feat: 初始化零工后端代码
This commit is contained in:
Daniel
@@ -1,23 +1,33 @@
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from datetime import datetime
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from fastapi import APIRouter, Depends, HTTPException
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from fastapi import APIRouter, Depends, HTTPException, Path
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from sqlalchemy import text
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from sqlalchemy.orm import Session
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from app.core.config import get_settings
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from app.db.session import get_db
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from app.domain.schemas import (
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AIObservabilityResponse,
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BootstrapResponse,
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ExplainResponse,
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ExtractResponse,
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ExtractTextRequest,
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HealthStatus,
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IngestJobRequest,
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IngestAsyncResponse,
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IngestWorkerRequest,
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JobCard,
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ListResponse,
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MatchFeedbackRequest,
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MatchAsyncJobsRequest,
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MatchAsyncResponse,
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MatchAsyncWorkersRequest,
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MatchJobsRequest,
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MatchResponse,
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MatchWeightResponse,
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MatchWorkersRequest,
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QueueStatusResponse,
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SystemOpsResponse,
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WorkerCard,
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)
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from app.repositories.job_repository import JobRepository
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@@ -25,14 +35,23 @@ from app.repositories.worker_repository import WorkerRepository
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from app.services.card_mapper import job_to_card, worker_to_card
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from app.services.extraction_service import ExtractionService
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from app.services.ingest_service import IngestService
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from app.services.llm_client import LLMClient
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from app.services.matching_service import MatchingService
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from app.services.cache_service import get_match_cache, get_query_cache
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from app.services.runtime_state import get_ingest_queue, get_match_queue, get_traffic_guard
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from app.services.rag.lightrag_adapter import LightRAGAdapter
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router = APIRouter()
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@router.get("/health", response_model=HealthStatus)
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@router.get(
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"/health",
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response_model=HealthStatus,
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tags=["系统"],
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summary="服务健康检查",
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description="检查 API 服务、数据库与 RAG 检索组件状态。",
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)
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def health(db: Session = Depends(get_db)) -> HealthStatus:
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settings = get_settings()
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db_status = "ok"
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@@ -48,32 +67,119 @@ def health(db: Session = Depends(get_db)) -> HealthStatus:
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return HealthStatus(service="ok", database=db_status, rag=rag_status, timestamp=datetime.now().astimezone())
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@router.post("/poc/extract/job", response_model=ExtractResponse)
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@router.post(
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"/poc/extract/job",
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response_model=ExtractResponse,
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tags=["抽取"],
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summary="岗位文本抽取",
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description="将岗位自然语言文本抽取为结构化 JobCard。",
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)
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def extract_job(payload: ExtractTextRequest) -> ExtractResponse:
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return ExtractionService().extract_job(payload.text)
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@router.post("/poc/extract/worker", response_model=ExtractResponse)
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@router.post(
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"/poc/extract/worker",
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response_model=ExtractResponse,
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tags=["抽取"],
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summary="工人文本抽取",
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description="将工人自然语言文本抽取为结构化 WorkerCard。",
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)
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def extract_worker(payload: ExtractTextRequest) -> ExtractResponse:
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return ExtractionService().extract_worker(payload.text)
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@router.post("/poc/ingest/job", response_model=JobCard)
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@router.post(
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"/poc/ingest/job",
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response_model=JobCard,
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tags=["入库"],
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summary="岗位入库",
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description="写入或更新岗位卡片，并同步更新检索索引。",
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)
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def ingest_job(payload: IngestJobRequest, db: Session = Depends(get_db)) -> JobCard:
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return IngestService(db).ingest_job(payload.job)
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@router.post("/poc/ingest/worker", response_model=WorkerCard)
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@router.post(
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"/poc/ingest/worker",
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response_model=WorkerCard,
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tags=["入库"],
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summary="工人入库",
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description="写入或更新工人卡片，并同步更新检索索引。",
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)
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def ingest_worker(payload: IngestWorkerRequest, db: Session = Depends(get_db)) -> WorkerCard:
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return IngestService(db).ingest_worker(payload.worker)
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@router.post("/poc/ingest/bootstrap")
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def bootstrap(db: Session = Depends(get_db)):
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@router.post(
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"/poc/ingest/job/async",
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response_model=IngestAsyncResponse,
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tags=["入库"],
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summary="岗位异步入库",
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description="将岗位入库请求写入异步队列，快速返回任务 ID。",
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)
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def ingest_job_async(payload: IngestJobRequest) -> IngestAsyncResponse:
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settings = get_settings()
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if not settings.ingest_async_enabled:
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raise HTTPException(status_code=400, detail="异步入库未开启")
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queue = get_ingest_queue()
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try:
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task_id = queue.enqueue_job(payload.job)
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except RuntimeError as exc:
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raise HTTPException(status_code=503, detail=str(exc)) from exc
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return IngestAsyncResponse(task_id=task_id, status=queue.task_status(task_id))
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@router.post(
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"/poc/ingest/worker/async",
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response_model=IngestAsyncResponse,
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tags=["入库"],
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summary="工人异步入库",
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description="将工人入库请求写入异步队列，快速返回任务 ID。",
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)
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def ingest_worker_async(payload: IngestWorkerRequest) -> IngestAsyncResponse:
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settings = get_settings()
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if not settings.ingest_async_enabled:
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raise HTTPException(status_code=400, detail="异步入库未开启")
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queue = get_ingest_queue()
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try:
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task_id = queue.enqueue_worker(payload.worker)
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except RuntimeError as exc:
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raise HTTPException(status_code=503, detail=str(exc)) from exc
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return IngestAsyncResponse(task_id=task_id, status=queue.task_status(task_id))
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@router.get(
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"/poc/ingest/queue/{task_id}",
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response_model=IngestAsyncResponse,
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tags=["入库"],
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summary="异步入库任务状态",
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description="根据 task_id 查询异步入库任务状态。",
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)
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def ingest_task_status(task_id: str) -> IngestAsyncResponse:
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queue = get_ingest_queue()
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return IngestAsyncResponse(task_id=task_id, status=queue.task_status(task_id))
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@router.post(
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"/poc/ingest/bootstrap",
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response_model=BootstrapResponse,
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tags=["入库"],
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summary="样本数据初始化",
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description="导入内置样本数据（岗位、工人、技能、类目、区域）并构建检索数据。",
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)
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def bootstrap(db: Session = Depends(get_db)) -> BootstrapResponse:
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return IngestService(db).bootstrap()
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@router.post("/poc/match/workers", response_model=MatchResponse)
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@router.post(
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"/poc/match/workers",
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response_model=MatchResponse,
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tags=["匹配"],
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summary="岗位匹配工人",
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description="支持通过 job_id 或内联 job 进行匹配，返回 top_n 条结果。",
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responses={404: {"description": "岗位不存在"}},
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)
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def match_workers(payload: MatchWorkersRequest, db: Session = Depends(get_db)) -> MatchResponse:
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service = MatchingService(db)
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source = payload.job
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@@ -85,7 +191,14 @@ def match_workers(payload: MatchWorkersRequest, db: Session = Depends(get_db)) -
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return MatchResponse(items=service.match_workers(source, payload.top_n))
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@router.post("/poc/match/jobs", response_model=MatchResponse)
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@router.post(
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"/poc/match/jobs",
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response_model=MatchResponse,
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tags=["匹配"],
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summary="工人匹配岗位",
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description="支持通过 worker_id 或内联 worker 进行匹配，返回 top_n 条结果。",
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responses={404: {"description": "工人不存在"}},
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)
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def match_jobs(payload: MatchJobsRequest, db: Session = Depends(get_db)) -> MatchResponse:
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service = MatchingService(db)
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source = payload.worker
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@@ -97,37 +210,245 @@ def match_jobs(payload: MatchJobsRequest, db: Session = Depends(get_db)) -> Matc
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return MatchResponse(items=service.match_jobs(source, payload.top_n))
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@router.get("/poc/match/explain/{match_id}", response_model=ExplainResponse)
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def explain_match(match_id: str, db: Session = Depends(get_db)) -> ExplainResponse:
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@router.post(
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"/poc/match/workers/async",
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response_model=MatchAsyncResponse,
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tags=["匹配"],
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summary="岗位异步匹配工人",
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description="将匹配任务放入队列异步计算，适合高并发削峰。",
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)
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def match_workers_async(payload: MatchAsyncWorkersRequest) -> MatchAsyncResponse:
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settings = get_settings()
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if not settings.match_async_enabled:
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raise HTTPException(status_code=400, detail="异步匹配未开启")
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queue = get_match_queue()
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try:
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task_id = queue.enqueue_workers(payload.job_id, payload.top_n)
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except RuntimeError as exc:
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raise HTTPException(status_code=503, detail=str(exc)) from exc
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return MatchAsyncResponse(task_id=task_id, status=queue.task_status(task_id))
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@router.post(
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"/poc/match/jobs/async",
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response_model=MatchAsyncResponse,
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tags=["匹配"],
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summary="工人异步匹配岗位",
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description="将匹配任务放入队列异步计算，适合高并发削峰。",
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)
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def match_jobs_async(payload: MatchAsyncJobsRequest) -> MatchAsyncResponse:
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settings = get_settings()
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if not settings.match_async_enabled:
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raise HTTPException(status_code=400, detail="异步匹配未开启")
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queue = get_match_queue()
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try:
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task_id = queue.enqueue_jobs(payload.worker_id, payload.top_n)
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except RuntimeError as exc:
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raise HTTPException(status_code=503, detail=str(exc)) from exc
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return MatchAsyncResponse(task_id=task_id, status=queue.task_status(task_id))
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@router.get(
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"/poc/match/queue/{task_id}",
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response_model=MatchAsyncResponse,
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tags=["匹配"],
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summary="异步匹配任务状态",
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description="根据 task_id 查询异步匹配任务状态，完成后返回匹配结果。",
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)
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def match_task_status(task_id: str) -> MatchAsyncResponse:
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queue = get_match_queue()
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status = queue.task_status(task_id)
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items = queue.task_result(task_id)
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return MatchAsyncResponse(task_id=task_id, status=status, items=items)
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@router.get(
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"/poc/match/explain/{match_id}",
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response_model=ExplainResponse,
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tags=["匹配"],
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summary="匹配结果解释",
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description="根据 match_id 获取匹配明细和解释理由。",
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responses={404: {"description": "匹配记录不存在"}},
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)
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def explain_match(
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match_id: str = Path(..., description="匹配记录 ID"),
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db: Session = Depends(get_db),
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) -> ExplainResponse:
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match = MatchingService(db).explain(match_id)
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if match is None:
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raise HTTPException(status_code=404, detail="匹配记录不存在")
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return ExplainResponse(match=match)
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@router.get("/poc/jobs", response_model=ListResponse)
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@router.post(
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"/poc/match/feedback",
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response_model=MatchWeightResponse,
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tags=["匹配"],
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summary="匹配反馈学习",
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description="提交单条匹配的接受/拒绝反馈，用于在线更新排序权重。",
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responses={404: {"description": "匹配记录不存在"}},
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)
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def feedback_match(payload: MatchFeedbackRequest, db: Session = Depends(get_db)) -> MatchWeightResponse:
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service = MatchingService(db)
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weights = service.feedback(payload.match_id, payload.accepted)
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if weights is None:
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raise HTTPException(status_code=404, detail="匹配记录不存在")
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return MatchWeightResponse(weights=weights, learning_enabled=get_settings().ranking_learning_enabled)
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@router.get(
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"/poc/match/weights",
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response_model=MatchWeightResponse,
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tags=["匹配"],
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summary="当前排序权重",
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description="查看当前生效的排序权重（默认权重或学习后的权重）。",
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)
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def get_match_weights(db: Session = Depends(get_db)) -> MatchWeightResponse:
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service = MatchingService(db)
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return MatchWeightResponse(weights=service.current_weights(), learning_enabled=get_settings().ranking_learning_enabled)
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@router.get(
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"/poc/ops/ai/metrics",
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response_model=AIObservabilityResponse,
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tags=["系统"],
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summary="AI 观测指标",
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description="返回 AI 调用的限流、熔断、降级与 fallback 命中率指标。",
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)
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def ai_metrics() -> AIObservabilityResponse:
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metrics = LLMClient(get_settings()).metrics()
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return AIObservabilityResponse(metrics=metrics)
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@router.get(
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"/poc/ops/system/metrics",
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response_model=SystemOpsResponse,
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tags=["系统"],
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summary="系统运行指标",
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description="返回全局流量护栏、缓存与异步队列指标。",
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)
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def system_metrics() -> SystemOpsResponse:
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queue_stats = get_ingest_queue().stats()
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match_queue_stats = get_match_queue().stats()
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match_cache_stats = get_match_cache().stats()
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query_cache_stats = get_query_cache().stats()
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return SystemOpsResponse(
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traffic=get_traffic_guard().snapshot(),
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cache={
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"backend": match_cache_stats.get("backend", "memory"),
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"match_hit_rate": match_cache_stats.get("hit_rate", 0.0),
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"query_hit_rate": query_cache_stats.get("hit_rate", 0.0),
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"match_size": int(match_cache_stats.get("size", 0)),
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"query_size": int(query_cache_stats.get("size", 0)),
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},
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ingest_queue=QueueStatusResponse(
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queued=queue_stats["queued"],
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processed=queue_stats["processed"],
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failed=queue_stats["failed"],
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),
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match_queue=QueueStatusResponse(
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queued=match_queue_stats["queued"],
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processed=match_queue_stats["processed"],
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failed=match_queue_stats["failed"],
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),
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)
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@router.get(
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"/poc/jobs",
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response_model=ListResponse,
