feat: implement Ansible-based process architecture for RunPod

Major architecture overhaul to address RunPod Docker limitations:

Core Infrastructure:
- Add base_service.py: Abstract base class for all AI services
- Add service_manager.py: Process lifecycle management
- Add core/requirements.txt: Core dependencies

Model Services (Standalone Python):
- Add models/vllm/server.py: Qwen 2.5 7B text generation
- Add models/flux/server.py: Flux.1 Schnell image generation
- Add models/musicgen/server.py: MusicGen Medium music generation
- Each service inherits from GPUService base class
- OpenAI-compatible APIs
- Standalone execution support

Ansible Deployment:
- Add playbook.yml: Comprehensive deployment automation
- Add ansible.cfg: Ansible configuration
- Add inventory.yml: Localhost inventory
- Tags: base, python, dependencies, models, tailscale, validate, cleanup

Scripts:
- Add scripts/install.sh: Full installation wrapper
- Add scripts/download-models.sh: Model download wrapper
- Add scripts/start-all.sh: Start orchestrator
- Add scripts/stop-all.sh: Stop all services

Documentation:
- Update ARCHITECTURE.md: Document distributed VPS+GPU architecture

Benefits:
- No Docker: Avoids RunPod CAP_SYS_ADMIN limitations
- Fully reproducible via Ansible
- Extensible: Add models in 3 steps
- Direct Python execution (no container overhead)

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

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

ARCHITECTURE.md

@@ -1,13 +1,15 @@
 # RunPod Multi-Modal AI Architecture
 
-**Clean, extensible Python-based architecture for RunPod GPU instances**
+**Clean, extensible distributed AI infrastructure spanning VPS and GPU**
 
 ## Design Principles
 
-1. **No Docker** - Direct Python execution for RunPod compatibility
-2. **Extensible** - Adding new models requires minimal code
-3. **Maintainable** - Clear structure and separation of concerns
-4. **Simple** - One command to start, easy to debug
+1. **Distributed** - VPS (UI/proxy) + GPU (models) connected via Tailscale
+2. **No Docker on GPU** - Direct Python for RunPod compatibility
+3. **Extensible** - Adding new models requires minimal code
+4. **Maintainable** - Clear structure and separation of concerns
+5. **Simple** - One command to start, easy to debug
+6. **OpenAI Compatible** - Works with standard AI tools
 
 ## Directory Structure