Initial project structure: MarketScanner - Fear-to-Fortune Trading Intelligence

Features:
- FastAPI backend with stocks, news, signals, watchlist, analytics endpoints
- React frontend with TailwindCSS dark mode trading dashboard
- Celery workers for news fetching, sentiment analysis, pattern detection
- TimescaleDB schema for time-series stock data
- Docker Compose setup for all services
- OpenAI integration for sentiment analysis

backend/app/schemas/news.py

@@ -0,0 +1,43 @@
+"""News schemas."""
+
+from typing import Optional
+from datetime import datetime
+from uuid import UUID
+from pydantic import BaseModel, Field
+
+
+class NewsBase(BaseModel):
+    """Base news schema."""
+    title: str
+    url: str
+    source: str
+    published_at: datetime
+
+
+class NewsCreate(NewsBase):
+    """Schema for creating a news article."""
+    content: Optional[str] = None
+    summary: Optional[str] = None
+    author: Optional[str] = None
+    image_url: Optional[str] = None
+
+
+class NewsResponse(NewsBase):
+    """Schema for news response."""
+    id: UUID
+    summary: Optional[str] = None
+    author: Optional[str] = None
+    fetched_at: datetime
+    
+    class Config:
+        from_attributes = True
+
+
+class NewsWithSentiment(NewsResponse):
+    """News response with sentiment analysis."""
+    content: Optional[str] = None
+    image_url: Optional[str] = None
+    sentiment_score: Optional[float] = None
+    sentiment_label: Optional[str] = None
+    sentiment_confidence: Optional[float] = None
+    is_processed: bool = False