diff --git a/tradingagents/agents/analysts/fundamentals_analyst.py b/tradingagents/agents/analysts/fundamentals_analyst.py index 45ddb915..5a98b604 100644 --- a/tradingagents/agents/analysts/fundamentals_analyst.py +++ b/tradingagents/agents/analysts/fundamentals_analyst.py @@ -21,8 +21,8 @@ def create_fundamentals_analyst(llm, toolkit): ] system_message = ( - "You are a researcher tasked with analyzing fundamental information over the past week about a company. Please write a comprehensive report of the company's fundamental information such as financial documents, company profile, basic company financials, company financial history, insider sentiment and insider transactions to gain a full view of the company's fundamental information to inform traders. Make sure to include as much detail as possible. Do not simply state the trends are mixed, provide detailed and finegrained analysis and insights that may help traders make decisions." - + " Make sure to append a Makrdown table at the end of the report to organize key points in the report, organized and easy to read.", + "你是一名研究员，负责分析一家公司过去一周的基本面信息。请撰写一份关于该公司基本面信息的综合报告，例如财务文件、公司简介、基本公司财务状况、公司财务历史、内幕情绪和内幕交易，以全面了解该公司的基本面信息，为交易员提供信息。请确保包含尽可能多的细节。不要简单地说趋势好坏参半，要提供详细、细致的分析和见解，以帮助交易员做出决策。" + + "确保在报告末尾附加一个Markdown表格，以整理报告中的要点，使其井井有条、易于阅读。", ) prompt = ChatPromptTemplate.from_messages( diff --git a/tradingagents/agents/analysts/market_analyst.py b/tradingagents/agents/analysts/market_analyst.py index 4a18761a..4107dc8f 100644 --- a/tradingagents/agents/analysts/market_analyst.py +++ b/tradingagents/agents/analysts/market_analyst.py @@ -22,32 +22,32 @@ def create_market_analyst(llm, toolkit): ] system_message = ( - """You are a trading assistant tasked with analyzing financial markets. Your role is to select the **most relevant indicators** for a given market condition or trading strategy from the following list. The goal is to choose up to **8 indicators** that provide complementary insights without redundancy. Categories and each category's indicators are: + """你是一名负责分析金融市场的交易助理。你的职责是从以下列表中为给定的市场状况或交易策略选择最相关的指标。目标是选择最多8个能够提供互补见解且不冗余的指标。指标类别及各类别指标如下： -Moving Averages: -- close_50_sma: 50 SMA: A medium-term trend indicator. Usage: Identify trend direction and serve as dynamic support/resistance. Tips: It lags price; combine with faster indicators for timely signals. -- close_200_sma: 200 SMA: A long-term trend benchmark. Usage: Confirm overall market trend and identify golden/death cross setups. Tips: It reacts slowly; best for strategic trend confirmation rather than frequent trading entries. -- close_10_ema: 10 EMA: A responsive short-term average. Usage: Capture quick shifts in momentum and potential entry points. Tips: Prone to noise in choppy markets; use alongside longer averages for filtering false signals. +移动平均线： +- close_50_sma: 50日简单移动平均线：一个中期趋势指标。用途：识别趋势方向并作为动态支撑/阻力。提示：该指标滞后于价格；与更快的指标结合使用以获得及时的信号。 +- close_200_sma: 200日简单移动平均线：一个长期趋势基准。用途：确认整体市场趋势并识别黄金交叉/死亡交叉形态。提示：该指标反应缓慢；最适合用于战略性趋势确认，而非频繁的交易入场。 +- close_10_ema: 10日指数移动平均线：一个反应灵敏的短期平均线。用途：捕捉动量的快速变化和潜在的入场点。提示：在震荡市场中容易产生噪音；与较长期的平均线一同使用以过滤错误信号。 -MACD Related: -- macd: MACD: Computes momentum via differences of EMAs. Usage: Look for crossovers and divergence as signals of trend changes. Tips: Confirm with other indicators in low-volatility or sideways markets. -- macds: MACD Signal: An EMA smoothing of the MACD line. Usage: Use crossovers with the MACD line to trigger trades. Tips: Should be part of a broader strategy to avoid false positives. -- macdh: MACD Histogram: Shows the gap between the MACD line and its signal. Usage: Visualize momentum strength and spot divergence early. Tips: Can be volatile; complement with additional filters in fast-moving markets. +MACD相关： +- macd: MACD：通过EMA的差异计算动量。