add skills

.vscode/launch.json

@@ -9,7 +9,8 @@
             "console": "integratedTerminal",
             "cwd": "${workspaceFolder}",
             "envFile": "${workspaceFolder}/.env",
-            "python": "${workspaceFolder}/.venv/bin/python"
+            "python": "${workspaceFolder}/.venv/bin/python",
+            "justMyCode": false
         }
     ]
 }

agent/deep_assistant.py

@@ -4,6 +4,7 @@ import time
 from typing import Any, Dict
 from langchain.chat_models import init_chat_model
 # from deepagents import create_deep_agent
+from deepagents_cli.agent import create_cli_agent
 from langchain.agents import create_agent
 from langchain.agents.middleware import SummarizationMiddleware
 from langchain_mcp_adapters.client import MultiServerMCPClient
@@ -117,7 +118,6 @@ async def init_agent(config: AgentConfig):
 
     # 检测或使用指定的提供商
     model_provider,base_url = detect_provider(config.model_name, config.model_server)
-
     # 构建模型参数
     model_kwargs = {
         "model": config.model_name,
@@ -130,39 +130,48 @@ async def init_agent(config: AgentConfig):
         model_kwargs.update(config.generate_cfg)
     llm_instance = init_chat_model(**model_kwargs)
 
-    # 构建中间件列表
-    middleware = []
-    # 只有在 enable_thinking 为 True 时才添加 GuidelineMiddleware
-    if config.enable_thinking:
-        middleware.append(GuidelineMiddleware(llm_instance, config, system_prompt))
-
-    # 添加工具输出长度控制中间件
-    tool_output_middleware = ToolOutputLengthMiddleware(
-        max_length=getattr(config.generate_cfg, 'tool_output_max_length', None) if config.generate_cfg else None or TOOL_OUTPUT_MAX_LENGTH,
-        truncation_strategy=getattr(config.generate_cfg, 'tool_output_truncation_strategy', 'smart') if config.generate_cfg else 'smart',
-        tool_filters=getattr(config.generate_cfg, 'tool_output_filters', None) if config.generate_cfg else None,  # 可配置特定工具
-        exclude_tools=getattr(config.generate_cfg, 'tool_output_exclude', []) if config.generate_cfg else [],  # 排除的工具
-        preserve_code_blocks=getattr(config.generate_cfg, 'preserve_code_blocks', True) if config.generate_cfg else True,
-        preserve_json=getattr(config.generate_cfg, 'preserve_json', True) if config.generate_cfg else True
-    )
-    middleware.append(tool_output_middleware)
-
-    if checkpointer:
-        summarization_middleware = SummarizationMiddleware(
+    if config.robot_type == "deep_agent":
+        # 使用 DeepAgentX 创建 agent
+        agent, composite_backend = create_cli_agent(
             model=llm_instance,
-            max_tokens_before_summary=SUMMARIZATION_MAX_TOKENS,
-            messages_to_keep=20,  # 摘要后保留最近 20 条消息
-            summary_prompt="请简洁地总结以上对话的要点，包括重要的用户信息、讨论过的话题和关键结论。"
+            assistant_id=config.bot_id,
+            tools=mcp_tools,
+            auto_approve=True,
         )
-        middleware.append(summarization_middleware)
+    else:
+        # 构建中间件列表
+        middleware = []
+        # 只有在 enable_thinking 为 True 时才添加 GuidelineMiddleware
+        if config.enable_thinking:
+            middleware.append(GuidelineMiddleware(llm_instance, config, system_prompt))
 
-    agent = create_agent(
-        model=llm_instance,
-        system_prompt=system_prompt,
-        tools=mcp_tools,
-        middleware=middleware,
-        checkpointer=checkpointer  # 传入 checkpointer 以启用持久化
-    )
+        # 添加工具输出长度控制中间件
+        tool_output_middleware = ToolOutputLengthMiddleware(
+            max_length=getattr(config.generate_cfg, 'tool_output_max_length', None) if config.generate_cfg else None or TOOL_OUTPUT_MAX_LENGTH,
+            truncation_strategy=getattr(config.generate_cfg, 'tool_output_truncation_strategy', 'smart') if config.generate_cfg else 'smart',
+            tool_filters=getattr(config.generate_cfg, 'tool_output_filters', None) if config.generate_cfg else None,  # 可配置特定工具
+            exclude_tools=getattr(config.generate_cfg, 'tool_output_exclude', []) if config.generate_cfg else [],  # 排除的工具
+            preserve_code_blocks=getattr(config.generate_cfg, 'preserve_code_blocks', True) if config.generate_cfg else True,
+            preserve_json=getattr(config.generate_cfg, 'preserve_json', True) if config.generate_cfg else True
+        )
+        middleware.append(tool_output_middleware)
+
+        if checkpointer:
+            summarization_middleware = SummarizationMiddleware(
+                model=llm_instance,
+                max_tokens_before_summary=SUMMARIZATION_MAX_TOKENS,
+                messages_to_keep=20,  # 摘要后保留最近 20 条消息
+                summary_prompt="请简洁地总结以上对话的要点，包括重要的用户信息、讨论过的话题和关键结论。"
+            )
+            middleware.append(summarization_middleware)
+
+        agent = create_agent(
+            model=llm_instance,
+            system_prompt=system_prompt,
+            tools=mcp_tools,
+            middleware=middleware,
+            checkpointer=checkpointer  # 传入 checkpointer 以启用持久化
+        )
     
