Sakurasan
912a224b6b
- 后端：AI分析服务、工具调用、定时任务 - 前端：报告列表、详情页、Mermaid图表支持 - 支持OpenAI API兼容模型 - 收盘后自动分析生成报告
128 lines
4.1 KiB
Python
128 lines
4.1 KiB
Python
"""AI 分析报告路由（/api/ai-analysis）
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提供：
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- 报告列表
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- 报告详情
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- 手动触发分析（12小时频率限制）
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- 重新生成报告
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- 检查某日是否有报告
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"""
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import json
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from datetime import datetime, timezone, timedelta
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from fastapi import APIRouter, HTTPException
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from fastapi.responses import JSONResponse
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from database import get_connection, dict_from_row
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_CST = timezone(timedelta(hours=8))
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_NO_CACHE_HEADERS = {"Cache-Control": "no-store, no-cache, must-revalidate, max-age=0"}
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router = APIRouter()
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def _has_ai_report(trade_date: str) -> bool:
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conn = get_connection()
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try:
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row = conn.execute(
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"SELECT 1 FROM ai_reports WHERE trade_date = ? AND report_type = 'daily' LIMIT 1",
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(trade_date,)
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).fetchone()
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return row is not None
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finally:
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conn.close()
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def _can_trigger(trade_date: str) -> tuple[bool, str]:
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"""检查是否可以触发分析（12小时频率限制）"""
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conn = get_connection()
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try:
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row = conn.execute(
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"SELECT created_at FROM ai_reports WHERE trade_date = ? ORDER BY id DESC LIMIT 1",
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(trade_date,)
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).fetchone()
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if row:
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last_time = datetime.strptime(row["created_at"], "%Y-%m-%d %H:%M:%S")
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now = datetime.now(_CST)
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if (now - last_time).total_seconds() < 12 * 3600:
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return False, "12小时内已触发过，请稍后再试"
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return True, ""
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finally:
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conn.close()
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@router.get("/ai-analysis", summary="AI 分析报告列表")
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async def list_reports():
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conn = get_connection()
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try:
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rows = conn.execute(
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"SELECT id, trade_date, report_type, title, summary, tools_used, model, tokens_used, created_at "
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"FROM ai_reports ORDER BY trade_date DESC, id DESC LIMIT 50"
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).fetchall()
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items = []
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for r in rows:
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item = dict_from_row(r)
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item["toolsUsed"] = json.loads(item.pop("tools_used") or "[]")
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items.append(item)
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return JSONResponse({"data": items}, headers=_NO_CACHE_HEADERS)
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finally:
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conn.close()
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@router.get("/ai-analysis/{report_id}", summary="AI 分析报告详情")
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async def get_report(report_id: int):
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conn = get_connection()
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try:
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row = conn.execute("SELECT * FROM ai_reports WHERE id = ?", (report_id,)).fetchone()
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if not row:
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raise HTTPException(status_code=404, detail="报告不存在")
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item = dict_from_row(row)
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item["toolsUsed"] = json.loads(item.pop("tools_used") or "[]")
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return JSONResponse({"data": item}, headers=_NO_CACHE_HEADERS)
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finally:
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conn.close()
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@router.get("/ai-analysis/check/{trade_date}", summary="检查某日是否有 AI 分析报告")
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async def check_report(trade_date: str):
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has = _has_ai_report(trade_date)
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return JSONResponse({"data": {"hasReport": has, "tradeDate": trade_date}})
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@router.post("/ai-analysis/trigger", summary="手动触发今日 AI 分析")
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async def trigger_analysis():
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now = datetime.now(_CST)
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trade_date = now.strftime("%Y-%m-%d")
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if _has_ai_report(trade_date):
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raise HTTPException(status_code=400, detail="今日已有分析报告")
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can, msg = _can_trigger(trade_date)
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if not can:
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raise HTTPException(status_code=429, detail=msg)
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from services.ai_service import collect_ai_analysis
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result = await collect_ai_analysis(trade_date)
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return JSONResponse({"data": result})
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@router.post("/ai-analysis/{report_id}/regenerate", summary="重新生成 AI 分析报告")
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async def regenerate_report(report_id: int):
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conn = get_connection()
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try:
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row = conn.execute("SELECT trade_date FROM ai_reports WHERE id = ?", (report_id,)).fetchone()
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if not row:
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raise HTTPException(status_code=404, detail="报告不存在")
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trade_date = row["trade_date"]
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finally:
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conn.close()
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can, msg = _can_trigger(trade_date)
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if not can:
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raise HTTPException(status_code=429, detail=msg)
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from services.ai_service import collect_ai_analysis
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result = await collect_ai_analysis(trade_date)
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return JSONResponse({"data": result})
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