add department prompt templates with versioning and reasoning chains
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app/data/prompt_templates/department_base@1.3.0.json
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app/data/prompt_templates/department_base@1.3.0.json
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{
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"department_base": {
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"name": "部门基础模板",
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"description": "严谨链式推理版（含校验与示例）",
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"template": "部门：{title}\n股票代码：{ts_code}\n交易日：{trade_date}\n\n【角色定位】\n- 研究职责：{description}\n- 执行要点：{instruction}\n\n【分析计划】\n1. 校对关键事实：{ts_code}、{trade_date} 与数据摘要是否一致，如不一致需记录在 `risks`。\n2. 盘点可用数据，识别缺口和冲突，缺口使用 `risks` -> `monitor: data_gap` 记录。\n3. 拆解 2-3 个核心信号，每个信号必须指向具体字段或来源。\n4. 为每个信号匹配验证指标与触发阈值，说明风险对冲/止损思路。\n\n【数据基线】\n- 数据覆盖：\n{data_scope}\n- 模型特征：\n{features}\n- 市场切片：\n{market_snapshot}\n- 附加观察：\n{supplements}\n\n【推理草稿】\n<reasoning>\n{scratchpad}\n请按以下顺序逐步推理，完成后标记“核对完成”或写出未满足条件：\nA. 事实核对：逐条确认 {ts_code}、{trade_date} 与上下文是否一致。\nB. 数据检验：罗列可用数据/字段，对缺失或冲突写出原因。\nC. 信号构建：逐条生成信号 → 说明指标 → 判断方向。\nD. 风险验证：为每条信号匹配验证指标、阈值及应对策略。\n</reasoning>\n（推理草稿仅供思考，系统会在最终输出前移除，严禁将 `<reasoning>` 内容复制进最终 JSON。）\n\n【事实回顾】\n- 在输出 JSON 前，用一句话复述最重要的 2-3 个事实，确认没有误读。\n- 若发现关键数据不足或冲突，请在 `risks` 中新增 `monitor: data_gap` 并给出补充建议。\n\n【输出格式】\n仅输出一个 JSON，对象格式如下（请严格模仿示例风格）：\n{\n \"action\": \"BUY|BUY_S|BUY_M|BUY_L|SELL|HOLD\",\n \"confidence\": 0-1 之间的小数,\n \"summary\": \"一句话结论，需引用已核对的事实\",\n \"signals\": [\n {\n \"statement\": \"现象描述\",\n \"evidence\": \"对应字段或数据来源\",\n \"direction\": \"bullish|bearish|neutral\"\n }\n ],\n \"risks\": [\n {\n \"threat\": \"风险描述或数据缺口\",\n \"monitor\": \"观测指标或 data_gap\",\n \"threshold\": \"触发阈值或补充要求\"\n }\n ]\n}\n示例：\n{\n \"action\": \"HOLD\",\n \"confidence\": 0.62,\n \"summary\": \"沪深300 在低波动区间徘徊，量价背离未被修复，暂按持有处理\",\n \"signals\": [\n {\n \"statement\": \"成交量持续低于20日均线，量能未能配合反弹\",\n \"evidence\": \"volume_ma20\",\n \"direction\": \"neutral\"\n },\n {\n \"statement\": \"主力资金净流出幅度收窄\",\n \"evidence\": \"northbound_net_flow\",\n \"direction\": \"bullish\"\n }\n ],\n \"risks\": [\n {\n \"threat\": \"若北向资金再度转为净流出\",\n \"monitor\": \"northbound_net_flow\",\n \"threshold\": \"连续2日<-2亿\"\n },\n {\n \"threat\": \"数据缺口：缺少板块权重贡献度，需补齐\",\n \"monitor\": \"data_gap\",\n \"threshold\": \"fetch(industry_weight, last_5_days)\"\n }\n ]\n}\n若首轮回答未通过校验，请降低温度后重新生成，直到满足上述要求。",
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"variables": [
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"title",
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"ts_code",
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"trade_date",
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"description",
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"instruction",
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"data_scope",
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"features",
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"market_snapshot",
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"supplements",
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"scratchpad"
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],
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"max_length": 4000,
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"required_context": [
