"""面向前端的请求/响应 DTO。与 DB 模型解耦,**响应里的 key 一律打码**。

模型资源 DTO 字段对齐前端 ComponentsModelsPage 的 ModelResource:
JSON 用 camelCase(modelId/interfaceType/apiUrl/apiKey),Python 内部用 snake_case,
靠 Pydantic alias 自动互转。FastAPI 响应默认 by_alias=True,所以出参也是 camelCase。
"""

from __future__ import annotations

from typing import Any, Literal

from pydantic import BaseModel, ConfigDict, Field, model_validator
from pydantic.alias_generators import to_camel

RuntimeMode = Literal["pipeline", "realtime"]
ModelType = Literal["LLM", "ASR", "TTS", "Realtime", "Embedding"]
AssistantType = Literal["prompt", "workflow", "dify", "fastgpt", "opencode"]

# 外部应用类型:其 config.apiKey 是该助手私有密钥,读时打码 / 写时哨兵
EXTERNAL_TYPES = {"dify", "fastgpt", "opencode"}

# 支持 realtime(语音到语音)的类型;外部托管大脑只能走 cascade。
# 与 services.brains 各 BrainSpec.supported_runtime_modes 对齐(此处独立声明,
# 避免 HTTP schema 层为做校验而引入 pipecat 重依赖)。
REALTIME_CAPABLE_TYPES = {"prompt", "workflow"}


class CamelModel(BaseModel):
    """JSON camelCase ↔ Python snake_case。protected_namespaces 关掉以允许 model_id。"""

    model_config = ConfigDict(
        alias_generator=to_camel,
        populate_by_name=True,
        protected_namespaces=(),
    )


# 各 type 允许的瘦字段(其余字段写入时清零,防止跨类型脏数据)
ALLOWED_FIELDS: dict[str, set[str]] = {
    "prompt": {"prompt"},
    "workflow": {"graph"},
    "dify": {"api_url", "api_key"},
    "fastgpt": {"app_id", "api_url", "api_key"},
    "opencode": {"prompt", "api_url", "api_key"},
}


# ---------- 助手(单表 STI:瘦类型真列 + workflow 图 JSON 列) ----------
class AssistantUpsert(CamelModel):
    name: str
    type: AssistantType = "prompt"
    runtime_mode: RuntimeMode = "pipeline"
    greeting: str = ""
    enable_interrupt: bool = True
    vision_enabled: bool = False
    vision_model_resource_id: str | None = None

    model_resource_ids: dict[ModelType, str] = Field(default_factory=dict)
    knowledge_base_id: str | None = None

    # 瘦类型专属(真列);按 type 取用,无关字段写入时清零
    prompt: str = ""
    api_url: str = ""
    api_key: str = ""  # 写时:占位符/空 → 保留旧(哨兵)
    app_id: str = ""
    # workflow 专属:图
    graph: dict[str, Any] = Field(default_factory=dict)

    @model_validator(mode="after")
    def _strip_irrelevant_fields(self):
        allowed = ALLOWED_FIELDS[self.type]
        for field in ("prompt", "api_url", "api_key", "app_id"):
            if field not in allowed:
                setattr(self, field, "")
        if "graph" not in allowed:
            self.graph = {}
        # 外部托管大脑只能 cascade,拦住不兼容的 realtime
        if self.runtime_mode == "realtime" and self.type not in REALTIME_CAPABLE_TYPES:
            raise ValueError(f"类型 {self.type} 不支持 realtime 运行模式")
        return self


class AssistantOut(AssistantUpsert):
    id: str
    updated_at: str | None = None


# ---------- 知识库 ----------
class KnowledgeBaseUpsert(CamelModel):
    name: str
    description: str = ""
    embedding_model_resource_id: str | None = None


class KnowledgeBaseOut(KnowledgeBaseUpsert):
    id: str
    status: str = "active"
    updated_at: str | None = None


# ---------- 接口定义驱动的统一模型资源 ----------
class InterfaceDefinitionOut(CamelModel):
    interface_type: str
    name: str
    capability: ModelType
    field_schema: dict[str, Any]
    enabled: bool
    version: int


class ModelResourceUpsert(CamelModel):
    name: str
    interface_type: str
    values: dict[str, Any] = Field(default_factory=dict)
    secrets: dict[str, Any] = Field(default_factory=dict)
    support_image_input: bool = False
    enabled: bool = True
    is_default: bool = False


class ModelResourceOut(ModelResourceUpsert):
    id: str
    capability: ModelType
    updated_at: str | None = None


class ModelResourceTestResult(CamelModel):
    ok: bool
    latency_ms: int | None = None
    message: str
    detail: str = ""