refactor: optimize backend module

domain/ai/types.py

@@ -0,0 +1,121 @@
+from typing import Any, Dict, Iterable, List, Optional
+
+from pydantic import BaseModel, Field, field_validator
+
+ABILITIES = ["chat", "vision", "embedding", "rerank", "voice", "tools"]
+
+
+def normalize_capabilities(items: Optional[Iterable[str]]) -> List[str]:
+    if not items:
+        return []
+    normalized: List[str] = []
+    for cap in items:
+        key = str(cap).strip().lower()
+        if key in ABILITIES and key not in normalized:
+            normalized.append(key)
+    return normalized
+
+
+class AIProviderBase(BaseModel):
+    name: str
+    identifier: str = Field(..., pattern=r"^[a-z0-9_\-\.]+$")
+    provider_type: Optional[str] = None
+    api_format: str
+    base_url: Optional[str] = None
+    api_key: Optional[str] = None
+    logo_url: Optional[str] = None
+    extra_config: Optional[dict] = None
+
+    @field_validator("api_format")
+    @classmethod
+    def normalize_format(cls, value: str) -> str:
+        fmt = value.lower()
+        if fmt not in {"openai", "gemini"}:
+            raise ValueError("api_format must be 'openai' or 'gemini'")
+        return fmt
+
+
+class AIProviderCreate(AIProviderBase):
+    pass
+
+
+class AIProviderUpdate(BaseModel):
+    name: Optional[str] = None
+    provider_type: Optional[str] = None
+    api_format: Optional[str] = None
+    base_url: Optional[str] = None
+    api_key: Optional[str] = None
+    logo_url: Optional[str] = None
+    extra_config: Optional[dict] = None
+
+    @field_validator("api_format")
+    @classmethod
+    def normalize_format(cls, value: Optional[str]) -> Optional[str]:
+        if value is None:
+            return value
+        fmt = value.lower()
+        if fmt not in {"openai", "gemini"}:
+            raise ValueError("api_format must be 'openai' or 'gemini'")
+        return fmt
+
+
+class AIModelBase(BaseModel):
+    name: str
+    display_name: Optional[str] = None
+    description: Optional[str] = None
+    capabilities: Optional[List[str]] = None
+    context_window: Optional[int] = None
+    embedding_dimensions: Optional[int] = None
+    metadata: Optional[dict] = None
+
+    @field_validator("capabilities")
+    @classmethod
+    def validate_capabilities(cls, items: Optional[List[str]]) -> Optional[List[str]]:
+        if items is None:
+            return None
+        normalized = normalize_capabilities(items)
+        invalid = set(items) - set(normalized)
+        if invalid:
+            raise ValueError(f"Unsupported capabilities: {', '.join(invalid)}")
+        return normalized
+
+
+class AIModelCreate(AIModelBase):
+    pass
+
+
+class AIModelUpdate(BaseModel):
+    display_name: Optional[str] = None
+    description: Optional[str] = None
+    capabilities: Optional[List[str]] = None
+    context_window: Optional[int] = None
+    embedding_dimensions: Optional[int] = None
+    metadata: Optional[dict] = None
+
+    @field_validator("capabilities")
+    @classmethod
+    def validate_capabilities(cls, items: Optional[List[str]]) -> Optional[List[str]]:
+        if items is None:
+            return None
+        normalized = normalize_capabilities(items)
+        invalid = set(items) - set(normalized)
+        if invalid:
+            raise ValueError(f"Unsupported capabilities: {', '.join(invalid)}")
+        return normalized
+
+
+class AIDefaultsUpdate(BaseModel):
+    chat: Optional[int] = None
+    vision: Optional[int] = None
+    embedding: Optional[int] = None
+    rerank: Optional[int] = None
+    voice: Optional[int] = None
+    tools: Optional[int] = None
+
+    def as_mapping(self) -> Dict[str, Optional[int]]:
+        return {ability: getattr(self, ability) for ability in ABILITIES}
+
+
+class VectorDBConfigPayload(BaseModel):
+    type: str = Field(..., description="向量数据库提供者类型")
+    config: Dict[str, Any] = Field(default_factory=dict, description="提供者配置参数")