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.
158 lines
5.8 KiB
Python
158 lines
5.8 KiB
Python
"""Pydantic output contract shared by the nightly agents and the morning executor.
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The agents emit ``AgentOutput`` (containing ``Pick`` items) to JSON; the executor reads
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it back. Validators enforce basic sanity so garbage never reaches order placement.
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"""
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from __future__ import annotations
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import re
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from datetime import datetime
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from enum import Enum
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from pydantic import BaseModel, Field, field_validator, model_validator
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# OCC option symbol: ROOT (<=6 chars) + YYMMDD + C/P + strike*1000 as 8 digits,
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# e.g. AAPL260724C00295000. LLMs sometimes fabricate near-miss symbols; reject them
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# here so an invented contract can never reach order placement.
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_OCC_SYMBOL_RE = re.compile(r"^[A-Z.]{1,6}\d{6}[CP]\d{8}$")
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class Direction(str, Enum):
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LONG = "long"
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SHORT = "short"
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class Horizon(str, Enum):
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INTRADAY = "intraday"
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SWING = "swing"
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WEEKS = "weeks"
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MONTHS = "months"
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class EntryType(str, Enum):
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MARKET = "market"
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LIMIT = "limit"
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class Instrument(str, Enum):
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EQUITY = "equity"
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OPTION = "option"
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class AgentStatus(str, Enum):
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COMPLETE = "complete"
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PARTIAL = "partial"
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TIMEOUT = "timeout"
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ERROR = "error"
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class Pick(BaseModel):
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"""One trade idea from an agent. Absolute prices are advisory (formed overnight on
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stale data); the executor derives real stop/take from pct off the actual fill."""
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ticker: str
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direction: Direction = Direction.LONG
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conviction: float = Field(ge=0.0, le=1.0)
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thesis: str
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catalysts: list[str] = Field(default_factory=list)
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time_horizon: Horizon = Horizon.SWING
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requested_weight_pct: float = Field(gt=0.0, le=1.0, description="fraction of equity")
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entry_type: EntryType = EntryType.MARKET
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limit_price: float | None = None
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stop_loss_pct: float | None = None
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stop_price: float | None = None
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take_profit_pct: float | None = None
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take_price: float | None = None
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risk_notes: str = ""
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data_refs: list[str] = Field(default_factory=list)
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# --- options (instrument=option): long calls/puts. contract_symbol from get_option_chain ---
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instrument: Instrument = Instrument.EQUITY
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option_right: str | None = None # "call" | "put"
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contract_symbol: str | None = None # OCC symbol, e.g. AAPL260724C00295000
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expiry: str | None = None
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strike: float | None = None
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@field_validator("ticker")
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@classmethod
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def _normalize_ticker(cls, v: str) -> str:
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v = v.strip().upper()
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if not v:
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raise ValueError("ticker must be non-empty")
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return v
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@field_validator("stop_loss_pct", "take_profit_pct")
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@classmethod
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def _pct_fraction(cls, v: float | None) -> float | None:
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if v is not None and not (0.0 < v < 1.0):
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raise ValueError("stop/take pct must be a fraction between 0 and 1")
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return v
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@model_validator(mode="after")
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def _check_option_fields(self) -> "Pick":
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if self.instrument == Instrument.OPTION:
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if not self.contract_symbol:
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raise ValueError("option pick requires contract_symbol (from get_option_chain)")
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self.contract_symbol = self.contract_symbol.strip().upper()
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if not _OCC_SYMBOL_RE.match(self.contract_symbol):
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raise ValueError(
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f"contract_symbol '{self.contract_symbol}' is not a valid OCC symbol — "
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"copy it EXACTLY from get_option_chain output, never construct one"
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)
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if (self.option_right or "").lower() not in ("call", "put"):
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raise ValueError("option pick requires option_right 'call' or 'put'")
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self.option_right = self.option_right.lower()
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# We only BUY options. A put marked direction=short is the same bearish bet
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# expressed sloppily (LLMs do this) — normalize to a long put. A short call has
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# no long-only equivalent, so reject it outright.
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if self.direction == Direction.SHORT:
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if self.option_right == "put":
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self.direction = Direction.LONG
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else:
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raise ValueError(
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"cannot short a call (selling options unsupported) — express a "
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"bearish view with a long put instead"
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)
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return self
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@model_validator(mode="after")
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def _check_absolute_levels(self) -> "Pick":
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# Only enforce ordering when an absolute entry reference exists (limit orders).
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ref = self.limit_price
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if ref is not None:
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if self.direction == Direction.LONG:
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if self.stop_price is not None and self.stop_price >= ref:
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raise ValueError("long stop_price must be below entry")
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if self.take_price is not None and self.take_price <= ref:
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raise ValueError("long take_price must be above entry")
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else: # SHORT
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if self.stop_price is not None and self.stop_price <= ref:
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raise ValueError("short stop_price must be above entry")
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if self.take_price is not None and self.take_price >= ref:
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raise ValueError("short take_price must be below entry")
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return self
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class AgentOutput(BaseModel):
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agent_name: str
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persona_id: str
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started_at: datetime
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ended_at: datetime | None = None
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status: AgentStatus = AgentStatus.PARTIAL
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steps_used: int = 0
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wall_seconds: float = 0.0
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market_summary: str = ""
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picks: list[Pick] = Field(default_factory=list)
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reasoning_trace: list[str] = Field(default_factory=list)
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errors: list[str] = Field(default_factory=list)
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class RunManifest(BaseModel):
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run_id: str
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trade_date: str # ET session date, YYYY-MM-DD
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model: str
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started_at: datetime
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ended_at: datetime | None = None
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status: str = "running"
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agents: list[str] = Field(default_factory=list)
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