uninstall fix

README.md

@@ -5,7 +5,7 @@
   <img alt="exo logo" src="/docs/imgs/exo-logo-transparent.png" width="50%" height="50%">
 </picture>
 
-exo: Run frontier AI locally. Maintained by [exo labs](https://x.com/exolabs).
+exo: Run your own AI cluster at home with everyday devices. Maintained by [exo labs](https://x.com/exolabs).
 
 <p align="center">
   <a href="https://discord.gg/TJ4P57arEm" target="_blank" rel="noopener noreferrer"><img src="https://img.shields.io/badge/Discord-Join%20Server-5865F2?logo=discord&logoColor=white" alt="Discord"></a>

app/EXO/EXO/EXOApp.swift

@@ -225,7 +225,7 @@ private final class ExoUpdaterDelegate: NSObject, SPUUpdaterDelegate {
         }
     }
 
-    private func showNotification(title: String, body: String) {
+    nonisolated private func showNotification(title: String, body: String) {
         let center = UNUserNotificationCenter.current()
         let content = UNMutableNotificationContent()
         content.title = title

app/EXO/EXO/Services/NetworkSetupHelper.swift

@@ -241,11 +241,11 @@ enum NetworkSetupHelper {
         rm -f "$LOG_OUT" "$LOG_ERR"
 
         # Switch back to Automatic network location
-        networksetup -switchtolocation Automatic 2>/dev/null || true
+        networksetup -switchtolocation Automatic >/dev/null 2>&1 || true
 
         # Delete the exo network location if it exists
-        networksetup -listlocations | grep -q '^exo$' && {
-          networksetup -deletelocation exo 2>/dev/null || true
+        networksetup -listlocations 2>/dev/null | grep -q '^exo$' && {
+          networksetup -deletelocation exo >/dev/null 2>&1 || true
         } || true
 
         # Re-enable any Thunderbolt Bridge service if it exists
@@ -255,12 +255,12 @@ enum NetworkSetupHelper {
           tb_devices=$(networksetup -listallhardwareports 2>/dev/null | awk '
             /^Hardware Port:/ { port = tolower(substr($0, 16)) }
             /^Device:/ { if (port ~ /thunderbolt/) print substr($0, 9) }
-          ')
+          ') || true
           [ -z "$tb_devices" ] && return 0
 
           # For each bridge device, check if it contains Thunderbolt interfaces
           for bridge in bridge0 bridge1 bridge2; do
-            members=$(ifconfig "$bridge" 2>/dev/null | awk '/member:/ {print $2}')
+            members=$(ifconfig "$bridge" 2>/dev/null | awk '/member:/ {print $2}') || true
             [ -z "$members" ] && continue
 
             for tb_dev in $tb_devices; do
@@ -269,7 +269,7 @@ enum NetworkSetupHelper {
                 service_name=$(networksetup -listnetworkserviceorder 2>/dev/null | awk -v dev="$bridge" '
                   /^\\([0-9*]/ { gsub(/^\\([0-9*]+\\) /, ""); svc = $0 }
                   /Device:/ && $0 ~ dev { print svc; exit }
-                ')
+                ') || true
                 if [ -n "$service_name" ]; then
                   networksetup -setnetworkserviceenabled "$service_name" on 2>/dev/null || true
                   return 0
@@ -277,8 +277,9 @@ enum NetworkSetupHelper {
               fi
             done
           done
+          return 0
         }
-        find_and_enable_thunderbolt_bridge
+        find_and_enable_thunderbolt_bridge || true
 
         echo "EXO network components removed successfully"
         """

app/EXO/EXO/Services/ThunderboltBridgeService.swift

@@ -127,21 +127,24 @@ final class ThunderboltBridgeService: ObservableObject {
 
         // 2. Request specific network configuration rights
         let rightName = "system.services.systemconfiguration.network"
-        var item = AuthorizationItem(
-            name: rightName,
-            valueLength: 0,
-            value: nil,
-            flags: 0
-        )
-        var rights = AuthorizationRights(count: 1, items: &item)
-
-        status = AuthorizationCopyRights(
-            authRef,
-            &rights,
-            nil,
-            [.extendRights, .interactionAllowed],
-            nil
-        )
+        status = rightName.withCString { nameCString in
+            var item = AuthorizationItem(
+                name: nameCString,
+                valueLength: 0,
+                value: nil,
+                flags: 0
+            )
+            return withUnsafeMutablePointer(to: &item) { itemPointer in
+                var rights = AuthorizationRights(count: 1, items: itemPointer)
+                return AuthorizationCopyRights(
+                    authRef,
+                    &rights,
+                    nil,
+                    [.extendRights, .interactionAllowed],
+                    nil
+                )
+            }
+        }
         guard status == errAuthorizationSuccess else {
             if status == errAuthorizationCanceled {
                 throw ThunderboltBridgeError.authorizationCanceled

