refactor: standardize portfolio manager, five-tier rating scale, fix analyst status tracking

tradingagents/agents/managers/portfolio_manager.py

@@ -0,0 +1,75 @@
+from tradingagents.agents.utils.agent_utils import build_instrument_context
+
+
+def create_portfolio_manager(llm, memory):
+    def portfolio_manager_node(state) -> dict:
+
+        instrument_context = build_instrument_context(state["company_of_interest"])
+
+        history = state["risk_debate_state"]["history"]
+        risk_debate_state = state["risk_debate_state"]
+        market_research_report = state["market_report"]
+        news_report = state["news_report"]
+        fundamentals_report = state["fundamentals_report"]
+        sentiment_report = state["sentiment_report"]
+        trader_plan = state["investment_plan"]
+
+        curr_situation = f"{market_research_report}\n\n{sentiment_report}\n\n{news_report}\n\n{fundamentals_report}"
+        past_memories = memory.get_memories(curr_situation, n_matches=2)
+
+        past_memory_str = ""
+        for i, rec in enumerate(past_memories, 1):
+            past_memory_str += rec["recommendation"] + "\n\n"
+
+        prompt = f"""As the Portfolio Manager, synthesize the risk analysts' debate and deliver the final trading decision.
+
+{instrument_context}
+
+---
+
+**Rating Scale** (use exactly one):
+- **Buy**: Strong conviction to enter or add to position
+- **Overweight**: Favorable outlook, gradually increase exposure
+- **Hold**: Maintain current position, no action needed
+- **Underweight**: Reduce exposure, take partial profits
+- **Sell**: Exit position or avoid entry
+
+**Context:**
+- Trader's proposed plan: **{trader_plan}**
+- Lessons from past decisions: **{past_memory_str}**
+
+**Required Output Structure:**
+1. **Rating**: State one of Buy / Overweight / Hold / Underweight / Sell.
+2. **Executive Summary**: A concise action plan covering entry strategy, position sizing, key risk levels, and time horizon.
+3. **Investment Thesis**: Detailed reasoning anchored in the analysts' debate and past reflections.
+
+---
+
+**Risk Analysts Debate History:**
+{history}
+
+---
+
+Be decisive and ground every conclusion in specific evidence from the analysts."""
+
+        response = llm.invoke(prompt)
+
+        new_risk_debate_state = {
+            "judge_decision": response.content,
+            "history": risk_debate_state["history"],
+            "aggressive_history": risk_debate_state["aggressive_history"],
+            "conservative_history": risk_debate_state["conservative_history"],
+            "neutral_history": risk_debate_state["neutral_history"],
+            "latest_speaker": "Judge",
+            "current_aggressive_response": risk_debate_state["current_aggressive_response"],
+            "current_conservative_response": risk_debate_state["current_conservative_response"],
+            "current_neutral_response": risk_debate_state["current_neutral_response"],
+            "count": risk_debate_state["count"],
+        }
+
+        return {
+            "risk_debate_state": new_risk_debate_state,
+            "final_trade_decision": response.content,
+        }
+
+    return portfolio_manager_node