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

tradingagents/agents/risk_mgmt/conservative_debator.py

@@ -1,3 +1,4 @@
+from tradingagents.agents.utils.agent_utils import get_language_instruction
 
 
 def create_conservative_debator(llm):
@@ -28,7 +29,7 @@ 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 aggressive analyst: {current_aggressive_response} Here is the last response 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.
 
-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.""" + get_language_instruction()
 
         response = llm.invoke(prompt)