pyproject.toml

@@ -6,6 +6,8 @@ readme = "README.md"
 requires-python = ">=3.13"
 dependencies = [
     "aiofiles>=24.1.0",
+    "aiohttp>=3.12.14",
+    "types-aiofiles>=24.1.0.20250708",
     "pydantic>=2.11.7",
     "fastapi>=0.116.1",
     "filelock>=3.18.0",
@@ -15,9 +17,9 @@ dependencies = [
     "loguru>=0.7.3",
     "exo_pyo3_bindings", # rust bindings
     "anyio==4.11.0",
-    "mlx==0.30.4; sys_platform == 'darwin'",
-    "mlx[cpu]==0.30.4; sys_platform == 'linux'",
-    "mlx-lm",
+    "mlx==0.30.3; sys_platform == 'darwin'",
+    "mlx[cpu]==0.30.3; sys_platform == 'linux'",
+    "mlx-lm==0.30.5",
     "tiktoken>=0.12.0", # required for kimi k2 tokenizer
     "hypercorn>=0.18.0",
     "openai-harmony>=0.0.8",
@@ -61,7 +63,6 @@ members = [
 
 [tool.uv.sources]
 exo_pyo3_bindings = { workspace = true }
-mlx-lm = { git = "https://github.com/ml-explore/mlx-lm", branch = "main" }
 # Uncomment to use local mlx/mlx-lm development versions:
 # mlx = { path = "/Users/Shared/mlx", editable=true }
 # mlx-lm = { path = "/Users/Shared/mlx-lm", editable=true }

src/exo/download/coordinator.py

@@ -121,7 +121,6 @@ class DownloadCoordinator:
     def _start_download_task(
         self, shard: ShardMetadata, initial_progress: RepoDownloadProgress
     ) -> None:
-        logger.warning("starting download for {shard}")
         model_id = shard.model_card.model_id
 
         # Emit ongoing status

src/exo/download/download_utils.py

@@ -8,13 +8,13 @@ import traceback
 from collections.abc import Awaitable
 from datetime import timedelta
 from pathlib import Path
-from typing import Callable, Literal, cast
+from typing import Callable, Literal
 from urllib.parse import urljoin
 
 import aiofiles
 import aiofiles.os as aios
+import aiohttp
 import certifi
-import httpx
 from huggingface_hub import (
     snapshot_download,  # pyright: ignore[reportUnknownVariableType]
 )
@@ -176,7 +176,7 @@ async def fetch_file_list_with_cache(
         # Fetch failed - try cache fallback
         if await aios.path.exists(cache_file):
             logger.warning(
-                f"{type(e).__name__}: Failed to fetch file list for {model_id}, using cached data"
+                f"Failed to fetch file list for {model_id}, using cached data: {e}"
             )
             async with aiofiles.open(cache_file, "r") as f:
                 return TypeAdapter(list[FileListEntry]).validate_json(await f.read())
@@ -196,7 +196,7 @@ async def fetch_file_list_with_retry(
         except Exception as e:
             if attempt == n_attempts - 1:
                 raise e
-            await asyncio.sleep(min(16, 0.5 * float(2.0 ** int(attempt))))
+            await asyncio.sleep(min(8, 0.1 * float(2.0 ** int(attempt))))
     raise Exception(
         f"Failed to fetch file list for {model_id=} {revision=} {path=} {recursive=}"
     )
@@ -211,25 +211,26 @@ async def _fetch_file_list(
     headers = await get_download_headers()
     async with (
         create_http_session(timeout_profile="short") as session,
+        session.get(url, headers=headers) as response,
     ):
-        response = await session.get(url, headers=headers)
-        if response.status_code in [401, 403]:
-            msg = await _build_auth_error_message(response.status_code, model_id)
+        if response.status in [401, 403]:
+            msg = await _build_auth_error_message(response.status, model_id)
             raise HuggingFaceAuthenticationError(msg)
-        if response.status_code != 200:
-            raise Exception(f"Failed to fetch file list: {response.status_code}")
-
-        data = TypeAdapter(list[FileListEntry]).validate_json(response.text)
-        files: list[FileListEntry] = []
-        for item in data:
-            if item.type == "file":
-                files.append(FileListEntry.model_validate(item))
-            elif item.type == "directory" and recursive:
-                subfiles = await _fetch_file_list(
-                    model_id, revision, item.path, recursive
-                )
-                files.extend(subfiles)
-        return files
+        if response.status == 200:
+            data_json = await response.text()
+            data = TypeAdapter(list[FileListEntry]).validate_json(data_json)
+            files: list[FileListEntry] = []
+            for item in data:
+                if item.type == "file":
+                    files.append(FileListEntry.model_validate(item))
+                elif item.type == "directory" and recursive:
+                    subfiles = await _fetch_file_list(
+                        model_id, revision, item.path, recursive
+                    )
+                    files.extend(subfiles)
+            return files
+        else:
+            raise Exception(f"Failed to fetch file list: {response.status}")
 