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tags=["查询"],
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summary="岗位列表查询",
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description="查询岗位列表，当前返回全量数据。",
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)
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def list_jobs(db: Session = Depends(get_db)) -> ListResponse:
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settings = get_settings()
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cache = get_query_cache()
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cache_key = "jobs:list"
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if settings.query_cache_enabled:
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cached = cache.get(cache_key)
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if cached is not None:
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return ListResponse(items=cached["items"], total=cached["total"])
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items = [job_to_card(item).model_dump(mode="json") for item in JobRepository(db).list()]
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return ListResponse(items=items, total=len(items))
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result = ListResponse(items=items, total=len(items))
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if settings.query_cache_enabled:
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cache.set(cache_key, result.model_dump(mode="json"))
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return result
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@router.get("/poc/workers", response_model=ListResponse)
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@router.get(
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"/poc/workers",
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response_model=ListResponse,
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tags=["查询"],
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summary="工人列表查询",
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description="查询工人列表，当前返回全量数据。",
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)
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def list_workers(db: Session = Depends(get_db)) -> ListResponse:
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settings = get_settings()
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cache = get_query_cache()
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cache_key = "workers:list"
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if settings.query_cache_enabled:
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cached = cache.get(cache_key)
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if cached is not None:
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return ListResponse(items=cached["items"], total=cached["total"])
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items = [worker_to_card(item).model_dump(mode="json") for item in WorkerRepository(db).list()]
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return ListResponse(items=items, total=len(items))
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result = ListResponse(items=items, total=len(items))
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if settings.query_cache_enabled:
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cache.set(cache_key, result.model_dump(mode="json"))
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return result
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@router.get("/poc/jobs/{job_id}", response_model=JobCard)
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def get_job(job_id: str, db: Session = Depends(get_db)) -> JobCard:
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@router.get(
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"/poc/jobs/{job_id}",
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response_model=JobCard,
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tags=["查询"],
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summary="岗位详情查询",
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description="根据岗位 ID 查询单个岗位详情。",
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responses={404: {"description": "岗位不存在"}},
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)
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def get_job(
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job_id: str = Path(..., description="岗位 ID"),
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db: Session = Depends(get_db),
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) -> JobCard:
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settings = get_settings()
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cache = get_query_cache()
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cache_key = f"jobs:detail:{job_id}"
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if settings.query_cache_enabled:
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cached = cache.get(cache_key)
|
||||
if cached is not None:
|
||||
return JobCard(**cached)
|
||||
item = JobRepository(db).get(job_id)
|
||||
if item is None:
|
||||
raise HTTPException(status_code=404, detail="岗位不存在")
|
||||
return job_to_card(item)
|
||||
result = job_to_card(item)
|
||||
if settings.query_cache_enabled:
|
||||
cache.set(cache_key, result.model_dump(mode="json"))
|
||||
return result
|
||||
|
||||
|
||||
@router.get("/poc/workers/{worker_id}", response_model=WorkerCard)
|
||||
def get_worker(worker_id: str, db: Session = Depends(get_db)) -> WorkerCard:
|
||||
@router.get(
|
||||
"/poc/workers/{worker_id}",
|
||||
response_model=WorkerCard,
|
||||
tags=["查询"],
|
||||
summary="工人详情查询",
|
||||
description="根据工人 ID 查询单个工人详情。",
|
||||
responses={404: {"description": "工人不存在"}},
|
||||
)
|
||||
def get_worker(
|
||||
worker_id: str = Path(..., description="工人 ID"),
|
||||
db: Session = Depends(get_db),
|
||||
) -> WorkerCard:
|
||||
settings = get_settings()
|
||||
cache = get_query_cache()
|
||||
cache_key = f"workers:detail:{worker_id}"
|
||||
if settings.query_cache_enabled:
|
||||
cached = cache.get(cache_key)
|
||||
if cached is not None:
|
||||
return WorkerCard(**cached)
|
||||
item = WorkerRepository(db).get(worker_id)
|
||||
if item is None:
|
||||
raise HTTPException(status_code=404, detail="工人不存在")
|
||||
return worker_to_card(item)
|
||||
result = worker_to_card(item)
|
||||
if settings.query_cache_enabled:
|
||||
cache.set(cache_key, result.model_dump(mode="json"))
|
||||
return result
|
||||
|
||||
@@ -17,18 +17,39 @@ class Settings(BaseSettings):
|
||||
app_host: str = "0.0.0.0"
|
||||
app_port: int = 8000
|
||||
log_level: str = "INFO"
|
||||
app_rate_limit_per_minute: int = 1200
|
||||
app_circuit_breaker_error_rate: float = 0.5
|
||||
app_circuit_breaker_min_requests: int = 50
|
||||
app_circuit_breaker_window_seconds: int = 60
|
||||
app_circuit_breaker_cooldown_seconds: int = 30
|
||||
alert_webhook_url: str | None = None
|
||||
|
||||
database_url: str = "postgresql+psycopg://gig:gig@postgres:5432/gig_poc"
|
||||
database_pool_size: int = 20
|
||||
database_max_overflow: int = 30
|
||||
database_pool_timeout: int = 30
|
||||
qdrant_url: str = "http://qdrant:6333"
|
||||
qdrant_collection: str = "gig_poc_entities"
|
||||
vector_size: int = 64
|
||||
|
||||
llm_enabled: bool = False
|
||||
llm_base_url: str | None = None
|
||||
llm_fallback_base_urls: list[str] = Field(default_factory=list)
|
||||
llm_api_key: str | None = None
|
||||
llm_model: str = "gpt-5.4"
|
||||
extraction_llm_max_retries: int = 2
|
||||
|
||||
embedding_backend: str = "hash" # hash | openai_compatible
|
||||
embedding_enabled: bool = False
|
||||
embedding_base_url: str | None = None
|
||||
embedding_fallback_base_urls: list[str] = Field(default_factory=list)
|
||||
embedding_api_key: str | None = None
|
||||
embedding_model: str = "text-embedding-3-small"
|
||||
embedding_vector_size: int = 1536
|
||||
ai_request_timeout_seconds: float = 30.0
|
||||
ai_rate_limit_per_minute: int = 120
|
||||
ai_circuit_breaker_fail_threshold: int = 5
|
||||
ai_circuit_breaker_cooldown_seconds: int = 30
|
||||
|
||||
bootstrap_jobs: int = 100
|
||||
bootstrap_workers: int = 300
|
||||
@@ -38,12 +59,27 @@ class Settings(BaseSettings):
|
||||
prompt_dir: Path = Field(default=ROOT_DIR / "packages" / "prompts")
|
||||
sample_data_dir: Path = Field(default=ROOT_DIR / "packages" / "sample-data")
|
||||
shared_types_dir: Path = Field(default=ROOT_DIR / "packages" / "shared-types")
|
||||
data_dir: Path = Field(default=ROOT_DIR / "data")
|
||||
match_weights_path: Path = Field(default=ROOT_DIR / "data" / "match_weights.json")
|
||||
|
||||
score_skill_weight: float = 0.35
|
||||
score_region_weight: float = 0.20
|
||||
score_time_weight: float = 0.15
|
||||
score_experience_weight: float = 0.15
|
||||
score_reliability_weight: float = 0.15
|
||||
ranking_learning_enabled: bool = True
|
||||
ranking_learning_rate: float = 0.08
|
||||
cache_backend: str = "memory" # memory | redis
|
||||
redis_url: str = "redis://redis:6379/0"
|
||||
redis_prefix: str = "gig_poc"
|
||||
match_cache_enabled: bool = True
|
||||
match_cache_ttl_seconds: int = 30
|
||||
query_cache_enabled: bool = True
|
||||
query_cache_ttl_seconds: int = 20
|
||||
ingest_async_enabled: bool = True
|
||||
ingest_queue_max_size: int = 10000
|
||||
match_async_enabled: bool = True
|
||||
match_queue_max_size: int = 10000
|
||||
|
||||
|
||||
@lru_cache
|
||||
|
||||
@@ -7,7 +7,14 @@ from app.core.config import get_settings
|
||||
|
||||
|
||||
settings = get_settings()
|
||||
engine = create_engine(settings.database_url, future=True, pool_pre_ping=True)
|
||||
engine = create_engine(
|
||||
settings.database_url,
|
||||
future=True,
|
||||
pool_pre_ping=True,
|
||||
pool_size=settings.database_pool_size,
|
||||
max_overflow=settings.database_max_overflow,
|
||||
pool_timeout=settings.database_pool_timeout,
|
||||
)
|
||||
SessionLocal = sessionmaker(bind=engine, autoflush=False, autocommit=False, future=True)
|
||||
|
||||
|
||||
|
||||
@@ -3,7 +3,7 @@ from __future__ import annotations
|
||||
from datetime import datetime
|
||||
from enum import Enum
|
||||
|
||||
from pydantic import BaseModel, Field, field_validator, model_validator
|
||||
from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
|
||||
|
||||
|
||||
class SalaryType(str, Enum):
|
||||
@@ -19,82 +19,89 @@ class SourceType(str, Enum):
|
||||
|
||||
|
||||
class Salary(BaseModel):
|
||||
type: SalaryType = SalaryType.daily
|
||||
amount: float = 0
|
||||
currency: str = "CNY"
|
||||
type: SalaryType = Field(default=SalaryType.daily, description="薪资类型：daily/hourly/monthly/task")
|
||||
amount: float = Field(default=0, description="薪资金额")
|
||||
currency: str = Field(default="CNY", description="货币类型，默认 CNY")
|
||||
|
||||
|
||||
class SkillScore(BaseModel):
|
||||
name: str
|
||||
score: float = Field(ge=0, le=1)
|
||||
name: str = Field(description="技能名称")
|
||||
score: float = Field(ge=0, le=1, description="技能熟练度，范围 0~1")
|
||||
|
||||
|
||||
class JobCard(BaseModel):
|
||||
job_id: str
|
||||
title: str
|
||||
category: str
|
||||
description: str
|
||||
skills: list[str] = Field(default_factory=list)
|
||||
city: str
|
||||
region: str
|
||||
location_detail: str
|
||||
start_time: datetime
|
||||
duration_hours: float = Field(gt=0)
|
||||
headcount: int = Field(gt=0)
|
||||
salary: Salary
|
||||
work_mode: str
|
||||
tags: list[str] = Field(default_factory=list)
|
||||
confidence: float = Field(ge=0, le=1)
|
||||
job_id: str = Field(description="岗位唯一 ID")
|
||||
title: str = Field(description="岗位标题")
|
||||
category: str = Field(description="岗位类别")
|
||||
description: str = Field(description="岗位描述")
|
||||
skills: list[str] = Field(default_factory=list, description="岗位技能要求列表")
|
||||
city: str = Field(description="城市")
|
||||
region: str = Field(description="区域")
|
||||
location_detail: str = Field(description="详细地点描述")
|
||||
start_time: datetime = Field(description="岗位开始时间，ISO-8601")
|
||||
duration_hours: float = Field(gt=0, description="工时（小时），必须大于 0")
|
||||
headcount: int = Field(gt=0, description="招聘人数，必须大于 0")
|
||||
salary: Salary = Field(description="薪资信息")
|
||||
work_mode: str = Field(description="工作模式，如兼职、全职、活动")
|
||||
tags: list[str] = Field(default_factory=list, description="业务标签列表")
|
||||
confidence: float = Field(ge=0, le=1, description="数据置信度，范围 0~1")
|
||||
|
||||
|
||||
class WorkerCard(BaseModel):
|
||||
worker_id: str
|
||||
name: str
|
||||
description: str
|
||||
skills: list[SkillScore] = Field(default_factory=list)
|
||||
cities: list[str] = Field(default_factory=list)
|
||||
regions: list[str] = Field(default_factory=list)
|
||||
availability: list[str] = Field(default_factory=list)
|
||||
experience_tags: list[str] = Field(default_factory=list)
|
||||
reliability_score: float = Field(ge=0, le=1)
|
||||
profile_completion: float = Field(ge=0, le=1)
|
||||
confidence: float = Field(ge=0, le=1)
|
||||
worker_id: str = Field(description="工人唯一 ID")
|
||||
name: str = Field(description="工人姓名或昵称")
|
||||
description: str = Field(description="工人自我描述")
|
||||
skills: list[SkillScore] = Field(default_factory=list, description="技能及熟练度列表")
|
||||
cities: list[str] = Field(default_factory=list, description="可接单城市列表")
|
||||
regions: list[str] = Field(default_factory=list, description="可接单区域列表")
|
||||
availability: list[str] = Field(default_factory=list, description="可上岗时间描述")
|
||||
experience_tags: list[str] = Field(default_factory=list, description="经验标签列表")
|
||||
reliability_score: float = Field(ge=0, le=1, description="履约可靠性分，范围 0~1")
|
||||
profile_completion: float = Field(ge=0, le=1, description="档案完善度，范围 0~1")
|
||||
confidence: float = Field(ge=0, le=1, description="数据置信度，范围 0~1")
|
||||
|
||||
|
||||
class MatchBreakdown(BaseModel):
|
||||
skill_score: float = Field(ge=0, le=1)
|
||||
region_score: float = Field(ge=0, le=1)
|
||||
time_score: float = Field(ge=0, le=1)
|
||||
experience_score: float = Field(ge=0, le=1)
|
||||
reliability_score: float = Field(ge=0, le=1)
|
||||
skill_score: float = Field(ge=0, le=1, description="技能匹配分，范围 0~1")
|
||||
region_score: float = Field(ge=0, le=1, description="地域匹配分，范围 0~1")
|
||||
time_score: float = Field(ge=0, le=1, description="时间匹配分，范围 0~1")
|
||||
experience_score: float = Field(ge=0, le=1, description="经验匹配分，范围 0~1")
|
||||
reliability_score: float = Field(ge=0, le=1, description="可靠性匹配分，范围 0~1")
|
||||
|
||||
|
||||
class MatchResult(BaseModel):
|
||||
match_id: str
|
||||
source_type: SourceType
|
||||
source_id: str
|
||||
target_id: str
|
||||
match_score: float = Field(ge=0, le=1)
|
||||
breakdown: MatchBreakdown
|
||||
reasons: list[str] = Field(default_factory=list, min_length=3)
|
||||
match_id: str = Field(description="匹配记录 ID")
|
||||
source_type: SourceType = Field(description="匹配方向：job_to_worker 或 worker_to_job")
|
||||
source_id: str = Field(description="源实体 ID")
|
||||
target_id: str = Field(description="目标实体 ID")
|
||||
match_score: float = Field(ge=0, le=1, description="综合匹配分，范围 0~1")
|
||||
breakdown: MatchBreakdown = Field(description="多维打分拆解")
|
||||
reasons: list[str] = Field(default_factory=list, min_length=3, description="匹配理由，至少 3 条")
|
||||
|
||||
|
||||
class ExtractTextRequest(BaseModel):
|
||||
text: str = Field(min_length=5)
|
||||
text: str = Field(min_length=5, description="待抽取的自然语言文本，最少 5 个字符")
|
||||
model_config = ConfigDict(
|
||||
json_schema_extra={
|
||||
"example": {
|
||||
"text": "明天下午南山会展中心需要2个签到协助，5小时，150/人，女生优先",
|
||||
}
|
||||
}
|
||||
)
|
||||
|
||||
|
||||
class IngestJobRequest(BaseModel):
|
||||
job: JobCard
|
||||
job: JobCard = Field(description="岗位卡片对象")
|
||||
|
||||
|
||||
class IngestWorkerRequest(BaseModel):
|
||||
worker: WorkerCard
|
||||
worker: WorkerCard = Field(description="工人卡片对象")
|
||||
|
||||
|
||||
class MatchWorkersRequest(BaseModel):
|
||||
job_id: str | None = None
|
||||
job: JobCard | None = None
|
||||
top_n: int = Field(default=10, ge=1, le=50)
|
||||
job_id: str | None = Field(default=None, description="岗位 ID（与 job 二选一）")
|
||||
job: JobCard | None = Field(default=None, description="内联岗位对象（与 job_id 二选一）")
|
||||
top_n: int = Field(default=10, ge=1, le=50, description="返回条数，范围 1~50")
|
||||
|
||||
@model_validator(mode="after")
|
||||
def validate_source(self) -> "MatchWorkersRequest":
|
||||
@@ -104,9 +111,9 @@ class MatchWorkersRequest(BaseModel):
|
||||
|
||||
|
||||
class MatchJobsRequest(BaseModel):
|
||||
worker_id: str | None = None
|
||||
worker: WorkerCard | None = None
|
||||
top_n: int = Field(default=10, ge=1, le=50)
|
||||
worker_id: str | None = Field(default=None, description="工人 ID（与 worker 二选一）")
|
||||
worker: WorkerCard | None = Field(default=None, description="内联工人对象（与 worker_id 二选一）")
|
||||
top_n: int = Field(default=10, ge=1, le=50, description="返回条数，范围 1~50")
|
||||
|
||||
@model_validator(mode="after")
|
||||
def validate_source(self) -> "MatchJobsRequest":
|
||||
@@ -116,38 +123,86 @@ class MatchJobsRequest(BaseModel):
|
||||
|
||||
|
||||
class ExtractResponse(BaseModel):
|
||||
success: bool
|
||||
data: JobCard | WorkerCard | None = None
|
||||
errors: list[str] = Field(default_factory=list)
|
||||
missing_fields: list[str] = Field(default_factory=list)
|
||||
success: bool = Field(description="抽取是否成功")
|
||||
data: JobCard | WorkerCard | None = Field(default=None, description="抽取结果对象，可能为空")
|
||||
errors: list[str] = Field(default_factory=list, description="错误信息列表")
|
||||
missing_fields: list[str] = Field(default_factory=list, description="缺失字段列表")
|
||||
|
||||
|
||||
class BootstrapResponse(BaseModel):
|
||||
jobs: int
|
||||
workers: int
|
||||
skills: int
|
||||
categories: int
|
||||
regions: int
|
||||
jobs: int = Field(description="导入岗位数量")
|
||||
workers: int = Field(description="导入工人数量")
|
||||
skills: int = Field(description="技能词条数量")
|
||||
categories: int = Field(description="类目数量")
|
||||
regions: int = Field(description="区域数量")
|
||||
|
||||
|
||||
class HealthStatus(BaseModel):
|
||||
service: str
|
||||
database: str
|
||||
rag: str
|
||||
timestamp: datetime
|
||||
service: str = Field(description="服务状态，通常为 ok")
|
||||
database: str = Field(description="数据库状态：ok 或 error")
|
||||
rag: str = Field(description="RAG 组件状态：ok 或 error")
|
||||
timestamp: datetime = Field(description="服务端当前时间")
|
||||
|
||||
|
||||
class ListResponse(BaseModel):
|
||||
items: list[dict]
|
||||
total: int
|
||||
items: list[dict] = Field(description="列表项")
|
||||
total: int = Field(description="总数")
|
||||
|
||||
|
||||
class MatchResponse(BaseModel):
|
||||
items: list[MatchResult]
|
||||
items: list[MatchResult] = Field(description="匹配结果列表")
|
||||
|
||||
|
||||
class ExplainResponse(BaseModel):
|
||||
match: MatchResult
|
||||
match: MatchResult = Field(description="单条匹配结果详情")
|
||||
|
||||
|
||||
class MatchFeedbackRequest(BaseModel):
|
||||
match_id: str = Field(description="匹配记录 ID")
|
||||
accepted: bool = Field(description="反馈是否接受该推荐")
|
||||
|
||||
|
||||
class MatchWeightResponse(BaseModel):
|
||||
weights: dict[str, float] = Field(description="当前生效的排序权重")
|
||||
learning_enabled: bool = Field(description="是否开启在线学习")
|
||||
|
||||
|
||||
class AIObservabilityResponse(BaseModel):
|
||||
metrics: dict[str, float | int] = Field(description="AI 调用观测指标")
|
||||
|
||||
|
||||
class IngestAsyncResponse(BaseModel):
|
||||
task_id: str = Field(description="异步任务 ID")
|
||||
status: str = Field(description="任务状态")
|
||||
|
||||
|
||||
class QueueStatusResponse(BaseModel):
|
||||
queued: int = Field(description="当前队列中任务数量")
|
||||
processed: int = Field(description="历史处理成功数量")
|
||||
failed: int = Field(description="历史处理失败数量")
|
||||
|
||||
|
||||
class MatchAsyncWorkersRequest(BaseModel):
|
||||
job_id: str = Field(description="岗位 ID")
|
||||
top_n: int = Field(default=10, ge=1, le=50, description="返回条数，范围 1~50")
|
||||
|
||||
|
||||
class MatchAsyncJobsRequest(BaseModel):
|
||||
worker_id: str = Field(description="工人 ID")
|
||||
top_n: int = Field(default=10, ge=1, le=50, description="返回条数，范围 1~50")
|
||||
|
||||
|
||||
class MatchAsyncResponse(BaseModel):
|
||||
task_id: str = Field(description="异步任务 ID")
|
||||
status: str = Field(description="任务状态")
|
||||
items: list[MatchResult] | None = Field(default=None, description="任务完成后返回的匹配结果")
|
||||
|
||||
|
||||
class SystemOpsResponse(BaseModel):
|
||||
traffic: dict[str, float | int] = Field(description="全局流量护栏与错误窗口指标")
|
||||
cache: dict[str, float | int | str] = Field(description="缓存命中与大小")
|
||||
ingest_queue: QueueStatusResponse = Field(description="异步入库队列状态")
|
||||
match_queue: QueueStatusResponse = Field(description="异步匹配队列状态")
|
||||
|
||||
|
||||
class PromptOutput(BaseModel):
|
||||
|
||||
@@ -1,6 +1,8 @@
|
||||
from contextlib import asynccontextmanager
|
||||
from time import perf_counter
|
||||
|
||||
from fastapi import FastAPI
|
||||
from fastapi import FastAPI, Request
|
||||
from fastapi.responses import JSONResponse
|
||||
from fastapi.middleware.cors import CORSMiddleware
|
||||
|
||||
from app.api.routes import router
|
||||
@@ -9,6 +11,7 @@ from app.core.logging import configure_logging, logger
|
||||
from app.db.base import Base
|
||||
from app.db.session import engine
|
||||
from app.services.rag.lightrag_adapter import LightRAGAdapter
|
||||
from app.services.runtime_state import get_ingest_queue, get_match_queue, get_traffic_guard
|
||||
|
||||
|
||||
settings = get_settings()
|
||||
@@ -18,14 +21,33 @@ configure_logging(settings.log_level)
|
||||
@asynccontextmanager
|
||||
async def lifespan(_: FastAPI):
|
||||
Base.metadata.create_all(bind=engine)
|
||||
get_ingest_queue().start()
|
||||
get_match_queue().start()
|
||||
try:
|
||||
LightRAGAdapter(settings).ensure_ready()
|
||||
except Exception:
|
||||
logger.exception("Qdrant initialization skipped during startup")
|
||||
yield
|
||||
get_ingest_queue().stop()
|
||||
get_match_queue().stop()
|
||||
|
||||
|
||||
app = FastAPI(title=settings.app_name, lifespan=lifespan)
|
||||
app = FastAPI(
|
||||
title=settings.app_name,
|
||||
description=(
|
||||
"Gig POC 接口文档。\n\n"
|
||||
"接口分组：系统、抽取、入库、匹配、查询。\n"
|
||||
"完整业务说明请参考项目文档 `docs/API.md`。"
|
||||
),
|
||||
openapi_tags=[
|
||||
{"name": "系统", "description": "服务与依赖组件状态检查接口"},
|
||||
{"name": "抽取", "description": "自然语言文本抽取为结构化卡片"},
|
||||
{"name": "入库", "description": "结构化岗位/工人数据写入与初始化"},
|
||||
{"name": "匹配", "description": "岗位与工人双向匹配及结果解释"},
|
||||
{"name": "查询", "description": "岗位/工人列表与详情查询"},
|
||||
],
|
||||
lifespan=lifespan,
|
||||
)
|
||||
app.add_middleware(
|
||||
CORSMiddleware,
|
||||
allow_origins=["*"],
|
||||
@@ -33,4 +55,23 @@ app.add_middleware(
|
||||
allow_methods=["*"],
|
||||
allow_headers=["*"],
|
||||
)
|
||||
|
||||
|
||||
@app.middleware("http")
|
||||
async def traffic_guard_middleware(request: Request, call_next):
|
||||
guard = get_traffic_guard()
|
||||
allowed, reason = guard.allow(request.url.path)
|
||||
if not allowed:
|
||||
status_code = 429 if reason == "rate_limited" else 503
|
||||
return JSONResponse(status_code=status_code, content={"detail": reason})
|
||||
start = perf_counter()
|
||||
try:
|
||||
response = await call_next(request)
|
||||
except Exception:
|
||||
guard.record(500, (perf_counter() - start) * 1000)
|
||||
raise
|
||||
guard.record(response.status_code, (perf_counter() - start) * 1000)
|
||||
return response
|
||||
|
||||
|
||||
app.include_router(router)
|
||||
|
||||
87
gig-poc/apps/api/app/services/ai_guard.py
Normal file
87
gig-poc/apps/api/app/services/ai_guard.py
Normal file
@@ -0,0 +1,87 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import time
|
||||
from dataclasses import dataclass
|
||||
from threading import Lock
|
||||
|
||||
from app.core.config import Settings
|
||||
|
||||
|
||||
@dataclass
|
||||
class EndpointState:
|
||||
current_minute: int = 0
|
||||
minute_count: int = 0
|
||||
consecutive_failures: int = 0
|
||||
circuit_open_until: float = 0.0
|
||||
|
||||
|
||||
class AIGuard:
|
||||
_lock = Lock()
|
||||
_endpoint_states: dict[str, EndpointState] = {}
|
||||
_metrics = {
|
||||
"requests_total": 0,
|
||||
"success_total": 0,
|
||||
"fail_total": 0,
|
||||
"fallback_total": 0,
|
||||
"rate_limited_total": 0,
|
||||
"circuit_open_total": 0,
|
||||
"endpoint_failover_total": 0,
|
||||
}
|
||||
|
||||
def __init__(self, settings: Settings):
|
||||
self.settings = settings
|
||||
|
||||
def allow_request(self, endpoint: str) -> tuple[bool, str]:
|
||||
now = time.time()
|
||||
now_minute = int(now // 60)
|
||||
with self._lock:
|
||||
state = self._endpoint_states.setdefault(endpoint, EndpointState())
|
||||
if state.circuit_open_until > now:
|
||||
self._metrics["circuit_open_total"] += 1
|
||||
return False, "circuit_open"
|
||||
if state.current_minute != now_minute:
|
||||
state.current_minute = now_minute
|
||||
state.minute_count = 0
|
||||
if state.minute_count >= self.settings.ai_rate_limit_per_minute:
|
||||
self._metrics["rate_limited_total"] += 1
|
||||
return False, "rate_limited"
|
||||
state.minute_count += 1
|
||||
self._metrics["requests_total"] += 1
|
||||
return True, "ok"
|
||||
|
||||
def record_success(self, endpoint: str) -> None:
|
||||
with self._lock:
|
||||
state = self._endpoint_states.setdefault(endpoint, EndpointState())
|
||||
state.consecutive_failures = 0
|
||||
state.circuit_open_until = 0.0
|
||||
self._metrics["success_total"] += 1
|
||||
|
||||
def record_failure(self, endpoint: str) -> None:
|
||||
with self._lock:
|
||||
state = self._endpoint_states.setdefault(endpoint, EndpointState())
|
||||
state.consecutive_failures += 1
|
||||
self._metrics["fail_total"] += 1
|
||||
if state.consecutive_failures >= self.settings.ai_circuit_breaker_fail_threshold:
|
||||
state.circuit_open_until = time.time() + self.settings.ai_circuit_breaker_cooldown_seconds
|
||||
state.consecutive_failures = 0
|
||||
|
||||
def record_fallback(self) -> None:
|
||||
with self._lock:
|
||||
self._metrics["fallback_total"] += 1
|
||||
|
||||
def record_failover(self) -> None:
|
||||
with self._lock:
|
||||
self._metrics["endpoint_failover_total"] += 1
|
||||
|
||||
def snapshot(self) -> dict:
|
||||
with self._lock:
|
||||
requests_total = self._metrics["requests_total"]
|
||||
fallback_total = self._metrics["fallback_total"]
|
||||
success_total = self._metrics["success_total"]
|
||||
fail_total = self._metrics["fail_total"]
|
||||
return {
|
||||
**self._metrics,
|
||||
"fallback_hit_rate": round(fallback_total / requests_total, 4) if requests_total else 0.0,
|
||||
"success_rate": round(success_total / requests_total, 4) if requests_total else 0.0,
|
||||
"failure_rate": round(fail_total / requests_total, 4) if requests_total else 0.0,
|
||||
}
|
||||
146
gig-poc/apps/api/app/services/cache_service.py
Normal file
146
gig-poc/apps/api/app/services/cache_service.py
Normal file
@@ -0,0 +1,146 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import time
|
||||
from functools import lru_cache
|
||||
from threading import Lock
|
||||
from typing import Any, Protocol
|
||||
|
||||
from app.core.config import get_settings
|
||||
from app.core.logging import logger
|
||||
|
||||
try:
|
||||
from redis import Redis
|
||||
except Exception: # pragma: no cover
|
||||
Redis = None # type: ignore[assignment]
|
||||
|
||||
|
||||
class Cache(Protocol):
|
||||
def get(self, key: str): ...
