代码内容转移

backend_service/src/main.py

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+import asyncio
+import os
+from fastapi import FastAPI, WebSocket, WebSocketDisconnect
+from fastapi.staticfiles import StaticFiles
+import logging
+import threading
+import rclpy
+
+from .models import GeneratePlanRequest, ExecuteMissionRequest
+from .websocket_manager import websocket_manager
+from .py_tree_generator import py_tree_generator
+from .ros2_client import MissionActionClient
+
+# --- Application Setup ---
+app = FastAPI(
+    title="Drone Backend Service",
+    description="Handles mission planning, generation, and execution for the drone.",
+    version="1.0.0",
+)
+
+# --- Mount Static Files for Visualizations ---
+static_dir = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', 'generated_visualizations'))
+app.mount("/static", StaticFiles(directory=static_dir), name="static")
+
+# --- ROS2 Node and Client Initialization ---
+rclpy.init()
+ros2_client = MissionActionClient()
+
+def run_ros2_node():
+    """Spins the ROS2 node in a dedicated thread."""
+    logging.info("Starting to spin ROS2 node...")
+    rclpy.spin(ros2_client)
+    logging.info("ROS2 node has stopped spinning.")
+
+# --- API Endpoints ---
+
+@app.post("/generate_plan", response_model=dict)
+async def generate_plan_endpoint(request: GeneratePlanRequest):
+    """
+    Receives a user prompt and returns a generated `py_tree.json` with a visualization URL.
+    """
+    try:
+        pytree_dict = await py_tree_generator.generate(request.user_prompt)
+        return pytree_dict
+    except RuntimeError as e:
+        return {"error": str(e)}
+
+@app.post("/execute_mission", response_model=dict)
+async def execute_mission_endpoint(request: ExecuteMissionRequest):
+    """
+    Receives a `py_tree.json` and sends it to the drone for execution.
+    """
+    ros2_client.send_goal(request.py_tree)
+    return {"status": "execution_started"}
+
+@app.websocket("/ws/status")
+async def websocket_endpoint(websocket: WebSocket):
+    """
+    Handles the WebSocket connection for real-time status updates.
+    """
+    await websocket_manager.connect(websocket)
+    try:
+        while True:
+            await websocket.receive_text()
+    except WebSocketDisconnect:
+        websocket_manager.disconnect(websocket)
+        logging.info("Client disconnected from WebSocket.")
+
+
+# --- Server Lifecycle ---
+
+@app.on_event("startup")
+async def startup_event():
+    """
+    On startup, get the current asyncio event loop and pass it to the websocket manager.
+    Also, start the ROS2 node in a background thread.
+    """
+    # Configure WebSocket Manager
+    loop = asyncio.get_running_loop()
+    websocket_manager.set_loop(loop)
+    logging.info("WebSocket event loop configured.")
+
+    # Start ROS2 node in a background thread
+    ros2_thread = threading.Thread(target=run_ros2_node, daemon=True)
+    ros2_thread.start()
+    logging.info("ROS2 node thread started.")
+
+@app.on_event("shutdown")
+async def shutdown_event():
+    logging.info("Backend service shutting down.")
+    ros2_client.destroy_node()
+    rclpy.shutdown()
+    logging.info("ROS2 node shut down successfully.")

backend_service/src/models.py

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+from pydantic import BaseModel
+from typing import Dict, Any
+
+class GeneratePlanRequest(BaseModel):
+    user_prompt: str
+
+class ExecuteMissionRequest(BaseModel):
+    py_tree: Dict[str, Any]
+
+class StatusUpdate(BaseModel):
+    node_id: str
+    status: int

