refactor: clean up runpod repository structure

Removed facefusion and VPS-related files:
- compose.yaml, postgres/, litellm-config.yaml (VPS services)
- Dockerfile, entrypoint.sh, disable-nsfw-filter.patch (facefusion)

Removed outdated documentation:
- DOCKER_GPU_SETUP.md, README_GPU_SETUP.md, SETUP_GUIDE.md
- TAILSCALE_SETUP.md, WIREGUARD_SETUP.md (covered in DEPLOYMENT.md)
- GPU_EXPANSION_PLAN.md (historical planning doc)
- gpu-server-compose.yaml, litellm-config-gpu.yaml (old versions)
- deploy-gpu-stack.sh, simple_vllm_server.py (old scripts)

Organized documentation:
- Created docs/ directory
- Moved DEPLOYMENT.md, RUNPOD_TEMPLATE.md, GPU_DEPLOYMENT_LOG.md to docs/
- Updated all documentation links in README.md

Final structure:
- Clean root directory with only GPU-specific files
- Organized documentation in docs/
- Model services in dedicated directories (model-orchestrator/, vllm/, flux/, musicgen/)
- Automation scripts in scripts/

README.md

@@ -35,7 +35,7 @@ For first-time setup on a new RunPod instance:
 2. SSH to GPU server: `ssh gpu-server`
 3. Run preparation script: `cd /workspace/ai && chmod +x scripts/prepare-template.sh && ./scripts/prepare-template.sh`
 
-**See**: [DEPLOYMENT.md](DEPLOYMENT.md) for detailed deployment guide.
+**See**: [docs/DEPLOYMENT.md](docs/DEPLOYMENT.md) for detailed deployment guide.
 
 ## Architecture
 
@@ -64,16 +64,9 @@ All requests route through the orchestrator, which automatically loads the appro
 
 ## Documentation
 
-### Primary Docs
-- **[DEPLOYMENT.md](DEPLOYMENT.md)** - Complete deployment and usage guide
-- **[RUNPOD_TEMPLATE.md](RUNPOD_TEMPLATE.md)** - Template creation and usage
-- **[GPU_DEPLOYMENT_LOG.md](GPU_DEPLOYMENT_LOG.md)** - Deployment history and technical notes
-
-### Setup Guides (Historical)
-- `DOCKER_GPU_SETUP.md` - Docker configuration for GPU support
-- `TAILSCALE_SETUP.md` - Tailscale VPN setup
-- `WIREGUARD_SETUP.md` - WireGuard VPN (deprecated, use Tailscale)
-- `SETUP_GUIDE.md` - General setup instructions
+- **[docs/DEPLOYMENT.md](docs/DEPLOYMENT.md)** - Complete deployment and usage guide
+- **[docs/RUNPOD_TEMPLATE.md](docs/RUNPOD_TEMPLATE.md)** - Template creation and usage
+- **[docs/GPU_DEPLOYMENT_LOG.md](docs/GPU_DEPLOYMENT_LOG.md)** - Deployment history and technical notes
 
 ### Architecture Components
 - `model-orchestrator/` - FastAPI orchestrator managing model lifecycle
@@ -96,7 +89,7 @@ All requests route through the orchestrator, which automatically loads the appro
 3. Save pod as template in RunPod dashboard
 4. Name: `multi-modal-ai-v1.0`
 
-**See**: [RUNPOD_TEMPLATE.md](RUNPOD_TEMPLATE.md) for step-by-step guide.
+**See**: [docs/RUNPOD_TEMPLATE.md](docs/RUNPOD_TEMPLATE.md) for step-by-step guide.
 
 ## Adding New Models
 
@@ -116,7 +109,7 @@ models:
 
 Then add the Docker service to `docker-compose.gpu.yaml` and restart the orchestrator.
 
-**See**: [DEPLOYMENT.md](DEPLOYMENT.md#adding-new-models) for complete instructions.
+**See**: [docs/DEPLOYMENT.md](docs/DEPLOYMENT.md#adding-new-models) for complete instructions.
 
 ## Usage Examples
 
@@ -166,8 +159,8 @@ nvidia-smi
 
 For issues:
 1. Check orchestrator logs: `docker logs ai_orchestrator`
-2. Review [DEPLOYMENT.md](DEPLOYMENT.md#troubleshooting)
-3. Check [GPU_DEPLOYMENT_LOG.md](GPU_DEPLOYMENT_LOG.md) for deployment history
+2. Review [docs/DEPLOYMENT.md](docs/DEPLOYMENT.md#troubleshooting)
+3. Check [docs/GPU_DEPLOYMENT_LOG.md](docs/GPU_DEPLOYMENT_LOG.md) for deployment history
 
 ## License