67 lines
2.1 KiB
Python
67 lines
2.1 KiB
Python
"""涨幅轮动矩阵 API。
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供「概念分析 → 涨幅RPS轮动」对话框调用。返回最近 N 个交易日的概念涨幅
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排名矩阵:每列(日期)各自把所有概念按当天涨幅从高到低排序。
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"""
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from __future__ import annotations
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from fastapi import APIRouter, Query, Request
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from fastapi.responses import StreamingResponse
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from pydantic import BaseModel
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from app.services import rps_rotation
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from app.services.concept_rotation_analyzer import analyze_rotation_stream
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router = APIRouter(prefix="/api/rps", tags=["rps"])
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@router.get("/rotation")
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def get_rotation(
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request: Request,
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days: int = Query(12, ge=7, le=30, description="最近 N 个交易日(7-30)"),
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) -> dict:
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"""概念涨幅轮动矩阵。
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Returns:
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dates: 日期字符串列表(最新在最前)
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columns: {日期: [[概念名, 涨幅小数], ...]} 每列各自降序
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concept_count: 去重概念总数
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"""
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return rps_rotation.build_rps_rotation(request.app.state.repo, days)
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class AnalyzeRequest(BaseModel):
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"""AI 概念轮动分析请求。"""
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days: int = 12 # 分析最近 N 个交易日
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focus: str = "" # 用户追加的关注点
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@router.post("/rotation-analyze")
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async def analyze_rotation(request: Request, req: AnalyzeRequest):
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"""AI 概念轮动分析 — NDJSON 流式返回。
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装配轮动矩阵信号 + 大盘背景 → 分析提示词 → 流式调用 LLM →
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逐 chunk 以 NDJSON 推给前端(每行一个 JSON)。
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协议:
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{"type":"meta","days","summary"}
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{"type":"delta","content":"..."}
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{"type":"error","message":"..."}
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{"type":"done"}
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"""
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repo = request.app.state.repo
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days = max(7, min(30, req.days))
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async def stream_gen():
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async for chunk in analyze_rotation_stream(
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repo, days, req.focus,
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username=request.state.username,
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):
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yield chunk + "\n"
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return StreamingResponse(
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stream_gen(),
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media_type="application/x-ndjson",
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headers={"Cache-Control": "no-cache", "X-Accel-Buffering": "no"},
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)
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