defer heavy imoprts

openlrc/__init__.py

@@ -1,8 +1,9 @@
 #  Copyright (C) 2024. Hao Zheng
 #  All rights reserved.
 
+from openlrc.config import TranscriptionConfig, TranslationConfig
 from openlrc.models import ModelConfig, ModelProvider, list_chatbot_models
-from openlrc.openlrc import LRCer, TranscriptionConfig, TranslationConfig
+from openlrc.openlrc import LRCer
 
 __all__ = ("LRCer", "TranscriptionConfig", "TranslationConfig", "ModelConfig", "list_chatbot_models", "ModelProvider")
 __version__ = "1.6.1"

openlrc/config.py

@@ -0,0 +1,58 @@
+#  Copyright (C) 2025. Hao Zheng
+#  All rights reserved.
+
+from dataclasses import dataclass
+from pathlib import Path
+
+from openlrc.models import ModelConfig
+
+
+@dataclass
+class TranscriptionConfig:
+    """
+    Configuration for the transcription stage.
+
+    Args:
+        whisper_model: Name of whisper model. Default: ``large-v3``
+        compute_type: Computation type (``default``, ``int8``, ``int8_float16``,
+            ``int16``, ``float16``, ``float32``). Default: ``float16``
+        device: Device for computation. Default: ``cuda``
+        asr_options: Parameters for whisper model.
+        vad_options: Parameters for VAD model.
+        preprocess_options: Options for audio preprocessing.
+    """
+
+    whisper_model: str = "large-v3"
+    compute_type: str = "float16"
+    device: str = "cuda"
+    asr_options: dict | None = None
+    vad_options: dict | None = None
+    preprocess_options: dict | None = None
+
+
+@dataclass
+class TranslationConfig:
+    """
+    Configuration for the translation stage.
+
+    Args:
+        chatbot_model: The chatbot model to use. Can be a string like
+            ``'gpt-4.1-nano'`` or ``'provider:model-name'``, or a ``ModelConfig``
+            instance. Default: ``gpt-4.1-nano``
+        fee_limit: Maximum fee per translation call in USD. Default: ``0.8``
+        consumer_thread: Number of parallel translation threads. Default: ``4``
+        proxy: Proxy for API requests. e.g. ``'http://127.0.0.1:7890'``
+        base_url_config: Base URL dict for OpenAI & Anthropic.
+        glossary: Dictionary or path mapping source words to translations.
+        retry_model: Fallback model for translation retries.
+        is_force_glossary_used: Force glossary usage in context. Default: ``False``
+    """
+
+    chatbot_model: str | ModelConfig = "gpt-4.1-nano"
+    fee_limit: float = 0.8
+    consumer_thread: int = 4
+    proxy: str | None = None
+    base_url_config: dict | None = None
+    glossary: dict | str | Path | None = None
+    retry_model: str | ModelConfig | None = None
+    is_force_glossary_used: bool = False

openlrc/openlrc.py

@@ -1,30 +1,28 @@
 #  Copyright (C) 2025. Hao Zheng
 #  All rights reserved.
 
+from __future__ import annotations
+
 import concurrent.futures
 import json
 import shutil
 import traceback
 import warnings
 from copy import deepcopy
-from dataclasses import dataclass
 from pathlib import Path
 from pprint import pformat
 from queue import Queue
 from threading import Lock
-from typing import Any
+from typing import TYPE_CHECKING, Any
 
-from faster_whisper.transcribe import Segment
+if TYPE_CHECKING:
+    from faster_whisper.transcribe import Segment
 
-from openlrc.context import TranslateInfo
+from openlrc.config import TranscriptionConfig, TranslationConfig
 from openlrc.defaults import default_asr_options, default_preprocess_options, default_vad_options
 from openlrc.logger import logger
-from openlrc.models import ModelConfig
 from openlrc.opt import SubtitleOptimizer
-from openlrc.preprocess import Preprocessor
 from openlrc.subtitle import BilingualSubtitle, Subtitle
-from openlrc.transcribe import Transcriber
-from openlrc.translate import LLMTranslator
 from openlrc.utils import (
     Timer,
     extend_filename,
@@ -38,57 +36,6 @@
 _SENTINEL = object()
 
