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Yijia-Xiao
825e6321ae
- about seventy '# Create/Initialize/Add ...' lines across graph, cli and dataflows, and the file-path headers; comments that give a reason stay
62 lines
2.9 KiB
Python
62 lines
2.9 KiB
Python
from typing import Any
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class Reflector:
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"""Handles reflection on trading decisions."""
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def __init__(self, quick_thinking_llm: Any):
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"""Initialize the reflector with an LLM."""
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self.quick_thinking_llm = quick_thinking_llm
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def _system_prompt(self, holding_days: int) -> str:
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"""Concise prompt for reflect_on_final_decision (Phase B log entries).
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Produces 2-4 sentences of plain prose, compact enough to be re-injected
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into future agent prompts without bloating the context window. The
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window is named because it bounds what the outcome can show: a thesis
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written for months is not disproved by a week, and a lesson that ignores
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the difference is read by later runs as an established failure.
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"""
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return (
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"You are a trading analyst reviewing your own past decision now that the outcome is known.\n"
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f"The outcome covers {holding_days} trading days after the analysis date, "
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"which may be shorter than the horizon the decision was written for.\n"
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"Write exactly 2-4 sentences of plain prose (no bullets, no headers, no markdown).\n\n"
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"Cover in order:\n"
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f"1. What the {holding_days}-day alpha shows about the directional call (cite the figure), "
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"and say so plainly if the window is too short to judge the thesis.\n"
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"2. Which part of the investment thesis this window supports or undercuts.\n"
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"3. One concrete lesson to apply to the next similar analysis.\n\n"
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"Be specific and terse. Your output will be stored verbatim in a decision log "
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"and re-read by future analysts, so every word must earn its place."
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)
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def reflect_on_final_decision(
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self,
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final_decision: str,
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raw_return: float,
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alpha_return: float,
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benchmark_name: str = "SPY",
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holding_days: int = 5,
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) -> str:
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"""Single reflection call on the final trade decision with outcome context.
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Used by Phase B deferred reflection. The final_trade_decision already
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synthesises all analyst insights, so no separate market context is needed.
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``benchmark_name`` is the label used for the alpha line (e.g. ``"SPY"``
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for US tickers, ``"^N225"`` for ``.T`` listings); defaults to SPY for
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callers that haven't been updated to thread the benchmark through.
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"""
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messages = [
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("system", self._system_prompt(holding_days)),
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(
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"human",
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(
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f"Raw return over {holding_days} trading days: {raw_return:+.1%}\n"
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f"Alpha vs {benchmark_name}: {alpha_return:+.1%}\n\n"
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f"Final Decision:\n{final_decision}"
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),
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),
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]
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return self.quick_thinking_llm.invoke(messages).content
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