Aryan SinghandClaude Opus 4.8
4beee3dc82
- regime.py: computed SPY/VIX/sector-momentum snapshot injected into every kickoff - journal.py: each agent sees its own past picks marked-to-market (learns from wins/losses) - committee.py: Chief-Risk-Officer LLM pass over the whole book — approve/reduce/veto per pick with reasons; memo lands in reports; executor enforces verdicts at open Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_016DvdRZkyCy9NJpHYDdPqmS
65 lines
2.2 KiB
Python
65 lines
2.2 KiB
Python
"""Self-learning trade journal — each agent sees its own past picks AND how they worked out
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before researching tonight. Losses and wins become explicit lessons instead of being forgotten.
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Joins past theses with their execution price (orders table) and marks each to market via the
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current price. Compact text block injected into the agent's kickoff.
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"""
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from __future__ import annotations
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from loguru import logger
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from config.settings import get_settings
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from state import db as statedb
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from tools.market_data import latest_price
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_MAX_ROWS = 10
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def lessons_for(persona_id: str) -> str:
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"""Past-pick scorecard for one agent. Empty string if no history/DB yet."""
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s = get_settings()
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if not s.db_path.exists():
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return ""
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try:
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con = statedb.connect(s.db_path)
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rows = con.execute(
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"""
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SELECT t.trade_date, t.ticker, t.direction, t.conviction, t.thesis,
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o.est_price, o.status
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FROM theses t
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LEFT JOIN orders o
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ON o.trade_date = t.trade_date AND o.agent = t.agent AND o.ticker = t.ticker
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WHERE t.agent = ?
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ORDER BY t.trade_date DESC, t.conviction DESC
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LIMIT ?
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""",
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(persona_id, _MAX_ROWS),
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).fetchall()
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con.close()
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except Exception as e:
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logger.warning("journal query failed for {}: {}", persona_id, e)
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return ""
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if not rows:
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return ""
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lines = []
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for r in rows:
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entry = r["est_price"]
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outcome = "not executed"
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if entry:
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px = latest_price(r["ticker"])
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if px:
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chg = (px / entry - 1) * 100
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if (r["direction"] or "long") == "short":
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chg = -chg
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outcome = f"{chg:+.1f}% since {r['trade_date']} (entry ~{entry:.2f})"
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lines.append(
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f"- {r['trade_date']} {r['ticker']} {r['direction']} conv={r['conviction']}: {outcome}"
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f" | thesis was: {(r['thesis'] or '')[:100]}"
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)
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return (
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"YOUR TRACK RECORD (mark-to-market of your past picks — learn from it; double down on "
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"what worked, avoid repeating what failed):\n" + "\n".join(lines)
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)
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