# -*- coding: utf-8 -*-
"""Signal and analysis-related schemas."""

from pydantic import BaseModel

from shared.schema.portfolio import Portfolio


class AnalystSignal(BaseModel):
    signal: str | None = None
    confidence: float | None = None
    reasoning: dict | str | None = None
    # Extended fields for richer signal information
    reasons: list[str] | None = None  # Core drivers/reasons for the signal
    risks: list[str] | None = None  # Key risk factors
    invalidation: str | None = None  # Conditions that would invalidate the thesis
    next_action: str | None = None  # Suggested next action for PM
    # Valuation-related fields
    intrinsic_value: float | None = None  # DCF intrinsic value
    fair_value_range: dict | None = None  # {bear, base, bull} fair value range
    value_gap_pct: float | None = None  # Value gap percentage
    valuation_methods: list[str] | None = None  # List of valuation methods used
    max_position_size: float | None = None  # For risk management signals


class TickerAnalysis(BaseModel):
    ticker: str
    analyst_signals: dict[str, AnalystSignal]  # agent_name -> signal mapping


class AgentStateData(BaseModel):
    tickers: list[str]
    portfolio: Portfolio
    start_date: str
    end_date: str
    ticker_analyses: dict[str, TickerAnalysis]  # ticker -> analysis mapping


class AgentStateMetadata(BaseModel):
    show_reasoning: bool = False
    model_config = {"extra": "allow"}