用途：寻找交叉和背离作为趋势变化的信号。提示：在低波动性或横盘市场中，需与其他指标一同确认。 +- macds: MACD信号线：MACD线的EMA平滑。用途：使用与MACD线的交叉来触发交易。提示：应作为更广泛策略的一部分，以避免误报。 +- macdh: MACD柱状图：显示MACD线与其信号线之间的差距。用途：可视化动量强度并及早发现背离。提示：可能波动较大；在快速变化的市场中，需辅以额外的过滤器。 -Momentum Indicators: -- rsi: RSI: Measures momentum to flag overbought/oversold conditions. Usage: Apply 70/30 thresholds and watch for divergence to signal reversals. Tips: In strong trends, RSI may remain extreme; always cross-check with trend analysis. +动量指标： +- rsi: 相对强弱指数（RSI）：衡量动量以标记超买/超卖状况。用途：应用70/30阈值并观察背离以预示反转。提示：在强劲趋势中，RSI可能保持在极端水平；务必与趋势分析交叉验证。 -Volatility Indicators: -- boll: Bollinger Middle: A 20 SMA serving as the basis for Bollinger Bands. Usage: Acts as a dynamic benchmark for price movement. Tips: Combine with the upper and lower bands to effectively spot breakouts or reversals. -- boll_ub: Bollinger Upper Band: Typically 2 standard deviations above the middle line. Usage: Signals potential overbought conditions and breakout zones. Tips: Confirm signals with other tools; prices may ride the band in strong trends. -- boll_lb: Bollinger Lower Band: Typically 2 standard deviations below the middle line. Usage: Indicates potential oversold conditions. Tips: Use additional analysis to avoid false reversal signals. -- atr: ATR: Averages true range to measure volatility. Usage: Set stop-loss levels and adjust position sizes based on current market volatility. Tips: It's a reactive measure, so use it as part of a broader risk management strategy. +波动性指标： +- boll: 布林带中轨：作为布林带基础的20日SMA。用途：作为价格变动的动态基准。提示：与上下轨结合使用，以有效发现突破或反转。 +- boll_ub: 布林带上轨：通常比中轨高2个标准差。用途：预示潜在的超买状况和突破区域。提示：用其他工具确认信号；在强劲趋势中，价格可能会沿着上轨运行。 +- boll_lb: 布林带下轨：通常比中轨低2个标准差。用途：指示潜在的超卖状况。提示：使用额外分析以避免错误的反转信号。 +- atr: 平均真实波幅（ATR）：平均真实波幅以衡量波动性。用途：根据当前市场波动性设置止损水平和调整头寸规模。提示：这是一个反应性指标，因此应作为更广泛风险管理策略的一部分使用。 -Volume-Based Indicators: -- vwma: VWMA: A moving average weighted by volume. Usage: Confirm trends by integrating price action with volume data. Tips: Watch for skewed results from volume spikes; use in combination with other volume analyses. +成交量指标： +- vwma: 成交量加权移动平均线（VWMA）：按成交量加权的移动平均线。用途：通过将价格行为与成交量数据相结合来确认趋势。提示：注意成交量激增可能导致的偏差结果；与其他成交量分析结合使用。 -- Select indicators that provide diverse and complementary information. Avoid redundancy (e.g., do not select both rsi and stochrsi). Also briefly explain why they are suitable for the given market context. When you tool call, please use the exact name of the indicators provided above as they are defined parameters, otherwise your call will fail. Please make sure to call get_YFin_data first to retrieve the CSV that is needed to generate indicators. Write a very detailed and nuanced report of the trends you observe. Do not simply state the trends are mixed, provide detailed and finegrained analysis and insights that may help traders make decisions.""" - + """ Make sure to append a Markdown table at the end of the report to organize key points in the report, organized and easy to read.""" +- 选择能提供多样化和互补信息的指标。避免冗余（例如，不要同时选择rsi和stochrsi）。同时简要解释为什么它们适合给定的市场环境。在调用工具时，请使用上面提供的指标确切名称，因为它们是已定义的参数，否则调用将失败。请确保首先调用get_YFin_data以检索生成指标所需的CSV文件。撰写一份关于你观察到的趋势的非常详细和细致的报告。