backend_service/src/prompts/system_prompt.txt

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+你是一个无人机任务规划专家。你的**唯一**任务是根据用户提供的任务指令和参考知识，生成一个结构化、可执行的行为树（Pytree）。
+
+你的输出**必须**是一个严格的、单一的JSON对象，不包含任何形式的解释、总结或自然语言描述。
+
+---
+
+#### 1. 可用节点定义 (必须遵守)
+
+你**必须**严格从以下JSON定义的列表中选择节点来构建行为树。不允许幻想或使用任何未定义的节点。
+
+```json
+{
+  "actions": [
+    {
+      "name": "takeoff",
+      "description": "无人机从当前位置垂直起飞到指定的海拔高度。",
+      "params": {
+        "altitude": "float, 目标海拔高度(米)"
+      }
+    },
+    {
+      "name": "fly_to_waypoint",
+      "description": "导航至一个WGS84坐标航点。无人机到达航点后该动作才算完成。",
+      "params": {
+        "latitude": "float, 目标纬度",
+        "longitude": "float, 目标经度",
+        "altitude": "float, 目标海拔高度(米)"
+      }
+    },
+    {
+      "name": "loiter_for_duration",
+      "description": "在当前位置上空悬停或盘旋一段时间。",
+      "params": {
+        "duration": "float, 悬停时间(秒)"
+      }
+    },
+    {
+      "name": "land_at_position",
+      "description": "在当前位置降落。",
+      "params": {}
+    },
+    {
+      "name": "return_to_launch",
+      "description": "自动返航并降落到起飞点。",
+      "params": {}
+    }
+  ],
+  "conditions": [],
+  "control_flow": [
+      {
+        "name": "Sequence",
+        "description": "序列节点，按顺序执行其子节点。只有当所有子节点都成功时，它才成功。",
+        "params": {},
+        "children": "array, 包含按顺序执行的子节点"
+      }
+  ]
+}
+```
+
+---
+
+#### 2. JSON结构规范 (必须遵守)
+
+生成的JSON对象**必须**有一个名为`root`的键，其值是一个有效的行为树节点对象。每个节点都必须包含 "type" 和 "name" 字段。
+
+```json
+{
+  "root": {
+    "type": "string, 'action' 或 'Sequence'",
+    "name": "string, 来自上方可用节点列表",
+    "params": "object, 包含所需的参数",
+    "children": "array, (可选) 包含子节点对象"
+  }
+}
+```
+
+---
+
+#### 3. 如何使用参考知识 (必须遵守)
+
+当系统提供“参考知识”时，你**必须**使用其中的坐标来填充`params`字段。例如，如果任务是“飞到教学楼”，并且参考知识中提供了“教学楼”的坐标是 `(纬度: 31.2304, 经度: 121.4737)`，那么你的 `fly_to_waypoint` 节点应该写成：
+
+`"params": {"latitude": 31.2304, "longitude": 121.4737, "altitude": 50.0}` (高度为默认或指定值)
+
+---
+
+#### 4. 任务规划示例 (Few-shot Learning)
+
+以下是一些完整的任务规划示例，请学习并模仿它们的思考过程和输出格式。
+
+##### 示例 1
+
+**用户任务:**
+"无人机起飞，飞到教学楼进行30秒的勘察，然后返航降落。"
+
+**参考知识:**
+"地理元素 '教学楼' (ID: 123) 是一个 建筑。 其中心位置坐标大约为 (纬度: 31.2304, 经度: 121.4737)。"
+
+**生成的Pytree:**
+```json
+{
+  "root": {
+    "type": "Sequence",
+    "name": "Mission",
+    "children": [
+      { "type": "action", "name": "takeoff", "params": { "altitude": 20.0 } },
+      { "type": "action", "name": "fly_to_waypoint", "params": { "latitude": 31.2304, "longitude": 121.4737, "altitude": 20.0 } },
+      { "type": "action", "name": "loiter_for_duration", "params": { "duration": 30.0 } },
+      { "type": "action", "name": "return_to_launch", "params": {} }
+    ]
+  }
+}
+```
+
+##### 示例 2
+
+**用户任务:**
+"飞到图书馆，然后去体育馆，最后在体育馆的位置降落。"
+
+**参考知识:**
+"地理元素 '图书馆' (ID: 456) 是一个 建筑。 其中心位置坐标大约为 (纬度: 31.2315, 经度: 121.4758)。
+地理元素 '体育馆' (ID: 789) 是一个 建筑。 其中心位置坐标大约为 (纬度: 31.2330, 经度: 121.4780)。"
+
+**生成的Pytree:**
+```json
+{
+  "root": {
+    "type": "Sequence",
+    "name": "Mission",
+    "children": [
+      { "type": "action", "name": "takeoff", "params": { "altitude": 50.0 } },
+      { "type": "action", "name": "fly_to_waypoint", "params": { "latitude": 31.2315, "longitude": 121.4758, "altitude": 50.0 } },
+      { "type": "action", "name": "fly_to_waypoint", "params": { "latitude": 31.2330, "longitude": 121.4780, "altitude": 50.0 } },
+      { "type": "action", "name": "land_at_position", "params": {} }
+    ]
+  }
+}
+```
+---
+
+#### 5. 最终指令
+
+现在，请严格按照以上规则和示例，根据用户提供的最新任务和参考知识，生成行为树JSON。直接输出JSON对象，不要有任何其他内容。