     # 如果有缓存键，将 agent 加入缓存
     if cache_key:

agent/prompt_loader.py

@@ -98,7 +98,9 @@ async def load_system_prompt_async(project_dir: str, language: str = None, syste
     datetime_str = format_datetime_by_language(language) if language else format_datetime_by_language('en')
 
     # 如果存在{language} 占位符，那么就直接使用 system_prompt
-    if robot_type == "general_agent" or robot_type == "catalog_agent":
+    if robot_type == "deep_agent":
+        return None
+    elif robot_type == "general_agent" or robot_type == "catalog_agent":
         """
         优先使用项目目录的README.md，没有才使用默认的system_prompt_{robot_type}.md
         """

fastapi_app.py

@@ -12,7 +12,7 @@ from fastapi.middleware.cors import CORSMiddleware
 from routes.file_manager import router as file_manager_router
 import logging
 
-
+from utils.symlink_utils import setup_project_directories
 from utils.log_util.logger import init_with_fastapi
 
 
@@ -25,6 +25,9 @@ init_with_fastapi(app)
 
 logger = logging.getLogger('app')
 
+# Setup project directories and symbolic links
+setup_project_directories()
+
 # 挂载public文件夹为静态文件服务
 app.mount("/public", StaticFiles(directory="public"), name="static")
 

prompt/wowtalk.md

@@ -98,8 +98,18 @@
         - 如果用户未指定具体设备或房间，但使用了"这个设备"、"那个房间"、"它"等指代词，需要从最近的聊天记录中推断对应的设备或房间
         - 优先考虑最近一次查询的设备信息（如最近查询的房间设备、设备ID等）
         - 如果上下文中有多台设备，需要向用户确认具体操作哪台设备
-    2.  **若用户已明确确认**：直接调用【设备控制】工具执行操作。
-    3.  **若用户未确认且为新请求**：向用户发送确认提示："即将为您 [操作内容] [设备名称] [具体参数]，是否确认？"，待用户确认后再执行。
+    2.  **空调温度调节确认方式**：
+        - 如果用户说"有点热"、"调低点"、"太热了"等，表示要降温：
+            1. 先查询当前室温
+            2. 默认将温度调低1度（当前温度-1度）
+            3. 回复格式："现在室温xx度，调整到xx度可以吗？"
+        - 如果用户说"有点冷"、"调高点"、"太冷了"等，表示要升温：
+            1. 先查询当前室温
+            2. 默认将温度调高1度（当前温度+1度）
+            3. 回复格式："现在室温xx度，调整到xx度可以吗？"
+        - 如果用户指定了具体温度（如"调到25度"），直接使用指定温度
+    3.  **若用户已明确确认**：直接调用【设备控制】工具执行操作。
+    4.  **若用户未确认且为新请求**：向用户发送确认提示："即将为您 [操作内容] [设备名称] [具体参数]，是否确认？"，待用户确认后再执行。
 
 4. 查询人员信息/wowtalk账号/人员位置
 -   **条件**：用户意图为查找某人、员工、同事或房间位置。

pyproject.toml

@@ -27,11 +27,12 @@ dependencies = [
     "chardet>=5.0.0",
     "psutil (>=7.1.3,<8.0.0)",
     "uvloop (>=0.22.1,<0.23.0)",
-    "deepagents (>=0.3.0,<0.4.0)",
+    "deepagents (>=0.2.8,<0.4.0)",
     "langchain-mcp-adapters (>=0.2.1,<0.3.0)",
     "langchain-openai (>=1.1.1,<2.0.0)",
     "cachetools (>=6.2.4,<7.0.0)",
     "langgraph-checkpoint-sqlite (>=3.0.1,<4.0.0)",
+    "deepagents-cli (>=0.0.11,<0.0.12)",
 ]
 
