Initial commit: LLM Automation Docs & Remediation Engine v2.0

Features:
- Automated datacenter documentation generation
- MCP integration for device connectivity
- Auto-remediation engine with safety checks
- Multi-factor reliability scoring (0-100%)
- Human feedback learning loop
- Pattern recognition and continuous improvement
- Agentic chat support with AI
- API for ticket resolution
- Frontend React with Material-UI
- CI/CD pipelines (GitLab + Gitea)
- Docker & Kubernetes deployment
- Complete documentation and guides

v2.0 Highlights:
- Auto-remediation with write operations (disabled by default)
- Reliability calculator with 4-factor scoring
- Human feedback system for continuous learning
- Pattern-based progressive automation
- Approval workflow for critical actions
- Full audit trail and rollback capability

src/datacenter_docs/api/models.py

@@ -0,0 +1,152 @@
+"""
+MongoDB Models using Beanie ODM
+"""
+
+from datetime import datetime
+from typing import Optional, List, Dict, Any
+from beanie import Document, Indexed
+from pydantic import Field
+
+
+class Ticket(Document):
+    """Ticket document for MongoDB"""
+    
+    ticket_id: Indexed(str, unique=True)  # External ticket ID
+    title: str
+    description: str
+    priority: str = "medium"  # low, medium, high, critical
+    category: Optional[str] = None  # network, server, storage, etc.
+    requester: Optional[str] = None
+    
+    # Status and resolution
+    status: str = "processing"  # processing, resolved, failed
+    resolution: Optional[str] = None
+    suggested_actions: Optional[List[str]] = None
+    related_docs: Optional[List[Dict[str, str]]] = None
+    
+    # Metrics
+    confidence_score: Optional[float] = None
+    processing_time: Optional[float] = None
+    
+    # Metadata
+    metadata: Dict[str, Any] = Field(default_factory=dict)
+    
+    # Timestamps
+    created_at: datetime = Field(default_factory=datetime.now)
+    updated_at: datetime = Field(default_factory=datetime.now)
+    
+    class Settings:
+        name = "tickets"
+        indexes = [
+            "ticket_id",
+            "status",
+            "category",
+            "created_at",
+            [("status", 1), ("created_at", -1)],  # Compound index
+        ]
+
+
+class DocumentationSection(Document):
+    """Documentation section metadata"""
+    
+    section_id: Indexed(str, unique=True)
+    name: str
+    description: Optional[str] = None
+    
+    # Generation info
+    last_generated: Optional[datetime] = None
+    generation_status: str = "pending"  # pending, processing, completed, failed
+    generation_time: Optional[float] = None
+    
+    # Content metadata
+    file_path: Optional[str] = None
+    file_size: Optional[int] = None
+    checksum: Optional[str] = None
+    
+    # Statistics
+    total_chunks: Optional[int] = None
+    total_tokens: Optional[int] = None
+    
+    # Timestamps
+    created_at: datetime = Field(default_factory=datetime.now)
+    updated_at: datetime = Field(default_factory=datetime.now)
+    
+    class Settings:
+        name = "documentation_sections"
+
+
+class ChatSession(Document):
+    """Chat session for tracking conversations"""
+    
+    session_id: Indexed(str, unique=True)
+    user_id: Optional[str] = None
+    
+    # Messages
+    messages: List[Dict[str, Any]] = Field(default_factory=list)
+    
+    # Session metadata
+    started_at: datetime = Field(default_factory=datetime.now)
+    last_activity: datetime = Field(default_factory=datetime.now)
+    total_messages: int = 0
+    
+    # Context
+    context: Dict[str, Any] = Field(default_factory=dict)
+    
+    class Settings:
+        name = "chat_sessions"
+        indexes = [
+            "session_id",
+            "user_id",
+            "last_activity",
+        ]
+
+
+class SystemMetric(Document):
+    """System metrics and statistics"""
+    
+    metric_type: str  # tickets, api_calls, generation, chat
+    metric_name: str
+    value: float
+    
+    # Dimensions
+    dimensions: Dict[str, str] = Field(default_factory=dict)
+    
+    # Timestamp
+    timestamp: datetime = Field(default_factory=datetime.now)
+    
+    class Settings:
+        name = "system_metrics"
+        indexes = [
+            "metric_type",
+            "metric_name",
+            "timestamp",
+            [("metric_type", 1), ("timestamp", -1)],
+        ]
+
+
+class AuditLog(Document):
+    """Audit log for tracking system actions"""
+    
+    action: str
+    actor: Optional[str] = None
+    resource_type: str
+    resource_id: str
+    
+    # Details
+    details: Dict[str, Any] = Field(default_factory=dict)
+    
+    # Result
+    success: bool = True
+    error_message: Optional[str] = None
+    
+    # Timestamp
+    timestamp: datetime = Field(default_factory=datetime.now)
+    
+    class Settings:
+        name = "audit_logs"
+        indexes = [
+            "action",
+            "resource_type",
+            "timestamp",
+            [("resource_type", 1), ("timestamp", -1)],
+        ]