fix: fix segfault in load model (#3879)

# What does this PR do?
Fix segfault with load model
The cc-vec integration failed with segfault when used with default
embedding model on macOS
`model_id: nomic-ai/nomic-embed-text-v1.5` and `provider_id:
sentence-transformers`
Checked crash report and see this is due to torch OPENMP settings.
Constrainting to 1 thread works without crashes.


## Test Plan
Tested with cc-vec integration 
1. start server llama stack run starter
2. Do the setup in https://github.com/raghotham/cc-vec to set env
variables and try
`uv run cc-vec index --url-patterns "%.github.io" --vector-store-name
"ml-research" --limit 50 --chunk-size 800 --overlap 400`

llama_stack/providers/utils/inference/embedding_mixin.py

@@ -6,9 +6,12 @@
 
 import asyncio
 import base64
+import platform
 import struct
 from typing import TYPE_CHECKING
 
+import torch
+
 from llama_stack.log import get_logger
 
 if TYPE_CHECKING:
@@ -24,6 +27,8 @@ from llama_stack.apis.inference import (
 
 EMBEDDING_MODELS = {}
 
+DARWIN = "Darwin"
+
 
 log = get_logger(name=__name__, category="providers::utils")
 
@@ -83,6 +88,13 @@ class SentenceTransformerEmbeddingMixin:
         def _load_model():
             from sentence_transformers import SentenceTransformer
 
+            platform_name = platform.system()
+            if platform_name == DARWIN:
+                # PyTorch's OpenMP kernels can segfault on macOS when spawned from background
+                # threads with the default parallel settings, so force a single-threaded CPU run.
+                log.debug(f"Constraining torch threads on {platform_name} to a single worker")
+                torch.set_num_threads(1)
+
             return SentenceTransformer(model, trust_remote_code=True)
 
         loaded_model = await asyncio.to_thread(_load_model)