config.py

"""
Configuration module for the AI Trading Experiment.
Contains both participant-visible and researcher-controlled parameters.
"""

from dataclasses import dataclass, field
from typing import Dict, List, Optional
import json


@dataclass
class ParticipantVisibleParams:
    """Parameters that participants can adjust."""
    explanation_depth: int = 50  # 0-100: Minimal to Detailed
    communication_style: int = 50  # 0-100: Formal to Casual


@dataclass
class ResearcherControlledParams:
    """Hidden parameters controlled by researcher for experimental conditions."""
    accuracy_rate: float = 0.7  # 0-1: Probability AI advice leads to good outcome
    proactivity_level: int = 50  # 0-100: How often AI initiates advice
    confidence_framing: int = 50  # 0-100: How assertive advice sounds
    risk_bias: int = 50  # 0-100: Conservative to Aggressive recommendations

    # Experimental condition identifier
    condition_name: str = "default"


@dataclass
class ExperimentConfig:
    """Overall experiment configuration."""
    # Starting conditions
    initial_portfolio_value: float = 100000.0
    currency_symbol: str = "credits"

    # Session settings
    scenarios_per_session: int = 8
    min_decision_time_seconds: float = 5.0  # Minimum time before decision allowed

    # Proactive AI settings
    proactive_delay_seconds: float = 3.0  # Delay before AI offers proactive advice
    proactive_probability: float = 0.7  # Base probability of proactive advice per scenario

    # Data collection
    track_mouse_movements: bool = False  # Future feature
    track_time_on_elements: bool = True

    # UI settings
    show_portfolio_history: bool = True
    show_ai_accuracy_feedback: bool = False  # Whether to reveal if AI was right

    # Researcher params (can be overridden per experiment condition)
    researcher_params: ResearcherControlledParams = field(
        default_factory=ResearcherControlledParams
    )


# Pre-defined experimental conditions for A/B testing
EXPERIMENT_CONDITIONS: Dict[str, ResearcherControlledParams] = {
    "high_accuracy_high_confidence": ResearcherControlledParams(
        accuracy_rate=0.85,
        proactivity_level=70,
        confidence_framing=80,
        risk_bias=50,
        condition_name="high_accuracy_high_confidence"
    ),
    "high_accuracy_low_confidence": ResearcherControlledParams(
        accuracy_rate=0.85,
        proactivity_level=70,
        confidence_framing=20,
        risk_bias=50,
        condition_name="high_accuracy_low_confidence"
    ),
    "low_accuracy_high_confidence": ResearcherControlledParams(
        accuracy_rate=0.40,
        proactivity_level=70,
        confidence_framing=80,
        risk_bias=50,
        condition_name="low_accuracy_high_confidence"
    ),
    "low_accuracy_low_confidence": ResearcherControlledParams(
        accuracy_rate=0.40,
        proactivity_level=70,
        confidence_framing=20,
        risk_bias=50,
        condition_name="low_accuracy_low_confidence"
    ),
    "conservative_advisor": ResearcherControlledParams(
        accuracy_rate=0.70,
        proactivity_level=50,
        confidence_framing=50,
        risk_bias=20,
        condition_name="conservative_advisor"
    ),
    "aggressive_advisor": ResearcherControlledParams(
        accuracy_rate=0.70,
        proactivity_level=50,
        confidence_framing=50,
        risk_bias=80,
        condition_name="aggressive_advisor"
    ),
    "passive_advisor": ResearcherControlledParams(
        accuracy_rate=0.70,
        proactivity_level=20,
        confidence_framing=50,
        risk_bias=50,
        condition_name="passive_advisor"
    ),
    "active_advisor": ResearcherControlledParams(
        accuracy_rate=0.70,
        proactivity_level=80,
        confidence_framing=50,
        risk_bias=50,
        condition_name="active_advisor"
    ),
}


@dataclass
class Scenario:
    """A trading scenario presented to the participant."""
    scenario_id: str
    company_symbol: str
    company_name: str
    sector: str
    country: str
    current_price: float
    situation_description: str

    # Hidden from participant - determines outcomes
    optimal_action: str  # "BUY", "SELL", or "HOLD"
    ai_recommendation: str  # What AI will recommend (may differ from optimal)
    ai_is_correct: bool  # Whether AI recommendation matches optimal

    # Outcome percentages based on decision
    outcome_buy: float  # e.g., -0.08 for -8%
    outcome_sell: float
    outcome_hold: float

