Files
trading-agent/orchestration/run_nightly.py
T
Aryan Singh e1ac514f30 Add dynamic agent registry and options mandate
Introduces a dashboard-managed agent registry (`state/agents.json`) used by nightly research and market-open execution, including support for custom/disabled agents and per-agent time budgets. Expands personas to four agents (adds Maverick), shifts pick targets to include mandatory options, and updates prompts/finalization nudges to enforce option research without hard-failing runs.

Strengthens execution safety by adding option-specific guardrails (conviction floor, premium cap, reserved option slot through trade/day/buying-power caps), validates OCC option symbols in schemas, and normalizes invalid option direction cases. The dashboard was refactored into modular views, adds an Agents admin tab, and improves live portfolio visibility with Alpaca-first data and snapshot fallback.
2026-07-07 22:00:20 -05:00

141 lines
5.6 KiB
Python

"""ENTRYPOINT #1 — the nightly research run.
Brings up oMLX, then runs the 3 personas strictly sequentially (one model, time-sliced),
each under a rollover wall-clock budget bounded by the hard stop. Every agent's output is
checkpointed to state/output/<trade_date>/. Run with --compressed for a fast end-to-end
test (short budgets).
uv run python -m orchestration.run_nightly [--compressed]
"""
from __future__ import annotations
import sys
import time
from datetime import datetime, timezone
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
from loguru import logger # noqa: E402
from agents.graph import run_agent # noqa: E402
from agents.schemas import RunManifest # noqa: E402
from config.agent_registry import load_personas # noqa: E402
from config.settings import get_settings # noqa: E402
from llm import server # noqa: E402
from llm.client import resolve_model_id # noqa: E402
from orchestration.budget import ( # noqa: E402
local_hard_stop_ts,
next_deadline,
next_market_trade_date,
)
from orchestration import committee as committee_mod # noqa: E402
from orchestration.checkpoint import Checkpointer # noqa: E402
from orchestration.regime import market_regime # noqa: E402
from reporting import report_writer # noqa: E402
from reporting.journal import lessons_for # noqa: E402
def main(compressed: bool = False) -> int:
s = get_settings()
s.ensure_dirs()
trade_date = next_market_trade_date(s.market_tz)
logger.add(s.log_dir / f"nightly_{trade_date}.log", rotation="10 MB", retention="14 days")
logger.info("=== nightly run trade_date={} profile={} compressed={} ===",
trade_date, s.model_profile, compressed)
if not server.ensure_ready():
logger.error("oMLX not ready; aborting.")
return 1
# preflight: confirm internet before committing to a long run (warn but continue)
try:
from tools.web import web_search
probe = web_search.invoke({"query": "stock market news today"})
logger.info("internet preflight: {}", "OK" if "http" in probe else "no results (degraded)")
except Exception as e:
logger.warning("internet preflight failed (continuing): {}", e)
model_name = resolve_model_id()
run_id = datetime.now(timezone.utc).strftime("%Y%m%dT%H%M%SZ")
cp = Checkpointer(s.output_dir, trade_date)
manifest = RunManifest(
run_id=run_id,
trade_date=trade_date,
model=model_name,
started_at=datetime.now(timezone.utc),
status="running",
)
cp.write_manifest(manifest)
hard_stop = local_hard_stop_ts(s.hard_stop, s.local_tz)
step_budget = 12 if compressed else s.per_agent_step_budget
min_steps = 4 if compressed else s.per_agent_min_steps
# dashboard-managed registry: built-ins + overrides + custom agents, disabled excluded
personas = load_personas()
logger.info("agents tonight: {}", ", ".join(p.id for p in personas))
# shared ground truth for all agents tonight (computed, deterministic)
regime = market_regime()
if regime:
logger.info("regime: {}", regime[:140])
outputs = []
records: dict[str, str] = {}
for i, persona in enumerate(personas):
# per-agent budgets (dashboard-editable), falling back to the global settings
if compressed:
per_agent_cap_s, min_seconds = 5 * 60, 60
else:
per_agent_cap_s = (persona.time_budget_min or s.per_agent_wallclock_min) * 60
min_seconds = (persona.min_research_min or s.per_agent_min_minutes) * 60
now = time.time()
if now >= hard_stop:
logger.warning("hard stop reached; skipping {} remaining agents", len(personas) - i)
break
deadline = next_deadline(now, hard_stop, len(personas) - i, per_agent_cap_s)
logger.info("--- {} until {} ---", persona.id,
datetime.fromtimestamp(deadline).strftime("%H:%M:%S"))
if not server.server_up(): # recover if a prior agent left oMLX unresponsive
logger.warning("oMLX unreachable before {}; recovering...", persona.id)
server.ensure_ready(warm=False)
lessons = lessons_for(persona.id) # self-learning: past picks marked to market
records[persona.id] = lessons
blurb = "\n\n".join(x for x in (regime, lessons) if x)
out = run_agent(persona, deadline_ts=deadline, step_budget=step_budget,
min_steps=min_steps, min_seconds=min_seconds,
context_blurb=blurb, checkpointer=cp, model_name=model_name)
cp.write(out)
outputs.append(out)
manifest.agents.append(persona.id)
try:
report_writer.write_agent_report(out, trade_date) # analyst research note
except Exception as e:
logger.warning("agent report failed for {}: {}", persona.id, e)
# Investment Committee: risk-officer pass over the whole book (verdicts enforce at open)
try:
committee_mod.run_committee(outputs, trade_date, regime, records)
except Exception as e:
logger.warning("committee failed (fail-open): {}", e)
# combined daily report (execution results appended in the morning by run_market_open)
try:
daily = report_writer.write_daily_report(trade_date, outputs)
report_writer.to_pdf(daily)
except Exception as e:
logger.warning("daily report failed: {}", e)
manifest.status = "complete"
manifest.ended_at = datetime.now(timezone.utc)
cp.write_manifest(manifest)
logger.info("=== nightly run complete; output in {} ===", cp.dir)
return 0
if __name__ == "__main__":
raise SystemExit(main(compressed="--compressed" in sys.argv))