[代码重构中]编写class STT_Runner中，将设计为线程启动。作为异步IO与资源管理模块。

src/pipeline/__init__.py

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+from src.pipeline.base import PipelineBase, Pipeline
+
+__all__ = ["PipelineBase", "Pipeline"]

src/pipeline/base.py

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+from abc import ABC, abstractmethod
+
+
+class PipelineBase(ABC):
+    """
+    管道基类
+    """
+    @abstractmethod
+    def run(self, *args, **kwargs):
+        """
+        运行管道
+        """
+
+class Pipeline(PipelineBase):
+    """
+    管道类
+    """
+    def __init__(self, *args, **kwargs):
+        """
+        """
+        pass

src/runner.py

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+"""
+运行器模块
+提供运行器基类和运行器类，用于管理音频数据和模型的交互。
+主要包含:
+- RunnerBase: 运行器基类,定义了基本接口
+- Runner: 运行器类,工厂模式实现
+- RunnerFactory: 运行器工厂类,用于创建运行器
+"""
+from abc import ABC, abstractmethod
+from typing import Dict, Any, List, Queue
+from src.audio_chunk import AudioChunk, AudioBinary
+from src.pipeline import Pipeline
+from src.model_loader import ModelLoader
+
+audio_chunk = AudioChunk()
+models_loaded = ModelLoader()
+pipelines_loaded = PipelineLoader()
+
+class RunnerBase(ABC):
+    """
+    运行器基类
+    """
+    # 计算资源
+    _audio_binary: AudioBinary = None
+    _models: Dict[str, Any] = {}
+    _pipeline: Pipeline = None
+
+    # IO交互
+    _receivers: List[callable] = []
+
+    # 异步交互消息队列
+    _input_queue: Queue = None
+    _output_queue: Queue = None
+
+    @abstractmethod
+    def adder(self, *args, **kwargs):
+        """
+        添加数据
+        """
+
+    @abstractmethod
+    def add_recevier(self, *args, **kwargs):
+        """
+        接收数据
+        """
+
+class STT_Runner(RunnerBase):
+    """
+    运行器类
+    工厂模式
+    """
+
+
+    def __init__(
+        self,
+        *,
+        audio_binary_list: List[AudioBinary],
+        models: Dict[str, Any],
+        pipeline_list: List[Pipeline],
+        input_queue: Queue,
+    ):
+        """
+        初始化
+        """
+        # 接收资源
+        self._audio_binary_list = audio_binary_list
+        self._models = models
+        self._pipeline_list = pipeline_list
+
+        # 配置资源
+        for pipeline in self._pipeline_list:
+            # 配置
+            if pipeline.get_config('audio_binary_name') is not None:
+                pipeline.set_audio_binary(self._audio_binary_list[pipeline.get_config('audio_binary_name')])
+            if pipeline.get_config('model_name_list') is not None:
+                pipeline.set_models(self._models)
+
+    def adder(self, *args, **kwargs):
+        """
+        添加数据
+        """
+        if self._pipeline_thread is None:
+            raise RuntimeError("Pipeline thread not started")
+        self._input_queue.put(args["data"])
+    
+    def add_recevier(self, recevier: callable):
+        """
+        添加数据接收者
+        """
+        if self._pipeline_thread is None:
+            raise RuntimeError("Pipeline thread not started")
+        self._receivers.append(recevier)
+
+    def run(self):
+        """
+        运行pipeline子线程
+        """
+        # 创建pipeline子线程
+        self._pipeline_thread = threading.Thread(
+            target=self._pipeline.run, 
+            args=(
+                input_queue=self._input_queue, 
+                output_queue=self._output_queue
+            )
+        )
+        self._pipeline_thread.start()
+
+    def stop(self):
+        """
+        停止pipeline子线程
+        """
+        # 结束pipeline子线程
+        self._pipeline_thread.join()
+    
+    def __del__(self):
+        """
+        析构
+        """
+        self.stop()
+
+class STT_RunnerFactory:
+    """
+    STT Runner工厂类
+    """
+    def _create_runner(
+        audio_binary_name: str,
+        model_name_list: List[str],
+        pipeline_name_list: List[str],
+    ):
+        """
+        全参数创建Runner
+        参数:
+            audio_binary_name: 音频二进制名称
+            model_name_list: 模型名称列表
+            pipeline_name_list: 管道名称列表
+        返回:
+            Runner实例
+        """
+        audio_binary = audio_chunk.get_audio_binary(audio_binary_name)
+        models: Dict[str, Any] = {
+            model_name: models_loaded.models[model_name]
+            for model_name in model_name_list
+        }
+        pipelines: List[Pipeline] = [
+            pipelines_loaded.pipelines[pipeline_name]
+            for pipeline_name in pipeline_name_list
+        ]
+        return Runner(audio_binary, models, pipelines)
+
+    @classmethod
+    def create_runner_from_config(
+        cls,
+        config: Dict[str, Any],
+    ):
+        audio_binary_name = config["audio_binary_name"]
+        model_name_list = config["model_name_list"]
+        pipeline_name_list = config["pipeline_name_list"]
+        return cls._create_runner(audio_binary_name, model_name_list, pipeline_name_list)
+
+    @classmethod
+    def create_runner_normal(
+        cls
+    )
+        audio_binary_name = None
+        model_name_list = models_loaded.models.keys()
+        pipeline_name_list = None
+        return cls._create_runner(audio_binary_name, model_name_list, pipeline_name_list)