    # Additional context for AI reasoning
    key_factors: List[str] = field(default_factory=list)
    red_flags: List[str] = field(default_factory=list)
    positive_signals: List[str] = field(default_factory=list)


# Pre-defined scenarios
SCENARIOS: List[Scenario] = [
    Scenario(
        scenario_id="S001",
        company_symbol="MRD",
        company_name="Meridian Industries",
        sector="Manufacturing",
        country="Republic of Valdoria",
        current_price=52.30,
        situation_description="""Meridian Industries recently announced a 5-year defense contract worth 2.1B credits.
The stock has risen 12% over the past month on this news. Labor disputes at the southern facility
have been resolved. The company maintains a healthy balance sheet with low debt.""",
        optimal_action="HOLD",
        ai_recommendation="HOLD",
        ai_is_correct=True,
        outcome_buy=-0.035,  # -3.5% (already priced in)
        outcome_sell=-0.042,  # Miss further gains
        outcome_hold=0.032,  # +3.2% steady growth
        key_factors=["Defense contract secured", "Labor issues resolved", "Strong balance sheet"],
        red_flags=[],
        positive_signals=["Government contract", "Low debt", "Stable management"]
    ),
    Scenario(
        scenario_id="S002",
        company_symbol="NGP",
        company_name="Northgate Pharmaceuticals",
        sector="Healthcare",
        country="Federation of Eastholm",
        current_price=85.50,
        situation_description="""Northgate Pharmaceuticals has Phase 3 trial results expected next month for their
flagship rare disease treatment. However, unusual trading volume was detected last week, a board member
resigned citing "personal reasons," and the CFO sold shares worth 500K credits. Competitor Apex Biotech
announced a similar drug in development.""",
        optimal_action="SELL",
        ai_recommendation="BUY",  # AI gives bad advice here
        ai_is_correct=False,
        outcome_buy=-0.153,  # -15.3% (trial fails)
        outcome_sell=0.153,  # +15.3% (avoided loss)
        outcome_hold=-0.153,  # Same as buy
        key_factors=["Phase 3 trial pending", "Insider activity", "Competitive pressure"],
        red_flags=["Board member resignation", "CFO share sale", "Unusual trading volume"],
        positive_signals=["Strong pipeline", "Rare disease focus"]
    ),
    Scenario(
        scenario_id="S003",
        company_symbol="TFE",
        company_name="Terraform Energy",
        sector="Energy",
        country="United Provinces of Somara",
        current_price=132.80,
        situation_description="""Terraform Energy's fusion prototype achieved a 40% efficiency milestone, a significant
breakthrough. The company has government subsidies locked in for 10 years and is awaiting regulatory
approval for expansion into Valdoria. Last quarter's earnings beat expectations by 12%.""",
        optimal_action="BUY",
        ai_recommendation="BUY",
        ai_is_correct=True,
        outcome_buy=0.124,  # +12.4%
        outcome_sell=-0.089,  # Miss the rally
        outcome_hold=0.056,  # Partial gain
        key_factors=["Fusion breakthrough", "Government support", "Expansion pending"],
        red_flags=["Regulatory approval uncertainty"],
        positive_signals=["Technology leadership", "Stable subsidies", "Earnings beat"]
    ),
    Scenario(
        scenario_id="S004",
        company_symbol="NXC",
        company_name="Nexus Communications",
        sector="Technology",
        country="Coastal Republic of Marinea",
        current_price=218.40,
        situation_description="""Nexus Communications holds a monopoly position in Marinea's telecommunications market.
There are unconfirmed rumors of an antitrust investigation. The company's 5G rollout is 60% complete,
and they're planning a satellite constellation launch. Subscriber growth is slowing in mature markets.""",
        optimal_action="HOLD",
        ai_recommendation="SELL",  # AI is overly cautious
        ai_is_correct=False,
        outcome_buy=0.045,  # Slight gain, rumors overblown
        outcome_sell=-0.067,  # Miss continued performance
        outcome_hold=0.045,  # Same as buy
        key_factors=["Monopoly position", "Antitrust rumors", "5G expansion"],
        red_flags=["Regulatory risk", "Slowing growth"],
        positive_signals=["Strong cash reserves", "Infrastructure investments"]
    ),
    Scenario(
        scenario_id="S005",
        company_symbol="APX",
        company_name="Apex Biotech",
        sector="Healthcare",
        country="Republic of Valdoria",
        current_price=71.20,
        situation_description="""Apex Biotech announced a competing drug to Northgate's flagship product. The company
