fix:修复不启动意图识别，functioncall依旧加载的bug (#691)

update：intent_llm意图识别获取新闻和天气过长，tts容易出错，暂时只支持简单简单工具
2026-07-26 00:53:54 +08:00 · 2025-04-07 13:23:22 +08:00
parent 17bcaba026
commit d9cd9acd27
10 changed files with 228 additions and 181 deletions
@@ -132,9 +132,6 @@ class ConnectionHandler:
            await self.websocket.send(json.dumps(self.welcome_msg))
            # Load private configuration if device_id is provided
            bUsePrivateConfig = self.config.get("use_private_config", False)
-            self.logger.bind(tag=TAG).info(
-                f"bUsePrivateConfig: {bUsePrivateConfig}, device_id: {device_id}"
-            )
            if bUsePrivateConfig and device_id:
                try:
                    self.private_config = PrivateConfig(
@@ -220,50 +217,58 @@ class ConnectionHandler:
            self.prompt = self.private_config.private_config.get("prompt", self.prompt)
        self.dialogue.put(Message(role="system", content=self.prompt))

-        """加载插件"""
-        self.func_handler = FunctionHandler(self)
-        self.mcp_manager = MCPManager(self)
        """加载记忆"""
-        device_id = self.headers.get("device-id", None)
-        self.memory.init_memory(device_id, self.llm)
-
-        """为意图识别设置LLM，优先使用专用LLM"""
-        # 检查是否配置了专用的意图识别LLM
-        intent_llm_name = self.config["Intent"]["intent_llm"]["llm"]
-
-        # 记录开始初始化意图识别LLM的时间
-        intent_llm_init_start = time.time()
-
-        if (
-            not self.use_function_call_mode
-            and intent_llm_name
-            and intent_llm_name in self.config["LLM"]
-        ):
-            # 如果配置了专用LLM，则创建独立的LLM实例
-            from core.utils import llm as llm_utils
-
-            intent_llm_config = self.config["LLM"][intent_llm_name]
-            intent_llm_type = intent_llm_config.get("type", intent_llm_name)
-            intent_llm = llm_utils.create_instance(intent_llm_type, intent_llm_config)
-            self.logger.bind(tag=TAG).info(
-                f"为意图识别创建了专用LLM: {intent_llm_name}, 类型: {intent_llm_type}"
-            )
-
-            self.intent.set_llm(intent_llm)
-        else:
-            # 否则使用主LLM
-            self.intent.set_llm(self.llm)
-
-        # 记录意图识别LLM初始化耗时
-        intent_llm_init_time = time.time() - intent_llm_init_start
-
+        self._initialize_memory()
+        """加载意图识别"""
+        self._initialize_intent()
        """加载位置信息"""
        self.client_ip_info = get_ip_info(self.client_ip)
        if self.client_ip_info is not None and "city" in self.client_ip_info:
            self.logger.bind(tag=TAG).info(f"Client ip info: {self.client_ip_info}")
            self.prompt = self.prompt + f"\nuser location:{self.client_ip_info}"
+
            self.dialogue.update_system_message(self.prompt)

+    def _initialize_memory(self):
+        """初始化记忆模块"""
+        device_id = self.headers.get("device-id", None)
+        self.memory.init_memory(device_id, self.llm)
+
+    def _initialize_intent(self):
+        """初始化意图识别模块"""
+        # 获取意图识别配置
+        intent_config = self.config["Intent"]
+        intent_type = self.config["selected_module"]["Intent"]
+
+        # 如果使用 nointent，直接返回
+        if intent_type == "nointent":
+            return
+        # 使用 intent_llm 模式
+        elif intent_type == "intent_llm":
+            intent_llm_name = intent_config["intent_llm"]["llm"]
+
+            if intent_llm_name and intent_llm_name in self.config["LLM"]:
+                # 如果配置了专用LLM，则创建独立的LLM实例
+                from core.utils import llm as llm_utils
+
+                intent_llm_config = self.config["LLM"][intent_llm_name]
+                intent_llm_type = intent_llm_config.get("type", intent_llm_name)
+                intent_llm = llm_utils.create_instance(
+                    intent_llm_type, intent_llm_config
+                )
+                self.logger.bind(tag=TAG).info(
+                    f"为意图识别创建了专用LLM: {intent_llm_name}, 类型: {intent_llm_type}"
+                )
+                self.intent.set_llm(intent_llm)
+            else:
+                # 否则使用主LLM
+                self.intent.set_llm(self.llm)
+                self.logger.bind(tag=TAG).info("使用主LLM作为意图识别模型")
+
+        """加载插件"""
+        self.func_handler = FunctionHandler(self)
+        self.mcp_manager = MCPManager(self)
+
        """加载MCP工具"""
        asyncio.run_coroutine_threadsafe(
            self.mcp_manager.initialize_servers(), self.loop
@@ -769,7 +774,8 @@ class ConnectionHandler:
    async def close(self, ws=None):
        """资源清理方法"""
        # 清理MCP资源
-        await self.mcp_manager.cleanup_all()
+        if hasattr(self, "mcp_manager") and self.mcp_manager:
+            await self.mcp_manager.cleanup_all()