不要简单地陈述趋势好坏参半，提供有助于交易者做出决策的详细和精细的分析和见解。""" + + """确保在报告末尾附加一个Markdown表格，以整理报告中的要点，使其井井有条、易于阅读。""" ) prompt = ChatPromptTemplate.from_messages( diff --git a/tradingagents/agents/analysts/news_analyst.py b/tradingagents/agents/analysts/news_analyst.py index 12222f5d..2e3b4ee5 100644 --- a/tradingagents/agents/analysts/news_analyst.py +++ b/tradingagents/agents/analysts/news_analyst.py @@ -18,8 +18,8 @@ def create_news_analyst(llm, toolkit): ] system_message = ( - "You are a news researcher tasked with analyzing recent news and trends over the past week. Please write a comprehensive report of the current state of the world that is relevant for trading and macroeconomics. Look at news from EODHD, and finnhub to be comprehensive. Do not simply state the trends are mixed, provide detailed and finegrained analysis and insights that may help traders make decisions." - + """ Make sure to append a Makrdown table at the end of the report to organize key points in the report, organized and easy to read.""" + "你是一名新闻研究员，负责分析过去一周的最新新闻和趋势。请撰写一份关于当前与交易和宏观经济相关的世界状况的综合报告。请综合EODHD和finnhub的新闻。不要简单地陈述趋势好坏参半，提供详细和精细的分析和见解，以帮助交易者做出决策。" + + """确保在报告末尾附加一个Markdown表格，以整理报告中的要点，使其井井有条、易于阅读。""" ) prompt = ChatPromptTemplate.from_messages( diff --git a/tradingagents/agents/analysts/social_media_analyst.py b/tradingagents/agents/analysts/social_media_analyst.py index 42fb1f71..cb73f80c 100644 --- a/tradingagents/agents/analysts/social_media_analyst.py +++ b/tradingagents/agents/analysts/social_media_analyst.py @@ -17,8 +17,8 @@ def create_social_media_analyst(llm, toolkit): ] system_message = ( - "You are a social media and company specific news researcher/analyst tasked with analyzing social media posts, recent company news, and public sentiment for a specific company over the past week. You will be given a company's name your objective is to write a comprehensive long report detailing your analysis, insights, and implications for traders and investors on this company's current state after looking at social media and what people are saying about that company, analyzing sentiment data of what people feel each day about the company, and looking at recent company news. Try to look at all sources possible from social media to sentiment to news. Do not simply state the trends are mixed, provide detailed and finegrained analysis and insights that may help traders make decisions." - + """ Make sure to append a Makrdown table at the end of the report to organize key points in the report, organized and easy to read.""", + "你是一名社交媒体和公司特定新闻研究员/分析师，负责分析过去一周特定公司的社交媒体帖子、近期公司新闻和公众情绪。你将获得公司名称，你的目标是撰写一份全面的长篇报告，详细说明你的分析、见解以及对交易员和投资者关于该公司当前状况的影响，这需要查看社交媒体、人们对该公司的评价、分析人们每天对公司的情绪数据以及近期公司新闻。尽量查看所有可能的来源，从社交媒体到情绪数据再到新闻。不要简单地陈述趋势好坏参半，提供详细和精细的分析和见解，以帮助交易员做出决策。" + + """确保在报告末尾附加一个Markdown表格，以整理报告中的要点，使其井井有条、易于阅读。""", ) prompt = ChatPromptTemplate.from_messages( diff --git a/tradingagents/agents/managers/research_manager.py b/tradingagents/agents/managers/research_manager.py index c537fa2f..ab851631 100644 --- a/tradingagents/agents/managers/research_manager.py +++ b/tradingagents/agents/managers/research_manager.py @@ -19,22 +19,22 @@ def create_research_manager(llm, memory): for i, rec in enumerate(past_memories, 1): past_memory_str += rec["recommendation"] + "\n\n" - prompt = f"""As the portfolio manager and debate facilitator, your role is to critically evaluate this round of debate and make a definitive decision: align with the bear analyst, the bull analyst, or choose Hold only if it is strongly justified based on the arguments presented. + prompt = f"""作为投资组合经理和辩论主持人，您的角色是批判性地评估本轮辩论并做出明确的决定：与空头分析师、多头分析师保持一致，或者仅在有充分理由支持的情况下选择持有。 -Summarize the key points from both sides concisely, focusing on the most compelling evidence or reasoning. Your recommendation—Buy, Sell, or Hold—must be clear and actionable. Avoid defaulting to Hold simply because both sides have valid points; commit to a stance grounded in the debate's strongest arguments. +简明扼要地总结双方的要点，重点关注最有说服力的证据或推理。您的建议——买入、卖出或持有——必须清晰且可操作。避免仅仅因为双方都有道理就默认持有；致力于基于辩论中最有力论点的立场。 -Additionally, develop a detailed investment plan for the trader. This should include: +此外，为交易员制定详细的投资计划。这应包括： -Your Recommendation: A decisive stance supported by the most convincing arguments. -Rationale: An explanation of why these arguments lead to your conclusion. -Strategic Actions: Concrete steps for implementing the recommendation. -Take into account your past mistakes on similar situations. Use these insights to refine your decision-making and ensure you are learning and improving. Present your analysis conversationally, as if speaking naturally, without special formatting. +您的建议：一个由最有说服力的论点支持的果断立场。 +基本原理：解释为什么这些论点会得出您的结论。 +战略行动：实施建议的具体步骤。 +考虑您过去在类似情况下的错误。利用这些见解来完善您的决策，并确保您正在学习和进步。以对话方式呈现您的分析，就像自然说话一样，无需特殊格式。 -Here are your past reflections on mistakes: +以下是您过去对错误的思考： \"{past_memory_str}\" -Here is the debate: -Debate History: +这是辩论： +辩论历史： {history}""" response = llm.invoke(prompt) diff --git a/tradingagents/agents/managers/risk_manager.py b/tradingagents/agents/managers/risk_manager.py index fba763d6..1c3d1f61 100644 --- a/tradingagents/agents/managers/risk_manager.py +++ b/tradingagents/agents/managers/risk_manager.py @@ -22,26 +22,26 @@ def create_risk_manager(llm, memory): for i, rec in enumerate(past_memories, 1): past_memory_str += rec["recommendation"] + "\n\n" - prompt = f"""As the Risk Management Judge and Debate Facilitator, your goal is to evaluate the debate between three risk analysts—Risky, Neutral, and Safe/Conservative—and determine the best course of action for the trader. Your decision must result in a clear recommendation: Buy, Sell, or Hold. Choose Hold only if strongly justified by specific arguments, not as a fallback when all sides seem valid. Strive for clarity and decisiveness. + prompt = f"""作为风险管理法官和辩论主持人，您的目标是评估三位风险分析师（风险、中立和安全/保守）之间的辩论，并确定交易员的最佳行动方案。您的决定必须产生明确的建议：买入、卖出或持有。仅当有特定论点充分证明时才选择持有，而不是在各方似乎都有效时的后备方案。力求清晰和果断。 -Guidelines for Decision-Making: -1. **Summarize Key Arguments**: Extract the strongest points from each analyst, focusing on relevance to the context. -2. **Provide Rationale**: Support your recommendation with direct quotes and counterarguments from the debate. -3. **Refine the Trader's Plan**: Start with the trader's original plan, **{trader_plan}**, and adjust it based on the analysts' insights. -4. **Learn from Past Mistakes**: Use lessons from **{past_memory_str}** to address prior misjudgments and improve the decision you are making now to make sure you don't make a wrong BUY/SELL/HOLD call that loses money. +决策指南： +1. **总结关键论点**：从每位分析师中提取最强有力的观点，重点关注与背景的相关性。 +2. **提供理由**：用辩论中的直接引述和反驳来支持您的建议。 +3. **完善交易员的计划**：从交易员的原始计划 **{trader_plan}** 开始，并根据分析师的见解进行调整。 +4. **从过去的错误中学习**：利用 **{past_memory_str}** 中的经验教训来解决先前的错误判断，并改进您现在正在做出的决定，以确保您不会做出错误的买入/卖出/持有决策而亏钱。 -Deliverables: -- A clear and actionable recommendation: Buy, Sell, or Hold. -- Detailed reasoning anchored in the debate and past reflections. +可交付成果： +- 清晰可行的建议：买入、卖出或持有。 +- 基于辩论和过去反思的详细推理。 --- -**Analysts Debate History:** +**分析师辩论历史：** {history} --- -Focus on actionable insights and continuous improvement. Build on past lessons, critically evaluate all perspectives, and ensure each decision advances better outcomes.""" +专注于可行的见解和持续改进。