is integrating a recent acquisition and there are rumors they may be an acquisition target themselves.
The CFO sold shares worth 2M credits last month, though this was part of a pre-planned selling program.""",
        optimal_action="HOLD",
        ai_recommendation="HOLD",
        ai_is_correct=True,
        outcome_buy=-0.028,  # Slight decline, uncertainty
        outcome_sell=-0.015,  # Miss potential upside
        outcome_hold=0.018,  # Modest gain
        key_factors=["Competitive positioning", "M&A activity", "Insider sales"],
        red_flags=["CFO share sale", "Integration risks"],
        positive_signals=["Strong patent portfolio", "Acquisition rumors"]
    ),
    Scenario(
        scenario_id="S006",
        company_symbol="ICS",
        company_name="Ironclad Security",
        sector="Defense",
        country="Federation of Eastholm",
        current_price=93.60,
        situation_description="""Ironclad Security won a major cybersecurity contract with the Marinea government.
A cyber attack on a competitor has enhanced ICS's reputation. The company is planning to hire 500
new engineers. Their order backlog represents 18 months of revenue.""",
        optimal_action="BUY",
        ai_recommendation="BUY",
        ai_is_correct=True,
        outcome_buy=0.098,  # +9.8%
        outcome_sell=-0.065,  # Miss rally
        outcome_hold=0.042,  # Partial gain
        key_factors=["Major contract win", "Strong backlog", "Expansion hiring"],
        red_flags=[],
        positive_signals=["Government contracts", "Reputation boost", "Growth investment"]
    ),
    Scenario(
        scenario_id="S007",
        company_symbol="CSC",
        company_name="Coastal Shipping Corp",
        sector="Transportation",
        country="Coastal Republic of Marinea",
        current_price=35.80,
        situation_description="""Coastal Shipping Corp benefits from a new trade agreement with Somara. Their fuel
hedging strategy has reduced costs by 8%. However, there are ongoing port strike risks in Valdoria,
and trade treaty negotiations could impact several key routes. The company offers a high dividend yield.""",
        optimal_action="HOLD",
        ai_recommendation="BUY",  # AI is too aggressive
        ai_is_correct=False,
        outcome_buy=-0.072,  # Port strike materializes
        outcome_sell=0.034,  # Avoided loss
        outcome_hold=-0.018,  # Small loss
        key_factors=["Trade agreements", "Fuel hedging", "Labor risks"],
        red_flags=["Port strike risk", "Trade negotiations"],
        positive_signals=["New trade deal", "Cost management", "High dividend"]
    ),
    Scenario(
        scenario_id="S008",
        company_symbol="AUR",
        company_name="Aurora Entertainment",
        sector="Consumer Discretionary",
        country="United Provinces of Somara",
        current_price=61.40,
        situation_description="""Aurora Entertainment's hit series "Valdoria Rising" broke viewership records.
However, their gaming division underperformed expectations. A new VR platform launches next quarter.
There are rumors Nexus Communications may acquire the company. Cash flow remains negative despite growth.""",
        optimal_action="BUY",
        ai_recommendation="HOLD",  # AI is too conservative
        ai_is_correct=False,
        outcome_buy=0.186,  # Acquisition announced
        outcome_sell=-0.142,  # Miss acquisition premium
        outcome_hold=0.065,  # Partial gain from rumors
        key_factors=["Content success", "Gaming weakness", "Acquisition rumors"],
        red_flags=["Negative cash flow", "Gaming underperformance"],
        positive_signals=["Viewership records", "VR launch", "Acquisition interest"]
    ),
]


def get_scenario_by_id(scenario_id: str) -> Optional[Scenario]:
    """Retrieve a scenario by its ID."""
    for scenario in SCENARIOS:
        if scenario.scenario_id == scenario_id:
            return scenario
    return None


def get_condition(condition_name: str) -> ResearcherControlledParams:
    """Get a pre-defined experimental condition."""
    return EXPERIMENT_CONDITIONS.get(
        condition_name,
        ResearcherControlledParams()
    )


def create_custom_condition(
    accuracy_rate: float = 0.7,
    proactivity_level: int = 50,
    confidence_framing: int = 50,
    risk_bias: int = 50,
    name: str = "custom"
) -> ResearcherControlledParams:
    """Create a custom experimental condition."""
    return ResearcherControlledParams(
        accuracy_rate=accuracy_rate,
        proactivity_level=proactivity_level,
        confidence_framing=confidence_framing,
        risk_bias=risk_bias,
        condition_name=name
    )


# Default configuration instance
DEFAULT_CONFIG = ExperimentConfig()