feat: Implement backend core functionality for news-engine-console

Phase 1 Backend Implementation:
- ✅ MongoDB data models (Keyword, Pipeline, User, Application)
- ✅ Pydantic schemas for all models with validation
- ✅ KeywordService: Full CRUD, filtering, pagination, stats, toggle status
- ✅ PipelineService: Full CRUD, start/stop/restart, logs, config management
- ✅ Keywords API: 8 endpoints with complete functionality
- ✅ Pipelines API: 11 endpoints with complete functionality
- ✅ Updated TODO.md to reflect completion

Key Features:
- Async MongoDB operations with Motor
- Comprehensive filtering and pagination support
- Pipeline logging system
- Statistics tracking for keywords and pipelines
- Proper error handling with HTTP status codes
- Type-safe request/response models

Files Added:
- models/: 4 data models with PyObjectId support
- schemas/: 4 schema modules with Create/Update/Response patterns
- services/: KeywordService (234 lines) + PipelineService (332 lines)

Files Modified:
- api/keywords.py: 40 → 212 lines (complete implementation)
- api/pipelines.py: 25 → 300 lines (complete implementation)
- TODO.md: Updated checklist with completed items

Next Steps:
- UserService with authentication
- ApplicationService for OAuth2
- MonitoringService
- Redis integration
- Frontend implementation

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

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

services/news-engine-console/backend/app/models/keyword.py

@@ -0,0 +1,55 @@
+from datetime import datetime
+from typing import Optional, Dict, Any
+from pydantic import BaseModel, Field
+from bson import ObjectId
+
+
+class PyObjectId(ObjectId):
+    """Custom ObjectId type for Pydantic"""
+    @classmethod
+    def __get_validators__(cls):
+        yield cls.validate
+
+    @classmethod
+    def validate(cls, v):
+        if not ObjectId.is_valid(v):
+            raise ValueError("Invalid ObjectId")
+        return ObjectId(v)
+
+    @classmethod
+    def __get_pydantic_json_schema__(cls, field_schema):
+        field_schema.update(type="string")
+
+
+class Keyword(BaseModel):
+    """Keyword data model for pipeline management"""
+
+    id: Optional[PyObjectId] = Field(default=None, alias="_id")
+    keyword: str = Field(..., min_length=1, max_length=200)
+    category: str = Field(..., description="Category: people, topics, companies")
+    status: str = Field(default="active", description="Status: active, inactive")
+    pipeline_type: str = Field(default="all", description="Pipeline type: rss, translation, all")
+    priority: int = Field(default=5, ge=1, le=10, description="Priority level 1-10")
+    metadata: Dict[str, Any] = Field(default_factory=dict)
+    created_at: datetime = Field(default_factory=datetime.utcnow)
+    updated_at: datetime = Field(default_factory=datetime.utcnow)
+    created_by: Optional[str] = Field(default=None, description="User ID who created this keyword")
+
+    class Config:
+        populate_by_name = True
+        arbitrary_types_allowed = True
+        json_encoders = {ObjectId: str}
+        json_schema_extra = {
+            "example": {
+                "keyword": "도널드 트럼프",
+                "category": "people",
+                "status": "active",
+                "pipeline_type": "all",
+                "priority": 8,
+                "metadata": {
+                    "description": "Former US President",
+                    "aliases": ["Donald Trump", "Trump"]
+                },
+                "created_by": "admin"
+            }
+        }