|
||||
def set(self, key: str, value: Any) -> None: ...
|
||||
def delete(self, key: str) -> None: ...
|
||||
def clear(self) -> None: ...
|
||||
def stats(self) -> dict[str, int | float | str]: ...
|
||||
|
||||
|
||||
class TTLCache:
|
||||
def __init__(self, ttl_seconds: int):
|
||||
self.ttl_seconds = ttl_seconds
|
||||
self._store: dict[str, tuple[float, Any]] = {}
|
||||
self._lock = Lock()
|
||||
self._hits = 0
|
||||
self._misses = 0
|
||||
|
||||
def get(self, key: str):
|
||||
now = time.time()
|
||||
with self._lock:
|
||||
item = self._store.get(key)
|
||||
if item is None:
|
||||
self._misses += 1
|
||||
return None
|
||||
expires_at, value = item
|
||||
if expires_at < now:
|
||||
self._store.pop(key, None)
|
||||
self._misses += 1
|
||||
return None
|
||||
self._hits += 1
|
||||
return value
|
||||
|
||||
def set(self, key: str, value: Any) -> None:
|
||||
expires_at = time.time() + self.ttl_seconds
|
||||
with self._lock:
|
||||
self._store[key] = (expires_at, value)
|
||||
|
||||
def delete(self, key: str) -> None:
|
||||
with self._lock:
|
||||
self._store.pop(key, None)
|
||||
|
||||
def clear(self) -> None:
|
||||
with self._lock:
|
||||
self._store.clear()
|
||||
|
||||
def stats(self) -> dict[str, int | float | str]:
|
||||
with self._lock:
|
||||
requests = self._hits + self._misses
|
||||
hit_rate = (self._hits / requests) if requests else 0.0
|
||||
return {
|
||||
"backend": "memory",
|
||||
"size": len(self._store),
|
||||
"hits": self._hits,
|
||||
"misses": self._misses,
|
||||
"hit_rate": round(hit_rate, 4),
|
||||
}
|
||||
|
||||
|
||||
class RedisCache:
|
||||
def __init__(self, url: str, prefix: str, ttl_seconds: int):
|
||||
if Redis is None:
|
||||
raise RuntimeError("redis package is not installed")
|
||||
self.client = Redis.from_url(url, decode_responses=True)
|
||||
self.prefix = prefix
|
||||
self.ttl_seconds = ttl_seconds
|
||||
self._hits = 0
|
||||
self._misses = 0
|
||||
self._lock = Lock()
|
||||
|
||||
def get(self, key: str):
|
||||
raw = self.client.get(self._key(key))
|
||||
with self._lock:
|
||||
if raw is None:
|
||||
self._misses += 1
|
||||
return None
|
||||
self._hits += 1
|
||||
return json.loads(raw)
|
||||
|
||||
def set(self, key: str, value: Any) -> None:
|
||||
self.client.set(self._key(key), json.dumps(value, ensure_ascii=False), ex=self.ttl_seconds)
|
||||
|
||||
def delete(self, key: str) -> None:
|
||||
self.client.delete(self._key(key))
|
||||
|
||||
def clear(self) -> None:
|
||||
pattern = f"{self.prefix}:*"
|
||||
cursor = 0
|
||||
while True:
|
||||
cursor, keys = self.client.scan(cursor=cursor, match=pattern, count=200)
|
||||
if keys:
|
||||
self.client.delete(*keys)
|
||||
if cursor == 0:
|
||||
break
|
||||
|
||||
def stats(self) -> dict[str, int | float | str]:
|
||||
with self._lock:
|
||||
requests = self._hits + self._misses
|
||||
hit_rate = (self._hits / requests) if requests else 0.0
|
||||
return {
|
||||
"backend": "redis",
|
||||
"size": int(self.client.dbsize()),
|
||||
"hits": self._hits,
|
||||
"misses": self._misses,
|
||||
"hit_rate": round(hit_rate, 4),
|
||||
}
|
||||
|
||||
def _key(self, key: str) -> str:
|
||||
return f"{self.prefix}:{key}"
|
||||
|
||||
|
||||
def _build_cache(namespace: str, ttl_seconds: int) -> Cache:
|
||||
settings = get_settings()
|
||||
if settings.cache_backend == "redis":
|
||||
try:
|
||||
return RedisCache(settings.redis_url, f"{settings.redis_prefix}:{namespace}", ttl_seconds=ttl_seconds)
|
||||
except Exception:
|
||||
logger.exception("failed to init redis cache namespace=%s fallback to memory cache", namespace)
|
||||
return TTLCache(ttl_seconds=ttl_seconds)
|
||||
|
||||
|
||||
@lru_cache
|
||||
def get_match_cache() -> Cache:
|
||||
settings = get_settings()
|
||||
return _build_cache("match", settings.match_cache_ttl_seconds)
|
||||
|
||||
|
||||
@lru_cache
|
||||
def get_query_cache() -> Cache:
|
||||
settings = get_settings()
|
||||
return _build_cache("query", settings.query_cache_ttl_seconds)
|
||||
@@ -26,13 +26,9 @@ class ExtractionService:
|
||||
|
||||
def extract_job(self, text: str) -> ExtractResponse:
|
||||
logger.info("extract_job request text=%s", text)
|
||||
llm_result = self._llm_extract(text, self.settings.prompt_dir / "job_extract.md")
|
||||
if llm_result:
|
||||
try:
|
||||
return ExtractResponse(success=True, data=JobCard(**llm_result.content))
|
||||
except ValidationError as exc:
|
||||
logger.exception("LLM job extraction validation failed")
|
||||
return ExtractResponse(success=False, errors=[str(exc)], missing_fields=self._missing_fields(exc))
|
||||
llm_card = self._llm_extract_with_retry(text, self.settings.prompt_dir / "job_extract.md", JobCard)
|
||||
if llm_card:
|
||||
return ExtractResponse(success=True, data=llm_card)
|
||||
|
||||
try:
|
||||
card = self._extract_job_rule(text)
|
||||
@@ -43,13 +39,9 @@ class ExtractionService:
|
||||
|
||||
def extract_worker(self, text: str) -> ExtractResponse:
|
||||
logger.info("extract_worker request text=%s", text)
|
||||
llm_result = self._llm_extract(text, self.settings.prompt_dir / "worker_extract.md")
|
||||
if llm_result:
|
||||
try:
|
||||
return ExtractResponse(success=True, data=WorkerCard(**llm_result.content))
|
||||
except ValidationError as exc:
|
||||
logger.exception("LLM worker extraction validation failed")
|
||||
return ExtractResponse(success=False, errors=[str(exc)], missing_fields=self._missing_fields(exc))
|
||||
llm_card = self._llm_extract_with_retry(text, self.settings.prompt_dir / "worker_extract.md", WorkerCard)
|
||||
if llm_card:
|
||||
return ExtractResponse(success=True, data=llm_card)
|
||||
|
||||
try:
|
||||
card = self._extract_worker_rule(text)
|
||||
@@ -65,6 +57,57 @@ class ExtractionService:
|
||||
logger.exception("LLM extraction failed, fallback to rule-based extraction")
|
||||
return None
|
||||
|
||||
def _llm_extract_with_retry(self, text: str, prompt_path: Path, schema_cls):
|
||||
base_prompt = load_prompt(prompt_path)
|
||||
llm_result = self._llm_extract(text, prompt_path)
|
||||
if not llm_result:
|
||||
return None
|
||||
|
||||
try:
|
||||
return schema_cls(**llm_result.content)
|
||||
except ValidationError as exc:
|
||||
logger.warning("LLM extraction validation failed, trying schema-aware retry")
|
||||
last_error = exc
|
||||
last_output = llm_result.content
|
||||
|
||||
for _ in range(self.settings.extraction_llm_max_retries):
|
||||
missing_fields = self._missing_fields(last_error)
|
||||
repair_prompt = self._build_repair_prompt(base_prompt, schema_cls, missing_fields)
|
||||
try:
|
||||
repair_result = self.llm_client.extract_json(
|
||||
repair_prompt,
|
||||
self._build_repair_input(text, last_output, missing_fields),
|
||||
)
|
||||
except Exception:
|
||||
logger.exception("LLM schema-aware retry failed")
|
||||
return None
|
||||
if not repair_result:
|
||||
return None
|
||||
last_output = repair_result.content
|
||||
try:
|
||||
return schema_cls(**repair_result.content)
|
||||
except ValidationError as exc:
|
||||
last_error = exc
|
||||
logger.warning("LLM schema-aware retry still invalid missing_fields=%s", self._missing_fields(exc))
|
||||
return None
|
||||
|
||||
def _build_repair_prompt(self, base_prompt: str, schema_cls, missing_fields: list[str]) -> str:
|
||||
schema_json = json.dumps(schema_cls.model_json_schema(), ensure_ascii=False)
|
||||
return (
|
||||
f"{base_prompt}\n\n"
|
||||
"你是结构化修复助手。请严格输出可被 JSON 解析的对象，不要输出解释文字。\n"
|
||||
"目标是根据给定 schema 修复字段缺失和类型错误，优先保证必填字段完整。\n"
|
||||
f"缺失或错误字段: {', '.join(missing_fields) if missing_fields else 'unknown'}\n"
|
||||
f"JSON Schema: {schema_json}\n"
|
||||
)
|
||||
|
||||
def _build_repair_input(self, original_text: str, last_output: dict, missing_fields: list[str]) -> str:
|
||||
return (
|
||||
f"原始文本:\n{original_text}\n\n"
|
||||
f"上一次抽取结果:\n{json.dumps(last_output, ensure_ascii=False)}\n\n"
|
||||
f"请重点修复字段:\n{json.dumps(missing_fields, ensure_ascii=False)}"
|
||||
)
|
||||
|
||||
def _extract_job_rule(self, text: str) -> JobCard:
|
||||
skill_hits = [item for item in self.skills if item in text]
|
||||
category = next((item for item in self.categories if item in text), "活动执行")
|
||||
|
||||
105
gig-poc/apps/api/app/services/ingest_queue.py
Normal file
105
gig-poc/apps/api/app/services/ingest_queue.py
Normal file
@@ -0,0 +1,105 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from dataclasses import dataclass
|
||||
from queue import Empty, Full, Queue
|
||||
from threading import Event, Lock, Thread
|
||||
from typing import Any
|
||||
|
||||
from app.core.config import Settings
|
||||
from app.core.logging import logger
|
||||
from app.db.session import SessionLocal
|
||||
from app.domain.schemas import JobCard, WorkerCard
|
||||
from app.services.ingest_service import IngestService
|
||||
from app.utils.ids import generate_id
|
||||
|
||||
|
||||
@dataclass
|
||||
class QueueTask:
|
||||
task_id: str
|
||||
kind: str
|
||||
payload: dict[str, Any]
|
||||
|
||||
|
||||
class IngestQueue:
|
||||
def __init__(self, settings: Settings):
|
||||
self.settings = settings
|
||||
self.queue: Queue[QueueTask] = Queue(maxsize=settings.ingest_queue_max_size)
|
||||
self._stop_event = Event()
|
||||
self._thread: Thread | None = None
|
||||
self._lock = Lock()
|
||||
self._status: dict[str, str] = {}
|
||||
self._processed = 0
|
||||
self._failed = 0
|
||||
|
||||
def start(self) -> None:
|
||||
if not self.settings.ingest_async_enabled:
|
||||
return
|
||||
if self._thread and self._thread.is_alive():
|
||||
return
|
||||
self._thread = Thread(target=self._run, daemon=True, name="ingest-queue-worker")
|
||||
self._thread.start()
|
||||
logger.info("ingest queue worker started")
|
||||
|
||||
def stop(self) -> None:
|
||||
self._stop_event.set()
|
||||
if self._thread and self._thread.is_alive():
|
||||
self._thread.join(timeout=3)
|
||||
|
||||
def enqueue_job(self, card: JobCard) -> str:
|
||||
return self._enqueue("job", card.model_dump(mode="json"))
|
||||
|
||||
def enqueue_worker(self, card: WorkerCard) -> str:
|
||||
return self._enqueue("worker", card.model_dump(mode="json"))
|
||||
|
||||
def task_status(self, task_id: str) -> str:
|
||||
with self._lock:
|
||||
return self._status.get(task_id, "not_found")
|
||||
|
||||
def stats(self) -> dict[str, int]:
|
||||
with self._lock:
|
||||
return {
|
||||
"queued": self.queue.qsize(),
|
||||
"processed": self._processed,
|
||||
"failed": self._failed,
|
||||
}
|
||||
|
||||
def _enqueue(self, kind: str, payload: dict[str, Any]) -> str:
|
||||
task_id = generate_id("queue")
|
||||
task = QueueTask(task_id=task_id, kind=kind, payload=payload)
|
||||
with self._lock:
|
||||
self._status[task_id] = "queued"
|
||||
try:
|
||||
self.queue.put_nowait(task)
|
||||
except Full as exc:
|
||||
with self._lock:
|
||||
self._status[task_id] = "rejected"
|
||||
raise RuntimeError("ingest queue is full") from exc
|
||||
return task_id
|
||||
|
||||
def _run(self) -> None:
|
||||
while not self._stop_event.is_set():
|
||||
try:
|
||||
task = self.queue.get(timeout=0.5)
|
||||
except Empty:
|
||||
continue
|
||||
try:
|
||||
with self._lock:
|
||||
self._status[task.task_id] = "processing"
|
||||
with SessionLocal() as db:
|
||||
service = IngestService(db)
|
||||
if task.kind == "job":
|
||||
service.ingest_job(JobCard(**task.payload))
|
||||
elif task.kind == "worker":
|
||||
service.ingest_worker(WorkerCard(**task.payload))
|
||||
else:
|
||||
raise ValueError(f"unknown task kind {task.kind}")
|
||||
with self._lock:
|
||||
self._status[task.task_id] = "done"
|
||||
self._processed += 1
|
||||
except Exception:
|
||||
logger.exception("ingest queue task failed task_id=%s kind=%s", task.task_id, task.kind)
|
||||
with self._lock:
|
||||
self._status[task.task_id] = "failed"
|
||||
self._failed += 1
|
||||
finally:
|
||||
self.queue.task_done()
|
||||
@@ -9,6 +9,7 @@ from app.core.logging import logger
|
||||
from app.domain.schemas import BootstrapResponse, JobCard, WorkerCard
|
||||
from app.repositories.job_repository import JobRepository
|
||||
from app.repositories.worker_repository import WorkerRepository
|
||||
from app.services.cache_service import get_match_cache, get_query_cache
|
||||
from app.services.rag.lightrag_adapter import LightRAGAdapter
|
||||
|
||||
|
||||
@@ -19,17 +20,27 @@ class IngestService:
|
||||
self.job_repository = JobRepository(db)
|
||||
self.worker_repository = WorkerRepository(db)
|
||||
self.rag = LightRAGAdapter(self.settings)
|
||||
self.match_cache = get_match_cache()
|
||||
self.query_cache = get_query_cache()
|
||||
|
||||
def ingest_job(self, card: JobCard) -> JobCard:
|
||||
logger.info("ingest_job job_id=%s", card.job_id)
|
||||
self.job_repository.upsert(card)
|
||||
self.rag.upsert_job(card)
|
||||
if self.settings.match_cache_enabled:
|
||||
self.match_cache.clear()
|
||||
if self.settings.query_cache_enabled:
|
||||
self.query_cache.clear()
|
||||
return card
|
||||
|
||||
def ingest_worker(self, card: WorkerCard) -> WorkerCard:
|
||||
logger.info("ingest_worker worker_id=%s", card.worker_id)
|
||||
self.worker_repository.upsert(card)
|
||||
self.rag.upsert_worker(card)
|
||||
if self.settings.match_cache_enabled:
|
||||
self.match_cache.clear()
|
||||
if self.settings.query_cache_enabled:
|
||||
self.query_cache.clear()
|
||||
return card
|
||||
|
||||
def bootstrap(self) -> BootstrapResponse:
|
||||
@@ -43,6 +54,10 @@ class IngestService:
|
||||
self.ingest_job(JobCard(**item))
|
||||
for item in workers:
|
||||
self.ingest_worker(WorkerCard(**item))
|
||||
if self.settings.match_cache_enabled:
|
||||
self.match_cache.clear()
|
||||
if self.settings.query_cache_enabled:
|
||||
self.query_cache.clear()
|
||||
return BootstrapResponse(
|
||||
jobs=len(jobs),
|
||||
workers=len(workers),
|
||||
|
||||
@@ -6,14 +6,17 @@ import httpx
|
||||
|
||||
from app.core.config import Settings
|
||||
from app.domain.schemas import PromptOutput
|
||||
from app.services.ai_guard import AIGuard
|
||||
|
||||
|
||||
class LLMClient:
|
||||
def __init__(self, settings: Settings):
|
||||
self.settings = settings
|
||||
self.guard = AIGuard(settings)
|
||||
|
||||
def extract_json(self, system_prompt: str, user_text: str) -> PromptOutput | None:
|
||||
if not self.settings.llm_enabled or not self.settings.llm_base_url or not self.settings.llm_api_key:
|
||||
self.guard.record_fallback()
|
||||
return None
|
||||
|
||||
payload = {
|
||||
@@ -25,10 +28,77 @@ class LLMClient:
|
||||
"temperature": 0.1,
|
||||
"response_format": {"type": "json_object"},
|
||||
}
|
||||
headers = {"Authorization": f"Bearer {self.settings.llm_api_key}"}
|
||||
with httpx.Client(timeout=30.0) as client:
|
||||
response = client.post(f"{self.settings.llm_base_url.rstrip('/')}/chat/completions", json=payload, headers=headers)
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
raw_text = data["choices"][0]["message"]["content"]
|
||||
endpoints = [self.settings.llm_base_url, *self.settings.llm_fallback_base_urls]
|
||||
raw_text = self._request_with_failover(
|
||||
endpoints=endpoints,
|
||||
path="/chat/completions",
|
||||
payload=payload,
|
||||
api_key=self.settings.llm_api_key,
|
||||
)
|
||||
if raw_text is None:
|
||||
self.guard.record_fallback()
|
||||
return None
|
||||
return PromptOutput(content=json.loads(raw_text), raw_text=raw_text)
|
||||
|
||||
def embedding(self, text: str) -> list[float] | None:
|
||||
if not self.settings.embedding_enabled:
|
||||
return None
|
||||
base_url = self.settings.embedding_base_url or self.settings.llm_base_url
|
||||
api_key = self.settings.embedding_api_key or self.settings.llm_api_key
|
||||
if not base_url or not api_key:
|
||||
self.guard.record_fallback()
|
||||
return None
|
||||
|
||||
payload = {
|
||||
"model": self.settings.embedding_model,
|
||||
"input": text,
|
||||
}
|
||||
endpoints = [base_url, *self.settings.embedding_fallback_base_urls]
|
||||
data = self._request_with_failover(
|
||||
endpoints=endpoints,
|
||||
path="/embeddings",
|
||||
payload=payload,
|
||||
api_key=api_key,
|
||||
return_full_response=True,
|
||||
)
|
||||
if data is None:
|
||||
self.guard.record_fallback()
|
||||
return None
|
||||
embedding = data["data"][0]["embedding"]
|
||||
if not isinstance(embedding, list):
|
||||
return None
|
||||
return [float(item) for item in embedding]
|
||||
|
||||
def metrics(self) -> dict:
|
||||
return self.guard.snapshot()
|
||||
|
||||
def _request_with_failover(
|
||||
self,
|
||||
endpoints: list[str],
|
||||
path: str,
|
||||
payload: dict,
|
||||
api_key: str,
|
||||
return_full_response: bool = False,
|
||||
):
|
||||
if not endpoints:
|
||||
return None
|
||||
for index, endpoint in enumerate([item for item in endpoints if item]):
|
||||
allowed, _ = self.guard.allow_request(endpoint)
|
||||
if not allowed:
|
||||
continue
|
||||
if index > 0:
|
||||
self.guard.record_failover()
|
||||
try:
|
||||
headers = {"Authorization": f"Bearer {api_key}"}
|
||||
with httpx.Client(timeout=self.settings.ai_request_timeout_seconds) as client:
|
||||
response = client.post(f"{endpoint.rstrip('/')}{path}", json=payload, headers=headers)
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
self.guard.record_success(endpoint)
|
||||
if return_full_response:
|
||||
return data
|
||||
return data["choices"][0]["message"]["content"]
|
||||
except Exception:
|
||||
self.guard.record_failure(endpoint)
|
||||
continue
|
||||
return None
|
||||
|
||||
121
gig-poc/apps/api/app/services/match_queue.py
Normal file
121
gig-poc/apps/api/app/services/match_queue.py
Normal file
@@ -0,0 +1,121 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from dataclasses import dataclass
|
||||
from queue import Empty, Full, Queue
|
||||
from threading import Event, Lock, Thread
|
||||
from typing import Any
|
||||
|
||||
from app.core.config import Settings
|
||||
from app.core.logging import logger
|
||||
from app.db.session import SessionLocal
|
||||
from app.domain.schemas import MatchResult
|
||||
from app.repositories.job_repository import JobRepository
|
||||
from app.repositories.worker_repository import WorkerRepository
|
||||
from app.services.card_mapper import job_to_card, worker_to_card
|
||||
from app.services.matching_service import MatchingService
|
||||
from app.utils.ids import generate_id
|
||||
|
||||
|
||||
@dataclass
|
||||
class MatchTask:
|
||||
task_id: str
|
||||
kind: str
|
||||
source_id: str
|
||||
top_n: int
|
||||
|
||||
|
||||
class MatchQueue:
|
||||
def __init__(self, settings: Settings):
|
||||
self.settings = settings
|
||||
self.queue: Queue[MatchTask] = Queue(maxsize=settings.match_queue_max_size)
|
||||
self._stop_event = Event()
|
||||
self._thread: Thread | None = None
|
||||
self._lock = Lock()
|
||||
self._status: dict[str, str] = {}
|
||||
self._results: dict[str, list[dict[str, Any]]] = {}
|
||||
self._processed = 0
|
||||
self._failed = 0
|
||||
|
||||
def start(self) -> None:
|
||||
if not self.settings.match_async_enabled:
|
||||
return
|
||||
if self._thread and self._thread.is_alive():
|
||||
return
|
||||
self._thread = Thread(target=self._run, daemon=True, name="match-queue-worker")
|
||||
self._thread.start()
|
||||
logger.info("match queue worker started")
|
||||
|
||||
def stop(self) -> None:
|
||||
self._stop_event.set()
|
||||
if self._thread and self._thread.is_alive():
|
||||
self._thread.join(timeout=3)
|
||||
|
||||
def enqueue_workers(self, job_id: str, top_n: int) -> str:
|
||||
return self._enqueue("workers", job_id, top_n)
|
||||
|
||||
def enqueue_jobs(self, worker_id: str, top_n: int) -> str:
|
||||
return self._enqueue("jobs", worker_id, top_n)
|
||||
|
||||
def task_status(self, task_id: str) -> str:
|
||||
with self._lock:
|
||||
return self._status.get(task_id, "not_found")
|
||||
|
||||
def task_result(self, task_id: str) -> list[dict[str, Any]] | None:
|
||||
with self._lock:
|
||||
return self._results.get(task_id)
|
||||
|
||||
def stats(self) -> dict[str, int]:
|
||||
with self._lock:
|
||||
return {
|
||||
"queued": self.queue.qsize(),
|
||||
"processed": self._processed,
|
||||
"failed": self._failed,
|
||||
}
|
||||
|
||||
def _enqueue(self, kind: str, source_id: str, top_n: int) -> str:
|
||||
task_id = generate_id("mq")
|
||||
task = MatchTask(task_id=task_id, kind=kind, source_id=source_id, top_n=top_n)
|
||||
with self._lock:
|
||||
self._status[task_id] = "queued"
|
||||
try:
|
||||
self.queue.put_nowait(task)
|
||||
except Full as exc:
|
||||
with self._lock:
|
||||
self._status[task_id] = "rejected"
|
||||
raise RuntimeError("match queue is full") from exc
|
||||
return task_id
|
||||
|
||||
def _run(self) -> None:
|
||||
while not self._stop_event.is_set():
|
||||
try:
|
||||
task = self.queue.get(timeout=0.5)
|
||||
except Empty:
|
||||
continue
|
||||
try:
|
||||
with self._lock:
|
||||
self._status[task.task_id] = "processing"
|
||||
with SessionLocal() as db:
|
||||
service = MatchingService(db)
|
||||
if task.kind == "workers":
|
||||
job = JobRepository(db).get(task.source_id)
|
||||
if job is None:
|
||||
raise ValueError("job not found")
|
||||
items = service.match_workers(job_to_card(job), task.top_n)
|
||||
elif task.kind == "jobs":
|
||||
worker = WorkerRepository(db).get(task.source_id)
|
||||
if worker is None:
|
||||
raise ValueError("worker not found")
|
||||
items = service.match_jobs(worker_to_card(worker), task.top_n)
|
||||
else:
|
||||
raise ValueError(f"unknown task kind {task.kind}")
|
||||
with self._lock:
|
||||
self._status[task.task_id] = "done"
|
||||
self._results[task.task_id] = [item.model_dump(mode="json") for item in items]
|
||||
self._processed += 1
|
||||
except Exception:
|
||||
logger.exception("match queue task failed task_id=%s kind=%s", task.task_id, task.kind)
|
||||
with self._lock:
|
||||
self._status[task.task_id] = "failed"
|
||||
self._failed += 1
|
||||
finally:
|
||||
self.queue.task_done()
|
||||
@@ -10,8 +10,10 @@ from app.domain.schemas import JobCard, MatchBreakdown, MatchResult, QueryFilter
|
||||
from app.repositories.job_repository import JobRepository
|
||||
from app.repositories.match_repository import MatchRepository
|
||||
from app.repositories.worker_repository import WorkerRepository
|
||||
from app.services.cache_service import get_match_cache
|
||||
from app.services.card_mapper import job_to_card, worker_to_card
|
||||
from app.services.rag.lightrag_adapter import LightRAGAdapter
|
||||
from app.services.weight_service import MatchWeightService
|
||||
from app.utils.ids import generate_id
|
||||
|
||||
|
||||
@@ -23,9 +25,16 @@ class MatchingService:
|
||||
self.workers = WorkerRepository(db)
|
||||
self.matches = MatchRepository(db)
|
||||
self.rag = LightRAGAdapter(self.settings)
|
||||
self.weight_service = MatchWeightService(self.settings)
|
||||
self.cache = get_match_cache()
|
||||
|
||||
def match_workers(self, source: JobCard, top_n: int) -> list[MatchResult]:
|
||||
logger.info("match_workers source_id=%s top_n=%s", source.job_id, top_n)
|
||||
cache_key = f"match_workers:{source.job_id}:{top_n}"
|
||||
if self.settings.match_cache_enabled:
|
||||
cached = self.cache.get(cache_key)
|
||||
if cached is not None:
|
||||
return self._parse_cached_matches(cached)
|
||||
query_text = " ".join([source.title, source.category, source.city, source.region, *source.skills, *source.tags])
|
||||
candidate_ids = self.rag.search(
|
||||
query_text=query_text,
|
||||
@@ -36,10 +45,17 @@ class MatchingService:
|
||||
results = [self._build_job_to_worker_match(source, worker_to_card(worker)) for worker in candidates]
|
||||
results = sorted(results, key=lambda item: item.match_score, reverse=True)[:top_n]
|
||||
self.matches.bulk_replace(results, SourceType.job_to_worker.value, source.job_id)
|
||||
if self.settings.match_cache_enabled:
|
||||
self.cache.set(cache_key, [item.model_dump(mode="json") for item in results])
|
||||
return results
|
||||
|
||||
def match_jobs(self, source: WorkerCard, top_n: int) -> list[MatchResult]:
|
||||
logger.info("match_jobs source_id=%s top_n=%s", source.worker_id, top_n)
|
||||
cache_key = f"match_jobs:{source.worker_id}:{top_n}"
|
||||
if self.settings.match_cache_enabled:
|
||||
cached = self.cache.get(cache_key)
|
||||
if cached is not None:
|
||||
return self._parse_cached_matches(cached)
|
||||
query_text = " ".join([source.name, *source.cities, *source.regions, *[item.name for item in source.skills], *source.experience_tags])
|
||||
city = source.cities[0] if source.cities else None
|
||||
candidate_ids = self.rag.search(
|
||||
@@ -51,6 +67,8 @@ class MatchingService:
|
||||
results = [self._build_worker_to_job_match(source, job_to_card(job)) for job in candidates]
|
||||
results = sorted(results, key=lambda item: item.match_score, reverse=True)[:top_n]
|
||||
self.matches.bulk_replace(results, SourceType.worker_to_job.value, source.worker_id)
|
||||
if self.settings.match_cache_enabled:
|
||||
self.cache.set(cache_key, [item.model_dump(mode="json") for item in results])
|
||||
return results
|
||||
|
||||
def explain(self, match_id: str) -> MatchResult | None:
|
||||
@@ -61,6 +79,20 @@ class MatchingService:
|
||||
|
||||
return match_record_to_schema(record)
|
||||
|
||||
def feedback(self, match_id: str, accepted: bool) -> dict[str, float] | None:
|
||||
record = self.matches.get(match_id)
|
||||
if record is None:
|
||||
return None
|
||||
from app.services.card_mapper import match_record_to_schema
|
||||
|
||||
match = match_record_to_schema(record)
|
||||
if self.settings.ranking_learning_enabled:
|
||||
return self.weight_service.update_from_feedback(match.breakdown, accepted)
|
||||
return self.weight_service.get_weights()
|
||||
|
||||
def current_weights(self) -> dict[str, float]:
|
||||
return self.weight_service.get_weights()
|
||||
|
||||
def _build_job_to_worker_match(self, job: JobCard, worker: WorkerCard) -> MatchResult:
|
||||
job_skills = set(job.skills)
|
||||
expanded_skills = self.rag.expand_skills(job.skills)
|
||||
@@ -143,13 +175,14 @@ class MatchingService:
|
||||
experience_score: float,
|
||||
reliability_score: float,
|
||||
) -> float:
|
||||
return (
|
||||
self.settings.score_skill_weight * skill_score
|
||||
+ self.settings.score_region_weight * region_score
|
||||
+ self.settings.score_time_weight * time_score
|
||||
+ self.settings.score_experience_weight * experience_score
|
||||
+ self.settings.score_reliability_weight * reliability_score
|
||||
breakdown = MatchBreakdown(
|
||||
skill_score=skill_score,
|
||||
region_score=region_score,
|
||||
time_score=time_score,
|
||||
experience_score=experience_score,
|
||||
reliability_score=reliability_score,
|
||||
)
|
||||
return self.weight_service.score(breakdown)
|
||||
|
||||
def _build_reasons(
|
||||
self,
|
||||
@@ -176,3 +209,10 @@ class MatchingService:
|
||||
while len(reasons) < 3:
|
||||
reasons.append("岗位需求与候选画像存在基础匹配")
|
||||
return reasons[:5]
|
||||
|
||||
def _parse_cached_matches(self, cached) -> list[MatchResult]:
|
||||
if isinstance(cached, list) and cached and isinstance(cached[0], MatchResult):
|
||||
return cached
|
||||
if isinstance(cached, list):
|
||||
return [MatchResult(**item) for item in cached]
|
||||
return []
|
||||
|
||||
@@ -10,6 +10,7 @@ from qdrant_client import QdrantClient, models
|
||||
from app.core.config import Settings
|
||||
from app.core.logging import logger
|
||||
from app.domain.schemas import JobCard, QueryFilters, WorkerCard
|
||||
from app.services.llm_client import LLMClient
|
||||
|
||||
|
||||
class LightRAGAdapter:
|
||||
@@ -17,13 +18,28 @@ class LightRAGAdapter:
|
||||
self.settings = settings
|
||||
self.client = QdrantClient(url=settings.qdrant_url)
|
||||
self.skill_graph = self._load_skill_graph()
|
||||
self.llm_client = LLMClient(settings)
|
||||
self.collection_vector_size: int | None = None
|
||||
|
||||
def ensure_ready(self) -> None:
|
||||
collections = {item.name for item in self.client.get_collections().collections}
|
||||
expected_size = self._configured_vector_size()
|
||||
if self.settings.qdrant_collection not in collections:
|
||||
self.client.create_collection(
|
||||
collection_name=self.settings.qdrant_collection,
|
||||
vectors_config=models.VectorParams(size=self.settings.vector_size, distance=models.Distance.COSINE),
|
||||
vectors_config=models.VectorParams(size=expected_size, distance=models.Distance.COSINE),
|
||||
)
|
||||
self.collection_vector_size = expected_size
|
||||
return
|
||||
info = self.client.get_collection(self.settings.qdrant_collection)
|
||||
configured_size = info.config.params.vectors.size
|
||||
self.collection_vector_size = int(configured_size)
|
||||
if self.collection_vector_size != expected_size:
|
||||
logger.warning(
|
||||
"qdrant vector size mismatch, collection=%s expected=%s actual=%s; using actual size",
|
||||
self.settings.qdrant_collection,
|
||||
expected_size,
|
||||
self.collection_vector_size,
|
||||
)
|
||||
|
||||
def health(self) -> str:
|
||||
@@ -125,14 +141,40 @@ class LightRAGAdapter:
|
||||
)
|
||||
|
||||
def _vectorize(self, text: str) -> list[float]:
|
||||
vector = [0.0 for _ in range(self.settings.vector_size)]
|
||||
if self.settings.embedding_enabled and self.settings.embedding_backend == "openai_compatible":
|
||||
try:
|
||||
embedding = self.llm_client.embedding(text)
|
||||
if embedding:
|
||||
return self._normalize_embedding(embedding)
|
||||
except Exception:
|
||||
logger.exception("embedding request failed, fallback to hash vector")
|
||||
target_size = self._active_vector_size()
|
||||
vector = [0.0 for _ in range(target_size)]
|
||||
tokens = self._tokenize(text)
|
||||
for token in tokens:
|
||||
index = hash(token) % self.settings.vector_size
|
||||
index = hash(token) % target_size
|
||||
vector[index] += 1.0
|
||||
norm = math.sqrt(sum(item * item for item in vector)) or 1.0
|
||||
return [item / norm for item in vector]
|
||||
|
||||
def _normalize_embedding(self, embedding: list[float]) -> list[float]:
|
||||
target_size = self._active_vector_size()
|
||||
vector = embedding[:target_size]
|
||||
if len(vector) < target_size:
|
||||
vector.extend([0.0] * (target_size - len(vector)))
|
||||
norm = math.sqrt(sum(item * item for item in vector)) or 1.0
|
||||
return [item / norm for item in vector]
|
||||
|
||||
def _active_vector_size(self) -> int:
|
||||
if self.collection_vector_size:
|
||||
return self.collection_vector_size
|
||||
return self._configured_vector_size()
|
||||
|
||||
def _configured_vector_size(self) -> int:
|
||||
if self.settings.embedding_enabled and self.settings.embedding_backend == "openai_compatible":
|
||||
return self.settings.embedding_vector_size
|
||||
return self.settings.vector_size
|
||||
|
||||
def _tokenize(self, text: str) -> list[str]:
|
||||
cleaned = [part.strip().lower() for part in text.replace("，", " ").replace("、", " ").replace("。", " ").split()]
|
||||
tokens = [part for part in cleaned if part]
|
||||
|
||||
23
gig-poc/apps/api/app/services/runtime_state.py
Normal file
23
gig-poc/apps/api/app/services/runtime_state.py
Normal file
@@ -0,0 +1,23 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from functools import lru_cache
|
||||
|
||||
from app.core.config import get_settings
|
||||
from app.services.ingest_queue import IngestQueue
|
||||
from app.services.match_queue import MatchQueue
