wip: snapshot full local workspace state
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@@ -1,61 +1,61 @@
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from contextlib import asynccontextmanager
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from fastapi import FastAPI
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from fastapi.middleware.cors import CORSMiddleware
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from app.api import admin_providers, admin_reload
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from app.core.config import settings
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from app.core.logging import get_logger, setup_logging
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from app.db.database import init_db
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setup_logging()
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logger = get_logger(__name__)
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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"""Admin App lifespan manager."""
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logger.info("admin_app_starting")
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await init_db()
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# 可以在这里加载特定的 Admin 缓存或预热
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yield
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logger.info("admin_app_shutdown")
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app = FastAPI(
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title=f"{settings.app_name} Admin Console",
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description="Administrative Control Plane for DreamWeaver.",
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version="0.1.0",
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lifespan=lifespan,
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)
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# Admin 后台通常允许更宽松的 CORS，或者特定的管理域名
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app.add_middleware(
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CORSMiddleware,
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allow_origins=settings.cors_origins, # 或者专门的 ADMIN_CORS_ORIGINS
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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# 根据配置开关挂载路由
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if settings.enable_admin_console:
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app.include_router(admin_providers.router, prefix="/admin", tags=["admin-providers"])
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app.include_router(admin_reload.router, prefix="/admin", tags=["admin-reload"])
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else:
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@app.get("/admin/{path:path}")
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@app.post("/admin/{path:path}")
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@app.put("/admin/{path:path}")
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@app.delete("/admin/{path:path}")
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async def admin_disabled(path: str):
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from fastapi import HTTPException
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raise HTTPException(
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status_code=403,
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detail="Admin console is disabled in environment configuration."
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)
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@app.get("/health")
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async def health_check():
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return {"status": "ok", "service": "admin-backend"}
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from contextlib import asynccontextmanager
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from fastapi import FastAPI
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from fastapi.middleware.cors import CORSMiddleware
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from app.api import admin_providers, admin_reload
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from app.core.config import settings
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from app.core.logging import get_logger, setup_logging
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from app.db.database import init_db
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setup_logging()
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logger = get_logger(__name__)
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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"""Admin App lifespan manager."""
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logger.info("admin_app_starting")
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await init_db()
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# 可以在这里加载特定的 Admin 缓存或预热
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yield
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logger.info("admin_app_shutdown")
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app = FastAPI(
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title=f"{settings.app_name} Admin Console",
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description="Administrative Control Plane for DreamWeaver.",
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version="0.1.0",
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lifespan=lifespan,
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)
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# Admin 后台通常允许更宽松的 CORS，或者特定的管理域名
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app.add_middleware(
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CORSMiddleware,
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allow_origins=settings.cors_origins, # 或者专门的 ADMIN_CORS_ORIGINS
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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# 根据配置开关挂载路由
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if settings.enable_admin_console:
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app.include_router(admin_providers.router, prefix="/admin", tags=["admin-providers"])
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app.include_router(admin_reload.router, prefix="/admin", tags=["admin-reload"])
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else:
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@app.get("/admin/{path:path}")
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@app.post("/admin/{path:path}")
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@app.put("/admin/{path:path}")
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@app.delete("/admin/{path:path}")
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async def admin_disabled(path: str):
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from fastapi import HTTPException
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raise HTTPException(
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status_code=403,
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detail="Admin console is disabled in environment configuration."
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)
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@app.get("/health")
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async def health_check():
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return {"status": "ok", "service": "admin-backend"}
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@@ -1,268 +1,268 @@
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"""Memory management APIs."""
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from fastapi import APIRouter, Depends, HTTPException
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from pydantic import BaseModel, Field
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.core.deps import require_user
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from app.db.database import get_db
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from app.db.models import ChildProfile, User
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from app.services import memory_service
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from app.services.memory_service import MemoryType
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router = APIRouter()
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class MemoryItemResponse(BaseModel):
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"""Memory item response."""
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id: str
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type: str
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value: dict
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base_weight: float
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ttl_days: int | None
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created_at: str
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last_used_at: str | None
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class Config:
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from_attributes = True
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class MemoryListResponse(BaseModel):
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"""Memory list response."""
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memories: list[MemoryItemResponse]
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total: int
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class CreateMemoryRequest(BaseModel):
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"""Create memory request."""
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type: str = Field(..., description="记忆类型")
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value: dict = Field(..., description="记忆内容")
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universe_id: str | None = Field(default=None, description="关联的故事宇宙 ID")
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weight: float | None = Field(default=None, description="权重")
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ttl_days: int | None = Field(default=None, description="过期天数")
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class CreateCharacterMemoryRequest(BaseModel):
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"""Create character memory request."""
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name: str = Field(..., description="角色名称")
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description: str | None = Field(default=None, description="角色描述")
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source_story_id: int | None = Field(default=None, description="来源故事 ID")
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affinity_score: float = Field(default=1.0, ge=0.0, le=1.0, description="喜爱程度")
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universe_id: str | None = Field(default=None, description="关联的故事宇宙 ID")
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class CreateScaryElementRequest(BaseModel):
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"""Create scary element memory request."""
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keyword: str = Field(..., description="回避的关键词")
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category: str = Field(default="other", description="分类")
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source_story_id: int | None = Field(default=None, description="来源故事 ID")
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async def _verify_profile_ownership(
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profile_id: str, user: User, db: AsyncSession
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) -> ChildProfile:
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"""验证档案所有权。"""
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from sqlalchemy import select
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result = await db.execute(
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select(ChildProfile).where(
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ChildProfile.id == profile_id,
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ChildProfile.user_id == user.id,
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)
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)
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profile = result.scalar_one_or_none()
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if not profile:
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raise HTTPException(status_code=404, detail="档案不存在")
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return profile
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@router.get("/profiles/{profile_id}/memories", response_model=MemoryListResponse)
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async def list_memories(
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profile_id: str,
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memory_type: str | None = None,
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universe_id: str | None = None,
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limit: int = 50,
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user: User = Depends(require_user),
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db: AsyncSession = Depends(get_db),
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):
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"""获取档案的记忆列表。"""
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await _verify_profile_ownership(profile_id, user, db)
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memories = await memory_service.get_profile_memories(
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db=db,
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profile_id=profile_id,
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memory_type=memory_type,
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universe_id=universe_id,
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limit=limit,
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)
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return MemoryListResponse(
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memories=[
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MemoryItemResponse(
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id=m.id,
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type=m.type,
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value=m.value,
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base_weight=m.base_weight,
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ttl_days=m.ttl_days,
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created_at=m.created_at.isoformat() if m.created_at else "",
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last_used_at=m.last_used_at.isoformat() if m.last_used_at else None,
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)
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for m in memories
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],
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total=len(memories),
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)
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@router.post("/profiles/{profile_id}/memories", response_model=MemoryItemResponse)
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async def create_memory(
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profile_id: str,
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payload: CreateMemoryRequest,
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user: User = Depends(require_user),
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db: AsyncSession = Depends(get_db),
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):
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"""创建新的记忆项。"""
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await _verify_profile_ownership(profile_id, user, db)
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# 验证类型
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valid_types = [
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MemoryType.RECENT_STORY,
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MemoryType.FAVORITE_CHARACTER,
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MemoryType.SCARY_ELEMENT,
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MemoryType.VOCABULARY_GROWTH,
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MemoryType.EMOTIONAL_HIGHLIGHT,
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MemoryType.READING_PREFERENCE,
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MemoryType.MILESTONE,
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MemoryType.SKILL_MASTERED,
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]
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if payload.type not in valid_types:
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raise HTTPException(status_code=400, detail=f"无效的记忆类型: {payload.type}")
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memory = await memory_service.create_memory(
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db=db,
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profile_id=profile_id,
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memory_type=payload.type,
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value=payload.value,
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universe_id=payload.universe_id,
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weight=payload.weight,
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ttl_days=payload.ttl_days,
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)
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return MemoryItemResponse(
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id=memory.id,
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type=memory.type,
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value=memory.value,
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base_weight=memory.base_weight,
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ttl_days=memory.ttl_days,
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created_at=memory.created_at.isoformat() if memory.created_at else "",
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last_used_at=memory.last_used_at.isoformat() if memory.last_used_at else None,
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)
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@router.post("/profiles/{profile_id}/memories/character", response_model=MemoryItemResponse)
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async def create_character_memory(
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profile_id: str,
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payload: CreateCharacterMemoryRequest,
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user: User = Depends(require_user),
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db: AsyncSession = Depends(get_db),
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):
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"""添加喜欢的角色。"""
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await _verify_profile_ownership(profile_id, user, db)
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memory = await memory_service.create_character_memory(
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db=db,
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profile_id=profile_id,
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name=payload.name,
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description=payload.description,
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source_story_id=payload.source_story_id,
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affinity_score=payload.affinity_score,
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universe_id=payload.universe_id,
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)
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return MemoryItemResponse(
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id=memory.id,
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type=memory.type,
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value=memory.value,
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base_weight=memory.base_weight,
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ttl_days=memory.ttl_days,
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created_at=memory.created_at.isoformat() if memory.created_at else "",
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last_used_at=memory.last_used_at.isoformat() if memory.last_used_at else None,
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)
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@router.post("/profiles/{profile_id}/memories/scary", response_model=MemoryItemResponse)
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async def create_scary_element_memory(
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profile_id: str,
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payload: CreateScaryElementRequest,
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user: User = Depends(require_user),
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db: AsyncSession = Depends(get_db),
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):
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"""添加回避元素。"""
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await _verify_profile_ownership(profile_id, user, db)
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memory = await memory_service.create_scary_element_memory(
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db=db,
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profile_id=profile_id,
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keyword=payload.keyword,
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category=payload.category,
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source_story_id=payload.source_story_id,
|
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)
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return MemoryItemResponse(
|
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id=memory.id,
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type=memory.type,
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value=memory.value,
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base_weight=memory.base_weight,
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ttl_days=memory.ttl_days,
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created_at=memory.created_at.isoformat() if memory.created_at else "",
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last_used_at=memory.last_used_at.isoformat() if memory.last_used_at else None,
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)
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|
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@router.delete("/profiles/{profile_id}/memories/{memory_id}")
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async def delete_memory(
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profile_id: str,
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memory_id: str,
|
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user: User = Depends(require_user),
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db: AsyncSession = Depends(get_db),
|
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):
|
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"""删除记忆项。"""
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from sqlalchemy import select
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from app.db.models import MemoryItem
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await _verify_profile_ownership(profile_id, user, db)
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|
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result = await db.execute(
|
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select(MemoryItem).where(
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MemoryItem.id == memory_id,
|
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MemoryItem.child_profile_id == profile_id,
|
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)
|
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)
|
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memory = result.scalar_one_or_none()
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|
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if not memory:
|
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raise HTTPException(status_code=404, detail="记忆不存在")
|
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|
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await db.delete(memory)
|
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await db.commit()
|
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|
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return {"message": "Deleted"}
|
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|
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|
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@router.get("/memory-types")
|
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async def list_memory_types():
|
||||
"""获取所有可用的记忆类型及其配置。"""
|
||||
types = []
|
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for type_name, config in MemoryType.CONFIG.items():
|
||||
types.append({
|
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"type": type_name,
|
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"default_weight": config[0],
|
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"default_ttl_days": config[1],
|
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"description": config[2],
|
||||
})
|
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return {"types": types}
|
||||
"""Memory management APIs."""
|
||||
|
||||
from fastapi import APIRouter, Depends, HTTPException
|
||||
from pydantic import BaseModel, Field
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
|
||||
from app.core.deps import require_user
|
||||
from app.db.database import get_db
|
||||
from app.db.models import ChildProfile, User
|
||||
from app.services import memory_service
|
||||
from app.services.memory_service import MemoryType
|
||||
|
||||
router = APIRouter()
|
||||
|
||||
|
||||
class MemoryItemResponse(BaseModel):
|
||||
"""Memory item response."""
|
||||
|
||||
id: str
|
||||
type: str
|
||||
value: dict
|
||||
base_weight: float
|
||||
ttl_days: int | None
|
||||
created_at: str
|
||||
last_used_at: str | None
|
||||
|
||||
class Config:
|
||||
from_attributes = True
|
||||
|
||||
|
||||
class MemoryListResponse(BaseModel):
|
||||
"""Memory list response."""
|
||||
|
||||
memories: list[MemoryItemResponse]
|
||||
total: int
|
||||
|
||||
|
||||
class CreateMemoryRequest(BaseModel):
|
||||
"""Create memory request."""
|
||||
|
||||
type: str = Field(..., description="记忆类型")
|
||||
value: dict = Field(..., description="记忆内容")
|
||||
universe_id: str | None = Field(default=None, description="关联的故事宇宙 ID")
|
||||
weight: float | None = Field(default=None, description="权重")
|
||||
ttl_days: int | None = Field(default=None, description="过期天数")
|
||||
|
||||
|
||||
class CreateCharacterMemoryRequest(BaseModel):
|
||||
"""Create character memory request."""
|
||||
|
||||
name: str = Field(..., description="角色名称")
|
||||
description: str | None = Field(default=None, description="角色描述")
|
||||
source_story_id: int | None = Field(default=None, description="来源故事 ID")
|
||||
affinity_score: float = Field(default=1.0, ge=0.0, le=1.0, description="喜爱程度")
|
||||
universe_id: str | None = Field(default=None, description="关联的故事宇宙 ID")
|
||||
|
||||
|
||||
class CreateScaryElementRequest(BaseModel):
|
||||
"""Create scary element memory request."""
|
||||
|
||||
keyword: str = Field(..., description="回避的关键词")
|
||||
category: str = Field(default="other", description="分类")
|
||||
source_story_id: int | None = Field(default=None, description="来源故事 ID")
|
||||
|
||||
|
||||
async def _verify_profile_ownership(
|
||||
profile_id: str, user: User, db: AsyncSession
|
||||
) -> ChildProfile:
|
||||
"""验证档案所有权。"""
|
||||
from sqlalchemy import select
|
||||
|
||||
result = await db.execute(
|
||||
select(ChildProfile).where(
|
||||
ChildProfile.id == profile_id,
|
||||
ChildProfile.user_id == user.id,
|
||||
)
|
||||
)
|
||||
profile = result.scalar_one_or_none()
|
||||
if not profile:
|
||||
raise HTTPException(status_code=404, detail="档案不存在")
|
||||
return profile
|
||||
|
||||
|
||||
@router.get("/profiles/{profile_id}/memories", response_model=MemoryListResponse)
|
||||
async def list_memories(
|
||||
profile_id: str,
|
||||
memory_type: str | None = None,
|
||||
universe_id: str | None = None,
|
||||
limit: int = 50,
|
||||
user: User = Depends(require_user),
|
||||
db: AsyncSession = Depends(get_db),
|
||||
):
|
||||
"""获取档案的记忆列表。"""
|
||||
await _verify_profile_ownership(profile_id, user, db)
|
||||
|
||||
memories = await memory_service.get_profile_memories(
|
||||
db=db,
|
||||
profile_id=profile_id,
|
||||
memory_type=memory_type,
|
||||
universe_id=universe_id,
|
||||
limit=limit,
|
||||
)
|
||||
|
||||
return MemoryListResponse(
|
||||
memories=[
|
||||
MemoryItemResponse(
|
||||
id=m.id,
|
||||
type=m.type,
|
||||
value=m.value,
|
||||
base_weight=m.base_weight,
|
||||
ttl_days=m.ttl_days,
|
||||
created_at=m.created_at.isoformat() if m.created_at else "",
|
||||
last_used_at=m.last_used_at.isoformat() if m.last_used_at else None,
|
||||
)
|
||||
for m in memories
|
||||
],
|
||||
total=len(memories),
|
||||
)
|
||||
|
||||
|
||||
@router.post("/profiles/{profile_id}/memories", response_model=MemoryItemResponse)
|
||||
async def create_memory(
|
||||
profile_id: str,
|
||||
payload: CreateMemoryRequest,
|
||||
user: User = Depends(require_user),
|
||||
db: AsyncSession = Depends(get_db),
|
||||
):
|
||||
"""创建新的记忆项。"""
|
||||
await _verify_profile_ownership(profile_id, user, db)
|
||||
|
||||
# 验证类型
|
||||
valid_types = [
|
||||
MemoryType.RECENT_STORY,
|
||||
MemoryType.FAVORITE_CHARACTER,
|
||||
MemoryType.SCARY_ELEMENT,
|
||||
MemoryType.VOCABULARY_GROWTH,
|
||||
MemoryType.EMOTIONAL_HIGHLIGHT,
|
||||
MemoryType.READING_PREFERENCE,
|
||||
MemoryType.MILESTONE,
|
||||
MemoryType.SKILL_MASTERED,
|
||||
]
|
||||
if payload.type not in valid_types:
|
||||
raise HTTPException(status_code=400, detail=f"无效的记忆类型: {payload.type}")
|
||||
|
||||
memory = await memory_service.create_memory(
|
||||
db=db,
|
||||
profile_id=profile_id,
|
||||
memory_type=payload.type,
|
||||
value=payload.value,
|
||||
universe_id=payload.universe_id,
|
||||
weight=payload.weight,
|
||||
ttl_days=payload.ttl_days,
|
||||
)
|
||||
|
||||
return MemoryItemResponse(
|
||||
id=memory.id,
|
||||
type=memory.type,
|
||||
value=memory.value,
|
||||
base_weight=memory.base_weight,
|
||||
ttl_days=memory.ttl_days,
|
||||
created_at=memory.created_at.isoformat() if memory.created_at else "",
|
||||
last_used_at=memory.last_used_at.isoformat() if memory.last_used_at else None,
|
||||
)
|
||||
|
||||
|
||||
@router.post("/profiles/{profile_id}/memories/character", response_model=MemoryItemResponse)
|
||||
async def create_character_memory(
|
||||
profile_id: str,
|
||||
payload: CreateCharacterMemoryRequest,
|
||||
user: User = Depends(require_user),
|
||||
db: AsyncSession = Depends(get_db),
|
||||
):
|
||||
"""添加喜欢的角色。"""
|
||||
await _verify_profile_ownership(profile_id, user, db)
|
||||
|
||||
memory = await memory_service.create_character_memory(
|
||||
db=db,
|
||||
profile_id=profile_id,
|
||||
name=payload.name,
|
||||
description=payload.description,
|
||||
source_story_id=payload.source_story_id,
|
||||
affinity_score=payload.affinity_score,
|
||||
universe_id=payload.universe_id,
|
||||
)
|
||||
|
||||
return MemoryItemResponse(
|
||||
id=memory.id,
|
||||
type=memory.type,
|
||||
value=memory.value,
|
||||
base_weight=memory.base_weight,
|
||||
ttl_days=memory.ttl_days,
|
||||
created_at=memory.created_at.isoformat() if memory.created_at else "",
|
||||
last_used_at=memory.last_used_at.isoformat() if memory.last_used_at else None,
|
||||
)
|
||||
|
||||
|
||||
@router.post("/profiles/{profile_id}/memories/scary", response_model=MemoryItemResponse)
|
||||
async def create_scary_element_memory(
|
||||
profile_id: str,
|
||||
payload: CreateScaryElementRequest,
|
||||
user: User = Depends(require_user),
|
||||
db: AsyncSession = Depends(get_db),
|
||||
):
|
||||
"""添加回避元素。"""
|
||||
await _verify_profile_ownership(profile_id, user, db)
|
||||
|
||||
memory = await memory_service.create_scary_element_memory(
|
||||
db=db,
|
||||
profile_id=profile_id,
|
||||
keyword=payload.keyword,
|
||||
category=payload.category,
|
||||
source_story_id=payload.source_story_id,
|
||||
)
|
||||
|
||||
return MemoryItemResponse(
|
||||
id=memory.id,
|
||||
type=memory.type,
|
||||
value=memory.value,
|
||||
base_weight=memory.base_weight,
|
||||
ttl_days=memory.ttl_days,
|
||||
created_at=memory.created_at.isoformat() if memory.created_at else "",
|
||||
last_used_at=memory.last_used_at.isoformat() if memory.last_used_at else None,
|
||||
)
|
||||
|
||||
|
||||
@router.delete("/profiles/{profile_id}/memories/{memory_id}")
|
||||
async def delete_memory(
|
||||
profile_id: str,
|
||||
memory_id: str,
|
||||
user: User = Depends(require_user),
|
||||
db: AsyncSession = Depends(get_db),
|
||||
):
|
||||
"""删除记忆项。"""
|
||||
from sqlalchemy import select
|
||||
|
||||
from app.db.models import MemoryItem
|
||||
|
||||
await _verify_profile_ownership(profile_id, user, db)
|
||||
|
||||
result = await db.execute(
|
||||
select(MemoryItem).where(
|
||||
MemoryItem.id == memory_id,
|
||||
MemoryItem.child_profile_id == profile_id,
|
||||
)
|
||||
)
|
||||
memory = result.scalar_one_or_none()
|
||||
|
||||
if not memory:
|
||||
raise HTTPException(status_code=404, detail="记忆不存在")
|
||||
|
||||
await db.delete(memory)
|
||||
await db.commit()
|
||||
|
||||
return {"message": "Deleted"}
|
||||
|
||||
|
||||
@router.get("/memory-types")
|
||||
async def list_memory_types():
|
||||
"""获取所有可用的记忆类型及其配置。"""
|
||||
types = []
|
||||
for type_name, config in MemoryType.CONFIG.items():
|
||||
types.append({
|
||||
"type": type_name,
|
||||
"default_weight": config[0],
|
||||
"default_ttl_days": config[1],
|
||||
"description": config[2],
|
||||
})
|
||||
return {"types": types}
|
||||
|
||||
@@ -117,4 +117,4 @@ async def create_reading_event(
|
||||
await db.commit()
|
||||
await db.refresh(event)
|
||||
|
||||
return event
|
||||
return event
|
||||
|
||||
@@ -198,4 +198,4 @@ async def add_achievement(
|
||||
await db.commit()
|
||||
await db.refresh(universe)
|
||||
|
||||
return universe
|
||||
return universe
|
||||
|
||||
@@ -1,60 +1,60 @@
|
||||
import secrets
|
||||
|
||||
from fastapi import Depends, HTTPException, Request, status
|
||||
from fastapi.security import HTTPBasic, HTTPBasicCredentials
|
||||
|
||||
from app.core.config import settings
|
||||
from app.core.rate_limiter import (
|
||||
clear_failed_attempts,
|
||||
is_locked_out,
|
||||
record_failed_attempt,
|
||||
)
|
||||
|
||||
security = HTTPBasic()
|
||||
|
||||
MAX_ATTEMPTS = 5
|
||||
LOCKOUT_SECONDS = 900 # 15分钟
|
||||
|
||||
|
||||
def _get_client_ip(request: Request) -> str:
|
||||
forwarded = request.headers.get("x-forwarded-for")
|
||||
if forwarded:
|
||||
return forwarded.split(",")[0].strip()
|
||||
if request.client and request.client.host:
|
||||
return request.client.host
|
||||
return "unknown"
|
||||
|
||||
|
||||
async def admin_guard(
|
||||
request: Request,
|
||||
credentials: HTTPBasicCredentials = Depends(security),
|
||||
):
|
||||
client_ip = _get_client_ip(request)
|
||||
lockout_key = f"admin_login:{client_ip}"
|
||||
|
||||
# 检查是否被锁定
|
||||
remaining = await is_locked_out(lockout_key, MAX_ATTEMPTS, LOCKOUT_SECONDS)
|
||||
if remaining > 0:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_429_TOO_MANY_REQUESTS,
|
||||
detail=f"登录尝试过多，请 {remaining} 秒后重试",
|
||||
)
|
||||
|
||||
# 使用 secrets.compare_digest 防止时序攻击
|
||||
username_ok = secrets.compare_digest(
|
||||
credentials.username.encode(), settings.admin_username.encode()
|
||||
)
|
||||
password_ok = secrets.compare_digest(
|
||||
credentials.password.encode(), settings.admin_password.encode()
|
||||
)
|
||||
|
||||
if not (username_ok and password_ok):
|
||||
await record_failed_attempt(lockout_key, MAX_ATTEMPTS, LOCKOUT_SECONDS)
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_401_UNAUTHORIZED,
|
||||
detail="用户名或密码错误",
|
||||
)
|
||||
|
||||
# 登录成功，清除失败记录
|
||||
await clear_failed_attempts(lockout_key)
|
||||
return True
|
||||
import secrets
|
||||
|
||||
from fastapi import Depends, HTTPException, Request, status
|
||||
from fastapi.security import HTTPBasic, HTTPBasicCredentials
|
||||
|
||||
from app.core.config import settings
|
||||
from app.core.rate_limiter import (
|
||||
clear_failed_attempts,
|
||||
is_locked_out,
|
||||
record_failed_attempt,
|
||||
)
|
||||
|
||||
security = HTTPBasic()
|
||||
|
||||
MAX_ATTEMPTS = 5
|
||||
LOCKOUT_SECONDS = 900 # 15分钟
|
||||
|
||||
|
||||
def _get_client_ip(request: Request) -> str:
|
||||
forwarded = request.headers.get("x-forwarded-for")
|
||||
if forwarded:
|
||||
return forwarded.split(",")[0].strip()
|
||||
if request.client and request.client.host:
|
||||
return request.client.host
|
||||
return "unknown"
|
||||
|
||||
|
||||
async def admin_guard(
|
||||
request: Request,
|
||||
credentials: HTTPBasicCredentials = Depends(security),
|
||||
):
|
||||
client_ip = _get_client_ip(request)
|
||||
lockout_key = f"admin_login:{client_ip}"
|
||||
|
||||
# 检查是否被锁定
|
||||
remaining = await is_locked_out(lockout_key, MAX_ATTEMPTS, LOCKOUT_SECONDS)
|
||||
if remaining > 0:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_429_TOO_MANY_REQUESTS,
|
||||
detail=f"登录尝试过多，请 {remaining} 秒后重试",
|
||||
)
|
||||
|
||||
# 使用 secrets.compare_digest 防止时序攻击
|
||||
username_ok = secrets.compare_digest(
|
||||
credentials.username.encode(), settings.admin_username.encode()
|
||||
)
|
||||
password_ok = secrets.compare_digest(
|
||||
credentials.password.encode(), settings.admin_password.encode()
|
||||
)
|
||||
|
||||
if not (username_ok and password_ok):
|
||||
await record_failed_attempt(lockout_key, MAX_ATTEMPTS, LOCKOUT_SECONDS)
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_401_UNAUTHORIZED,
|
||||
detail="用户名或密码错误",
|
||||
)
|
||||
|
||||
# 登录成功，清除失败记录
|
||||
await clear_failed_attempts(lockout_key)
|
||||
return True
|
||||
|
||||
@@ -1,48 +1,48 @@
|
||||
"""结构化日志配置。"""
|
||||
|
||||
import logging
|
||||
import sys
|
||||
|
||||
import structlog
|
||||
|
||||
from app.core.config import settings
|
||||
|
||||
|
||||
def setup_logging():
|
||||
"""配置 structlog 结构化日志。"""
|
||||
shared_processors = [
|
||||
structlog.contextvars.merge_contextvars,
|
||||
structlog.stdlib.add_log_level,
|
||||
structlog.stdlib.add_logger_name,
|
||||
structlog.processors.TimeStamper(fmt="iso"),
|
||||
structlog.processors.StackInfoRenderer(),
|
||||
]
|
||||
|
||||
if settings.debug:
|
||||
processors = shared_processors + [
|
||||
structlog.dev.ConsoleRenderer(colors=True),
|
||||
]
|
||||
else:
|
||||
processors = shared_processors + [
|
||||
structlog.processors.format_exc_info,
|
||||
structlog.processors.JSONRenderer(),
|
||||
]
|
||||
|
||||
structlog.configure(
|
||||
processors=processors,
|
||||
wrapper_class=structlog.stdlib.BoundLogger,
|
||||
context_class=dict,
|
||||
logger_factory=structlog.stdlib.LoggerFactory(),
|
||||
cache_logger_on_first_use=True,
|
||||
)
|
||||
|
||||
logging.basicConfig(
|
||||
format="%(message)s",
|
||||
stream=sys.stdout,
|
||||
level=logging.DEBUG if settings.debug else logging.INFO,
|
||||
)
|
||||
|
||||
|
||||
def get_logger(name: str) -> structlog.stdlib.BoundLogger:
|
||||
"""获取结构化日志器。"""
|
||||
return structlog.get_logger(name)
|
||||
"""结构化日志配置。"""
|
||||
|
||||
import logging
|
||||
import sys
|
||||
|
||||
import structlog
|
||||
|
||||
from app.core.config import settings
|
||||
|
||||
|
||||
def setup_logging():
|
||||
"""配置 structlog 结构化日志。"""
|
||||
shared_processors = [
|
||||
structlog.contextvars.merge_contextvars,
|
||||
structlog.stdlib.add_log_level,
|
||||
structlog.stdlib.add_logger_name,
|
||||
structlog.processors.TimeStamper(fmt="iso"),
|
||||
structlog.processors.StackInfoRenderer(),
|
||||
]
|
||||
|
||||
if settings.debug:
|
||||
processors = shared_processors + [
|
||||
structlog.dev.ConsoleRenderer(colors=True),
|
||||
]
|
||||
else:
|
||||
processors = shared_processors + [
|
||||
structlog.processors.format_exc_info,
|
||||
structlog.processors.JSONRenderer(),
|
||||
]
|
||||
|
||||
structlog.configure(
|
||||
processors=processors,
|
||||
wrapper_class=structlog.stdlib.BoundLogger,
|
||||
context_class=dict,
|
||||
logger_factory=structlog.stdlib.LoggerFactory(),
|
||||
cache_logger_on_first_use=True,
|
||||
)
|
||||
|
||||
logging.basicConfig(
|
||||
format="%(message)s",
|
||||
stream=sys.stdout,
|
||||
level=logging.DEBUG if settings.debug else logging.INFO,
|
||||
)
|
||||
|
||||
|
||||
def get_logger(name: str) -> structlog.stdlib.BoundLogger:
|
||||
"""获取结构化日志器。"""
|
||||
return structlog.get_logger(name)
|
||||
|
||||
@@ -1,190 +1,190 @@
|
||||
# ruff: noqa: E501
|
||||
"""AI 提示词模板 (Modernized)"""
|
||||
|
||||
# 随机元素列表：为故事注入不可预测的魔法
|
||||
RANDOM_ELEMENTS = [
|
||||
"一个会打喷嚏的云朵",
|
||||
"一本地图上找不到的神秘图书馆",
|
||||
"一只能实现小愿望的彩色蜗牛",
|
||||
"一扇通往颠倒世界的门",
|
||||
"一顶能听懂动物说话的旧帽子",
|
||||
"一个装着星星的玻璃罐",
|
||||
"一棵结满笑声果实的树",
|
||||
"一只能在水上画画的画笔",
|
||||
"一个怕黑的影子",
|
||||
"一只收集回声的瓶子",
|
||||
"一双会自己跳舞的红鞋子",
|
||||
"一个只能在月光下看见的邮筒",
|
||||
"一张会改变模样的全家福",
|
||||
"一把可以打开梦境的钥匙",
|
||||
"一个喜欢讲冷笑话的冰箱",
|
||||
"一条通往星期八的秘密小径"
|
||||
]
|
||||
|
||||
# ==============================================================================
|
||||
# Model A: 故事生成 (Story Generation)
|
||||
# ==============================================================================
|
||||
|
||||
SYSTEM_INSTRUCTION_STORYTELLER = """
|
||||
# Role
|
||||
You are "**Dream Weaver**", a world-class children's storyteller with the imagination of Pixar and the warmth of Miyazaki.
|
||||
Your mission is to create engaging, safe, and educational stories for children (ages 3-8).
|
||||
|
||||
# Core Philosophy
|
||||
1. **Show, Don't Tell**: Don't preach the lesson. Let the character's actions and the plot demonstrate the theme.
|
||||
2. **Safety First**: No violence, horror, or scary elements. Conflict should be emotional or situational, not physical.
|
||||
3. **Vivid Imagery**: Use sensory details (colors, sounds, smells) that appeal to children.
|
||||
4. **Empowerment**: The child protagonist should solve the problem using wit, kindness, or courage, not just luck.
|
||||
|
||||
# Continuity & Memory (CRITICAL)
|
||||
- **Universal Context**: The story takes place in the child's established "Story Universe". Respect existing world rules.
|
||||
- **Character Consistency**: If "Child Profile" or "Sidekicks" are provided, you MUST use their specific names and traits. Do NOT invent new main characters unless asked.
|
||||
- **Callback**: If "Past Memories" are provided, try to make a natural, one-sentence reference to a past adventure to build a sense of continuity (e.g., "Just like when we found the lost star...").
|
||||
|
||||
# Output Format
|
||||
You MUST return a pure JSON object with NO markdown formatting (no ```json code blocks).
|
||||
The JSON object must have the following schema:
|
||||
{
|
||||
"mode": "generated",
|
||||
"title": "A catchy, imaginative title",
|
||||
"story_text": "The full story text. Use \\n\\n for paragraph breaks.",
|
||||
"cover_prompt_suggestion": "A detailed English image generation prompt for the story cover. Style: whimsical, children's book illustration, soft lighting, vibrant colors."
