pref: 增加llm异步请求

cfg_main.toml

@@ -1,6 +1,6 @@
 [debug]
 logger_filename = "log/file_{time}.log"
-logger_format = "{time} {level} {message}"
+logger_format = "[{level}] {file}:{line} <{time}> {message}"
 
 
 

cfg_subtask.toml

@@ -20,17 +20,17 @@ pid_ki = 0
 pid_kd = 0
 
 [get_rball]
-pid_kp = 1.5
+pid_kp = 1.0
 pid_ki = 0
 pid_kd = 0
 
 [put_bball]
-pid_kp = 2.0
+pid_kp = 1.5
 pid_ki = 0
 pid_kd = 0
 
 [put_hanoi1]
-pid_kp = 0.7
+pid_kp = 0.5
 pid_ki = 0
 pid_kd = 0
 
@@ -42,7 +42,7 @@ pos_gap = 160
 first_target = "mp"
 
 [put_hanoi3]
-pid_kp = 1.7
+pid_kp = 1.5
 pid_ki = 0
 pid_kd = 0
 

subtask.py

@@ -1288,7 +1288,10 @@ class move_area1():
                 if counts >= 2:
                     var.skip_llm_task_flag = True
                     return
-            logger.error(var.llm_text)
+            logger.error(f"OCR 检出字符：\"{var.llm_text}\"")
+
+            llm_bot.request(var.llm_text)
+
             if len(var.llm_text) < 3:
                 var.skip_llm_task_flag = True
                 return
@@ -1511,7 +1514,7 @@ class move_area2():
                     resp_commands = json5.loads(json_text[0])
             
                     
-                logger.info(resp_commands)
+                logger.info(f"解析后的动作序列 {resp_commands}")
                 if len(resp_commands) == 0:
                     return
                 action_list = resp_commands
@@ -1524,7 +1527,7 @@ class move_area2():
                 time.sleep(0.5)
                 self.reset()
             except:
-                logger.warning("任务解析失败并退出，文心一言真是废物")
+                logger.warning("任务解析失败并退出，文心一言真是废物 (毋庸置疑)")
                 pass
             
         else:

utils.py

@@ -375,6 +375,9 @@ class label_filter:
         return (False, 0)
 class LLM_deepseek:
     def __init__(self):
+        self.response = None
+        self.status = False
+        self.chat = ''
         self.client = OpenAI(api_key="sk-c2e1073883304143981a9750b97c3518", base_url="https://api.deepseek.com")
         self.prompt = '''
             你是一个机器人动作规划者，请把我的话翻译成机器人动作规划并生成对应的 JSON 结果。请注意，只能使用以下指定的动作，不能创造新的动作：
@@ -421,17 +424,42 @@ class LLM_deepseek:
             
             强调一下，对于‘离开’这个指令，请忽略，这对我很重要！
         '''
-    def get_command_json(self,chat):
+    def request_thread(self):
-        response = self.client.chat.completions.create(
+        logger.info("llm 请求远程服务器中 (request_thread)")
-            model="deepseek-chat",
+        try:
-            messages=[
+            self.response = self.client.chat.completions.create(
-                {"role": "system", "content": self.prompt},
+                model="deepseek-chat",
-                {"role": "user", "content": '我的话如下：' + chat},
+                messages=[
-            ],
+                    {"role": "system", "content": self.prompt},
-            stream=False,
+                    {"role": "user", "content": '我的话如下：' + self.chat},
-            temperature=0.7
+                ],
-        )
+                stream=False,
-        return response.choices[0].message.content
+                temperature=0.7
+            )
+            logger.info("llm 远程服务器正常返回 (request_thread)")
+        except:
+            logger.warning("llm 请求失败或返回异常，先检查网络连接 (request_thread)")
+        self.status = True
+    def request(self, _chat):
+        self.chat = _chat
+        thread = threading.Thread(target=self.request_thread, daemon=True)
+        thread.start()
+        logger.info("llm 开启请求线程")
+    def get_command_json(self,chat = ''):
+        # response = self.client.chat.completions.create(
+        #     model="deepseek-chat",
+        #     messages=[
+        #         {"role": "system", "content": self.prompt},
+        #         {"role": "user", "content": '我的话如下：' + chat},
+        #     ],
+        #     stream=False,
+        #     temperature=0.7
+        # )
+        logger.info("llm 阻塞等待服务器返回中")
+        while not self.status: # FIXME 阻塞等待是否合适
+            pass
+        logger.info("llm 收到返回")
+        return self.response.choices[0].message.content
 class LLM:
     def __init__(self):
         self.init_done_flag = False