 
 async def get_download_headers() -> dict[str, str]:
@@ -237,29 +238,34 @@ async def get_download_headers() -> dict[str, str]:
 
 
 def create_http_session(
+    auto_decompress: bool = False,
     timeout_profile: Literal["short", "long"] = "long",
-) -> httpx.AsyncClient:
+) -> aiohttp.ClientSession:
     if timeout_profile == "short":
         total_timeout = 30
         connect_timeout = 10
-        read_timeout = 30
+        sock_read_timeout = 30
+        sock_connect_timeout = 10
     else:
         total_timeout = 1800
         connect_timeout = 60
-        read_timeout = 1800
+        sock_read_timeout = 1800
+        sock_connect_timeout = 60
 
     ssl_context = ssl.create_default_context(
         cafile=os.getenv("SSL_CERT_FILE") or certifi.where()
     )
+    connector = aiohttp.TCPConnector(ssl=ssl_context)
 
-    # default here is to load env vars
-    return httpx.AsyncClient(
-        verify=ssl_context,
-        timeout=httpx.Timeout(
+    return aiohttp.ClientSession(
+        auto_decompress=auto_decompress,
+        connector=connector,
+        proxy=os.getenv("HTTPS_PROXY") or os.getenv("HTTP_PROXY") or None,
+        timeout=aiohttp.ClientTimeout(
+            total=total_timeout,
             connect=connect_timeout,
-            read=read_timeout,
-            write=total_timeout,
-            pool=total_timeout,
+            sock_read=sock_read_timeout,
+            sock_connect=sock_connect_timeout,
         ),
     )
 
@@ -286,28 +292,26 @@ async def file_meta(
     headers = await get_download_headers()
     async with (
         create_http_session(timeout_profile="short") as session,
-        session.stream("HEAD", url, headers=headers) as r,
+        session.head(url, headers=headers) as r,
     ):
-        if r.status_code == 307:
+        if r.status == 307:
             # On redirect, only trust Hugging Face's x-linked-* headers.
-            x_linked_size = cast(str | None, r.headers.get("x-linked-size"))
-            x_linked_etag = cast(str | None, r.headers.get("x-linked-etag"))
+            x_linked_size = r.headers.get("x-linked-size")
+            x_linked_etag = r.headers.get("x-linked-etag")
             if x_linked_size and x_linked_etag:
                 content_length = int(x_linked_size)
                 etag = trim_etag(x_linked_etag)
                 return content_length, etag
             # Otherwise, follow the redirect to get authoritative size/hash
-            redirected_location = cast(str | None, r.headers.get("location"))
+            redirected_location = r.headers.get("location")
             return await file_meta(model_id, revision, path, redirected_location)
-        if r.status_code in [401, 403]:
-            msg = await _build_auth_error_message(r.status_code, model_id)
+        if r.status in [401, 403]:
+            msg = await _build_auth_error_message(r.status, model_id)
             raise HuggingFaceAuthenticationError(msg)
-        content_length = cast(
-            str | None,
-            r.headers.get("x-linked-size") or r.headers.get("content-length"),
+        content_length = int(
+            r.headers.get("x-linked-size") or r.headers.get("content-length") or 0
         )
-        content_length = 0 if content_length is None else int(content_length)
-        etag = cast(str | None, r.headers.get("x-linked-etag") or r.headers.get("etag"))
+        etag = r.headers.get("x-linked-etag") or r.headers.get("etag")
         assert content_length > 0, f"No content length for {url}"
         assert etag is not None, f"No remote hash for {url}"
         etag = trim_etag(etag)
@@ -336,7 +340,7 @@ async def download_file_with_retry(
                 f"Download error on attempt {attempt}/{n_attempts} for {model_id=} {revision=} {path=} {target_dir=}"
             )
             logger.error(traceback.format_exc())
-            await asyncio.sleep(min(16, 0.5 * (2.0**attempt)))
+            await asyncio.sleep(min(8, 0.1 * (2.0**attempt)))
     raise Exception(
         f"Failed to download file {model_id=} {revision=} {path=} {target_dir=}"
     )
@@ -349,7 +353,6 @@ async def _download_file(
     target_dir: Path,
     on_progress: Callable[[int, int, bool], None] = lambda _, __, ___: None,
 ) -> Path:
-    logger.warning(f"downloading {path} from {model_id} to {target_dir}")
     target_path = target_dir / path
 