backend_service/src/py_tree_generator.py

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+import json
+import os
+import logging
+import uuid
+import re
+from typing import Dict, Any, Optional, Set
+
+import chromadb
+import openai
+from openai import OpenAIError
+import jsonschema
+import requests
+
+# --- 自定义远程嵌入函数 (与ingest.py中定义一致) ---
+from chromadb.api.types import Documents, EmbeddingFunction, Embeddings, Embeddable
+
+class RemoteEmbeddingFunction(EmbeddingFunction[Embeddable]):
+    def __init__(self, api_url: str):
+        self._api_url = api_url
+
+    def __call__(self, input: Embeddable) -> Embeddings:
+        if not isinstance(input, list) or not all(isinstance(doc, str) for doc in input):
+            return []
+        try:
+            response = requests.post(
+                self._api_url,
+                json={"input": input},
+                headers={"Content-Type": "application/json"}
+            )
+            response.raise_for_status()
+            data = response.json().get("data", [])
+            if not data:
+                return []
+            return [item['embedding'] for item in data]
+        except Exception as e:
+            logging.error(f"调用远程嵌入API时出错: {e}")
+            return []
+
+# --- 日志记录设置 ---
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s - %(levelname)s - %(message)s',
+    handlers=[
+        logging.StreamHandler()
+    ]
+)
+
+# ==============================================================================
+#  VALIDATION LOGIC (from utils/validation.py)
+# ==============================================================================
+
+def _parse_allowed_nodes_from_prompt(prompt_text: str) -> tuple[Set[str], Set[str]]:
+    """
+    从系统提示词中解析出允许的行动和条件节点。
+    """
+    try:
+        # 使用正则表达式查找JSON代码块
+        match = re.search(r"```json\s*({.*?})\s*```", prompt_text, re.DOTALL)
+        if not match:
+            logging.error("在系统提示词中未找到可用节点的JSON定义块。")
+            return set(), set()
+
+        json_str = match.group(1)
+        allowed_nodes = json.loads(json_str)
+        
+        # 从对象列表中提取节点名称
+        actions = {action['name'] for action in allowed_nodes.get("actions", []) if 'name' in action}
+        conditions = {condition['name'] for condition in allowed_nodes.get("conditions", []) if 'name' in condition}
+        
+        if not actions:
+            logging.warning("关键错误：从提示词解析出的行动节点列表为空，无法生成任何有效任务。")
+            
+        return actions, conditions
+
+    except json.JSONDecodeError:
+        logging.error("解析系统提示词中的JSON时失败。请检查格式。")
+        return set(), set()
+    except Exception as e:
+        logging.error(f"解析可用节点时发生未知错误: {e}")
+        return set(), set()
+
+def _generate_pytree_schema(allowed_actions: set, allowed_conditions: set) -> dict:
+    """
+    根据允许的行动和条件节点，动态生成一个JSON Schema。
+    """
+    # 递归节点定义
+    node_definition = {
+        "type": "object",
+        "properties": {
+            "type": {"type": "string", "enum": ["action", "condition", "Sequence", "Selector"]},
+            "name": {"type": "string"},
+            "params": {"type": "object"},
+            "children": {
+                "type": "array",
+                "items": {"$ref": "#/definitions/node"}
+            }
+        },
+        "required": ["type", "name"],
+        # 使用 allOf 和 if/then 来实现基于'type'字段的条件性'name'验证
+        "allOf": [
+            {
+                "if": {"properties": {"type": {"const": "action"}}},
+                "then": {"properties": {"name": {"enum": sorted(list(allowed_actions))}}}
+            },
+            {
+                "if": {"properties": {"type": {"const": "condition"}}},
+                "then": {"properties": {"name": {"enum": sorted(list(allowed_conditions))}}}
+            }
+        ]
+    }
+
+    # 完整的Schema结构
+    schema = {
+        "$schema": "http://json-schema.org/draft-07/schema#",
+        "title": "Pytree",
+        "definitions": {
+            "node": node_definition
+        },
+        "type": "object",
+        "properties": {
+            "root": { "$ref": "#/definitions/node" }
+        },
+        "required": ["root"]
+    }