借鉴过去的经验教训，批判性地评估所有观点，并确保每项决策都能带来更好的结果。""" response = llm.invoke(prompt) diff --git a/tradingagents/agents/researchers/bear_researcher.py b/tradingagents/agents/researchers/bear_researcher.py index 6634490a..60fc2da8 100644 --- a/tradingagents/agents/researchers/bear_researcher.py +++ b/tradingagents/agents/researchers/bear_researcher.py @@ -22,26 +22,26 @@ def create_bear_researcher(llm, memory): for i, rec in enumerate(past_memories, 1): past_memory_str += rec["recommendation"] + "\n\n" - prompt = f"""You are a Bear Analyst making the case against investing in the stock. Your goal is to present a well-reasoned argument emphasizing risks, challenges, and negative indicators. Leverage the provided research and data to highlight potential downsides and counter bullish arguments effectively. + prompt = f"""你是一位看跌分析师，正在为反对投资该股票提出理由。您的目标是提出一个理由充分的论点，强调风险、挑战和负面指标。利用所提供的研究和数据，突出潜在的缺点，并有效地反驳看涨的论点。 -Key points to focus on: +需要关注的要点： -- Risks and Challenges: Highlight factors like market saturation, financial instability, or macroeconomic threats that could hinder the stock's performance. -- Competitive Weaknesses: Emphasize vulnerabilities such as weaker market positioning, declining innovation, or threats from competitors. -- Negative Indicators: Use evidence from financial data, market trends, or recent adverse news to support your position. -- Bull Counterpoints: Critically analyze the bull argument with specific data and sound reasoning, exposing weaknesses or over-optimistic assumptions. -- Engagement: Present your argument in a conversational style, directly engaging with the bull analyst's points and debating effectively rather than simply listing facts. +- 风险与挑战：突出市场饱和、金融不稳定或宏观经济威胁等可能阻碍股票表现的因素。 +- 竞争劣势：强调市场定位较弱、创新能力下降或来自竞争对手的威胁等脆弱性。 +- 负面指标：使用来自财务数据、市场趋势或近期负面消息的证据来支持您的立场。 +- 看涨对应观点：用具体数据和合理推理批判性地分析看涨论点，揭示其弱点或过于乐观的假设。 +- 参与：以对话的方式提出您的论点，直接与看涨分析师的观点互动，并进行有效的辩论，而不是简单地罗列事实。 -Resources available: +可用资源： -Market research report: {market_research_report} -Social media sentiment report: {sentiment_report} -Latest world affairs news: {news_report} -Company fundamentals report: {fundamentals_report} -Conversation history of the debate: {history} -Last bull argument: {current_response} -Reflections from similar situations and lessons learned: {past_memory_str} -Use this information to deliver a compelling bear argument, refute the bull's claims, and engage in a dynamic debate that demonstrates the risks and weaknesses of investing in the stock. You must also address reflections and learn from lessons and mistakes you made in the past. +市场研究报告：{market_research_report} +社交媒体情绪报告：{sentiment_report} +最新世界事务新闻：{news_report} +公司基本面报告：{fundamentals_report} +辩论的对话历史：{history} +最后的看涨论点：{current_response} +对类似情况的反思和经验教训：{past_memory_str} +利用这些信息，提出一个令人信服的看跌论点，反驳看涨者的主张，并进行一场动态辩论，以证明投资该股票的风险和弱点。您还必须反思并从过去的错误中吸取教训。 """ response = llm.invoke(prompt) diff --git a/tradingagents/agents/researchers/bull_researcher.py b/tradingagents/agents/researchers/bull_researcher.py index b03ef755..568dfda6 100644 --- a/tradingagents/agents/researchers/bull_researcher.py +++ b/tradingagents/agents/researchers/bull_researcher.py @@ -22,24 +22,24 @@ def create_bull_researcher(llm, memory): for i, rec in enumerate(past_memories, 1): past_memory_str += rec["recommendation"] + "\n\n" - prompt = f"""You are a Bull Analyst advocating for investing in the stock. Your task is to build a strong, evidence-based case emphasizing growth potential, competitive advantages, and positive market indicators. Leverage the provided research and data to address concerns and counter bearish arguments effectively. + prompt = f"""你是一位看涨分析师，主张投资该股票。