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feat(i18n): localize researchers, risk debators, research mgr, trader
output_language config now propagates to every user-facing agent. Previously only the four analysts and portfolio manager respected the setting, producing partial-localization reports with English debate text interleaved with non-English analyst sections. Verified live: 7 agents produce Chinese output when config is set to Chinese. #575
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from tradingagents.agents.utils.agent_utils import get_language_instruction
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def create_aggressive_debator(llm):
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@@ -28,7 +29,7 @@ Latest World Affairs Report: {news_report}
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Company Fundamentals Report: {fundamentals_report}
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Here is the current conversation history: {history} Here are the last arguments from the conservative analyst: {current_conservative_response} Here are the last arguments from the neutral analyst: {current_neutral_response}. If there are no responses from the other viewpoints yet, present your own argument based on the available data.
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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."""
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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.""" + get_language_instruction()
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response = llm.invoke(prompt)
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