+    return schema
+
+def _validate_pytree_with_schema(pytree_instance: dict, schema: dict) -> bool:
+    """
+    使用JSON Schema验证给定的Pytree实例。
+    """
+    try:
+        jsonschema.validate(instance=pytree_instance, schema=schema)
+        logging.info("验证成功！Pytree格式和内容均符合规范。")
+        return True
+    except jsonschema.ValidationError as e:
+        logging.warning("--- Pytree验证失败 ---")
+        logging.warning(f"错误信息: {e.message}")
+        error_path = list(e.path)
+        logging.warning(f"错误路径: {' -> '.join(map(str, error_path)) if error_path else '根节点'}")
+        logging.warning(f"出错的实例部分: {e.instance}")
+        return False
+    except Exception as e:
+        logging.error(f"进行JSON Schema验证时发生未知错误: {e}")
+        return False
+
+# ==============================================================================
+#  VISUALIZATION LOGIC (from utils/visualization.py)
+# ==============================================================================
+
+def _visualize_pytree(node: Dict, file_path: str):
+    """
+    使用Graphviz将Pytree字典可视化，并保存到指定路径。
+    """
+    try:
+        from graphviz import Digraph
+    except ImportError:
+        logging.critical("错误：未安装graphviz库。请运行: pip install graphviz")
+        return
+
+    dot = Digraph('Pytree', comment='Drone Mission Plan')
+    dot.attr('node', shape='box', style='rounded,filled', fontname='helvetica')
+    dot.attr(rankdir='TB', label='Drone Mission Plan', fontsize='20')
+
+    _add_nodes_and_edges(node, dot)
+    
+    try:
+        # 保存为 .png 文件，并自动删除源码 .gv 文件
+        output_path = dot.render(file_path, format='png', cleanup=True, view=False)
+        logging.info("--- 任务树可视化成功 ---")
+        logging.info(f"图形已保存到: {output_path}")
+    except Exception as e:
+        logging.error("--- 错误：生成可视化图形失败 ---")
+        logging.error("请确保您的系统已经正确安装了Graphviz图形库。")
+        logging.error(f"错误详情: {e}")
+
+def _add_nodes_and_edges(node: dict, dot, parent_id: str | None = None) -> str:
+    """递归辅助函数，用于添加节点和边。"""
+    
+    # 为每个节点创建一个唯一的ID
+    current_id = str(id(node))
+    
+    # 准备节点标签
+    node_label = f"<{node['name']}<br/><i>({node['type']})</i>"
+    if node.get('params'):
+        params_str = json.dumps(node.get('params'))
+        node_label += f"<br/><font point-size='10'>params: {params_str}</font>"
+    node_label += ">"
+
+    # 根据类型设置节点样式
+    node_type = node.get('type', '').lower()
+    if node_type == 'action':
+        dot.node(current_id, label=node_label, shape='box', color="#cde4ff")
+    elif node_type == 'condition':
+        dot.node(current_id, label=node_label, shape='diamond', color="#fff2cc")
+    else: # Sequence, Selector, etc.
+        dot.node(current_id, label=node_label, shape='ellipse', color='#e6e6e6')
+
+    # 连接父节点
+    if parent_id:
+        dot.edge(parent_id, current_id)
+    
+    # 递归处理子节点
+    last_child_id = current_id
+    for child in node.get("children", []):
+        # 对于序列，边是连续的；对于选择器，所有子节点都连接到父节点
+        if node_type in ['sequence']:
+             last_child_id = _add_nodes_and_edges(child, dot, last_child_id)
+        else: # Selector, Parallel
+            _add_nodes_and_edges(child, dot, current_id)
+            
+    return current_id
+
+# ==============================================================================
+#  CORE PYTREE GENERATOR CLASS
+# ==============================================================================
+
+class PyTreeGenerator:
+    def __init__(self):
+        self.base_dir = os.path.dirname(os.path.abspath(__file__))
+        self.prompts_dir = os.path.join(self.base_dir, 'prompts')
+        
+        # Updated output directory for visualizations
+        self.vis_dir = os.path.abspath(os.path.join(self.base_dir, '..', 'generated_visualizations'))
+        os.makedirs(self.vis_dir, exist_ok=True)
+
+        self.system_prompt = self._load_prompt("system_prompt.txt")
+        
+        self.orin_ip = os.getenv("ORIN_IP", "172.101.1.117")
+        self.llm_client = openai.OpenAI(
+            api_key=os.getenv("OPENAI_API_KEY", "sk-no-key-required"),
+            base_url=f"http://{self.orin_ip}:8081/v1"
+        )
+