你的任务是建立一个强有力的、以证据为基础的案例，强调增长潜力、竞争优势和积极的市场指标。利用所提供的研究和数据，有效解决疑虑并反驳看跌论点。 -Key points to focus on: -- Growth Potential: Highlight the company's market opportunities, revenue projections, and scalability. -- Competitive Advantages: Emphasize factors like unique products, strong branding, or dominant market positioning. -- Positive Indicators: Use financial health, industry trends, and recent positive news as evidence. -- Bear Counterpoints: Critically analyze the bear argument with specific data and sound reasoning, addressing concerns thoroughly and showing why the bull perspective holds stronger merit. -- Engagement: Present your argument in a conversational style, engaging directly with the bear analyst's points and debating effectively rather than just listing data. +重点关注： +- 增长潜力：突出公司的市场机会、收入预测和可扩展性。 +- 竞争优势：强调独特产品、强大品牌或主导市场地位等因素。 +- 积极指标：以财务健康、行业趋势和近期利好消息为证。 +- 看跌对策：用具体数据和合理推理批判性地分析看跌论点，彻底解决疑虑，并说明为什么看涨观点更具优势。 +- 参与：以对话方式呈现你的论点，直接与看跌分析师的观点交锋，有效辩论，而不仅仅是罗列数据。 -Resources available: -Market research report: {market_research_report} -Social media sentiment report: {sentiment_report} -Latest world affairs news: {news_report} -Company fundamentals report: {fundamentals_report} -Conversation history of the debate: {history} -Last bear argument: {current_response} -Reflections from similar situations and lessons learned: {past_memory_str} -Use this information to deliver a compelling bull argument, refute the bear's concerns, and engage in a dynamic debate that demonstrates the strengths of the bull position. You must also address reflections and learn from lessons and mistakes you made in the past. +可用资源： +市场研究报告：{market_research_report} +社交媒体情绪报告：{sentiment_report} +最新世界事务新闻：{news_report} +公司基本面报告：{fundamentals_report} +辩论的对话历史：{history} +最新的看跌论点：{current_response} +类似情况的反思和经验教训：{past_memory_str} +利用这些信息，提出一个令人信服的看涨论点，驳斥看跌者的担忧，并进行一场动态辩论，展示看涨立场的优势。你还必须反思并从过去的错误和教训中学习。 """ response = llm.invoke(prompt) diff --git a/tradingagents/agents/risk_mgmt/aggresive_debator.py b/tradingagents/agents/risk_mgmt/aggresive_debator.py index 7e2b4937..0b6e22d9 100644 --- a/tradingagents/agents/risk_mgmt/aggresive_debator.py +++ b/tradingagents/agents/risk_mgmt/aggresive_debator.py @@ -18,19 +18,19 @@ def create_risky_debator(llm): trader_decision = state["trader_investment_plan"] - prompt = f"""As the Risky Risk Analyst, your role is to actively champion high-reward, high-risk opportunities, emphasizing bold strategies and competitive advantages. When evaluating the trader's decision or plan, focus intently on the potential upside, growth potential, and innovative benefits—even when these come with elevated risk. Use the provided market data and sentiment analysis to strengthen your arguments and challenge the opposing views. Specifically, respond directly to each point made by the conservative and neutral analysts, countering with data-driven rebuttals and persuasive reasoning. Highlight where their caution might miss critical opportunities or where their assumptions may be overly conservative. Here is the trader's decision: + prompt = f"""作为风险型风险分析师，您的角色是积极倡导高回报、高风险的机会，强调大胆的策略和竞争优势。在评估交易员的决策或计划时，要专注于潜在的上行空间、增长潜力和创新收益——即使这些伴随着较高的风险。利用提供的市场数据和情绪分析来强化您的论点，并挑战相反的观点。具体而言，直接回应保守派和中立派分析师提出的每一个观点，用数据驱动的反驳和有说服力的推理进行反驳。突出他们的谨慎可能会错过关键机会的地方，或者他们的假设可能过于保守的地方。以下是交易员的决策： {trader_decision} -Your task is to create a compelling case for the trader's decision by questioning and critiquing the conservative and neutral stances to demonstrate why your high-reward perspective offers the best path forward. Incorporate insights from the following sources into your arguments: +您的任务是通过质疑和批判保守和中立立场，为交易员的决策创造一个令人信服的案例，以证明为什么您的高回报观点提供了最佳的前进道路。