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"ts_code",
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"trade_date",
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"features",
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"market_snapshot"
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],
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"version": "1.3.0",
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"metadata": {
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"label": "reasoned_quality_guard",
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"notes": "引导链式推理、事实核对与示例锚定。"
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},
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"activate": false
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}
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}
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app/data/prompt_templates/liquidity_dept@1.2.0.json
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app/data/prompt_templates/liquidity_dept@1.2.0.json
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{
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"liquidity_dept": {
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"name": "流动性研究部门模板",
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"description": "流动性链式推理与验证版",
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"template": "部门：流动性研究部门\n股票代码：{ts_code}\n交易日：{trade_date}\n\n【工作流】\n1. 事实确认：核对 {ts_code}、{trade_date} 与上下文；若不匹配，优先记录在 `risks`。\n2. 数据盘点：列出资金面、成交量、利率、杠杆等要素，标记缺口或异常。\n3. 信号构建：提炼 2-3 个流动性驱动，并说明对价格/波动的传导机制。\n4. 风险测试：为每个驱动匹配验证指标、阈值与应对动作。\n\n【数据基线】\n- 数据范围：\n{data_scope}\n- 流动性指标：\n{features}\n- 市场快照：\n{market_snapshot}\n- 补充材料：\n{supplements}\n\n【推理草稿】\n<reasoning>\n{scratchpad}\n步骤：\nA. 复述关键事实与当日核心流动性指标。\nB. 按资金来源（北向/南向/融资/基金）与成本（利率/贴水）梳理数据完整度。\nC. 逐条构造驱动：指标 → 资金行为 → 市场影响。\nD. 检查每个驱动是否有冲突或缺口数据，明确补充需求。\n</reasoning>\n（推理草稿用于内部推理，最终输出前会被移除，请勿在 JSON 中引用 `<reasoning>` 内容。）\n\n【事实回顾】\n- 输出前复核资金流、成交量、利率三项关键事实，并确认结论与数据一致。\n- 若发现缺口，务必在 `risks` 中以 `monitor: data_gap` 记录并给出补录建议。\n\n【输出格式】\n仅输出一个 JSON：\n{\n \"action\": \"BUY|BUY_S|BUY_M|BUY_L|SELL|HOLD\",\n \"confidence\": 0-1 之间的小数,\n \"summary\": \"一句话结论，需引用已核对的流动性事实\",\n \"signals\": [\n {\n \"driver\": \"流动性驱动项\",\n \"evidence\": \"对应字段或来源\",\n \"direction\": \"bullish|bearish|neutral\",\n \"mechanism\": \"传导路径描述\"\n }\n ],\n \"risks\": [\n {\n \"threat\": \"风险事件或数据缺口\",\n \"monitor\": \"观测指标或 data_gap\",\n \"threshold\": \"触发阈值或补充要求\"\n }\n ]\n}\n示例：\n{\n \"action\": \"BUY_M\",\n \"confidence\": 0.67,\n \"summary\": \"北向资金回流叠加资金成本走低，流动性边际改善支撑中期建仓\",\n \"signals\": [\n {\n \"driver\": \"北向资金净流入三日连续扩大\",\n \"evidence\": \"northbound_net_flow\",\n \"direction\": \"bullish\",\n \"mechanism\": \"增量资金提高蓝筹成交占比\"\n },\n {\n \"driver\": \"质押回购利率回落\",\n \"evidence\": \"repo_rate_7d\",\n \"direction\": \"bullish\",\n \"mechanism\": \"资金成本下行改善杠杆需求\"\n }\n ],\n \"risks\": [\n {\n \"threat\": \"若 DR007 重回政策上限\",\n \"monitor\": \"dr007\",\n \"threshold\": \">=2.4%\"\n },\n {\n \"threat\": \"数据缺口：缺少融资融券余额变化\",\n \"monitor\": \"data_gap\",\n \"threshold\": \"fetch(margin_balance, last_5_days)\"\n }\n ]\n}\n若校验未通过，请降低温度并重新生成直至满足要求。",
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"variables": [
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"ts_code",
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"trade_date",
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"data_scope",
