🐛 修复 risk_mgmt prompt 字符串断行 SyntaxError

This commit is contained in:
dw1161 2026-03-21 15:28:27 +08:00
parent 4d7a78cea4
commit 2c87c33c69
4 changed files with 4 additions and 12 deletions

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@ -43,9 +43,7 @@ Deliverables:
Focus on actionable insights and continuous improvement. Build on past lessons, critically evaluate all perspectives, and ensure each decision advances better outcomes.""" Focus on actionable insights and continuous improvement. Build on past lessons, critically evaluate all perspectives, and ensure each decision advances better outcomes."""
prompt += " prompt += "\n\n**重要:请完全用简体中文输出你的分析和辩论内容。**"
**重要请完全用简体中文输出你的分析和辩论内容**"
response = llm.invoke(prompt) response = llm.invoke(prompt)
new_risk_debate_state = { new_risk_debate_state = {

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@ -32,9 +32,7 @@ Here is the current conversation history: {history} Here are the last arguments
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.""" 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."""
prompt += " prompt += "\n\n**重要:请完全用简体中文输出你的分析和辩论内容。**"
**重要请完全用简体中文输出你的分析和辩论内容**"
response = llm.invoke(prompt) response = llm.invoke(prompt)
argument = f"Aggressive Analyst: {response.content}" argument = f"Aggressive Analyst: {response.content}"

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@ -33,9 +33,7 @@ Here is the current conversation history: {history} Here is the last response fr
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.""" 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."""
prompt += " prompt += "\n\n**重要:请完全用简体中文输出你的分析和辩论内容。**"
**重要请完全用简体中文输出你的分析和辩论内容**"
response = llm.invoke(prompt) response = llm.invoke(prompt)
argument = f"Conservative Analyst: {response.content}" argument = f"Conservative Analyst: {response.content}"

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@ -32,9 +32,7 @@ Here is the current conversation history: {history} Here is the last response fr
Engage actively by analyzing both sides critically, addressing weaknesses in the aggressive 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.""" Engage actively by analyzing both sides critically, addressing weaknesses in the aggressive 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."""
prompt += " prompt += "\n\n**重要:请完全用简体中文输出你的分析和辩论内容。**"
**重要请完全用简体中文输出你的分析和辩论内容**"
response = llm.invoke(prompt) response = llm.invoke(prompt)
argument = f"Neutral Analyst: {response.content}" argument = f"Neutral Analyst: {response.content}"