|
||||
}
|
||||
"""
|
||||
|
||||
USER_PROMPT_GENERATION = """
|
||||
# Task: Write a Children's Story
|
||||
|
||||
## Contextual Memory (Use these if provided)
|
||||
{memory_context}
|
||||
|
||||
## Inputs
|
||||
- **Keywords/Topic**: {keywords}
|
||||
- **Educational Theme**: {education_theme}
|
||||
- **Magic Element (Must Incorporate)**: {random_element}
|
||||
|
||||
## Constraints
|
||||
- Length: 300-600 words.
|
||||
- Structure: Beginning (Hook) -> Middle (Challenge) -> End (Resolution & Growth).
|
||||
"""
|
||||
|
||||
# ==============================================================================
|
||||
# Model B: 故事润色 (Story Enhancement)
|
||||
# ==============================================================================
|
||||
|
||||
SYSTEM_INSTRUCTION_ENHANCER = """
|
||||
# Role
|
||||
You are "**Dream Weaver Editor**", an expert children's book editor who turns rough drafts into polished gems.
|
||||
|
||||
# Mission
|
||||
Analyze the user's input story and rewrite it to be:
|
||||
1. **More Engaging**: Enhance the plot with a "Magic Element" to add surprise.
|
||||
2. **More Educational**: Weave the "Educational Theme" deeper into the narrative arc.
|
||||
3. **Better Written**: Polish the sentences for rhythm and flow (suitable for reading aloud).
|
||||
4. **Safe**: Remove any inappropriate content (violence, scary interaction) and replace it with constructive solutions.
|
||||
|
||||
# Output Format
|
||||
You MUST return a pure JSON object with NO markdown formatting (no ```json code blocks).
|
||||
The JSON object must have the following schema:
|
||||
{
|
||||
"mode": "enhanced",
|
||||
"title": "An improved title (or the original if perfect)",
|
||||
"story_text": "The rewritten story text. Use \\n\\n for paragraph breaks.",
|
||||
"cover_prompt_suggestion": "A detailed English image generation prompt for the cover."
|
||||
}
|
||||
"""
|
||||
|
||||
USER_PROMPT_ENHANCEMENT = """
|
||||
# Task: Enhance This Story
|
||||
|
||||
## Contextual Memory
|
||||
{memory_context}
|
||||
|
||||
## Inputs
|
||||
- **Original Story**: {full_story}
|
||||
- **Target Theme**: {education_theme}
|
||||
- **Magic Element to Add**: {random_element}
|
||||
|
||||
## Constraints
|
||||
- Length: 300-600 words.
|
||||
- Keep the original character names if possible, but feel free to upgrade the plot.
|
||||
"""
|
||||
|
||||
# ==============================================================================
|
||||
# Model C: 成就提取 (Achievement Extraction)
|
||||
# ==============================================================================
|
||||
|
||||
# 保持简单，暂不使用 System Instruction，沿用单次提示
|
||||
ACHIEVEMENT_EXTRACTION_PROMPT = """
|
||||
Analyze the story and extract key growth moments or achievements for the child protagonist.
|
||||
|
||||
# Story
|
||||
{story_text}
|
||||
|
||||
# Target Categories (Examples)
|
||||
- **Courage**: Overcoming fear, trying something new.
|
||||
- **Kindness**: Helping others, sharing, empathy.
|
||||
- **Curiosity**: Asking questions, exploring, learning.
|
||||
- **Resilience**: Not giving up, handling failure.
|
||||
- **Wisdom**: Problem-solving, honesty, patience.
|
||||
|
||||
# Output Format
|
||||
Return a pure JSON object (no markdown):
|
||||
{{
|
||||
"achievements": [
|
||||
{{
|
||||
"type": "Category Name",
|
||||
"description": "Brief reason (max 10 words)",
|
||||
"score": 8 // 1-10 intensity
|
||||
}}
|
||||
]
|
||||
}}
|
||||
"""
|
||||
|
||||
# ==============================================================================
|
||||
# Model D: 绘本生成 (Storybook Generation)
|
||||
# ==============================================================================
|
||||
|
||||
SYSTEM_INSTRUCTION_STORYBOOK = """
|
||||
# Role
|
||||
You are "**Dream Weaver Illustrator**", a creative children's book author and visual director.
|
||||
Your mission is to create a paginated picture book for children (ages 3-8), where each page has text and a matching illustration prompt.
|
||||
|
||||
# Core Philosophy
|
||||
1. **Pacing**: The story must flow logically across the specified number of pages.
|
||||
2. **Visual Consistency**: Define the "Main Character" and "Art Style" once, and ensure all image prompts adhere to them.
|
||||
3. **Language**: The story text MUST be in **Chinese (Simplified)**. The image prompts MUST be in **English**.
|
||||
4. **Memory**: If a memory context is provided, incorporate known characters or references naturally.
|
||||
|
||||
# Output Format
|
||||
You MUST return a pure JSON object using the following schema (no markdown):
|
||||
{
|
||||
"title": "Story Title (Chinese)",
|
||||
"main_character": "Description of the protagonist (e.g., 'A small blue robot with rusty gears')",
|
||||
"art_style": "Visual style description (e.g., 'Watercolor, soft pastel colors, whimsical')",
|
||||
"pages": [
|
||||
{
|
||||
"page_number": 1,
|
||||
"text": "Page text in Chinese (30-60 chars).",
|
||||
"image_prompt": "Detailed English image prompt describing the scene. Include 'main_character' reference."
|
||||
}
|
||||
],
|
||||
"cover_prompt": "English image prompt for the book cover."
|
||||
}
|
||||
"""
|
||||
|
||||
USER_PROMPT_STORYBOOK = """
|
||||
# Task: Create a {page_count}-Page Storybook
|
||||
|
||||
## Contextual Memory
|
||||
{memory_context}
|
||||
|
||||
## Inputs
|
||||
- **Keywords/Topic**: {keywords}
|
||||
- **Educational Theme**: {education_theme}
|
||||
- **Magic Element**: {random_element}
|
||||
|
||||
## Constraints
|
||||
- Pages: Exactly {page_count} pages.
|
||||
- Structure: Intro -> Development -> Climax -> Resolution.
|
||||
"""
|
||||
# ruff: noqa: E501
|
||||
"""AI 提示词模板 (Modernized)"""
|
||||
|
||||
# 随机元素列表：为故事注入不可预测的魔法
|
||||
RANDOM_ELEMENTS = [
|
||||
"一个会打喷嚏的云朵",
|
||||
"一本地图上找不到的神秘图书馆",
|
||||
"一只能实现小愿望的彩色蜗牛",
|
||||
"一扇通往颠倒世界的门",
|
||||
"一顶能听懂动物说话的旧帽子",
|
||||
"一个装着星星的玻璃罐",
|
||||
"一棵结满笑声果实的树",
|
||||
"一只能在水上画画的画笔",
|
||||
"一个怕黑的影子",
|
||||
"一只收集回声的瓶子",
|
||||
"一双会自己跳舞的红鞋子",
|
||||
"一个只能在月光下看见的邮筒",
|
||||
"一张会改变模样的全家福",
|
||||
"一把可以打开梦境的钥匙",
|
||||
"一个喜欢讲冷笑话的冰箱",
|
||||
"一条通往星期八的秘密小径"
|
||||
]
|
||||
|
||||
# ==============================================================================
|
||||
# Model A: 故事生成 (Story Generation)
|
||||
# ==============================================================================
|
||||
|
||||
SYSTEM_INSTRUCTION_STORYTELLER = """
|
||||
# Role
|
||||
You are "**Dream Weaver**", a world-class children's storyteller with the imagination of Pixar and the warmth of Miyazaki.
|
||||
Your mission is to create engaging, safe, and educational stories for children (ages 3-8).
|
||||
|
||||
# Core Philosophy
|
||||
1. **Show, Don't Tell**: Don't preach the lesson. Let the character's actions and the plot demonstrate the theme.
|
||||
2. **Safety First**: No violence, horror, or scary elements. Conflict should be emotional or situational, not physical.
|
||||
3. **Vivid Imagery**: Use sensory details (colors, sounds, smells) that appeal to children.
|
||||
4. **Empowerment**: The child protagonist should solve the problem using wit, kindness, or courage, not just luck.
|
||||
|
||||
# Continuity & Memory (CRITICAL)
|
||||
- **Universal Context**: The story takes place in the child's established "Story Universe". Respect existing world rules.
|
||||
- **Character Consistency**: If "Child Profile" or "Sidekicks" are provided, you MUST use their specific names and traits. Do NOT invent new main characters unless asked.
|
||||
- **Callback**: If "Past Memories" are provided, try to make a natural, one-sentence reference to a past adventure to build a sense of continuity (e.g., "Just like when we found the lost star...").
|
||||
|
||||
# Output Format
|
||||
You MUST return a pure JSON object with NO markdown formatting (no ```json code blocks).
|
||||
The JSON object must have the following schema:
|
||||
{
|
||||
"mode": "generated",
|
||||
"title": "A catchy, imaginative title",
|
||||
"story_text": "The full story text. Use \\n\\n for paragraph breaks.",
|
||||
"cover_prompt_suggestion": "A detailed English image generation prompt for the story cover. Style: whimsical, children's book illustration, soft lighting, vibrant colors."
|
||||
}
|
||||
"""
|
||||
|
||||
USER_PROMPT_GENERATION = """
|
||||
# Task: Write a Children's Story
|
||||
|
||||
## Contextual Memory (Use these if provided)
|
||||
{memory_context}
|
||||
|
||||
## Inputs
|
||||
- **Keywords/Topic**: {keywords}
|
||||
- **Educational Theme**: {education_theme}
|
||||
- **Magic Element (Must Incorporate)**: {random_element}
|
||||
|
||||
## Constraints
|
||||
- Length: 300-600 words.
|
||||
- Structure: Beginning (Hook) -> Middle (Challenge) -> End (Resolution & Growth).
|
||||
"""
|
||||
|
||||
# ==============================================================================
|
||||
# Model B: 故事润色 (Story Enhancement)
|
||||
# ==============================================================================
|
||||
|
||||
SYSTEM_INSTRUCTION_ENHANCER = """
|
||||
# Role
|
||||
You are "**Dream Weaver Editor**", an expert children's book editor who turns rough drafts into polished gems.
|
||||
|
||||
# Mission
|
||||
Analyze the user's input story and rewrite it to be:
|
||||
1. **More Engaging**: Enhance the plot with a "Magic Element" to add surprise.
|
||||
2. **More Educational**: Weave the "Educational Theme" deeper into the narrative arc.
|
||||
3. **Better Written**: Polish the sentences for rhythm and flow (suitable for reading aloud).
|
||||
4. **Safe**: Remove any inappropriate content (violence, scary interaction) and replace it with constructive solutions.
|
||||
|
||||
# Output Format
|
||||
You MUST return a pure JSON object with NO markdown formatting (no ```json code blocks).
|
||||
The JSON object must have the following schema:
|
||||
{
|
||||
"mode": "enhanced",
|
||||
"title": "An improved title (or the original if perfect)",
|
||||
"story_text": "The rewritten story text. Use \\n\\n for paragraph breaks.",
|
||||
"cover_prompt_suggestion": "A detailed English image generation prompt for the cover."
|
||||
}
|
||||
"""
|
||||
|
||||
USER_PROMPT_ENHANCEMENT = """
|
||||
# Task: Enhance This Story
|
||||
|
||||
## Contextual Memory
|
||||
{memory_context}
|
||||
|
||||
## Inputs
|
||||
- **Original Story**: {full_story}
|
||||
- **Target Theme**: {education_theme}
|
||||
- **Magic Element to Add**: {random_element}
|
||||
|
||||
## Constraints
|
||||
- Length: 300-600 words.
|
||||
- Keep the original character names if possible, but feel free to upgrade the plot.
|
||||
"""
|
||||
|
||||
# ==============================================================================
|
||||
# Model C: 成就提取 (Achievement Extraction)
|
||||
# ==============================================================================
|
||||
|
||||
# 保持简单，暂不使用 System Instruction，沿用单次提示
|
||||
ACHIEVEMENT_EXTRACTION_PROMPT = """
|
||||
Analyze the story and extract key growth moments or achievements for the child protagonist.
|
||||
|
||||
# Story
|
||||
{story_text}
|
||||
|
||||
# Target Categories (Examples)
|
||||
- **Courage**: Overcoming fear, trying something new.
|
||||
- **Kindness**: Helping others, sharing, empathy.
|
||||
- **Curiosity**: Asking questions, exploring, learning.
|
||||
- **Resilience**: Not giving up, handling failure.
|
||||
- **Wisdom**: Problem-solving, honesty, patience.
|
||||
|
||||
# Output Format
|
||||
Return a pure JSON object (no markdown):
|
||||
{{
|
||||
"achievements": [
|
||||
{{
|
||||
"type": "Category Name",
|
||||
"description": "Brief reason (max 10 words)",
|
||||
"score": 8 // 1-10 intensity
|
||||
}}
|
||||
]
|
||||
}}
|
||||
"""
|
||||
|
||||
# ==============================================================================
|
||||
# Model D: 绘本生成 (Storybook Generation)
|
||||
# ==============================================================================
|
||||
|
||||
SYSTEM_INSTRUCTION_STORYBOOK = """
|
||||
# Role
|
||||
You are "**Dream Weaver Illustrator**", a creative children's book author and visual director.
|
||||
Your mission is to create a paginated picture book for children (ages 3-8), where each page has text and a matching illustration prompt.
|
||||
|
||||
# Core Philosophy
|
||||
1. **Pacing**: The story must flow logically across the specified number of pages.
|
||||
2. **Visual Consistency**: Define the "Main Character" and "Art Style" once, and ensure all image prompts adhere to them.
|
||||
3. **Language**: The story text MUST be in **Chinese (Simplified)**. The image prompts MUST be in **English**.
|
||||
4. **Memory**: If a memory context is provided, incorporate known characters or references naturally.
|
||||
|
||||
# Output Format
|
||||
You MUST return a pure JSON object using the following schema (no markdown):
|
||||
{
|
||||
"title": "Story Title (Chinese)",
|
||||
"main_character": "Description of the protagonist (e.g., 'A small blue robot with rusty gears')",
|
||||
"art_style": "Visual style description (e.g., 'Watercolor, soft pastel colors, whimsical')",
|
||||
"pages": [
|
||||
{
|
||||
"page_number": 1,
|
||||
"text": "Page text in Chinese (30-60 chars).",
|
||||
"image_prompt": "Detailed English image prompt describing the scene. Include 'main_character' reference."
|
||||
}
|
||||
],
|
||||
"cover_prompt": "English image prompt for the book cover."
|
||||
}
|
||||
"""
|
||||
|
||||
USER_PROMPT_STORYBOOK = """
|
||||
# Task: Create a {page_count}-Page Storybook
|
||||
|
||||
## Contextual Memory
|
||||
{memory_context}
|
||||
|
||||
## Inputs
|
||||
- **Keywords/Topic**: {keywords}
|
||||
- **Educational Theme**: {education_theme}
|
||||
- **Magic Element**: {random_element}
|
||||
|
||||
## Constraints
|
||||
- Pages: Exactly {page_count} pages.
|
||||
- Structure: Intro -> Development -> Climax -> Resolution.
|
||||
"""
|
||||
|
||||
@@ -1,141 +1,141 @@
|
||||
"""Redis-backed rate limiter with in-memory fallback.
|
||||
|
||||
Uses a fixed-window counter pattern via Redis INCR + EXPIRE.
|
||||
Falls back to an in-memory TTLCache when Redis is unavailable,
|
||||
preserving identical behavior for dev/test environments.
|
||||
"""
|
||||
|
||||
import time
|
||||
|
||||
from cachetools import TTLCache
|
||||
from fastapi import HTTPException
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.core.redis import get_redis
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
# ── In-memory fallback caches ──────────────────────────────────────────────
|
||||
_local_rate_cache: TTLCache[str, int] = TTLCache(maxsize=10000, ttl=120)
|
||||
_local_lockout_cache: TTLCache[str, tuple[int, float]] = TTLCache(maxsize=1000, ttl=900)
|
||||
|
||||
|
||||
async def check_rate_limit(key: str, limit: int, window_seconds: int) -> None:
|
||||
"""Check and increment a sliding-window rate counter.
|
||||
|
||||
Args:
|
||||
key: Unique identifier (e.g. ``"story:<user_id>"``).
|
||||
limit: Maximum requests allowed within the window.
|
||||
window_seconds: Window duration in seconds.
|
||||
|
||||
Raises:
|
||||
HTTPException: 429 when the limit is exceeded.
|
||||
"""
|
||||
try:
|
||||
redis = await get_redis()
|
||||
# Fixed-window bucket: key + minute boundary
|
||||
bucket = int(time.time() // window_seconds)
|
||||
redis_key = f"ratelimit:{key}:{bucket}"
|
||||
|
||||
count = await redis.incr(redis_key)
|
||||
if count == 1:
|
||||
await redis.expire(redis_key, window_seconds)
|
||||
|
||||
if count > limit:
|
||||
raise HTTPException(
|
||||
status_code=429,
|
||||
detail="Too many requests, please slow down.",
|
||||
)
|
||||
return
|
||||
except HTTPException:
|
||||
raise
|
||||
except Exception as exc:
|
||||
logger.warning("rate_limit_redis_fallback", error=str(exc))
|
||||
|
||||
# ── Fallback: in-memory counter ────────────────────────────────────────
|
||||
count = _local_rate_cache.get(key, 0) + 1
|
||||
_local_rate_cache[key] = count
|
||||
if count > limit:
|
||||
raise HTTPException(
|
||||
status_code=429,
|
||||
detail="Too many requests, please slow down.",
|
||||
)
|
||||
|
||||
|
||||
async def record_failed_attempt(
|
||||
key: str,
|
||||
max_attempts: int,
|
||||
lockout_seconds: int,
|
||||
) -> bool:
|
||||
"""Record a failed login attempt and return whether the key is locked out.
|
||||
|
||||
Args:
|
||||
key: Unique identifier (e.g. ``"admin_login:<ip>"``).
|
||||
max_attempts: Number of failures before lockout.
|
||||
lockout_seconds: Duration of lockout in seconds.
|
||||
|
||||
Returns:
|
||||
``True`` if the key is now locked out, ``False`` otherwise.
|
||||
"""
|
||||
try:
|
||||
redis = await get_redis()
|
||||
redis_key = f"lockout:{key}"
|
||||
|
||||
count = await redis.incr(redis_key)
|
||||
if count == 1:
|
||||
await redis.expire(redis_key, lockout_seconds)
|
||||
|
||||
return count >= max_attempts
|
||||
except Exception as exc:
|
||||
logger.warning("lockout_redis_fallback", error=str(exc))
|
||||
|
||||
# ── Fallback ───────────────────────────────────────────────────────────
|
||||
if key in _local_lockout_cache:
|
||||
attempts, first_fail = _local_lockout_cache[key]
|
||||
_local_lockout_cache[key] = (attempts + 1, first_fail)
|
||||
return (attempts + 1) >= max_attempts
|
||||
else:
|
||||
_local_lockout_cache[key] = (1, time.time())
|
||||
return 1 >= max_attempts
|
||||
|
||||
|
||||
async def is_locked_out(key: str, max_attempts: int, lockout_seconds: int) -> int:
|
||||
"""Check if a key is currently locked out.
|
||||
|
||||
Returns:
|
||||
Remaining lockout seconds (> 0 means locked), 0 means not locked.
|
||||
"""
|
||||
try:
|
||||
redis = await get_redis()
|
||||
redis_key = f"lockout:{key}"
|
||||
|
||||
count = await redis.get(redis_key)
|
||||
if count is not None and int(count) >= max_attempts:
|
||||
ttl = await redis.ttl(redis_key)
|
||||
return max(ttl, 0)
|
||||
return 0
|
||||
except Exception as exc:
|
||||
logger.warning("lockout_check_redis_fallback", error=str(exc))
|
||||
|
||||
# ── Fallback ───────────────────────────────────────────────────────────
|
||||
if key in _local_lockout_cache:
|
||||
attempts, first_fail = _local_lockout_cache[key]
|
||||
if attempts >= max_attempts:
|
||||
remaining = int(lockout_seconds - (time.time() - first_fail))
|
||||
if remaining > 0:
|
||||
return remaining
|
||||
else:
|
||||
del _local_lockout_cache[key]
|
||||
return 0
|
||||
|
||||
|
||||
async def clear_failed_attempts(key: str) -> None:
|
||||
"""Clear lockout state on successful login."""
|
||||
try:
|
||||
redis = await get_redis()
|
||||
await redis.delete(f"lockout:{key}")
|
||||
except Exception as exc:
|
||||
logger.warning("lockout_clear_redis_fallback", error=str(exc))
|
||||
|
||||
# Always clear local cache too
|
||||
_local_lockout_cache.pop(key, None)
|
||||
"""Redis-backed rate limiter with in-memory fallback.
|
||||
|
||||
Uses a fixed-window counter pattern via Redis INCR + EXPIRE.
|
||||
Falls back to an in-memory TTLCache when Redis is unavailable,
|
||||
preserving identical behavior for dev/test environments.
|
||||
"""
|
||||
|
||||
import time
|
||||
|
||||
from cachetools import TTLCache
|
||||
from fastapi import HTTPException
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.core.redis import get_redis
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
# ── In-memory fallback caches ──────────────────────────────────────────────
|
||||
_local_rate_cache: TTLCache[str, int] = TTLCache(maxsize=10000, ttl=120)
|
||||
_local_lockout_cache: TTLCache[str, tuple[int, float]] = TTLCache(maxsize=1000, ttl=900)
|
||||
|
||||
|
||||
async def check_rate_limit(key: str, limit: int, window_seconds: int) -> None:
|
||||
"""Check and increment a sliding-window rate counter.
|
||||
|
||||
Args:
|
||||
key: Unique identifier (e.g. ``"story:<user_id>"``).
|
||||
limit: Maximum requests allowed within the window.
|
||||
window_seconds: Window duration in seconds.
|
||||
|
||||
Raises:
|
||||
HTTPException: 429 when the limit is exceeded.
|
||||
"""
|
||||
try:
|
||||
redis = await get_redis()
|
||||
# Fixed-window bucket: key + minute boundary
|
||||
bucket = int(time.time() // window_seconds)
|
||||
redis_key = f"ratelimit:{key}:{bucket}"
|
||||
|
||||
count = await redis.incr(redis_key)
|
||||
if count == 1:
|
||||
await redis.expire(redis_key, window_seconds)
|
||||
|
||||
if count > limit:
|
||||
raise HTTPException(
|
||||
status_code=429,
|
||||
detail="Too many requests, please slow down.",
|
||||
)
|
||||
return
|
||||
except HTTPException:
|
||||
raise
|
||||
except Exception as exc:
|
||||
logger.warning("rate_limit_redis_fallback", error=str(exc))
|
||||
|
||||
# ── Fallback: in-memory counter ────────────────────────────────────────
|
||||
count = _local_rate_cache.get(key, 0) + 1
|
||||
_local_rate_cache[key] = count
|
||||
if count > limit:
|
||||
raise HTTPException(
|
||||
status_code=429,
|
||||
detail="Too many requests, please slow down.",
|
||||
)
|
||||
|
||||
|
||||
async def record_failed_attempt(
|
||||
key: str,
|
||||
max_attempts: int,
|
||||
lockout_seconds: int,
|
||||
) -> bool:
|
||||
"""Record a failed login attempt and return whether the key is locked out.
|
||||
|
||||
Args:
|
||||
key: Unique identifier (e.g. ``"admin_login:<ip>"``).
|
||||
max_attempts: Number of failures before lockout.
|
||||
lockout_seconds: Duration of lockout in seconds.
|
||||
|
||||
Returns:
|
||||
``True`` if the key is now locked out, ``False`` otherwise.
|
||||
"""
|
||||
try:
|
||||
redis = await get_redis()
|
||||
redis_key = f"lockout:{key}"
|
||||
|
||||
count = await redis.incr(redis_key)
|
||||
if count == 1:
|
||||
await redis.expire(redis_key, lockout_seconds)
|
||||
|
||||
return count >= max_attempts
|
||||
except Exception as exc:
|
||||
logger.warning("lockout_redis_fallback", error=str(exc))
|
||||
|
||||
# ── Fallback ───────────────────────────────────────────────────────────
|
||||
if key in _local_lockout_cache:
|
||||
attempts, first_fail = _local_lockout_cache[key]
|
||||
_local_lockout_cache[key] = (attempts + 1, first_fail)
|
||||
return (attempts + 1) >= max_attempts
|
||||
else:
|
||||
_local_lockout_cache[key] = (1, time.time())
|
||||
return 1 >= max_attempts
|
||||
|
||||
|
||||
async def is_locked_out(key: str, max_attempts: int, lockout_seconds: int) -> int:
|
||||
"""Check if a key is currently locked out.
|
||||
|
||||
Returns:
|
||||
Remaining lockout seconds (> 0 means locked), 0 means not locked.
|
||||
"""
|
||||
try:
|
||||
redis = await get_redis()
|
||||
redis_key = f"lockout:{key}"
|
||||
|
||||
count = await redis.get(redis_key)
|
||||
if count is not None and int(count) >= max_attempts:
|
||||
ttl = await redis.ttl(redis_key)
|
||||
return max(ttl, 0)
|
||||
return 0
|
||||
except Exception as exc:
|
||||
logger.warning("lockout_check_redis_fallback", error=str(exc))
|
||||
|
||||
# ── Fallback ───────────────────────────────────────────────────────────
|
||||
if key in _local_lockout_cache:
|
||||
attempts, first_fail = _local_lockout_cache[key]
|
||||
if attempts >= max_attempts:
|
||||
remaining = int(lockout_seconds - (time.time() - first_fail))
|
||||
if remaining > 0:
|
||||
return remaining
|
||||
else:
|
||||
del _local_lockout_cache[key]
|
||||
return 0
|
||||
|
||||
|
||||
async def clear_failed_attempts(key: str) -> None:
|
||||
"""Clear lockout state on successful login."""
