mirror of
https://github.com/xinnan-tech/xiaozhi-esp32-server.git
synced 2026-07-22 07:03:53 +08:00
@@ -197,7 +197,7 @@ class ConnectionHandler:
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self.dialogue.put(Message(role="system", content=self.prompt))
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self.func_handler = FunctionHandler(self.config)
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def change_system_prompt(self, prompt):
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self.prompt = prompt
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# 找到原来的role==system,替换原来的系统提示
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@@ -303,7 +303,7 @@ class ConnectionHandler:
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self.logger.bind(tag=TAG).debug(json.dumps(self.dialogue.get_llm_dialogue(), indent=4, ensure_ascii=False))
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return True
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def chat_with_function_calling(self, query, tool_call = False):
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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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if self.isNeedAuth():
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@@ -311,7 +311,7 @@ class ConnectionHandler:
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future = asyncio.run_coroutine_threadsafe(self._check_and_broadcast_auth_code(), self.loop)
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future.result()
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return True
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if not tool_call:
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self.dialogue.put(Message(role="user", content=query))
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@@ -320,7 +320,7 @@ class ConnectionHandler:
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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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@@ -328,7 +328,7 @@ class ConnectionHandler:
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future = asyncio.run_coroutine_threadsafe(self.memory.query_memory(query), self.loop)
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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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# 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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@@ -351,8 +351,8 @@ 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 content is not None and len(content)>0:
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if len(response_message)<=0 and (content=="```" or "<tool_call>" in content):
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if content is not None and len(content) > 0:
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if len(response_message) <= 0 and (content == "```" or "<tool_call>" in content):
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tool_call_flag = True
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if tools_call is not None:
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@@ -366,7 +366,7 @@ class ConnectionHandler:
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if content is not None and len(content) > 0:
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if tool_call_flag:
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content_arguments+=content
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content_arguments += content
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else:
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response_message.append(content)
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@@ -422,16 +422,17 @@ class ConnectionHandler:
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else:
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function_arguments = json.loads(function_arguments)
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if not bHasError:
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self.logger.bind(tag=TAG).info(f"function_name={function_name}, function_id={function_id}, function_arguments={function_arguments}")
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self.logger.bind(tag=TAG).info(
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f"function_name={function_name}, function_id={function_id}, function_arguments={function_arguments}")
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function_call_data = {
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"name": function_name,
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"id": function_id,
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"arguments": function_arguments
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}
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result = self.func_handler.handle_llm_function_call(self, function_call_data)
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self._handle_function_result(result, function_call_data, text_index+1)
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self._handle_function_result(result, function_call_data, text_index + 1)
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# 处理最后剩余的文本
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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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@@ -443,7 +444,7 @@ class ConnectionHandler:
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self.tts_queue.put(future)
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# 存储对话内容
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if len(response_message)>0:
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if len(response_message) > 0:
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self.dialogue.put(Message(role="assistant", content="".join(response_message)))
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self.llm_finish_task = True
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@@ -452,32 +453,40 @@ class ConnectionHandler:
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return True
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def _handle_function_result(self, result, function_call_data, text_index):
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if result.action == Action.RESPONSE: # 直接回复前端
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if result.action == Action.RESPONSE: # 直接回复前端
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text = result.response
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self.recode_first_last_text(text, text_index)
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future = self.executor.submit(self.speak_and_play, text, text_index)
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self.tts_queue.put(future)
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self.dialogue.put(Message(role="assistant", content=text))
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elif result.action == Action.REQLLM: # 调用函数后再请求llm生成回复
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elif result.action == Action.REQLLM: # 调用函数后再请求llm生成回复
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text = result.result
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if text is not None and len(text) > 0:
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function_id = function_call_data["id"]
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function_name = function_call_data["name"]
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function_arguments = function_call_data["arguments"]
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self.dialogue.put(Message(role='assistant',
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tool_calls=[{"id": function_id,
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"function": {"arguments": function_arguments,"name": function_name},
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"type": 'function',
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"index": 0}]))
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tool_calls=[{"id": function_id,
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"function": {"arguments": function_arguments,
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"name": function_name},
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"type": 'function',
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"index": 0}]))
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self.dialogue.put(Message(role="tool", tool_call_id=function_id, content=text))
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self.chat_with_function_calling(text, tool_call=True)
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elif result.action == Action.NOTFOUND:
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text = result.response
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text = result.result
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self.recode_first_last_text(text, text_index)
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future = self.executor.submit(self.speak_and_play, text, text_index)
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self.tts_queue.put(future)
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self.dialogue.put(Message(role="assistant", content=text))
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else:
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text = result.response
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text = result.result
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self.recode_first_last_text(text, text_index)
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future = self.executor.submit(self.speak_and_play, text, text_index)
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self.tts_queue.put(future)
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self.dialogue.put(Message(role="assistant", content=text))
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def _tts_priority_thread(self):
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while not self.stop_event.is_set():
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@@ -197,12 +197,12 @@ def register_device_type(descriptor):
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# 为每个属性创建查询函数
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for prop_name, prop_info in descriptor["properties"].items():
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func_name = f"get_{{device_name.lower()}}_{{prop_name.lower()}}"
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func_name = f"get_{device_name.lower()}_{prop_name.lower()}"
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func_desc = {
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"type": "function",
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"function": {
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"name": func_name,
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"description": f"查询{{descriptor['description']}}的{{prop_info['description']}}",
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"description": f"查询{descriptor['description']}的{prop_info['description']}",
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"parameters": {
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"type": "object",
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"properties": {
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@@ -212,7 +212,7 @@ def register_device_type(descriptor):
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},
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"response_failure": {
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"type": "string",
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"description": f"查询失败时的友好回复,例如:'无法获取{{device_name}}的{{prop_info['description']}}'"
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"description": f"查询失败时的友好回复,例如:'无法获取{device_name}的{prop_info['description']}'"
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}
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},
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"required": ["response_success", "response_failure"]
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@@ -256,7 +256,7 @@ def register_device_type(descriptor):
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"type": "function",
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"function": {
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"name": func_name,
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"description": f"{{descriptor['description']}} - {{method_info['description']}}",
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"description": f"{descriptor['description']} - {method_info['description']}",
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"parameters": {
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"type": "object",
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"properties": parameters,
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