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Author SHA1 Message Date
Ettore Di Giacinto
69c7a8e71d fix(mlx): strip file:// LocalPrefix before loading filesystem-imported models
MLX backends passed request.Model verbatim to mlx_lm/mlx_vlm load(). For a
model imported from the filesystem, LocalAI hands the backend a file:// URI
(its LocalPrefix), which load() rejects: the scheme is neither a valid HF
repo id nor an existing path (Path(model).exists() fails on the scheme),
producing "Repo id must be in the form 'repo_name' or 'namespace/repo_name'
... Use repo_type argument if needed".

Add a pure, unit-testable resolve_model_path(model, model_file) helper in the
shared python_utils: it prefers the resolved ModelFile, strips a file://
scheme and percent-decodes the path, and leaves plain repo ids and local
paths untouched. Wire it into the mlx, mlx-vlm and mlx-distributed backends
(load, model_key, and the distributed broadcast all use the normalized path).

Fixes #7461.

Assisted-by: claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-12 22:07:06 +00:00
7 changed files with 94 additions and 111 deletions

View File

@@ -5,6 +5,31 @@ imported by any backend that needs to parse LocalAI gRPC options or build a
chat-template-compatible message list from proto Message objects.
"""
import json
from urllib.parse import unquote
def resolve_model_path(model, model_file=""):
"""Resolve a LocalAI model reference to something an HF/MLX loader accepts.
LocalAI hands backends either a plain HuggingFace repo id
(``namespace/name``), an already-local filesystem path, or a
``file://`` URI (its ``LocalPrefix``) for models imported from disk.
Loaders such as ``mlx_lm.load`` reject the ``file://`` form because the
scheme is neither a valid repo id nor an existing path, so we normalize
it here before loading.
Resolution order:
1. Prefer ``model_file`` when set and non-empty - that is the resolved
local path LocalAI computed for the model.
2. Strip a ``file://`` scheme and percent-decode it to a plain path.
3. Leave plain repo ids and already-local paths unchanged.
"""
candidate = model_file if model_file else model
if candidate is None:
return candidate
if candidate.startswith("file://"):
return unquote(candidate[len("file://"):])
return candidate
def parse_options(options_list):

View File

@@ -28,7 +28,7 @@ import grpc
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'common'))
sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'common'))
from grpc_auth import get_auth_interceptors
from python_utils import messages_to_dicts, parse_options as _shared_parse_options
from python_utils import messages_to_dicts, parse_options as _shared_parse_options, resolve_model_path
from mlx_utils import parse_tool_calls, split_reasoning
@@ -99,7 +99,11 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
from mlx_lm import load
from mlx_lm.models.cache import make_prompt_cache, can_trim_prompt_cache, trim_prompt_cache
print(f"[Rank 0] Loading model: {request.Model}", file=sys.stderr)
# Normalize the model reference: strip LocalAI's file:// LocalPrefix
# and prefer the resolved ModelFile so mlx_lm.load() gets a plain
# repo id or filesystem path (it rejects file:// URIs).
model_path = resolve_model_path(request.Model, request.ModelFile)
print(f"[Rank 0] Loading model: {model_path}", file=sys.stderr)
self.options = parse_options(request.Options)
print(f"Options: {self.options}", file=sys.stderr)
@@ -128,7 +132,7 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
)
self.coordinator = DistributedCoordinator(self.group)
self.coordinator.broadcast_command(CMD_LOAD_MODEL)
self.coordinator.broadcast_model_name(request.Model)
self.coordinator.broadcast_model_name(model_path)
else:
print("[Rank 0] No hostfile configured, running single-node", file=sys.stderr)
@@ -144,9 +148,9 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
if tokenizer_config:
print(f"Loading with tokenizer_config: {tokenizer_config}", file=sys.stderr)
self.model, self.tokenizer = load(request.Model, tokenizer_config=tokenizer_config)
self.model, self.tokenizer = load(model_path, tokenizer_config=tokenizer_config)
else:
self.model, self.tokenizer = load(request.Model)
self.model, self.tokenizer = load(model_path)
if self.group is not None:
from sharding import pipeline_auto_parallel
@@ -157,7 +161,7 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
from mlx_cache import ThreadSafeLRUPromptCache
max_cache_entries = self.options.get("max_cache_entries", 10)
self.max_kv_size = self.options.get("max_kv_size", None)
self.model_key = request.Model
self.model_key = model_path
self.lru_cache = ThreadSafeLRUPromptCache(
max_size=max_cache_entries,
can_trim_fn=can_trim_prompt_cache,