     if await aios.path.exists(target_path):
@@ -389,20 +392,20 @@ async def _download_file(
         n_read = resume_byte_pos or 0
         async with (
             create_http_session(timeout_profile="long") as session,
-            session.stream("GET", url, headers=headers, follow_redirects=True) as r,
+            session.get(url, headers=headers) as r,
         ):
-            if r.status_code == 404:
+            if r.status == 404:
                 raise FileNotFoundError(f"File not found: {url}")
-            if r.status_code in [401, 403]:
-                msg = await _build_auth_error_message(r.status_code, model_id)
+            if r.status in [401, 403]:
+                msg = await _build_auth_error_message(r.status, model_id)
                 raise HuggingFaceAuthenticationError(msg)
-            assert r.status_code in [200, 206], (
-                f"Failed to download {path} from {url}: {r.status_code}"
+            assert r.status in [200, 206], (
+                f"Failed to download {path} from {url}: {r.status}"
             )
             async with aiofiles.open(
                 partial_path, "ab" if resume_byte_pos else "wb"
             ) as f:
-                async for chunk in r.aiter_bytes(8 * 1024 * 1024):
+                while chunk := await r.content.read(8 * 1024 * 1024):
                     n_read = n_read + (await f.write(chunk))
                     on_progress(n_read, length, False)
 

src/exo/download/impl_shard_downloader.py

@@ -168,8 +168,7 @@ class ResumableShardDownloader(ShardDownloader):
                 yield await task
             # TODO: except Exception
             except Exception as e:
-                task.cancel()
-                logger.opt(exception=e).error("Error downloading shard")
+                logger.error("Error downloading shard:", e)
 
     async def get_shard_download_status_for_shard(
         self, shard: ShardMetadata

src/exo/shared/models/model_cards.py

@@ -1,5 +1,5 @@
 from enum import Enum
-from typing import Annotated, Any
+from typing import Annotated
 
 import aiofiles
 import aiofiles.os as aios
@@ -7,14 +7,7 @@ import tomlkit
 from anyio import Path, open_file
 from huggingface_hub import model_info
 from loguru import logger
-from pydantic import (
-    AliasChoices,
-    BaseModel,
-    Field,
-    PositiveInt,
-    field_validator,
-    model_validator,
-)
+from pydantic import BaseModel, Field, PositiveInt, field_validator
 
 from exo.shared.constants import EXO_ENABLE_IMAGE_MODELS
 from exo.shared.types.common import ModelId
@@ -128,14 +121,6 @@ MODEL_CARDS: dict[str, ModelCard] = {
         supports_tensor=True,
         tasks=[ModelTask.TextGeneration],
     ),
-    "kimi-k2.5": ModelCard(
-        model_id=ModelId("mlx-community/Kimi-K2.5"),
-        storage_size=Memory.from_gb(617),
-        n_layers=61,
-        hidden_size=7168,
-        supports_tensor=True,
-        tasks=[ModelTask.TextGeneration],
-    ),
     # llama-3.1
     "llama-3.1-8b": ModelCard(
         model_id=ModelId("mlx-community/Meta-Llama-3.1-8B-Instruct-4bit"),
@@ -718,18 +703,15 @@ if EXO_ENABLE_IMAGE_MODELS:
 class ConfigData(BaseModel):
     model_config = {"extra": "ignore"}  # Allow unknown fields
 