 [tool.poetry.requires-plugins]

utils/__init__.py

@@ -84,6 +84,11 @@ from .multi_project_manager import (
     generate_robot_readme
 )
 
+from .symlink_utils import (
+    setup_deepagents_symlink,
+    setup_project_directories
+)
+
 __all__ = [
     # file_utils
     'download_file',
@@ -152,4 +157,8 @@ __all__ = [
     'get_unique_folder_name',
     'copy_dataset_folder',
     'generate_robot_readme',
+
+    # symlink_utils
+    'setup_deepagents_symlink',
+    'setup_project_directories',
 ]

utils/fastapi_utils.py

@@ -367,7 +367,8 @@ def format_messages_to_chat_history(messages: List[Dict[str, str]]) -> str:
 def create_project_directory(dataset_ids: Optional[List[str]], bot_id: str, robot_type: str = "general_agent") -> Optional[str]:
     """创建项目目录的公共逻辑"""
     # 只有当 robot_type == "catalog_agent" 且 dataset_ids 不为空时才创建目录
-    if robot_type != "catalog_agent" or not dataset_ids or len(dataset_ids) == 0:
+    
+    if robot_type == "general_agent":
         return None
 
     try:

utils/symlink_utils.py

@@ -0,0 +1,95 @@
+#!/usr/bin/env python3
+"""
+Utilities for managing symbolic links and directory setup.
+"""
+
+import os
+import logging
+from pathlib import Path
+
+logger = logging.getLogger(__name__)
+
+
+def setup_deepagents_symlink():
+    """
+    Create a symbolic link from projects/robot to ~/.deepagents
+    if it doesn't already exist.
+    """
+    try:
+        # Get paths
+        project_root = Path(__file__).parent.parent
+        robot_dir = project_root / "projects" / "robot"
+        deepagents_dir = Path.home() / ".deepagents"
+
+        # Create robot directory if it doesn't exist
+        robot_dir.mkdir(parents=True, exist_ok=True)
+
+        # If ~/.deepagents already exists and is not a symlink, backup and remove it
+        if deepagents_dir.exists() and not deepagents_dir.is_symlink():
+            backup_dir = deepagents_dir.parent / f"{deepagents_dir.name}.backup"
+            logger.warning(f"~/.deepagents directory exists but is not a symlink.")
+            logger.warning(f"Creating backup at {backup_dir}")
+
+            try:
+                # Create backup
+                import shutil
+                if backup_dir.exists():
+                    shutil.rmtree(backup_dir)
+                shutil.move(str(deepagents_dir), str(backup_dir))
+                logger.info(f"Successfully backed up existing directory to {backup_dir}")
+            except Exception as backup_error:
+                logger.error(f"Failed to backup existing directory: {backup_error}")
+                logger.error("Please manually remove or backup ~/.deepagents to proceed")
+                return False
+
+        # If ~/.deepagents is already a symlink pointing to the right place, do nothing
+        if deepagents_dir.is_symlink():
+            target = deepagents_dir.resolve()
+            if target == robot_dir.resolve():
+                logger.info(f"~/.deepagents already points to {robot_dir}")
+                return True
+            else:
+                # Remove existing symlink pointing elsewhere
+                deepagents_dir.unlink()
+                logger.info(f"Removed existing symlink pointing to {target}")
+
+        # Create the symbolic link
+        os.symlink(robot_dir, deepagents_dir, target_is_directory=True)
+        logger.info(f"Created symbolic link: {deepagents_dir} -> {robot_dir}")
+        return True
+
+    except Exception as e:
+        logger.error(f"Failed to create symbolic link: {e}")
+        return False
+
+
+def setup_project_directories():
+    """
+    Set up all necessary directories and symbolic links for the project.
+    """
+    logger.info("Setting up project directories...")
+
+    # Setup ~/.deepagents symlink
+    symlink_success = setup_deepagents_symlink()
+
+    if symlink_success:
+        logger.info("Project directories setup completed successfully")
+    else:
+        logger.warning("Project directories setup completed with warnings")
+
+    return symlink_success
+
+
+if __name__ == "__main__":
+    # Set up basic logging for standalone testing
+    logging.basicConfig(
+        level=logging.INFO,
+        format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+    )
+
+    # Test the function
+    success = setup_deepagents_symlink()
+    if success:
+        print("✅ Symbolic link setup successful")
+    else:
+        print("❌ Symbolic link setup failed")