feat(backends): add darwin/metal (MPS) build for trl

Authors backend/python/trl/requirements-mps.txt and wires trl into the
darwin CI matrix and gallery so the MPS training path can be built and
validated on Apple Silicon. The MPS variant installs plain PyPI torch
wheels (MPS-capable on macOS arm64) and the trl training stack; bitsandbytes
is omitted as it is a CUDA-only dependency with poor Apple Silicon support.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:opus-4.8 [Claude Code]

.github/backend-matrix.yml

@@ -4974,6 +4974,9 @@ includeDarwin:
   - backend: "kitten-tts"
     tag-suffix: "-metal-darwin-arm64-kitten-tts"
     build-type: "mps"
+  - backend: "trl"
+    tag-suffix: "-metal-darwin-arm64-trl"
+    build-type: "mps"
   - backend: "piper"
     tag-suffix: "-metal-darwin-arm64-piper"
     build-type: "metal"

backend/index.yaml

@@ -5282,6 +5282,7 @@
     nvidia: "cuda12-trl"
     nvidia-cuda-12: "cuda12-trl"
     nvidia-cuda-13: "cuda13-trl"
+    metal: "metal-trl"
 ## TRL backend images
 - !!merge <<: *trl
   name: "cpu-trl"
@@ -5313,6 +5314,16 @@
   uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-13-trl"
   mirrors:
     - localai/localai-backends:master-gpu-nvidia-cuda-13-trl
+- !!merge <<: *trl
+  name: "metal-trl"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-metal-darwin-arm64-trl"
+  mirrors:
+    - localai/localai-backends:latest-metal-darwin-arm64-trl
+- !!merge <<: *trl
+  name: "metal-trl-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-metal-darwin-arm64-trl"
+  mirrors:
+    - localai/localai-backends:master-metal-darwin-arm64-trl
 ## llama.cpp quantization backend
 - &llama-cpp-quantization
   name: "llama-cpp-quantization"

backend/python/trl/requirements-mps.txt

@@ -0,0 +1,12 @@
+torch==2.10.0
+trl
+peft
+datasets>=3.0.0
+transformers>=4.56.2
+accelerate>=1.4.0
+huggingface-hub>=1.3.0
+sentencepiece
+# Note: bitsandbytes is intentionally omitted on MPS. It is only used by the
+# CUDA (cublas) variants for 8-bit/4-bit quantization and has poor support on
+# Apple Silicon. torch here uses the plain PyPI wheels, which ship MPS support
+# on macOS arm64.