feat(backends): add darwin/metal (MPS) build for trl (#10487)

* 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]

* fix(trl): guard uv-only --index-strategy for the pip/darwin path

The darwin/MPS build installs with pip (USE_PIP=true), which rejects the
uv-only --index-strategy flag and failed the darwin backend build. Add it
only on the uv path; Linux/CUDA resolution is unchanged.

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

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>

.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: "liquid-audio"
     tag-suffix: "-metal-darwin-arm64-liquid-audio"
     build-type: "mps"

backend/index.yaml

@@ -5295,6 +5295,7 @@
     nvidia: "cuda12-trl"
     nvidia-cuda-12: "cuda12-trl"
     nvidia-cuda-13: "cuda13-trl"
+    metal: "metal-trl"
 ## TRL backend images
 - !!merge <<: *trl
   name: "cpu-trl"
@@ -5326,6 +5327,16 @@
   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/install.sh

@@ -8,7 +8,13 @@ else
     source $backend_dir/../common/libbackend.sh
 fi
 
-EXTRA_PIP_INSTALL_FLAGS+=" --upgrade --index-strategy=unsafe-first-match"
+EXTRA_PIP_INSTALL_FLAGS+=" --upgrade"
+# --index-strategy is a uv-only flag. The darwin/MPS build installs with pip
+# (USE_PIP=true in scripts/build/python-darwin.sh), which rejects it. Only add
+# it when uv is the installer, keeping the Linux/CUDA resolution unchanged.
+if [ "x${USE_PIP:-}" != "xtrue" ]; then
+    EXTRA_PIP_INSTALL_FLAGS+=" --index-strategy=unsafe-first-match"
+fi
 installRequirements
 
 # Fetch convert_hf_to_gguf.py and gguf package from the same llama.cpp version

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.