95 lines
2.3 KiB
Python
95 lines
2.3 KiB
Python
"""FastAPI 网关：对外提供 /chat /health /metrics 接口。
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启动：
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uvicorn gateway.api:app --host 0.0.0.0 --port 8000
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或：
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python -m gateway.api
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依赖：fastapi, uvicorn, pydantic（见 requirements.txt）
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"""
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from __future__ import annotations
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from typing import List, Optional
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from pydantic import BaseModel, Field
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from router_system.config import load_config
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from router_system.router import Router, build_router
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# ---- 全局单例 ----
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_router: Optional[Router] = None
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def get_router() -> Router:
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global _router
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if _router is None:
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_router = build_router()
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return _router
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# ---- 请求/响应模型 ----
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class QueryRequest(BaseModel):
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query: str = Field(..., min_length=1, max_length=8000, description="用户查询")
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class QueryResponse(BaseModel):
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response: str
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domain: str
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difficulty: str
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confidence: float
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upgraded: bool
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quality_score: float
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model_used: str
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route: List[str]
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latency_ms: float
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cache_hit: bool
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cache_level: Optional[str]
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cost_est: float
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error: Optional[str] = None
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class HealthResponse(BaseModel):
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status: str
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domains: List[str]
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classifier: str
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judge: str
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fallback: str
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# ---- FastAPI 应用 ----
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try:
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from fastapi import FastAPI
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app = FastAPI(
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title="Multi-Expert Router API",
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description="多专业小模型 + 路由模型系统（MVP）",
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version="0.1.0",
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)
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@app.get("/health", response_model=HealthResponse, tags=["system"])
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async def health():
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return get_router().health()
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@app.post("/chat", response_model=QueryResponse, tags=["chat"])
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async def chat(req: QueryRequest):
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result = await get_router().route(req.query)
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return QueryResponse(**result.to_dict())
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@app.get("/metrics", tags=["system"])
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async def metrics():
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r = get_router()
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return {
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"router": r.stats.summary(),
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"cache": r.cache.stats(),
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}
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except ImportError:
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# fastapi 未安装时，提供 CLI 入口提示
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app = None
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print("[gateway] 未安装 fastapi，请执行: pip install -r requirements.txt")
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if __name__ == "__main__":
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import uvicorn
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uvicorn.run("gateway.api:app", host="0.0.0.0", port=8000, reload=False)
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