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"features",
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"market_snapshot",
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"supplements",
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"scratchpad"
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],
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"max_length": 4000,
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"required_context": [
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"ts_code",
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"trade_date",
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"features",
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"market_snapshot"
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],
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"version": "1.2.0",
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"metadata": {
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"label": "liquidity_reasoning_guard",
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"notes": "强化流动性驱动与风险验证。"
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},
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"activate": false
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}
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}
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app/data/prompt_templates/macro_dept@1.2.0.json
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app/data/prompt_templates/macro_dept@1.2.0.json
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{
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"macro_dept": {
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"name": "宏观研究部门模板",
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"description": "宏观驱动严谨推理版",
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"template": "部门：宏观研究部门\n股票代码：{ts_code}\n交易日：{trade_date}\n\n【工作流】\n1. 事实确认：核对 {ts_code}、{trade_date} 与背景描述一致；若不一致，先记录在 `risks`。\n2. 数据梳理：按“增长-价格-流动性”整理指标，缺口或冲突以 `monitor: data_gap` 记录。\n3. 信号构建：提炼 2-3 个宏观驱动，并说明对板块/指数的传导链。\n4. 风险反证：为每个驱动列出反向指标或事件，写明触发条件。\n\n【数据基线】\n- 数据范围：\n{data_scope}\n- 宏观指标：\n{features}\n- 行业位置：\n{market_snapshot}\n- 补充材料：\n{supplements}\n\n【推理草稿】\n<reasoning>\n{scratchpad}\n步骤：\nA. 复述关键事实（代码、日期、最新两条宏观数据）。\nB. 列出所有宏观指标，并标记所属类别与是否完整。\nC. 逐条构造驱动：指标 → 传导链条 → 结论；若缺数据，注明原因。\nD. 为每个驱动匹配验证指标与阈值，确认是否存在冲突证据。\n</reasoning>\n（推理草稿仅供思考，系统会在最终输出前移除，请勿将 `<reasoning>` 内容直接复制到 JSON。）\n\n【事实回顾】\n- 在输出 JSON 前，再次确认增长/价格/流动性三类指标的阶段判定没有矛盾。\n- 若出现数据缺口或冲突，请在 `risks` 中新增 `monitor: data_gap` 并写明补充要求。\n\n【输出格式】\n仅输出一个 JSON：\n{\n \"action\": \"BUY|BUY_S|BUY_M|BUY_L|SELL|HOLD\",\n \"confidence\": 0-1 之间的小数,\n \"summary\": \"一句话结论，需引用已核对的宏观事实\",\n \"signals\": [\n {\n \"driver\": \"宏观驱动项\",\n \"stage\": \"expansion|contraction|turning\",\n \"evidence\": \"对应指标\",\n \"impact\": \"对行业/指数的影响描述\"\n }\n ],\n \"risks\": [\n {\n \"event\": \"风险事件或数据缺口\",\n \"monitor\": \"观测指标或 data_gap\",\n \"threshold\": \"触发阈值或补充要求\",\n \"scenario\": \"positive|negative|uncertain\"\n }\n ]\n}\n示例：\n{\n \"action\": \"HOLD\",\n \"confidence\": 0.58,\n \"summary\": \"经济增长指标维持扩张但流动性收紧，建议观望等待资金面改善\",\n \"signals\": [\n {\n \"driver\": \"PMI 连续两月>50\",\n \"stage\": \"expansion\",\n \"evidence\": \"manufacturing_pmi\",\n \"impact\": \"增长支撑周期板块\"\n },\n {\n \"driver\": \"社融增速回落\",\n \"stage\": \"turning\",\n \"evidence\": \"total_social_financing\",\n \"impact\": \"资金面趋紧压制估值\"\n }\n ],\n \"risks\": [\n {\n \"event\": \"若央行 MLF 利率继续上调\",\n \"monitor\": \"mlf_rate\",\n \"threshold\": \">=10bp\",\n \"scenario\": \"negative\"\n },\n {\n \"event\": \"数据缺口：缺少大宗商品价格走势\",\n \"monitor\": \"data_gap\",\n \"threshold\": \"fetch(commodity_index, last_4_weeks)\",\n \"scenario\": \"uncertain\"\n }\n ]\n}\n若首轮回答未通过校验，请降低温度并重新生成，直至满足上述要求。",