View File

@@ -18,7 +18,7 @@ import grpc
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'common'))
sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'common'))
from grpc_auth import get_auth_interceptors
from python_utils import messages_to_dicts, parse_options
from python_utils import messages_to_dicts, parse_options, resolve_model_path
from mlx_utils import parse_tool_calls, split_reasoning
from mlx_vlm import load, stream_generate
@@ -67,7 +67,11 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
backend_pb2.Result: The load model result.
"""
try:
print(f"Loading MLX-VLM model: {request.Model}", file=sys.stderr)
# Normalize the model reference: strip LocalAI's file:// LocalPrefix
# and prefer the resolved ModelFile so mlx_vlm.load() gets a plain
# repo id or filesystem path (it rejects file:// URIs).
model_path = resolve_model_path(request.Model, request.ModelFile)
print(f"Loading MLX-VLM model: {model_path}", file=sys.stderr)
print(f"Request: {request}", file=sys.stderr)
# Parse Options[] key:value strings into a typed dict
@@ -76,10 +80,10 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
# Load model and processor using MLX-VLM
# mlx-vlm load function returns (model, processor) instead of (model, tokenizer)
self.model, self.processor = load(request.Model)
self.model, self.processor = load(model_path)
# Load model config for chat template support
self.config = load_config(request.Model)
self.config = load_config(model_path)
# Auto-infer the tool parser from the chat template. mlx-vlm has
# its own _infer_tool_parser that falls back to mlx-lm parsers.

View File

@@ -17,7 +17,7 @@ import grpc
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'common'))
sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'common'))
from grpc_auth import get_auth_interceptors
from python_utils import messages_to_dicts, parse_options
from python_utils import messages_to_dicts, parse_options, resolve_model_path
from mlx_utils import parse_tool_calls, split_reasoning
from mlx_lm import load, stream_generate
@@ -63,7 +63,11 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
backend_pb2.Result: The load model result.
"""
try:
print(f"Loading MLX model: {request.Model}", file=sys.stderr)
# Normalize the model reference: strip LocalAI's file:// LocalPrefix
# and prefer the resolved ModelFile so mlx_lm.load() gets a plain
# repo id or filesystem path (it rejects file:// URIs).
model_path = resolve_model_path(request.Model, request.ModelFile)
print(f"Loading MLX model: {model_path}", file=sys.stderr)
print(f"Request: {request}", file=sys.stderr)
# Parse Options[] key:value strings into a typed dict (shared helper)
@@ -89,9 +93,9 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
# Load model and tokenizer using MLX
if tokenizer_config:
print(f"Loading with tokenizer_config: {tokenizer_config}", file=sys.stderr)
self.model, self.tokenizer = load(request.Model, tokenizer_config=tokenizer_config)
self.model, self.tokenizer = load(model_path, tokenizer_config=tokenizer_config)
else:
self.model, self.tokenizer = load(request.Model)
self.model, self.tokenizer = load(model_path)
# mlx_lm.load() returns a TokenizerWrapper that detects tool
# calling and thinking markers from the chat template / vocab.
@@ -111,7 +115,7 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
# Initialize thread-safe LRU prompt cache for efficient generation
max_cache_entries = self.options.get("max_cache_entries", 10)
self.max_kv_size = self.options.get("max_kv_size", None)
self.model_key = request.Model
self.model_key = model_path
self.lru_cache = ThreadSafeLRUPromptCache(
max_size=max_cache_entries,
can_trim_fn=can_trim_prompt_cache,

View File

@@ -12,7 +12,7 @@ import backend_pb2_grpc
# Make the shared helpers importable so we can unit-test them without a
# running gRPC server.
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'common'))
from python_utils import messages_to_dicts, parse_options
from python_utils import messages_to_dicts, parse_options, resolve_model_path
from mlx_utils import parse_tool_calls, split_reasoning
class TestBackendServicer(unittest.TestCase):
@@ -322,6 +322,42 @@ class TestSharedHelpers(unittest.TestCase):
self.assertEqual(r, "")
self.assertEqual(c, "just text")
def test_resolve_model_path_file_uri(self):
# file:// LocalPrefix (LocalAI import) is stripped to a plain path.
self.assertEqual(resolve_model_path("file:///a/b"), "/a/b")
def test_resolve_model_path_file_uri_percent_decoded(self):
# Percent-encoded characters (e.g. spaces) are decoded.
self.assertEqual(
resolve_model_path("file:///Users/me/My%20Models/Qwen3"),
"/Users/me/My Models/Qwen3",
)
def test_resolve_model_path_hf_repo_id_unchanged(self):
# Plain HuggingFace repo ids must pass through untouched.
self.assertEqual(
resolve_model_path("mlx-community/Qwen3-Coder-30B"),
"mlx-community/Qwen3-Coder-30B",
)
def test_resolve_model_path_local_path_unchanged(self):
# An already-local absolute path is left as-is.
self.assertEqual(resolve_model_path("/models/Qwen3"), "/models/Qwen3")
def test_resolve_model_path_prefers_model_file(self):
# The resolved ModelFile wins over Model when both are set.
self.assertEqual(
resolve_model_path("file:///ignored", "/resolved/local/path"),
"/resolved/local/path",
)
def test_resolve_model_path_model_file_file_uri(self):
# A ModelFile that is itself a file:// URI is also normalized.
self.assertEqual(
resolve_model_path("ignored", "file:///a/b"),
"/a/b",
)
def test_parse_tool_calls_with_shim(self):
tm = types.SimpleNamespace(
tool_call_start="<tool_call>",

