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2026-07-03 16:58:28 +08:00
commit 32b43f85bd
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+# TradingAgents/graph/reflection.py
+
+from typing import Any
+
+
+class Reflector:
+    """Handles reflection on trading decisions."""
+
+    def __init__(self, quick_thinking_llm: Any):
+        """Initialize the reflector with an LLM."""
+        self.quick_thinking_llm = quick_thinking_llm
+        self.log_reflection_prompt = self._get_log_reflection_prompt()
+
+    def _get_log_reflection_prompt(self) -> str:
+        """Concise prompt for reflect_on_final_decision (Phase B log entries).
+
+        Produces 2-4 sentences of plain prose — compact enough to be re-injected
+        into future agent prompts without bloating the context window.
+        """
+        return (
+            "You are a trading analyst reviewing your own past decision now that the outcome is known.\n"
+            "Write exactly 2-4 sentences of plain prose (no bullets, no headers, no markdown).\n\n"
+            "Cover in order:\n"
+            "1. Was the directional call correct? (cite the alpha figure)\n"
+            "2. Which part of the investment thesis held or failed?\n"
+            "3. One concrete lesson to apply to the next similar analysis.\n\n"
+            "Be specific and terse. Your output will be stored verbatim in a decision log "
+            "and re-read by future analysts, so every word must earn its place."
+        )
+
+    def reflect_on_final_decision(
+        self,
+        final_decision: str,
+        raw_return: float,
+        alpha_return: float,
+    ) -> str:
+        """Single reflection call on the final trade decision with outcome context.
+
+        Used by Phase B deferred reflection. The final_trade_decision already
+        synthesises all analyst insights, so no separate market context is needed.
+        """
+        messages = [
+            ("system", self.log_reflection_prompt),
+            (
+                "human",
+                (
+                    f"Raw return: {raw_return:+.1%}\n"
+                    f"Alpha vs SPY: {alpha_return:+.1%}\n\n"
+                    f"Final Decision:\n{final_decision}"
+                ),
+            ),
+        ]
+        return self.quick_thinking_llm.invoke(messages).content