 
-@dataclass
-class TranscriptionConfig:
-    """
-    Configuration for the transcription stage.
-
-    Args:
-        whisper_model: Name of whisper model. Default: ``large-v3``
-        compute_type: Computation type (``default``, ``int8``, ``int8_float16``,
-            ``int16``, ``float16``, ``float32``). Default: ``float16``
-        device: Device for computation. Default: ``cuda``
-        asr_options: Parameters for whisper model.
-        vad_options: Parameters for VAD model.
-        preprocess_options: Options for audio preprocessing.
-    """
-
-    whisper_model: str = "large-v3"
-    compute_type: str = "float16"
-    device: str = "cuda"
-    asr_options: dict | None = None
-    vad_options: dict | None = None
-    preprocess_options: dict | None = None
-
-
-@dataclass
-class TranslationConfig:
-    """
-    Configuration for the translation stage.
-
-    Args:
-        chatbot_model: The chatbot model to use. Can be a string like
-            ``'gpt-4.1-nano'`` or ``'provider:model-name'``, or a ``ModelConfig``
-            instance. Default: ``gpt-4.1-nano``
-        fee_limit: Maximum fee per translation call in USD. Default: ``0.8``
-        consumer_thread: Number of parallel translation threads. Default: ``4``
-        proxy: Proxy for API requests. e.g. ``'http://127.0.0.1:7890'``
-        base_url_config: Base URL dict for OpenAI & Anthropic.
-        glossary: Dictionary or path mapping source words to translations.
-        retry_model: Fallback model for translation retries.
-        is_force_glossary_used: Force glossary usage in context. Default: ``False``
-    """
-
-    chatbot_model: str | ModelConfig = "gpt-4.1-nano"
-    fee_limit: float = 0.8
-    consumer_thread: int = 4
-    proxy: str | None = None
-    base_url_config: dict | None = None
-    glossary: dict | str | Path | None = None
-    retry_model: str | ModelConfig | None = None
-    is_force_glossary_used: bool = False
-
-
 class LRCer:
     """
     Orchestrator for audio/video transcription and translation.
@@ -220,9 +167,11 @@ def __init__(
         self.transcribed_paths = []
 
     @property
-    def transcriber(self) -> Transcriber:
+    def transcriber(self):
         """Lazily initialize and return the Transcriber instance (thread-safe)."""
         if self._transcriber is None:
+            from openlrc.transcribe import Transcriber
+
             with self._transcriber_lock:
                 if self._transcriber is None:
                     self._transcriber = Transcriber(
@@ -567,6 +516,9 @@ def _translate(self, audio_name, target_lang, transcribed_opt_sub, translated_pa
         This method handles the translation process, including context preparation,
         actual translation, and post-processing of the translated subtitles.
         """
+        from openlrc.context import TranslateInfo
+        from openlrc.translate import LLMTranslator
+
         context = TranslateInfo(
             title=audio_name, audio_type="Movie", glossary=self.glossary, forced_glossary=self.is_force_glossary_used
         )
@@ -810,6 +762,8 @@ def pre_process(self, paths, noise_suppress=False):
                     extract_audio(path)
                 paths[i] = audio_path
 
+        from openlrc.preprocess import Preprocessor
+
         return Preprocessor(paths, options=self.preprocess_options).run(noise_suppress)
 
     @staticmethod

openlrc/preprocess.py

@@ -4,8 +4,6 @@
 from concurrent.futures import ProcessPoolExecutor
 from pathlib import Path
 
-import torch
-from df.enhance import enhance, init_df, load_audio, save_audio
 from ffmpeg_normalize import FFmpegNormalize
 from tqdm import tqdm
 
@@ -63,6 +61,9 @@ def noise_suppression(self, audio_paths: list[Path], atten_lim_db: int = 15):
         if not audio_paths:
             return []
 
+        import torch
+        from df.enhance import enhance, init_df, load_audio, save_audio
+
         if "atten_lim_db" in self.options:
             atten_lim_db = self.options["atten_lim_db"]
 

tests/test_preprocess.py

@@ -1,6 +1,8 @@
 #  Copyright (C) 2024. Hao Zheng
 #  All rights reserved.
 import shutil
+import sys
+import types
 import unittest
 from pathlib import Path
 from unittest.mock import Mock, patch
@@ -9,16 +11,30 @@
 
 from openlrc.preprocess import Preprocessor
 
+# Python 3.10's unittest.mock.patch has a bug where @patch("df.enhance.enhance")
+# caches the function object `enhance` as the resolved `df.enhance`, causing
+# subsequent @patch("df.enhance.save_audio") to look up `save_audio` on the
+# function instead of the module (AttributeError). Fixed in Python 3.11+.
+# Workaround: inject a fake df.enhance module via sys.modules and use
+# patch.object() to avoid string-based path resolution entirely.
+_df_enhance = types.ModuleType("df.enhance")
+_df_enhance.enhance = lambda *a, **kw: None  # type: ignore[attr-defined]
+_df_enhance.init_df = lambda *a, **kw: None  # type: ignore[attr-defined]
+_df_enhance.load_audio = lambda *a, **kw: None  # type: ignore[attr-defined]
+_df_enhance.save_audio = lambda *a, **kw: None  # type: ignore[attr-defined]
+sys.modules.setdefault("df", types.ModuleType("df"))
+sys.modules.setdefault("df.enhance", _df_enhance)
+
 
 class TestPreprocessor(unittest.TestCase):
     def tearDown(self) -> None:
         preprocessed_path = Path("data/preprocessed")
         shutil.rmtree(preprocessed_path, ignore_errors=True)
 
-    @patch("openlrc.preprocess.enhance")
-    @patch("openlrc.preprocess.init_df")
-    @patch("openlrc.preprocess.load_audio")
-    @patch("openlrc.preprocess.save_audio")
+    @patch.object(_df_enhance, "enhance")
+    @patch.object(_df_enhance, "init_df")
+    @patch.object(_df_enhance, "load_audio")
+    @patch.object(_df_enhance, "save_audio")
     @patch("openlrc.preprocess.release_memory")
     def test_noise_suppression_returns_path_objects(
         self, mock_release_memory, mock_save_audio, mock_load_audio, mock_init_df, mock_enhance