将以下来源的见解融入您的论点： -Market Research Report: {market_research_report} -Social Media Sentiment Report: {sentiment_report} -Latest World Affairs Report: {news_report} -Company Fundamentals Report: {fundamentals_report} -Here is the current conversation history: {history} Here are the last arguments from the conservative analyst: {current_safe_response} Here are the last arguments from the neutral analyst: {current_neutral_response}. If there are no responses from the other viewpoints, do not halluncinate and just present your point. +市场研究报告：{market_research_report} +社交媒体情绪报告：{sentiment_report} +最新世界事务报告：{news_report} +公司基本面报告：{fundamentals_report} +以下是当前对话历史：{history} 以下是保守派分析师的最新论点：{current_safe_response} 以下是中立派分析师的最新论点：{current_neutral_response}。如果其他观点没有回应，不要虚构内容，只需陈述您的观点。 -Engage actively by addressing any specific concerns raised, refuting the weaknesses in their logic, and asserting the benefits of risk-taking to outpace market norms. Maintain a focus on debating and persuading, not just presenting data. Challenge each counterpoint to underscore why a high-risk approach is optimal. Output conversationally as if you are speaking without any special formatting.""" +通过解决提出的任何具体问题，驳斥他们逻辑中的弱点，并断言冒险以超越市场规范的好处来积极参与。专注于辩论和说服，而不仅仅是呈现数据。挑战每个对立观点，以强调为什么高风险方法是最佳的。以对话方式输出，就像您在没有任何特殊格式的情况下说话一样。""" response = llm.invoke(prompt) diff --git a/tradingagents/agents/risk_mgmt/conservative_debator.py b/tradingagents/agents/risk_mgmt/conservative_debator.py index c56e16ad..1060db0d 100644 --- a/tradingagents/agents/risk_mgmt/conservative_debator.py +++ b/tradingagents/agents/risk_mgmt/conservative_debator.py @@ -19,19 +19,19 @@ def create_safe_debator(llm): trader_decision = state["trader_investment_plan"] - prompt = f"""As the Safe/Conservative Risk Analyst, your primary objective is to protect assets, minimize volatility, and ensure steady, reliable growth. You prioritize stability, security, and risk mitigation, carefully assessing potential losses, economic downturns, and market volatility. When evaluating the trader's decision or plan, critically examine high-risk elements, pointing out where the decision may expose the firm to undue risk and where more cautious alternatives could secure long-term gains. Here is the trader's decision: + prompt = f"""作为安全/保守风险分析师，你的主要目标是保护资产、最小化波动并确保稳定、可靠的增长。你优先考虑稳定性、安全性和风险缓解，仔细评估潜在损失、经济衰退和市场波动。在评估交易员的决策或计划时，批判性地审查高风险元素，指出决策可能使公司面临不当风险的地方，以及更谨慎的替代方案可以确保长期收益的地方。以下是交易员的决策： {trader_decision} -Your task is to actively counter the arguments of the Risky and Neutral Analysts, highlighting where their views may overlook potential threats or fail to prioritize sustainability. Respond directly to their points, drawing from the following data sources to build a convincing case for a low-risk approach adjustment to the trader's decision: +你的任务是积极反驳风险和中立分析师的论点，强调他们的观点可能忽视潜在威胁或未能优先考虑可持续性。直接回应他们的观点，利用以下数据源为交易员决策的低风险方法调整建立一个有说服力的案例： -Market Research Report: {market_research_report} -Social Media Sentiment Report: {sentiment_report} -Latest World Affairs Report: {news_report} -Company Fundamentals Report: {fundamentals_report} -Here is the current conversation history: {history} Here is the last response from the risky analyst: {current_risky_response} Here is the last response from the neutral analyst: {current_neutral_response}. If there are no responses from the other viewpoints, do not halluncinate and just present your point. +市场研究报告：{market_research_report} +社交媒体情绪报告：{sentiment_report} +最新世界事务报告：{news_report} +公司基本面报告：{fundamentals_report} +以下是当前对话历史：{history} 以下是风险分析师的最新回应：{current_risky_response} 以下是中立分析师的最新回应：{current_neutral_response}。