+        # --- ChromaDB Client Setup ---
+        vector_store_path = os.path.abspath(os.path.join(self.base_dir, '..', '..', 'tools', 'vector_store'))
+        self.chroma_client = chromadb.PersistentClient(path=vector_store_path)
+        
+        # Explicitly use the remote embedding function for queries
+        embedding_api_url = f"http://{self.orin_ip}:8090/v1/embeddings"
+        embedding_func = RemoteEmbeddingFunction(api_url=embedding_api_url)
+
+        self.collection = self.chroma_client.get_collection(
+            name="drone_docs",
+            embedding_function=embedding_func
+        )
+
+        allowed_actions, allowed_conditions = _parse_allowed_nodes_from_prompt(self.system_prompt)
+        self.schema = _generate_pytree_schema(allowed_actions, allowed_conditions)
+
+    def _load_prompt(self, file_name: str) -> str:
+        try:
+            with open(os.path.join(self.prompts_dir, file_name), 'r', encoding='utf-8') as f:
+                return f.read()
+        except FileNotFoundError:
+            logging.error(f"提示词文件未找到 -> {file_name}")
+            return ""
+
+    def _retrieve_context(self, query: str) -> Optional[str]:
+        logging.info("--- 开始从向量数据库检索上下文 ---")
+        try:
+            results = self.collection.query(query_texts=[query], n_results=5)
+            retrieved_docs = results.get("documents", [[]])[0]
+            if not retrieved_docs:
+                logging.warning("在向量数据库中没有找到相关的上下文信息。")
+                return None
+            context_str = "\n\n".join(retrieved_docs)
+            logging.info("--- 成功检索到上下文信息 ---")
+            return context_str
+        except Exception as e:
+            logging.error(f"从向量数据库检索时发生错误: {e}")
+            return None
+
+    async def generate(self, user_prompt: str) -> Dict[str, Any]:
+        """
+        Generates a py_tree.json structure based on the user's prompt.
+        """
+        logging.info(f"接收到用户请求: {user_prompt}")
+        
+        retrieved_context = self._retrieve_context(user_prompt)
+        
+        final_user_prompt = user_prompt
+        if retrieved_context:
+            augmentation = (
+                "\n\n---\n"
+                "参考知识：\n"
+                "以下是从知识库中检索到的、与当前任务最相关的信息，请优先参考这些信息来生成行为树：\n"
+                f"{retrieved_context}"
+                "\n---"
+            )
+            final_user_prompt += augmentation
+        else:
+            logging.warning("未检索到上下文或检索失败，将使用原始用户提示词。")
+
+        for attempt in range(3):
+            logging.info(f"--- 第 {attempt + 1}/3 次尝试生成Pytree ---")
+            try:
+                response = self.llm_client.chat.completions.create(
+                    model="local-model",
+                    messages=[
+                        {"role": "system", "content": self.system_prompt},
+                        {"role": "user", "content": final_user_prompt}
+                    ],
+                    temperature=0.1,
+                    response_format={"type": "json_object"}
+                )
+                pytree_str = response.choices[0].message.content
+                pytree_dict = json.loads(pytree_str)
+
+                if _validate_pytree_with_schema(pytree_dict, self.schema):
+                    logging.info("成功生成并验证了Pytree。")
+                    plan_id = str(uuid.uuid4())
+                    pytree_dict['plan_id'] = plan_id
+                    
+                    # Generate visualization to a static path
+                    vis_filename = "py_tree.png"
+                    vis_path = os.path.join(self.vis_dir, vis_filename)
+                    _visualize_pytree(pytree_dict['root'], os.path.splitext(vis_path)[0])
+                    pytree_dict['visualization_url'] = f"/static/{vis_filename}"
+
+                    return pytree_dict
+                else:
+                    logging.warning("生成的Pytree验证失败，正在重试...")
+
+            except (OpenAIError, json.JSONDecodeError) as e:
+                logging.error(f"生成Pytree时发生错误: {e}")
+        
+        raise RuntimeError("在3次尝试后，仍未能生成一个有效的Pytree。")
+
+# Create a single instance for the application
+py_tree_generator = PyTreeGenerator()