|
||||
try:
|
||||
redis = await get_redis()
|
||||
await redis.delete(f"lockout:{key}")
|
||||
except Exception as exc:
|
||||
logger.warning("lockout_clear_redis_fallback", error=str(exc))
|
||||
|
||||
# Always clear local cache too
|
||||
_local_lockout_cache.pop(key, None)
|
||||
|
||||
@@ -1,25 +1,25 @@
|
||||
from datetime import datetime, timedelta, timezone
|
||||
|
||||
from jose import JWTError, jwt
|
||||
|
||||
from app.core.config import settings
|
||||
|
||||
ALGORITHM = "HS256"
|
||||
ACCESS_TOKEN_EXPIRE_DAYS = 7
|
||||
|
||||
|
||||
def create_access_token(data: dict) -> str:
|
||||
"""创建 JWT token"""
|
||||
to_encode = data.copy()
|
||||
expire = datetime.now(timezone.utc) + timedelta(days=ACCESS_TOKEN_EXPIRE_DAYS)
|
||||
to_encode.update({"exp": expire})
|
||||
return jwt.encode(to_encode, settings.secret_key, algorithm=ALGORITHM)
|
||||
|
||||
|
||||
def decode_access_token(token: str) -> dict | None:
|
||||
"""解码 JWT token"""
|
||||
try:
|
||||
payload = jwt.decode(token, settings.secret_key, algorithms=[ALGORITHM])
|
||||
return payload
|
||||
except JWTError:
|
||||
return None
|
||||
from datetime import datetime, timedelta, timezone
|
||||
|
||||
from jose import JWTError, jwt
|
||||
|
||||
from app.core.config import settings
|
||||
|
||||
ALGORITHM = "HS256"
|
||||
ACCESS_TOKEN_EXPIRE_DAYS = 7
|
||||
|
||||
|
||||
def create_access_token(data: dict) -> str:
|
||||
"""创建 JWT token"""
|
||||
to_encode = data.copy()
|
||||
expire = datetime.now(timezone.utc) + timedelta(days=ACCESS_TOKEN_EXPIRE_DAYS)
|
||||
to_encode.update({"exp": expire})
|
||||
return jwt.encode(to_encode, settings.secret_key, algorithm=ALGORITHM)
|
||||
|
||||
|
||||
def decode_access_token(token: str) -> dict | None:
|
||||
"""解码 JWT token"""
|
||||
try:
|
||||
payload = jwt.decode(token, settings.secret_key, algorithms=[ALGORITHM])
|
||||
return payload
|
||||
except JWTError:
|
||||
return None
|
||||
|
||||
@@ -1 +1 @@
|
||||
"""故事相关 Schema 模块。"""
|
||||
"""故事相关 Schema 模块。"""
|
||||
|
||||
@@ -1,21 +1,21 @@
|
||||
"""适配器模块 - 供应商平台化架构核心。"""
|
||||
|
||||
from app.services.adapters.base import AdapterConfig, BaseAdapter
|
||||
|
||||
# Image adapters
|
||||
from app.services.adapters.image import cqtai as _image_cqtai_adapter # noqa: F401
|
||||
from app.services.adapters.registry import AdapterRegistry
|
||||
|
||||
# Storybook adapters
|
||||
from app.services.adapters.storybook import primary as _storybook_primary # noqa: F401
|
||||
from app.services.adapters.text import gemini as _text_gemini_adapter # noqa: F401
|
||||
|
||||
# 导入所有适配器以触发注册
|
||||
# Text adapters
|
||||
from app.services.adapters.text import openai as _text_openai_adapter # noqa: F401
|
||||
|
||||
# TTS adapters
|
||||
from app.services.adapters.tts import elevenlabs as _tts_elevenlabs_adapter # noqa: F401
|
||||
from app.services.adapters.tts import minimax as _tts_minimax_adapter # noqa: F401
|
||||
|
||||
__all__ = ["AdapterConfig", "BaseAdapter", "AdapterRegistry"]
|
||||
"""适配器模块 - 供应商平台化架构核心。"""
|
||||
|
||||
from app.services.adapters.base import AdapterConfig, BaseAdapter
|
||||
|
||||
# Image adapters
|
||||
from app.services.adapters.image import cqtai as _image_cqtai_adapter # noqa: F401
|
||||
from app.services.adapters.registry import AdapterRegistry
|
||||
|
||||
# Storybook adapters
|
||||
from app.services.adapters.storybook import primary as _storybook_primary # noqa: F401
|
||||
from app.services.adapters.text import gemini as _text_gemini_adapter # noqa: F401
|
||||
|
||||
# 导入所有适配器以触发注册
|
||||
# Text adapters
|
||||
from app.services.adapters.text import openai as _text_openai_adapter # noqa: F401
|
||||
|
||||
# TTS adapters
|
||||
from app.services.adapters.tts import elevenlabs as _tts_elevenlabs_adapter # noqa: F401
|
||||
from app.services.adapters.tts import minimax as _tts_minimax_adapter # noqa: F401
|
||||
|
||||
__all__ = ["AdapterConfig", "BaseAdapter", "AdapterRegistry"]
|
||||
|
||||
@@ -1,46 +1,46 @@
|
||||
"""适配器基类定义。"""
|
||||
|
||||
from abc import ABC, abstractmethod
|
||||
from typing import Generic, TypeVar
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
T = TypeVar("T")
|
||||
|
||||
|
||||
class AdapterConfig(BaseModel):
|
||||
"""适配器配置基类。"""
|
||||
|
||||
api_key: str
|
||||
api_base: str | None = None
|
||||
model: str | None = None
|
||||
timeout_ms: int = 60000
|
||||
max_retries: int = 3
|
||||
extra_config: dict = {}
|
||||
|
||||
|
||||
class BaseAdapter(ABC, Generic[T]):
|
||||
"""适配器基类，所有供应商适配器必须继承此类。"""
|
||||
|
||||
# 子类必须定义
|
||||
adapter_type: str # text / image / tts
|
||||
adapter_name: str # text_primary / image_primary / tts_primary
|
||||
|
||||
def __init__(self, config: AdapterConfig):
|
||||
self.config = config
|
||||
|
||||
@abstractmethod
|
||||
async def execute(self, **kwargs) -> T:
|
||||
"""执行适配器逻辑，返回结果。"""
|
||||
pass
|
||||
|
||||
@abstractmethod
|
||||
async def health_check(self) -> bool:
|
||||
"""健康检查，返回是否可用。"""
|
||||
pass
|
||||
|
||||
@property
|
||||
@abstractmethod
|
||||
def estimated_cost(self) -> float:
|
||||
"""预估单次调用成本 (USD)。"""
|
||||
pass
|
||||
"""适配器基类定义。"""
|
||||
|
||||
from abc import ABC, abstractmethod
|
||||
from typing import Generic, TypeVar
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
T = TypeVar("T")
|
||||
|
||||
|
||||
class AdapterConfig(BaseModel):
|
||||
"""适配器配置基类。"""
|
||||
|
||||
api_key: str
|
||||
api_base: str | None = None
|
||||
model: str | None = None
|
||||
timeout_ms: int = 60000
|
||||
max_retries: int = 3
|
||||
extra_config: dict = {}
|
||||
|
||||
|
||||
class BaseAdapter(ABC, Generic[T]):
|
||||
"""适配器基类，所有供应商适配器必须继承此类。"""
|
||||
|
||||
# 子类必须定义
|
||||
adapter_type: str # text / image / tts
|
||||
adapter_name: str # text_primary / image_primary / tts_primary
|
||||
|
||||
def __init__(self, config: AdapterConfig):
|
||||
self.config = config
|
||||
|
||||
@abstractmethod
|
||||
async def execute(self, **kwargs) -> T:
|
||||
"""执行适配器逻辑，返回结果。"""
|
||||
pass
|
||||
|
||||
@abstractmethod
|
||||
async def health_check(self) -> bool:
|
||||
"""健康检查，返回是否可用。"""
|
||||
pass
|
||||
|
||||
@property
|
||||
@abstractmethod
|
||||
def estimated_cost(self) -> float:
|
||||
"""预估单次调用成本 (USD)。"""
|
||||
pass
|
||||
|
||||
@@ -1,3 +1,3 @@
|
||||
"""图像生成适配器。"""# Image adapters
|
||||
from app.services.adapters.image import cqtai as _image_cqtai_adapter # noqa: F401
|
||||
from app.services.adapters.image import antigravity as _image_antigravity_adapter # noqa: F401
|
||||
"""图像生成适配器。"""# Image adapters
|
||||
from app.services.adapters.image import cqtai as _image_cqtai_adapter # noqa: F401
|
||||
from app.services.adapters.image import antigravity as _image_antigravity_adapter # noqa: F401
|
||||
|
||||
@@ -1,214 +1,214 @@
|
||||
"""Antigravity 图像生成适配器。
|
||||
|
||||
使用 OpenAI 兼容 API 生成图像。
|
||||
支持 gemini-3-pro-image 等模型。
|
||||
"""
|
||||
|
||||
import base64
|
||||
import time
|
||||
from typing import Any
|
||||
|
||||
from openai import AsyncOpenAI
|
||||
from tenacity import (
|
||||
retry,
|
||||
retry_if_exception_type,
|
||||
stop_after_attempt,
|
||||
wait_exponential,
|
||||
)
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.services.adapters.base import AdapterConfig, BaseAdapter
|
||||
from app.services.adapters.registry import AdapterRegistry
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
# 默认配置
|
||||
DEFAULT_API_BASE = "http://127.0.0.1:8045/v1"
|
||||
DEFAULT_MODEL = "gemini-3-pro-image"
|
||||
DEFAULT_SIZE = "1024x1024"
|
||||
|
||||
# 支持的尺寸映射
|
||||
SUPPORTED_SIZES = {
|
||||
"1024x1024": "1:1",
|
||||
"1280x720": "16:9",
|
||||
"720x1280": "9:16",
|
||||
"1216x896": "4:3",
|
||||
}
|
||||
|
||||
|
||||
@AdapterRegistry.register("image", "antigravity")
|
||||
class AntigravityImageAdapter(BaseAdapter[str]):
|
||||
"""Antigravity 图像生成适配器 (OpenAI 兼容 API)。
|
||||
|
||||
特点:
|
||||
- 使用 OpenAI 兼容的 chat.completions 端点
|
||||
- 通过 extra_body.size 指定图像尺寸
|
||||
- 支持 gemini-3-pro-image 等模型
|
||||
- 返回图片 URL 或 base64
|
||||
"""
|
||||
|
||||
adapter_type = "image"
|
||||
adapter_name = "antigravity"
|
||||
|
||||
def __init__(self, config: AdapterConfig):
|
||||
super().__init__(config)
|
||||
self.api_base = config.api_base or DEFAULT_API_BASE
|
||||
self.client = AsyncOpenAI(
|
||||
base_url=self.api_base,
|
||||
api_key=config.api_key,
|
||||
timeout=config.timeout_ms / 1000,
|
||||
)
|
||||
|
||||
async def execute(
|
||||
self,
|
||||
prompt: str,
|
||||
model: str | None = None,
|
||||
size: str | None = None,
|
||||
num_images: int = 1,
|
||||
**kwargs,
|
||||
) -> str | list[str]:
|
||||
"""根据提示词生成图片，返回 URL 或 base64。
|
||||
|
||||
Args:
|
||||
prompt: 图片描述提示词
|
||||
model: 模型名称 (gemini-3-pro-image / gemini-3-pro-image-16-9 等)
|
||||
size: 图像尺寸 (1024x1024, 1280x720, 720x1280, 1216x896)
|
||||
num_images: 生成图片数量 (暂只支持 1)
|
||||
|
||||
Returns:
|
||||
图片 URL 或 base64 字符串
|
||||
"""
|
||||
# 优先使用传入参数，其次使用 Adapter 配置，最后使用默认值
|
||||
model = model or self.config.model or DEFAULT_MODEL
|
||||
|
||||
cfg = self.config.extra_config or {}
|
||||
size = size or cfg.get("size") or DEFAULT_SIZE
|
||||
|
||||
start_time = time.time()
|
||||
logger.info(
|
||||
"antigravity_generate_start",
|
||||
prompt_length=len(prompt),
|
||||
model=model,
|
||||
size=size,
|
||||
)
|
||||
|
||||
# 调用 API
|
||||
image_url = await self._generate_image(prompt, model, size)
|
||||
|
||||
elapsed = time.time() - start_time
|
||||
logger.info(
|
||||
"antigravity_generate_success",
|
||||
elapsed_seconds=round(elapsed, 2),
|
||||
model=model,
|
||||
)
|
||||
|
||||
return image_url
|
||||
|
||||
async def health_check(self) -> bool:
|
||||
"""检查 Antigravity API 是否可用。"""
|
||||
try:
|
||||
# 简单测试连通性
|
||||
response = await self.client.chat.completions.create(
|
||||
model=self.config.model or DEFAULT_MODEL,
|
||||
messages=[{"role": "user", "content": "test"}],
|
||||
max_tokens=1,
|
||||
)
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.warning("antigravity_health_check_failed", error=str(e))
|
||||
return False
|
||||
|
||||
@property
|
||||
def estimated_cost(self) -> float:
|
||||
"""预估每张图片成本 (USD)。
|
||||
|
||||
Antigravity 使用 Gemini 模型，成本约 $0.02/张。
|
||||
"""
|
||||
return 0.02
|
||||
|
||||
@retry(
|
||||
stop=stop_after_attempt(3),
|
||||
wait=wait_exponential(multiplier=1, min=1, max=10),
|
||||
retry=retry_if_exception_type((Exception,)),
|
||||
reraise=True,
|
||||
)
|
||||
async def _generate_image(
|
||||
self,
|
||||
prompt: str,
|
||||
model: str,
|
||||
size: str,
|
||||
) -> str:
|
||||
"""调用 Antigravity API 生成图像。
|
||||
|
||||
Returns:
|
||||
图片 URL 或 base64 data URI
|
||||
"""
|
||||
try:
|
||||
response = await self.client.chat.completions.create(
|
||||
model=model,
|
||||
messages=[{"role": "user", "content": prompt}],
|
||||
extra_body={"size": size},
|
||||
)
|
||||
|
||||
# 解析响应
|
||||
content = response.choices[0].message.content
|
||||
if not content:
|
||||
raise ValueError("Antigravity 未返回内容")
|
||||
|
||||
# 尝试解析为图片 URL 或 base64
|
||||
# 响应可能是纯 URL、base64 或 markdown 格式的图片
|
||||
image_url = self._extract_image_url(content)
|
||||
if image_url:
|
||||
return image_url
|
||||
|
||||
raise ValueError(f"Antigravity 响应无法解析为图片: {content[:200]}")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(
|
||||
"antigravity_generate_error",
|
||||
error=str(e),
|
||||
model=model,
|
||||
)
|
||||
raise
|
||||
|
||||
def _extract_image_url(self, content: str) -> str | None:
|
||||
"""从响应内容中提取图片 URL。
|
||||
|
||||
支持多种格式:
|
||||
- 纯 URL: https://...
|
||||
- Markdown: 
|
||||
- Base64 data URI: data:image/...
|
||||
- 纯 base64 字符串
|
||||
"""
|
||||
content = content.strip()
|
||||
|
||||
# 1. 检查是否为 data URI
|
||||
if content.startswith("data:image/"):
|
||||
return content
|
||||
|
||||
# 2. 检查是否为纯 URL
|
||||
if content.startswith("http://") or content.startswith("https://"):
|
||||
# 可能有多行，取第一行
|
||||
return content.split("\n")[0].strip()
|
||||
|
||||
# 3. 检查 Markdown 图片格式 
|
||||
import re
|
||||
md_match = re.search(r"!\[.*?\]\((https?://[^\)]+)\)", content)
|
||||
if md_match:
|
||||
return md_match.group(1)
|
||||
|
||||
# 4. 检查是否像 base64 编码的图片数据
|
||||
if self._looks_like_base64(content):
|
||||
# 假设是 PNG
|
||||
return f"data:image/png;base64,{content}"
|
||||
|
||||
return None
|
||||
|
||||
def _looks_like_base64(self, s: str) -> bool:
|
||||
"""判断字符串是否看起来像 base64 编码。"""
|
||||
# Base64 只包含 A-Z, a-z, 0-9, +, /, =
|
||||
# 且长度通常较长
|
||||
if len(s) < 100:
|
||||
return False
|
||||
import re
|
||||
return bool(re.match(r"^[A-Za-z0-9+/=]+$", s.replace("\n", "")))
|
||||
"""Antigravity 图像生成适配器。
|
||||
|
||||
使用 OpenAI 兼容 API 生成图像。
|
||||
支持 gemini-3-pro-image 等模型。
|
||||
"""
|
||||
|
||||
import base64
|
||||
import time
|
||||
from typing import Any
|
||||
|
||||
from openai import AsyncOpenAI
|
||||
from tenacity import (
|
||||
retry,
|
||||
retry_if_exception_type,
|
||||
stop_after_attempt,
|
||||
wait_exponential,
|
||||
)
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.services.adapters.base import AdapterConfig, BaseAdapter
|
||||
from app.services.adapters.registry import AdapterRegistry
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
# 默认配置
|
||||
DEFAULT_API_BASE = "http://127.0.0.1:8045/v1"
|
||||
DEFAULT_MODEL = "gemini-3-pro-image"
|
||||
DEFAULT_SIZE = "1024x1024"
|
||||
|
||||
# 支持的尺寸映射
|
||||
SUPPORTED_SIZES = {
|
||||
"1024x1024": "1:1",
|
||||
"1280x720": "16:9",
|
||||
"720x1280": "9:16",
|
||||
"1216x896": "4:3",
|
||||
}
|
||||
|
||||
|
||||
@AdapterRegistry.register("image", "antigravity")
|
||||
class AntigravityImageAdapter(BaseAdapter[str]):
|
||||
"""Antigravity 图像生成适配器 (OpenAI 兼容 API)。
|
||||
|
||||
特点:
|
||||
- 使用 OpenAI 兼容的 chat.completions 端点
|
||||
- 通过 extra_body.size 指定图像尺寸
|
||||
- 支持 gemini-3-pro-image 等模型
|
||||
- 返回图片 URL 或 base64
|
||||
"""
|
||||
|
||||
adapter_type = "image"
|
||||
adapter_name = "antigravity"
|
||||
|
||||
def __init__(self, config: AdapterConfig):
|
||||
super().__init__(config)
|
||||
self.api_base = config.api_base or DEFAULT_API_BASE
|
||||
self.client = AsyncOpenAI(
|
||||
base_url=self.api_base,
|
||||
api_key=config.api_key,
|
||||
timeout=config.timeout_ms / 1000,
|
||||
)
|
||||
|
||||
async def execute(
|
||||
self,
|
||||
prompt: str,
|
||||
model: str | None = None,
|
||||
size: str | None = None,
|
||||
num_images: int = 1,
|
||||
**kwargs,
|
||||
) -> str | list[str]:
|
||||
"""根据提示词生成图片，返回 URL 或 base64。
|
||||
|
||||
Args:
|
||||
prompt: 图片描述提示词
|
||||
model: 模型名称 (gemini-3-pro-image / gemini-3-pro-image-16-9 等)
|
||||
size: 图像尺寸 (1024x1024, 1280x720, 720x1280, 1216x896)
|
||||
num_images: 生成图片数量 (暂只支持 1)
|
||||
|
||||
Returns:
|
||||
图片 URL 或 base64 字符串
|
||||
"""
|
||||
# 优先使用传入参数，其次使用 Adapter 配置，最后使用默认值
|
||||
model = model or self.config.model or DEFAULT_MODEL
|
||||
|
||||
cfg = self.config.extra_config or {}
|
||||
size = size or cfg.get("size") or DEFAULT_SIZE
|
||||
|
||||
start_time = time.time()
|
||||
logger.info(
|
||||
"antigravity_generate_start",
|
||||
prompt_length=len(prompt),
|
||||
model=model,
|
||||
size=size,
|
||||
)
|
||||
|
||||
# 调用 API
|
||||
image_url = await self._generate_image(prompt, model, size)
|
||||
|
||||
elapsed = time.time() - start_time
|
||||
logger.info(
|
||||
"antigravity_generate_success",
|
||||
elapsed_seconds=round(elapsed, 2),
|
||||
model=model,
|
||||
)
|
||||
|
||||
return image_url
|
||||
|
||||
async def health_check(self) -> bool:
|
||||
"""检查 Antigravity API 是否可用。"""
|
||||
try:
|
||||
# 简单测试连通性
|
||||
response = await self.client.chat.completions.create(
|
||||
model=self.config.model or DEFAULT_MODEL,
|
||||
messages=[{"role": "user", "content": "test"}],
|
||||
max_tokens=1,
|
||||
)
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.warning("antigravity_health_check_failed", error=str(e))
|
||||
return False
|
||||
|
||||
@property
|
||||
def estimated_cost(self) -> float:
|
||||
"""预估每张图片成本 (USD)。
|
||||
|
||||
Antigravity 使用 Gemini 模型，成本约 $0.02/张。
|
||||
"""
|
||||
return 0.02
|
||||
|
||||
@retry(
|
||||
stop=stop_after_attempt(3),
|
||||
wait=wait_exponential(multiplier=1, min=1, max=10),
|
||||
retry=retry_if_exception_type((Exception,)),
|
||||
reraise=True,
|
||||
)
|
||||
async def _generate_image(
|
||||
self,
|
||||
prompt: str,
|
||||
model: str,
|
||||
size: str,
|
||||
) -> str:
|
||||
"""调用 Antigravity API 生成图像。
|
||||
|
||||
Returns:
|
||||
图片 URL 或 base64 data URI
|
||||
"""
|
||||
try:
|
||||
response = await self.client.chat.completions.create(
|
||||
model=model,
|
||||
messages=[{"role": "user", "content": prompt}],
|
||||
extra_body={"size": size},
|
||||
)
|
||||
|
||||
# 解析响应
|
||||
content = response.choices[0].message.content
|
||||
if not content:
|
||||
raise ValueError("Antigravity 未返回内容")
|
||||
|
||||
# 尝试解析为图片 URL 或 base64
|
||||
# 响应可能是纯 URL、base64 或 markdown 格式的图片
|
||||
image_url = self._extract_image_url(content)
|
||||
if image_url:
|
||||
return image_url
|
||||
|
||||
raise ValueError(f"Antigravity 响应无法解析为图片: {content[:200]}")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(
|
||||
"antigravity_generate_error",
|
||||
error=str(e),
|
||||
model=model,
|
||||
)
|
||||
raise
|
||||
|
||||
def _extract_image_url(self, content: str) -> str | None:
|
||||
"""从响应内容中提取图片 URL。
|
||||
|
||||
支持多种格式:
|
||||
- 纯 URL: https://...
|
||||
- Markdown: 
|
||||
- Base64 data URI: data:image/...
|
||||
- 纯 base64 字符串
|
||||
"""
|
||||
content = content.strip()
|
||||
|
||||
# 1. 检查是否为 data URI
|
||||
if content.startswith("data:image/"):
|
||||
return content
|
||||
|
||||
# 2. 检查是否为纯 URL
|
||||
if content.startswith("http://") or content.startswith("https://"):
|
||||
# 可能有多行，取第一行
|
||||
return content.split("\n")[0].strip()
|
||||
|
||||
# 3. 检查 Markdown 图片格式 
|
||||
import re
|
||||
md_match = re.search(r"!\[.*?\]\((https?://[^\)]+)\)", content)
|
||||
if md_match:
|
||||
return md_match.group(1)
|
||||
|
||||
# 4. 检查是否像 base64 编码的图片数据
|
||||
if self._looks_like_base64(content):
|
||||
# 假设是 PNG
|
||||
return f"data:image/png;base64,{content}"
|
||||
|
||||
return None
|
||||
|
||||
def _looks_like_base64(self, s: str) -> bool:
|
||||
"""判断字符串是否看起来像 base64 编码。"""
|
||||
# Base64 只包含 A-Z, a-z, 0-9, +, /, =
|
||||
# 且长度通常较长
|
||||
if len(s) < 100:
|
||||
return False
|
||||
import re
|
||||
return bool(re.match(r"^[A-Za-z0-9+/=]+$", s.replace("\n", "")))
|
||||
|
||||
@@ -1,252 +1,252 @@
|
||||
"""CQTAI nano 图像生成适配器。
|
||||
|
||||
支持异步生成 + 轮询获取结果。
|
||||
API 文档: https://api.cqtai.com
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import time
|
||||
|
||||
import httpx
|
||||
from tenacity import (
|
||||
retry,
|
||||
retry_if_exception_type,
|
||||
stop_after_attempt,
|
||||
wait_exponential,
|
||||
)
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.services.adapters.base import AdapterConfig, BaseAdapter
|
||||
from app.services.adapters.registry import AdapterRegistry
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
# 默认配置
|
||||
DEFAULT_API_BASE = "https://api.cqtai.com"
|
||||
DEFAULT_MODEL = "nano-banana"
|
||||
DEFAULT_RESOLUTION = "2K"
|
||||
DEFAULT_ASPECT_RATIO = "1:1"
|
||||
POLL_INTERVAL_SECONDS = 2
|
||||
MAX_POLL_ATTEMPTS = 60 # 最多轮询 2 分钟
|
||||
|
||||
|
||||
@AdapterRegistry.register("image", "cqtai")
|
||||
class CQTAIImageAdapter(BaseAdapter[str]):
|
||||
"""CQTAI nano 图像生成适配器，返回图片 URL。
|
||||
|
||||
特点:
|
||||
- 异步生成 + 轮询获取结果
|
||||
- 支持 nano-banana (标准) 和 nano-banana-pro (高画质)
|
||||
- 支持多种分辨率和画面比例
|
||||
- 支持图生图 (filesUrl)
|
||||
"""
|
||||
|
||||
adapter_type = "image"
|
||||
adapter_name = "cqtai"
|
||||
|
||||
def __init__(self, config: AdapterConfig):
|
||||
super().__init__(config)
|
||||
self.api_base = config.api_base or DEFAULT_API_BASE
|
||||
|
||||
async def execute(
|
||||
self,
|
||||
prompt: str,
|
||||
model: str | None = None,
|
||||
resolution: str | None = None,
|
||||
aspect_ratio: str | None = None,
|
||||
num_images: int = 1,
|
||||
files_url: list[str] | None = None,
|
||||
**kwargs,
|
||||
) -> str | list[str]:
|
||||
"""根据提示词生成图片，返回 URL 或 URL 列表。
|
||||
|
||||
Args:
|
||||
prompt: 图片描述提示词
|
||||
model: 模型名称 (nano-banana / nano-banana-pro)
|
||||
resolution: 分辨率 (1K / 2K / 4K)
|
||||
aspect_ratio: 画面比例 (1:1, 16:9, 9:16, 4:3, 3:4 等)
|
||||
num_images: 生成图片数量 (1-4)
|
||||
files_url: 输入图片 URL 列表 (图生图)
|
||||
|
||||
Returns:
|
||||
单张图片返回 str，多张返回 list[str]
|
||||
"""
|
||||
# 1. 优先使用传入参数
|
||||
# 2. 其次使用 Adapter 配置里的 default (extra_config)
|
||||
# 3. 最后使用系统默认值
|
||||
model = model or self.config.model or DEFAULT_MODEL
|
||||
|
||||
cfg = self.config.extra_config or {}
|
||||
resolution = resolution or cfg.get("resolution") or DEFAULT_RESOLUTION
|
||||
aspect_ratio = aspect_ratio or cfg.get("aspect_ratio") or DEFAULT_ASPECT_RATIO
|
||||
num_images = min(max(num_images, 1), 4) # 限制 1-4
|
||||
|
||||
start_time = time.time()
|
||||
logger.info(
|
||||
"cqtai_generate_start",
|
||||
prompt_length=len(prompt),
|
||||
model=model,
|
||||
resolution=resolution,
|
||||
aspect_ratio=aspect_ratio,
|
||||
num_images=num_images,
|
||||
)
|
||||
|
||||
# 1. 提交生成任务
|
||||
task_id = await self._submit_task(
|
||||
prompt=prompt,
|
||||
model=model,
|
||||
resolution=resolution,
|
||||
aspect_ratio=aspect_ratio,
|
||||
num_images=num_images,
|
||||
files_url=files_url or [],
|
||||
)
|
||||
|
||||
logger.info("cqtai_task_submitted", task_id=task_id)
|
||||
|
||||
# 2. 轮询获取结果
|
||||
result = await self._poll_result(task_id)
|
||||
|
||||
elapsed = time.time() - start_time
|
||||
logger.info(
|
||||
"cqtai_generate_success",
|
||||
task_id=task_id,
|
||||
elapsed_seconds=round(elapsed, 2),
|
||||
image_count=len(result) if isinstance(result, list) else 1,
|
||||
)
|
||||
|
||||
# 单张图片返回字符串，多张返回列表
|
||||
if num_images == 1 and isinstance(result, list) and len(result) == 1:
|
||||
return result[0]
|
||||
return result
|
||||
|
||||
async def health_check(self) -> bool:
|
||||
"""检查 CQTAI API 是否可用。"""
|
||||
try:
|
||||
async with httpx.AsyncClient(timeout=10) as client:
|
||||
# 简单的连通性测试
|
||||
response = await client.get(
|
||||
f"{self.api_base}/api/cqt/info/nano",
|
||||
params={"id": "health_check_test"},
|
||||
headers={"Authorization": self.config.api_key},
|
||||
)
|
||||
# 即使返回错误也说明服务可达
|
||||
return response.status_code in (200, 400, 401, 403, 404)
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
@property
|
||||
def estimated_cost(self) -> float:
|
||||
"""预估每张图片成本 (USD)。
|
||||
|
||||
nano-banana: ¥0.1 ≈ $0.014
|
||||
nano-banana-pro: ¥0.2 ≈ $0.028
|
||||
"""
|
||||
model = self.config.model or DEFAULT_MODEL
|
||||
if model == "nano-banana-pro":
|
||||
return 0.028
|
||||
return 0.014
|
||||
|
||||
@retry(
|
||||
stop=stop_after_attempt(3),
|
||||
wait=wait_exponential(multiplier=1, min=1, max=10),
|
||||
retry=retry_if_exception_type((httpx.HTTPError, httpx.TimeoutException)),
|
||||
reraise=True,
|
||||
)
|
||||
async def _submit_task(
|
||||
self,
|
||||
prompt: str,
|
||||
model: str,
|
||||
resolution: str,
|
||||
aspect_ratio: str,
|
||||
num_images: int,
|
||||
files_url: list[str],
|
||||
) -> str:
|
||||
"""提交图像生成任务，返回任务 ID。"""
|
||||
timeout = self.config.timeout_ms / 1000
|
||||
|
||||
payload = {
|
||||
"prompt": prompt,
|
||||
"numImages": num_images,
|
||||
"aspectRatio": aspect_ratio,
|
||||
"filesUrl": files_url,
|
||||
}
|
||||
|
||||
# 可选参数，不传则使用默认值
|
||||
if model != DEFAULT_MODEL:
|
||||
payload["model"] = model
|
||||
if resolution != DEFAULT_RESOLUTION:
|
||||
payload["resolution"] = resolution
|
||||
|
||||
async with httpx.AsyncClient(timeout=timeout) as client:
|
||||
response = await client.post(
|
||||
f"{self.api_base}/api/cqt/generator/nano",
|
||||
json=payload,
|
||||
headers={
|
||||
"Authorization": self.config.api_key,
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
)
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
|
||||
if data.get("code") != 200:
|
||||
raise ValueError(f"CQTAI 任务提交失败: {data.get('msg', '未知错误')}")
|
||||
|
||||
task_id = data.get("data")
|
||||
if not task_id:
|
||||
raise ValueError("CQTAI 未返回任务 ID")
|
||||
|
||||
return task_id
|
||||
|
||||
async def _poll_result(self, task_id: str) -> list[str]:
|
||||
"""轮询获取生成结果。
|
||||
|
||||
Returns:
|
||||
图片 URL 列表
|
||||
"""
|
||||
timeout = self.config.timeout_ms / 1000
|
||||
|
||||
for attempt in range(MAX_POLL_ATTEMPTS):
|
||||
async with httpx.AsyncClient(timeout=timeout) as client:
|
||||
response = await client.get(
|
||||
f"{self.api_base}/api/cqt/info/nano",
|
||||
params={"id": task_id},
|
||||
headers={"Authorization": self.config.api_key},
|
||||
)
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
|
||||
if data.get("code") != 200:
|
||||
raise ValueError(f"CQTAI 查询失败: {data.get('msg', '未知错误')}")
|
||||
|
||||
result_data = data.get("data", {})
|
||||
status = result_data.get("status")
|
||||
|
||||
if status == "completed":
|
||||
# 提取图片 URL
|
||||
images = result_data.get("images", [])
|
||||
if not images:
|
||||
# 兼容不同返回格式
|
||||
image_url = result_data.get("imageUrl") or result_data.get("url")
|
||||
if image_url:
|
||||
images = [image_url]
|
||||
|
||||
if not images:
|
||||
raise ValueError("CQTAI 未返回图片 URL")
|
||||
|
||||
return images
|
||||
|
||||
elif status == "failed":
|
||||
error_msg = result_data.get("error", "生成失败")
|
||||
raise ValueError(f"CQTAI 图像生成失败: {error_msg}")
|
||||
|
||||
# 继续等待
|
||||
logger.debug(
|
||||
"cqtai_poll_waiting",
|
||||
task_id=task_id,
|
||||
attempt=attempt + 1,
|
||||
status=status,
|
||||
)
|
||||
await asyncio.sleep(POLL_INTERVAL_SECONDS)
|
||||
|
||||
raise TimeoutError(f"CQTAI 任务超时: {task_id}")
|
||||
"""CQTAI nano 图像生成适配器。
|
||||
|
||||
支持异步生成 + 轮询获取结果。
|
||||
API 文档: https://api.cqtai.com
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import time
|
||||
|
||||
import httpx
|
||||
from tenacity import (
|
||||
retry,
|
||||
retry_if_exception_type,
|
||||
stop_after_attempt,
|
||||
wait_exponential,
|
||||
)
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.services.adapters.base import AdapterConfig, BaseAdapter
|
||||
from app.services.adapters.registry import AdapterRegistry
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
# 默认配置
|
||||
DEFAULT_API_BASE = "https://api.cqtai.com"
|
||||
DEFAULT_MODEL = "nano-banana"
|
||||
DEFAULT_RESOLUTION = "2K"
|
||||
DEFAULT_ASPECT_RATIO = "1:1"
|
||||
POLL_INTERVAL_SECONDS = 2
|
||||
MAX_POLL_ATTEMPTS = 60 # 最多轮询 2 分钟
|
||||
|
||||
|
||||
@AdapterRegistry.register("image", "cqtai")
|
||||
class CQTAIImageAdapter(BaseAdapter[str]):
|
||||
"""CQTAI nano 图像生成适配器，返回图片 URL。
|
||||
|
||||
特点:
|
||||
- 异步生成 + 轮询获取结果
|
||||
- 支持 nano-banana (标准) 和 nano-banana-pro (高画质)
|
||||
- 支持多种分辨率和画面比例
|
||||
- 支持图生图 (filesUrl)
|
||||
"""
|
||||
|
||||
adapter_type = "image"
|
||||
adapter_name = "cqtai"
|
||||
|
||||
def __init__(self, config: AdapterConfig):
|
||||
super().__init__(config)
|
||||
self.api_base = config.api_base or DEFAULT_API_BASE
|
||||
|
||||
async def execute(
|
||||
self,
|
||||
prompt: str,
|
||||
model: str | None = None,
|
||||
resolution: str | None = None,
|
||||
aspect_ratio: str | None = None,
|
||||
num_images: int = 1,
|
||||
files_url: list[str] | None = None,
|
||||
**kwargs,
|
||||
) -> str | list[str]:
|
||||
"""根据提示词生成图片，返回 URL 或 URL 列表。
|
||||
|
||||
Args:
|
||||
prompt: 图片描述提示词
|
||||
model: 模型名称 (nano-banana / nano-banana-pro)
|
||||
resolution: 分辨率 (1K / 2K / 4K)
|
||||
aspect_ratio: 画面比例 (1:1, 16:9, 9:16, 4:3, 3:4 等)
|
||||
num_images: 生成图片数量 (1-4)
|
||||
files_url: 输入图片 URL 列表 (图生图)
|
||||
|
||||
Returns:
|
||||
单张图片返回 str，多张返回 list[str]
|
||||
"""
|
||||
# 1. 优先使用传入参数
|
||||
# 2. 其次使用 Adapter 配置里的 default (extra_config)
|
||||
# 3. 最后使用系统默认值
|
||||
model = model or self.config.model or DEFAULT_MODEL
|
||||
|
||||
cfg = self.config.extra_config or {}
|
||||
resolution = resolution or cfg.get("resolution") or DEFAULT_RESOLUTION
|
||||
aspect_ratio = aspect_ratio or cfg.get("aspect_ratio") or DEFAULT_ASPECT_RATIO
|
||||
num_images = min(max(num_images, 1), 4) # 限制 1-4
|
||||
|
||||
start_time = time.time()
|
||||
logger.info(
|
||||
"cqtai_generate_start",
|
||||
prompt_length=len(prompt),
|
||||
model=model,
|
||||
resolution=resolution,
|
||||
aspect_ratio=aspect_ratio,
|
||||
num_images=num_images,
|
||||
)
|
||||
|
||||
# 1. 提交生成任务
|
||||
task_id = await self._submit_task(
|
||||
prompt=prompt,
|
||||
model=model,
|
||||
resolution=resolution,
|
||||
aspect_ratio=aspect_ratio,
|
||||
num_images=num_images,
|
||||
files_url=files_url or [],
|
||||
)
|
||||
|
||||
logger.info("cqtai_task_submitted", task_id=task_id)
|
||||
|
||||
# 2. 轮询获取结果
|
||||
result = await self._poll_result(task_id)
|
||||
|
||||
elapsed = time.time() - start_time
|
||||
logger.info(
|
||||
"cqtai_generate_success",
|
||||
task_id=task_id,
|
||||
elapsed_seconds=round(elapsed, 2),
|
||||
image_count=len(result) if isinstance(result, list) else 1,
|
||||
)
|
||||
|
||||
# 单张图片返回字符串，多张返回列表
|
||||
if num_images == 1 and isinstance(result, list) and len(result) == 1:
|
||||
return result[0]
|
||||
return result
|
||||
|
||||
async def health_check(self) -> bool:
|
||||
"""检查 CQTAI API 是否可用。"""
|
||||
try:
|
||||
async with httpx.AsyncClient(timeout=10) as client:
|
||||
# 简单的连通性测试
|
||||
response = await client.get(
|
||||
f"{self.api_base}/api/cqt/info/nano",
|
||||
params={"id": "health_check_test"},
|
||||
headers={"Authorization": self.config.api_key},
|
||||
)
|
||||
# 即使返回错误也说明服务可达
|
||||
return response.status_code in (200, 400, 401, 403, 404)
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
@property
|
||||
def estimated_cost(self) -> float:
|
||||
"""预估每张图片成本 (USD)。
|
||||
|
||||
nano-banana: ¥0.1 ≈ $0.014
|
||||
nano-banana-pro: ¥0.2 ≈ $0.028
|
||||
"""
|
||||
model = self.config.model or DEFAULT_MODEL
|
||||
if model == "nano-banana-pro":
|
||||
return 0.028
|
||||
return 0.014
|
||||
|
||||
@retry(
|
||||
stop=stop_after_attempt(3),
|
||||
wait=wait_exponential(multiplier=1, min=1, max=10),
|
||||
retry=retry_if_exception_type((httpx.HTTPError, httpx.TimeoutException)),
|
||||
reraise=True,
|
||||
)
|
||||
async def _submit_task(
|
||||
self,
|
||||
prompt: str,
|
||||
model: str,
|
||||
resolution: str,
|
||||
aspect_ratio: str,
|
||||
num_images: int,
|
||||
files_url: list[str],
|
||||
) -> str:
|
||||
"""提交图像生成任务，返回任务 ID。"""
|
||||
timeout = self.config.timeout_ms / 1000
|
||||
|
||||
payload = {
|
||||
"prompt": prompt,
|
||||
"numImages": num_images,
|
||||
"aspectRatio": aspect_ratio,
|
||||
"filesUrl": files_url,
|
||||
}
|
||||
|
||||
# 可选参数，不传则使用默认值
|
||||
if model != DEFAULT_MODEL:
|
||||
payload["model"] = model
|
||||
if resolution != DEFAULT_RESOLUTION:
|
||||
payload["resolution"] = resolution
|
||||
|
||||
async with httpx.AsyncClient(timeout=timeout) as client:
|
||||
response = await client.post(
|
||||
f"{self.api_base}/api/cqt/generator/nano",
|
||||
json=payload,
|
||||
headers={
|
||||
"Authorization": self.config.api_key,
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
)
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
|
||||
if data.get("code") != 200:
|
||||
raise ValueError(f"CQTAI 任务提交失败: {data.get('msg', '未知错误')}")
|
||||
|
||||
task_id = data.get("data")
|
||||
if not task_id:
|
||||
raise ValueError("CQTAI 未返回任务 ID")
|
||||
|
||||
return task_id
|
||||
|
||||
async def _poll_result(self, task_id: str) -> list[str]:
|
||||
"""轮询获取生成结果。
|
||||
|
||||
Returns:
|
||||
图片 URL 列表
|
||||
"""
|
||||
timeout = self.config.timeout_ms / 1000
|
||||
|
||||
for attempt in range(MAX_POLL_ATTEMPTS):
|
||||
async with httpx.AsyncClient(timeout=timeout) as client:
|
||||
response = await client.get(
|
||||
f"{self.api_base}/api/cqt/info/nano",
|
||||
params={"id": task_id},
|
||||
headers={"Authorization": self.config.api_key},
|
||||
)
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
|
||||
if data.get("code") != 200:
|
||||
raise ValueError(f"CQTAI 查询失败: {data.get('msg', '未知错误')}")
|
||||
|
||||
result_data = data.get("data", {})
|
||||
status = result_data.get("status")
|
||||
|
||||
if status == "completed":
|
||||
# 提取图片 URL
|
||||
images = result_data.get("images", [])
|
||||
if not images:
|
||||
# 兼容不同返回格式
|
||||
image_url = result_data.get("imageUrl") or result_data.get("url")
|
||||
if image_url:
|
||||
images = [image_url]
|
||||
|
||||
if not images:
|
||||
raise ValueError("CQTAI 未返回图片 URL")
|
||||
|
||||
return images
|
||||
|
||||
elif status == "failed":
|
||||
error_msg = result_data.get("error", "生成失败")
|
||||
raise ValueError(f"CQTAI 图像生成失败: {error_msg}")
|
||||
|
||||
# 继续等待
|
||||
logger.debug(
|
||||
"cqtai_poll_waiting",
|
||||
task_id=task_id,
|
||||
attempt=attempt + 1,
|
||||
status=status,
|
||||
)
|
||||
await asyncio.sleep(POLL_INTERVAL_SECONDS)
|
||||
|
||||
raise TimeoutError(f"CQTAI 任务超时: {task_id}")
|
||||
|
||||
@@ -1,73 +1,73 @@
|
||||
"""适配器注册表 - 支持动态注册和工厂创建。"""
|
||||
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from app.services.adapters.base import AdapterConfig, BaseAdapter
|
||||
|
||||
|
||||
class AdapterRegistry:
|
||||
"""适配器注册表，管理所有已注册的适配器类。"""
|
||||
|
||||
_adapters: dict[str, type["BaseAdapter"]] = {}
|
||||
|
||||
@classmethod
|
||||
def register(cls, adapter_type: str, adapter_name: str):
|
||||
"""装饰器：注册适配器类。
|
||||
|
||||
用法:
|
||||
"""适配器注册表 - 支持动态注册和工厂创建。"""
|
||||
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from app.services.adapters.base import AdapterConfig, BaseAdapter
|
||||
|
||||
|
||||
class AdapterRegistry:
|
||||
"""适配器注册表，管理所有已注册的适配器类。"""
|
||||
|
||||
_adapters: dict[str, type["BaseAdapter"]] = {}
|
||||
|
||||
@classmethod
|
||||
def register(cls, adapter_type: str, adapter_name: str):
|
||||
"""装饰器：注册适配器类。
|
||||
|
||||
用法:
|
||||
@AdapterRegistry.register("text", "text_primary")
|
||||
class TextPrimaryAdapter(BaseAdapter[StoryOutput]):
|
||||
...