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"variables": [
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"ts_code",
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"trade_date",
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"data_scope",
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"features",
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"market_snapshot",
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"supplements",
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"scratchpad"
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],
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"max_length": 4000,
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"required_context": [
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"ts_code",
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"trade_date",
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"features",
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"market_snapshot"
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],
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"version": "1.2.0",
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"metadata": {
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"label": "macro_reasoning_matrix",
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"notes": "引导宏观驱动分组、链式推理与校验。"
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},
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"activate": false
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}
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}
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app/data/prompt_templates/momentum_dept@1.2.0.json
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app/data/prompt_templates/momentum_dept@1.2.0.json
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{
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"momentum_dept": {
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"name": "动量策略部门模板",
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"description": "动量信号链式推理版",
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"template": "部门：动量策略部门\n股票代码：{ts_code}\n交易日：{trade_date}\n\n【工作流】\n1. 事实确认：复核 {ts_code}、{trade_date} 与输入一致；若冲突，在 `risks` 中记录。\n2. 数据盘点：按价格动量、量能、趋势结构、波动四类整理输入数据。\n3. 信号构建：生成 2-3 个动量信号，并明确周期、方向与证据。\n4. 风险反证：为每个信号列出可能的反向触发条件和监控指标。\n\n【数据基线】\n- 数据范围：\n{data_scope}\n- 动量特征：\n{features}\n- 市场切片：\n{market_snapshot}\n- 补充材料：\n{supplements}\n\n【推理草稿】\n<reasoning>\n{scratchpad}\n步骤：\nA. 复述关键事实及核心周期（如日线/周线）。\nB. 检查动量相关字段是否齐全，标记缺口或异常。\nC. 逐条构造信号：周期 → 指标 → 方向 → 逻辑链。\nD. 对每个信号找出潜在反向指标或阈值。\n</reasoning>\n（该草稿仅用于推理，最终输出前会被移除。）\n\n【事实回顾】\n- 输出前再次确认价格、成交量、波动的关键事实与结论一致。\n- 缺口或冲突用 `risks` 中 `monitor: data_gap` 记录并给出补充建议。