"""Typed JSON schemas for document intelligence, trend summaries, and recommendations."""
from __future__ import annotations

import uuid
from datetime import datetime
from enum import Enum
from typing import List, Optional

from pydantic import BaseModel, Field

# --- Enums ---

class DocumentType(str, Enum):
    ARTICLE = "article"
    FILING = "filing"
    TRANSCRIPT = "transcript"
    PRESS_RELEASE = "press_release"


class SourceType(str, Enum):
    MARKET_API = "market_api"
    NEWS_API = "news_api"
    FILINGS_API = "filings_api"
    WEB_SCRAPE = "web_scrape"
    BROKER = "broker"


class Sentiment(str, Enum):
    POSITIVE = "positive"
    NEGATIVE = "negative"
    NEUTRAL = "neutral"
    MIXED = "mixed"


class CatalystType(str, Enum):
    EARNINGS = "earnings"
    PRODUCT = "product"
    LEGAL = "legal"
    MACRO = "macro"
    SUPPLY_CHAIN = "supply_chain"
    M_AND_A = "m_and_a"
    RATING_CHANGE = "rating_change"
    OTHER = "other"


class TrendDirection(str, Enum):
    BULLISH = "bullish"
    BEARISH = "bearish"
    MIXED = "mixed"
    NEUTRAL = "neutral"


class ActionType(str, Enum):
    BUY = "buy"
    SELL = "sell"
    HOLD = "hold"
    WATCH = "watch"


class RecommendationMode(str, Enum):
    INFORMATIONAL = "informational"
    PAPER_ELIGIBLE = "paper_eligible"
    LIVE_ELIGIBLE = "live_eligible"


class TrendWindow(str, Enum):
    INTRADAY = "intraday"
    ONE_DAY = "1d"
    SEVEN_DAY = "7d"
    THIRTY_DAY = "30d"
    NINETY_DAY = "90d"


# --- Document Intelligence ---

class CompanyImpact(BaseModel):
    ticker: str
    company_name: str
    relevance: float = Field(ge=0, le=1)
    sentiment: Sentiment
    impact_score: float = Field(ge=0, le=1)
    impact_horizon: str
    catalyst_type: CatalystType
    key_facts: List[str] = Field(default_factory=list)
    risks: List[str] = Field(default_factory=list)
    evidence_spans: List[str] = Field(default_factory=list)


class ModelMetadata(BaseModel):
    provider: str = "ollama"
    model_name: str = ""
    prompt_version: str = ""
    schema_version: str = "2.0.0"


class DocumentIntelligence(BaseModel):
    document_id: str = Field(default_factory=lambda: str(uuid.uuid4()))
    document_type: DocumentType = DocumentType.ARTICLE
    summary: str = ""
    companies: List[CompanyImpact] = Field(default_factory=list)
    macro_themes: List[str] = Field(default_factory=list)
    novelty_score: float = Field(ge=0, le=1, default=0.5)
    source_credibility: float = Field(ge=0, le=1, default=0.5)
    extraction_warnings: List[str] = Field(default_factory=list)
    confidence: float = Field(ge=0, le=1, default=0.5)
    model: ModelMetadata = Field(default_factory=ModelMetadata)


# --- Trend Summary ---

class TrendSummary(BaseModel):
    entity_type: str = "company"
    entity_id: str = ""
    window: TrendWindow = TrendWindow.SEVEN_DAY
    trend_direction: TrendDirection = TrendDirection.NEUTRAL
    trend_strength: float = Field(ge=0, le=1, default=0.5)
    confidence: float = Field(ge=0, le=1, default=0.5)
    top_supporting_evidence: List[str] = Field(default_factory=list)
    top_opposing_evidence: List[str] = Field(default_factory=list)
    dominant_catalysts: List[str] = Field(default_factory=list)
    material_risks: List[str] = Field(default_factory=list)
    contradiction_score: float = Field(ge=0, le=1, default=0.0)
    generated_at: datetime = Field(default_factory=datetime.utcnow)


# --- Recommendation ---

class PositionSizing(BaseModel):
    portfolio_pct: float = Field(ge=0, le=1, default=0.02)
    max_loss_pct: float = Field(ge=0, le=1, default=0.005)


class Recommendation(BaseModel):
    recommendation_id: str = Field(default_factory=lambda: str(uuid.uuid4()))
    ticker: str = ""
    action: ActionType = ActionType.WATCH
    mode: RecommendationMode = RecommendationMode.INFORMATIONAL
    confidence: float = Field(ge=0, le=1, default=0.5)
    time_horizon: str = ""
    thesis: str = ""
    invalidation_conditions: List[str] = Field(default_factory=list)
    position_sizing: PositionSizing = Field(default_factory=PositionSizing)
    evidence_refs: List[str] = Field(default_factory=list)
    model_metadata: ModelMetadata = Field(default_factory=ModelMetadata)
    generated_at: datetime = Field(default_factory=datetime.utcnow)


# --- Document Metadata ---

class StorageRefs(BaseModel):
    raw_html: Optional[str] = None
    raw_payload: Optional[str] = None
    normalized_text: Optional[str] = None


class DocumentMetadata(BaseModel):
    document_id: str = Field(default_factory=lambda: str(uuid.uuid4()))
    document_type: DocumentType = DocumentType.ARTICLE
    symbol_candidates: List[str] = Field(default_factory=list)
    source_type: SourceType = SourceType.NEWS_API
    publisher: str = ""
    url: Optional[str] = None
    canonical_url: Optional[str] = None
    title: str = ""
    published_at: Optional[datetime] = None
    retrieved_at: datetime = Field(default_factory=datetime.utcnow)
    language: str = "en"
    content_hash: str = ""
    storage_refs: StorageRefs = Field(default_factory=StorageRefs)