
    external_knowledge_id: str | None = None
    external_knowledge_api_id: str | None = None
    external_knowledge_api_name: str | None = None
    external_knowledge_api_endpoint: str | None = None


class DatasetExternalRetrievalModelResponse(ResponseModel):
    top_k: int
    score_threshold: float | None = None
    score_threshold_enabled: bool | None = None


class DatasetDocMetadataResponse(ResponseModel):
    id: str
    name: str
    type: MetadataValueType


class DatasetIconInfoResponse(ResponseModel):
    icon_type: str | None = None
    icon: str | None = None
    icon_background: str | None = None
    icon_url: str | None = None


class DatasetDetailResponse(ResponseModel):
    id: str
    name: str
    description: str | None
    provider: str
    permission: DatasetPermission
    data_source_type: DatasetDataSourceType | None
    indexing_technique: IndexTechniqueType | None
    keyword_number: int | None = Field(default=None, description="Keywords extracted per chunk by the economy index.")
    app_count: int
    document_count: int
    word_count: int
    created_by: str
    author_name: str | None
    created_at: int
    updated_by: str | None
    updated_at: int
    embedding_model: str | None
    embedding_model_provider: str | None
    embedding_available: bool | None = None
    retrieval_model_dict: DatasetRetrievalModelResponse = Field(
        description="Retrieval configuration for the knowledge base."
    )
    summary_index_setting: DatasetSummaryIndexSettingResponse = Field(
        default_factory=DatasetSummaryIndexSettingResponse,
        description="Summary index configuration.",
    )
    tags: list[DatasetTagResponse]
    doc_form: str | None
    external_knowledge_info: DatasetExternalKnowledgeInfoResponse = Field(
        default_factory=DatasetExternalKnowledgeInfoResponse,
        description=(
            "Connection details for external knowledge bases. Populated when `provider` is `external`; otherwise "
            "its properties are `null`."
        ),
    )
    external_retrieval_model: DatasetExternalRetrievalModelResponse | None
    doc_metadata: list[DatasetDocMetadataResponse]
    built_in_field_enabled: bool
    pipeline_id: str | None
    runtime_mode: DatasetRuntimeMode | None
    chunk_structure: str | None
    icon_info: DatasetIconInfoResponse = Field(
        default_factory=DatasetIconInfoResponse,
        description="Icon display configuration for the knowledge base.",
    )
    is_published: bool
    total_documents: int
    total_available_documents: int
    enable_api: bool
    is_multimodal: bool
    permission_keys: list[str] = Field(default_factory=list)
    maintainer: str | None = None

    @field_validator("created_at", "updated_at", mode="before")
    @classmethod
    def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
        return to_timestamp(value)

    @field_validator("summary_index_setting", "external_knowledge_info", "icon_info", mode="before")
    @classmethod
    def _expand_null_nested(cls, value: object) -> object:
        return {} if value is None else value