diff --git a/ft-app/app/prompt_builder.py b/ft-app/app/prompt_builder.py new file mode 100644 index 0000000..3fc9c91 --- /dev/null +++ b/ft-app/app/prompt_builder.py @@ -0,0 +1,229 @@ +"""持仓分析 prompt 生成器。 + +根据最近 5 个交易日的主力持仓排名生成结构化分析 prompt， +按席位属性（家人/大户/其他/噪音）分类汇总，聚焦资金风向变化。 +""" + +from collections import defaultdict +from datetime import date, timedelta + +from app.database import SessionLocal +from app.models import PositionRanking, Contract + + +# ── 席位分类 ── +FAMILY_NAMES = [ + "东方财富", "徽商期货", "方正中期", "中信建投", "平安期货", +] +WHALE_NAMES = [ + "永安期货", "中信期货", "国泰君安", "海通期货", "华泰期货", + "高盛期货", "乾坤期货", "摩根大通", "中粮期货", +] +NOISE_NAMES = ["东证期货"] + +TYPE_LABEL = {"volume": "成交量", "long": "多单持仓", "short": "空单持仓"} + + +def _classify(inst: str) -> str: + """匹配席位分类，返回 家人/大户/噪音/其他。""" + for kw in FAMILY_NAMES: + if kw in inst: + return "家人" + for kw in WHALE_NAMES: + if kw in inst: + return "大户" + for kw in NOISE_NAMES: + if kw in inst: + return "噪音" + return "其他" + + +def _build_legend() -> str: + """生成席位分类图例。""" + lines = ["## 席位分类", ""] + lines.append(f"- **家人席位（散户）**: {'、'.join(FAMILY_NAMES)}") + lines.append(f"- **大户席位（产业/套保）**: {'、'.join(WHALE_NAMES)}") + lines.append(f"- **噪音席位（忽略）**: {'、'.join(NOISE_NAMES)}") + lines.append("- **其他席位**: 未归入以上三类的席位") + lines.append("") + return "\n".join(lines) + + +def _format_number(n: int) -> str: + """数字格式化为万手。""" + v = n / 10000 + sign = "+" if n > 0 else "" + return f"{sign}{v:.2f}万" + + +def build_prompt(contract_code: str | None = None) -> str: + """生成单个或全部活跃合约的持仓分析 prompt。 + + Args: + contract_code: 合约代码（如 FG2609），为 None 时分析所有活跃合约。 + + Returns: + 可直接发送给 AI 进行分析的 prompt 文本。 + """ + db = SessionLocal() + try: + if contract_code: + codes = [contract_code.upper()] + else: + codes = [ + r[0] for r in + db.query(Contract.code) + .filter(Contract.is_active == True) + .order_by(Contract.code) + .all() + ] + + # 取最近 5 个有持仓数据的交易日 + all_dates = sorted({ + r[0] for r in + db.query(PositionRanking.date) + .filter(PositionRanking.contract_code.in_(codes)) + .distinct() + .all() + }, reverse=True)[:5] + all_dates.reverse() # 从旧到新 + + if not all_dates: + return "无持仓数据" + + # 拉取全部数据 + rankings = ( + db.query(PositionRanking) + .filter( + PositionRanking.contract_code.in_(codes), + PositionRanking.date.in_(all_dates), + ) + .order_by(PositionRanking.contract_code, PositionRanking.date, PositionRanking.data_type, PositionRanking.rank) + .all() + ) + + # 按 contract → date → data_type 组织 + data: dict[str, dict] = defaultdict(lambda: defaultdict(lambda: defaultdict(list))) + for r in rankings: + data[r.contract_code][r.date][r.data_type].append(r) + + parts = [_build_legend()] + + for code in codes: + if code not in data: + continue + cd = data[code] + parts.append(f"## {code}") + parts.append("") + parts.append(f"分析区间: {min(all_dates)} → {max(all_dates)}（共 {len(all_dates)} 个交易日）") + parts.append("") + + # ── 每日明细 ── + for d in all_dates: + if d not in cd: + continue + parts.append(f"### {d} {_weekday_zh(d)}") + parts.append("") + + for dtype in ["volume", "long", "short"]: + rows = cd[d].get(dtype, []) + if not rows: + continue + parts.append(f"**{TYPE_LABEL[dtype]} Top 20**") + parts.append("") + parts.append("| 排名 | 席位 | 分类 | 持仓量 | 增减 |") + parts.append("|------|------|------|--------|------|") + for r in rows[:20]: + tag = _classify(r.institution) + if tag == "噪音": + continue # 跳过东证 + parts.append( + f"| {r.rank} | {r.institution} | {tag} | " + f"{_format_number(r.value)} | {_format_number(r.change)} |" + ) + parts.append("") + + # ── 每日家人 vs 大户汇总 ── + parts.append(f"### {code} 