        # 触发停止事件并清理资源
        if self.stop_event:
@@ -69,12 +69,13 @@ async def process_intent_result(conn, intent_result, original_text):
        # 检查是否有function_call
        if "function_call" in intent_data:
            # 直接从意图识别获取了function_call
-            logger.bind(tag=TAG).info(
+            logger.bind(tag=TAG).debug(
                f"检测到function_call格式的意图结果: {intent_data['function_call']['name']}"
            )
            function_name = intent_data["function_call"]["name"]
            if function_name == "continue_chat":
                return False
+
            function_args = None
            if "arguments" in intent_data["function_call"]:
                function_args = intent_data["function_call"]["arguments"]
@@ -263,6 +263,8 @@ def register_device_type(descriptor):

 # 用于接受前端设备推送的搜索iot描述
 async def handleIotDescriptors(conn, descriptors):
+    if not conn.use_function_call_mode:
+        return
    wait_max_time = 5
    while conn.func_handler is None or not conn.func_handler.finish_init:
        await asyncio.sleep(1)
@@ -9,20 +9,23 @@ logger = setup_logging()
 class IntentProviderBase(ABC):
    def __init__(self, config):
        self.config = config
-        self.intent_options = config.get("intent_options", {
-            "handle_exit_intent": "结束聊天, 用户发来如再见之类的表示结束的话, 不想再进行对话的时候",
-            "play_music": "播放音乐, 用户希望你可以播放音乐, 只用于播放音乐的意图",
-            "get_weather": "查询天气, 用户希望查询某个地点的天气情况",
-            "get_news": "查询新闻, 用户希望查询最新新闻或特定类型的新闻",
-            "get_lunar": "用于获取今天的阴历/农历和黄历信息",
-            "get_time": "获取今天日期或者当前时间信息",
-            "continue_chat": "继续聊天",
-        })
+        self.intent_options = [
+            {
+                "name": "handle_exit_intent",
+                "desc": "结束聊天, 用户发来如再见之类的表示结束的话, 不想再进行对话的时候",
+            },
+            {
+                "name": "play_music",
+                "desc": "播放音乐, 用户希望你可以播放音乐, 只用于播放音乐的意图",
+            },
+            {"name": "get_time", "desc": "获取今天日期或者当前时间信息"},
+            {"name": "continue_chat", "desc": "继续聊天"},
+        ]

    def set_llm(self, llm):
        self.llm = llm
        # 获取模型名称和类型信息
-        model_name = getattr(llm, 'model_name', str(llm.__class__.__name__))
+        model_name = getattr(llm, "model_name", str(llm.__class__.__name__))
        # 记录更详细的日志
        logger.bind(tag=TAG).info(f"意图识别设置LLM: {model_name}")

@@ -35,7 +38,7 @@ class IntentProviderBase(ABC):
        Returns:
            返回识别出的意图，格式为:
            - "继续聊天"
-            - "结束聊天" 
+            - "结束聊天"
            - "播放音乐 歌名" 或 "随机播放音乐"
            - "查询天气 地点名" 或 "查询天气 [当前位置]"
        """
@@ -16,5 +16,7 @@ class IntentProvider(IntentProviderBase):
        Returns:
            固定返回"继续聊天"
        """
-        logger.bind(tag=TAG).debug("Using functionCallProvider, always returning continue chat")
-        return self.intent_options["continue_chat"]
+        logger.bind(tag=TAG).debug(
+            "Using functionCallProvider, always returning continue chat"
+        )
+        return '{"function_call": {"name": "continue_chat"}}'
@@ -27,119 +27,94 @@ class IntentProvider(IntentProviderBase):
        Returns:
            格式化后的系统提示词
        """
-        intent_list = []