|
||||
from app.services.traffic_guard import TrafficGuard
|
||||
|
||||
|
||||
@lru_cache
|
||||
def get_ingest_queue() -> IngestQueue:
|
||||
return IngestQueue(get_settings())
|
||||
|
||||
|
||||
@lru_cache
|
||||
def get_match_queue() -> MatchQueue:
|
||||
return MatchQueue(get_settings())
|
||||
|
||||
|
||||
@lru_cache
|
||||
def get_traffic_guard() -> TrafficGuard:
|
||||
return TrafficGuard(get_settings())
|
||||
108
gig-poc/apps/api/app/services/traffic_guard.py
Normal file
108
gig-poc/apps/api/app/services/traffic_guard.py
Normal file
@@ -0,0 +1,108 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import time
|
||||
from collections import deque
|
||||
from threading import Lock
|
||||
|
||||
import httpx
|
||||
|
||||
from app.core.config import Settings
|
||||
from app.core.logging import logger
|
||||
|
||||
|
||||
class TrafficGuard:
|
||||
def __init__(self, settings: Settings):
|
||||
self.settings = settings
|
||||
self._lock = Lock()
|
||||
self._minute = 0
|
||||
self._minute_count = 0
|
||||
self._open_until = 0.0
|
||||
self._events: deque[tuple[float, int]] = deque()
|
||||
self._requests = 0
|
||||
self._rate_limited = 0
|
||||
self._circuit_blocked = 0
|
||||
self._avg_latency_ms = 0.0
|
||||
self._alert_last_sent = 0.0
|
||||
|
||||
def allow(self, path: str) -> tuple[bool, str]:
|
||||
now = time.time()
|
||||
with self._lock:
|
||||
minute = int(now // 60)
|
||||
if self._minute != minute:
|
||||
self._minute = minute
|
||||
self._minute_count = 0
|
||||
if self._minute_count >= self.settings.app_rate_limit_per_minute:
|
||||
self._rate_limited += 1
|
||||
return False, "rate_limited"
|
||||
if self._open_until > now and not self._is_exempt(path):
|
||||
self._circuit_blocked += 1
|
||||
return False, "circuit_open"
|
||||
self._minute_count += 1
|
||||
self._requests += 1
|
||||
return True, "ok"
|
||||
|
||||
def record(self, status_code: int, latency_ms: float) -> None:
|
||||
now = time.time()
|
||||
with self._lock:
|
||||
self._events.append((now, status_code))
|
||||
self._avg_latency_ms = self._ema(self._avg_latency_ms, latency_ms)
|
||||
self._trim(now)
|
||||
total = len(self._events)
|
||||
if total < self.settings.app_circuit_breaker_min_requests:
|
||||
return
|
||||
errors = sum(1 for _, code in self._events if code >= 500)
|
||||
error_rate = errors / total
|
||||
if error_rate >= self.settings.app_circuit_breaker_error_rate:
|
||||
self._open_until = now + self.settings.app_circuit_breaker_cooldown_seconds
|
||||
self._send_alert(
|
||||
"app circuit opened",
|
||||
{
|
||||
"error_rate": round(error_rate, 4),
|
||||
"window_requests": total,
|
||||
"cooldown_seconds": self.settings.app_circuit_breaker_cooldown_seconds,
|
||||
},
|
||||
)
|
||||
|
||||
def snapshot(self) -> dict[str, float | int]:
|
||||
now = time.time()
|
||||
with self._lock:
|
||||
self._trim(now)
|
||||
total = len(self._events)
|
||||
errors = sum(1 for _, code in self._events if code >= 500)
|
||||
return {
|
||||
"requests_total": self._requests,
|
||||
"rate_limited_total": self._rate_limited,
|
||||
"circuit_blocked_total": self._circuit_blocked,
|
||||
"window_requests": total,
|
||||
"window_errors": errors,
|
||||
"window_error_rate": round((errors / total), 4) if total else 0.0,
|
||||
"avg_latency_ms": round(self._avg_latency_ms, 2),
|
||||
"circuit_open": 1 if self._open_until > now else 0,
|
||||
}
|
||||
|
||||
def _trim(self, now: float) -> None:
|
||||
lower = now - self.settings.app_circuit_breaker_window_seconds
|
||||
while self._events and self._events[0][0] < lower:
|
||||
self._events.popleft()
|
||||
|
||||
def _ema(self, prev: float, value: float, alpha: float = 0.2) -> float:
|
||||
if prev <= 0:
|
||||
return value
|
||||
return alpha * value + (1 - alpha) * prev
|
||||
|
||||
def _is_exempt(self, path: str) -> bool:
|
||||
return path in {"/health", "/docs", "/openapi.json", "/poc/ops/system/metrics", "/poc/ops/ai/metrics"}
|
||||
|
||||
def _send_alert(self, message: str, extra: dict) -> None:
|
||||
now = time.time()
|
||||
if now - self._alert_last_sent < 30:
|
||||
return
|
||||
self._alert_last_sent = now
|
||||
logger.warning("%s extra=%s", message, extra)
|
||||
if not self.settings.alert_webhook_url:
|
||||
return
|
||||
try:
|
||||
with httpx.Client(timeout=2.0) as client:
|
||||
client.post(self.settings.alert_webhook_url, json={"message": message, "extra": extra})
|
||||
except Exception:
|
||||
logger.exception("alert webhook send failed")
|
||||
77
gig-poc/apps/api/app/services/weight_service.py
Normal file
77
gig-poc/apps/api/app/services/weight_service.py
Normal file
@@ -0,0 +1,77 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
from pathlib import Path
|
||||
|
||||
from app.core.config import Settings
|
||||
from app.core.logging import logger
|
||||
from app.domain.schemas import MatchBreakdown
|
||||
|
||||
|
||||
class MatchWeightService:
|
||||
def __init__(self, settings: Settings):
|
||||
self.settings = settings
|
||||
self.path: Path = settings.match_weights_path
|
||||
|
||||
def default_weights(self) -> dict[str, float]:
|
||||
return {
|
||||
"skill": self.settings.score_skill_weight,
|
||||
"region": self.settings.score_region_weight,
|
||||
"time": self.settings.score_time_weight,
|
||||
"experience": self.settings.score_experience_weight,
|
||||
"reliability": self.settings.score_reliability_weight,
|
||||
}
|
||||
|
||||
def get_weights(self) -> dict[str, float]:
|
||||
weights = self.default_weights()
|
||||
if not self.path.exists():
|
||||
return self._normalize(weights)
|
||||
try:
|
||||
data = json.loads(self.path.read_text(encoding="utf-8"))
|
||||
for key in weights:
|
||||
value = data.get(key)
|
||||
if isinstance(value, (int, float)):
|
||||
weights[key] = float(value)
|
||||
except Exception:
|
||||
logger.exception("failed to read learned ranking weights, fallback to defaults")
|
||||
return self._normalize(weights)
|
||||
|
||||
def score(self, breakdown: MatchBreakdown) -> float:
|
||||
weights = self.get_weights()
|
||||
return (
|
||||
weights["skill"] * breakdown.skill_score
|
||||
+ weights["region"] * breakdown.region_score
|
||||
+ weights["time"] * breakdown.time_score
|
||||
+ weights["experience"] * breakdown.experience_score
|
||||
+ weights["reliability"] * breakdown.reliability_score
|
||||
)
|
||||
|
||||
def update_from_feedback(self, breakdown: MatchBreakdown, accepted: bool) -> dict[str, float]:
|
||||
weights = self.get_weights()
|
||||
features = {
|
||||
"skill": breakdown.skill_score,
|
||||
"region": breakdown.region_score,
|
||||
"time": breakdown.time_score,
|
||||
"experience": breakdown.experience_score,
|
||||
"reliability": breakdown.reliability_score,
|
||||
}
|
||||
target = 1.0 if accepted else 0.0
|
||||
prediction = sum(weights[name] * value for name, value in features.items())
|
||||
error = target - prediction
|
||||
lr = self.settings.ranking_learning_rate
|
||||
updated = {name: max(0.0, weights[name] + lr * error * value) for name, value in features.items()}
|
||||
normalized = self._normalize(updated)
|
||||
self._save_weights(normalized)
|
||||
return normalized
|
||||
|
||||
def _save_weights(self, weights: dict[str, float]) -> None:
|
||||
self.settings.data_dir.mkdir(parents=True, exist_ok=True)
|
||||
self.path.write_text(json.dumps(weights, ensure_ascii=False, indent=2), encoding="utf-8")
|
||||
|
||||
def _normalize(self, weights: dict[str, float]) -> dict[str, float]:
|
||||
total = sum(max(value, 0.0) for value in weights.values())
|
||||
if total <= 0:
|
||||
fallback = self.default_weights()
|
||||
total = sum(fallback.values())
|
||||
return {key: value / total for key, value in fallback.items()}
|
||||
return {key: max(value, 0.0) / total for key, value in weights.items()}
|
||||
@@ -11,6 +11,7 @@ dependencies = [
|
||||
"pydantic==2.11.3",
|
||||
"pydantic-settings==2.8.1",
|
||||
"httpx==0.28.1",
|
||||
"redis==5.2.1",
|
||||
"qdrant-client==1.14.2",
|
||||
"python-dateutil==2.9.0.post0",
|
||||
"orjson==3.10.16",
|
||||
|
||||
1
gig-poc/apps/web/src/vite-env.d.ts
vendored
Normal file
1
gig-poc/apps/web/src/vite-env.d.ts
vendored
Normal file
@@ -0,0 +1 @@
|
||||
/// <reference types="vite/client" />
|
||||
@@ -1,8 +1,98 @@
|
||||
# API 文档
|
||||
# API 文档（中文完整版）
|
||||
|
||||
## 机器可读文档（推荐作为联调基准）
|
||||
- Swagger UI：`http://127.0.0.1:8000/docs`
|
||||
- OpenAPI JSON：`http://127.0.0.1:8000/openapi.json`
|
||||
- 一键导出：
|
||||
```bash
|
||||
cd gig-poc
|
||||
sh infrastructure/scripts/export-openapi.sh
|
||||
```
|
||||
- 导出到自定义路径：
|
||||
```bash
|
||||
sh infrastructure/scripts/export-openapi.sh ./docs/openapi.prod.json
|
||||
```
|
||||
|
||||
## 通用约定
|
||||
- 基础路径：默认通过网关暴露为 `/api`，下文写的是服务内部路径（如 `/poc/...`）。
|
||||
- 数据格式：`Content-Type: application/json`。
|
||||
- 时间字段：ISO-8601 格式（示例：`2026-03-30T12:00:00+08:00`）。
|
||||
- 分数字段：大部分评分为 `0~1` 浮点数。
|
||||
- 常见错误码：
|
||||
- `400/422`：请求参数不合法（字段缺失、类型不匹配、取值超范围）。
|
||||
- `404`：查询对象不存在（如岗位 ID、工人 ID、匹配记录 ID 不存在）。
|
||||
- `500`：服务内部异常（数据库、向量检索、模型调用失败等）。
|
||||
|
||||
## 数据结构说明
|
||||
|
||||
### Salary（薪资结构）
|
||||
| 字段 | 类型 | 说明 |
|
||||
| --- | --- | --- |
|
||||
| `type` | `daily/hourly/monthly/task` | 薪资类型：日薪/时薪/月薪/按单 |
|
||||
| `amount` | `number` | 薪资金额 |
|
||||
| `currency` | `string` | 货币，默认 `CNY` |
|
||||
|
||||
### SkillScore（技能分）
|
||||
| 字段 | 类型 | 说明 |
|
||||
| --- | --- | --- |
|
||||
| `name` | `string` | 技能名称 |
|
||||
| `score` | `number` | 技能熟练度，范围 `0~1` |
|
||||
|
||||
### JobCard（岗位卡片）
|
||||
| 字段 | 类型 | 说明 |
|
||||
| --- | --- | --- |
|
||||
| `job_id` | `string` | 岗位唯一 ID |
|
||||
| `title` | `string` | 岗位标题 |
|
||||
| `category` | `string` | 岗位类别 |
|
||||
| `description` | `string` | 岗位描述 |
|
||||
| `skills` | `string[]` | 需要的技能列表 |
|
||||
| `city` | `string` | 城市 |
|
||||
| `region` | `string` | 区域 |
|
||||
| `location_detail` | `string` | 详细地址或地标 |
|
||||
| `start_time` | `datetime` | 开始时间 |
|
||||
| `duration_hours` | `number` | 工时（小时，>0） |
|
||||
| `headcount` | `number` | 需求人数（>0） |
|
||||
| `salary` | `Salary` | 薪资信息 |
|
||||
| `work_mode` | `string` | 工作模式（如兼职/全职/活动） |
|
||||
| `tags` | `string[]` | 业务标签 |
|
||||
| `confidence` | `number` | 抽取或录入置信度，范围 `0~1` |
|
||||
|
||||
### WorkerCard（工人卡片）
|
||||
| 字段 | 类型 | 说明 |
|
||||
| --- | --- | --- |
|
||||
| `worker_id` | `string` | 工人唯一 ID |
|
||||
| `name` | `string` | 姓名/昵称 |
|
||||
| `description` | `string` | 自我描述 |
|
||||
| `skills` | `SkillScore[]` | 技能及熟练度 |
|
||||
| `cities` | `string[]` | 可接单城市 |
|
||||
| `regions` | `string[]` | 可接单区域 |
|
||||
| `availability` | `string[]` | 可上岗时段（自由文本） |
|
||||
| `experience_tags` | `string[]` | 经验标签 |
|
||||
| `reliability_score` | `number` | 履约可靠性分，范围 `0~1` |
|
||||
| `profile_completion` | `number` | 档案完善度，范围 `0~1` |
|
||||
| `confidence` | `number` | 抽取或录入置信度，范围 `0~1` |
|
||||
|
||||
### MatchResult（匹配结果）
|
||||
| 字段 | 类型 | 说明 |
|
||||
| --- | --- | --- |
|
||||
| `match_id` | `string` | 匹配记录 ID |
|
||||
| `source_type` | `job_to_worker/worker_to_job` | 匹配方向 |
|
||||
| `source_id` | `string` | 发起匹配的实体 ID |
|
||||
| `target_id` | `string` | 被匹配到的实体 ID |
|
||||
| `match_score` | `number` | 综合匹配分（`0~1`） |
|
||||
| `breakdown.skill_score` | `number` | 技能匹配分 |
|
||||
| `breakdown.region_score` | `number` | 地域匹配分 |
|
||||
| `breakdown.time_score` | `number` | 时间匹配分 |
|
||||
| `breakdown.experience_score` | `number` | 经验匹配分 |
|
||||
| `breakdown.reliability_score` | `number` | 可靠性匹配分 |
|
||||
| `reasons` | `string[]` | 至少 3 条可解释理由 |
|
||||
|
||||
## 系统接口
|
||||
|
||||
### `GET /health`
|
||||
返回：
|
||||
用途：检查服务、数据库、RAG 组件是否可用。
|
||||
|
||||
返回示例：
|
||||
```json
|
||||
{
|
||||
"service": "ok",
|
||||
@@ -12,38 +102,242 @@
|
||||
}
|
||||
```
|
||||
|
||||
## 抽取接口
|
||||
### `POST /poc/extract/job`
|
||||
请求：
|
||||
字段说明：
|
||||
- `service`：API 进程状态。
|
||||
- `database`：数据库连通状态（`ok/error`）。
|
||||
- `rag`：检索增强组件状态（`ok/error`）。
|
||||
- `timestamp`：服务端当前时间。
|
||||
|
||||
### `GET /poc/ops/ai/metrics`
|
||||
用途：查看 AI 调用观测指标（限流、熔断、降级、fallback 命中率）。
|
||||
|
||||
返回示例：
|
||||
```json
|
||||
{ "text": "明天下午南山会展中心需要2个签到协助，5小时，150/人，女生优先" }
|
||||
{
|
||||
"metrics": {
|
||||
"requests_total": 12,
|
||||
"success_total": 10,
|
||||
"fail_total": 2,
|
||||
"fallback_total": 1,
|
||||
"rate_limited_total": 0,
|
||||
"circuit_open_total": 0,
|
||||
"endpoint_failover_total": 1,
|
||||
"fallback_hit_rate": 0.0833,
|
||||
"success_rate": 0.8333,
|
||||
"failure_rate": 0.1667
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### `GET /poc/ops/system/metrics`
|
||||
用途：查看全局系统护栏指标（流量限流、熔断状态、缓存命中率、异步队列状态）。
|
||||
|
||||
返回示例：
|
||||
```json
|
||||
{
|
||||
"traffic": {
|
||||
"requests_total": 1000,
|
||||
"rate_limited_total": 0,
|
||||
"circuit_blocked_total": 0,
|
||||
"window_requests": 120,
|
||||
"window_errors": 3,
|
||||
"window_error_rate": 0.025,
|
||||
"avg_latency_ms": 35.4,
|
||||
"circuit_open": 0
|
||||
},
|
||||
"cache": {
|
||||
"backend": "redis",
|
||||
"match_hit_rate": 0.62,
|
||||
"query_hit_rate": 0.73,
|
||||
"match_size": 320,
|
||||
"query_size": 800
|
||||
},
|
||||
"ingest_queue": {
|
||||
"queued": 0,
|
||||
"processed": 1200,
|
||||
"failed": 2
|
||||
},
|
||||
"match_queue": {
|
||||
"queued": 2,
|
||||
"processed": 3400,
|
||||
"failed": 7
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
## 抽取接口
|
||||
|
||||
### `POST /poc/extract/job`
|
||||
用途：将岗位自然语言文本抽取为结构化 `JobCard`。
|
||||
|
||||
请求体：
|
||||
```json
|
||||
{
|
||||
"text": "明天下午南山会展中心需要2个签到协助，5小时，150/人，女生优先"
|
||||
}
|
||||
```
|
||||
|
||||
请求字段说明：
|
||||
- `text`：待抽取文本，最小长度 5。
|
||||
|
||||
返回结构：`ExtractResponse`
|
||||
```json
|
||||
{
|
||||
"success": true,
|
||||
"data": {
|
||||
"job_id": "job_demo_001",
|
||||
"title": "活动签到协助",
|
||||
"category": "会展活动",
|
||||
"description": "南山会展中心活动签到协助",
|
||||
"skills": ["签到", "引导"],
|
||||
"city": "深圳",
|
||||
"region": "南山",
|
||||
"location_detail": "南山会展中心",
|
||||
"start_time": "2026-04-01T14:00:00+08:00",
|
||||
"duration_hours": 5,
|
||||
"headcount": 2,
|
||||
"salary": { "type": "daily", "amount": 150, "currency": "CNY" },
|
||||
"work_mode": "兼职",
|
||||
"tags": ["女生优先"],
|
||||
"confidence": 0.88
|
||||
},
|
||||
"errors": [],
|
||||
"missing_fields": []
|
||||
}
|
||||
```
|
||||
|
||||
字段说明：
|
||||
- `success`：是否抽取成功。
|
||||
- `data`：抽取出的结构化岗位对象；失败时可能为 `null`。
|
||||
- `errors`：错误信息列表。
|
||||
- `missing_fields`：缺失字段列表，便于前端二次补录。
|
||||
|
||||
### `POST /poc/extract/worker`
|
||||
请求：
|
||||
用途：将工人自然语言文本抽取为结构化 `WorkerCard`。
|
||||
|
||||
请求体：
|
||||
```json
|
||||
{ "text": "我做过商场促销和活动签到，也能做登记和引导，周末都能接，福田南山都方便。" }
|
||||
{
|
||||
"text": "我做过商场促销和活动签到，也能做登记和引导，周末都能接，福田南山都方便。"
|
||||
}
|
||||
```
|
||||
|
||||
返回结构：同 `ExtractResponse`，其中 `data` 为 `WorkerCard`。
|
||||
|
||||
说明：
|
||||
- 适合把聊天文本/简历摘要快速转成可入库结构。
|
||||
- 若模型无法识别关键字段，会在 `missing_fields` 中给出提示。
|
||||
|
||||
## 入库接口
|
||||
|
||||
### `POST /poc/ingest/job`
|
||||
用途：写入或更新岗位卡片（同时更新检索索引）。
|
||||
|
||||
请求体：
|
||||
```json
|
||||
{ "job": { "...": "JobCard" } }
|
||||
{
|
||||
"job": {
|
||||
"job_id": "job_001",
|
||||
"title": "活动签到",
|
||||
"category": "会展活动",
|
||||
"description": "负责活动签到与引导",
|
||||
"skills": ["签到", "沟通"],
|
||||
"city": "深圳",
|
||||
"region": "福田",
|
||||
"location_detail": "会展中心",
|
||||
"start_time": "2026-04-02T09:00:00+08:00",
|
||||
"duration_hours": 8,
|
||||
"headcount": 3,
|
||||
"salary": { "type": "daily", "amount": 180, "currency": "CNY" },
|
||||
"work_mode": "兼职",
|
||||
"tags": ["展会"],
|
||||
"confidence": 0.95
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
返回：返回入库后的 `JobCard`（通常与请求体一致）。
|
||||
|
||||
### `POST /poc/ingest/worker`
|
||||
用途：写入或更新工人卡片（同时更新检索索引）。
|
||||
|
||||
请求体：
|
||||