|
||||
"""
|
||||
|
||||
def decorator(adapter_class: type["BaseAdapter"]):
|
||||
key = f"{adapter_type}:{adapter_name}"
|
||||
cls._adapters[key] = adapter_class
|
||||
# 自动设置类属性
|
||||
adapter_class.adapter_type = adapter_type
|
||||
adapter_class.adapter_name = adapter_name
|
||||
return adapter_class
|
||||
|
||||
return decorator
|
||||
|
||||
@classmethod
|
||||
def get(cls, adapter_type: str, adapter_name: str) -> type["BaseAdapter"] | None:
|
||||
"""获取已注册的适配器类。"""
|
||||
key = f"{adapter_type}:{adapter_name}"
|
||||
return cls._adapters.get(key)
|
||||
|
||||
@classmethod
|
||||
def list_adapters(cls, adapter_type: str | None = None) -> list[str]:
|
||||
"""列出所有已注册的适配器。
|
||||
|
||||
Args:
|
||||
adapter_type: 可选，筛选特定类型 (text/image/tts)
|
||||
|
||||
Returns:
|
||||
适配器键列表，格式为 "type:name"
|
||||
"""
|
||||
if adapter_type:
|
||||
return [k for k in cls._adapters if k.startswith(f"{adapter_type}:")]
|
||||
return list(cls._adapters.keys())
|
||||
|
||||
@classmethod
|
||||
def create(
|
||||
cls,
|
||||
adapter_type: str,
|
||||
adapter_name: str,
|
||||
config: "AdapterConfig",
|
||||
) -> "BaseAdapter":
|
||||
"""工厂方法：创建适配器实例。
|
||||
|
||||
Raises:
|
||||
ValueError: 适配器未注册
|
||||
"""
|
||||
adapter_class = cls.get(adapter_type, adapter_name)
|
||||
if not adapter_class:
|
||||
available = cls.list_adapters(adapter_type)
|
||||
raise ValueError(
|
||||
f"适配器 '{adapter_type}:{adapter_name}' 未注册。"
|
||||
f"可用: {available}"
|
||||
)
|
||||
return adapter_class(config)
|
||||
...
|
||||
"""
|
||||
|
||||
def decorator(adapter_class: type["BaseAdapter"]):
|
||||
key = f"{adapter_type}:{adapter_name}"
|
||||
cls._adapters[key] = adapter_class
|
||||
# 自动设置类属性
|
||||
adapter_class.adapter_type = adapter_type
|
||||
adapter_class.adapter_name = adapter_name
|
||||
return adapter_class
|
||||
|
||||
return decorator
|
||||
|
||||
@classmethod
|
||||
def get(cls, adapter_type: str, adapter_name: str) -> type["BaseAdapter"] | None:
|
||||
"""获取已注册的适配器类。"""
|
||||
key = f"{adapter_type}:{adapter_name}"
|
||||
return cls._adapters.get(key)
|
||||
|
||||
@classmethod
|
||||
def list_adapters(cls, adapter_type: str | None = None) -> list[str]:
|
||||
"""列出所有已注册的适配器。
|
||||
|
||||
Args:
|
||||
adapter_type: 可选，筛选特定类型 (text/image/tts)
|
||||
|
||||
Returns:
|
||||
适配器键列表，格式为 "type:name"
|
||||
"""
|
||||
if adapter_type:
|
||||
return [k for k in cls._adapters if k.startswith(f"{adapter_type}:")]
|
||||
return list(cls._adapters.keys())
|
||||
|
||||
@classmethod
|
||||
def create(
|
||||
cls,
|
||||
adapter_type: str,
|
||||
adapter_name: str,
|
||||
config: "AdapterConfig",
|
||||
) -> "BaseAdapter":
|
||||
"""工厂方法：创建适配器实例。
|
||||
|
||||
Raises:
|
||||
ValueError: 适配器未注册
|
||||
"""
|
||||
adapter_class = cls.get(adapter_type, adapter_name)
|
||||
if not adapter_class:
|
||||
available = cls.list_adapters(adapter_type)
|
||||
raise ValueError(
|
||||
f"适配器 '{adapter_type}:{adapter_name}' 未注册。"
|
||||
f"可用: {available}"
|
||||
)
|
||||
return adapter_class(config)
|
||||
|
||||
@@ -1 +1 @@
|
||||
"""Storybook 适配器模块。"""
|
||||
"""Storybook 适配器模块。"""
|
||||
|
||||
@@ -1,195 +1,195 @@
|
||||
"""Storybook 适配器 - 生成可翻页的分页故事书。"""
|
||||
|
||||
import json
|
||||
import random
|
||||
import re
|
||||
import time
|
||||
from dataclasses import dataclass, field
|
||||
|
||||
import httpx
|
||||
from tenacity import (
|
||||
retry,
|
||||
retry_if_exception_type,
|
||||
stop_after_attempt,
|
||||
wait_exponential,
|
||||
)
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.core.prompts import (
|
||||
RANDOM_ELEMENTS,
|
||||
SYSTEM_INSTRUCTION_STORYBOOK,
|
||||
USER_PROMPT_STORYBOOK,
|
||||
)
|
||||
from app.services.adapters.base import BaseAdapter
|
||||
from app.services.adapters.registry import AdapterRegistry
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
TEXT_API_BASE = "https://generativelanguage.googleapis.com/v1beta/models"
|
||||
|
||||
|
||||
@dataclass
|
||||
class StorybookPage:
|
||||
"""故事书单页。"""
|
||||
|
||||
page_number: int
|
||||
text: str
|
||||
image_prompt: str
|
||||
image_url: str | None = None
|
||||
|
||||
|
||||
@dataclass
|
||||
class Storybook:
|
||||
"""故事书输出。"""
|
||||
|
||||
title: str
|
||||
main_character: str
|
||||
art_style: str
|
||||
pages: list[StorybookPage] = field(default_factory=list)
|
||||
cover_prompt: str = ""
|
||||
cover_url: str | None = None
|
||||
|
||||
|
||||
@AdapterRegistry.register("storybook", "storybook_primary")
|
||||
class StorybookPrimaryAdapter(BaseAdapter[Storybook]):
|
||||
"""Storybook 生成适配器（默认）。
|
||||
|
||||
生成分页故事书结构，包含每页文字和图像提示词。
|
||||
图像生成需要单独调用 image adapter。
|
||||
"""
|
||||
|
||||
adapter_type = "storybook"
|
||||
adapter_name = "storybook_primary"
|
||||
|
||||
async def execute(
|
||||
self,
|
||||
keywords: str,
|
||||
page_count: int = 6,
|
||||
education_theme: str | None = None,
|
||||
memory_context: str | None = None,
|
||||
**kwargs,
|
||||
) -> Storybook:
|
||||
"""生成分页故事书。
|
||||
|
||||
Args:
|
||||
keywords: 故事关键词
|
||||
page_count: 页数 (4-12)
|
||||
education_theme: 教育主题
|
||||
memory_context: 记忆上下文
|
||||
|
||||
Returns:
|
||||
Storybook 对象，包含标题、页面列表和封面提示词
|
||||
"""
|
||||
start_time = time.time()
|
||||
page_count = max(4, min(page_count, 12)) # 限制 4-12 页
|
||||
|
||||
logger.info(
|
||||
"storybook_generate_start",
|
||||
keywords=keywords,
|
||||
page_count=page_count,
|
||||
has_memory=bool(memory_context),
|
||||
)
|
||||
|
||||
theme = education_theme or "成长"
|
||||
random_element = random.choice(RANDOM_ELEMENTS)
|
||||
|
||||
prompt = USER_PROMPT_STORYBOOK.format(
|
||||
keywords=keywords,
|
||||
education_theme=theme,
|
||||
random_element=random_element,
|
||||
page_count=page_count,
|
||||
memory_context=memory_context or "",
|
||||
)
|
||||
|
||||
payload = {
|
||||
"system_instruction": {"parts": [{"text": SYSTEM_INSTRUCTION_STORYBOOK}]},
|
||||
"contents": [{"parts": [{"text": prompt}]}],
|
||||
"generationConfig": {
|
||||
"responseMimeType": "application/json",
|
||||
"temperature": 0.95,
|
||||
"topP": 0.9,
|
||||
},
|
||||
}
|
||||
|
||||
result = await self._call_api(payload)
|
||||
|
||||
candidates = result.get("candidates") or []
|
||||
if not candidates:
|
||||
raise ValueError("Storybook 服务未返回内容")
|
||||
|
||||
parts = candidates[0].get("content", {}).get("parts") or []
|
||||
if not parts or "text" not in parts[0]:
|
||||
raise ValueError("Storybook 服务响应缺少文本")
|
||||
|
||||
response_text = parts[0]["text"]
|
||||
clean_json = response_text
|
||||
if response_text.startswith("```json"):
|
||||
clean_json = re.sub(r"^```json\n|```$", "", response_text)
|
||||
|
||||
try:
|
||||
parsed = json.loads(clean_json)
|
||||
except json.JSONDecodeError as exc:
|
||||
raise ValueError(f"Storybook JSON 解析失败: {exc}")
|
||||
|
||||
# 构建 Storybook 对象
|
||||
pages = [
|
||||
StorybookPage(
|
||||
page_number=p.get("page_number", i + 1),
|
||||
text=p.get("text", ""),
|
||||
image_prompt=p.get("image_prompt", ""),
|
||||
)
|
||||
for i, p in enumerate(parsed.get("pages", []))
|
||||
]
|
||||
|
||||
storybook = Storybook(
|
||||
title=parsed.get("title", "未命名故事"),
|
||||
main_character=parsed.get("main_character", ""),
|
||||
art_style=parsed.get("art_style", ""),
|
||||
pages=pages,
|
||||
cover_prompt=parsed.get("cover_prompt", ""),
|
||||
)
|
||||
|
||||
elapsed = time.time() - start_time
|
||||
logger.info(
|
||||
"storybook_generate_success",
|
||||
elapsed_seconds=round(elapsed, 2),
|
||||
title=storybook.title,
|
||||
page_count=len(pages),
|
||||
)
|
||||
|
||||
return storybook
|
||||
|
||||
|
||||
async def health_check(self) -> bool:
|
||||
"""检查 API 是否可用。"""
|
||||
try:
|
||||
payload = {
|
||||
"contents": [{"parts": [{"text": "Hi"}]}],
|
||||
"generationConfig": {"maxOutputTokens": 10},
|
||||
}
|
||||
await self._call_api(payload)
|
||||
return True
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
@property
|
||||
def estimated_cost(self) -> float:
|
||||
"""预估成本（仅文本生成，不含图像）。"""
|
||||
return 0.002 # 比普通故事稍贵，因为输出更长
|
||||
|
||||
@retry(
|
||||
stop=stop_after_attempt(3),
|
||||
wait=wait_exponential(multiplier=1, min=1, max=10),
|
||||
retry=retry_if_exception_type((httpx.HTTPError, httpx.TimeoutException)),
|
||||
reraise=True,
|
||||
)
|
||||
async def _call_api(self, payload: dict) -> dict:
|
||||
"""调用 API，带重试机制。"""
|
||||
model = self.config.model or "gemini-2.0-flash"
|
||||
url = f"{TEXT_API_BASE}/{model}:generateContent?key={self.config.api_key}"
|
||||
timeout = self.config.timeout_ms / 1000
|
||||
|
||||
async with httpx.AsyncClient(timeout=timeout) as client:
|
||||
response = await client.post(url, json=payload)
|
||||
response.raise_for_status()
|
||||
return response.json()
|
||||
"""Storybook 适配器 - 生成可翻页的分页故事书。"""
|
||||
|
||||
import json
|
||||
import random
|
||||
import re
|
||||
import time
|
||||
from dataclasses import dataclass, field
|
||||
|
||||
import httpx
|
||||
from tenacity import (
|
||||
retry,
|
||||
retry_if_exception_type,
|
||||
stop_after_attempt,
|
||||
wait_exponential,
|
||||
)
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.core.prompts import (
|
||||
RANDOM_ELEMENTS,
|
||||
SYSTEM_INSTRUCTION_STORYBOOK,
|
||||
USER_PROMPT_STORYBOOK,
|
||||
)
|
||||
from app.services.adapters.base import BaseAdapter
|
||||
from app.services.adapters.registry import AdapterRegistry
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
TEXT_API_BASE = "https://generativelanguage.googleapis.com/v1beta/models"
|
||||
|
||||
|
||||
@dataclass
|
||||
class StorybookPage:
|
||||
"""故事书单页。"""
|
||||
|
||||
page_number: int
|
||||
text: str
|
||||
image_prompt: str
|
||||
image_url: str | None = None
|
||||
|
||||
|
||||
@dataclass
|
||||
class Storybook:
|
||||
"""故事书输出。"""
|
||||
|
||||
title: str
|
||||
main_character: str
|
||||
art_style: str
|
||||
pages: list[StorybookPage] = field(default_factory=list)
|
||||
cover_prompt: str = ""
|
||||
cover_url: str | None = None
|
||||
|
||||
|
||||
@AdapterRegistry.register("storybook", "storybook_primary")
|
||||
class StorybookPrimaryAdapter(BaseAdapter[Storybook]):
|
||||
"""Storybook 生成适配器（默认）。
|
||||
|
||||
生成分页故事书结构，包含每页文字和图像提示词。
|
||||
图像生成需要单独调用 image adapter。
|
||||
"""
|
||||
|
||||
adapter_type = "storybook"
|
||||
adapter_name = "storybook_primary"
|
||||
|
||||
async def execute(
|
||||
self,
|
||||
keywords: str,
|
||||
page_count: int = 6,
|
||||
education_theme: str | None = None,
|
||||
memory_context: str | None = None,
|
||||
**kwargs,
|
||||
) -> Storybook:
|
||||
"""生成分页故事书。
|
||||
|
||||
Args:
|
||||
keywords: 故事关键词
|
||||
page_count: 页数 (4-12)
|
||||
education_theme: 教育主题
|
||||
memory_context: 记忆上下文
|
||||
|
||||
Returns:
|
||||
Storybook 对象，包含标题、页面列表和封面提示词
|
||||
"""
|
||||
start_time = time.time()
|
||||
page_count = max(4, min(page_count, 12)) # 限制 4-12 页
|
||||
|
||||
logger.info(
|
||||
"storybook_generate_start",
|
||||
keywords=keywords,
|
||||
page_count=page_count,
|
||||
has_memory=bool(memory_context),
|
||||
)
|
||||
|
||||
theme = education_theme or "成长"
|
||||
random_element = random.choice(RANDOM_ELEMENTS)
|
||||
|
||||
prompt = USER_PROMPT_STORYBOOK.format(
|
||||
keywords=keywords,
|
||||
education_theme=theme,
|
||||
random_element=random_element,
|
||||
page_count=page_count,
|
||||
memory_context=memory_context or "",
|
||||
)
|
||||
|
||||
payload = {
|
||||
"system_instruction": {"parts": [{"text": SYSTEM_INSTRUCTION_STORYBOOK}]},
|
||||
"contents": [{"parts": [{"text": prompt}]}],
|
||||
"generationConfig": {
|
||||
"responseMimeType": "application/json",
|
||||
"temperature": 0.95,
|
||||
"topP": 0.9,
|
||||
},
|
||||
}
|
||||
|
||||
result = await self._call_api(payload)
|
||||
|
||||
candidates = result.get("candidates") or []
|
||||
if not candidates:
|
||||
raise ValueError("Storybook 服务未返回内容")
|
||||
|
||||
parts = candidates[0].get("content", {}).get("parts") or []
|
||||
if not parts or "text" not in parts[0]:
|
||||
raise ValueError("Storybook 服务响应缺少文本")
|
||||
|
||||
response_text = parts[0]["text"]
|
||||
clean_json = response_text
|
||||
if response_text.startswith("```json"):
|
||||
clean_json = re.sub(r"^```json\n|```$", "", response_text)
|
||||
|
||||
try:
|
||||
parsed = json.loads(clean_json)
|
||||
except json.JSONDecodeError as exc:
|
||||
raise ValueError(f"Storybook JSON 解析失败: {exc}")
|
||||
|
||||
# 构建 Storybook 对象
|
||||
pages = [
|
||||
StorybookPage(
|
||||
page_number=p.get("page_number", i + 1),
|
||||
text=p.get("text", ""),
|
||||
image_prompt=p.get("image_prompt", ""),
|
||||
)
|
||||
for i, p in enumerate(parsed.get("pages", []))
|
||||
]
|
||||
|
||||
storybook = Storybook(
|
||||
title=parsed.get("title", "未命名故事"),
|
||||
main_character=parsed.get("main_character", ""),
|
||||
art_style=parsed.get("art_style", ""),
|
||||
pages=pages,
|
||||
cover_prompt=parsed.get("cover_prompt", ""),
|
||||
)
|
||||
|
||||
elapsed = time.time() - start_time
|
||||
logger.info(
|
||||
"storybook_generate_success",
|
||||
elapsed_seconds=round(elapsed, 2),
|
||||
title=storybook.title,
|
||||
page_count=len(pages),
|
||||
)
|
||||
|
||||
return storybook
|
||||
|
||||
|
||||
async def health_check(self) -> bool:
|
||||
"""检查 API 是否可用。"""
|
||||
try:
|
||||
payload = {
|
||||
"contents": [{"parts": [{"text": "Hi"}]}],
|
||||
"generationConfig": {"maxOutputTokens": 10},
|
||||
}
|
||||
await self._call_api(payload)
|
||||
return True
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
@property
|
||||
def estimated_cost(self) -> float:
|
||||
"""预估成本（仅文本生成，不含图像）。"""
|
||||
return 0.002 # 比普通故事稍贵，因为输出更长
|
||||
|
||||
@retry(
|
||||
stop=stop_after_attempt(3),
|
||||
wait=wait_exponential(multiplier=1, min=1, max=10),
|
||||
retry=retry_if_exception_type((httpx.HTTPError, httpx.TimeoutException)),
|
||||
reraise=True,
|
||||
)
|
||||
async def _call_api(self, payload: dict) -> dict:
|
||||
"""调用 API，带重试机制。"""
|
||||
model = self.config.model or "gemini-2.0-flash"
|
||||
url = f"{TEXT_API_BASE}/{model}:generateContent?key={self.config.api_key}"
|
||||
timeout = self.config.timeout_ms / 1000
|
||||
|
||||
async with httpx.AsyncClient(timeout=timeout) as client:
|
||||
response = await client.post(url, json=payload)
|
||||
response.raise_for_status()
|
||||
return response.json()
|
||||
|
||||
@@ -1 +1 @@
|
||||
"""文本生成适配器。"""
|
||||
"""文本生成适配器。"""
|
||||
|
||||
@@ -1,164 +1,164 @@
|
||||
"""文本生成适配器 (Google Gemini)。"""
|
||||
|
||||
import json
|
||||
import random
|
||||
import re
|
||||
import time
|
||||
from typing import Literal
|
||||
|
||||
import httpx
|
||||
from tenacity import (
|
||||
retry,
|
||||
retry_if_exception_type,
|
||||
stop_after_attempt,
|
||||
wait_exponential,
|
||||
)
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.core.prompts import (
|
||||
RANDOM_ELEMENTS,
|
||||
SYSTEM_INSTRUCTION_ENHANCER,
|
||||
SYSTEM_INSTRUCTION_STORYTELLER,
|
||||
USER_PROMPT_ENHANCEMENT,
|
||||
USER_PROMPT_GENERATION,
|
||||
)
|
||||
from app.services.adapters.base import BaseAdapter
|
||||
from app.services.adapters.registry import AdapterRegistry
|
||||
from app.services.adapters.text.models import StoryOutput
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
TEXT_API_BASE = "https://generativelanguage.googleapis.com/v1beta/models"
|
||||
|
||||
|
||||
@AdapterRegistry.register("text", "gemini")
|
||||
class GeminiTextAdapter(BaseAdapter[StoryOutput]):
|
||||
"""Google Gemini 文本生成适配器。"""
|
||||
|
||||
adapter_type = "text"
|
||||
adapter_name = "gemini"
|
||||
|
||||
async def execute(
|
||||
self,
|
||||
input_type: Literal["keywords", "full_story"],
|
||||
data: str,
|
||||
education_theme: str | None = None,
|
||||
memory_context: str | None = None,
|
||||
**kwargs,
|
||||
) -> StoryOutput:
|
||||
"""生成或润色故事。"""
|
||||
start_time = time.time()
|
||||
logger.info("request_start", adapter="gemini", input_type=input_type, data_length=len(data))
|
||||
|
||||
theme = education_theme or "成长"
|
||||
random_element = random.choice(RANDOM_ELEMENTS)
|
||||
|
||||
if input_type == "keywords":
|
||||
system_instruction = SYSTEM_INSTRUCTION_STORYTELLER
|
||||
prompt = USER_PROMPT_GENERATION.format(
|
||||
keywords=data,
|
||||
education_theme=theme,
|
||||
random_element=random_element,
|
||||
memory_context=memory_context or "",
|
||||
)
|
||||
else:
|
||||
system_instruction = SYSTEM_INSTRUCTION_ENHANCER
|
||||
prompt = USER_PROMPT_ENHANCEMENT.format(
|
||||
full_story=data,
|
||||
education_theme=theme,
|
||||
random_element=random_element,
|
||||
memory_context=memory_context or "",
|
||||
)
|
||||
|
||||
# Gemini API Payload supports 'system_instruction'
|
||||
payload = {
|
||||
"system_instruction": {"parts": [{"text": system_instruction}]},
|
||||
"contents": [{"parts": [{"text": prompt}]}],
|
||||
"generationConfig": {
|
||||
"responseMimeType": "application/json",
|
||||
"temperature": 0.95,
|
||||
"topP": 0.9,
|
||||
},
|
||||
}
|
||||
|
||||
result = await self._call_api(payload)
|
||||
|
||||
candidates = result.get("candidates") or []
|
||||
if not candidates:
|
||||
raise ValueError("Gemini 未返回内容")
|
||||
|
||||
parts = candidates[0].get("content", {}).get("parts") or []
|
||||
if not parts or "text" not in parts[0]:
|
||||
raise ValueError("Gemini 响应缺少文本")
|
||||
|
||||
response_text = parts[0]["text"]
|
||||
clean_json = response_text
|
||||
if response_text.startswith("```json"):
|
||||
clean_json = re.sub(r"^```json\n|```$", "", response_text)
|
||||
|
||||
try:
|
||||
parsed = json.loads(clean_json)
|
||||
except json.JSONDecodeError as exc:
|
||||
raise ValueError(f"Gemini 输出 JSON 解析失败: {exc}")
|
||||
|
||||
required_fields = ["mode", "title", "story_text", "cover_prompt_suggestion"]
|
||||
if any(field not in parsed for field in required_fields):
|
||||
raise ValueError("Gemini 输出缺少必要字段")
|
||||
|
||||
elapsed = time.time() - start_time
|
||||
logger.info(
|
||||
"request_success",
|
||||
adapter="gemini",
|
||||
elapsed_seconds=round(elapsed, 2),
|
||||
title=parsed["title"],
|
||||
)
|
||||
|
||||
return StoryOutput(
|
||||
mode=parsed["mode"],
|
||||
title=parsed["title"],
|
||||
story_text=parsed["story_text"],
|
||||
cover_prompt_suggestion=parsed["cover_prompt_suggestion"],
|
||||
)
|
||||
|
||||
async def health_check(self) -> bool:
|
||||
"""检查 Gemini API 是否可用。"""
|
||||
try:
|
||||
payload = {
|
||||
"contents": [{"parts": [{"text": "Hi"}]}],
|
||||
"generationConfig": {"maxOutputTokens": 10},
|
||||
}
|
||||
await self._call_api(payload)
|
||||
return True
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
@property
|
||||
def estimated_cost(self) -> float:
|
||||
return 0.001
|
||||
|
||||
@retry(
|
||||
stop=stop_after_attempt(3),
|
||||
wait=wait_exponential(multiplier=1, min=1, max=10),
|
||||
retry=retry_if_exception_type((httpx.HTTPError, httpx.TimeoutException)),
|
||||
reraise=True,
|
||||
)
|
||||
async def _call_api(self, payload: dict) -> dict:
|
||||
"""调用 Gemini API。"""
|
||||
model = self.config.model or "gemini-2.0-flash"
|
||||
base_url = self.config.api_base or TEXT_API_BASE
|
||||
|
||||
# 智能补全:
|
||||
# 1. 如果用户填了完整路径 (以 /models 结尾)，就直接用 (支持 v1 或 v1beta)
|
||||
if self.config.api_base and base_url.rstrip("/").endswith("/models"):
|
||||
pass
|
||||
# 2. 如果没填路径 (只是域名)，默认补全代码适配的 /v1beta/models
|
||||
elif self.config.api_base:
|
||||
base_url = f"{base_url.rstrip('/')}/v1beta/models"
|
||||
|
||||
url = f"{base_url}/{model}:generateContent?key={self.config.api_key}"
|
||||
timeout = self.config.timeout_ms / 1000
|
||||
|
||||
async with httpx.AsyncClient(timeout=timeout) as client:
|
||||
response = await client.post(url, json=payload)
|
||||
response.raise_for_status()
|
||||
return response.json()
|
||||
"""文本生成适配器 (Google Gemini)。"""
|
||||
|
||||
import json
|
||||
import random
|
||||
import re
|
||||
import time
|
||||
from typing import Literal
|
||||
|
||||
import httpx
|
||||
from tenacity import (
|
||||
retry,
|
||||
retry_if_exception_type,
|
||||
stop_after_attempt,
|
||||
wait_exponential,
|
||||
)
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.core.prompts import (
|
||||
RANDOM_ELEMENTS,
|
||||
SYSTEM_INSTRUCTION_ENHANCER,
|
||||
SYSTEM_INSTRUCTION_STORYTELLER,
|
||||
USER_PROMPT_ENHANCEMENT,
|
||||
USER_PROMPT_GENERATION,
|
||||
)
|
||||
from app.services.adapters.base import BaseAdapter
|
||||
from app.services.adapters.registry import AdapterRegistry
|
||||
from app.services.adapters.text.models import StoryOutput
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
TEXT_API_BASE = "https://generativelanguage.googleapis.com/v1beta/models"
|
||||
|
||||
|
||||
@AdapterRegistry.register("text", "gemini")
|
||||
class GeminiTextAdapter(BaseAdapter[StoryOutput]):
|
||||
"""Google Gemini 文本生成适配器。"""
|
||||
|
||||
adapter_type = "text"
|
||||
adapter_name = "gemini"
|
||||
|
||||
async def execute(
|
||||
self,
|
||||
input_type: Literal["keywords", "full_story"],
|
||||
data: str,
|
||||
education_theme: str | None = None,
|
||||
memory_context: str | None = None,
|
||||
**kwargs,
|
||||
) -> StoryOutput:
|
||||
"""生成或润色故事。"""
|
||||
start_time = time.time()
|
||||
logger.info("request_start", adapter="gemini", input_type=input_type, data_length=len(data))
|
||||
|
||||
theme = education_theme or "成长"
|
||||
random_element = random.choice(RANDOM_ELEMENTS)
|
||||
|
||||
if input_type == "keywords":
|
||||
system_instruction = SYSTEM_INSTRUCTION_STORYTELLER
|
||||
prompt = USER_PROMPT_GENERATION.format(
|
||||
keywords=data,
|
||||
education_theme=theme,
|
||||
random_element=random_element,
|
||||
memory_context=memory_context or "",
|
||||
)
|
||||
else:
|
||||
system_instruction = SYSTEM_INSTRUCTION_ENHANCER
|
||||
prompt = USER_PROMPT_ENHANCEMENT.format(
|
||||
full_story=data,
|
||||
education_theme=theme,
|
||||
random_element=random_element,
|
||||
memory_context=memory_context or "",
|
||||
)
|
||||
|
||||
# Gemini API Payload supports 'system_instruction'
|
||||
payload = {
|
||||
"system_instruction": {"parts": [{"text": system_instruction}]},
|
||||
"contents": [{"parts": [{"text": prompt}]}],
|
||||
"generationConfig": {
|
||||
"responseMimeType": "application/json",
|
||||
"temperature": 0.95,
|
||||
"topP": 0.9,
|
||||
},
|
||||
}
|
||||
|
||||
result = await self._call_api(payload)
|
||||
|
||||
candidates = result.get("candidates") or []
|
||||
if not candidates:
|
||||
raise ValueError("Gemini 未返回内容")
|
||||
|
||||
parts = candidates[0].get("content", {}).get("parts") or []
|
||||
if not parts or "text" not in parts[0]:
|
||||
raise ValueError("Gemini 响应缺少文本")
|
||||
|
||||
response_text = parts[0]["text"]
|
||||
clean_json = response_text
|
||||
if response_text.startswith("```json"):
|
||||
clean_json = re.sub(r"^```json\n|```$", "", response_text)
|
||||
|
||||
try:
|
||||
parsed = json.loads(clean_json)
|
||||
except json.JSONDecodeError as exc:
|
||||
raise ValueError(f"Gemini 输出 JSON 解析失败: {exc}")
|
||||
|
||||
required_fields = ["mode", "title", "story_text", "cover_prompt_suggestion"]
|
||||
if any(field not in parsed for field in required_fields):
|
||||
raise ValueError("Gemini 输出缺少必要字段")
|
||||
|
||||
elapsed = time.time() - start_time
|
||||
logger.info(
|
||||
"request_success",
|
||||
adapter="gemini",
|
||||
elapsed_seconds=round(elapsed, 2),
|
||||
title=parsed["title"],
|
||||
)
|
||||
|
||||
return StoryOutput(
|
||||
mode=parsed["mode"],
|
||||
title=parsed["title"],
|
||||
story_text=parsed["story_text"],
|
||||
cover_prompt_suggestion=parsed["cover_prompt_suggestion"],
|
||||
)
|
||||
|
||||
async def health_check(self) -> bool:
|
||||
"""检查 Gemini API 是否可用。"""
|
||||
try:
|
||||
payload = {
|
||||
"contents": [{"parts": [{"text": "Hi"}]}],
|
||||
"generationConfig": {"maxOutputTokens": 10},
|
||||
}
|
||||
await self._call_api(payload)
|
||||
return True
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
@property
|
||||
def estimated_cost(self) -> float:
|
||||
return 0.001
|
||||
|
||||
@retry(
|
||||
stop=stop_after_attempt(3),
|
||||
wait=wait_exponential(multiplier=1, min=1, max=10),
|
||||
retry=retry_if_exception_type((httpx.HTTPError, httpx.TimeoutException)),
|
||||
reraise=True,
|
||||
)
|
||||
async def _call_api(self, payload: dict) -> dict:
|
||||
"""调用 Gemini API。"""
|
||||
model = self.config.model or "gemini-2.0-flash"
|
||||
base_url = self.config.api_base or TEXT_API_BASE
|
||||
|
||||
# 智能补全:
|
||||
# 1. 如果用户填了完整路径 (以 /models 结尾)，就直接用 (支持 v1 或 v1beta)
|
||||
if self.config.api_base and base_url.rstrip("/").endswith("/models"):
|
||||
pass
|
||||
# 2. 如果没填路径 (只是域名)，默认补全代码适配的 /v1beta/models
|
||||
elif self.config.api_base:
|
||||
base_url = f"{base_url.rstrip('/')}/v1beta/models"
|
||||
|
||||
url = f"{base_url}/{model}:generateContent?key={self.config.api_key}"
|
||||
timeout = self.config.timeout_ms / 1000
|
||||
|
||||
async with httpx.AsyncClient(timeout=timeout) as client:
|
||||
response = await client.post(url, json=payload)
|
||||
response.raise_for_status()
|
||||
return response.json()
|
||||
|
||||
@@ -1,11 +1,11 @@
|
||||
from dataclasses import dataclass
|
||||
from typing import Literal
|
||||
|
||||
|
||||
@dataclass
|
||||
class StoryOutput:
|
||||
"""故事生成输出。"""
|
||||
mode: Literal["generated", "enhanced"]
|
||||
title: str
|
||||
story_text: str
|
||||
cover_prompt_suggestion: str
|
||||
from dataclasses import dataclass
|
||||
from typing import Literal
|
||||
|
||||
|
||||
@dataclass
|
||||
class StoryOutput:
|
||||
"""故事生成输出。"""
|
||||
mode: Literal["generated", "enhanced"]
|
||||
title: str
|
||||
story_text: str
|
||||
cover_prompt_suggestion: str
|
||||
|
||||
@@ -1,172 +1,172 @@
|
||||
"""OpenAI 文本生成适配器。"""
|
||||
|
||||
import json
|
||||
import random
|
||||
import re
|
||||
import time
|
||||
from typing import Literal
|
||||
|
||||
import httpx
|
||||
from tenacity import (
|
||||
retry,
|
||||
retry_if_exception_type,
|
||||
stop_after_attempt,
|
||||
wait_exponential,
|
||||
)
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.core.prompts import (
|
||||
RANDOM_ELEMENTS,
|
||||
SYSTEM_INSTRUCTION_ENHANCER,
|
||||
SYSTEM_INSTRUCTION_STORYTELLER,
|
||||
USER_PROMPT_ENHANCEMENT,
|
||||
USER_PROMPT_GENERATION,
|
||||
)
|
||||
from app.services.adapters.base import BaseAdapter
|
||||
from app.services.adapters.registry import AdapterRegistry
|
||||
from app.services.adapters.text.models import StoryOutput
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
OPENAI_API_BASE = "https://api.openai.com/v1/chat/completions"
|
||||
|
||||
|
||||
|
||||
|
||||
@AdapterRegistry.register("text", "openai")
|
||||
class OpenAITextAdapter(BaseAdapter[StoryOutput]):
|
||||
"""OpenAI 文本生成适配器。"""
|
||||
|
||||
adapter_type = "text"
|
||||
adapter_name = "openai"
|
||||
|
||||
async def execute(
|
||||
self,
|
||||
input_type: Literal["keywords", "full_story"],
|
||||
data: str,
|
||||
education_theme: str | None = None,
|
||||
memory_context: str | None = None,
|
||||
**kwargs,
|
||||
) -> StoryOutput:
|
||||
"""生成或润色故事。"""
|
||||
start_time = time.time()
|
||||
logger.info("openai_text_request_start", input_type=input_type, data_length=len(data))
|
||||
|
||||
theme = education_theme or "成长"
|
||||
random_element = random.choice(RANDOM_ELEMENTS)
|
||||
|
||||
if input_type == "keywords":
|
||||
system_instruction = SYSTEM_INSTRUCTION_STORYTELLER
|
||||
prompt = USER_PROMPT_GENERATION.format(