        prompt = (
            "你是一个意图识别助手。请分析用户的最后一句话，判断用户意图属于以下哪一类：\n"
            "<start>"
-            f"{', '.join(intent_list)}"
+            f"{str(self.intent_options)}"
            "<end>\n"
            "处理步骤:"
            "1. 思考意图类型，生成function_call格式"
            "\n\n"
            "返回格式示例：\n"
-            "1. 播放音乐意图: {\"function_call\": {\"name\": \"play_music\", \"arguments\": {\"song_name\": \"音乐名称\"}}}\n"
-            "2. 查询天气意图: {\"function_call\": {\"name\": \"get_weather\", \"arguments\": {\"location\": \"地点名称\", \"lang\": \"zh_CN\"}}}\n"
-            "3. 查询新闻意图: {\"function_call\": {\"name\": \"get_news\", \"arguments\": {\"category\": \"新闻类别\", \"detail\": false, \"lang\": \"zh_CN\"}}}\n"
-            "4. 结束对话意图: {\"function_call\": {\"name\": \"handle_exit_intent\", \"arguments\": {\"say_goodbye\": \"goodbye\"}}}\n"
-            "5. 获取当天日期时间: {\"function_call\": {\"name\": \"get_time\"}}\n"
-            "6. 获取当前黄历意图: {\"function_call\": {\"name\": \"get_lunar\"}}\n"
-            "7. 继续聊天意图: {\"function_call\": {\"name\": \"continue_chat\"}}\n"
+            '1. 播放音乐意图: {"function_call": {"name": "play_music", "arguments": {"song_name": "音乐名称"}}}\n'
+            '2. 结束对话意图: {"function_call": {"name": "handle_exit_intent", "arguments": {"say_goodbye": "goodbye"}}}\n'
+            '3. 获取当天日期时间: {"function_call": {"name": "get_time"}}\n'
+            '4. 继续聊天意图: {"function_call": {"name": "continue_chat"}}\n'
            "\n"
            "注意:\n"
-            "- 播放音乐：无歌名时，song_name设为\"random\"\n"
-            "- 查询天气：无地点时，location设为null\n"
-            "- 查询新闻：无类别时，category设为null；查询详情时，detail设为true\n"
+            '- 播放音乐：无歌名时，song_name设为"random"\n'
            "- 如果没有明显的意图，应按照继续聊天意图处理\n"
            "- 只返回纯JSON，不要任何其他内容\n"
            "\n"
            "示例分析:\n"
            "```\n"
-            "用户: 你好小智\n"
-            "返回: {\"function_call\": {\"name\": \"continue_chat\"}}\n"
-            "```\n"
-            "```\n"
-            "用户: 你今天怎么样?\n"
-            "返回: {\"function_call\": {\"name\": \"continue_chat\"}}\n"
+            "用户: 你也太搞笑了\n"
+            '返回: {"function_call": {"name": "continue_chat"}}\n'
            "```\n"
            "```\n"
            "用户: 现在是几号了?现在几点了？\n"
-            "返回: {\"function_call\": {\"name\": \"get_time\"}}\n"
-            "```\n"
-            "```\n"
-            "用户: 今天农历是多少？\n"
-            "返回: {\"function_call\": {\"name\": \"get_lunar\"}}\n"
+            '返回: {"function_call": {"name": "get_time"}}\n'
            "```\n"
            "```\n"
            "用户: 我们明天再聊吧\n"
-            "返回: {\"function_call\": {\"name\": \"handle_exit_intent\"}}\n"
+            '返回: {"function_call": {"name": "handle_exit_intent"}}\n'
            "```\n"
            "```\n"
            "用户: 播放中秋月\n"
-            "返回: {\"function_call\": {\"name\": \"play_music\", \"arguments\": {\"song_name\": \"中秋月\"}}}\n"
+            '返回: {"function_call": {"name": "play_music", "arguments": {"song_name": "中秋月"}}}\n'
            "```\n"
            "```\n"
-            "用户: 北京天气怎么样\n"
-            "返回: {\"function_call\": {\"name\": \"get_weather\", \"arguments\": {\"location\": \"北京\", \"lang\": \"zh_CN\"}}}\n"
-            "```\n"
-            "```\n"
-            "用户: 今天天气怎么样\n"
-            "返回: {\"function_call\": {\"name\": \"get_weather\", \"arguments\": {\"location\": null, \"lang\": \"zh_CN\"}}}\n"
-            "```\n"
-            "```\n"
-            "用户: 播报财经新闻\n"
-            "返回: {\"function_call\": {\"name\": \"get_news\", \"arguments\": {\"category\": \"财经\", \"detail\": false, \"lang\": \"zh_CN\"}}}\n"
-            "```\n"
-            "```\n"
-            "用户: 有什么最新新闻\n"
-            "返回: {\"function_call\": {\"name\": \"get_news\", \"arguments\": {\"category\": null, \"detail\": false, \"lang\": \"zh_CN\"}}}\n"
-            "```\n"
-            "```\n"
-            "用户: 详细介绍一下这条新闻\n"
-            "返回: {\"function_call\": {\"name\": \"get_news\", \"arguments\": {\"detail\": true, \"lang\": \"zh_CN\"}}}\n"
-            "```\n"
            "可用的音乐名称:\n"
        )
        return prompt
-        
+
    def clean_cache(self):
        """清理过期缓存"""
        now = time.time()
        # 找出过期键
-        expired_keys = [k for k, v in self.intent_cache.items() if now - v['timestamp'] > self.cache_expiry]
+        expired_keys = [
+            k
+            for k, v in self.intent_cache.items()
+            if now - v["timestamp"] > self.cache_expiry
+        ]
        for key in expired_keys:
            del self.intent_cache[key]
-            
+
        # 如果缓存太大，移除最旧的条目
        if len(self.intent_cache) > self.cache_max_size:
            # 按时间戳排序并保留最新的条目
-            sorted_items = sorted(self.intent_cache.items(), key=lambda x: x[1]['timestamp'])
-            for key, _ in sorted_items[:len(sorted_items) - self.cache_max_size]:
+            sorted_items = sorted(
+                self.intent_cache.items(), key=lambda x: x[1]["timestamp"]
+            )
+            for key, _ in sorted_items[: len(sorted_items) - self.cache_max_size]:
                del self.intent_cache[key]