```json
|
||||
{ "worker": { "...": "WorkerCard" } }
|
||||
{
|
||||
"worker": {
|
||||
"worker_id": "worker_001",
|
||||
"name": "张三",
|
||||
"description": "有活动执行经验",
|
||||
"skills": [
|
||||
{ "name": "签到", "score": 0.9 },
|
||||
{ "name": "引导", "score": 0.8 }
|
||||
],
|
||||
"cities": ["深圳"],
|
||||
"regions": ["福田", "南山"],
|
||||
"availability": ["周末全天"],
|
||||
"experience_tags": ["会展", "地推"],
|
||||
"reliability_score": 0.92,
|
||||
"profile_completion": 0.86,
|
||||
"confidence": 0.93
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
返回：返回入库后的 `WorkerCard`（通常与请求体一致）。
|
||||
|
||||
### `POST /poc/ingest/job/async`
|
||||
用途：异步岗位入库，快速返回任务 ID，不阻塞主请求。
|
||||
|
||||
返回示例：
|
||||
```json
|
||||
{
|
||||
"task_id": "queue_xxx",
|
||||
"status": "queued"
|
||||
}
|
||||
```
|
||||
|
||||
### `POST /poc/ingest/worker/async`
|
||||
用途：异步工人入库，快速返回任务 ID，不阻塞主请求。
|
||||
|
||||
返回结构同 `POST /poc/ingest/job/async`。
|
||||
|
||||
### `GET /poc/ingest/queue/{task_id}`
|
||||
用途：查询异步入库任务状态。
|
||||
|
||||
可能状态：
|
||||
- `queued`
|
||||
- `processing`
|
||||
- `done`
|
||||
- `failed`
|
||||
- `not_found`
|
||||
|
||||
### `POST /poc/ingest/bootstrap`
|
||||
说明：导入样本数据、词表、Qdrant 检索索引数据。
|
||||
用途：导入内置样本数据（岗位、工人、技能、类目、区域）并构建检索数据。
|
||||
|
||||
请求体：无。
|
||||
|
||||
返回示例：
|
||||
```json
|
||||
{
|
||||
"jobs": 100,
|
||||
"workers": 300,
|
||||
"skills": 120,
|
||||
"categories": 20,
|
||||
"regions": 50
|
||||
}
|
||||
```
|
||||
|
||||
说明：
|
||||
- 适合开发环境初始化。
|
||||
- 重复执行会触发 upsert 逻辑（覆盖同 ID 数据）。
|
||||
|
||||
## 匹配接口
|
||||
|
||||
### `POST /poc/match/workers`
|
||||
支持 `job_id` 或内联 `job`：
|
||||
用途：以岗位为源，匹配合适工人。
|
||||
|
||||
请求体（二选一）：
|
||||
1. 传 `job_id`（按已入库岗位匹配）：
|
||||
```json
|
||||
{
|
||||
"job_id": "job_001",
|
||||
@@ -51,8 +345,51 @@
|
||||
}
|
||||
```
|
||||
|
||||
2. 传内联 `job`（不依赖入库）：
|
||||
```json
|
||||
{
|
||||
"job": { "...": "JobCard" },
|
||||
"top_n": 10
|
||||
}
|
||||
```
|
||||
|
||||
字段说明：
|
||||
- `job_id`：岗位 ID。
|
||||
- `job`：完整岗位对象。
|
||||
- `top_n`：返回条数，范围 `1~50`，默认 `10`。
|
||||
- `job_id` 与 `job` 至少提供一个。
|
||||
|
||||
返回：
|
||||
```json
|
||||
{
|
||||
"items": [
|
||||
{
|
||||
"match_id": "match_001",
|
||||
"source_type": "job_to_worker",
|
||||
"source_id": "job_001",
|
||||
"target_id": "worker_007",
|
||||
"match_score": 0.87,
|
||||
"breakdown": {
|
||||
"skill_score": 0.9,
|
||||
"region_score": 1.0,
|
||||
"time_score": 0.8,
|
||||
"experience_score": 0.85,
|
||||
"reliability_score": 0.8
|
||||
},
|
||||
"reasons": ["技能高度匹配", "同区域可到岗", "有同类活动经验"]
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
错误说明：
|
||||
- 当 `job_id` 不存在且未传 `job` 时，返回 `404`，提示“岗位不存在”。
|
||||
|
||||
### `POST /poc/match/jobs`
|
||||
支持 `worker_id` 或内联 `worker`：
|
||||
用途：以工人为源，匹配合适岗位。
|
||||
|
||||
请求体（二选一）：
|
||||
1. 传 `worker_id`：
|
||||
```json
|
||||
{
|
||||
"worker_id": "worker_001",
|
||||
@@ -60,16 +397,212 @@
|
||||
}
|
||||
```
|
||||
|
||||
2. 传内联 `worker`：
|
||||
```json
|
||||
{
|
||||
"worker": { "...": "WorkerCard" },
|
||||
"top_n": 10
|
||||
}
|
||||
```
|
||||
|
||||
字段约束：
|
||||
- `worker_id` 与 `worker` 至少提供一个。
|
||||
- `top_n` 范围 `1~50`，默认 `10`。
|
||||
|
||||
返回：`MatchResponse`，结构同上，`source_type` 为 `worker_to_job`。
|
||||
|
||||
错误说明：
|
||||
- 当 `worker_id` 不存在且未传 `worker` 时，返回 `404`，提示“工人不存在”。
|
||||
|
||||
### `POST /poc/match/workers/async`
|
||||
用途：岗位异步匹配工人（削峰入口），快速返回任务 ID。
|
||||
|
||||
请求体：
|
||||
```json
|
||||
{
|
||||
"job_id": "job_001",
|
||||
"top_n": 10
|
||||
}
|
||||
```
|
||||
|
||||
返回示例：
|
||||
```json
|
||||
{
|
||||
"task_id": "mq_xxx",
|
||||
"status": "queued"
|
||||
}
|
||||
```
|
||||
|
||||
### `POST /poc/match/jobs/async`
|
||||
用途：工人异步匹配岗位（削峰入口），快速返回任务 ID。
|
||||
|
||||
请求体：
|
||||
```json
|
||||
{
|
||||
"worker_id": "worker_001",
|
||||
"top_n": 10
|
||||
}
|
||||
```
|
||||
|
||||
返回结构同 `POST /poc/match/workers/async`。
|
||||
|
||||
### `GET /poc/match/queue/{task_id}`
|
||||
用途：查询异步匹配任务状态，完成后返回 `items` 结果集。
|
||||
|
||||
可能状态：
|
||||
- `queued`
|
||||
- `processing`
|
||||
- `done`
|
||||
- `failed`
|
||||
- `not_found`
|
||||
|
||||
### `GET /poc/match/explain/{match_id}`
|
||||
返回具体匹配明细与理由。
|
||||
用途：查询单条匹配记录详情与解释理由。
|
||||
|
||||
路径参数：
|
||||
- `match_id`：匹配记录 ID。
|
||||
|
||||
返回：
|
||||
```json
|
||||
{
|
||||
"match": {
|
||||
"match_id": "match_001",
|
||||
"source_type": "job_to_worker",
|
||||
"source_id": "job_001",
|
||||
"target_id": "worker_007",
|
||||
"match_score": 0.87,
|
||||
"breakdown": {
|
||||
"skill_score": 0.9,
|
||||
"region_score": 1.0,
|
||||
"time_score": 0.8,
|
||||
"experience_score": 0.85,
|
||||
"reliability_score": 0.8
|
||||
},
|
||||
"reasons": ["技能高度匹配", "同区域可到岗", "有同类活动经验"]
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
错误说明：
|
||||
- 找不到匹配记录时返回 `404`，提示“匹配记录不存在”。
|
||||
|
||||
### `POST /poc/match/feedback`
|
||||
用途：提交匹配反馈（接受/拒绝），用于在线更新排序权重。
|
||||
|
||||
请求体：
|
||||
```json
|
||||
{
|
||||
"match_id": "match_001",
|
||||
"accepted": true
|
||||
}
|
||||
```
|
||||
|
||||
返回：
|
||||
```json
|
||||
{
|
||||
"weights": {
|
||||
"skill": 0.36,
|
||||
"region": 0.21,
|
||||
"time": 0.14,
|
||||
"experience": 0.14,
|
||||
"reliability": 0.15
|
||||
},
|
||||
"learning_enabled": true
|
||||
}
|
||||
```
|
||||
|
||||
错误说明：
|
||||
- `match_id` 不存在时返回 `404`，提示“匹配记录不存在”。
|
||||
|
||||
### `GET /poc/match/weights`
|
||||
用途：查看当前生效排序权重（默认权重或学习后的权重）。
|
||||
|
||||
返回结构同 `POST /poc/match/feedback`。
|
||||
|
||||
## 查询接口
|
||||
### `GET /poc/jobs`
|
||||
### `GET /poc/workers`
|
||||
### `GET /poc/jobs/{job_id}`
|
||||
### `GET /poc/workers/{worker_id}`
|
||||
|
||||
## 交接说明
|
||||
- 抽取接口返回 `success/data/errors/missing_fields`，方便后续切换更强 LLM 时做错误回退。
|
||||
- 匹配接口输出 `breakdown` 五维打分，可直接给后续运营、策略或模型团队继续调权。
|
||||
- `packages/shared-types/src/index.ts` 保留了前端可复用类型定义。
|
||||
### `GET /poc/jobs`
|
||||
用途：分页前的基础列表查询（当前返回全量）。
|
||||
|
||||
返回：
|
||||
```json
|
||||
{
|
||||
"items": [{ "...": "JobCard(JSON)" }],
|
||||
"total": 100
|
||||
}
|
||||
```
|
||||
|
||||
### `GET /poc/workers`
|
||||
用途：查询工人列表（当前返回全量）。
|
||||
|
||||
返回：
|
||||
```json
|
||||
{
|
||||
"items": [{ "...": "WorkerCard(JSON)" }],
|
||||
"total": 300
|
||||
}
|
||||
```
|
||||
|
||||
### `GET /poc/jobs/{job_id}`
|
||||
用途：根据 ID 查询单个岗位。
|
||||
|
||||
路径参数：
|
||||
- `job_id`：岗位 ID。
|
||||
|
||||
返回：`JobCard`。
|
||||
|
||||
错误说明：
|
||||
- ID 不存在返回 `404`，提示“岗位不存在”。
|
||||
|
||||
### `GET /poc/workers/{worker_id}`
|
||||
用途：根据 ID 查询单个工人。
|
||||
|
||||
路径参数：
|
||||
- `worker_id`：工人 ID。
|
||||
|
||||
返回：`WorkerCard`。
|
||||
|
||||
错误说明：
|
||||
- ID 不存在返回 `404`，提示“工人不存在”。
|
||||
|
||||
## 交接建议
|
||||
- 以 `docs/openapi.json` 作为机器契约，`docs/API.md` 作为业务语义解释。
|
||||
- 前端与测试联调时，优先校验：
|
||||
- 抽取失败时 `errors/missing_fields` 是否按预期返回。
|
||||
- 匹配结果 `breakdown` 五维分是否完整。
|
||||
- `top_n` 边界值（`1`、`50`、`>50`）的校验行为。
|
||||
|
||||
## 升级配置说明
|
||||
- 抽取增强（schema-aware 重试）：
|
||||
- `EXTRACTION_LLM_MAX_RETRIES`：LLM 校验失败后的修复重试次数，默认 `2`。
|
||||
- 检索 embedding 可配置：
|
||||
- `EMBEDDING_ENABLED`：是否启用正式 embedding，默认 `false`。
|
||||
- `EMBEDDING_BACKEND`：`hash` 或 `openai_compatible`。
|
||||
- `EMBEDDING_BASE_URL` / `EMBEDDING_API_KEY` / `EMBEDDING_MODEL`：embedding 服务配置。
|
||||
- `EMBEDDING_VECTOR_SIZE`：embedding 维度（需与 Qdrant 集合维度一致）。
|
||||
- 排序在线学习：
|
||||
- `RANKING_LEARNING_ENABLED`：是否启用反馈学习，默认 `true`。
|
||||
- `RANKING_LEARNING_RATE`：在线更新学习率，默认 `0.08`。
|
||||
- 权重持久化文件：`data/match_weights.json`。
|
||||
- 全局稳定性护栏：
|
||||
- `APP_RATE_LIMIT_PER_MINUTE`：全局每分钟请求上限。
|
||||
- `APP_CIRCUIT_BREAKER_ERROR_RATE`：窗口 5xx 错误率触发阈值。
|
||||
- `APP_CIRCUIT_BREAKER_MIN_REQUESTS`：熔断判定最小请求数。
|
||||
- `APP_CIRCUIT_BREAKER_WINDOW_SECONDS`：错误率统计窗口。
|
||||
- `APP_CIRCUIT_BREAKER_COOLDOWN_SECONDS`：熔断冷却时长。
|
||||
- `ALERT_WEBHOOK_URL`：告警 webhook 地址（可选）。
|
||||
- 异步队列与缓存：
|
||||
- `INGEST_ASYNC_ENABLED`：是否启用异步入库队列。
|
||||
- `INGEST_QUEUE_MAX_SIZE`：队列最大长度。
|
||||
- `MATCH_ASYNC_ENABLED`：是否启用异步匹配队列。
|
||||
- `MATCH_QUEUE_MAX_SIZE`：异步匹配队列最大长度。
|
||||
- `MATCH_CACHE_ENABLED`：是否启用匹配缓存。
|
||||
- `MATCH_CACHE_TTL_SECONDS`：匹配缓存有效期。
|
||||
- `QUERY_CACHE_ENABLED`：是否启用查询缓存。
|
||||
- `QUERY_CACHE_TTL_SECONDS`：查询缓存有效期。
|
||||
- `CACHE_BACKEND`：缓存后端 `memory/redis`。
|
||||
- `REDIS_URL`：Redis 连接地址。
|
||||
- 数据库连接池：
|
||||
- `DATABASE_POOL_SIZE`：连接池大小。
|
||||
- `DATABASE_MAX_OVERFLOW`：溢出连接数。
|
||||
- `DATABASE_POOL_TIMEOUT`：获取连接超时秒数。
|
||||
|
||||
19
gig-poc/docs/CAPACITY_BASELINE.md
Normal file
19
gig-poc/docs/CAPACITY_BASELINE.md
Normal file
@@ -0,0 +1,19 @@
|
||||
# 容量基线（自动生成）
|
||||
|
||||
- 生成时间: 2026-03-31 14:36:58 +0800
|
||||
- API_BASE: http://127.0.0.1:8000
|
||||
- TOTAL_REQUESTS: 80
|
||||
- CONCURRENCY: 20
|
||||
|
||||
| 场景 | 成功率 | RPS | 平均延迟(ms) | P95(ms) | P99(ms) |
|
||||
| --- | --- | --- | --- | --- | --- |
|
||||
| health | 1.0 | 19.34 | 978.98 | 1434.66 | 1544.06 |
|
||||
| jobs | 1.0 | 95.39 | 197.95 | 409.12 | 424.99 |
|
||||
| match_workers | 1.0 | 20.81 | 913.73 | 1975.6 | 2118.65 |
|
||||
| match_jobs | 1.0 | 19.88 | 975.29 | 2001.08 | 2147.74 |
|
||||
| match_workers_cached | 1.0 | 23.52 | 819.62 | 1220.26 | 1331.26 |
|
||||
| match_jobs_cached | 1.0 | 25.21 | 759.14 | 1077.45 | 1200.4 |
|
||||
| match_workers_async | 1.0 | 211.09 | 89.04 | 151.04 | 158.89 |
|
||||
| match_jobs_async | 1.0 | 221.04 | 83.96 | 143.35 | 162.95 |
|
||||
|
||||
> 建议：该基线仅代表当前单机/当前数据量下表现，发布前请在目标环境按 2x/5x 峰值复测。
|
||||
@@ -5,6 +5,12 @@
|
||||
cd gig-poc
|
||||
sh infrastructure/scripts/dev-up.sh
|
||||
```
|
||||
默认会自动完成：
|
||||
- 启动容器并健康检查
|
||||
- bootstrap 样本数据
|
||||
- 闭环验收（抽取 -> 入库 -> 匹配 -> 解释）
|
||||
- 导出 `docs/openapi.json`
|
||||
- 可选压测并生成 `docs/CAPACITY_BASELINE.md`（`RUN_BASELINE_ON_UP=true`）
|
||||
|
||||
## 演示步骤
|
||||
1. 打开 `http://127.0.0.1:5173`
|
||||
@@ -21,6 +27,42 @@ cd gig-poc
|
||||
sh infrastructure/scripts/prod-up.sh
|
||||
```
|
||||
|
||||
## 生产环境停止
|
||||
```bash
|
||||
cd gig-poc
|
||||
sh infrastructure/scripts/prod-down.sh
|
||||
```
|
||||
|
||||
## OpenAPI 交接文件导出
|
||||
```bash
|
||||
cd gig-poc
|
||||
sh infrastructure/scripts/export-openapi.sh
|
||||
```
|
||||
|
||||
## OpenAPI 固化入库（离线）
|
||||
```bash
|
||||
cd gig-poc
|
||||
sh infrastructure/scripts/freeze-openapi.sh
|
||||
```
|
||||
|
||||
## 一键闭环验收（可单独执行）
|
||||
```bash
|
||||
cd gig-poc
|
||||
sh infrastructure/scripts/acceptance-e2e.sh
|
||||
```
|
||||
|
||||
## 容量基线压测（可单独执行）
|
||||
```bash
|
||||
cd gig-poc
|
||||
sh infrastructure/scripts/load-baseline.sh
|
||||
```
|
||||
|
||||
## 高并发演示建议
|
||||
1. 同步匹配：调用 `POST /poc/match/workers` 观察实时结果。
|
||||
2. 异步匹配削峰：调用 `POST /poc/match/workers/async` 获取 `task_id`。
|
||||
3. 轮询结果：调用 `GET /poc/match/queue/{task_id}` 直到 `status=done`。
|
||||
4. 打开 `GET /poc/ops/system/metrics` 观察缓存命中率、队列积压和限流熔断状态。
|
||||
|
||||
## 演示建议
|
||||
- 先演示系统状态页，确认健康与 bootstrap 正常
|
||||
- 再演示岗位找人、人找岗位两个闭环
|
||||
|
||||
@@ -39,10 +39,45 @@
|
||||
- `LLM_BASE_URL`：OpenAI 兼容接口地址
|
||||
- `LLM_API_KEY`：模型服务密钥
|
||||
- `LLM_MODEL`：模型名称
|
||||
- `LLM_FALLBACK_BASE_URLS`：LLM 备用端点列表（JSON 数组）
|
||||
- `AI_RATE_LIMIT_PER_MINUTE`：AI 请求每分钟限流阈值
|
||||
- `AI_CIRCUIT_BREAKER_FAIL_THRESHOLD`：熔断触发失败次数
|
||||
- `AI_CIRCUIT_BREAKER_COOLDOWN_SECONDS`：熔断冷却秒数
|
||||
- `EMBEDDING_ENABLED`：是否启用正式 embedding
|
||||
- `EMBEDDING_BACKEND`：`hash` 或 `openai_compatible`
|
||||
- `EMBEDDING_BASE_URL` / `EMBEDDING_API_KEY` / `EMBEDDING_MODEL`：embedding 配置
|
||||
- `INGEST_ASYNC_ENABLED`：是否启用异步入库队列
|
||||
- `INGEST_QUEUE_MAX_SIZE`：异步队列最大长度
|
||||
- `MATCH_CACHE_ENABLED`：是否启用匹配缓存
|
||||
- `MATCH_CACHE_TTL_SECONDS`：匹配缓存 TTL（秒）
|
||||
- `QUERY_CACHE_ENABLED`：是否启用查询缓存（列表与详情）
|
||||
- `QUERY_CACHE_TTL_SECONDS`：查询缓存 TTL（秒）
|
||||
- `CACHE_BACKEND`：缓存后端，`memory` 或 `redis`
|
||||
- `REDIS_URL`：Redis 连接串
|
||||
- `APP_RATE_LIMIT_PER_MINUTE`：全局请求限流阈值
|
||||
- `APP_CIRCUIT_BREAKER_*`：全局熔断参数（错误率、窗口、冷却）
|
||||
- `ALERT_WEBHOOK_URL`：告警 webhook（可选）
|
||||
- `DATABASE_POOL_SIZE` / `DATABASE_MAX_OVERFLOW` / `DATABASE_POOL_TIMEOUT`：数据库连接池参数
|
||||
- `MATCH_ASYNC_ENABLED`：是否启用异步匹配队列
|
||||
- `MATCH_QUEUE_MAX_SIZE`：异步匹配队列最大长度
|
||||
|
||||
## 启动方式
|
||||
1. `cd gig-poc`
|
||||
2. `sh infrastructure/scripts/dev-up.sh`
|
||||
3. 默认会自动执行：
|
||||
- 健康检查 + bootstrap
|
||||
- 一键闭环验收脚本（抽取 -> 入库 -> 匹配 -> 解释）
|
||||
- 导出 `docs/openapi.json`
|
||||
4. 可选开启容量基线压测：
|
||||
- `RUN_BASELINE_ON_UP=true sh infrastructure/scripts/dev-up.sh`
|
||||
|
||||
## 生产环境启动/停止
|
||||
- 启动：`sh infrastructure/scripts/prod-up.sh`
|
||||
- 停止：`sh infrastructure/scripts/prod-down.sh`
|
||||
- 可选环境变量：
|
||||
- `WEB_PORT`（默认 `80`）
|
||||
- `API_PORT`（默认 `8000`）
|
||||
- `BOOTSTRAP_ON_UP`（默认 `true`，可设置为 `false` 跳过样本初始化）
|
||||
|
||||
## 样本导入方式
|
||||
`dev-up.sh` 会在健康检查通过后自动触发 `/poc/ingest/bootstrap`，导入 100 岗位、300 工人和词表。
|
||||
@@ -50,6 +85,11 @@
|
||||
## API 地址
|
||||
- `http://127.0.0.1:8000`
|
||||
- OpenAPI：`http://127.0.0.1:8000/docs`
|
||||
- OpenAPI JSON 导出：`sh infrastructure/scripts/export-openapi.sh`
|
||||
- OpenAPI 固化（离线生成并入库）：`sh infrastructure/scripts/freeze-openapi.sh`
|
||||
- AI 观测接口：`GET /poc/ops/ai/metrics`
|
||||
- 系统观测接口：`GET /poc/ops/system/metrics`
|
||||
- 异步匹配接口：`POST /poc/match/workers/async`、`POST /poc/match/jobs/async`、`GET /poc/match/queue/{task_id}`
|
||||
|
||||
## 前端访问地址
|
||||
- `http://127.0.0.1:5173`
|
||||
@@ -61,6 +101,53 @@
|
||||
4. 点击入库并匹配岗位
|
||||
5. 在系统状态页执行健康检查和样本导入
|
||||
|
||||
## 一键闭环验收
|
||||
```bash
|
||||
cd gig-poc
|
||||
sh infrastructure/scripts/acceptance-e2e.sh
|
||||
```
|
||||
|
||||
该脚本会自动验证两条链路：
|
||||
- 岗位文本抽取 -> 岗位入库 -> 岗位匹配工人 -> 匹配解释
|
||||
- 工人文本抽取 -> 工人入库 -> 工人匹配岗位 -> 匹配解释
|
||||
|
||||
## 容量基线压测
|
||||
```bash
|
||||
cd gig-poc
|
||||
sh infrastructure/scripts/load-baseline.sh
|
||||
```
|
||||
|
||||
输出文件：
|
||||
- `docs/CAPACITY_BASELINE.md`
|
||||
|
||||
可选参数：
|
||||
- `TOTAL_REQUESTS`（默认 `400`）
|
||||
- `CONCURRENCY`（默认 `40`）
|
||||
|
||||
## 规模化建议（上线前）
|
||||
- 应用层：开启多实例部署（建议至少 2 个 API 实例）并接入负载均衡。
|
||||
- 数据层：PostgreSQL、Qdrant 使用托管或主从/集群形态，避免单点。
|
||||
- 链路层：优先走异步入库接口（`/poc/ingest/*/async`）吸收突发写流量。
|
||||
- 匹配层：高峰请求优先走异步匹配接口（`/poc/match/*/async`）做削峰。
|
||||
- 观测层：接入 `/poc/ops/system/metrics` 与 `/poc/ops/ai/metrics` 到监控告警系统。
|
||||
- 发布层：每次发布前更新 `docs/openapi.json` 与 `docs/CAPACITY_BASELINE.md`。
|
||||
|
||||
## K8s 扩容部署（基础模板）
|
||||
目录：`infrastructure/k8s`
|
||||
|
||||
```bash
|
||||
cd gig-poc
|
||||
kubectl apply -k infrastructure/k8s
|
||||
```
|
||||
|
||||
包含资源：
|
||||
- API Deployment + Service + HPA（默认 3~20 副本）
|
||||
- Web Deployment + Service + HPA（默认 2~10 副本）
|
||||
- Redis Deployment + Service
|
||||
- Ingress 示例路由
|
||||
|
||||
详细策略说明见：`docs/SCALING.md`
|
||||
|
||||
## 已实现范围
|
||||
- 岗位抽取
|
||||
- 工人抽取
|
||||
|
||||
19
gig-poc/docs/SCALING.md
Normal file
19
gig-poc/docs/SCALING.md
Normal file
@@ -0,0 +1,19 @@
|
||||
# 扩容与高 DAU 策略
|
||||
|
||||
## 当前能力
|
||||
- API/Web 提供 K8s 多副本与 HPA 模板：`infrastructure/k8s`
|
||||
- Redis 缓存后端支持：热点匹配与查询链路缓存
|
||||
- 异步队列：入库与匹配都支持异步削峰
|
||||
- 观测接口：`/poc/ops/system/metrics`、`/poc/ops/ai/metrics`
|
||||
|
||||
## 推荐上线形态
|
||||
1. API 多副本（>=3）+ HPA（3~20）
|
||||
2. Web 多副本（>=2）+ HPA（2~10）
|
||||
3. Redis 独立高可用（哨兵或托管）
|
||||
4. PostgreSQL、Qdrant 使用托管或主从/集群
|
||||
5. 异步接口承接高峰写流量与匹配重算
|
||||
|
||||
## 发布前门槛
|
||||
- 运行 `sh infrastructure/scripts/load-baseline.sh`
|
||||
- 更新并提交 `docs/CAPACITY_BASELINE.md`
|
||||
- 验证 P95/P99、成功率和队列积压指标
|
||||
1
gig-poc/docs/openapi.json
Normal file
1
gig-poc/docs/openapi.json
Normal file
File diff suppressed because one or more lines are too long
@@ -19,6 +19,13 @@ services:
|
||||
volumes:
|
||||
- qdrant_prod_data:/qdrant/storage
|
||||
|
||||
redis:
|
||||
image: docker.m.daocloud.io/library/redis:7-alpine
|
||||
restart: unless-stopped
|
||||
command: ["redis-server", "--appendonly", "yes"]
|
||||
volumes:
|
||||
- redis_prod_data:/data
|
||||
|
||||
api:
|
||||
build:
|
||||
context: ..