|
||||
keywords=data,
|
||||
education_theme=theme,
|
||||
random_element=random_element,
|
||||
memory_context=memory_context or "",
|
||||
)
|
||||
else:
|
||||
system_instruction = SYSTEM_INSTRUCTION_ENHANCER
|
||||
prompt = USER_PROMPT_ENHANCEMENT.format(
|
||||
full_story=data,
|
||||
education_theme=theme,
|
||||
random_element=random_element,
|
||||
memory_context=memory_context or "",
|
||||
)
|
||||
|
||||
model = self.config.model or "gpt-4o-mini"
|
||||
payload = {
|
||||
"model": model,
|
||||
"messages": [
|
||||
{
|
||||
"role": "system",
|
||||
"content": system_instruction,
|
||||
},
|
||||
{"role": "user", "content": prompt},
|
||||
],
|
||||
"response_format": {"type": "json_object"},
|
||||
"temperature": 0.95,
|
||||
"top_p": 0.9,
|
||||
}
|
||||
|
||||
result = await self._call_api(payload)
|
||||
|
||||
choices = result.get("choices") or []
|
||||
if not choices:
|
||||
raise ValueError("OpenAI 未返回内容")
|
||||
|
||||
response_text = choices[0].get("message", {}).get("content", "")
|
||||
if not response_text:
|
||||
raise ValueError("OpenAI 响应缺少文本")
|
||||
|
||||
clean_json = response_text
|
||||
if response_text.startswith("```json"):
|
||||
clean_json = re.sub(r"^```json\n|```$", "", response_text)
|
||||
|
||||
try:
|
||||
parsed = json.loads(clean_json)
|
||||
except json.JSONDecodeError as exc:
|
||||
raise ValueError(f"OpenAI 输出 JSON 解析失败: {exc}")
|
||||
|
||||
required_fields = ["mode", "title", "story_text", "cover_prompt_suggestion"]
|
||||
if any(field not in parsed for field in required_fields):
|
||||
raise ValueError("OpenAI 输出缺少必要字段")
|
||||
|
||||
elapsed = time.time() - start_time
|
||||
logger.info(
|
||||
"openai_text_request_success",
|
||||
elapsed_seconds=round(elapsed, 2),
|
||||
title=parsed["title"],
|
||||
mode=parsed["mode"],
|
||||
)
|
||||
|
||||
return StoryOutput(
|
||||
mode=parsed["mode"],
|
||||
title=parsed["title"],
|
||||
story_text=parsed["story_text"],
|
||||
cover_prompt_suggestion=parsed["cover_prompt_suggestion"],
|
||||
)
|
||||
|
||||
@retry(
|
||||
stop=stop_after_attempt(3),
|
||||
wait=wait_exponential(multiplier=1, min=4, max=10),
|
||||
retry=retry_if_exception_type(httpx.HTTPStatusError),
|
||||
)
|
||||
async def _call_api(self, payload: dict) -> dict:
|
||||
"""调用 OpenAI API，带重试机制。"""
|
||||
url = self.config.api_base or OPENAI_API_BASE
|
||||
|
||||
# 智能补全: 如果用户只填了 Base URL，自动补全路径
|
||||
if self.config.api_base and not url.endswith("/chat/completions"):
|
||||
base = url.rstrip("/")
|
||||
url = f"{base}/chat/completions"
|
||||
|
||||
timeout = self.config.timeout_ms / 1000
|
||||
|
||||
async with httpx.AsyncClient(timeout=timeout) as client:
|
||||
response = await client.post(
|
||||
url,
|
||||
json=payload,
|
||||
headers={
|
||||
"Authorization": f"Bearer {self.config.api_key}",
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
)
|
||||
response.raise_for_status()
|
||||
return response.json()
|
||||
|
||||
async def health_check(self) -> bool:
|
||||
"""检查 OpenAI API 是否可用。"""
|
||||
try:
|
||||
payload = {
|
||||
"model": self.config.model or "gpt-4o-mini",
|
||||
"messages": [{"role": "user", "content": "Hi"}],
|
||||
"max_tokens": 5,
|
||||
}
|
||||
await self._call_api(payload)
|
||||
return True
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
@property
|
||||
def estimated_cost(self) -> float:
|
||||
"""预估文本生成成本 (USD)。"""
|
||||
return 0.01
|
||||
"""OpenAI 文本生成适配器。"""
|
||||
|
||||
import json
|
||||
import random
|
||||
import re
|
||||
import time
|
||||
from typing import Literal
|
||||
|
||||
import httpx
|
||||
from tenacity import (
|
||||
retry,
|
||||
retry_if_exception_type,
|
||||
stop_after_attempt,
|
||||
wait_exponential,
|
||||
)
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.core.prompts import (
|
||||
RANDOM_ELEMENTS,
|
||||
SYSTEM_INSTRUCTION_ENHANCER,
|
||||
SYSTEM_INSTRUCTION_STORYTELLER,
|
||||
USER_PROMPT_ENHANCEMENT,
|
||||
USER_PROMPT_GENERATION,
|
||||
)
|
||||
from app.services.adapters.base import BaseAdapter
|
||||
from app.services.adapters.registry import AdapterRegistry
|
||||
from app.services.adapters.text.models import StoryOutput
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
OPENAI_API_BASE = "https://api.openai.com/v1/chat/completions"
|
||||
|
||||
|
||||
|
||||
|
||||
@AdapterRegistry.register("text", "openai")
|
||||
class OpenAITextAdapter(BaseAdapter[StoryOutput]):
|
||||
"""OpenAI 文本生成适配器。"""
|
||||
|
||||
adapter_type = "text"
|
||||
adapter_name = "openai"
|
||||
|
||||
async def execute(
|
||||
self,
|
||||
input_type: Literal["keywords", "full_story"],
|
||||
data: str,
|
||||
education_theme: str | None = None,
|
||||
memory_context: str | None = None,
|
||||
**kwargs,
|
||||
) -> StoryOutput:
|
||||
"""生成或润色故事。"""
|
||||
start_time = time.time()
|
||||
logger.info("openai_text_request_start", input_type=input_type, data_length=len(data))
|
||||
|
||||
theme = education_theme or "成长"
|
||||
random_element = random.choice(RANDOM_ELEMENTS)
|
||||
|
||||
if input_type == "keywords":
|
||||
system_instruction = SYSTEM_INSTRUCTION_STORYTELLER
|
||||
prompt = USER_PROMPT_GENERATION.format(
|
||||
keywords=data,
|
||||
education_theme=theme,
|
||||
random_element=random_element,
|
||||
memory_context=memory_context or "",
|
||||
)
|
||||
else:
|
||||
system_instruction = SYSTEM_INSTRUCTION_ENHANCER
|
||||
prompt = USER_PROMPT_ENHANCEMENT.format(
|
||||
full_story=data,
|
||||
education_theme=theme,
|
||||
random_element=random_element,
|
||||
memory_context=memory_context or "",
|
||||
)
|
||||
|
||||
model = self.config.model or "gpt-4o-mini"
|
||||
payload = {
|
||||
"model": model,
|
||||
"messages": [
|
||||
{
|
||||
"role": "system",
|
||||
"content": system_instruction,
|
||||
},
|
||||
{"role": "user", "content": prompt},
|
||||
],
|
||||
"response_format": {"type": "json_object"},
|
||||
"temperature": 0.95,
|
||||
"top_p": 0.9,
|
||||
}
|
||||
|
||||
result = await self._call_api(payload)
|
||||
|
||||
choices = result.get("choices") or []
|
||||
if not choices:
|
||||
raise ValueError("OpenAI 未返回内容")
|
||||
|
||||
response_text = choices[0].get("message", {}).get("content", "")
|
||||
if not response_text:
|
||||
raise ValueError("OpenAI 响应缺少文本")
|
||||
|
||||
clean_json = response_text
|
||||
if response_text.startswith("```json"):
|
||||
clean_json = re.sub(r"^```json\n|```$", "", response_text)
|
||||
|
||||
try:
|
||||
parsed = json.loads(clean_json)
|
||||
except json.JSONDecodeError as exc:
|
||||
raise ValueError(f"OpenAI 输出 JSON 解析失败: {exc}")
|
||||
|
||||
required_fields = ["mode", "title", "story_text", "cover_prompt_suggestion"]
|
||||
if any(field not in parsed for field in required_fields):
|
||||
raise ValueError("OpenAI 输出缺少必要字段")
|
||||
|
||||
elapsed = time.time() - start_time
|
||||
logger.info(
|
||||
"openai_text_request_success",
|
||||
elapsed_seconds=round(elapsed, 2),
|
||||
title=parsed["title"],
|
||||
mode=parsed["mode"],
|
||||
)
|
||||
|
||||
return StoryOutput(
|
||||
mode=parsed["mode"],
|
||||
title=parsed["title"],
|
||||
story_text=parsed["story_text"],
|
||||
cover_prompt_suggestion=parsed["cover_prompt_suggestion"],
|
||||
)
|
||||
|
||||
@retry(
|
||||
stop=stop_after_attempt(3),
|
||||
wait=wait_exponential(multiplier=1, min=4, max=10),
|
||||
retry=retry_if_exception_type(httpx.HTTPStatusError),
|
||||
)
|
||||
async def _call_api(self, payload: dict) -> dict:
|
||||
"""调用 OpenAI API，带重试机制。"""
|
||||
url = self.config.api_base or OPENAI_API_BASE
|
||||
|
||||
# 智能补全: 如果用户只填了 Base URL，自动补全路径
|
||||
if self.config.api_base and not url.endswith("/chat/completions"):
|
||||
base = url.rstrip("/")
|
||||
url = f"{base}/chat/completions"
|
||||
|
||||
timeout = self.config.timeout_ms / 1000
|
||||
|
||||
async with httpx.AsyncClient(timeout=timeout) as client:
|
||||
response = await client.post(
|
||||
url,
|
||||
json=payload,
|
||||
headers={
|
||||
"Authorization": f"Bearer {self.config.api_key}",
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
)
|
||||
response.raise_for_status()
|
||||
return response.json()
|
||||
|
||||
async def health_check(self) -> bool:
|
||||
"""检查 OpenAI API 是否可用。"""
|
||||
try:
|
||||
payload = {
|
||||
"model": self.config.model or "gpt-4o-mini",
|
||||
"messages": [{"role": "user", "content": "Hi"}],
|
||||
"max_tokens": 5,
|
||||
}
|
||||
await self._call_api(payload)
|
||||
return True
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
@property
|
||||
def estimated_cost(self) -> float:
|
||||
"""预估文本生成成本 (USD)。"""
|
||||
return 0.01
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
"""TTS 语音合成适配器。"""
|
||||
|
||||
from app.services.adapters.tts import edge_tts as _tts_edge_tts_adapter # noqa: F401
|
||||
from app.services.adapters.tts import elevenlabs as _tts_elevenlabs_adapter # noqa: F401
|
||||
from app.services.adapters.tts import minimax as _tts_minimax_adapter # noqa: F401
|
||||
"""TTS 语音合成适配器。"""
|
||||
|
||||
from app.services.adapters.tts import edge_tts as _tts_edge_tts_adapter # noqa: F401
|
||||
from app.services.adapters.tts import elevenlabs as _tts_elevenlabs_adapter # noqa: F401
|
||||
from app.services.adapters.tts import minimax as _tts_minimax_adapter # noqa: F401
|
||||
|
||||
@@ -1,66 +1,66 @@
|
||||
"""EdgeTTS 免费语音生成适配器。"""
|
||||
|
||||
import time
|
||||
|
||||
import edge_tts
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.services.adapters.base import BaseAdapter
|
||||
from app.services.adapters.registry import AdapterRegistry
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
# 默认中文女声 (晓晓)
|
||||
DEFAULT_VOICE = "zh-CN-XiaoxiaoNeural"
|
||||
|
||||
|
||||
@AdapterRegistry.register("tts", "edge_tts")
|
||||
class EdgeTTSAdapter(BaseAdapter[bytes]):
|
||||
"""EdgeTTS 语音生成适配器 (Free)。
|
||||
|
||||
不需要 API Key。
|
||||
"""
|
||||
|
||||
adapter_type = "tts"
|
||||
adapter_name = "edge_tts"
|
||||
|
||||
async def execute(self, text: str, **kwargs) -> bytes:
|
||||
"""生成语音。"""
|
||||
# 支持动态指定音色
|
||||
voice = kwargs.get("voice") or self.config.model or DEFAULT_VOICE
|
||||
|
||||
start_time = time.time()
|
||||
logger.info("edge_tts_generate_start", text_length=len(text), voice=voice)
|
||||
|
||||
# EdgeTTS 只能输出到文件，我们需要用临时文件周转一下
|
||||
# 或者直接 capture stream (communicate) 但 edge-tts 库主要面向文件
|
||||
|
||||
# 优化: 使用 communicate 直接获取 bytes，无需磁盘IO
|
||||
communicate = edge_tts.Communicate(text, voice)
|
||||
|
||||
audio_data = b""
|
||||
async for chunk in communicate.stream():
|
||||
if chunk["type"] == "audio":
|
||||
audio_data += chunk["data"]
|
||||
|
||||
elapsed = time.time() - start_time
|
||||
logger.info(
|
||||
"edge_tts_generate_success",
|
||||
elapsed_seconds=round(elapsed, 2),
|
||||
audio_size_bytes=len(audio_data),
|
||||
)
|
||||
|
||||
return audio_data
|
||||
|
||||
async def health_check(self) -> bool:
|
||||
"""检查 EdgeTTS 是否可用 (网络连通性)。"""
|
||||
try:
|
||||
# 简单生成一个词
|
||||
await self.execute("Hi")
|
||||
return True
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
@property
|
||||
def estimated_cost(self) -> float:
|
||||
return 0.0 # Free!
|
||||
"""EdgeTTS 免费语音生成适配器。"""
|
||||
|
||||
import time
|
||||
|
||||
import edge_tts
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.services.adapters.base import BaseAdapter
|
||||
from app.services.adapters.registry import AdapterRegistry
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
# 默认中文女声 (晓晓)
|
||||
DEFAULT_VOICE = "zh-CN-XiaoxiaoNeural"
|
||||
|
||||
|
||||
@AdapterRegistry.register("tts", "edge_tts")
|
||||
class EdgeTTSAdapter(BaseAdapter[bytes]):
|
||||
"""EdgeTTS 语音生成适配器 (Free)。
|
||||
|
||||
不需要 API Key。
|
||||
"""
|
||||
|
||||
adapter_type = "tts"
|
||||
adapter_name = "edge_tts"
|
||||
|
||||
async def execute(self, text: str, **kwargs) -> bytes:
|
||||
"""生成语音。"""
|
||||
# 支持动态指定音色
|
||||
voice = kwargs.get("voice") or self.config.model or DEFAULT_VOICE
|
||||
|
||||
start_time = time.time()
|
||||
logger.info("edge_tts_generate_start", text_length=len(text), voice=voice)
|
||||
|
||||
# EdgeTTS 只能输出到文件，我们需要用临时文件周转一下
|
||||
# 或者直接 capture stream (communicate) 但 edge-tts 库主要面向文件
|
||||
|
||||
# 优化: 使用 communicate 直接获取 bytes，无需磁盘IO
|
||||
communicate = edge_tts.Communicate(text, voice)
|
||||
|
||||
audio_data = b""
|
||||
async for chunk in communicate.stream():
|
||||
if chunk["type"] == "audio":
|
||||
audio_data += chunk["data"]
|
||||
|
||||
elapsed = time.time() - start_time
|
||||
logger.info(
|
||||
"edge_tts_generate_success",
|
||||
elapsed_seconds=round(elapsed, 2),
|
||||
audio_size_bytes=len(audio_data),
|
||||
)
|
||||
|
||||
return audio_data
|
||||
|
||||
async def health_check(self) -> bool:
|
||||
"""检查 EdgeTTS 是否可用 (网络连通性)。"""
|
||||
try:
|
||||
# 简单生成一个词
|
||||
await self.execute("Hi")
|
||||
return True
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
@property
|
||||
def estimated_cost(self) -> float:
|
||||
return 0.0 # Free!
|
||||
|
||||
@@ -1,104 +1,104 @@
|
||||
"""ElevenLabs TTS 语音合成适配器。"""
|
||||
|
||||
import time
|
||||
|
||||
import httpx
|
||||
from tenacity import (
|
||||
retry,
|
||||
retry_if_exception_type,
|
||||
stop_after_attempt,
|
||||
wait_exponential,
|
||||
)
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.services.adapters.base import AdapterConfig, BaseAdapter
|
||||
from app.services.adapters.registry import AdapterRegistry
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
ELEVENLABS_API_BASE = "https://api.elevenlabs.io/v1"
|
||||
DEFAULT_VOICE_ID = "21m00Tcm4TlvDq8ikWAM" # Rachel
|
||||
|
||||
|
||||
@AdapterRegistry.register("tts", "elevenlabs")
|
||||
class ElevenLabsTtsAdapter(BaseAdapter[bytes]):
|
||||
"""ElevenLabs TTS 语音合成适配器，返回 MP3 bytes。"""
|
||||
|
||||
adapter_type = "tts"
|
||||
adapter_name = "elevenlabs"
|
||||
|
||||
def __init__(self, config: AdapterConfig):
|
||||
super().__init__(config)
|
||||
self.api_base = config.api_base or ELEVENLABS_API_BASE
|
||||
|
||||
async def execute(self, text: str, **kwargs) -> bytes:
|
||||
"""将文本转换为语音 MP3 bytes。"""
|
||||
start_time = time.time()
|
||||
logger.info("elevenlabs_tts_start", text_length=len(text))
|
||||
|
||||
voice_id = kwargs.get("voice_id") or DEFAULT_VOICE_ID
|
||||
model_id = kwargs.get("model") or self.config.model or "eleven_multilingual_v2"
|
||||
stability = kwargs.get("stability", 0.5)
|
||||
similarity_boost = kwargs.get("similarity_boost", 0.75)
|
||||
|
||||
url = f"{self.api_base}/text-to-speech/{voice_id}"
|
||||
|
||||
payload = {
|
||||
"text": text,
|
||||
"model_id": model_id,
|
||||
"voice_settings": {
|
||||
"stability": stability,
|
||||
"similarity_boost": similarity_boost,
|
||||
},
|
||||
}
|
||||
|
||||
audio_bytes = await self._call_api(url, payload)
|
||||
|
||||
elapsed = time.time() - start_time
|
||||
logger.info(
|
||||
"elevenlabs_tts_success",
|
||||
elapsed_seconds=round(elapsed, 2),
|
||||
audio_size_bytes=len(audio_bytes),
|
||||
)
|
||||
|
||||
return audio_bytes
|
||||
|
||||
async def health_check(self) -> bool:
|
||||
"""检查 ElevenLabs API 是否可用。"""
|
||||
try:
|
||||
async with httpx.AsyncClient(timeout=10) as client:
|
||||
response = await client.get(
|
||||
f"{self.api_base}/voices",
|
||||
headers={"xi-api-key": self.config.api_key},
|
||||
)
|
||||
return response.status_code == 200
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
@property
|
||||
def estimated_cost(self) -> float:
|
||||
"""预估每千字符成本 (USD)。"""
|
||||
return 0.03
|
||||
|
||||
@retry(
|
||||
stop=stop_after_attempt(3),
|
||||
wait=wait_exponential(multiplier=1, min=1, max=10),
|
||||
retry=retry_if_exception_type((httpx.HTTPError, httpx.TimeoutException)),
|
||||
reraise=True,
|
||||
)
|
||||
async def _call_api(self, url: str, payload: dict) -> bytes:
|
||||
"""调用 ElevenLabs API，带重试机制。"""
|
||||
timeout = self.config.timeout_ms / 1000
|
||||
|
||||
async with httpx.AsyncClient(timeout=timeout) as client:
|
||||
response = await client.post(
|
||||
url,
|
||||
json=payload,
|
||||
headers={
|
||||
"xi-api-key": self.config.api_key,
|
||||
"Content-Type": "application/json",
|
||||
"Accept": "audio/mpeg",
|
||||
},
|
||||
)
|
||||
response.raise_for_status()
|
||||
return response.content
|
||||
"""ElevenLabs TTS 语音合成适配器。"""
|
||||
|
||||
import time
|
||||
|
||||
import httpx
|
||||
from tenacity import (
|
||||
retry,
|
||||
retry_if_exception_type,
|
||||
stop_after_attempt,
|
||||
wait_exponential,
|
||||
)
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.services.adapters.base import AdapterConfig, BaseAdapter
|
||||
from app.services.adapters.registry import AdapterRegistry
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
ELEVENLABS_API_BASE = "https://api.elevenlabs.io/v1"
|
||||
DEFAULT_VOICE_ID = "21m00Tcm4TlvDq8ikWAM" # Rachel
|
||||
|
||||
|
||||
@AdapterRegistry.register("tts", "elevenlabs")
|
||||
class ElevenLabsTtsAdapter(BaseAdapter[bytes]):
|
||||
"""ElevenLabs TTS 语音合成适配器，返回 MP3 bytes。"""
|
||||
|
||||
adapter_type = "tts"
|
||||
adapter_name = "elevenlabs"
|
||||
|
||||
def __init__(self, config: AdapterConfig):
|
||||
super().__init__(config)
|
||||
self.api_base = config.api_base or ELEVENLABS_API_BASE
|
||||
|
||||
async def execute(self, text: str, **kwargs) -> bytes:
|
||||
"""将文本转换为语音 MP3 bytes。"""
|
||||
start_time = time.time()
|
||||
logger.info("elevenlabs_tts_start", text_length=len(text))
|
||||
|
||||
voice_id = kwargs.get("voice_id") or DEFAULT_VOICE_ID
|
||||
model_id = kwargs.get("model") or self.config.model or "eleven_multilingual_v2"
|
||||
stability = kwargs.get("stability", 0.5)
|
||||
similarity_boost = kwargs.get("similarity_boost", 0.75)
|
||||
|
||||
url = f"{self.api_base}/text-to-speech/{voice_id}"
|
||||
|
||||
payload = {
|
||||
"text": text,
|
||||
"model_id": model_id,
|
||||
"voice_settings": {
|
||||
"stability": stability,
|
||||
"similarity_boost": similarity_boost,
|
||||
},
|
||||
}
|
||||
|
||||
audio_bytes = await self._call_api(url, payload)
|
||||
|
||||
elapsed = time.time() - start_time
|
||||
logger.info(
|
||||
"elevenlabs_tts_success",
|
||||
elapsed_seconds=round(elapsed, 2),
|
||||
audio_size_bytes=len(audio_bytes),
|
||||
)
|
||||
|
||||
return audio_bytes
|
||||
|
||||
async def health_check(self) -> bool:
|
||||
"""检查 ElevenLabs API 是否可用。"""
|
||||
try:
|
||||
async with httpx.AsyncClient(timeout=10) as client:
|
||||
response = await client.get(
|
||||
f"{self.api_base}/voices",
|
||||
headers={"xi-api-key": self.config.api_key},
|
||||
)
|
||||
return response.status_code == 200
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
@property
|
||||
def estimated_cost(self) -> float:
|
||||
"""预估每千字符成本 (USD)。"""
|
||||
return 0.03
|
||||
|
||||
@retry(
|
||||
stop=stop_after_attempt(3),
|
||||
wait=wait_exponential(multiplier=1, min=1, max=10),
|
||||
retry=retry_if_exception_type((httpx.HTTPError, httpx.TimeoutException)),
|
||||
reraise=True,
|
||||
)
|
||||
async def _call_api(self, url: str, payload: dict) -> bytes:
|
||||
"""调用 ElevenLabs API，带重试机制。"""
|
||||
timeout = self.config.timeout_ms / 1000
|
||||
|
||||
async with httpx.AsyncClient(timeout=timeout) as client:
|
||||
response = await client.post(
|
||||
url,
|
||||
json=payload,
|
||||
headers={
|
||||
"xi-api-key": self.config.api_key,
|
||||
"Content-Type": "application/json",
|
||||
"Accept": "audio/mpeg",
|
||||
},
|
||||
)
|
||||
response.raise_for_status()
|
||||
return response.content
|
||||
|
||||
@@ -1,149 +1,149 @@
|
||||
"""MiniMax 语音生成适配器 (T2A V2)。"""
|
||||
|
||||
import time
|
||||
|
||||
import httpx
|
||||
from tenacity import (
|
||||
retry,
|
||||
retry_if_exception_type,
|
||||
stop_after_attempt,
|
||||
wait_exponential,
|
||||
)
|
||||
|
||||
from app.core.config import settings
|
||||
from app.core.logging import get_logger
|
||||
from app.services.adapters.base import AdapterConfig, BaseAdapter
|
||||
from app.services.adapters.registry import AdapterRegistry
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
# MiniMax API 配置
|
||||
DEFAULT_API_URL = "https://api.minimaxi.com/v1/t2a_v2"
|
||||
DEFAULT_MODEL = "speech-2.6-turbo"
|
||||
|
||||
@AdapterRegistry.register("tts", "minimax")
|
||||
class MiniMaxTTSAdapter(BaseAdapter[bytes]):
|
||||
"""MiniMax 语音生成适配器。
|
||||
|
||||
需要配置:
|
||||
- api_key: MiniMax API Key
|
||||
- minimax_group_id: 可选 (取决于使用的模型/账户类型)
|
||||
"""
|
||||
|
||||
adapter_type = "tts"
|
||||
adapter_name = "minimax"
|
||||
|
||||
def __init__(self, config: AdapterConfig):
|
||||
super().__init__(config)
|
||||
self.api_url = DEFAULT_API_URL
|
||||
|
||||
async def execute(
|
||||
self,
|
||||
text: str,
|
||||
voice_id: str | None = None,
|
||||
model: str | None = None,
|
||||
speed: float | None = None,
|
||||
vol: float | None = None,
|
||||
pitch: int | None = None,
|
||||
emotion: str | None = None,
|
||||
**kwargs,
|
||||
) -> bytes:
|
||||
"""生成语音。"""
|
||||
# 1. 优先使用传入参数
|
||||
# 2. 其次使用 Adapter 配置里的 default
|
||||
# 3. 最后使用系统默认值
|
||||
model = model or self.config.model or DEFAULT_MODEL
|
||||
|
||||
cfg = self.config.extra_config or {}
|
||||
|
||||
voice_id = voice_id or cfg.get("voice_id") or "male-qn-qingse"
|
||||
speed = speed if speed is not None else (cfg.get("speed") or 1.0)
|
||||
vol = vol if vol is not None else (cfg.get("vol") or 1.0)
|
||||
pitch = pitch if pitch is not None else (cfg.get("pitch") or 0)
|
||||
emotion = emotion or cfg.get("emotion")
|
||||
group_id = kwargs.get("group_id") or settings.minimax_group_id
|
||||
|
||||
url = self.api_url
|
||||
if group_id:
|
||||
url = f"{self.api_url}?GroupId={group_id}"
|
||||
|
||||
payload = {
|
||||
"model": model,
|
||||
"text": text,
|
||||
"stream": False,
|
||||
"voice_setting": {
|
||||
"voice_id": voice_id,
|
||||
"speed": speed,
|
||||
"vol": vol,
|
||||
"pitch": pitch,
|
||||
},
|
||||
"audio_setting": {
|
||||
"sample_rate": 32000,
|
||||
"bitrate": 128000,
|
||||
"format": "mp3",
|
||||
"channel": 1
|
||||
}
|
||||
}
|
||||
|
||||
if emotion:
|
||||
payload["voice_setting"]["emotion"] = emotion
|
||||
|
||||
start_time = time.time()
|
||||
logger.info("minimax_generate_start", text_length=len(text), model=model)
|
||||
|
||||
result = await self._call_api(url, payload)
|
||||
|
||||
# 错误处理
|
||||
if result.get("base_resp", {}).get("status_code") != 0:
|
||||
error_msg = result.get("base_resp", {}).get("status_msg", "未知错误")
|
||||
raise ValueError(f"MiniMax API 错误: {error_msg}")
|
||||
|
||||
# Hex 解码 (关键逻辑，从 primary.py 迁移)
|
||||
hex_audio = result.get("data", {}).get("audio")
|
||||
if not hex_audio:
|
||||
raise ValueError("API 响应中未找到音频数据 (data.audio)")
|
||||
|
||||
try:
|
||||
audio_bytes = bytes.fromhex(hex_audio)
|
||||
except ValueError:
|
||||
raise ValueError("MiniMax 返回的音频数据不是有效的 Hex 字符串")
|
||||
|
||||
elapsed = time.time() - start_time
|
||||
logger.info(
|
||||
"minimax_generate_success",
|
||||
elapsed_seconds=round(elapsed, 2),
|
||||
audio_size_bytes=len(audio_bytes),
|
||||
)
|
||||
|
||||
return audio_bytes
|
||||
|
||||
async def health_check(self) -> bool:
|
||||
"""检查 Minimax API 是否可用。"""
|
||||
try:
|
||||
# 尝试生成极短文本
|
||||
await self.execute("Hi")
|
||||
return True
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
@retry(
|
||||
stop=stop_after_attempt(3),
|
||||
wait=wait_exponential(multiplier=1, min=1, max=10),
|
||||
retry=retry_if_exception_type((httpx.HTTPError, httpx.TimeoutException)),
|
||||
reraise=True,
|
||||
)
|
||||
async def _call_api(self, url: str, payload: dict) -> dict:
|
||||
"""调用 API，带重试机制。"""
|
||||
timeout = self.config.timeout_ms / 1000
|
||||
|
||||
async with httpx.AsyncClient(timeout=timeout) as client:
|
||||
response = await client.post(
|
||||
url,
|
||||
json=payload,
|
||||
headers={
|
||||
"Authorization": f"Bearer {self.config.api_key}",
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
)
|
||||
response.raise_for_status()
|
||||
return response.json()
|
||||
"""MiniMax 语音生成适配器 (T2A V2)。"""
|
||||
|
||||
import time
|
||||
|
||||
import httpx
|
||||
from tenacity import (
|
||||
retry,
|
||||
retry_if_exception_type,
|
||||
stop_after_attempt,
|
||||
wait_exponential,
|
||||
)
|
||||
|
||||
from app.core.config import settings
|
||||
from app.core.logging import get_logger
|
||||
from app.services.adapters.base import AdapterConfig, BaseAdapter
|
||||
from app.services.adapters.registry import AdapterRegistry
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
# MiniMax API 配置
|
||||
DEFAULT_API_URL = "https://api.minimaxi.com/v1/t2a_v2"
|
||||
DEFAULT_MODEL = "speech-2.6-turbo"
|
||||
|
||||
@AdapterRegistry.register("tts", "minimax")
|
||||
class MiniMaxTTSAdapter(BaseAdapter[bytes]):
|
||||
"""MiniMax 语音生成适配器。
|
||||
|
||||
需要配置:
|
||||
- api_key: MiniMax API Key
|
||||
- minimax_group_id: 可选 (取决于使用的模型/账户类型)
|
||||
"""
|
||||
|
||||
adapter_type = "tts"
|
||||
adapter_name = "minimax"
|
||||
|
||||
def __init__(self, config: AdapterConfig):
|
||||
super().__init__(config)
|
||||
self.api_url = DEFAULT_API_URL
|
||||
|
||||
async def execute(
|
||||
self,
|
||||
text: str,
|
||||
voice_id: str | None = None,
|
||||
model: str | None = None,
|
||||
speed: float | None = None,
|
||||
vol: float | None = None,
|
||||
pitch: int | None = None,
|
||||
emotion: str | None = None,
|
||||
**kwargs,
|
||||
) -> bytes:
|
||||
"""生成语音。"""
|
||||
# 1. 优先使用传入参数
|
||||
# 2. 其次使用 Adapter 配置里的 default
|
||||
# 3. 最后使用系统默认值
|
||||
model = model or self.config.model or DEFAULT_MODEL
|
||||
|
||||
cfg = self.config.extra_config or {}
|
||||
|
||||
voice_id = voice_id or cfg.get("voice_id") or "male-qn-qingse"
|
||||
speed = speed if speed is not None else (cfg.get("speed") or 1.0)
|
||||
vol = vol if vol is not None else (cfg.get("vol") or 1.0)
|
||||
pitch = pitch if pitch is not None else (cfg.get("pitch") or 0)
|
||||
emotion = emotion or cfg.get("emotion")
|
||||
group_id = kwargs.get("group_id") or settings.minimax_group_id
|
||||
|
||||
url = self.api_url
|
||||
if group_id:
|
||||
url = f"{self.api_url}?GroupId={group_id}"
|
||||
|
||||
payload = {
|
||||
"model": model,
|
||||
"text": text,
|
||||
"stream": False,
|
||||
"voice_setting": {
|
||||
"voice_id": voice_id,
|
||||
"speed": speed,
|
||||
"vol": vol,
|
||||
"pitch": pitch,
|
||||
},
|
||||
"audio_setting": {
|
||||
"sample_rate": 32000,
|
||||
"bitrate": 128000,
|
||||
"format": "mp3",
|
||||
"channel": 1
|
||||
}
|
||||
}
|
||||
|
||||
if emotion:
|
||||
payload["voice_setting"]["emotion"] = emotion
|
||||
|
||||
start_time = time.time()
|
||||
logger.info("minimax_generate_start", text_length=len(text), model=model)
|
||||
|
||||
result = await self._call_api(url, payload)
|
||||
|
||||
# 错误处理
|
||||
if result.get("base_resp", {}).get("status_code") != 0:
|
||||
error_msg = result.get("base_resp", {}).get("status_msg", "未知错误")
|
||||
raise ValueError(f"MiniMax API 错误: {error_msg}")
|
||||
|
||||
# Hex 解码 (关键逻辑，从 primary.py 迁移)
|
||||
hex_audio = result.get("data", {}).get("audio")
|
||||
if not hex_audio:
|
||||
raise ValueError("API 响应中未找到音频数据 (data.audio)")
|
||||
|
||||
try:
|
||||
audio_bytes = bytes.fromhex(hex_audio)
|
||||
except ValueError:
|
||||
raise ValueError("MiniMax 返回的音频数据不是有效的 Hex 字符串")
|
||||
|
||||
elapsed = time.time() - start_time
|
||||
logger.info(
|
||||
"minimax_generate_success",
|
||||
elapsed_seconds=round(elapsed, 2),
|
||||