    async def detect_intent(self, conn, dialogue_history: List[Dict], text: str) -> str:
        if not self.llm:
            raise ValueError("LLM provider not set")
-            
+
        # 记录整体开始时间
        total_start_time = time.time()
-            
+
        # 打印使用的模型信息
-        model_info = getattr(self.llm, 'model_name', str(self.llm.__class__.__name__))
-        logger.bind(tag=TAG).info(f"使用意图识别模型: {model_info}")
-            
+        model_info = getattr(self.llm, "model_name", str(self.llm.__class__.__name__))
+        logger.bind(tag=TAG).debug(f"使用意图识别模型: {model_info}")
+
        # 计算缓存键
        cache_key = hashlib.md5(text.encode()).hexdigest()
-        
+
        # 检查缓存
        if cache_key in self.intent_cache:
            cache_entry = self.intent_cache[cache_key]
            # 检查缓存是否过期
-            if time.time() - cache_entry['timestamp'] <= self.cache_expiry:
+            if time.time() - cache_entry["timestamp"] <= self.cache_expiry:
                cache_time = time.time() - total_start_time
-                logger.bind(tag=TAG).info(f"使用缓存的意图: {cache_key} -> {cache_entry['intent']}, 耗时: {cache_time:.4f}秒")
-                return cache_entry['intent']
-                
+                logger.bind(tag=TAG).debug(
+                    f"使用缓存的意图: {cache_key} -> {cache_entry['intent']}, 耗时: {cache_time:.4f}秒"
+                )
+                return cache_entry["intent"]
+
        # 清理缓存
        self.clean_cache()