|
||||
@@ -33,9 +40,28 @@ services:
|
||||
LLM_BASE_URL: ${LLM_BASE_URL:-}
|
||||
LLM_API_KEY: ${LLM_API_KEY:-}
|
||||
LLM_MODEL: ${LLM_MODEL:-gpt-5.4}
|
||||
CACHE_BACKEND: ${CACHE_BACKEND:-redis}
|
||||
REDIS_URL: ${REDIS_URL:-redis://redis:6379/0}
|
||||
INGEST_ASYNC_ENABLED: ${INGEST_ASYNC_ENABLED:-true}
|
||||
MATCH_ASYNC_ENABLED: ${MATCH_ASYNC_ENABLED:-true}
|
||||
MATCH_CACHE_ENABLED: ${MATCH_CACHE_ENABLED:-true}
|
||||
MATCH_CACHE_TTL_SECONDS: ${MATCH_CACHE_TTL_SECONDS:-30}
|
||||
QUERY_CACHE_ENABLED: ${QUERY_CACHE_ENABLED:-true}
|
||||
QUERY_CACHE_TTL_SECONDS: ${QUERY_CACHE_TTL_SECONDS:-20}
|
||||
APP_RATE_LIMIT_PER_MINUTE: ${APP_RATE_LIMIT_PER_MINUTE:-1200}
|
||||
APP_CIRCUIT_BREAKER_ERROR_RATE: ${APP_CIRCUIT_BREAKER_ERROR_RATE:-0.5}
|
||||
APP_CIRCUIT_BREAKER_MIN_REQUESTS: ${APP_CIRCUIT_BREAKER_MIN_REQUESTS:-50}
|
||||
APP_CIRCUIT_BREAKER_WINDOW_SECONDS: ${APP_CIRCUIT_BREAKER_WINDOW_SECONDS:-60}
|
||||
APP_CIRCUIT_BREAKER_COOLDOWN_SECONDS: ${APP_CIRCUIT_BREAKER_COOLDOWN_SECONDS:-30}
|
||||
DATABASE_POOL_SIZE: ${DATABASE_POOL_SIZE:-20}
|
||||
DATABASE_MAX_OVERFLOW: ${DATABASE_MAX_OVERFLOW:-30}
|
||||
DATABASE_POOL_TIMEOUT: ${DATABASE_POOL_TIMEOUT:-30}
|
||||
depends_on:
|
||||
- postgres
|
||||
- qdrant
|
||||
- redis
|
||||
ports:
|
||||
- "${API_PORT:-8000}:8000"
|
||||
|
||||
web:
|
||||
build:
|
||||
@@ -50,3 +76,4 @@ services:
|
||||
volumes:
|
||||
postgres_prod_data:
|
||||
qdrant_prod_data:
|
||||
redis_prod_data:
|
||||
|
||||
@@ -26,6 +26,14 @@ services:
|
||||
ports:
|
||||
- "6333:6333"
|
||||
|
||||
redis:
|
||||
image: docker.m.daocloud.io/library/redis:7-alpine
|
||||
command: ["redis-server", "--appendonly", "yes"]
|
||||
volumes:
|
||||
- redis_data:/data
|
||||
ports:
|
||||
- "6379:6379"
|
||||
|
||||
api:
|
||||
build:
|
||||
context: ..
|
||||
@@ -36,11 +44,29 @@ services:
|
||||
QDRANT_URL: http://qdrant:6333
|
||||
LOG_LEVEL: INFO
|
||||
LLM_ENABLED: "false"
|
||||
CACHE_BACKEND: "redis"
|
||||
REDIS_URL: redis://redis:6379/0
|
||||
INGEST_ASYNC_ENABLED: "true"
|
||||
MATCH_ASYNC_ENABLED: "true"
|
||||
MATCH_CACHE_ENABLED: "true"
|
||||
MATCH_CACHE_TTL_SECONDS: "30"
|
||||
QUERY_CACHE_ENABLED: "true"
|
||||
QUERY_CACHE_TTL_SECONDS: "20"
|
||||
APP_RATE_LIMIT_PER_MINUTE: "1200"
|
||||
APP_CIRCUIT_BREAKER_ERROR_RATE: "0.5"
|
||||
APP_CIRCUIT_BREAKER_MIN_REQUESTS: "50"
|
||||
APP_CIRCUIT_BREAKER_WINDOW_SECONDS: "60"
|
||||
APP_CIRCUIT_BREAKER_COOLDOWN_SECONDS: "30"
|
||||
DATABASE_POOL_SIZE: "20"
|
||||
DATABASE_MAX_OVERFLOW: "30"
|
||||
DATABASE_POOL_TIMEOUT: "30"
|
||||
depends_on:
|
||||
postgres:
|
||||
condition: service_healthy
|
||||
qdrant:
|
||||
condition: service_started
|
||||
redis:
|
||||
condition: service_started
|
||||
ports:
|
||||
- "8000:8000"
|
||||
|
||||
@@ -57,3 +83,4 @@ services:
|
||||
volumes:
|
||||
postgres_data:
|
||||
qdrant_data:
|
||||
redis_data:
|
||||
|
||||
90
gig-poc/infrastructure/k8s/api.yaml
Normal file
90
gig-poc/infrastructure/k8s/api.yaml
Normal file
@@ -0,0 +1,90 @@
|
||||
apiVersion: apps/v1
|
||||
kind: Deployment
|
||||
metadata:
|
||||
name: gig-poc-api
|
||||
namespace: gig-poc
|
||||
spec:
|
||||
replicas: 3
|
||||
selector:
|
||||
matchLabels:
|
||||
app: gig-poc-api
|
||||
template:
|
||||
metadata:
|
||||
labels:
|
||||
app: gig-poc-api
|
||||
spec:
|
||||
containers:
|
||||
- name: api
|
||||
image: gig-poc-api:latest
|
||||
imagePullPolicy: IfNotPresent
|
||||
ports:
|
||||
- containerPort: 8000
|
||||
env:
|
||||
- name: APP_ENV
|
||||
value: production
|
||||
- name: CACHE_BACKEND
|
||||
value: redis
|
||||
- name: REDIS_URL
|
||||
value: redis://gig-poc-redis:6379/0
|
||||
- name: INGEST_ASYNC_ENABLED
|
||||
value: "true"
|
||||
- name: MATCH_ASYNC_ENABLED
|
||||
value: "true"
|
||||
- name: MATCH_CACHE_ENABLED
|
||||
value: "true"
|
||||
- name: QUERY_CACHE_ENABLED
|
||||
value: "true"
|
||||
- name: APP_RATE_LIMIT_PER_MINUTE
|
||||
value: "3000"
|
||||
resources:
|
||||
requests:
|
||||
cpu: "500m"
|
||||
memory: "512Mi"
|
||||
limits:
|
||||
cpu: "2"
|
||||
memory: "2Gi"
|
||||
readinessProbe:
|
||||
httpGet:
|
||||
path: /health
|
||||
port: 8000
|
||||
initialDelaySeconds: 10
|
||||
periodSeconds: 10
|
||||
livenessProbe:
|
||||
httpGet:
|
||||
path: /health
|
||||
port: 8000
|
||||
initialDelaySeconds: 30
|
||||
periodSeconds: 15
|
||||
---
|
||||
apiVersion: v1
|
||||
kind: Service
|
||||
metadata:
|
||||
name: gig-poc-api
|
||||
namespace: gig-poc
|
||||
spec:
|
||||
selector:
|
||||
app: gig-poc-api
|
||||
ports:
|
||||
- name: http
|
||||
port: 8000
|
||||
targetPort: 8000
|
||||
---
|
||||
apiVersion: autoscaling/v2
|
||||
kind: HorizontalPodAutoscaler
|
||||
metadata:
|
||||
name: gig-poc-api-hpa
|
||||
namespace: gig-poc
|
||||
spec:
|
||||
scaleTargetRef:
|
||||
apiVersion: apps/v1
|
||||
kind: Deployment
|
||||
name: gig-poc-api
|
||||
minReplicas: 3
|
||||
maxReplicas: 20
|
||||
metrics:
|
||||
- type: Resource
|
||||
resource:
|
||||
name: cpu
|
||||
target:
|
||||
type: Utilization
|
||||
averageUtilization: 70
|
||||
24
gig-poc/infrastructure/k8s/ingress.yaml
Normal file
24
gig-poc/infrastructure/k8s/ingress.yaml
Normal file
@@ -0,0 +1,24 @@
|
||||
apiVersion: networking.k8s.io/v1
|
||||
kind: Ingress
|
||||
metadata:
|
||||
name: gig-poc-ingress
|
||||
namespace: gig-poc
|
||||
spec:
|
||||
rules:
|
||||
- host: gig-poc.local
|
||||
http:
|
||||
paths:
|
||||
- path: /api
|
||||
pathType: Prefix
|
||||
backend:
|
||||
service:
|
||||
name: gig-poc-api
|
||||
port:
|
||||
number: 8000
|
||||
- path: /
|
||||
pathType: Prefix
|
||||
backend:
|
||||
service:
|
||||
name: gig-poc-web
|
||||
port:
|
||||
number: 80
|
||||
9
gig-poc/infrastructure/k8s/kustomization.yaml
Normal file
9
gig-poc/infrastructure/k8s/kustomization.yaml
Normal file
@@ -0,0 +1,9 @@
|
||||
apiVersion: kustomize.config.k8s.io/v1beta1
|
||||
kind: Kustomization
|
||||
namespace: gig-poc
|
||||
resources:
|
||||
- namespace.yaml
|
||||
- redis.yaml
|
||||
- api.yaml
|
||||
- web.yaml
|
||||
- ingress.yaml
|
||||
4
gig-poc/infrastructure/k8s/namespace.yaml
Normal file
4
gig-poc/infrastructure/k8s/namespace.yaml
Normal file
@@ -0,0 +1,4 @@
|
||||
apiVersion: v1
|
||||
kind: Namespace
|
||||
metadata:
|
||||
name: gig-poc
|
||||
41
gig-poc/infrastructure/k8s/redis.yaml
Normal file
41
gig-poc/infrastructure/k8s/redis.yaml
Normal file
@@ -0,0 +1,41 @@
|
||||
apiVersion: apps/v1
|
||||
kind: Deployment
|
||||
metadata:
|
||||
name: gig-poc-redis
|
||||
namespace: gig-poc
|
||||
spec:
|
||||
replicas: 1
|
||||
selector:
|
||||
matchLabels:
|
||||
app: gig-poc-redis
|
||||
template:
|
||||
metadata:
|
||||
labels:
|
||||
app: gig-poc-redis
|
||||
spec:
|
||||
containers:
|
||||
- name: redis
|
||||
image: redis:7-alpine
|
||||
args: ["redis-server", "--appendonly", "yes"]
|
||||
ports:
|
||||
- containerPort: 6379
|
||||
resources:
|
||||
requests:
|
||||
cpu: "100m"
|
||||
memory: "128Mi"
|
||||
limits:
|
||||
cpu: "500m"
|
||||
memory: "512Mi"
|
||||
---
|
||||
apiVersion: v1
|
||||
kind: Service
|
||||
metadata:
|
||||
name: gig-poc-redis
|
||||
namespace: gig-poc
|
||||
spec:
|
||||
selector:
|
||||
app: gig-poc-redis
|
||||
ports:
|
||||
- name: redis
|
||||
port: 6379
|
||||
targetPort: 6379
|
||||
61
gig-poc/infrastructure/k8s/web.yaml
Normal file
61
gig-poc/infrastructure/k8s/web.yaml
Normal file
@@ -0,0 +1,61 @@
|
||||
apiVersion: apps/v1
|
||||
kind: Deployment
|
||||
metadata:
|
||||
name: gig-poc-web
|
||||
namespace: gig-poc
|
||||
spec:
|
||||
replicas: 2
|
||||
selector:
|
||||
matchLabels:
|
||||
app: gig-poc-web
|
||||
template:
|
||||
metadata:
|
||||
labels:
|
||||
app: gig-poc-web
|
||||
spec:
|
||||
containers:
|
||||
- name: web
|
||||
image: gig-poc-web:latest
|
||||
imagePullPolicy: IfNotPresent
|
||||
ports:
|
||||
- containerPort: 80
|
||||
resources:
|
||||
requests:
|
||||
cpu: "200m"
|
||||
memory: "256Mi"
|
||||
limits:
|
||||
cpu: "1"
|
||||
memory: "1Gi"
|
||||
---
|
||||
apiVersion: v1
|
||||
kind: Service
|
||||
metadata:
|
||||
name: gig-poc-web
|
||||
namespace: gig-poc
|
||||
spec:
|
||||
selector:
|
||||
app: gig-poc-web
|
||||
ports:
|
||||
- name: http
|
||||
port: 80
|
||||
targetPort: 80
|
||||
---
|
||||
apiVersion: autoscaling/v2
|
||||
kind: HorizontalPodAutoscaler
|
||||
metadata:
|
||||
name: gig-poc-web-hpa
|
||||
namespace: gig-poc
|
||||
spec:
|
||||
scaleTargetRef:
|
||||
apiVersion: apps/v1
|
||||
kind: Deployment
|
||||
name: gig-poc-web
|
||||
minReplicas: 2
|
||||
maxReplicas: 10
|
||||
metrics:
|
||||
- type: Resource
|
||||
resource:
|
||||
name: cpu
|
||||
target:
|
||||
type: Utilization
|
||||
averageUtilization: 70
|
||||
114
gig-poc/infrastructure/scripts/acceptance-e2e.sh
Executable file
114
gig-poc/infrastructure/scripts/acceptance-e2e.sh
Executable file
@@ -0,0 +1,114 @@
|
||||
#!/usr/bin/env sh
|
||||
set -eu
|
||||
|
||||
API_BASE="${API_BASE:-http://127.0.0.1:8000}"
|
||||
BOOTSTRAP_ON_RUN="${BOOTSTRAP_ON_RUN:-true}"
|
||||
|
||||
TMP_DIR="$(mktemp -d)"
|
||||
trap 'rm -rf "$TMP_DIR"' EXIT
|
||||
|
||||
step() {
|
||||
echo "[ACCEPTANCE] $1"
|
||||
}
|
||||
|
||||
fail() {
|
||||
echo "[ACCEPTANCE][FAIL] $1" >&2
|
||||
exit 1
|
||||
}
|
||||
|
||||
parse_json() {
|
||||
PY_EXPR="$1"
|
||||
INPUT_FILE="$2"
|
||||
python3 - "$PY_EXPR" "$INPUT_FILE" <<'PY'
|
||||
import json
|
||||
import sys
|
||||
|
||||
expr = sys.argv[1]
|
||||
path = sys.argv[2]
|
||||
data = json.loads(open(path, "r", encoding="utf-8").read())
|
||||
safe_builtins = {"bool": bool, "len": len, "str": str}
|
||||
value = eval(expr, {"__builtins__": safe_builtins}, {"data": data})
|
||||
if isinstance(value, (dict, list)):
|
||||
print(json.dumps(value, ensure_ascii=False))
|
||||
elif value is None:
|
||||
print("")
|
||||
else:
|
||||
print(str(value))
|
||||
PY
|
||||
}
|
||||
|
||||
step "健康检查"
|
||||
curl -fsS "${API_BASE}/health" >"$TMP_DIR/health.json" || fail "health 接口不可用"
|
||||
|
||||
if [ "$BOOTSTRAP_ON_RUN" = "true" ]; then
|
||||
step "执行 bootstrap"
|
||||
curl -fsS -X POST "${API_BASE}/poc/ingest/bootstrap" >"$TMP_DIR/bootstrap.json" || fail "bootstrap 失败"
|
||||
fi
|
||||
|
||||
step "抽取岗位"
|
||||
curl -fsS -X POST "${API_BASE}/poc/extract/job" \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{"text":"明天下午南山会展中心需要2个签到协助，5小时，150/人，女生优先"}' \
|
||||
>"$TMP_DIR/extract_job.json" || fail "岗位抽取调用失败"
|
||||
[ "$(parse_json "bool(data.get('success'))" "$TMP_DIR/extract_job.json")" = "True" ] || fail "岗位抽取失败"
|
||||
parse_json "data.get('data')" "$TMP_DIR/extract_job.json" >"$TMP_DIR/job.json"
|
||||
JOB_ID="$(parse_json "data.get('data', {}).get('job_id')" "$TMP_DIR/extract_job.json")"
|
||||
[ -n "$JOB_ID" ] || fail "岗位抽取缺少 job_id"
|
||||
|
||||
step "岗位入库"
|
||||
python3 - "$TMP_DIR/job.json" >"$TMP_DIR/ingest_job_payload.json" <<'PY'
|
||||
import json
|
||||
import sys
|
||||
job = json.loads(open(sys.argv[1], "r", encoding="utf-8").read())
|
||||
print(json.dumps({"job": job}, ensure_ascii=False))
|
||||
PY
|
||||
curl -fsS -X POST "${API_BASE}/poc/ingest/job" \
|
||||
-H "Content-Type: application/json" \
|
||||
--data @"$TMP_DIR/ingest_job_payload.json" \
|
||||
>"$TMP_DIR/ingest_job.json" || fail "岗位入库失败"
|
||||
|
||||
step "岗位匹配工人"
|
||||
curl -fsS -X POST "${API_BASE}/poc/match/workers" \
|
||||
-H "Content-Type: application/json" \
|
||||
-d "{\"job_id\":\"${JOB_ID}\",\"top_n\":3}" \
|
||||
>"$TMP_DIR/match_workers.json" || fail "岗位匹配工人失败"
|
||||
MATCH_ID_1="$(parse_json "((data.get('items') or [{}])[0]).get('match_id')" "$TMP_DIR/match_workers.json")"
|
||||
[ -n "$MATCH_ID_1" ] || fail "岗位匹配工人未返回 match_id"
|
||||
|
||||
step "解释匹配（岗位->工人）"
|
||||
curl -fsS "${API_BASE}/poc/match/explain/${MATCH_ID_1}" >"$TMP_DIR/explain_1.json" || fail "匹配解释失败（岗位->工人）"
|
||||
|
||||
step "抽取工人"
|
||||
curl -fsS -X POST "${API_BASE}/poc/extract/worker" \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{"text":"我做过商场促销和活动签到，也能做登记和引导，周末都能接，福田南山都方便。"}' \
|
||||
>"$TMP_DIR/extract_worker.json" || fail "工人抽取调用失败"
|
||||
[ "$(parse_json "bool(data.get('success'))" "$TMP_DIR/extract_worker.json")" = "True" ] || fail "工人抽取失败"
|
||||
parse_json "data.get('data')" "$TMP_DIR/extract_worker.json" >"$TMP_DIR/worker.json"
|
||||
WORKER_ID="$(parse_json "data.get('data', {}).get('worker_id')" "$TMP_DIR/extract_worker.json")"
|
||||
[ -n "$WORKER_ID" ] || fail "工人抽取缺少 worker_id"
|
||||
|
||||
step "工人入库"
|
||||
python3 - "$TMP_DIR/worker.json" >"$TMP_DIR/ingest_worker_payload.json" <<'PY'
|
||||
import json
|
||||
import sys
|
||||
worker = json.loads(open(sys.argv[1], "r", encoding="utf-8").read())
|
||||
print(json.dumps({"worker": worker}, ensure_ascii=False))
|
||||
PY
|
||||
curl -fsS -X POST "${API_BASE}/poc/ingest/worker" \
|
||||
-H "Content-Type: application/json" \
|
||||
--data @"$TMP_DIR/ingest_worker_payload.json" \
|
||||
>"$TMP_DIR/ingest_worker.json" || fail "工人入库失败"
|
||||
|
||||
step "工人匹配岗位"
|
||||
curl -fsS -X POST "${API_BASE}/poc/match/jobs" \
|
||||
-H "Content-Type: application/json" \
|
||||
-d "{\"worker_id\":\"${WORKER_ID}\",\"top_n\":3}" \
|
||||
>"$TMP_DIR/match_jobs.json" || fail "工人匹配岗位失败"
|
||||
MATCH_ID_2="$(parse_json "((data.get('items') or [{}])[0]).get('match_id')" "$TMP_DIR/match_jobs.json")"
|
||||
[ -n "$MATCH_ID_2" ] || fail "工人匹配岗位未返回 match_id"
|
||||
|
||||
step "解释匹配（工人->岗位）"
|
||||
curl -fsS "${API_BASE}/poc/match/explain/${MATCH_ID_2}" >"$TMP_DIR/explain_2.json" || fail "匹配解释失败（工人->岗位）"
|
||||
|
||||
step "链路验收通过：抽取 -> 入库 -> 匹配 -> 解释"
|
||||
@@ -3,6 +3,10 @@ set -eu
|
||||
|
||||
SCRIPT_DIR=$(CDPATH= cd -- "$(dirname "$0")" && pwd)
|
||||
INFRA_DIR=$(CDPATH= cd -- "$SCRIPT_DIR/.." && pwd)
|
||||
PROJECT_DIR=$(CDPATH= cd -- "$INFRA_DIR/.." && pwd)
|
||||
RUN_ACCEPTANCE_ON_UP="${RUN_ACCEPTANCE_ON_UP:-true}"
|
||||
EXPORT_OPENAPI_ON_UP="${EXPORT_OPENAPI_ON_UP:-true}"
|
||||
RUN_BASELINE_ON_UP="${RUN_BASELINE_ON_UP:-false}"
|
||||
|
||||
cd "$INFRA_DIR"
|
||||
docker compose -f docker-compose.yml up --build -d
|
||||
@@ -13,4 +17,20 @@ done
|
||||
until curl -fsS -X POST http://127.0.0.1:8000/poc/ingest/bootstrap >/dev/null 2>&1; do
|
||||
sleep 3
|
||||
done
|
||||
|
||||
if [ "$RUN_ACCEPTANCE_ON_UP" = "true" ]; then
|
||||
echo "执行一键闭环验收脚本..."