audio_size_bytes=len(audio_bytes),
|
||||
)
|
||||
|
||||
return audio_bytes
|
||||
|
||||
async def health_check(self) -> bool:
|
||||
"""检查 Minimax API 是否可用。"""
|
||||
try:
|
||||
# 尝试生成极短文本
|
||||
await self.execute("Hi")
|
||||
return True
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
@retry(
|
||||
stop=stop_after_attempt(3),
|
||||
wait=wait_exponential(multiplier=1, min=1, max=10),
|
||||
retry=retry_if_exception_type((httpx.HTTPError, httpx.TimeoutException)),
|
||||
reraise=True,
|
||||
)
|
||||
async def _call_api(self, url: str, payload: dict) -> dict:
|
||||
"""调用 API，带重试机制。"""
|
||||
timeout = self.config.timeout_ms / 1000
|
||||
|
||||
async with httpx.AsyncClient(timeout=timeout) as client:
|
||||
response = await client.post(
|
||||
url,
|
||||
json=payload,
|
||||
headers={
|
||||
"Authorization": f"Bearer {self.config.api_key}",
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
)
|
||||
response.raise_for_status()
|
||||
return response.json()
|
||||
|
||||
@@ -1,196 +1,196 @@
|
||||
"""成本追踪服务。
|
||||
|
||||
记录 API 调用成本，支持预算控制。
|
||||
"""
|
||||
|
||||
from datetime import datetime, timedelta
|
||||
from decimal import Decimal
|
||||
|
||||
from sqlalchemy import func, select
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.db.admin_models import CostRecord, UserBudget
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
|
||||
class BudgetExceededError(Exception):
|
||||
"""预算超限错误。"""
|
||||
|
||||
def __init__(self, limit_type: str, used: Decimal, limit: Decimal):
|
||||
self.limit_type = limit_type
|
||||
self.used = used
|
||||
self.limit = limit
|
||||
super().__init__(f"{limit_type} 预算已超限: {used}/{limit} USD")
|
||||
|
||||
|
||||
class CostTracker:
|
||||
"""成本追踪器。"""
|
||||
|
||||
async def record_cost(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
user_id: str,
|
||||
provider_name: str,
|
||||
capability: str,
|
||||
estimated_cost: float,
|
||||
provider_id: str | None = None,
|
||||
) -> CostRecord:
|
||||
"""记录一次 API 调用成本。"""
|
||||
record = CostRecord(
|
||||
user_id=user_id,
|
||||
provider_id=provider_id,
|
||||
provider_name=provider_name,
|
||||
capability=capability,
|
||||
estimated_cost=Decimal(str(estimated_cost)),
|
||||
)
|
||||
db.add(record)
|
||||
await db.commit()
|
||||
|
||||
logger.debug(
|
||||
"cost_recorded",
|
||||
user_id=user_id,
|
||||
provider=provider_name,
|
||||
capability=capability,
|
||||
cost=estimated_cost,
|
||||
)
|
||||
return record
|
||||
|
||||
async def get_daily_cost(self, db: AsyncSession, user_id: str) -> Decimal:
|
||||
"""获取用户今日成本。"""
|
||||
today_start = datetime.utcnow().replace(hour=0, minute=0, second=0, microsecond=0)
|
||||
|
||||
result = await db.execute(
|
||||
select(func.sum(CostRecord.estimated_cost)).where(
|
||||
CostRecord.user_id == user_id,
|
||||
CostRecord.timestamp >= today_start,
|
||||
)
|
||||
)
|
||||
total = result.scalar()
|
||||
return Decimal(str(total)) if total else Decimal("0")
|
||||
|
||||
async def get_monthly_cost(self, db: AsyncSession, user_id: str) -> Decimal:
|
||||
"""获取用户本月成本。"""
|
||||
now = datetime.utcnow()
|
||||
month_start = now.replace(day=1, hour=0, minute=0, second=0, microsecond=0)
|
||||
|
||||
result = await db.execute(
|
||||
select(func.sum(CostRecord.estimated_cost)).where(
|
||||
CostRecord.user_id == user_id,
|
||||
CostRecord.timestamp >= month_start,
|
||||
)
|
||||
)
|
||||
total = result.scalar()
|
||||
return Decimal(str(total)) if total else Decimal("0")
|
||||
|
||||
async def get_cost_by_capability(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
user_id: str,
|
||||
days: int = 30,
|
||||
) -> dict[str, Decimal]:
|
||||
"""按能力类型统计成本。"""
|
||||
since = datetime.utcnow() - timedelta(days=days)
|
||||
|
||||
result = await db.execute(
|
||||
select(CostRecord.capability, func.sum(CostRecord.estimated_cost))
|
||||
.where(CostRecord.user_id == user_id, CostRecord.timestamp >= since)
|
||||
.group_by(CostRecord.capability)
|
||||
)
|
||||
return {row[0]: Decimal(str(row[1])) for row in result.all()}
|
||||
|
||||
async def check_budget(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
user_id: str,
|
||||
estimated_cost: float,
|
||||
) -> bool:
|
||||
"""检查预算是否允许此次调用。
|
||||
|
||||
Returns:
|
||||
True 如果允许，否则抛出 BudgetExceededError
|
||||
"""
|
||||
budget = await self.get_user_budget(db, user_id)
|
||||
if not budget or not budget.enabled:
|
||||
return True
|
||||
|
||||
# 检查日预算
|
||||
daily_cost = await self.get_daily_cost(db, user_id)
|
||||
if daily_cost + Decimal(str(estimated_cost)) > budget.daily_limit_usd:
|
||||
raise BudgetExceededError("日", daily_cost, budget.daily_limit_usd)
|
||||
|
||||
# 检查月预算
|
||||
monthly_cost = await self.get_monthly_cost(db, user_id)
|
||||
if monthly_cost + Decimal(str(estimated_cost)) > budget.monthly_limit_usd:
|
||||
raise BudgetExceededError("月", monthly_cost, budget.monthly_limit_usd)
|
||||
|
||||
return True
|
||||
|
||||
async def get_user_budget(self, db: AsyncSession, user_id: str) -> UserBudget | None:
|
||||
"""获取用户预算配置。"""
|
||||
result = await db.execute(
|
||||
select(UserBudget).where(UserBudget.user_id == user_id)
|
||||
)
|
||||
return result.scalar_one_or_none()
|
||||
|
||||
async def set_user_budget(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
user_id: str,
|
||||
daily_limit: float | None = None,
|
||||
monthly_limit: float | None = None,
|
||||
alert_threshold: float | None = None,
|
||||
enabled: bool | None = None,
|
||||
) -> UserBudget:
|
||||
"""设置用户预算。"""
|
||||
budget = await self.get_user_budget(db, user_id)
|
||||
|
||||
if budget is None:
|
||||
budget = UserBudget(user_id=user_id)
|
||||
db.add(budget)
|
||||
|
||||
if daily_limit is not None:
|
||||
budget.daily_limit_usd = Decimal(str(daily_limit))
|
||||
if monthly_limit is not None:
|
||||
budget.monthly_limit_usd = Decimal(str(monthly_limit))
|
||||
if alert_threshold is not None:
|
||||
budget.alert_threshold = Decimal(str(alert_threshold))
|
||||
if enabled is not None:
|
||||
budget.enabled = enabled
|
||||
|
||||
await db.commit()
|
||||
await db.refresh(budget)
|
||||
return budget
|
||||
|
||||
async def get_cost_summary(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
user_id: str,
|
||||
) -> dict:
|
||||
"""获取用户成本摘要。"""
|
||||
daily = await self.get_daily_cost(db, user_id)
|
||||
monthly = await self.get_monthly_cost(db, user_id)
|
||||
by_capability = await self.get_cost_by_capability(db, user_id)
|
||||
budget = await self.get_user_budget(db, user_id)
|
||||
|
||||
return {
|
||||
"daily_cost_usd": float(daily),
|
||||
"monthly_cost_usd": float(monthly),
|
||||
"by_capability": {k: float(v) for k, v in by_capability.items()},
|
||||
"budget": {
|
||||
"daily_limit_usd": float(budget.daily_limit_usd) if budget else None,
|
||||
"monthly_limit_usd": float(budget.monthly_limit_usd) if budget else None,
|
||||
"daily_usage_percent": float(daily / budget.daily_limit_usd * 100)
|
||||
if budget and budget.daily_limit_usd
|
||||
else None,
|
||||
"monthly_usage_percent": float(monthly / budget.monthly_limit_usd * 100)
|
||||
if budget and budget.monthly_limit_usd
|
||||
else None,
|
||||
"enabled": budget.enabled if budget else False,
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
# 全局单例
|
||||
cost_tracker = CostTracker()
|
||||
"""成本追踪服务。
|
||||
|
||||
记录 API 调用成本，支持预算控制。
|
||||
"""
|
||||
|
||||
from datetime import datetime, timedelta
|
||||
from decimal import Decimal
|
||||
|
||||
from sqlalchemy import func, select
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.db.admin_models import CostRecord, UserBudget
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
|
||||
class BudgetExceededError(Exception):
|
||||
"""预算超限错误。"""
|
||||
|
||||
def __init__(self, limit_type: str, used: Decimal, limit: Decimal):
|
||||
self.limit_type = limit_type
|
||||
self.used = used
|
||||
self.limit = limit
|
||||
super().__init__(f"{limit_type} 预算已超限: {used}/{limit} USD")
|
||||
|
||||
|
||||
class CostTracker:
|
||||
"""成本追踪器。"""
|
||||
|
||||
async def record_cost(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
user_id: str,
|
||||
provider_name: str,
|
||||
capability: str,
|
||||
estimated_cost: float,
|
||||
provider_id: str | None = None,
|
||||
) -> CostRecord:
|
||||
"""记录一次 API 调用成本。"""
|
||||
record = CostRecord(
|
||||
user_id=user_id,
|
||||
provider_id=provider_id,
|
||||
provider_name=provider_name,
|
||||
capability=capability,
|
||||
estimated_cost=Decimal(str(estimated_cost)),
|
||||
)
|
||||
db.add(record)
|
||||
await db.commit()
|
||||
|
||||
logger.debug(
|
||||
"cost_recorded",
|
||||
user_id=user_id,
|
||||
provider=provider_name,
|
||||
capability=capability,
|
||||
cost=estimated_cost,
|
||||
)
|
||||
return record
|
||||
|
||||
async def get_daily_cost(self, db: AsyncSession, user_id: str) -> Decimal:
|
||||
"""获取用户今日成本。"""
|
||||
today_start = datetime.utcnow().replace(hour=0, minute=0, second=0, microsecond=0)
|
||||
|
||||
result = await db.execute(
|
||||
select(func.sum(CostRecord.estimated_cost)).where(
|
||||
CostRecord.user_id == user_id,
|
||||
CostRecord.timestamp >= today_start,
|
||||
)
|
||||
)
|
||||
total = result.scalar()
|
||||
return Decimal(str(total)) if total else Decimal("0")
|
||||
|
||||
async def get_monthly_cost(self, db: AsyncSession, user_id: str) -> Decimal:
|
||||
"""获取用户本月成本。"""
|
||||
now = datetime.utcnow()
|
||||
month_start = now.replace(day=1, hour=0, minute=0, second=0, microsecond=0)
|
||||
|
||||
result = await db.execute(
|
||||
select(func.sum(CostRecord.estimated_cost)).where(
|
||||
CostRecord.user_id == user_id,
|
||||
CostRecord.timestamp >= month_start,
|
||||
)
|
||||
)
|
||||
total = result.scalar()
|
||||
return Decimal(str(total)) if total else Decimal("0")
|
||||
|
||||
async def get_cost_by_capability(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
user_id: str,
|
||||
days: int = 30,
|
||||
) -> dict[str, Decimal]:
|
||||
"""按能力类型统计成本。"""
|
||||
since = datetime.utcnow() - timedelta(days=days)
|
||||
|
||||
result = await db.execute(
|
||||
select(CostRecord.capability, func.sum(CostRecord.estimated_cost))
|
||||
.where(CostRecord.user_id == user_id, CostRecord.timestamp >= since)
|
||||
.group_by(CostRecord.capability)
|
||||
)
|
||||
return {row[0]: Decimal(str(row[1])) for row in result.all()}
|
||||
|
||||
async def check_budget(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
user_id: str,
|
||||
estimated_cost: float,
|
||||
) -> bool:
|
||||
"""检查预算是否允许此次调用。
|
||||
|
||||
Returns:
|
||||
True 如果允许，否则抛出 BudgetExceededError
|
||||
"""
|
||||
budget = await self.get_user_budget(db, user_id)
|
||||
if not budget or not budget.enabled:
|
||||
return True
|
||||
|
||||
# 检查日预算
|
||||
daily_cost = await self.get_daily_cost(db, user_id)
|
||||
if daily_cost + Decimal(str(estimated_cost)) > budget.daily_limit_usd:
|
||||
raise BudgetExceededError("日", daily_cost, budget.daily_limit_usd)
|
||||
|
||||
# 检查月预算
|
||||
monthly_cost = await self.get_monthly_cost(db, user_id)
|
||||
if monthly_cost + Decimal(str(estimated_cost)) > budget.monthly_limit_usd:
|
||||
raise BudgetExceededError("月", monthly_cost, budget.monthly_limit_usd)
|
||||
|
||||
return True
|
||||
|
||||
async def get_user_budget(self, db: AsyncSession, user_id: str) -> UserBudget | None:
|
||||
"""获取用户预算配置。"""
|
||||
result = await db.execute(
|
||||
select(UserBudget).where(UserBudget.user_id == user_id)
|
||||
)
|
||||
return result.scalar_one_or_none()
|
||||
|
||||
async def set_user_budget(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
user_id: str,
|
||||
daily_limit: float | None = None,
|
||||
monthly_limit: float | None = None,
|
||||
alert_threshold: float | None = None,
|
||||
enabled: bool | None = None,
|
||||
) -> UserBudget:
|
||||
"""设置用户预算。"""
|
||||
budget = await self.get_user_budget(db, user_id)
|
||||
|
||||
if budget is None:
|
||||
budget = UserBudget(user_id=user_id)
|
||||
db.add(budget)
|
||||
|
||||
if daily_limit is not None:
|
||||
budget.daily_limit_usd = Decimal(str(daily_limit))
|
||||
if monthly_limit is not None:
|
||||
budget.monthly_limit_usd = Decimal(str(monthly_limit))
|
||||
if alert_threshold is not None:
|
||||
budget.alert_threshold = Decimal(str(alert_threshold))
|
||||
if enabled is not None:
|
||||
budget.enabled = enabled
|
||||
|
||||
await db.commit()
|
||||
await db.refresh(budget)
|
||||
return budget
|
||||
|
||||
async def get_cost_summary(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
user_id: str,
|
||||
) -> dict:
|
||||
"""获取用户成本摘要。"""
|
||||
daily = await self.get_daily_cost(db, user_id)
|
||||
monthly = await self.get_monthly_cost(db, user_id)
|
||||
by_capability = await self.get_cost_by_capability(db, user_id)
|
||||
budget = await self.get_user_budget(db, user_id)
|
||||
|
||||
return {
|
||||
"daily_cost_usd": float(daily),
|
||||
"monthly_cost_usd": float(monthly),
|
||||
"by_capability": {k: float(v) for k, v in by_capability.items()},
|
||||
"budget": {
|
||||
"daily_limit_usd": float(budget.daily_limit_usd) if budget else None,
|
||||
"monthly_limit_usd": float(budget.monthly_limit_usd) if budget else None,
|
||||
"daily_usage_percent": float(daily / budget.daily_limit_usd * 100)
|
||||
if budget and budget.daily_limit_usd
|
||||
else None,
|
||||
"monthly_usage_percent": float(monthly / budget.monthly_limit_usd * 100)
|
||||
if budget and budget.monthly_limit_usd
|
||||
else None,
|
||||
"enabled": budget.enabled if budget else False,
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
# 全局单例
|
||||
cost_tracker = CostTracker()
|
||||
|
||||
@@ -1,471 +1,471 @@
|
||||
"""Memory service handles memory retrieval, scoring, and prompt injection."""
|
||||
|
||||
from datetime import datetime, timezone
|
||||
|
||||
from sqlalchemy import select
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.db.models import ChildProfile, MemoryItem, StoryUniverse
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
|
||||
class MemoryType:
|
||||
"""记忆类型常量及配置。"""
|
||||
|
||||
# 基础类型
|
||||
RECENT_STORY = "recent_story"
|
||||
FAVORITE_CHARACTER = "favorite_character"
|
||||
SCARY_ELEMENT = "scary_element"
|
||||
VOCABULARY_GROWTH = "vocabulary_growth"
|
||||
EMOTIONAL_HIGHLIGHT = "emotional_highlight"
|
||||
|
||||
# Phase 1 新增类型
|
||||
READING_PREFERENCE = "reading_preference" # 阅读偏好
|
||||
MILESTONE = "milestone" # 里程碑事件
|
||||
SKILL_MASTERED = "skill_mastered" # 掌握的技能
|
||||
|
||||
# 类型配置: (默认权重, 默认TTL天数, 描述)
|
||||
CONFIG = {
|
||||
RECENT_STORY: (1.0, 30, "最近阅读的故事"),
|
||||
FAVORITE_CHARACTER: (1.5, None, "喜欢的角色"), # None = 永久
|
||||
SCARY_ELEMENT: (2.0, None, "回避的元素"), # 高权重，永久有效
|
||||
VOCABULARY_GROWTH: (0.8, 90, "词汇积累"),
|
||||
EMOTIONAL_HIGHLIGHT: (1.2, 60, "情感高光"),
|
||||
READING_PREFERENCE: (1.0, None, "阅读偏好"),
|
||||
MILESTONE: (1.5, None, "里程碑事件"),
|
||||
SKILL_MASTERED: (1.0, 180, "掌握的技能"),
|
||||
}
|
||||
|
||||
@classmethod
|
||||
def get_default_weight(cls, memory_type: str) -> float:
|
||||
"""获取类型的默认权重。"""
|
||||
config = cls.CONFIG.get(memory_type)
|
||||
return config[0] if config else 1.0
|
||||
|
||||
@classmethod
|
||||
def get_default_ttl(cls, memory_type: str) -> int | None:
|
||||
"""获取类型的默认 TTL 天数。"""
|
||||
config = cls.CONFIG.get(memory_type)
|
||||
return config[1] if config else None
|
||||
|
||||
|
||||
def _decay_factor(days: float) -> float:
|
||||
"""计算时间衰减因子。"""
|
||||
if days <= 7:
|
||||
return 1.0
|
||||
if days <= 30:
|
||||
return 0.7
|
||||
if days <= 90:
|
||||
return 0.4
|
||||
return 0.2
|
||||
|
||||
|
||||
async def build_enhanced_memory_context(
|
||||
profile_id: str | None,
|
||||
universe_id: str | None,
|
||||
db: AsyncSession,
|
||||
) -> str | None:
|
||||
"""构建增强版记忆上下文（自然语言 Prompt）。"""
|
||||
if not profile_id and not universe_id:
|
||||
return None
|
||||
|
||||
context_parts: list[str] = []
|
||||
|
||||
# 1. 基础档案 (Identity Layer)
|
||||
if profile_id:
|
||||
profile = await db.scalar(select(ChildProfile).where(ChildProfile.id == profile_id))
|
||||
if profile:
|
||||
context_parts.append(f"【目标读者】\n姓名：{profile.name}")
|
||||
if profile.age:
|
||||
context_parts.append(f"年龄：{profile.age}岁")
|
||||
if profile.interests:
|
||||
context_parts.append(f"兴趣爱好：{'、'.join(profile.interests)}")
|
||||
if profile.growth_themes:
|
||||
context_parts.append(f"当前成长关注点：{'、'.join(profile.growth_themes)}")
|
||||
context_parts.append("") # 空行
|
||||
|
||||
# 2. 故事宇宙 (Universe Layer)
|
||||
if universe_id:
|
||||
universe = await db.scalar(select(StoryUniverse).where(StoryUniverse.id == universe_id))
|
||||
if universe:
|
||||
context_parts.append("【故事宇宙设定】")
|
||||
context_parts.append(f"世界观：{universe.name}")
|
||||
|
||||
# 主角
|
||||
protagonist = universe.protagonist or {}
|
||||
p_desc = f"{protagonist.get('name', '主角')} ({protagonist.get('personality', '')})"
|
||||
context_parts.append(f"主角设定：{p_desc}")
|
||||
|
||||
# 常驻角色
|
||||
if universe.recurring_characters:
|
||||
chars = [f"{c.get('name')} ({c.get('type')})" for c in universe.recurring_characters if isinstance(c, dict)]
|
||||
context_parts.append(f"已知伙伴：{'、'.join(chars)}")
|
||||
|
||||
# 成就
|
||||
if universe.achievements:
|
||||
badges = [str(a.get('type')) for a in universe.achievements if isinstance(a, dict)]
|
||||
if badges:
|
||||
context_parts.append(f"已获荣誉：{'、'.join(badges[:5])}")
|
||||
|
||||
context_parts.append("")
|
||||
|
||||
# 3. 动态记忆 (Working Memory)
|
||||
if profile_id:
|
||||
memories = await _fetch_scored_memories(profile_id, universe_id, db)
|
||||
if memories:
|
||||
memory_text = _format_memories_to_prompt(memories)
|
||||
if memory_text:
|
||||
context_parts.append("【关键记忆回忆】(请在故事中自然地融入或致敬以下元素)")
|
||||
context_parts.append(memory_text)
|
||||
|
||||
return "\n".join(context_parts)
|
||||
|
||||
|
||||
async def _fetch_scored_memories(
|
||||
profile_id: str,
|
||||
universe_id: str | None,
|
||||
db: AsyncSession,
|
||||
limit: int = 8
|
||||
) -> list[MemoryItem]:
|
||||
"""获取并评分记忆项，返回 Top N。"""
|
||||
query = select(MemoryItem).where(MemoryItem.child_profile_id == profile_id)
|
||||
if universe_id:
|
||||
query = query.where(
|
||||
(MemoryItem.universe_id == universe_id) | (MemoryItem.universe_id.is_(None))
|
||||
)
|
||||
# 取最近 50 条进行评分
|
||||
query = query.order_by(MemoryItem.last_used_at.desc(), MemoryItem.created_at.desc()).limit(50)
|
||||
|
||||
result = await db.execute(query)
|
||||
items = result.scalars().all()
|
||||
|
||||
scored: list[tuple[float, MemoryItem]] = []
|
||||
now = datetime.now(timezone.utc)
|
||||
|
||||
for item in items:
|
||||
reference = item.last_used_at or item.created_at or now
|
||||
delta_days = max((now - reference).total_seconds() / 86400, 0)
|
||||
|
||||
if item.ttl_days and delta_days > item.ttl_days:
|
||||
continue
|
||||
|
||||
score = (item.base_weight or 1.0) * _decay_factor(delta_days)
|
||||
if score <= 0.1: # 忽略低权重
|
||||
continue
|
||||
|
||||
scored.append((score, item))
|
||||
|
||||
scored.sort(key=lambda x: x[0], reverse=True)
|
||||
return [item for _, item in scored[:limit]]
|
||||
|
||||
|
||||
def _format_memories_to_prompt(memories: list[MemoryItem]) -> str:
|
||||
"""将记忆项转换为自然语言指令。"""
|
||||
lines = []
|
||||
|
||||
# 分类处理
|
||||
recent_stories = []
|
||||
favorites = []
|
||||
scary = []
|
||||
vocab = []
|
||||
|
||||
for m in memories:
|
||||
if m.type == MemoryType.RECENT_STORY:
|
||||
recent_stories.append(m)
|
||||
elif m.type == MemoryType.FAVORITE_CHARACTER:
|
||||
favorites.append(m)
|
||||
elif m.type == MemoryType.SCARY_ELEMENT:
|
||||
scary.append(m)
|
||||
elif m.type == MemoryType.VOCABULARY_GROWTH:
|
||||
vocab.append(m)
|
||||
|
||||
# 1. 喜欢的角色
|
||||
if favorites:
|
||||
names = []
|
||||
for m in favorites:
|
||||
val = m.value
|
||||
if isinstance(val, dict):
|
||||
names.append(f"{val.get('name')} ({val.get('description', '')})")
|
||||
if names:
|
||||
lines.append(f"- 孩子特别喜欢这些角色，可以让他们客串出场：{', '.join(names)}")
|
||||
|
||||
# 2. 避雷区
|
||||
if scary:
|
||||
items = []
|
||||
for m in scary:
|
||||
val = m.value
|
||||
if isinstance(val, dict):
|
||||
items.append(val.get('keyword', ''))
|
||||
elif isinstance(val, str):
|
||||
items.append(val)
|
||||
if items:
|
||||
lines.append(f"- 【注意禁止】不要出现以下让孩子害怕的元素：{', '.join(items)}")
|
||||
|
||||
# 3. 近期故事 (取最近 2 个)
|
||||
if recent_stories:
|
||||
lines.append("- 近期经历（可作为彩蛋提及）：")
|
||||
for m in recent_stories[:2]:
|
||||
val = m.value
|
||||
if isinstance(val, dict):
|
||||
title = val.get('title', '未知故事')
|
||||
lines.append(f" * 之前读过《{title}》")
|
||||
|
||||
# 4. 词汇积累
|
||||
if vocab:
|
||||
words = []
|
||||
for m in vocab:
|
||||
val = m.value
|
||||
if isinstance(val, dict):
|
||||
words.append(val.get('word'))
|
||||
if words:
|
||||
lines.append(f"- 已掌握词汇（可适当复现以巩固）：{', '.join([w for w in words if w])}")
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
async def prune_expired_memories(db: AsyncSession) -> int:
|
||||
"""清理过期的记忆项。
|
||||
|
||||
Returns:
|
||||
删除的记录数量
|
||||
"""
|
||||
from sqlalchemy import delete
|
||||
|
||||
now = datetime.now(timezone.utc)
|
||||
|
||||
# 查找所有设置了 TTL 的项目
|
||||
stmt = select(MemoryItem).where(MemoryItem.ttl_days.is_not(None))
|
||||
result = await db.execute(stmt)
|
||||
candidates = result.scalars().all()
|
||||
|
||||
to_delete_ids = []
|
||||
for item in candidates:
|
||||
if not item.ttl_days:
|
||||
continue
|
||||
|
||||
reference = item.last_used_at or item.created_at or now
|
||||
delta_days = (now - reference).total_seconds() / 86400
|
||||
|
||||
if delta_days > item.ttl_days:
|
||||
to_delete_ids.append(item.id)
|
||||
|
||||
if not to_delete_ids:
|
||||
return 0
|
||||
|
||||
delete_stmt = delete(MemoryItem).where(MemoryItem.id.in_(to_delete_ids))
|
||||
await db.execute(delete_stmt)
|
||||
await db.commit()
|
||||
|
||||
logger.info("memory_pruned", count=len(to_delete_ids))
|
||||
return len(to_delete_ids)
|
||||
|
||||
|
||||
async def create_memory(
|
||||
db: AsyncSession,
|
||||
profile_id: str,
|
||||
memory_type: str,
|
||||
value: dict,
|
||||
universe_id: str | None = None,
|
||||
weight: float | None = None,
|
||||
ttl_days: int | None = None,
|
||||
) -> MemoryItem:
|
||||
"""创建新的记忆项。
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
profile_id: 孩子档案 ID
|
||||
memory_type: 记忆类型 (使用 MemoryType 常量)
|
||||
value: 记忆内容 (JSON 格式)
|
||||
universe_id: 可选，关联的故事宇宙 ID
|
||||
weight: 可选，权重 (默认使用类型配置)
|
||||
ttl_days: 可选，过期天数 (默认使用类型配置)
|
||||
|
||||
Returns:
|
||||
创建的 MemoryItem
|
||||
"""
|
||||
memory = MemoryItem(
|
||||
child_profile_id=profile_id,
|
||||
universe_id=universe_id,
|
||||
type=memory_type,
|
||||
value=value,
|
||||
base_weight=weight or MemoryType.get_default_weight(memory_type),
|
||||
ttl_days=ttl_days if ttl_days is not None else MemoryType.get_default_ttl(memory_type),
|
||||
)
|
||||
db.add(memory)
|
||||
await db.commit()
|
||||
await db.refresh(memory)
|
||||
|
||||
logger.info(
|
||||
"memory_created",
|
||||
memory_id=memory.id,
|
||||
profile_id=profile_id,
|
||||
type=memory_type,
|
||||
)
|
||||
return memory
|
||||
|
||||
|
||||
async def update_memory_usage(db: AsyncSession, memory_id: str) -> None:
|
||||
"""更新记忆的最后使用时间。
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
memory_id: 记忆项 ID
|
||||
"""
|
||||
result = await db.execute(select(MemoryItem).where(MemoryItem.id == memory_id))
|
||||
memory = result.scalar_one_or_none()
|
||||
|
||||
if memory:
|
||||
memory.last_used_at = datetime.now(timezone.utc)
|
||||
await db.commit()
|
||||
logger.debug("memory_usage_updated", memory_id=memory_id)
|
||||
|
||||
|
||||
async def get_profile_memories(
|
||||
db: AsyncSession,
|
||||
profile_id: str,
|
||||
memory_type: str | None = None,
|
||||
universe_id: str | None = None,
|
||||
limit: int = 50,
|
||||
) -> list[MemoryItem]:
|
||||
"""获取档案的记忆列表。
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
profile_id: 孩子档案 ID
|
||||
memory_type: 可选，按类型筛选
|
||||
universe_id: 可选，按宇宙筛选
|
||||
limit: 返回数量限制
|
||||
|
||||
Returns:
|
||||
MemoryItem 列表
|
||||
"""
|
||||
query = select(MemoryItem).where(MemoryItem.child_profile_id == profile_id)
|
||||
|
||||
if memory_type:
|
||||
query = query.where(MemoryItem.type == memory_type)
|
||||
|
||||
if universe_id:
|
||||
query = query.where(
|
||||
(MemoryItem.universe_id == universe_id) | (MemoryItem.universe_id.is_(None))
|
||||
)
|
||||
|
||||
query = query.order_by(MemoryItem.created_at.desc()).limit(limit)
|
||||
|
||||
result = await db.execute(query)
|
||||
return list(result.scalars().all())
|
||||
|
||||
|
||||
async def create_story_memory(
|
||||
db: AsyncSession,
|
||||
profile_id: str,
|
||||
story_id: int,
|
||||
title: str,
|
||||
summary: str | None = None,
|
||||
keywords: list[str] | None = None,
|
||||
universe_id: str | None = None,
|
||||
) -> MemoryItem:
|
||||
"""为故事创建记忆项。
|
||||
|
||||
这是一个便捷函数，专门用于在故事阅读后创建 recent_story 类型的记忆。
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
profile_id: 孩子档案 ID
|
||||
story_id: 故事 ID
|
||||
title: 故事标题
|
||||
summary: 故事梗概
|
||||
keywords: 关键词列表
|
||||
universe_id: 可选，关联的故事宇宙 ID
|
||||
|
||||
Returns:
|
||||
创建的 MemoryItem
|
||||
"""
|
||||
value = {
|
||||
"story_id": story_id,
|
||||
"title": title,
|
||||
"summary": summary or "",
|
||||
"keywords": keywords or [],
|
||||
}
|
||||
|
||||
return await create_memory(
|
||||
db=db,
|
||||
profile_id=profile_id,
|
||||
memory_type=MemoryType.RECENT_STORY,
|
||||
value=value,
|
||||
universe_id=universe_id,
|
||||
)
|
||||
|
||||
|
||||
async def create_character_memory(
|
||||
db: AsyncSession,
|
||||
profile_id: str,
|
||||
name: str,
|
||||
description: str | None = None,
|
||||
source_story_id: int | None = None,
|
||||
affinity_score: float = 1.0,
|
||||
universe_id: str | None = None,
|
||||
) -> MemoryItem:
|
||||
"""为喜欢的角色创建记忆项。
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
profile_id: 孩子档案 ID
|
||||
name: 角色名称
|
||||
description: 角色描述
|
||||
source_story_id: 来源故事 ID
|
||||
affinity_score: 喜爱程度 (0.0-1.0)
|
||||
universe_id: 可选，关联的故事宇宙 ID
|
||||
|
||||
Returns:
|
||||
创建的 MemoryItem
|
||||
"""
|
||||
value = {
|
||||
"name": name,
|
||||
"description": description or "",
|
||||
"source_story_id": source_story_id,
|
||||
"affinity_score": min(1.0, max(0.0, affinity_score)),
|
||||
}
|
||||
|
||||
return await create_memory(
|
||||
db=db,
|
||||
profile_id=profile_id,
|
||||
memory_type=MemoryType.FAVORITE_CHARACTER,
|
||||
value=value,
|
||||
universe_id=universe_id,
|
||||
)
|
||||
|
||||
|
||||
async def create_scary_element_memory(
|
||||
db: AsyncSession,
|
||||
profile_id: str,
|
||||
keyword: str,
|
||||
category: str = "other",
|
||||
source_story_id: int | None = None,
|
||||
) -> MemoryItem:
|
||||
"""为回避元素创建记忆项。
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
profile_id: 孩子档案 ID
|
||||
keyword: 回避的关键词
|
||||
category: 分类 (creature/scene/action/other)
|
||||
source_story_id: 来源故事 ID
|
||||
|
||||
Returns:
|
||||
创建的 MemoryItem
|
||||
"""
|
||||
value = {
|
||||
"keyword": keyword,
|
||||
"category": category,
|
||||
"source_story_id": source_story_id,
|
||||
}
|
||||
|
||||
return await create_memory(
|
||||
db=db,
|
||||
profile_id=profile_id,
|
||||
memory_type=MemoryType.SCARY_ELEMENT,
|
||||
value=value,
|
||||
)
|
||||
|
||||
"""Memory service handles memory retrieval, scoring, and prompt injection."""