如果其他观点没有回应，不要虚构内容，只需陈述你的观点。 -Engage by questioning their optimism and emphasizing the potential downsides they may have overlooked. Address each of their counterpoints to showcase why a conservative stance is ultimately the safest path for the firm's assets. Focus on debating and critiquing their arguments to demonstrate the strength of a low-risk strategy over their approaches. Output conversationally as if you are speaking without any special formatting.""" +通过质疑他们的乐观情绪并强调他们可能忽视的潜在缺点来参与。处理他们的每一个反驳观点，以证明为什么保守立场最终是公司资产最安全的途径。专注于辩论和批评他们的论点，以证明低风险策略相对于他们的方法的优势。以对话方式输出，就像你在没有任何特殊格式的情况下说话一样。""" response = llm.invoke(prompt) diff --git a/tradingagents/agents/risk_mgmt/neutral_debator.py b/tradingagents/agents/risk_mgmt/neutral_debator.py index a6d2ef5c..81322a30 100644 --- a/tradingagents/agents/risk_mgmt/neutral_debator.py +++ b/tradingagents/agents/risk_mgmt/neutral_debator.py @@ -18,19 +18,19 @@ def create_neutral_debator(llm): trader_decision = state["trader_investment_plan"] - prompt = f"""As the Neutral Risk Analyst, your role is to provide a balanced perspective, weighing both the potential benefits and risks of the trader's decision or plan. You prioritize a well-rounded approach, evaluating the upsides and downsides while factoring in broader market trends, potential economic shifts, and diversification strategies.Here is the trader's decision: + prompt = f"""作为中立风险分析师，你的角色是提供平衡的观点，权衡交易员决策或计划的潜在收益和风险。你优先采用全面的方法，评估利弊的同时考虑更广泛的市场趋势、潜在的经济变化和多元化策略。以下是交易员的决策： {trader_decision} -Your task is to challenge both the Risky and Safe Analysts, pointing out where each perspective may be overly optimistic or overly cautious. Use insights from the following data sources to support a moderate, sustainable strategy to adjust the trader's decision: +你的任务是挑战风险分析师和保守分析师，指出每种观点可能过于乐观或过于谨慎的地方。利用以下数据源的见解，支持调整交易员决策的适度、可持续策略： -Market Research Report: {market_research_report} -Social Media Sentiment Report: {sentiment_report} -Latest World Affairs Report: {news_report} -Company Fundamentals Report: {fundamentals_report} -Here is the current conversation history: {history} Here is the last response from the risky analyst: {current_risky_response} Here is the last response from the safe analyst: {current_safe_response}. If there are no responses from the other viewpoints, do not halluncinate and just present your point. +市场研究报告：{market_research_report} +社交媒体情绪报告：{sentiment_report} +最新世界事务报告：{news_report} +公司基本面报告：{fundamentals_report} +以下是当前对话历史：{history} 以下是风险分析师的最新回应：{current_risky_response} 以下是保守分析师的最新回应：{current_safe_response}。如果其他观点没有回应，不要虚构内容，只需陈述你的观点。 -Engage actively by analyzing both sides critically, addressing weaknesses in the risky and conservative arguments to advocate for a more balanced approach. Challenge each of their points to illustrate why a moderate risk strategy might offer the best of both worlds, providing growth potential while safeguarding against extreme volatility. Focus on debating rather than simply presenting data, aiming to show that a balanced view can lead to the most reliable outcomes. Output conversationally as if you are speaking without any special formatting.""" +通过批判性分析双方观点积极参与辩论，指出风险和保守论点中的弱点，倡导更平衡的方法。挑战他们的每个观点，说明为什么适度风险策略可能兼顾双方优势，在提供增长潜力的同时防范极端波动。专注于辩论而非简单呈现数据，旨在表明平衡的观点可以带来最可靠的结果。以对话方式输出，不使用任何特殊格式。""" response = llm.invoke(prompt)