@@ -158,38 +133,41 @@ class IntentProvider(IntentProviderBase):
        music_file_names = music_config["music_file_names"]
        prompt_music = f"{self.promot}\n<start>{music_file_names}\n<end>"
        logger.bind(tag=TAG).debug(f"User prompt: {prompt_music}")
-        
+
        # 记录预处理完成时间
        preprocess_time = time.time() - total_start_time
        logger.bind(tag=TAG).debug(f"意图识别预处理耗时: {preprocess_time:.4f}秒")
-        
+
        # 使用LLM进行意图识别
        llm_start_time = time.time()
-        logger.bind(tag=TAG).info(f"开始LLM意图识别调用, 模型: {model_info}")
-        
+        logger.bind(tag=TAG).debug(f"开始LLM意图识别调用, 模型: {model_info}")
+
        intent = self.llm.response_no_stream(
-            system_prompt=prompt_music,
-            user_prompt=user_prompt
+            system_prompt=prompt_music, user_prompt=user_prompt
        )
-        
+
        # 记录LLM调用完成时间
        llm_time = time.time() - llm_start_time
-        logger.bind(tag=TAG).info(f"LLM意图识别完成, 模型: {model_info}, 调用耗时: {llm_time:.4f}秒")
-        
+        logger.bind(tag=TAG).debug(
+            f"LLM意图识别完成, 模型: {model_info}, 调用耗时: {llm_time:.4f}秒"
+        )
+
        # 记录后处理开始时间
        postprocess_start_time = time.time()
-        
+
        # 清理和解析响应
        intent = intent.strip()
        # 尝试提取JSON部分
-        match = re.search(r'\{.*\}', intent, re.DOTALL)
+        match = re.search(r"\{.*\}", intent, re.DOTALL)
        if match:
            intent = match.group(0)
-        
+
        # 记录总处理时间
        total_time = time.time() - total_start_time
-        logger.bind(tag=TAG).info(f"【意图识别性能】模型: {model_info}, 总耗时: {total_time:.4f}秒, LLM调用: {llm_time:.4f}秒, 查询: '{text[:20]}...'")
-        
+        logger.bind(tag=TAG).debug(
+            f"【意图识别性能】模型: {model_info}, 总耗时: {total_time:.4f}秒, LLM调用: {llm_time:.4f}秒, 查询: '{text[:20]}...'"
+        )
+
        # 尝试解析为JSON
        try:
            intent_data = json.loads(intent)
@@ -198,38 +176,42 @@ class IntentProvider(IntentProviderBase):
                function_data = intent_data["function_call"]
                function_name = function_data.get("name")
                function_args = function_data.get("arguments", {})
-                
+
                # 记录识别到的function call
-                logger.bind(tag=TAG).info(f"识别到function call: {function_name}, 参数: {function_args}")
-                
+                logger.bind(tag=TAG).info(
+                    f"识别到function call: {function_name}, 参数: {function_args}"
+                )
+
                # 添加到缓存
                self.intent_cache[cache_key] = {
-                    'intent': intent,
-                    'timestamp': time.time()
+                    "intent": intent,
+                    "timestamp": time.time(),
                }
-                
+
                # 后处理时间
                postprocess_time = time.time() - postprocess_start_time
                logger.bind(tag=TAG).debug(f"意图后处理耗时: {postprocess_time:.4f}秒")
-                
+
                # 确保返回完全序列化的JSON字符串
                return intent
            else:
                # 添加到缓存
                self.intent_cache[cache_key] = {
-                    'intent': intent,
-                    'timestamp': time.time()
+                    "intent": intent,
+                    "timestamp": time.time(),
                }
-                
+
                # 后处理时间
                postprocess_time = time.time() - postprocess_start_time
                logger.bind(tag=TAG).debug(f"意图后处理耗时: {postprocess_time:.4f}秒")
-                
+
                # 返回普通意图
                return intent
        except json.JSONDecodeError:
            # 后处理时间
            postprocess_time = time.time() - postprocess_start_time
-            logger.bind(tag=TAG).error(f"无法解析意图JSON: {intent}, 后处理耗时: {postprocess_time:.4f}秒")
+            logger.bind(tag=TAG).error(
+                f"无法解析意图JSON: {intent}, 后处理耗时: {postprocess_time:.4f}秒"
+            )
            # 如果解析失败，默认返回继续聊天意图
-            return "{\"intent\": \"继续聊天\"}"
+            return '{"intent": "继续聊天"}'
@@ -16,5 +16,7 @@ class IntentProvider(IntentProviderBase):
        Returns:
            固定返回"继续聊天"
        """
-        logger.bind(tag=TAG).debug("Using NoIntentProvider, always returning continue chat")
-        return self.intent_options["continue_chat"]
+        logger.bind(tag=TAG).debug(
+            "Using NoIntentProvider, always returning continue chat"
+        )
+        return '{"function_call": {"name": "continue_chat"}}'