|
||||
|
||||
from datetime import datetime, timezone
|
||||
|
||||
from sqlalchemy import select
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.db.models import ChildProfile, MemoryItem, StoryUniverse
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
|
||||
class MemoryType:
|
||||
"""记忆类型常量及配置。"""
|
||||
|
||||
# 基础类型
|
||||
RECENT_STORY = "recent_story"
|
||||
FAVORITE_CHARACTER = "favorite_character"
|
||||
SCARY_ELEMENT = "scary_element"
|
||||
VOCABULARY_GROWTH = "vocabulary_growth"
|
||||
EMOTIONAL_HIGHLIGHT = "emotional_highlight"
|
||||
|
||||
# Phase 1 新增类型
|
||||
READING_PREFERENCE = "reading_preference" # 阅读偏好
|
||||
MILESTONE = "milestone" # 里程碑事件
|
||||
SKILL_MASTERED = "skill_mastered" # 掌握的技能
|
||||
|
||||
# 类型配置: (默认权重, 默认TTL天数, 描述)
|
||||
CONFIG = {
|
||||
RECENT_STORY: (1.0, 30, "最近阅读的故事"),
|
||||
FAVORITE_CHARACTER: (1.5, None, "喜欢的角色"), # None = 永久
|
||||
SCARY_ELEMENT: (2.0, None, "回避的元素"), # 高权重，永久有效
|
||||
VOCABULARY_GROWTH: (0.8, 90, "词汇积累"),
|
||||
EMOTIONAL_HIGHLIGHT: (1.2, 60, "情感高光"),
|
||||
READING_PREFERENCE: (1.0, None, "阅读偏好"),
|
||||
MILESTONE: (1.5, None, "里程碑事件"),
|
||||
SKILL_MASTERED: (1.0, 180, "掌握的技能"),
|
||||
}
|
||||
|
||||
@classmethod
|
||||
def get_default_weight(cls, memory_type: str) -> float:
|
||||
"""获取类型的默认权重。"""
|
||||
config = cls.CONFIG.get(memory_type)
|
||||
return config[0] if config else 1.0
|
||||
|
||||
@classmethod
|
||||
def get_default_ttl(cls, memory_type: str) -> int | None:
|
||||
"""获取类型的默认 TTL 天数。"""
|
||||
config = cls.CONFIG.get(memory_type)
|
||||
return config[1] if config else None
|
||||
|
||||
|
||||
def _decay_factor(days: float) -> float:
|
||||
"""计算时间衰减因子。"""
|
||||
if days <= 7:
|
||||
return 1.0
|
||||
if days <= 30:
|
||||
return 0.7
|
||||
if days <= 90:
|
||||
return 0.4
|
||||
return 0.2
|
||||
|
||||
|
||||
async def build_enhanced_memory_context(
|
||||
profile_id: str | None,
|
||||
universe_id: str | None,
|
||||
db: AsyncSession,
|
||||
) -> str | None:
|
||||
"""构建增强版记忆上下文（自然语言 Prompt）。"""
|
||||
if not profile_id and not universe_id:
|
||||
return None
|
||||
|
||||
context_parts: list[str] = []
|
||||
|
||||
# 1. 基础档案 (Identity Layer)
|
||||
if profile_id:
|
||||
profile = await db.scalar(select(ChildProfile).where(ChildProfile.id == profile_id))
|
||||
if profile:
|
||||
context_parts.append(f"【目标读者】\n姓名：{profile.name}")
|
||||
if profile.age:
|
||||
context_parts.append(f"年龄：{profile.age}岁")
|
||||
if profile.interests:
|
||||
context_parts.append(f"兴趣爱好：{'、'.join(profile.interests)}")
|
||||
if profile.growth_themes:
|
||||
context_parts.append(f"当前成长关注点：{'、'.join(profile.growth_themes)}")
|
||||
context_parts.append("") # 空行
|
||||
|
||||
# 2. 故事宇宙 (Universe Layer)
|
||||
if universe_id:
|
||||
universe = await db.scalar(select(StoryUniverse).where(StoryUniverse.id == universe_id))
|
||||
if universe:
|
||||
context_parts.append("【故事宇宙设定】")
|
||||
context_parts.append(f"世界观：{universe.name}")
|
||||
|
||||
# 主角
|
||||
protagonist = universe.protagonist or {}
|
||||
p_desc = f"{protagonist.get('name', '主角')} ({protagonist.get('personality', '')})"
|
||||
context_parts.append(f"主角设定：{p_desc}")
|
||||
|
||||
# 常驻角色
|
||||
if universe.recurring_characters:
|
||||
chars = [f"{c.get('name')} ({c.get('type')})" for c in universe.recurring_characters if isinstance(c, dict)]
|
||||
context_parts.append(f"已知伙伴：{'、'.join(chars)}")
|
||||
|
||||
# 成就
|
||||
if universe.achievements:
|
||||
badges = [str(a.get('type')) for a in universe.achievements if isinstance(a, dict)]
|
||||
if badges:
|
||||
context_parts.append(f"已获荣誉：{'、'.join(badges[:5])}")
|
||||
|
||||
context_parts.append("")
|
||||
|
||||
# 3. 动态记忆 (Working Memory)
|
||||
if profile_id:
|
||||
memories = await _fetch_scored_memories(profile_id, universe_id, db)
|
||||
if memories:
|
||||
memory_text = _format_memories_to_prompt(memories)
|
||||
if memory_text:
|
||||
context_parts.append("【关键记忆回忆】(请在故事中自然地融入或致敬以下元素)")
|
||||
context_parts.append(memory_text)
|
||||
|
||||
return "\n".join(context_parts)
|
||||
|
||||
|
||||
async def _fetch_scored_memories(
|
||||
profile_id: str,
|
||||
universe_id: str | None,
|
||||
db: AsyncSession,
|
||||
limit: int = 8
|
||||
) -> list[MemoryItem]:
|
||||
"""获取并评分记忆项，返回 Top N。"""
|
||||
query = select(MemoryItem).where(MemoryItem.child_profile_id == profile_id)
|
||||
if universe_id:
|
||||
query = query.where(
|
||||
(MemoryItem.universe_id == universe_id) | (MemoryItem.universe_id.is_(None))
|
||||
)
|
||||
# 取最近 50 条进行评分
|
||||
query = query.order_by(MemoryItem.last_used_at.desc(), MemoryItem.created_at.desc()).limit(50)
|
||||
|
||||
result = await db.execute(query)
|
||||
items = result.scalars().all()
|
||||
|
||||
scored: list[tuple[float, MemoryItem]] = []
|
||||
now = datetime.now(timezone.utc)
|
||||
|
||||
for item in items:
|
||||
reference = item.last_used_at or item.created_at or now
|
||||
delta_days = max((now - reference).total_seconds() / 86400, 0)
|
||||
|
||||
if item.ttl_days and delta_days > item.ttl_days:
|
||||
continue
|
||||
|
||||
score = (item.base_weight or 1.0) * _decay_factor(delta_days)
|
||||
if score <= 0.1: # 忽略低权重
|
||||
continue
|
||||
|
||||
scored.append((score, item))
|
||||
|
||||
scored.sort(key=lambda x: x[0], reverse=True)
|
||||
return [item for _, item in scored[:limit]]
|
||||
|
||||
|
||||
def _format_memories_to_prompt(memories: list[MemoryItem]) -> str:
|
||||
"""将记忆项转换为自然语言指令。"""
|
||||
lines = []
|
||||
|
||||
# 分类处理
|
||||
recent_stories = []
|
||||
favorites = []
|
||||
scary = []
|
||||
vocab = []
|
||||
|
||||
for m in memories:
|
||||
if m.type == MemoryType.RECENT_STORY:
|
||||
recent_stories.append(m)
|
||||
elif m.type == MemoryType.FAVORITE_CHARACTER:
|
||||
favorites.append(m)
|
||||
elif m.type == MemoryType.SCARY_ELEMENT:
|
||||
scary.append(m)
|
||||
elif m.type == MemoryType.VOCABULARY_GROWTH:
|
||||
vocab.append(m)
|
||||
|
||||
# 1. 喜欢的角色
|
||||
if favorites:
|
||||
names = []
|
||||
for m in favorites:
|
||||
val = m.value
|
||||
if isinstance(val, dict):
|
||||
names.append(f"{val.get('name')} ({val.get('description', '')})")
|
||||
if names:
|
||||
lines.append(f"- 孩子特别喜欢这些角色，可以让他们客串出场：{', '.join(names)}")
|
||||
|
||||
# 2. 避雷区
|
||||
if scary:
|
||||
items = []
|
||||
for m in scary:
|
||||
val = m.value
|
||||
if isinstance(val, dict):
|
||||
items.append(val.get('keyword', ''))
|
||||
elif isinstance(val, str):
|
||||
items.append(val)
|
||||
if items:
|
||||
lines.append(f"- 【注意禁止】不要出现以下让孩子害怕的元素：{', '.join(items)}")
|
||||
|
||||
# 3. 近期故事 (取最近 2 个)
|
||||
if recent_stories:
|
||||
lines.append("- 近期经历（可作为彩蛋提及）：")
|
||||
for m in recent_stories[:2]:
|
||||
val = m.value
|
||||
if isinstance(val, dict):
|
||||
title = val.get('title', '未知故事')
|
||||
lines.append(f" * 之前读过《{title}》")
|
||||
|
||||
# 4. 词汇积累
|
||||
if vocab:
|
||||
words = []
|
||||
for m in vocab:
|
||||
val = m.value
|
||||
if isinstance(val, dict):
|
||||
words.append(val.get('word'))
|
||||
if words:
|
||||
lines.append(f"- 已掌握词汇（可适当复现以巩固）：{', '.join([w for w in words if w])}")
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
async def prune_expired_memories(db: AsyncSession) -> int:
|
||||
"""清理过期的记忆项。
|
||||
|
||||
Returns:
|
||||
删除的记录数量
|
||||
"""
|
||||
from sqlalchemy import delete
|
||||
|
||||
now = datetime.now(timezone.utc)
|
||||
|
||||
# 查找所有设置了 TTL 的项目
|
||||
stmt = select(MemoryItem).where(MemoryItem.ttl_days.is_not(None))
|
||||
result = await db.execute(stmt)
|
||||
candidates = result.scalars().all()
|
||||
|
||||
to_delete_ids = []
|
||||
for item in candidates:
|
||||
if not item.ttl_days:
|
||||
continue
|
||||
|
||||
reference = item.last_used_at or item.created_at or now
|
||||
delta_days = (now - reference).total_seconds() / 86400
|
||||
|
||||
if delta_days > item.ttl_days:
|
||||
to_delete_ids.append(item.id)
|
||||
|
||||
if not to_delete_ids:
|
||||
return 0
|
||||
|
||||
delete_stmt = delete(MemoryItem).where(MemoryItem.id.in_(to_delete_ids))
|
||||
await db.execute(delete_stmt)
|
||||
await db.commit()
|
||||
|
||||
logger.info("memory_pruned", count=len(to_delete_ids))
|
||||
return len(to_delete_ids)
|
||||
|
||||
|
||||
async def create_memory(
|
||||
db: AsyncSession,
|
||||
profile_id: str,
|
||||
memory_type: str,
|
||||
value: dict,
|
||||
universe_id: str | None = None,
|
||||
weight: float | None = None,
|
||||
ttl_days: int | None = None,
|
||||
) -> MemoryItem:
|
||||
"""创建新的记忆项。
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
profile_id: 孩子档案 ID
|
||||
memory_type: 记忆类型 (使用 MemoryType 常量)
|
||||
value: 记忆内容 (JSON 格式)
|
||||
universe_id: 可选，关联的故事宇宙 ID
|
||||
weight: 可选，权重 (默认使用类型配置)
|
||||
ttl_days: 可选，过期天数 (默认使用类型配置)
|
||||
|
||||
Returns:
|
||||
创建的 MemoryItem
|
||||
"""
|
||||
memory = MemoryItem(
|
||||
child_profile_id=profile_id,
|
||||
universe_id=universe_id,
|
||||
type=memory_type,
|
||||
value=value,
|
||||
base_weight=weight or MemoryType.get_default_weight(memory_type),
|
||||
ttl_days=ttl_days if ttl_days is not None else MemoryType.get_default_ttl(memory_type),
|
||||
)
|
||||
db.add(memory)
|
||||
await db.commit()
|
||||
await db.refresh(memory)
|
||||
|
||||
logger.info(
|
||||
"memory_created",
|
||||
memory_id=memory.id,
|
||||
profile_id=profile_id,
|
||||
type=memory_type,
|
||||
)
|
||||
return memory
|
||||
|
||||
|
||||
async def update_memory_usage(db: AsyncSession, memory_id: str) -> None:
|
||||
"""更新记忆的最后使用时间。
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
memory_id: 记忆项 ID
|
||||
"""
|
||||
result = await db.execute(select(MemoryItem).where(MemoryItem.id == memory_id))
|
||||
memory = result.scalar_one_or_none()
|
||||
|
||||
if memory:
|
||||
memory.last_used_at = datetime.now(timezone.utc)
|
||||
await db.commit()
|
||||
logger.debug("memory_usage_updated", memory_id=memory_id)
|
||||
|
||||
|
||||
async def get_profile_memories(
|
||||
db: AsyncSession,
|
||||
profile_id: str,
|
||||
memory_type: str | None = None,
|
||||
universe_id: str | None = None,
|
||||
limit: int = 50,
|
||||
) -> list[MemoryItem]:
|
||||
"""获取档案的记忆列表。
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
profile_id: 孩子档案 ID
|
||||
memory_type: 可选，按类型筛选
|
||||
universe_id: 可选，按宇宙筛选
|
||||
limit: 返回数量限制
|
||||
|
||||
Returns:
|
||||
MemoryItem 列表
|
||||
"""
|
||||
query = select(MemoryItem).where(MemoryItem.child_profile_id == profile_id)
|
||||
|
||||
if memory_type:
|
||||
query = query.where(MemoryItem.type == memory_type)
|
||||
|
||||
if universe_id:
|
||||
query = query.where(
|
||||
(MemoryItem.universe_id == universe_id) | (MemoryItem.universe_id.is_(None))
|
||||
)
|
||||
|
||||
query = query.order_by(MemoryItem.created_at.desc()).limit(limit)
|
||||
|
||||
result = await db.execute(query)
|
||||
return list(result.scalars().all())
|
||||
|
||||
|
||||
async def create_story_memory(
|
||||
db: AsyncSession,
|
||||
profile_id: str,
|
||||
story_id: int,
|
||||
title: str,
|
||||
summary: str | None = None,
|
||||
keywords: list[str] | None = None,
|
||||
universe_id: str | None = None,
|
||||
) -> MemoryItem:
|
||||
"""为故事创建记忆项。
|
||||
|
||||
这是一个便捷函数，专门用于在故事阅读后创建 recent_story 类型的记忆。
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
profile_id: 孩子档案 ID
|
||||
story_id: 故事 ID
|
||||
title: 故事标题
|
||||
summary: 故事梗概
|
||||
keywords: 关键词列表
|
||||
universe_id: 可选，关联的故事宇宙 ID
|
||||
|
||||
Returns:
|
||||
创建的 MemoryItem
|
||||
"""
|
||||
value = {
|
||||
"story_id": story_id,
|
||||
"title": title,
|
||||
"summary": summary or "",
|
||||
"keywords": keywords or [],
|
||||
}
|
||||
|
||||
return await create_memory(
|
||||
db=db,
|
||||
profile_id=profile_id,
|
||||
memory_type=MemoryType.RECENT_STORY,
|
||||
value=value,
|
||||
universe_id=universe_id,
|
||||
)
|
||||
|
||||
|
||||
async def create_character_memory(
|
||||
db: AsyncSession,
|
||||
profile_id: str,
|
||||
name: str,
|
||||
description: str | None = None,
|
||||
source_story_id: int | None = None,
|
||||
affinity_score: float = 1.0,
|
||||
universe_id: str | None = None,
|
||||
) -> MemoryItem:
|
||||
"""为喜欢的角色创建记忆项。
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
profile_id: 孩子档案 ID
|
||||
name: 角色名称
|
||||
description: 角色描述
|
||||
source_story_id: 来源故事 ID
|
||||
affinity_score: 喜爱程度 (0.0-1.0)
|
||||
universe_id: 可选，关联的故事宇宙 ID
|
||||
|
||||
Returns:
|
||||
创建的 MemoryItem
|
||||
"""
|
||||
value = {
|
||||
"name": name,
|
||||
"description": description or "",
|
||||
"source_story_id": source_story_id,
|
||||
"affinity_score": min(1.0, max(0.0, affinity_score)),
|
||||
}
|
||||
|
||||
return await create_memory(
|
||||
db=db,
|
||||
profile_id=profile_id,
|
||||
memory_type=MemoryType.FAVORITE_CHARACTER,
|
||||
value=value,
|
||||
universe_id=universe_id,
|
||||
)
|
||||
|
||||
|
||||
async def create_scary_element_memory(
|
||||
db: AsyncSession,
|
||||
profile_id: str,
|
||||
keyword: str,
|
||||
category: str = "other",
|
||||
source_story_id: int | None = None,
|
||||
) -> MemoryItem:
|
||||
"""为回避元素创建记忆项。
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
profile_id: 孩子档案 ID
|
||||
keyword: 回避的关键词
|
||||
category: 分类 (creature/scene/action/other)
|
||||
source_story_id: 来源故事 ID
|
||||
|
||||
Returns:
|
||||
创建的 MemoryItem
|
||||
"""
|
||||
value = {
|
||||
"keyword": keyword,
|
||||
"category": category,
|
||||
"source_story_id": source_story_id,
|
||||
}
|
||||
|
||||
return await create_memory(
|
||||
db=db,
|
||||
profile_id=profile_id,
|
||||
memory_type=MemoryType.SCARY_ELEMENT,
|
||||
value=value,
|
||||
)
|
||||
|
||||
|
||||
@@ -1,109 +1,109 @@
|
||||
"""Redis-backed cache for providers loaded from DB."""
|
||||
|
||||
import json
|
||||
from collections import defaultdict
|
||||
from typing import Literal
|
||||
|
||||
from pydantic import BaseModel
|
||||
from sqlalchemy import select
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.core.redis import get_redis
|
||||
from app.db.admin_models import Provider
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
ProviderType = Literal["text", "image", "tts", "storybook"]
|
||||
|
||||
|
||||
class CachedProvider(BaseModel):
|
||||
"""Serializable provider configuration matching DB model fields."""
|
||||
id: str
|
||||
name: str
|
||||
type: str
|
||||
adapter: str
|
||||
model: str | None = None
|
||||
api_base: str | None = None
|
||||
api_key: str | None = None
|
||||
timeout_ms: int = 60000
|
||||
max_retries: int = 1
|
||||
weight: int = 1
|
||||
priority: int = 0
|
||||
enabled: bool = True
|
||||
config_json: dict | None = None
|
||||
config_ref: str | None = None
|
||||
|
||||
|
||||
# Local memory fallback (L1 cache)
|
||||
_local_cache: dict[ProviderType, list[CachedProvider]] = defaultdict(list)
|
||||
CACHE_KEY = "dreamweaver:providers:config"
|
||||
|
||||
|
||||
async def reload_providers(db: AsyncSession) -> dict[ProviderType, list[CachedProvider]]:
|
||||
"""Reload providers from DB and update Redis cache."""
|
||||
try:
|
||||
result = await db.execute(select(Provider).where(Provider.enabled == True)) # noqa: E712
|
||||
providers = result.scalars().all()
|
||||
|
||||
# Convert to Pydantic models
|
||||
cached_list = []
|
||||
for p in providers:
|
||||
cached_list.append(CachedProvider(
|
||||
id=p.id,
|
||||
name=p.name,
|
||||
type=p.type,
|
||||
adapter=p.adapter,
|
||||
model=p.model,
|
||||
api_base=p.api_base,
|
||||
api_key=p.api_key,
|
||||
timeout_ms=p.timeout_ms,
|
||||
max_retries=p.max_retries,
|
||||
weight=p.weight,
|
||||
priority=p.priority,
|
||||
enabled=p.enabled,
|
||||
config_json=p.config_json,
|
||||
config_ref=p.config_ref
|
||||
))
|
||||
|
||||
# Group by type
|
||||
grouped: dict[str, list[CachedProvider]] = defaultdict(list)
|
||||
for cp in cached_list:
|
||||
grouped[cp.type].append(cp)
|
||||
|
||||
# Sort
|
||||
for k in grouped:
|
||||
grouped[k].sort(key=lambda x: (x.priority, x.weight), reverse=True)
|
||||
|
||||
# Update Redis
|
||||
redis = await get_redis()
|
||||
# Serialize entire dict structure
|
||||
# Pydantic -> dict -> json
|
||||
json_data = {k: [p.model_dump() for p in v] for k, v in grouped.items()}
|
||||
await redis.set(CACHE_KEY, json.dumps(json_data))
|
||||
|
||||
# Update local cache
|
||||
_local_cache.clear()
|
||||
_local_cache.update(grouped)
|
||||
return grouped
|
||||
|
||||
except Exception as e:
|
||||
logger.error("failed_to_reload_providers", error=str(e))
|
||||
raise
|
||||
|
||||
|
||||
async def get_providers(provider_type: ProviderType) -> list[CachedProvider]:
|
||||
"""Get providers from Redis (preferred) or local fallback."""
|
||||
try:
|
||||
redis = await get_redis()
|
||||
data = await redis.get(CACHE_KEY)
|
||||
if data:
|
||||
raw_dict = json.loads(data)
|
||||
if provider_type in raw_dict:
|
||||
return [CachedProvider(**item) for item in raw_dict[provider_type]]
|
||||
return []
|
||||
except Exception as e:
|
||||
logger.warning("redis_cache_read_failed", error=str(e))
|
||||
|
||||
# Fallback to local memory
|
||||
return _local_cache.get(provider_type, [])
|
||||
"""Redis-backed cache for providers loaded from DB."""
|
||||
|
||||
import json
|
||||
from collections import defaultdict
|
||||
from typing import Literal
|
||||
|
||||
from pydantic import BaseModel
|
||||
from sqlalchemy import select
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.core.redis import get_redis
|
||||
from app.db.admin_models import Provider
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
ProviderType = Literal["text", "image", "tts", "storybook"]
|
||||
|
||||
|
||||
class CachedProvider(BaseModel):
|
||||
"""Serializable provider configuration matching DB model fields."""
|
||||
id: str
|
||||
name: str
|
||||
type: str
|
||||
adapter: str
|
||||
model: str | None = None
|
||||
api_base: str | None = None
|
||||
api_key: str | None = None
|
||||
timeout_ms: int = 60000
|
||||
max_retries: int = 1
|
||||
weight: int = 1
|
||||
priority: int = 0
|
||||
enabled: bool = True
|
||||
config_json: dict | None = None
|
||||
config_ref: str | None = None
|
||||
|
||||
|
||||
# Local memory fallback (L1 cache)
|
||||
_local_cache: dict[ProviderType, list[CachedProvider]] = defaultdict(list)
|
||||
CACHE_KEY = "dreamweaver:providers:config"
|
||||
|
||||
|
||||
async def reload_providers(db: AsyncSession) -> dict[ProviderType, list[CachedProvider]]:
|
||||
"""Reload providers from DB and update Redis cache."""
|
||||
try:
|
||||
result = await db.execute(select(Provider).where(Provider.enabled == True)) # noqa: E712
|
||||
providers = result.scalars().all()
|
||||
|
||||
# Convert to Pydantic models
|
||||
cached_list = []
|
||||
for p in providers:
|
||||
cached_list.append(CachedProvider(
|
||||
id=p.id,
|
||||
name=p.name,
|
||||
type=p.type,
|
||||
adapter=p.adapter,
|
||||
model=p.model,
|
||||
api_base=p.api_base,
|
||||
api_key=p.api_key,
|
||||
timeout_ms=p.timeout_ms,
|
||||
max_retries=p.max_retries,
|
||||
weight=p.weight,
|
||||
priority=p.priority,
|
||||
enabled=p.enabled,
|
||||
config_json=p.config_json,
|
||||
config_ref=p.config_ref
|
||||
))
|
||||
|
||||
# Group by type
|
||||
grouped: dict[str, list[CachedProvider]] = defaultdict(list)
|
||||
for cp in cached_list:
|
||||
grouped[cp.type].append(cp)
|
||||
|
||||
# Sort
|
||||
for k in grouped:
|
||||
grouped[k].sort(key=lambda x: (x.priority, x.weight), reverse=True)
|
||||
|
||||
# Update Redis
|
||||
redis = await get_redis()
|
||||
# Serialize entire dict structure
|
||||
# Pydantic -> dict -> json
|
||||
json_data = {k: [p.model_dump() for p in v] for k, v in grouped.items()}
|
||||
await redis.set(CACHE_KEY, json.dumps(json_data))
|
||||
|
||||
# Update local cache
|
||||
_local_cache.clear()
|
||||
_local_cache.update(grouped)
|
||||
return grouped
|
||||
|
||||
except Exception as e:
|
||||
logger.error("failed_to_reload_providers", error=str(e))
|
||||
raise
|
||||
|
||||
|
||||
async def get_providers(provider_type: ProviderType) -> list[CachedProvider]:
|
||||
"""Get providers from Redis (preferred) or local fallback."""