-    architectures: list[str] | None = None
+    # Common field names for number of layers across different architectures
+    num_hidden_layers: Annotated[int, Field(ge=0)] | None = None
+    num_layers: Annotated[int, Field(ge=0)] | None = None
+    n_layer: Annotated[int, Field(ge=0)] | None = None
+    n_layers: Annotated[int, Field(ge=0)] | None = None  # Sometimes used
+    num_decoder_layers: Annotated[int, Field(ge=0)] | None = None  # Transformer models
+    decoder_layers: Annotated[int, Field(ge=0)] | None = None  # Some architectures
     hidden_size: Annotated[int, Field(ge=0)] | None = None
-    layer_count: int = Field(
-        validation_alias=AliasChoices(
-            "num_hidden_layers",
-            "num_layers",
-            "n_layer",
-            "n_layers",
-            "num_decoder_layers",
-            "decoder_layers",
-        )
-    )
+    architectures: list[str] | None = None
 
     @property
     def supports_tensor(self) -> bool:
@@ -744,27 +726,25 @@ class ConfigData(BaseModel):
             ["GptOssForCausalLM"],
         ]
 
-    @model_validator(mode="before")
-    @classmethod
-    def defer_to_text_config(cls, data: dict[str, Any]):
-        text_config = data.get("text_config")
-        if text_config is None:
-            return data
+    @property
+    def layer_count(self) -> int:
+        # Check common field names for layer count
+        layer_fields = [
+            self.num_hidden_layers,
+            self.num_layers,
+            self.n_layer,
+            self.n_layers,
+            self.num_decoder_layers,
+            self.decoder_layers,
+        ]
 
-        for field in [
-            "architectures",
-            "hidden_size",
-            "num_hidden_layers",
-            "num_layers",
-            "n_layer",
-            "n_layers",
-            "num_decoder_layers",
-            "decoder_layers",
-        ]:
-            if (val := text_config.get(field)) is not None:  # pyright: ignore[reportAny]
-                data[field] = val
+        for layer_count in layer_fields:
+            if layer_count is not None:
+                return layer_count
 
-        return data
+        raise ValueError(
+            f"No layer count found in config.json: {self.model_dump_json()}"
+        )
 
 
 async def get_config_data(model_id: ModelId) -> ConfigData:

src/exo/utils/keyed_backoff.py

@@ -1,8 +1,10 @@
 import time
-from collections.abc import Hashable
+from typing import Generic, TypeVar
+
+K = TypeVar("K")
 
 
-class KeyedBackoff[K: Hashable]:
+class KeyedBackoff(Generic[K]):
     """Tracks exponential backoff state per key."""
 
     def __init__(self, base: float = 0.5, cap: float = 10.0):

src/exo/worker/engines/mlx/auto_parallel.py

@@ -23,7 +23,6 @@ from mlx_lm.models.glm4_moe_lite import Glm4MoeLiteDecoderLayer, Glm4MoeLiteMLP
 from mlx_lm.models.glm4_moe_lite import Model as GLM4MoeLiteModel
 from mlx_lm.models.gpt_oss import GptOssMoeModel
 from mlx_lm.models.gpt_oss import Model as GptOssModel
-from mlx_lm.models.kimi_k25 import Model as KimiK25Model
 from mlx_lm.models.llama import Model as LlamaModel
 from mlx_lm.models.minimax import Model as MiniMaxModel
 from mlx_lm.models.ministral3 import Model as Ministral3Model
@@ -345,7 +344,7 @@ def tensor_auto_parallel(
             all_to_sharded_linear_in_place,
             sharded_to_all_linear_in_place,
         )
-    elif isinstance(model, (DeepseekV3Model, DeepseekV32Model, KimiK25Model)):
+    elif isinstance(model, (DeepseekV3Model, DeepseekV32Model)):
         tensor_parallel_sharding_strategy = DeepSeekShardingStrategy(
             group,
             all_to_sharded_linear,
@@ -454,7 +453,7 @@ def _set_layers(model: nn.Module, layers: list[_LayerCallable]) -> None:
 
         # Update DeepSeek V3 specific parameters when layers are shrunk
         if isinstance(
-            model, (DeepseekV3Model, DeepseekV32Model, Glm4MoeModel, KimiK25Model)
+            model, (DeepseekV3Model, DeepseekV32Model, Glm4MoeModel)
         ) and hasattr(inner_model_instance, "num_layers"):
             logger.info(
                 f"Setting num_layers to {len(layers)} for model {model.model.__class__.__name__}"

src/exo/worker/engines/mlx/utils_mlx.py

@@ -165,11 +165,12 @@ def mlx_distributed_init(
 
                 jaccl_coordinator = jaccl_coordinators[bound_instance.bound_node_id]
 
+                # TODO: update once upstream fixes
                 logger.info(
-                    f"rank {rank} MLX_IBV_DEVICES: {coordination_file} with devices: {jaccl_devices_json}"
+                    f"rank {rank} MLX_JACCL_DEVICES: {coordination_file} with devices: {jaccl_devices_json}"
                 )
                 logger.info(f"rank {rank} MLX_JACCL_COORDINATOR: {jaccl_coordinator}")
-                os.environ["MLX_IBV_DEVICES"] = coordination_file
+                os.environ["MLX_JACCL_DEVICES"] = coordination_file
                 os.environ["MLX_RANK"] = str(rank)
                 os.environ["MLX_JACCL_COORDINATOR"] = jaccl_coordinator
                 group = mx.distributed.init(backend="jaccl", strict=True)
@@ -258,10 +259,10 @@ def shard_and_load(
 
     logger.info(f"Group size: {group.size()}, group rank: {group.rank()}")
 
-    # Estimate timeout based on model size (5x default for large queued workloads)
-    base_timeout = float(os.environ.get("EXO_MODEL_LOAD_TIMEOUT", "300"))
+    # Estimate timeout based on model size
+    base_timeout = float(os.environ.get("EXO_MODEL_LOAD_TIMEOUT", "60"))
     model_size_gb = get_weights_size(shard_metadata).in_bytes / (1024**3)
-    timeout_seconds = base_timeout + model_size_gb
+    timeout_seconds = base_timeout + model_size_gb / 5
     logger.info(
         f"Evaluating model parameters with timeout of {timeout_seconds:.0f}s "
         f"(model size: {model_size_gb:.1f}GB)"
@@ -338,35 +339,8 @@ def load_tokenizer_for_model_id(
 
     # Kimi uses a custom TikTokenTokenizer that transformers 5.x can't load via AutoTokenizer
     if "kimi-k2" in model_id_lower:
-        import importlib.util
-        import types
-
         sys.path.insert(0, str(model_path))
-
-        # Load tool_declaration_ts first (tokenization_kimi imports it with relative import)
-        tool_decl_path = model_path / "tool_declaration_ts.py"
-        if tool_decl_path.exists():
-            spec = importlib.util.spec_from_file_location(
-                "tool_declaration_ts", tool_decl_path
-            )
-            if spec and spec.loader:
-                tool_decl_module = importlib.util.module_from_spec(spec)
-                sys.modules["tool_declaration_ts"] = tool_decl_module
-                spec.loader.exec_module(tool_decl_module)
-
-        # Load tokenization_kimi with patched source (convert relative to absolute import)
-        tok_path = model_path / "tokenization_kimi.py"
-        source = tok_path.read_text()
-        source = source.replace("from .tool_declaration_ts", "from tool_declaration_ts")
-        spec = importlib.util.spec_from_file_location("tokenization_kimi", tok_path)
-        if spec:
-            tok_module = types.ModuleType("tokenization_kimi")
-            tok_module.__file__ = str(tok_path)
-            sys.modules["tokenization_kimi"] = tok_module
-            exec(compile(source, tok_path, "exec"), tok_module.__dict__)  # noqa: S102
-            TikTokenTokenizer = tok_module.TikTokenTokenizer  # type: ignore[attr-defined]  # noqa: N806
-        else:
-            from tokenization_kimi import TikTokenTokenizer  # type: ignore[import-not-found]  # noqa: I001
+        from tokenization_kimi import TikTokenTokenizer  # type: ignore[import-not-found]  # noqa: I001
 
         hf_tokenizer: Any = TikTokenTokenizer.from_pretrained(model_path)  # pyright: ignore[reportUnknownVariableType,reportUnknownMemberType]