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

dockerfiles/Dockerfile.ray-worker-nvidia

@@ -0,0 +1,53 @@
+# NVIDIA GPU Ray Worker for elminster (RTX 2070)
+# Used for: Whisper STT, TTS
+#
+# Build from llm-workflows root:
+#   docker build -t git.daviestechlabs.io/daviestechlabs/ray-worker-nvidia:latest -f dockerfiles/Dockerfile.ray-worker-nvidia .
+#
+FROM rayproject/ray:2.53.0-py311-cu121
+
+LABEL maintainer="billy-davies-2"
+LABEL description="Ray worker for NVIDIA GPUs (Whisper, TTS)"
+LABEL gpu.target="nvidia-cuda"
+
+WORKDIR /app
+
+# Install system dependencies for audio processing
+USER root
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    ffmpeg \
+    libsndfile1 \
+    git \
+    && rm -rf /var/lib/apt/lists/*
+USER ray
+
+# Install Python dependencies for inference
+RUN pip install --no-cache-dir \
+    faster-whisper \
+    openai-whisper \
+    TTS \
+    soundfile \
+    pydub \
+    librosa \
+    torch \
+    torchaudio \
+    fastapi \
+    uvicorn \
+    httpx \
+    pydantic
+
+# Copy Ray Serve Python code
+COPY --chown=ray:ray ray-serve/ /app/ray_serve/
+ENV PYTHONPATH=/app
+
+# Copy Ray Serve entrypoint
+COPY --chown=ray:ray dockerfiles/ray-entrypoint.sh /app/ray-entrypoint.sh
+RUN chmod +x /app/ray-entrypoint.sh
+
+# Default environment variables
+ENV CUDA_VISIBLE_DEVICES=0
+ENV RAY_HEAD_SVC="ai-inference-raycluster-head-svc"
+ENV GPU_RESOURCE="gpu_nvidia"
+ENV NUM_GPUS="1"
+
+ENTRYPOINT ["/app/ray-entrypoint.sh"]