feat: Add GPU-specific Ray worker images with CI/CD

- Add Dockerfiles for nvidia, rdna2, strixhalo, and intel GPU targets
- Add ray-serve modules (embeddings, whisper, tts, llm, reranker)
- Add Gitea Actions workflow for automated builds
- Add Makefile for local development
- Update README with comprehensive documentation

README.md

@@ -1,3 +1,89 @@
-# kuberay-images
+# KubeRay Worker Images
 
-Where all my kuberay images will go
+GPU-specific Ray worker images for the DaviesTechLabs AI/ML platform.
+
+## Images
+
+| Image | GPU Target | Workloads | Registry |
+|-------|------------|-----------|----------|
+| `ray-worker-nvidia` | NVIDIA CUDA (RTX 2070) | Whisper STT, XTTS TTS | `git.daviestechlabs.io/daviestechlabs/ray-worker-nvidia` |
+| `ray-worker-rdna2` | AMD ROCm (Radeon 680M) | BGE Embeddings | `git.daviestechlabs.io/daviestechlabs/ray-worker-rdna2` |
+| `ray-worker-strixhalo` | AMD ROCm (Strix Halo) | vLLM, BGE | `git.daviestechlabs.io/daviestechlabs/ray-worker-strixhalo` |
+| `ray-worker-intel` | Intel XPU (Arc) | BGE Reranker | `git.daviestechlabs.io/daviestechlabs/ray-worker-intel` |
+
+## Building Locally
+
+```bash
+# Build all images
+make build-all
+
+# Build specific image
+make build-nvidia
+make build-rdna2
+make build-strixhalo
+make build-intel
+
+# Push to Gitea registry (requires login)
+docker login git.daviestechlabs.io
+make push-all
+```
+
+## CI/CD
+
+Images are automatically built and pushed to `git.daviestechlabs.io` package registry on:
+- Push to `main` branch
+- Git tag creation (e.g., `v1.0.0`)
+
+### Gitea Actions Secrets Required
+
+Add these secrets in Gitea repo settings → Actions → Secrets:
+
+| Secret | Description |
+|--------|-------------|
+| `REGISTRY_USER` | Gitea username |
+| `REGISTRY_TOKEN` | Gitea access token with `package:write` scope |
+
+## Directory Structure
+
+```
+kuberay-images/
+├── dockerfiles/
+│   ├── Dockerfile.ray-worker-nvidia
+│   ├── Dockerfile.ray-worker-rdna2
+│   ├── Dockerfile.ray-worker-strixhalo
+│   ├── Dockerfile.ray-worker-intel
+│   └── ray-entrypoint.sh
+├── ray-serve/
+│   ├── serve_embeddings.py
+│   ├── serve_whisper.py
+│   ├── serve_tts.py
+│   ├── serve_llm.py
+│   ├── serve_reranker.py
+│   └── requirements.txt
+├── .gitea/workflows/
+│   └── build-push.yaml
+├── Makefile
+└── README.md
+```
+
+## Environment Variables
+
+| Variable | Description | Default |
+|----------|-------------|---------|
+| `RAY_HEAD_SVC` | Ray head service name | `ai-inference-raycluster-head-svc` |
+| `GPU_RESOURCE` | Custom Ray resource name | `gpu_nvidia`, `gpu_amd`, etc. |
+| `NUM_GPUS` | Number of GPUs to expose | `1` |
+
+## Node Allocation
+
+| Node | Image | GPU | Memory |
+|------|-------|-----|--------|
+| elminster | ray-worker-nvidia | RTX 2070 | 8GB VRAM |
+| khelben | ray-worker-strixhalo | Strix Halo | 64GB Unified |
+| drizzt | ray-worker-rdna2 | Radeon 680M | 12GB VRAM |
+| danilo | ray-worker-intel | Intel Arc | 16GB Shared |
+
+## Related
+
+- [homelab-design](https://git.daviestechlabs.io/daviestechlabs/homelab-design) - Architecture documentation
+- [homelab-k8s2](https://github.com/Billy-Davies-2/homelab-k8s2) - Kubernetes manifests