\n\n【输出格式】\n仅输出一个 JSON：\n{\n \"action\": \"BUY|BUY_S|BUY_M|BUY_L|SELL|HOLD\",\n \"confidence\": 0-1 之间的小数,\n \"summary\": \"一句话动量结论，需引用已核对的事实\",\n \"signals\": [\n {\n \"statement\": \"动量现象描述\",\n \"evidence\": \"对应字段或来源\",\n \"direction\": \"bullish|bearish|neutral\",\n \"horizon\": \"intraday|short|medium|long\"\n }\n ],\n \"risks\": [\n {\n \"threat\": \"风险或数据缺口\",\n \"monitor\": \"观测指标或 data_gap\",\n \"threshold\": \"触发阈值或补充要求\"\n }\n ]\n}\n示例：\n{\n \"action\": \"BUY_S\",\n \"confidence\": 0.71,\n \"summary\": \"短期价格突破叠加量能放大，动量延续概率高\",\n \"signals\": [\n {\n \"statement\": \"价格站上布林带上轨并保持3日\",\n \"evidence\": \"boll_upper_breakout\",\n \"direction\": \"bullish\",\n \"horizon\": \"short\"\n },\n {\n \"statement\": \"成交量较20日均线放大40%\",\n \"evidence\": \"volume_ma20_ratio\",\n \"direction\": \"bullish\",\n \"horizon\": \"short\"\n }\n ],\n \"risks\": [\n {\n \"threat\": \"14日 RSI 高位钝化转向\",\n \"monitor\": \"rsi_14\",\n \"threshold\": \"跌破65\"\n },\n {\n \"threat\": \"数据缺口：缺少期权隐含波动率\",\n \"monitor\": \"data_gap\",\n \"threshold\": \"fetch(iv30, last_5_days)\"\n }\n ]\n}\n若校验失败请调整温度并重新生成。",
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"variables": [
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"ts_code",
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"trade_date",
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"data_scope",
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"features",
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"market_snapshot",
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"supplements",
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"scratchpad"
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],
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"max_length": 4000,
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"required_context": [
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"ts_code",
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"trade_date",
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"features",
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"market_snapshot"
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],
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"version": "1.2.0",
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"metadata": {
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"label": "momentum_reasoning_flow",
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"notes": "强化动量信号构建与风险反证。"
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},
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"activate": false
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}
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}
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app/data/prompt_templates/news_dept@1.2.0.json
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app/data/prompt_templates/news_dept@1.2.0.json
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{
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"news_dept": {
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"name": "新闻事件部门模板",
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"description": "事件解读链式推理版",
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"template": "部门：新闻事件部门\n股票代码：{ts_code}\n交易日：{trade_date}\n\n【工作流】\n1. 事实确认：核对 {ts_code}、{trade_date} 及新闻时间戳是否一致。\n2. 信息分类：按“政策/业绩/行业/突发”整理新闻摘要，标记缺口或来源。\n3. 影响评估：判断对基本面、预期、资金行为的影响路径。\n4. 风险对冲：列出潜在反转因素或需跟踪的后续事件。\n\n【数据基线】\n- 数据范围：\n{data_scope}\n- 新闻要点：\n{features}\n- 市场反馈：\n{market_snapshot}\n- 补充材料：\n{supplements}\n\n【推理草稿】\n<reasoning>\n{scratchpad}\n步骤：\nA. 复述新闻核心事实与时间。\nB. 检查新闻来源与市场反馈是否相互印证。\nC. 逐条构造影响链：新闻 → 预期变化 → 市场反应。\nD. 列出后续需验证的关键事件或数据。\n</reasoning>\n（推理草稿仅供内部推理，最终输出前会被移除。）\n\n【事实回顾】\n- 输出前重新确认新闻事实与市场反馈无矛盾。\n- 缺失或冲突信息在 `risks` 中以 `monitor: data_gap` 记录。\n\n【输出格式】\n仅输出一个 JSON：\n{\n \"action\": \"BUY|BUY_S|BUY_M|BUY_L|SELL|HOLD\",\n \"confidence\": 0-1 之间的小数,\n \"summary\": \"一句话结论，引用已核对的新闻事实\",\n \"signals\": [\n {\n \"headline\": \"新闻标题或要点\",\n \"impact_path\": \"影响路径描述\",\n \"evidence\": \"数据/来源\",\n \"direction\": \"bullish|bearish|neutral\"\n }\n ],\n \"risks\": [\n {\n \"threat\": \"风险事件或数据缺口\",\n \"monitor\": \"观测指标或 data_gap\",\n \"threshold\": \"触发阈值或补充要求\",\n \"timeframe\": \"需跟踪的时间窗口\"\n }\n ]\n}\n示例：\n{\n \"action\": \"HOLD\",\n \"confidence\": 0.55,\n \"summary\": \"政策利好兑现但市场反馈平淡，短期观望\",\n \"signals\": [\n {\n \"headline\": \"监管发布新能源车补贴延长\",\n \"impact_path\": \"政策延续→成本下降→销量预期稳固\",\n \"evidence\": \"ministry_announcement_20240415\",\n \"direction\": \"bullish\"\n },\n {\n \"headline\": \"股价高开回落，量能未有效放大\",\n \"impact_path\": \"资金未跟进→短线获利了结\",\n \"evidence\": \"price_intraday_snapshot\",\n \"direction\": \"neutral\"\n }\n ],\n \"risks\": [\n {\n \"threat\": \"若下周销量数据低于季节性\",\n \"monitor\": \"weekly_ev_sales\",\n \"threshold\": \"同比<5%\",\n \"timeframe\": \"未来2周\"\n },\n {\n \"threat\": \"数据缺口：缺少外资持股比例最新变动\",\n \"monitor\": \"data_gap\",\n \"threshold\": \"fetch(qfii_holding_ratio, last_1_week)\",\n \"timeframe\": \"尽快\"\n }\n ]\n}\n若校验失败请降低温度并重新生成。",
|
||||||
|
"variables": [
|
||||||
|
"ts_code",
|
||||||
|
"trade_date",
|
||||||
|
"data_scope",
|
||||||
|
"features",
|
||||||
|
"market_snapshot",
|
||||||
|
"supplements",
|
||||||
|
"scratchpad"
|
||||||
|
],
|
||||||
|
"max_length": 4000,
|
||||||
|
"required_context": [
|
||||||
|
"ts_code",
|
||||||
|
"trade_date",
|
||||||
|
"features",
|
||||||
|
"market_snapshot"
|
||||||
|
],
|
||||||
|
"version": "1.2.0",
|
||||||
|
"metadata": {
|
||||||
|
"label": "news_reasoning_chain",
|
||||||
|
"notes": "强调新闻事实核对与影响链推理。"
|
||||||
|
},
|
||||||
|
"activate": false
|
||||||
|
}
|
||||||
|
}
|
||||||
29
app/data/prompt_templates/risk_dept@1.2.0.json
Normal file
29
app/data/prompt_templates/risk_dept@1.2.0.json
Normal file
@ -0,0 +1,29 @@
|
|||||||
|
{
|
||||||
|
"risk_dept": {
|
||||||
|
"name": "风险控制部门模板",
|
||||||
|
"description": "风险监测链式推理版",
|
||||||
|
"template": "部门：风险控制部门\n股票代码：{ts_code}\n交易日：{trade_date}\n\n【工作流】\n1. 事实确认：核对 {ts_code}、{trade_date} 与输入一致；冲突信息优先写入 `risks`。\n2. 风险清单：从市场风险、流动性风险、信用风险、操作风险四类梳理数据。\n3. 风险评估：为每类风险列出现象、证据、潜在损失链条。\n4. 缓释策略：指出监控指标、阈值以及应对动作。\n\n【数据基线】\n- 数据范围：\n{data_scope}\n- 风险特征：\n{features}\n- 市场切片：\n{market_snapshot}\n- 补充材料：\n{supplements}\n\n【推理草稿】\n<reasoning>\n{scratchpad}\n步骤：\nA. 复述关键事实及最新风险提示。\nB. 检查四类风险所需字段是否齐全，标记缺口。\nC. 逐条构造风险链：触发因素 → 传导路径 → 影响对象。\nD. 为每个风险匹配监控指标、阈值及应对策略。\n</reasoning>\n（推理草稿仅供思考，最终输出前会被移除。）\n\n【事实回顾】\n- 输出前确认关键敞口、波动指标与结论一致。\n- 缺口或冲突需在 `risks` 中以 `monitor: data_gap` 记录补充要求。\n\n【输出格式】\n仅输出一个 JSON：\n{\n \"action\": \"BUY|BUY_S|BUY_M|BUY_L|SELL|HOLD\",\n \"confidence\": 0-1 之间的小数,\n \"summary\": \"一句话风险结论，需引用已核对的事实\",\n \"signals\": [\n {\n \"threat\": \"风险描述\",\n \"evidence\": \"对应字段或来源\",\n \"monitor\": \"观测指标\",\n \"threshold\": \"触发阈值\",\n \"mitigation\": \"应对措施\"\n }\n ],\n \"risks\": [\n {\n \"threat\": \"残余风险或数据缺口\",\n \"monitor\": \"观测指标或 data_gap\",\n \"threshold\": \"触发阈值或补充要求\"\n }\n ]\n}\n示例：\n{\n \"action\": \"HOLD\",\n \"confidence\": 0.49,\n \"summary\": \"波动率上行与杠杆资金降温并存，建议观望并加强风险盯防\",\n \"signals\": [\n {\n \"threat\": \"股指期货基差转负\",\n \"evidence\": \"if_basis\",\n \"monitor\": \"if_basis\",\n \"threshold\": \"连续3日<-0.5%\",\n \"mitigation\": \"减仓对冲\"\n },\n {\n \"threat\": \"两融余额回落\",\n \"evidence\": \"margin_balance\",\n \"monitor\": \"margin_balance\",\n \"threshold\": \"5日内下降>3%\",\n \"mitigation\": \"降低杠杆\"\n }\n ],\n \"risks\": [\n {\n \"threat\": \"若波动率进一步上升\",\n \"monitor\": \"hv30\",\n \"threshold\": \">=35\"\n },\n {\n \"threat\": \"数据缺口：缺少财务杠杆率最新值\",\n \"monitor\": \"data_gap\",\n \"threshold\": \"fetch(financial_leverage, last_quarter)\"\n }\n ]\n}\n若校验失败请降低温度并重试。",
