phase 0+1: project scaffold, k8s manifests, CI pipeline, steering, hooks, tests
- Repository structure for all services, infra, lakehouse, dashboards - K8s manifests targeting stonks-oracle namespace with GHCR images - Ingress via Traefik with ca-issuer TLS for internal services - ConfigMap wired to existing cluster services (pg, redis, minio, ollama) - GitHub Actions workflow for lint, test, multi-service container builds - Dockerfile with build-arg CMD per service - Makefile for local build/push/deploy - Steering rules for TDD workflow, K8s conventions, project context - Agent hooks for lint-on-save, test-on-save, k8s-validate, phase-commit - Ruff linter config, all lint issues fixed - 14 passing tests for schemas, config, redis keys - PostgreSQL migrations, Trino catalogs, Superset config, MinIO lifecycle
This commit is contained in:
Celes Renata
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"""Typed JSON schemas for document intelligence, trend summaries, and recommendations."""
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from __future__ import annotations
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import uuid
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from datetime import datetime
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from enum import Enum
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from typing import List, Optional
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from pydantic import BaseModel, Field
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# --- Enums ---
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class DocumentType(str, Enum):
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ARTICLE = "article"
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FILING = "filing"
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TRANSCRIPT = "transcript"
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PRESS_RELEASE = "press_release"
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class SourceType(str, Enum):
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MARKET_API = "market_api"
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NEWS_API = "news_api"
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FILINGS_API = "filings_api"
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WEB_SCRAPE = "web_scrape"
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BROKER = "broker"
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class Sentiment(str, Enum):
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POSITIVE = "positive"
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NEGATIVE = "negative"
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NEUTRAL = "neutral"
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MIXED = "mixed"
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class CatalystType(str, Enum):
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EARNINGS = "earnings"
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PRODUCT = "product"
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LEGAL = "legal"
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MACRO = "macro"
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SUPPLY_CHAIN = "supply_chain"
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M_AND_A = "m_and_a"
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RATING_CHANGE = "rating_change"
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OTHER = "other"
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class TrendDirection(str, Enum):
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BULLISH = "bullish"
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BEARISH = "bearish"
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MIXED = "mixed"
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NEUTRAL = "neutral"
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class ActionType(str, Enum):
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BUY = "buy"
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SELL = "sell"
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HOLD = "hold"
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WATCH = "watch"
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class RecommendationMode(str, Enum):
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INFORMATIONAL = "informational"
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PAPER_ELIGIBLE = "paper_eligible"
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LIVE_ELIGIBLE = "live_eligible"
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class TrendWindow(str, Enum):
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INTRADAY = "intraday"
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ONE_DAY = "1d"
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SEVEN_DAY = "7d"
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THIRTY_DAY = "30d"
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NINETY_DAY = "90d"
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# --- Document Intelligence ---
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class CompanyImpact(BaseModel):
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ticker: str
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company_name: str
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relevance: float = Field(ge=0, le=1)
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sentiment: Sentiment
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impact_score: float = Field(ge=0, le=1)
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impact_horizon: str
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catalyst_type: CatalystType
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key_facts: List[str] = Field(default_factory=list)
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risks: List[str] = Field(default_factory=list)
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evidence_spans: List[str] = Field(default_factory=list)
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class ModelMetadata(BaseModel):
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provider: str = "ollama"
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model_name: str = ""
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prompt_version: str = ""
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schema_version: str = "2.0.0"
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class DocumentIntelligence(BaseModel):
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document_id: str = Field(default_factory=lambda: str(uuid.uuid4()))
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document_type: DocumentType = DocumentType.ARTICLE
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summary: str = ""
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companies: List[CompanyImpact] = Field(default_factory=list)
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macro_themes: List[str] = Field(default_factory=list)
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novelty_score: float = Field(ge=0, le=1, default=0.5)
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source_credibility: float = Field(ge=0, le=1, default=0.5)
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extraction_warnings: List[str] = Field(default_factory=list)
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confidence: float = Field(ge=0, le=1, default=0.5)
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model: ModelMetadata = Field(default_factory=ModelMetadata)
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# --- Trend Summary ---
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class TrendSummary(BaseModel):
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entity_type: str = "company"
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entity_id: str = ""
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window: TrendWindow = TrendWindow.SEVEN_DAY
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trend_direction: TrendDirection = TrendDirection.NEUTRAL
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trend_strength: float = Field(ge=0, le=1, default=0.5)
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confidence: float = Field(ge=0, le=1, default=0.5)
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top_supporting_evidence: List[str] = Field(default_factory=list)
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top_opposing_evidence: List[str] = Field(default_factory=list)
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dominant_catalysts: List[str] = Field(default_factory=list)
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material_risks: List[str] = Field(default_factory=list)
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contradiction_score: float = Field(ge=0, le=1, default=0.0)
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generated_at: datetime = Field(default_factory=datetime.utcnow)
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# --- Recommendation ---
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class PositionSizing(BaseModel):
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portfolio_pct: float = Field(ge=0, le=1, default=0.02)
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max_loss_pct: float = Field(ge=0, le=1, default=0.005)
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class Recommendation(BaseModel):
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recommendation_id: str = Field(default_factory=lambda: str(uuid.uuid4()))
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ticker: str = ""
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action: ActionType = ActionType.WATCH
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mode: RecommendationMode = RecommendationMode.INFORMATIONAL
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confidence: float = Field(ge=0, le=1, default=0.5)
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time_horizon: str = ""
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thesis: str = ""
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invalidation_conditions: List[str] = Field(default_factory=list)
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position_sizing: PositionSizing = Field(default_factory=PositionSizing)
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evidence_refs: List[str] = Field(default_factory=list)
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model_metadata: ModelMetadata = Field(default_factory=ModelMetadata)
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generated_at: datetime = Field(default_factory=datetime.utcnow)
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# --- Document Metadata ---
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class StorageRefs(BaseModel):
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raw_html: Optional[str] = None
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raw_payload: Optional[str] = None
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normalized_text: Optional[str] = None
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class DocumentMetadata(BaseModel):
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document_id: str = Field(default_factory=lambda: str(uuid.uuid4()))
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document_type: DocumentType = DocumentType.ARTICLE
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symbol_candidates: List[str] = Field(default_factory=list)
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source_type: SourceType = SourceType.NEWS_API
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publisher: str = ""
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url: Optional[str] = None
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canonical_url: Optional[str] = None
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title: str = ""
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published_at: Optional[datetime] = None
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retrieved_at: datetime = Field(default_factory=datetime.utcnow)
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language: str = "en"
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content_hash: str = ""
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storage_refs: StorageRefs = Field(default_factory=StorageRefs)
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