|
||||
sh "$SCRIPT_DIR/acceptance-e2e.sh"
|
||||
fi
|
||||
|
||||
if [ "$EXPORT_OPENAPI_ON_UP" = "true" ]; then
|
||||
echo "导出 OpenAPI 固化产物到 docs/openapi.json ..."
|
||||
sh "$SCRIPT_DIR/export-openapi.sh" "$PROJECT_DIR/docs/openapi.json"
|
||||
fi
|
||||
|
||||
if [ "$RUN_BASELINE_ON_UP" = "true" ]; then
|
||||
echo "执行容量基线压测..."
|
||||
sh "$SCRIPT_DIR/load-baseline.sh" "$PROJECT_DIR/docs/CAPACITY_BASELINE.md"
|
||||
fi
|
||||
|
||||
echo "本地环境已启动。Web: http://127.0.0.1:5173 API: http://127.0.0.1:8000/docs"
|
||||
|
||||
11
gig-poc/infrastructure/scripts/export-openapi.sh
Executable file
11
gig-poc/infrastructure/scripts/export-openapi.sh
Executable file
@@ -0,0 +1,11 @@
|
||||
#!/usr/bin/env sh
|
||||
set -eu
|
||||
|
||||
SCRIPT_DIR=$(CDPATH= cd -- "$(dirname "$0")" && pwd)
|
||||
PROJECT_DIR=$(CDPATH= cd -- "$SCRIPT_DIR/../.." && pwd)
|
||||
API_PORT="${API_PORT:-8000}"
|
||||
OUTPUT_PATH="${1:-$PROJECT_DIR/docs/openapi.json}"
|
||||
|
||||
mkdir -p "$(dirname "$OUTPUT_PATH")"
|
||||
curl -fsS "http://127.0.0.1:${API_PORT}/openapi.json" -o "$OUTPUT_PATH"
|
||||
echo "OpenAPI 已导出到: $OUTPUT_PATH"
|
||||
37
gig-poc/infrastructure/scripts/freeze-openapi.sh
Executable file
37
gig-poc/infrastructure/scripts/freeze-openapi.sh
Executable file
@@ -0,0 +1,37 @@
|
||||
#!/usr/bin/env sh
|
||||
set -eu
|
||||
|
||||
SCRIPT_DIR=$(CDPATH= cd -- "$(dirname "$0")" && pwd)
|
||||
PROJECT_DIR=$(CDPATH= cd -- "$SCRIPT_DIR/../.." && pwd)
|
||||
OUTPUT_PATH="${1:-$PROJECT_DIR/docs/openapi.json}"
|
||||
API_PORT="${API_PORT:-8000}"
|
||||
|
||||
mkdir -p "$(dirname "$OUTPUT_PATH")"
|
||||
|
||||
if PYTHONPATH="$PROJECT_DIR/apps/api" python3 - "$OUTPUT_PATH" <<'PY'
|
||||
import json
|
||||
import sys
|
||||
from app.main import app
|
||||
|
||||
output = sys.argv[1]
|
||||
spec = app.openapi()
|
||||
with open(output, "w", encoding="utf-8") as f:
|
||||
json.dump(spec, f, ensure_ascii=False, indent=2)
|
||||
f.write("\n")
|
||||
print(f"OpenAPI 已固化到: {output}")
|
||||
PY
|
||||
then
|
||||
exit 0
|
||||
fi
|
||||
|
||||
echo "本机缺少 API 依赖，尝试从已运行 API 导出..."
|
||||
if curl -fsS "http://127.0.0.1:${API_PORT}/openapi.json" -o "$OUTPUT_PATH"; then
|
||||
echo "OpenAPI 已固化到: $OUTPUT_PATH"
|
||||
exit 0
|
||||
fi
|
||||
|
||||
echo "本机 API 端口不可用，尝试通过 Docker 运行 API 镜像离线导出..."
|
||||
docker compose -f "$PROJECT_DIR/infrastructure/docker-compose.yml" run --rm api \
|
||||
python -c "import json; from app.main import app; print(json.dumps(app.openapi(), ensure_ascii=False, indent=2))" \
|
||||
> "$OUTPUT_PATH"
|
||||
echo "OpenAPI 已固化到: $OUTPUT_PATH"
|
||||
137
gig-poc/infrastructure/scripts/load-baseline.sh
Executable file
137
gig-poc/infrastructure/scripts/load-baseline.sh
Executable file
@@ -0,0 +1,137 @@
|
||||
#!/usr/bin/env sh
|
||||
set -eu
|
||||
|
||||
API_BASE="${API_BASE:-http://127.0.0.1:8000}"
|
||||
TOTAL_REQUESTS="${TOTAL_REQUESTS:-400}"
|
||||
CONCURRENCY="${CONCURRENCY:-40}"
|
||||
OUTPUT_PATH="${1:-$(CDPATH= cd -- "$(dirname "$0")/../.." && pwd)/docs/CAPACITY_BASELINE.md}"
|
||||
|
||||
TMP_DIR="$(mktemp -d)"
|
||||
trap 'rm -rf "$TMP_DIR"' EXIT
|
||||
|
||||
echo "[BASELINE] health check"
|
||||
curl -fsS "$API_BASE/health" >/dev/null
|
||||
|
||||
echo "[BASELINE] ensure bootstrap data"
|
||||
curl -fsS -X POST "$API_BASE/poc/ingest/bootstrap" >/dev/null
|
||||
|
||||
JOB_ID="$(curl -fsS "$API_BASE/poc/jobs" | python3 -c 'import json,sys; data=json.load(sys.stdin); print((data.get("items") or [{}])[0].get("job_id",""))')"
|
||||
WORKER_ID="$(curl -fsS "$API_BASE/poc/workers" | python3 -c 'import json,sys; data=json.load(sys.stdin); print((data.get("items") or [{}])[0].get("worker_id",""))')"
|
||||
|
||||
[ -n "$JOB_ID" ] || { echo "no job id found"; exit 1; }
|
||||
[ -n "$WORKER_ID" ] || { echo "no worker id found"; exit 1; }
|
||||
|
||||
run_case() {
|
||||
NAME="$1"
|
||||
METHOD="$2"
|
||||
URL="$3"
|
||||
BODY_FILE="$4"
|
||||
OUT_FILE="$5"
|
||||
python3 - "$METHOD" "$URL" "$BODY_FILE" "$TOTAL_REQUESTS" "$CONCURRENCY" "$OUT_FILE" <<'PY'
|
||||
import json
|
||||
import sys
|
||||
import time
|
||||
import urllib.request
|
||||
from concurrent.futures import ThreadPoolExecutor, as_completed
|
||||
|
||||
method, url, body_file, total, concurrency, out_file = sys.argv[1:]
|
||||
total = int(total)
|
||||
concurrency = int(concurrency)
|
||||
payload = None
|
||||
if body_file != "-":
|
||||
payload = open(body_file, "rb").read()
|
||||
|
||||
durations = []
|
||||
success = 0
|
||||
fail = 0
|
||||
|
||||
def once():
|
||||
start = time.perf_counter()
|
||||
req = urllib.request.Request(url=url, method=method)
|
||||
req.add_header("Content-Type", "application/json")
|
||||
try:
|
||||
if payload is None:
|
||||
with urllib.request.urlopen(req, timeout=20) as resp:
|
||||
code = resp.getcode()
|
||||
else:
|
||||
with urllib.request.urlopen(req, data=payload, timeout=20) as resp:
|
||||
code = resp.getcode()
|
||||
ok = 200 <= code < 400
|
||||
except Exception:
|
||||
ok = False
|
||||
ms = (time.perf_counter() - start) * 1000
|
||||
return ok, ms
|
||||
|
||||
bench_start = time.perf_counter()
|
||||
with ThreadPoolExecutor(max_workers=concurrency) as ex:
|
||||
futures = [ex.submit(once) for _ in range(total)]
|
||||
for f in as_completed(futures):
|
||||
ok, ms = f.result()
|
||||
durations.append(ms)
|
||||
if ok:
|
||||
success += 1
|
||||
else:
|
||||
fail += 1
|
||||
elapsed = time.perf_counter() - bench_start
|
||||
durations.sort()
|
||||
def pct(p):
|
||||
if not durations:
|
||||
return 0.0
|
||||
idx = min(len(durations) - 1, int(len(durations) * p))
|
||||
return round(durations[idx], 2)
|
||||
result = {
|
||||
"total": total,
|
||||
"success": success,
|
||||
"fail": fail,
|
||||
"success_rate": round(success / total, 4) if total else 0.0,
|
||||
"rps": round(total / elapsed, 2) if elapsed > 0 else 0.0,
|
||||
"latency_ms_avg": round(sum(durations) / len(durations), 2) if durations else 0.0,
|
||||
"latency_ms_p95": pct(0.95),
|
||||
"latency_ms_p99": pct(0.99),
|
||||
}
|
||||
with open(out_file, "w", encoding="utf-8") as f:
|
||||
json.dump(result, f, ensure_ascii=False, indent=2)
|
||||
PY
|
||||
echo "[BASELINE] done $NAME"
|
||||
}
|
||||
|
||||
printf '{"job_id":"%s","top_n":10}\n' "$JOB_ID" >"$TMP_DIR/match_workers.json"
|
||||
printf '{"worker_id":"%s","top_n":10}\n' "$WORKER_ID" >"$TMP_DIR/match_jobs.json"
|
||||
|
||||
run_case "health" "GET" "$API_BASE/health" "-" "$TMP_DIR/health.result.json"
|
||||
run_case "jobs_list" "GET" "$API_BASE/poc/jobs" "-" "$TMP_DIR/jobs.result.json"
|
||||
run_case "match_workers" "POST" "$API_BASE/poc/match/workers" "$TMP_DIR/match_workers.json" "$TMP_DIR/match_workers.result.json"
|
||||
run_case "match_jobs" "POST" "$API_BASE/poc/match/jobs" "$TMP_DIR/match_jobs.json" "$TMP_DIR/match_jobs.result.json"
|
||||
run_case "match_workers_cached" "POST" "$API_BASE/poc/match/workers" "$TMP_DIR/match_workers.json" "$TMP_DIR/match_workers_cached.result.json"
|
||||
run_case "match_jobs_cached" "POST" "$API_BASE/poc/match/jobs" "$TMP_DIR/match_jobs.json" "$TMP_DIR/match_jobs_cached.result.json"
|
||||
run_case "match_workers_async_enqueue" "POST" "$API_BASE/poc/match/workers/async" "$TMP_DIR/match_workers.json" "$TMP_DIR/match_workers_async.result.json"
|
||||
run_case "match_jobs_async_enqueue" "POST" "$API_BASE/poc/match/jobs/async" "$TMP_DIR/match_jobs.json" "$TMP_DIR/match_jobs_async.result.json"
|
||||
|
||||
NOW="$(date '+%Y-%m-%d %H:%M:%S %z')"
|
||||
mkdir -p "$(dirname "$OUTPUT_PATH")"
|
||||
|
||||
{
|
||||
echo "# 容量基线（自动生成）"
|
||||
echo
|
||||
echo "- 生成时间: $NOW"
|
||||
echo "- API_BASE: $API_BASE"
|
||||
echo "- TOTAL_REQUESTS: $TOTAL_REQUESTS"
|
||||
echo "- CONCURRENCY: $CONCURRENCY"
|
||||
echo
|
||||
echo "| 场景 | 成功率 | RPS | 平均延迟(ms) | P95(ms) | P99(ms) |"
|
||||
echo "| --- | --- | --- | --- | --- | --- |"
|
||||
for case in health jobs match_workers match_jobs match_workers_cached match_jobs_cached match_workers_async match_jobs_async; do
|
||||
FILE="$TMP_DIR/${case}.result.json"
|
||||
python3 - "$case" "$FILE" <<'PY'
|
||||
import json
|
||||
import sys
|
||||
case, path = sys.argv[1], sys.argv[2]
|
||||
data = json.loads(open(path, "r", encoding="utf-8").read())
|
||||
print(f"| {case} | {data['success_rate']} | {data['rps']} | {data['latency_ms_avg']} | {data['latency_ms_p95']} | {data['latency_ms_p99']} |")
|
||||
PY
|
||||
done
|
||||
echo
|
||||
echo "> 建议：该基线仅代表当前单机/当前数据量下表现，发布前请在目标环境按 2x/5x 峰值复测。"
|
||||
} >"$OUTPUT_PATH"
|
||||
|
||||
echo "[BASELINE] report generated at $OUTPUT_PATH"
|
||||
8
gig-poc/infrastructure/scripts/prod-down.sh
Executable file
8
gig-poc/infrastructure/scripts/prod-down.sh
Executable file
@@ -0,0 +1,8 @@
|
||||
#!/usr/bin/env sh
|
||||
set -eu
|
||||
|
||||
SCRIPT_DIR=$(CDPATH= cd -- "$(dirname "$0")" && pwd)
|
||||
INFRA_DIR=$(CDPATH= cd -- "$SCRIPT_DIR/.." && pwd)
|
||||
|
||||
cd "$INFRA_DIR"
|
||||
docker compose -f docker-compose.prod.yml down
|
||||
@@ -3,7 +3,21 @@ set -eu
|
||||
|
||||
SCRIPT_DIR=$(CDPATH= cd -- "$(dirname "$0")" && pwd)
|
||||
INFRA_DIR=$(CDPATH= cd -- "$SCRIPT_DIR/.." && pwd)
|
||||
API_PORT="${API_PORT:-8000}"
|
||||
BOOTSTRAP_ON_UP="${BOOTSTRAP_ON_UP:-true}"
|
||||
|
||||
cd "$INFRA_DIR"
|
||||
docker compose -f docker-compose.prod.yml up --build -d
|
||||
echo "生产部署容器已启动。请按实际域名或端口访问 Web。"
|
||||
echo "等待生产 API 健康检查..."
|
||||
until curl -fsS "http://127.0.0.1:${API_PORT}/health" >/dev/null 2>&1; do
|
||||
sleep 3
|
||||
done
|
||||
|
||||
if [ "$BOOTSTRAP_ON_UP" = "true" ]; then
|
||||
echo "执行 bootstrap 样本初始化..."
|
||||
until curl -fsS -X POST "http://127.0.0.1:${API_PORT}/poc/ingest/bootstrap" >/dev/null 2>&1; do
|
||||
sleep 3
|
||||
done
|
||||
fi
|
||||
|
||||
echo "生产环境已启动。Web: http://127.0.0.1:${WEB_PORT:-80} API: http://127.0.0.1:${API_PORT}/docs"
|
||||
|
||||
Reference in New Issue
Block a user