feat: implement template-based documentation generation system for Proxmox

Implement a scalable system for automatic documentation generation from infrastructure
systems, preventing LLM context overload through template-driven sectioning.

**New Features:**

1. **YAML Template System** (`templates/documentation/proxmox.yaml`)
   - Define documentation sections independently
   - Specify data requirements per section
   - Configure prompts, generation settings, and scheduling
   - Prevents LLM context overflow by sectioning data

2. **Template-Based Generator** (`src/datacenter_docs/generators/template_generator.py`)
   - Load and parse YAML templates
   - Generate documentation sections independently
   - Extract only required data for each section
   - Save sections individually to files and database
   - Combine sections with table of contents

3. **Celery Tasks** (`src/datacenter_docs/workers/documentation_tasks.py`)
   - `collect_and_generate_docs`: Collect data and generate docs
   - `generate_proxmox_docs`: Scheduled Proxmox documentation (daily at 2 AM)
   - `generate_all_docs`: Generate docs for all systems in parallel
   - `index_generated_docs`: Index generated docs into vector store for RAG
   - `full_docs_pipeline`: Complete workflow (collect → generate → index)

4. **Scheduled Jobs** (updated `celery_app.py`)
   - Daily Proxmox documentation generation
   - Every 6 hours: all systems documentation
   - Weekly: full pipeline with indexing
   - Proper task routing and rate limiting

5. **Test Script** (`scripts/test_proxmox_docs.py`)
   - End-to-end testing of documentation generation
   - Mock data collection from Proxmox
   - Template-based generation
   - File and database storage

6. **Configuration Updates** (`src/datacenter_docs/utils/config.py`)
   - Add port configuration fields for Docker services
   - Add MongoDB and Redis credentials
   - Support all required environment variables

**Proxmox Documentation Sections:**
- Infrastructure Overview (cluster, nodes, stats)
- Virtual Machines Inventory
- LXC Containers Inventory
- Storage Configuration
- Network Configuration
- Maintenance Procedures

**Benefits:**
- Scalable to multiple infrastructure systems
- Prevents LLM context window overflow
- Independent section generation
- Scheduled automatic updates
- Vector store integration for RAG chat
- Template-driven approach for consistency

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

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

src/datacenter_docs/utils/config.py

@@ -72,6 +72,20 @@ class Settings(BaseSettings):
     CELERY_BROKER_URL: str = "redis://localhost:6379/0"
     CELERY_RESULT_BACKEND: str = "redis://localhost:6379/0"
 
+    # Additional Port Configuration (for Docker services)
+    MONGODB_PORT: int = 27017
+    REDIS_PORT: int = 6379
+    CHAT_PORT: int = 8001
+    FLOWER_PORT: int = 5555
+    FRONTEND_PORT: int = 8080
+
+    # MongoDB Root Credentials (for Docker initialization)
+    MONGO_ROOT_USER: str = "admin"
+    MONGO_ROOT_PASSWORD: str = "admin123"
+
+    # Redis Password
+    REDIS_PASSWORD: str = ""
+
     @model_validator(mode="before")
     @classmethod
     def set_celery_defaults(cls, values: Dict[str, Any]) -> Dict[str, Any]: