[deps] goodbye python 3.9 (#9677)

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: hiyouga <16256802+hiyouga@users.noreply.github.com>
Co-authored-by: hiyouga <hiyouga@buaa.edu.cn>

src/llamafactory/webui/chatter.py

@@ -16,7 +16,7 @@ import json
 import os
 from collections.abc import Generator
 from contextlib import contextmanager
-from typing import TYPE_CHECKING, Any, Optional
+from typing import TYPE_CHECKING, Any
 
 from transformers.utils import is_torch_npu_available
 
@@ -81,7 +81,7 @@ class WebChatModel(ChatModel):
     def __init__(self, manager: "Manager", demo_mode: bool = False, lazy_init: bool = True) -> None:
         self.manager = manager
         self.demo_mode = demo_mode
-        self.engine: Optional[BaseEngine] = None
+        self.engine: BaseEngine | None = None
 
         if not lazy_init:  # read arguments from command line
             super().__init__()
@@ -197,9 +197,9 @@ class WebChatModel(ChatModel):
         lang: str,
         system: str,
         tools: str,
-        image: Optional[Any],
-        video: Optional[Any],
-        audio: Optional[Any],
+        image: Any | None,
+        video: Any | None,
+        audio: Any | None,
         max_new_tokens: int,
         top_p: float,
         temperature: float,

src/llamafactory/webui/common.py

@@ -17,7 +17,7 @@ import os
 import signal
 from collections import defaultdict
 from datetime import datetime
-from typing import Any, Optional, Union
+from typing import Any
 
 from psutil import Process
 from yaml import safe_dump, safe_load
@@ -71,7 +71,7 @@ def _get_config_path() -> os.PathLike:
     return os.path.join(DEFAULT_CACHE_DIR, USER_CONFIG)
 
 
-def load_config() -> dict[str, Union[str, dict[str, Any]]]:
+def load_config() -> dict[str, str | dict[str, Any]]:
     r"""Load user config if exists."""
     try:
         with open(_get_config_path(), encoding="utf-8") as f:
@@ -81,7 +81,7 @@ def load_config() -> dict[str, Union[str, dict[str, Any]]]:
 
 
 def save_config(
-    lang: str, hub_name: Optional[str] = None, model_name: Optional[str] = None, model_path: Optional[str] = None
+    lang: str, hub_name: str | None = None, model_name: str | None = None, model_path: str | None = None
 ) -> None:
     r"""Save user config."""
     os.makedirs(DEFAULT_CACHE_DIR, exist_ok=True)
@@ -151,7 +151,7 @@ def load_dataset_info(dataset_dir: str) -> dict[str, dict[str, Any]]:
         return {}
 
 
-def load_args(config_path: str) -> Optional[dict[str, Any]]:
+def load_args(config_path: str) -> dict[str, Any] | None:
     r"""Load the training configuration from config path."""
     try:
         with open(config_path, encoding="utf-8") as f:

src/llamafactory/webui/components/export.py

@@ -14,7 +14,7 @@
 
 import json
 from collections.abc import Generator
-from typing import TYPE_CHECKING, Union
+from typing import TYPE_CHECKING
 
 from ...extras.constants import PEFT_METHODS
 from ...extras.misc import torch_gc
@@ -37,7 +37,7 @@ if TYPE_CHECKING:
 GPTQ_BITS = ["8", "4", "3", "2"]
 
 
-def can_quantize(checkpoint_path: Union[str, list[str]]) -> "gr.Dropdown":
+def can_quantize(checkpoint_path: str | list[str]) -> "gr.Dropdown":
     if isinstance(checkpoint_path, list) and len(checkpoint_path) != 0:
         return gr.Dropdown(value="none", interactive=False)
     else:
@@ -49,7 +49,7 @@ def save_model(
     model_name: str,
     model_path: str,
     finetuning_type: str,
-    checkpoint_path: Union[str, list[str]],
+    checkpoint_path: str | list[str],
     template: str,
     export_size: int,
     export_quantization_bit: str,

src/llamafactory/webui/control.py

@@ -14,7 +14,7 @@
 
 import json
 import os
-from typing import Any, Optional
+from typing import Any
 
 from transformers.trainer_utils import get_last_checkpoint
 
@@ -206,7 +206,7 @@ def list_datasets(dataset_dir: str = None, training_stage: str = list(TRAINING_S
     return gr.Dropdown(choices=datasets)
 
 
-def list_output_dirs(model_name: Optional[str], finetuning_type: str, current_time: str) -> "gr.Dropdown":
+def list_output_dirs(model_name: str | None, finetuning_type: str, current_time: str) -> "gr.Dropdown":
     r"""List all the directories that can resume from.
 
     Inputs: top.model_name, top.finetuning_type, train.current_time

src/llamafactory/webui/runner.py

@@ -17,7 +17,7 @@ import os
 from collections.abc import Generator
 from copy import deepcopy
 from subprocess import PIPE, Popen, TimeoutExpired
-from typing import TYPE_CHECKING, Any, Optional
+from typing import TYPE_CHECKING, Any
 
 from transformers.utils import is_torch_npu_available
 
@@ -59,7 +59,7 @@ class Runner:
         self.manager = manager
         self.demo_mode = demo_mode
         """ Resume """
-        self.trainer: Optional[Popen] = None
+        self.trainer: Popen | None = None
         self.do_train = True
         self.running_data: dict[Component, Any] = None
         """ State """