mirror of
https://github.com/xinnan-tech/xiaozhi-esp32-server.git
synced 2026-07-22 07:03:53 +08:00
update:合并chat和chat_with_function_calling
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@@ -506,106 +506,20 @@ class ConnectionHandler:
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# 更新系统prompt至上下文
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self.dialogue.update_system_message(self.prompt)
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def chat(self, query):
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self.dialogue.put(Message(role="user", content=query))
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response_message = []
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processed_chars = 0 # 跟踪已处理的字符位置
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try:
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# 使用带记忆的对话
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memory_str = None
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if self.memory is not None:
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future = asyncio.run_coroutine_threadsafe(
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self.memory.query_memory(query), self.loop
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)
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memory_str = future.result()
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self.logger.bind(tag=TAG).debug(f"记忆内容: {memory_str}")
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llm_responses = self.llm.response(
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self.session_id, self.dialogue.get_llm_dialogue_with_memory(memory_str)
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)
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except Exception as e:
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self.logger.bind(tag=TAG).error(f"LLM 处理出错 {query}: {e}")
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return None
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self.llm_finish_task = False
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text_index = 0
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for content in llm_responses:
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response_message.append(content)
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if self.client_abort:
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break
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# 合并当前全部文本并处理未分割部分
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full_text = "".join(response_message)
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current_text = full_text[processed_chars:] # 从未处理的位置开始
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# 查找最后一个有效标点
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punctuations = ("。", ".", "?", "?", "!", "!", ";", ";", ":")
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last_punct_pos = -1
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number_flag = True
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for punct in punctuations:
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pos = current_text.rfind(punct)
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prev_char = current_text[pos - 1] if pos - 1 >= 0 else ""
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# 如果.前面是数字统一判断为小数
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if prev_char.isdigit() and punct == ".":
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number_flag = False
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if pos > last_punct_pos and number_flag:
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last_punct_pos = pos
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# 找到分割点则处理
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if last_punct_pos != -1:
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segment_text_raw = current_text[: last_punct_pos + 1]
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segment_text = get_string_no_punctuation_or_emoji(segment_text_raw)
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if segment_text:
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# 强制设置空字符,测试TTS出错返回语音的健壮性
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# if text_index % 2 == 0:
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# segment_text = " "
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text_index += 1
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self.recode_first_last_text(segment_text, text_index)
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future = self.executor.submit(
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self.speak_and_play, segment_text, text_index
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)
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self.tts_queue.put((future, text_index))
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processed_chars += len(segment_text_raw) # 更新已处理字符位置
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# 处理最后剩余的文本
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full_text = "".join(response_message)
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remaining_text = full_text[processed_chars:]
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if remaining_text:
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segment_text = get_string_no_punctuation_or_emoji(remaining_text)
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if segment_text:
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text_index += 1
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self.recode_first_last_text(segment_text, text_index)
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future = self.executor.submit(
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self.speak_and_play, segment_text, text_index
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)
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self.tts_queue.put((future, text_index))
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self.llm_finish_task = True
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self.dialogue.put(Message(role="assistant", content="".join(response_message)))
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self.logger.bind(tag=TAG).debug(
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json.dumps(self.dialogue.get_llm_dialogue(), indent=4, ensure_ascii=False)
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)
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return True
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def chat_with_function_calling(self, query, tool_call=False):
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self.logger.bind(tag=TAG).debug(f"Chat with function calling start: {query}")
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"""Chat with function calling for intent detection using streaming"""
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def chat(self, query, tool_call=False):
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self.logger.bind(tag=TAG).debug(f"Chat: {query}")
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if not tool_call:
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self.dialogue.put(Message(role="user", content=query))
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# Define intent functions
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functions = None
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if hasattr(self, "func_handler"):
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if self.intent_type == "function_call" and hasattr(self, "func_handler"):
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functions = self.func_handler.get_functions()
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response_message = []
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processed_chars = 0 # 跟踪已处理的字符位置
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try:
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start_time = time.time()
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# 使用带记忆的对话
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memory_str = None
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if self.memory is not None:
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@@ -614,14 +528,18 @@ class ConnectionHandler:
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)