分类资金变化汇总") + parts.append("") + parts.append("| 日期 | 家人多单增减 | 家人空单增减 | 大户多单增减 | 大户空单增减 | 其他多单增减 | 其他空单增减 |") + parts.append("|------|-------------|-------------|-------------|-------------|-------------|-------------|") + + for d in all_dates: + if d not in cd: + continue + cat_changes = defaultdict(lambda: defaultdict(int)) + for dtype in ["long", "short"]: + for r in cd[d].get(dtype, []): + tag = _classify(r.institution) + if tag == "噪音": + continue + cat_changes[tag][dtype] += r.change + + parts.append( + f"| {d} " + f"| {_format_number(cat_changes['家人']['long'])} " + f"| {_format_number(cat_changes['家人']['short'])} " + f"| {_format_number(cat_changes['大户']['long'])} " + f"| {_format_number(cat_changes['大户']['short'])} " + f"| {_format_number(cat_changes['其他']['long'])} " + f"| {_format_number(cat_changes['其他']['short'])} |" + ) + parts.append("") + + # ── 5日累计 ── + parts.append(f"### {code} 5日累计资金变化") + parts.append("") + total_cat = defaultdict(lambda: defaultdict(int)) + for d in all_dates: + if d not in cd: + continue + for dtype in ["long", "short"]: + for r in cd[d].get(dtype, []): + tag = _classify(r.institution) + if tag == "噪音": + continue + total_cat[tag][dtype] += r.change + + parts.append("| 分类 | 5日多单累计 | 5日空单累计 | 净多（多-空） |") + parts.append("|------|------------|------------|--------------|") + for tag in ["家人", "大户", "其他"]: + net = total_cat[tag]["long"] - total_cat[tag]["short"] + net_str = _format_number(net) + parts.append( + f"| {tag} | {_format_number(total_cat[tag]['long'])} " + f"| {_format_number(total_cat[tag]['short'])} | {net_str} |" + ) + parts.append("") + + # ── 分析引导 ── + parts.append("---") + parts.append("") + parts.append("请基于以上数据进行分析，重点关注：") + parts.append("") + parts.append("1. **家人席位动向**: 5日内多空增减趋势，散户情绪偏多还是偏空，" + "是否有明显的追涨杀跌行为。") + parts.append("2. **大户席位动向**: 产业资金和套保资金的布局方向，" + "多空增减是否与家人席位形成对手盘。") + parts.append("3. **多空力量对比**: 各分类的净多/净空方向，" + "整体市场情绪偏向。") + parts.append("4. **异常信号**: 单日大幅增减的席位，" + "分类资金出现明显分歧的交易日。") + parts.append("5. **行情预判**: 结合席位资金流向，" + "对下一交易日走势给出偏多/偏空/震荡的判断及理由。") + + return "\n".join(parts) + finally: + db.close() + + +def _weekday_zh(d: date) -> str: + return ["周一", "周二", "周三", "周四", "周五", "周六", "周日"][d.weekday()] + + +if __name__ == "__main__": + import sys + sys.path.insert(0, "/app") + from app.prompt_builder import build_prompt + prompt = build_prompt() + print(prompt) diff --git a/ft-app/app/routers/contracts.py b/ft-app/app/routers/contracts.py index ccd5b63..6932496 100644 --- a/ft-app/app/routers/contracts.py +++ b/ft-app/app/routers/contracts.py @@ -1,10 +1,11 @@ import math from datetime import date, timedelta from fastapi import APIRouter, Depends, Request, Query -from fastapi.responses import HTMLResponse +from fastapi.responses import HTMLResponse, PlainTextResponse from sqlalchemy.orm import Session from app.database import get_db from app.models import DailyBar, Contract, PositionRanking +from app.prompt_builder import build_prompt router = APIRouter(prefix="/contracts", tags=["contracts"]) @@ -205,3 +206,9 @@ def contract_detail( WEEKDAY_ZH=WEEKDAY_ZH, ) ) + + +@router.get("/{contract}/analysis-prompt", response_class=PlainTextResponse) +def contract_analysis_prompt(contract: str): + """返回合约的持仓分析 prompt 文本。""" + return build_prompt(contract.upper()) diff --git a/ft-app/app/templates/contract.html b/ft-app/app/templates/contract.html index f6ed68e..2f90453 100644 --- a/ft-app/app/templates/contract.html +++ b/ft-app/app/templates/contract.html @@ -72,6 +72,7 @@
持仓排名 · 前20 +
@@ -108,6 +109,18 @@
{% endif %} + + + {% endblock %}