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+"""Trader: turns the Research Manager's investment plan into a concrete transaction proposal."""
+
+from __future__ import annotations
+
+import functools
+
+from langchain_core.messages import AIMessage
+
+from tradingagents.agents.schemas import TraderProposal, render_trader_proposal
+from tradingagents.agents.utils.agent_utils import build_instrument_context, get_language_instruction
+from tradingagents.agents.utils.structured import (
+    bind_structured,
+    invoke_structured_or_freetext,
+)
+
+
+def create_trader(llm):
+    structured_llm = bind_structured(llm, TraderProposal, "Trader")
+
+    def trader_node(state, name):
+        company_name = state["company_of_interest"]
+        instrument_context = build_instrument_context(company_name)
+        investment_plan = state["investment_plan"]
+
+        messages = [
+            {
+                "role": "system",
+                "content": (
+                    "You are a trading agent analyzing market data to make investment decisions. "
+                    "Based on your analysis, provide a specific recommendation to buy, sell, or hold. "
+                    "Anchor your reasoning in the analysts' reports and the research plan."
+                    + get_language_instruction()
+                ),
+            },
+            {
+                "role": "user",
+                "content": (
+                    f"Based on a comprehensive analysis by a team of analysts, here is an investment "
+                    f"plan tailored for {company_name}. {instrument_context} This plan incorporates "
+                    f"insights from current technical market trends, macroeconomic indicators, and "
+                    f"social media sentiment. Use this plan as a foundation for evaluating your next "
+                    f"trading decision.\n\nProposed Investment Plan: {investment_plan}\n\n"
+                    f"Leverage these insights to make an informed and strategic decision."
+                ),
+            },
+        ]
+
+        trader_plan = invoke_structured_or_freetext(
+            structured_llm,
+            llm,
+            messages,
+            render_trader_proposal,
+            "Trader",
+        )
+
+        return {
+            "messages": [AIMessage(content=trader_plan)],
+            "trader_investment_plan": trader_plan,
+            "sender": name,
+        }
+
+    return functools.partial(trader_node, name="Trader")