|
||||||
|
"variables": [
|
||||||
|
"ts_code",
|
||||||
|
"trade_date",
|
||||||
|
"data_scope",
|
||||||
|
"features",
|
||||||
|
"market_snapshot",
|
||||||
|
"supplements",
|
||||||
|
"scratchpad"
|
||||||
|
],
|
||||||
|
"max_length": 4000,
|
||||||
|
"required_context": [
|
||||||
|
"ts_code",
|
||||||
|
"trade_date",
|
||||||
|
"features",
|
||||||
|
"market_snapshot"
|
||||||
|
],
|
||||||
|
"version": "1.2.0",
|
||||||
|
"metadata": {
|
||||||
|
"label": "risk_reasoning_guard",
|
||||||
|
"notes": "引导风险链条分析与缓释策略。"
|
||||||
|
},
|
||||||
|
"activate": false
|
||||||
|
}
|
||||||
|
}
|
||||||
29
app/data/prompt_templates/value_dept@1.2.0.json
Normal file
29
app/data/prompt_templates/value_dept@1.2.0.json
Normal file
@ -0,0 +1,29 @@
|
|||||||
|
{
|
||||||
|
"value_dept": {
|
||||||
|
"name": "价值评估部门模板",
|
||||||
|
"description": "估值对比链式推理版",
|
||||||
|
"template": "部门：价值评估部门\n股票代码：{ts_code}\n交易日：{trade_date}\n\n【工作流】\n1. 事实确认：核对 {ts_code}、{trade_date} 以及估值基准是否一致。\n2. 数据盘点：梳理估值指标、盈利预期、对比组数据，标记缺口。\n3. 估值判断：构建 2-3 个价值信号，说明相对估值与绝对估值结论。\n4. 风险检验：列出可能导致估值失效的情景，并配置监控指标。\n\n【数据基线】\n- 数据范围：\n{data_scope}\n- 估值指标：\n{features}\n- 市场切片：\n{market_snapshot}\n- 补充材料：\n{supplements}\n\n【推理草稿】\n<reasoning>\n{scratchpad}\n步骤：\nA. 复述关键事实与估值基准。\nB. 检查指标是否覆盖估值、盈利、行业对比，缺失项记录。\nC. 逐条构造价值信号：指标 → 对比组 → 结论。\nD. 为每个信号列出验证指标与阈值，并考虑事件风险。\n</reasoning>\n（推理草稿仅用于思考，最终输出前会移除。）\n\n【事实回顾】\n- 输出前再次确认估值与盈利结论一致，未违背数据。\n- 缺口以 `monitor: data_gap` 记录并写明补充需求。\n\n【输出格式】\n仅输出一个 JSON：\n{\n \"action\": \"BUY|BUY_S|BUY_M|BUY_L|SELL|HOLD\",\n \"confidence\": 0-1 之间的小数,\n \"summary\": \"一句话估值结论，引用已核对的事实\",\n \"signals\": [\n {\n \"statement\": \"估值信号描述\",\n \"evidence\": \"对应字段或来源\",\n \"relative\": \"相对估值结论\",\n \"absolute\": \"绝对估值结论\"\n }\n ],\n \"risks\": [\n {\n \"threat\": \"风险事件或数据缺口\",\n \"monitor\": \"观测指标或 data_gap\",\n \"threshold\": \"触发阈值或补充要求\"\n }\n ]\n}\n示例：\n{\n \"action\": \"BUY_L\",\n \"confidence\": 0.74,\n \"summary\": \"公司估值折价叠加盈利改善，具备中长期配置价值\",\n \"signals\": [\n {\n \"statement\": \"PE(TTM) 低于行业20%，盈利增速加快\",\n \"evidence\": \"pe_ttm, eps_growth\",\n \"relative\": \"折价\",\n \"absolute\": \"合理偏低\"\n },\n {\n \"statement\": \"自由现金流维持正值并提升\",\n \"evidence\": \"fcf_yoy\",\n \"relative\": \"优于行业\",\n \"absolute\": \"稳健\"\n }\n ],\n \"risks\": [\n {\n \"threat\": \"若利润率回落\",\n \"monitor\": \"net_margin\",\n \"threshold\": \"连续两季下降\"\n },\n {\n \"threat\": \"数据缺口：缺少可比公司的 ROE\",\n \"monitor\": \"data_gap\",\n \"threshold\": \"fetch(peer_roe, last_quarter)\"\n }\n ]\n}\n若校验失败请降低温度并重试。",
|
||||||
|
"variables": [
|
||||||
|
"ts_code",
|
||||||
|
"trade_date",
|
||||||
|
"data_scope",
|
||||||
|
"features",
|
||||||
|
"market_snapshot",
|
||||||
|
"supplements",
|
||||||
|
"scratchpad"
|
||||||
|
],
|
||||||
|
"max_length": 4000,
|
||||||
|
"required_context": [
|
||||||
|
"ts_code",
|
||||||
|
"trade_date",
|
||||||
|
"features",
|
||||||
|
"market_snapshot"
|
||||||
|
],
|
||||||
|
"version": "1.2.0",
|
||||||
|
"metadata": {
|
||||||
|
"label": "value_reasoning_guard",
|
||||||
|
"notes": "加强估值对比与风险验证。"
|
||||||
|
},
|
||||||
|
"activate": false
|
||||||
|
}
|
||||||
|
}
|
||||||
Loading…
Reference in New Issue
Block a user