feat: Implement async queue-based news pipeline with microservices

Major architectural transformation from synchronous to asynchronous processing:

## Pipeline Services (8 microservices)
- pipeline-scheduler: APScheduler for 30-minute periodic job triggers
- pipeline-rss-collector: RSS feed collection with deduplication (7-day TTL)
- pipeline-google-search: Content enrichment via Google Search API
- pipeline-ai-summarizer: AI summarization using Claude API (claude-sonnet-4-20250514)
- pipeline-translator: Translation using DeepL Pro API
- pipeline-image-generator: Image generation with Replicate API (Stable Diffusion)
- pipeline-article-assembly: Final article assembly and MongoDB storage
- pipeline-monitor: Real-time monitoring dashboard (port 8100)

## Key Features
- Redis-based job queue with deduplication
- Asynchronous processing with Python asyncio
- Shared models and queue manager for inter-service communication
- Docker containerization for all services
- Container names standardized with site11_ prefix

## Removed Services
- Moved to backup: google-search, rss-feed, news-aggregator, ai-writer

## Configuration
- DeepL Pro API: 3abbc796-2515-44a8-972d-22dcf27ab54a
- Claude Model: claude-sonnet-4-20250514
- Redis Queue TTL: 7 days for deduplication

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

backup-services/rss-feed/backend/app/models.py

@@ -0,0 +1,74 @@
+from pydantic import BaseModel, Field, HttpUrl
+from typing import Optional, List, Dict, Any
+from datetime import datetime
+from enum import Enum
+
+class FeedStatus(str, Enum):
+    ACTIVE = "active"
+    INACTIVE = "inactive"
+    ERROR = "error"
+
+class FeedCategory(str, Enum):
+    NEWS = "news"
+    TECH = "tech"
+    BUSINESS = "business"
+    SCIENCE = "science"
+    HEALTH = "health"
+    SPORTS = "sports"
+    ENTERTAINMENT = "entertainment"
+    LIFESTYLE = "lifestyle"
+    POLITICS = "politics"
+    OTHER = "other"
+
+class FeedSubscription(BaseModel):
+    id: Optional[str] = Field(None, alias="_id")
+    title: str
+    url: HttpUrl
+    description: Optional[str] = None
+    category: FeedCategory = FeedCategory.OTHER
+    status: FeedStatus = FeedStatus.ACTIVE
+    update_interval: int = 900  # seconds
+    last_fetch: Optional[datetime] = None
+    last_error: Optional[str] = None
+    error_count: int = 0
+    created_at: datetime = Field(default_factory=datetime.now)
+    updated_at: datetime = Field(default_factory=datetime.now)
+    metadata: Dict[str, Any] = {}
+
+class FeedEntry(BaseModel):
+    id: Optional[str] = Field(None, alias="_id")
+    feed_id: str
+    entry_id: str  # RSS entry unique ID
+    title: str
+    link: str
+    summary: Optional[str] = None
+    content: Optional[str] = None
+    author: Optional[str] = None
+    published: Optional[datetime] = None
+    updated: Optional[datetime] = None
+    categories: List[str] = []
+    thumbnail: Optional[str] = None
+    enclosures: List[Dict[str, Any]] = []
+    is_read: bool = False
+    is_starred: bool = False
+    created_at: datetime = Field(default_factory=datetime.now)
+
+class CreateFeedRequest(BaseModel):
+    url: HttpUrl
+    title: Optional[str] = None
+    category: FeedCategory = FeedCategory.OTHER
+    update_interval: Optional[int] = 900
+
+class UpdateFeedRequest(BaseModel):
+    title: Optional[str] = None
+    category: Optional[FeedCategory] = None
+    update_interval: Optional[int] = None
+    status: Optional[FeedStatus] = None
+
+class FeedStatistics(BaseModel):
+    feed_id: str
+    total_entries: int
+    unread_entries: int
+    starred_entries: int
+    last_update: Optional[datetime]
+    error_rate: float