分离api接口,增加差值日志

liveMan.py

@@ -422,7 +422,7 @@ class DouyinLiveWebReply:
         :param text: 文本
         :return: 耗时 单位秒
         """
-        return len(text)/5
+        return len(text)/4.5
 
     def __call__(self):
         """
@@ -531,9 +531,9 @@ class DouyinLiveWebReply:
                             self.live_chat_config.flush_precedence_reply_message()
                         logger.info(f"开始播放系统文案：{reply_message}")
                     cost = self.text_to_adio_cost_predict(reply_message)
-                    logger.info(f'文本:{reply_message}预计算出的语音时长：{cost}秒')
                     next_to_human_call_time = time.time() + cost
                     formatted_time = datetime.fromtimestamp(next_to_human_call_time).strftime("%Y-%m-%d %H:%M:%S")
+                    self.config["prediction_queue"].append(formatted_time)
                     logger.info(f'预计在{formatted_time}发送下一段语音')
                     self.post_to_human_sync(reply_message)
 

main.py

@@ -1,44 +1,15 @@
-import time
-from fastapi import FastAPI
-from pydantic import BaseModel
 import uvicorn
 from multiprocessing import Process, Event, freeze_support, Manager
 from loguru import logger
 
-from liveMan import DouyinLiveWebFetcher, DouyinLiveWebReply
 from helper import PromptQueue, LiveChatConfig
+from liveMan import DouyinLiveWebFetcher, DouyinLiveWebReply
 
-logger.add('log.log', encoding='utf-8', rotation="500MB")
-
-# FastAPI应用实例
-app = FastAPI(title="直播状态控制接口")
-
-# 请求体模型
-class SpeakingStatus(BaseModel):
-    is_speaking: bool
-
-# 全局变量，用于在FastAPI进程中存储共享字典引用
-app.state.shared_config = None
-
-# 接口：更新is_speaking状态
-@app.post("/speaking-status", summary="更新说话状态")
-def update_speaking_status(status: SpeakingStatus):
-    if app.state.shared_config is None:
-        return {"error": "服务未初始化"}
-    app.state.shared_config['is_speaking'] = status.is_speaking
-    # logger.info(f"通过API更新is_speaking状态为: {status.is_speaking}")
-    return {
-        "message": "状态更新成功",
-        "current_status": {
-            "is_speaking": app.state.shared_config['is_speaking'],
-        }
-    }
+logger.add("log.log", encoding="utf-8", rotation="500MB")
 
-# 启动FastAPI服务的函数，接收共享字典作为参数
 def start_fastapi_server(shared_config):
-    # 将共享字典存储到FastAPI应用的状态中
-    app.state.shared_config = shared_config
-    # 启动UVicorn服务器
+    from app import app
+    app.shared_config = shared_config
     uvicorn.run(app, host="0.0.0.0", port=8000)
 
 def fetch_user_chat_content(ws_open_event, queue):
@@ -49,19 +20,24 @@ def reply_user_chat_content(queue, config):
     reply = DouyinLiveWebReply(queue, config)
     reply()
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     freeze_support()
 
-    LiveChatConfig().update_chat_enable_status('启动中')
+    LiveChatConfig().update_chat_enable_status("启动中")
     with Manager() as manager:
-        # 创建共享字典，包含所有需要的键
+        prediction_queue = manager.list()  # 共享队列，用来存放预测时间（字符串）
+
         shared_config = manager.dict({
-            'is_speaking': False
+            "is_speaking": False,
+            "predicted_time": None,        # 最近一次用于对时差计算的预测时间
+            "speaking_false_time": None,   # is_speaking 变为 False 的真实时间
+            "time_diff_seconds": None,     # 真实时间 - 预测时间（秒）
+            "prediction_queue": prediction_queue  # FIFO 队列，避免覆盖
         })
+
         queue = PromptQueue(10)
         ws_open_event = Event()
 
-        # 创建进程时将共享字典传递给FastAPI服务
         api_process = Process(
             target=start_fastapi_server,
             args=(shared_config,),
@@ -69,20 +45,20 @@ if __name__ == '__main__':
         )
         fetch_process = Process(
             target=fetch_user_chat_content,
-            args=(ws_open_event, queue)
+            args=(ws_open_event, queue),
+            name="Fetcher"
         )
         reply_process = Process(
             target=reply_user_chat_content,
-            args=(queue, shared_config)
+            args=(queue, shared_config),
+            name="Replier"
         )
 
-        # 启动所有进程
         api_process.start()
         fetch_process.start()
         ws_open_event.wait()
         reply_process.start()
 
-        # 等待所有进程完成
         fetch_process.join()
         reply_process.join()
         api_process.join()