|
||||
try:
|
||||
redis = await get_redis()
|
||||
data = await redis.get(CACHE_KEY)
|
||||
if data:
|
||||
raw_dict = json.loads(data)
|
||||
if provider_type in raw_dict:
|
||||
return [CachedProvider(**item) for item in raw_dict[provider_type]]
|
||||
return []
|
||||
except Exception as e:
|
||||
logger.warning("redis_cache_read_failed", error=str(e))
|
||||
|
||||
# Fallback to local memory
|
||||
return _local_cache.get(provider_type, [])
|
||||
|
||||
@@ -1,248 +1,248 @@
|
||||
"""供应商指标收集和健康检查服务。"""
|
||||
|
||||
from datetime import datetime, timedelta
|
||||
from decimal import Decimal
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
from sqlalchemy import func, select
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.db.admin_models import ProviderHealth, ProviderMetrics
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from app.services.adapters.base import BaseAdapter
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
# 熔断阈值：连续失败次数
|
||||
CIRCUIT_BREAKER_THRESHOLD = 3
|
||||
# 熔断恢复时间（秒）
|
||||
CIRCUIT_BREAKER_RECOVERY_SECONDS = 60
|
||||
|
||||
|
||||
class MetricsCollector:
|
||||
"""供应商调用指标收集器。"""
|
||||
|
||||
async def record_call(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
provider_id: str,
|
||||
success: bool,
|
||||
latency_ms: int | None = None,
|
||||
cost_usd: float | None = None,
|
||||
error_message: str | None = None,
|
||||
request_id: str | None = None,
|
||||
) -> None:
|
||||
"""记录一次 API 调用。"""
|
||||
metric = ProviderMetrics(
|
||||
provider_id=provider_id,
|
||||
success=success,
|
||||
latency_ms=latency_ms,
|
||||
cost_usd=Decimal(str(cost_usd)) if cost_usd else None,
|
||||
error_message=error_message,
|
||||
request_id=request_id,
|
||||
)
|
||||
db.add(metric)
|
||||
await db.commit()
|
||||
|
||||
logger.debug(
|
||||
"metrics_recorded",
|
||||
provider_id=provider_id,
|
||||
success=success,
|
||||
latency_ms=latency_ms,
|
||||
)
|
||||
|
||||
async def get_success_rate(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
provider_id: str,
|
||||
window_minutes: int = 60,
|
||||
) -> float:
|
||||
"""获取指定时间窗口内的成功率。"""
|
||||
since = datetime.utcnow() - timedelta(minutes=window_minutes)
|
||||
|
||||
result = await db.execute(
|
||||
select(
|
||||
func.count().filter(ProviderMetrics.success.is_(True)).label("success_count"),
|
||||
func.count().label("total_count"),
|
||||
).where(
|
||||
ProviderMetrics.provider_id == provider_id,
|
||||
ProviderMetrics.timestamp >= since,
|
||||
)
|
||||
)
|
||||
row = result.one()
|
||||
success_count, total_count = row.success_count, row.total_count
|
||||
|
||||
if total_count == 0:
|
||||
return 1.0 # 无数据时假设健康
|
||||
|
||||
return success_count / total_count
|
||||
|
||||
async def get_avg_latency(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
provider_id: str,
|
||||
window_minutes: int = 60,
|
||||
) -> float:
|
||||
"""获取指定时间窗口内的平均延迟（毫秒）。"""
|
||||
since = datetime.utcnow() - timedelta(minutes=window_minutes)
|
||||
|
||||
result = await db.execute(
|
||||
select(func.avg(ProviderMetrics.latency_ms)).where(
|
||||
ProviderMetrics.provider_id == provider_id,
|
||||
ProviderMetrics.timestamp >= since,
|
||||
ProviderMetrics.latency_ms.isnot(None),
|
||||
)
|
||||
)
|
||||
avg = result.scalar()
|
||||
return float(avg) if avg else 0.0
|
||||
|
||||
async def get_total_cost(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
provider_id: str,
|
||||
window_minutes: int = 60,
|
||||
) -> float:
|
||||
"""获取指定时间窗口内的总成本（USD）。"""
|
||||
since = datetime.utcnow() - timedelta(minutes=window_minutes)
|
||||
|
||||
result = await db.execute(
|
||||
select(func.sum(ProviderMetrics.cost_usd)).where(
|
||||
ProviderMetrics.provider_id == provider_id,
|
||||
ProviderMetrics.timestamp >= since,
|
||||
)
|
||||
)
|
||||
total = result.scalar()
|
||||
return float(total) if total else 0.0
|
||||
|
||||
|
||||
class HealthChecker:
|
||||
"""供应商健康检查器。"""
|
||||
|
||||
async def check_provider(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
provider_id: str,
|
||||
adapter: "BaseAdapter",
|
||||
) -> bool:
|
||||
"""执行健康检查并更新状态。"""
|
||||
try:
|
||||
is_healthy = await adapter.health_check()
|
||||
except Exception as e:
|
||||
logger.warning("health_check_failed", provider_id=provider_id, error=str(e))
|
||||
is_healthy = False
|
||||
|
||||
await self.update_health_status(
|
||||
db,
|
||||
provider_id,
|
||||
is_healthy,
|
||||
error=None if is_healthy else "Health check failed",
|
||||
)
|
||||
return is_healthy
|
||||
|
||||
async def update_health_status(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
provider_id: str,
|
||||
is_healthy: bool,
|
||||
error: str | None = None,
|
||||
) -> None:
|
||||
"""更新供应商健康状态（含熔断逻辑）。"""
|
||||
result = await db.execute(
|
||||
select(ProviderHealth).where(ProviderHealth.provider_id == provider_id)
|
||||
)
|
||||
health = result.scalar_one_or_none()
|
||||
|
||||
now = datetime.utcnow()
|
||||
|
||||
if health is None:
|
||||
health = ProviderHealth(
|
||||
provider_id=provider_id,
|
||||
is_healthy=is_healthy,
|
||||
last_check=now,
|
||||
consecutive_failures=0 if is_healthy else 1,
|
||||
last_error=error,
|
||||
)
|
||||
db.add(health)
|
||||
else:
|
||||
health.last_check = now
|
||||
|
||||
if is_healthy:
|
||||
health.is_healthy = True
|
||||
health.consecutive_failures = 0
|
||||
health.last_error = None
|
||||
else:
|
||||
health.consecutive_failures += 1
|
||||
health.last_error = error
|
||||
|
||||
# 熔断逻辑
|
||||
if health.consecutive_failures >= CIRCUIT_BREAKER_THRESHOLD:
|
||||
health.is_healthy = False
|
||||
logger.warning(
|
||||
"circuit_breaker_triggered",
|
||||
provider_id=provider_id,
|
||||
consecutive_failures=health.consecutive_failures,
|
||||
)
|
||||
|
||||
await db.commit()
|
||||
|
||||
async def record_call_result(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
provider_id: str,
|
||||
success: bool,
|
||||
error: str | None = None,
|
||||
) -> None:
|
||||
"""根据调用结果更新健康状态。"""
|
||||
await self.update_health_status(db, provider_id, success, error)
|
||||
|
||||
async def get_healthy_providers(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
provider_ids: list[str],
|
||||
) -> list[str]:
|
||||
"""获取健康的供应商列表。"""
|
||||
if not provider_ids:
|
||||
return []
|
||||
|
||||
# 查询所有已记录的健康状态
|
||||
result = await db.execute(
|
||||
select(ProviderHealth.provider_id, ProviderHealth.is_healthy).where(
|
||||
ProviderHealth.provider_id.in_(provider_ids),
|
||||
)
|
||||
)
|
||||
health_map = {row[0]: row[1] for row in result.all()}
|
||||
|
||||
# 未记录的供应商默认健康，已记录但不健康的排除
|
||||
return [
|
||||
pid for pid in provider_ids
|
||||
if pid not in health_map or health_map[pid]
|
||||
]
|
||||
|
||||
async def is_healthy(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
provider_id: str,
|
||||
) -> bool:
|
||||
"""检查供应商是否健康。"""
|
||||
result = await db.execute(
|
||||
select(ProviderHealth).where(ProviderHealth.provider_id == provider_id)
|
||||
)
|
||||
health = result.scalar_one_or_none()
|
||||
|
||||
if health is None:
|
||||
return True # 未记录默认健康
|
||||
|
||||
# 检查是否可以恢复
|
||||
if not health.is_healthy and health.last_check:
|
||||
recovery_time = health.last_check + timedelta(seconds=CIRCUIT_BREAKER_RECOVERY_SECONDS)
|
||||
if datetime.utcnow() >= recovery_time:
|
||||
return True # 允许重试
|
||||
|
||||
return health.is_healthy
|
||||
|
||||
|
||||
# 全局单例
|
||||
metrics_collector = MetricsCollector()
|
||||
health_checker = HealthChecker()
|
||||
"""供应商指标收集和健康检查服务。"""
|
||||
|
||||
from datetime import datetime, timedelta
|
||||
from decimal import Decimal
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
from sqlalchemy import func, select
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
|
||||
from app.core.logging import get_logger
|
||||
from app.db.admin_models import ProviderHealth, ProviderMetrics
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from app.services.adapters.base import BaseAdapter
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
# 熔断阈值：连续失败次数
|
||||
CIRCUIT_BREAKER_THRESHOLD = 3
|
||||
# 熔断恢复时间（秒）
|
||||
CIRCUIT_BREAKER_RECOVERY_SECONDS = 60
|
||||
|
||||
|
||||
class MetricsCollector:
|
||||
"""供应商调用指标收集器。"""
|
||||
|
||||
async def record_call(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
provider_id: str,
|
||||
success: bool,
|
||||
latency_ms: int | None = None,
|
||||
cost_usd: float | None = None,
|
||||
error_message: str | None = None,
|
||||
request_id: str | None = None,
|
||||
) -> None:
|
||||
"""记录一次 API 调用。"""
|
||||
metric = ProviderMetrics(
|
||||
provider_id=provider_id,
|
||||
success=success,
|
||||
latency_ms=latency_ms,
|
||||
cost_usd=Decimal(str(cost_usd)) if cost_usd else None,
|
||||
error_message=error_message,
|
||||
request_id=request_id,
|
||||
)
|
||||
db.add(metric)
|
||||
await db.commit()
|
||||
|
||||
logger.debug(
|
||||
"metrics_recorded",
|
||||
provider_id=provider_id,
|
||||
success=success,
|
||||
latency_ms=latency_ms,
|
||||
)
|
||||
|
||||
async def get_success_rate(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
provider_id: str,
|
||||
window_minutes: int = 60,
|
||||
) -> float:
|
||||
"""获取指定时间窗口内的成功率。"""
|
||||
since = datetime.utcnow() - timedelta(minutes=window_minutes)
|
||||
|
||||
result = await db.execute(
|
||||
select(
|
||||
func.count().filter(ProviderMetrics.success.is_(True)).label("success_count"),
|
||||
func.count().label("total_count"),
|
||||
).where(
|
||||
ProviderMetrics.provider_id == provider_id,
|
||||
ProviderMetrics.timestamp >= since,
|
||||
)
|
||||
)
|
||||
row = result.one()
|
||||
success_count, total_count = row.success_count, row.total_count
|
||||
|
||||
if total_count == 0:
|
||||
return 1.0 # 无数据时假设健康
|
||||
|
||||
return success_count / total_count
|
||||
|
||||
async def get_avg_latency(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
provider_id: str,
|
||||
window_minutes: int = 60,
|
||||
) -> float:
|
||||
"""获取指定时间窗口内的平均延迟（毫秒）。"""
|
||||
since = datetime.utcnow() - timedelta(minutes=window_minutes)
|
||||
|
||||
result = await db.execute(
|
||||
select(func.avg(ProviderMetrics.latency_ms)).where(
|
||||
ProviderMetrics.provider_id == provider_id,
|
||||
ProviderMetrics.timestamp >= since,
|
||||
ProviderMetrics.latency_ms.isnot(None),
|
||||
)
|
||||
)
|
||||
avg = result.scalar()
|
||||
return float(avg) if avg else 0.0
|
||||
|
||||
async def get_total_cost(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
provider_id: str,
|
||||
window_minutes: int = 60,
|
||||
) -> float:
|
||||
"""获取指定时间窗口内的总成本（USD）。"""
|
||||
since = datetime.utcnow() - timedelta(minutes=window_minutes)
|
||||
|
||||
result = await db.execute(
|
||||
select(func.sum(ProviderMetrics.cost_usd)).where(
|
||||
ProviderMetrics.provider_id == provider_id,
|
||||
ProviderMetrics.timestamp >= since,
|
||||
)
|
||||
)
|
||||
total = result.scalar()
|
||||
return float(total) if total else 0.0
|
||||
|
||||
|
||||
class HealthChecker:
|
||||
"""供应商健康检查器。"""
|
||||
|
||||
async def check_provider(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
provider_id: str,
|
||||
adapter: "BaseAdapter",
|
||||
) -> bool:
|
||||
"""执行健康检查并更新状态。"""
|
||||
try:
|
||||
is_healthy = await adapter.health_check()
|
||||
except Exception as e:
|
||||
logger.warning("health_check_failed", provider_id=provider_id, error=str(e))
|
||||
is_healthy = False
|
||||
|
||||
await self.update_health_status(
|
||||
db,
|
||||
provider_id,
|
||||
is_healthy,
|
||||
error=None if is_healthy else "Health check failed",
|
||||
)
|
||||
return is_healthy
|
||||
|
||||
async def update_health_status(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
provider_id: str,
|
||||
is_healthy: bool,
|
||||
error: str | None = None,
|
||||
) -> None:
|
||||
"""更新供应商健康状态（含熔断逻辑）。"""
|
||||
result = await db.execute(
|
||||
select(ProviderHealth).where(ProviderHealth.provider_id == provider_id)
|
||||
)
|
||||
health = result.scalar_one_or_none()
|
||||
|
||||
now = datetime.utcnow()
|
||||
|
||||
if health is None:
|
||||
health = ProviderHealth(
|
||||
provider_id=provider_id,
|
||||
is_healthy=is_healthy,
|
||||
last_check=now,
|
||||
consecutive_failures=0 if is_healthy else 1,
|
||||
last_error=error,
|
||||
)
|
||||
db.add(health)
|
||||
else:
|
||||
health.last_check = now
|
||||
|
||||
if is_healthy:
|
||||
health.is_healthy = True
|
||||
health.consecutive_failures = 0
|
||||
health.last_error = None
|
||||
else:
|
||||
health.consecutive_failures += 1
|
||||
health.last_error = error
|
||||
|
||||
# 熔断逻辑
|
||||
if health.consecutive_failures >= CIRCUIT_BREAKER_THRESHOLD:
|
||||
health.is_healthy = False
|
||||
logger.warning(
|
||||
"circuit_breaker_triggered",
|
||||
provider_id=provider_id,
|
||||
consecutive_failures=health.consecutive_failures,
|
||||
)
|
||||
|
||||
await db.commit()
|
||||
|
||||
async def record_call_result(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
provider_id: str,
|
||||
success: bool,
|
||||
error: str | None = None,
|
||||
) -> None:
|
||||
"""根据调用结果更新健康状态。"""
|
||||
await self.update_health_status(db, provider_id, success, error)
|
||||
|
||||
async def get_healthy_providers(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
provider_ids: list[str],
|
||||
) -> list[str]:
|
||||
"""获取健康的供应商列表。"""
|
||||
if not provider_ids:
|
||||
return []
|
||||
|
||||
# 查询所有已记录的健康状态
|
||||
result = await db.execute(
|
||||
select(ProviderHealth.provider_id, ProviderHealth.is_healthy).where(
|
||||
ProviderHealth.provider_id.in_(provider_ids),
|
||||
)
|
||||
)
|
||||
health_map = {row[0]: row[1] for row in result.all()}
|
||||
|
||||
# 未记录的供应商默认健康，已记录但不健康的排除
|
||||
return [
|
||||
pid for pid in provider_ids
|
||||
if pid not in health_map or health_map[pid]
|
||||
]
|
||||
|
||||
async def is_healthy(
|
||||
self,
|
||||
db: AsyncSession,
|
||||
provider_id: str,
|
||||
) -> bool:
|
||||
"""检查供应商是否健康。"""
|
||||
result = await db.execute(
|
||||
select(ProviderHealth).where(ProviderHealth.provider_id == provider_id)
|
||||
)
|
||||
health = result.scalar_one_or_none()
|
||||
|
||||
if health is None:
|
||||
return True # 未记录默认健康
|
||||
|
||||
# 检查是否可以恢复
|
||||
if not health.is_healthy and health.last_check:
|
||||
recovery_time = health.last_check + timedelta(seconds=CIRCUIT_BREAKER_RECOVERY_SECONDS)
|
||||
if datetime.utcnow() >= recovery_time:
|
||||
return True # 允许重试
|
||||
|
||||
return health.is_healthy
|
||||
|
||||
|
||||
# 全局单例
|
||||
metrics_collector = MetricsCollector()
|
||||
health_checker = HealthChecker()
|
||||
|
||||
@@ -1,207 +1,207 @@
|
||||
"""供应商密钥加密存储服务。
|
||||
|
||||
使用 Fernet 对称加密，密钥从 SECRET_KEY 派生。
|
||||
"""
|
||||
|
||||
import base64
|
||||
import hashlib
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
from cryptography.fernet import Fernet, InvalidToken
|
||||
from sqlalchemy import select
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
|
||||
from app.core.config import settings
|
||||
from app.core.logging import get_logger
|
||||
from app.db.admin_models import ProviderSecret
|
||||
|
||||
if TYPE_CHECKING:
|
||||
pass
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
|
||||
class SecretEncryptionError(Exception):
|
||||
"""密钥加密/解密错误。"""
|
||||
|
||||
pass
|
||||
|
||||
|
||||
class SecretService:
|
||||
"""供应商密钥加密存储服务。"""
|
||||
|
||||
_fernet: Fernet | None = None
|
||||
|
||||
@classmethod
|
||||
def _get_fernet(cls) -> Fernet:
|
||||
"""获取 Fernet 实例，从 SECRET_KEY 派生加密密钥。"""
|
||||
if cls._fernet is None:
|
||||
# 从 SECRET_KEY 派生 32 字节密钥
|
||||
key_bytes = hashlib.sha256(settings.secret_key.encode()).digest()
|
||||
fernet_key = base64.urlsafe_b64encode(key_bytes)
|
||||
cls._fernet = Fernet(fernet_key)
|
||||
return cls._fernet
|
||||
|
||||
@classmethod
|
||||
def encrypt(cls, plaintext: str) -> str:
|
||||
"""加密明文，返回 base64 编码的密文。
|
||||
|
||||
Args:
|
||||
plaintext: 要加密的明文
|
||||
|
||||
Returns:
|
||||
base64 编码的密文
|
||||
"""
|
||||
if not plaintext:
|
||||
return ""
|
||||
fernet = cls._get_fernet()
|
||||
encrypted = fernet.encrypt(plaintext.encode())
|
||||
return encrypted.decode()
|
||||
|
||||
@classmethod
|
||||
def decrypt(cls, ciphertext: str) -> str:
|
||||
"""解密密文，返回明文。
|
||||
|
||||
Args:
|
||||
ciphertext: base64 编码的密文
|
||||
|
||||
Returns:
|
||||
解密后的明文
|
||||
|
||||
Raises:
|
||||
SecretEncryptionError: 解密失败
|
||||
"""
|
||||
if not ciphertext:
|
||||
return ""
|
||||
try:
|
||||
fernet = cls._get_fernet()
|
||||
decrypted = fernet.decrypt(ciphertext.encode())
|
||||
return decrypted.decode()
|
||||
except InvalidToken as e:
|
||||
logger.error("secret_decrypt_failed", error=str(e))
|
||||
raise SecretEncryptionError("密钥解密失败，可能是 SECRET_KEY 已更改") from e
|
||||
|
||||
@classmethod
|
||||
async def get_secret(cls, db: AsyncSession, name: str) -> str | None:
|
||||
"""从数据库获取并解密密钥。
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
name: 密钥名称
|
||||
|
||||
Returns:
|
||||
解密后的密钥值，不存在返回 None
|
||||
"""
|
||||
result = await db.execute(select(ProviderSecret).where(ProviderSecret.name == name))
|
||||
secret = result.scalar_one_or_none()
|
||||
if secret is None:
|
||||
return None
|
||||
return cls.decrypt(secret.encrypted_value)
|
||||
|
||||
@classmethod
|
||||
async def set_secret(cls, db: AsyncSession, name: str, value: str) -> ProviderSecret:
|
||||
"""存储或更新加密密钥。
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
name: 密钥名称
|
||||
value: 密钥明文值
|
||||
|
||||
Returns:
|
||||
ProviderSecret 实例
|
||||
"""
|
||||
encrypted = cls.encrypt(value)
|
||||
|
||||
result = await db.execute(select(ProviderSecret).where(ProviderSecret.name == name))
|
||||
secret = result.scalar_one_or_none()
|
||||
|
||||
if secret is None:
|
||||
secret = ProviderSecret(name=name, encrypted_value=encrypted)
|
||||
db.add(secret)
|
||||
else:
|
||||
secret.encrypted_value = encrypted
|
||||
|
||||
await db.commit()
|
||||
await db.refresh(secret)
|
||||
logger.info("secret_stored", name=name)
|
||||
return secret
|
||||
|
||||
@classmethod
|
||||
async def delete_secret(cls, db: AsyncSession, name: str) -> bool:
|
||||
"""删除密钥。
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
name: 密钥名称
|
||||
|
||||
Returns:
|
||||
是否删除成功
|
||||
"""
|
||||
result = await db.execute(select(ProviderSecret).where(ProviderSecret.name == name))
|
||||
secret = result.scalar_one_or_none()
|
||||
if secret is None:
|
||||
return False
|
||||
|
||||
await db.delete(secret)
|
||||
await db.commit()
|
||||
logger.info("secret_deleted", name=name)
|
||||
return True
|
||||
|
||||
@classmethod
|
||||
async def list_secrets(cls, db: AsyncSession) -> list[str]:
|
||||
"""列出所有密钥名称（不返回值）。
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
|
||||
Returns:
|
||||
密钥名称列表
|
||||
"""
|
||||
result = await db.execute(select(ProviderSecret.name))
|
||||
return [row[0] for row in result.fetchall()]
|
||||
|
||||
@classmethod
|
||||
async def get_api_key(
|
||||
cls,
|
||||
db: AsyncSession,
|
||||
provider_api_key: str | None,
|
||||
config_ref: str | None,
|
||||
) -> str | None:
|
||||
"""获取 Provider 的 API Key，按优先级查找。
|
||||
|
||||
优先级:
|
||||
1. provider.api_key (数据库明文/加密)
|
||||
2. provider.config_ref 指向的 ProviderSecret
|
||||
3. 环境变量 (config_ref 作为变量名)
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
provider_api_key: Provider 表中的 api_key 字段
|
||||
config_ref: Provider 表中的 config_ref 字段
|
||||
|
||||
Returns:
|
||||
API Key 或 None
|
||||
"""
|
||||
# 1. 直接使用 provider.api_key
|
||||
if provider_api_key:
|
||||
# 尝试解密，如果失败则当作明文
|
||||
try:
|
||||
decrypted = cls.decrypt(provider_api_key)
|
||||
if decrypted:
|
||||
return decrypted
|
||||
except SecretEncryptionError:
|
||||
pass
|
||||
return provider_api_key
|
||||
|
||||
# 2. 从 ProviderSecret 表查找
|
||||
if config_ref:
|
||||
secret_value = await cls.get_secret(db, config_ref)
|
||||
if secret_value:
|
||||
return secret_value
|
||||
|
||||
# 3. 从环境变量查找
|
||||
env_value = getattr(settings, config_ref.lower(), None)
|
||||
if env_value:
|
||||
return env_value
|
||||
|
||||
return None
|
||||
"""供应商密钥加密存储服务。
|
||||
|
||||
使用 Fernet 对称加密，密钥从 SECRET_KEY 派生。
|
||||
"""
|
||||
|
||||
import base64
|
||||
import hashlib
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
from cryptography.fernet import Fernet, InvalidToken
|
||||
from sqlalchemy import select
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
|
||||
from app.core.config import settings
|
||||
from app.core.logging import get_logger
|
||||
from app.db.admin_models import ProviderSecret
|
||||
|
||||
if TYPE_CHECKING:
|
||||
pass
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
|
||||
class SecretEncryptionError(Exception):
|
||||
"""密钥加密/解密错误。"""
|
||||
|
||||
pass
|
||||
|
||||
|
||||
class SecretService:
|
||||
"""供应商密钥加密存储服务。"""
|
||||
|
||||
_fernet: Fernet | None = None
|
||||
|
||||
@classmethod
|
||||
def _get_fernet(cls) -> Fernet:
|
||||
"""获取 Fernet 实例，从 SECRET_KEY 派生加密密钥。"""
|
||||
if cls._fernet is None:
|
||||
# 从 SECRET_KEY 派生 32 字节密钥
|
||||
key_bytes = hashlib.sha256(settings.secret_key.encode()).digest()
|
||||
fernet_key = base64.urlsafe_b64encode(key_bytes)
|
||||
cls._fernet = Fernet(fernet_key)
|
||||
return cls._fernet
|
||||
|
||||
@classmethod
|
||||
def encrypt(cls, plaintext: str) -> str:
|
||||
"""加密明文，返回 base64 编码的密文。
|
||||
|
||||
Args:
|
||||
plaintext: 要加密的明文
|
||||
|
||||
Returns:
|
||||
base64 编码的密文
|
||||
"""
|
||||
if not plaintext:
|
||||
return ""
|
||||
fernet = cls._get_fernet()
|
||||
encrypted = fernet.encrypt(plaintext.encode())
|
||||
return encrypted.decode()
|
||||
|
||||
@classmethod
|
||||
def decrypt(cls, ciphertext: str) -> str:
|
||||
"""解密密文，返回明文。
|
||||
|
||||
Args:
|
||||
ciphertext: base64 编码的密文
|
||||
|
||||
Returns:
|
||||
解密后的明文
|
||||
|
||||
Raises:
|
||||
SecretEncryptionError: 解密失败
|
||||
"""
|
||||
if not ciphertext:
|
||||
return ""
|
||||
try:
|
||||
fernet = cls._get_fernet()
|
||||
decrypted = fernet.decrypt(ciphertext.encode())
|
||||
return decrypted.decode()
|
||||
except InvalidToken as e:
|
||||
logger.error("secret_decrypt_failed", error=str(e))
|
||||
raise SecretEncryptionError("密钥解密失败，可能是 SECRET_KEY 已更改") from e
|
||||
|
||||
@classmethod
|
||||
async def get_secret(cls, db: AsyncSession, name: str) -> str | None:
|
||||
"""从数据库获取并解密密钥。
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
name: 密钥名称
|
||||
|
||||
Returns:
|
||||
解密后的密钥值，不存在返回 None
|
||||
"""
|
||||
result = await db.execute(select(ProviderSecret).where(ProviderSecret.name == name))
|
||||
secret = result.scalar_one_or_none()
|
||||
if secret is None:
|
||||
return None
|
||||
return cls.decrypt(secret.encrypted_value)
|
||||
|
||||
@classmethod
|
||||
async def set_secret(cls, db: AsyncSession, name: str, value: str) -> ProviderSecret:
|
||||
"""存储或更新加密密钥。
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
name: 密钥名称
|
||||
value: 密钥明文值
|
||||
|
||||
Returns:
|
||||
ProviderSecret 实例
|
||||
"""
|
||||
encrypted = cls.encrypt(value)
|
||||
|
||||
result = await db.execute(select(ProviderSecret).where(ProviderSecret.name == name))
|
||||
secret = result.scalar_one_or_none()
|
||||
|
||||
if secret is None:
|
||||
secret = ProviderSecret(name=name, encrypted_value=encrypted)
|
||||
db.add(secret)
|
||||
else:
|
||||
secret.encrypted_value = encrypted
|
||||
|
||||
await db.commit()
|
||||
await db.refresh(secret)
|
||||
logger.info("secret_stored", name=name)
|
||||
return secret
|
||||
|
||||
@classmethod
|
||||
async def delete_secret(cls, db: AsyncSession, name: str) -> bool:
|
||||
"""删除密钥。
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
name: 密钥名称
|
||||
|
||||
Returns:
|
||||
是否删除成功
|
||||
"""
|
||||
result = await db.execute(select(ProviderSecret).where(ProviderSecret.name == name))
|
||||
secret = result.scalar_one_or_none()
|
||||
if secret is None:
|
||||
return False
|
||||
|
||||
await db.delete(secret)
|
||||
await db.commit()
|
||||
logger.info("secret_deleted", name=name)
|
||||
return True
|
||||
|
||||
@classmethod
|
||||
async def list_secrets(cls, db: AsyncSession) -> list[str]:
|
||||
"""列出所有密钥名称（不返回值）。
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
|
||||
Returns:
|
||||
密钥名称列表
|
||||
"""
|
||||
result = await db.execute(select(ProviderSecret.name))
|
||||
return [row[0] for row in result.fetchall()]
|
||||
|
||||
@classmethod
|
||||
async def get_api_key(
|
||||
cls,
|
||||
db: AsyncSession,
|
||||
provider_api_key: str | None,
|
||||
config_ref: str | None,
|
||||
) -> str | None:
|
||||
"""获取 Provider 的 API Key，按优先级查找。
|
||||
|
||||
优先级:
|
||||
1. provider.api_key (数据库明文/加密)
|
||||
2. provider.config_ref 指向的 ProviderSecret
|
||||
3. 环境变量 (config_ref 作为变量名)
|
||||
|
||||
Args:
|
||||
db: 数据库会话
|
||||
provider_api_key: Provider 表中的 api_key 字段
|
||||
config_ref: Provider 表中的 config_ref 字段
|
||||
|
||||
Returns:
|
||||
API Key 或 None
|
||||
"""
|
||||
# 1. 直接使用 provider.api_key
|
||||
if provider_api_key:
|
||||
# 尝试解密，如果失败则当作明文
|
||||
try:
|
||||
decrypted = cls.decrypt(provider_api_key)
|
||||
if decrypted:
|
||||
return decrypted
|
||||
except SecretEncryptionError:
|
||||
pass
|
||||
return provider_api_key
|
||||
|
||||
# 2. 从 ProviderSecret 表查找
|
||||
if config_ref:
|
||||
secret_value = await cls.get_secret(db, config_ref)
|
||||
if secret_value:
|
||||
return secret_value
|
||||
|
||||
# 3. 从环境变量查找
|
||||
env_value = getattr(settings, config_ref.lower(), None)
|
||||
if env_value:
|
||||
return env_value
|
||||
|
||||
return None
|
||||
|
||||
@@ -1,29 +1,29 @@
|
||||
|
||||
import asyncio
|
||||
|
||||
from app.core.celery_app import celery_app
|
||||
from app.core.logging import get_logger
|
||||
from app.db.database import _get_session_factory
|
||||
from app.services.memory_service import prune_expired_memories
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
@celery_app.task
|
||||
def prune_memories_task():
|
||||
"""Daily task to prune expired memories."""
|
||||
logger.info("prune_memories_task_started")
|
||||
|
||||
async def _run():
|
||||
# Ensure engine is initialized in this process
|
||||
session_factory = _get_session_factory()
|
||||
async with session_factory() as session:
|
||||
return await prune_expired_memories(session)
|
||||
|
||||
try:
|
||||
# Create a new event loop for this task execution
|
||||
count = asyncio.run(_run())
|
||||
logger.info("prune_memories_task_completed", deleted_count=count)
|
||||
return f"Deleted {count} expired memories"
|
||||
except Exception as exc:
|
||||
logger.error("prune_memories_task_failed", error=str(exc))
|
||||
raise
|
||||
|
||||
import asyncio
|
||||
|
||||
from app.core.celery_app import celery_app
|
||||
from app.core.logging import get_logger
|
||||
from app.db.database import _get_session_factory
|
||||
from app.services.memory_service import prune_expired_memories
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
@celery_app.task
|
||||
def prune_memories_task():
|
||||
"""Daily task to prune expired memories."""
|
||||
logger.info("prune_memories_task_started")
|
||||
|
||||
async def _run():
|
||||
# Ensure engine is initialized in this process
|
||||
session_factory = _get_session_factory()
|
||||
async with session_factory() as session:
|
||||
return await prune_expired_memories(session)
|
||||
|
||||
try:
|
||||
# Create a new event loop for this task execution
|
||||
count = asyncio.run(_run())
|
||||
logger.info("prune_memories_task_completed", deleted_count=count)
|
||||
return f"Deleted {count} expired memories"
|
||||
except Exception as exc:
|
||||
logger.error("prune_memories_task_failed", error=str(exc))
|
||||
raise
|
||||
|
||||
Reference in New Issue
Block a user