View File

@@ -2,8 +2,6 @@ package openai
import (
"net/http"
"runtime"
"strings"
"time"
"github.com/labstack/echo/v4"
@@ -13,52 +11,6 @@ import (
"github.com/pion/webrtc/v4"
)
// opusBackendName is the canonical gallery name/alias of the opus audio codec
// backend that the realtime WebRTC transport needs.
const opusBackendName = "opus"
// resolveOpusBackend picks which installed opus-codec backend the realtime
// WebRTC transport should load. The transport historically hardcoded the
// literal "opus" backend name, but on darwin/arm64 the only installable opus
// codec is "metal-opus" (it shares the gallery alias "opus"). When that
// platform-specific variant is registered under its concrete directory name
// rather than the "opus" alias key, loading the literal "opus" fails with
// "opus backend not available" (issue #9813). Given the set of currently
// loadable backend names, this returns the best opus codec to load for the
// running platform, falling back to the literal name so the caller surfaces
// the same error as before when no opus codec is installed at all.
func resolveOpusBackend(installed []string, goos, goarch string) string {
// An exact match wins: this covers the plain "opus" backend as well as the
// "opus" alias key registered by gallery alias resolution for a
// user-installed platform variant.
for _, b := range installed {
if b == opusBackendName {
return opusBackendName
}
}
// No "opus" key is registered (e.g. a system-path metal-opus whose alias
// was never collected). Fall back to a platform-appropriate "*opus*" codec
// backend; on darwin/arm64 prefer the metal build.
var fallback string
for _, b := range installed {
if !strings.Contains(strings.ToLower(b), opusBackendName) {
continue
}
if goos == "darwin" && goarch == "arm64" && strings.Contains(strings.ToLower(b), "metal") {
return b
}
if fallback == "" {
fallback = b
}
}
if fallback != "" {
return fallback
}
return opusBackendName
}
// RealtimeCallRequest is the JSON body for POST /v1/realtime/calls.
type RealtimeCallRequest struct {
SDP string `json:"sdp"`
@@ -142,25 +94,15 @@ func RealtimeCalls(application *application.Application) echo.HandlerFunc {
}
}()
// Load the Opus backend. The opus codec ships under different backend
// names per platform (e.g. "metal-opus" on darwin/arm64), so resolve the
// platform-appropriate variant from the installed backends instead of
// hardcoding the literal "opus" name (issue #9813).
ml := application.ModelLoader()
installed := make([]string, 0)
for name := range ml.GetAllExternalBackends(nil) {
installed = append(installed, name)
}
opusName := resolveOpusBackend(installed, runtime.GOOS, runtime.GOARCH)
opusBackend, err := ml.Load(
model.WithBackendString(opusName),
// Load the Opus backend
opusBackend, err := application.ModelLoader().Load(
model.WithBackendString("opus"),
model.WithModelID("__opus_codec__"),
model.WithModel(opusName),
model.WithModel("opus"),
)
if err != nil {
pc.Close()
xlog.Error("failed to load opus backend", "error", err, "backend", opusName)
xlog.Error("failed to load opus backend", "error", err)
return c.JSON(http.StatusInternalServerError, map[string]string{"error": "opus backend not available"})
}

View File

@@ -1,32 +0,0 @@
package openai
import (
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
)
var _ = Describe("resolveOpusBackend", func() {
It("prefers the exact opus backend when it is installed", func() {
Expect(resolveOpusBackend([]string{"opus", "metal-opus"}, "linux", "amd64")).To(Equal("opus"))
})
It("resolves to the opus alias key on linux", func() {
Expect(resolveOpusBackend([]string{"opus"}, "linux", "amd64")).To(Equal("opus"))
})
It("selects metal-opus on darwin/arm64 when no plain opus is installed", func() {
Expect(resolveOpusBackend([]string{"metal-opus"}, "darwin", "arm64")).To(Equal("metal-opus"))
})
It("selects metal-opus on darwin/arm64 even when other backends are present", func() {
Expect(resolveOpusBackend([]string{"silero-vad", "metal-opus", "whisper"}, "darwin", "arm64")).To(Equal("metal-opus"))
})
It("falls back to any opus codec backend when there is no exact match (non-darwin)", func() {
Expect(resolveOpusBackend([]string{"metal-opus"}, "linux", "amd64")).To(Equal("metal-opus"))
})
It("returns the literal opus name when no opus codec is installed", func() {
Expect(resolveOpusBackend([]string{"silero-vad", "whisper"}, "darwin", "arm64")).To(Equal("opus"))
})
})