backend_service/src/ros2_client.py

@@ -0,0 +1,67 @@
+import rclpy
+from rclpy.action import ActionClient
+from rclpy.node import Node
+import json
+from typing import Dict, Any
+import logging
+
+from drone_interfaces.action import ExecuteMission
+from .websocket_manager import websocket_manager
+
+class MissionActionClient(Node):
+    """
+    Interfaces with the drone's `ExecuteMission` ROS2 Action Server.
+    """
+    def __init__(self):
+        super().__init__('mission_action_client')
+        self._action_client = ActionClient(self, ExecuteMission, 'execute_mission')
+        self.get_logger().info("MissionActionClient initialized.")
+
+    def send_goal(self, py_tree: Dict[str, Any]):
+        """
+        Sends the mission (py_tree) to the action server.
+        """
+        if not self._action_client.server_is_ready():
+            self.get_logger().error("Action server not available, goal not sent.")
+            # Optionally, you could broadcast a status update to the frontend here
+            return
+
+        self.get_logger().info("Received request to send goal to drone.")
+        goal_msg = ExecuteMission.Goal()
+        goal_msg.py_tree_json = json.dumps(py_tree)
+
+        self.get_logger().info(f"Sending goal to action server...")
+        send_goal_future = self._action_client.send_goal_async(
+            goal_msg,
+            feedback_callback=self.feedback_callback
+        )
+
+        send_goal_future.add_done_callback(self.goal_response_callback)
+
+    def goal_response_callback(self, future):
+        goal_handle = future.result()
+        if not goal_handle.accepted:
+            self.get_logger().info('Goal rejected :(')
+            return
+
+        self.get_logger().info('Goal accepted :)')
+
+        self._get_result_future = goal_handle.get_result_async()
+        self._get_result_future.add_done_callback(self.get_result_callback)
+
+    def get_result_callback(self, future):
+        result = future.result().result
+        self.get_logger().info(f'Result: {{success: {result.success}, message: {result.message}}}')
+        # Optionally, you can broadcast the final result via WebSocket here
+
+    def feedback_callback(self, feedback_msg):
+        """
+        This callback is triggered by the action server.
+        It forwards the status to the QGC plugin via the WebSocket manager in a thread-safe manner.
+        """
+        feedback = feedback_msg.feedback
+        feedback_payload = json.dumps({"node_id": feedback.node_id, "status": feedback.status})
+        self.get_logger().info(f"Received feedback: {feedback_payload}")
+        websocket_manager.broadcast(feedback_payload)
+
+# Note: The rclpy.init() and spinning of the node will be handled in main.py

backend_service/src/websocket_manager.py

@@ -0,0 +1,48 @@
+import asyncio
+from typing import List
+from fastapi import WebSocket
+import logging
+
+class ConnectionManager:
+    def __init__(self):
+        self.active_connections: List[WebSocket] = []
+        self.loop: asyncio.AbstractEventLoop | None = None
+
+    def set_loop(self, loop: asyncio.AbstractEventLoop):
+        """Sets the asyncio event loop."""
+        self.loop = loop
+
+    async def connect(self, websocket: WebSocket):
+        await websocket.accept()
+        self.active_connections.append(websocket)
+
+    def disconnect(self, websocket: WebSocket):
+        self.active_connections.remove(websocket)
+
+    def broadcast(self, message: str):
+        """
+        Thread-safely broadcasts a message to all active WebSocket connections.
+        This method is designed to be called from a different thread (e.g., a ROS2 callback).
+        """
+        if not self.loop:
+            logging.error("Event loop not set in ConnectionManager. Cannot broadcast.")
+            return
+
+        # Schedule the coroutine to be executed in the event loop
+        self.loop.call_soon_threadsafe(self._broadcast_in_loop, message)
+
+    def _broadcast_in_loop(self, message: str):
+        """
+        Helper to run the broadcast coroutine in the correct event loop.
+        """
+        asyncio.ensure_future(self._broadcast_async(message), loop=self.loop)
+
+    async def _broadcast_async(self, message: str):
+        """
+        The actual async method that sends messages.
+        """
+        tasks = [connection.send_text(message) for connection in self.active_connections]
+        await asyncio.gather(*tasks, return_exceptions=True)
+
+# Create a single instance of the manager to be used across the application
+websocket_manager = ConnectionManager()