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memory_str = future.result()
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# self.logger.bind(tag=TAG).info(f"对话记录: {self.dialogue.get_llm_dialogue_with_memory(memory_str)}")
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# 使用支持functions的streaming接口
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llm_responses = self.llm.response_with_functions(
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self.session_id,
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self.dialogue.get_llm_dialogue_with_memory(memory_str),
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functions=functions,
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)
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if functions is not None:
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# 使用支持functions的streaming接口
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llm_responses = self.llm.response_with_functions(
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self.session_id,
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self.dialogue.get_llm_dialogue_with_memory(memory_str),
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functions=functions,
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)
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else:
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llm_responses = self.llm.response(
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self.session_id,
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self.dialogue.get_llm_dialogue_with_memory(memory_str),
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)
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except Exception as e:
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self.logger.bind(tag=TAG).error(f"LLM 处理出错 {query}: {e}")
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return None
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@@ -637,27 +555,28 @@ class ConnectionHandler:
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content_arguments = ""
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for response in llm_responses:
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content, tools_call = response
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if self.intent_type == "function_call":
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content, tools_call = response
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if "content" in response:
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content = response["content"]
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tools_call = None
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if content is not None and len(content) > 0:
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content_arguments += content
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if "content" in response:
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content = response["content"]
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tools_call = None
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if content is not None and len(content) > 0:
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content_arguments += content
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if not tool_call_flag and content_arguments.startswith("<tool_call>"):
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# print("content_arguments", content_arguments)
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tool_call_flag = True
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if tools_call is not None:
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tool_call_flag = True
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if tools_call[0].id is not None:
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function_id = tools_call[0].id
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if tools_call[0].function.name is not None:
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function_name = tools_call[0].function.name
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if tools_call[0].function.arguments is not None:
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function_arguments += tools_call[0].function.arguments
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if not tool_call_flag and content_arguments.startswith("<tool_call>"):
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# print("content_arguments", content_arguments)
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tool_call_flag = True
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if tools_call is not None:
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tool_call_flag = True
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if tools_call[0].id is not None:
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function_id = tools_call[0].id
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if tools_call[0].function.name is not None:
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function_name = tools_call[0].function.name
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if tools_call[0].function.arguments is not None:
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function_arguments += tools_call[0].function.arguments
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else:
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content = response
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if content is not None and len(content) > 0:
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if not tool_call_flag:
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response_message.append(content)
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@@ -853,7 +772,7 @@ class ConnectionHandler:
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content=text,
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)
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)
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self.chat_with_function_calling(text, tool_call=True)
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self.chat(text, tool_call=True)
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elif result.action == Action.NOTFOUND or result.action == Action.ERROR:
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text = result.result
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self.recode_first_last_text(text, text_index)
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@@ -39,7 +39,9 @@ async def handleAudioMessage(conn, audio):
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if len(conn.asr_audio) < 15:
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conn.asr_server_receive = True
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else:
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raw_text, _ = await conn.asr.speech_to_text(conn.asr_audio, conn.session_id) # 确保ASR模块返回原始文本
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raw_text, _ = await conn.asr.speech_to_text(
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conn.asr_audio, conn.session_id
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) # 确保ASR模块返回原始文本
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conn.logger.bind(tag=TAG).info(f"识别文本: {raw_text}")
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text_len, _ = remove_punctuation_and_length(raw_text)
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if text_len > 0:
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@@ -76,11 +78,7 @@ async def startToChat(conn, text):
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# 意图未被处理,继续常规聊天流程
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await send_stt_message(conn, text)
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if conn.intent_type == "function_call":
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# 使用支持function calling的聊天方法
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conn.executor.submit(conn.chat_with_function_calling, text)
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else:
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conn.executor.submit(conn.chat, text)
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conn.executor.submit(conn.chat, text)
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async def no_voice_close_connect(conn):
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