添加环境变量

agent/agent_config.py

@@ -31,6 +31,7 @@ class AgentConfig:
     user_identifier: Optional[str] = None
     session_id: Optional[str] = None
     dataset_ids: Optional[List[str]] = field(default_factory=list)
+    trace_id: Optional[str] = None  # 请求追踪ID，从 X-Request-ID header 获取
 
     # 响应控制参数
     stream: bool = False
@@ -72,6 +73,7 @@ class AgentConfig:
             'messages': self.messages,
             'enable_memori': self.enable_memori,
             'memori_semantic_search_top_k': self.memori_semantic_search_top_k,
+            'trace_id': self.trace_id,
         }
         
     def safe_print(self):
@@ -93,10 +95,18 @@ class AgentConfig:
         )
         from .checkpoint_utils import prepare_checkpoint_message
         from .checkpoint_manager import get_checkpointer_manager
+        from utils.log_util.context import g
 
         if messages is None:
             messages = []
 
+        # 从全局上下文获取 trace_id
+        trace_id = None
+        try:
+            trace_id = getattr(g, 'trace_id', None)
+        except LookupError:
+            pass
+
         robot_type = request.robot_type
         if robot_type == "catalog_agent":
             robot_type = "deep_agent"
@@ -130,6 +140,7 @@ class AgentConfig:
             dataset_ids=request.dataset_ids,
             enable_memori=enable_memori,
             memori_semantic_search_top_k=getattr(request, 'memori_semantic_search_top_k', None) or MEM0_SEMANTIC_SEARCH_TOP_K,
+            trace_id=trace_id,
         )
 
         # 在创建 config 时尽早准备 checkpoint 消息
@@ -158,9 +169,17 @@ class AgentConfig:
         )
         from .checkpoint_utils import prepare_checkpoint_message
         from .checkpoint_manager import get_checkpointer_manager
+        from utils.log_util.context import g
 
         if messages is None:
             messages = []
+
+        # 从全局上下文获取 trace_id
+        trace_id = None
+        try:
+            trace_id = getattr(g, 'trace_id', None)
+        except LookupError:
+            pass
         language = request.language or bot_config.get("language", "zh")
         preamble_text, system_prompt = get_preamble_text(language, bot_config.get("system_prompt"))
         robot_type = bot_config.get("robot_type", "general_agent")
@@ -194,6 +213,7 @@ class AgentConfig:
             dataset_ids=bot_config.get("dataset_ids", []),  # 从后端配置获取dataset_ids
             enable_memori=enable_memori,
             memori_semantic_search_top_k=bot_config.get("memori_semantic_search_top_k", MEM0_SEMANTIC_SEARCH_TOP_K),
+            trace_id=trace_id,
         )
 
         # 在创建 config 时尽早准备 checkpoint 消息

agent/deep_assistant.py

@@ -137,7 +137,7 @@ async def init_agent(config: AgentConfig):
 
     # 加载配置
     final_system_prompt = await load_system_prompt_async(
-        config.project_dir, config.language, config.system_prompt, config.robot_type, config.bot_id, config.user_identifier
+        config.project_dir, config.language, config.system_prompt, config.robot_type, config.bot_id, config.user_identifier, config.trace_id or ""
     )
     final_mcp_settings = await load_mcp_settings_async(
         config.project_dir, config.mcp_settings, config.bot_id, config.robot_type
@@ -240,7 +240,11 @@ async def init_agent(config: AgentConfig):
             enable_memory=False,
             workspace_root=workspace_root,
             middleware=middleware,
-            checkpointer=checkpointer
+            checkpointer=checkpointer,
+            shell_env={
+              "ASSISTANT_ID": config.bot_id,
+              "TRACE_ID": config.trace_id
+            }
         )
     else:
         # 只有在 enable_thinking 为 True 时才添加 GuidelineMiddleware
@@ -369,6 +373,7 @@ def create_custom_cli_agent(
     workspace_root: str | None = None,
     checkpointer: Checkpointer | None = None,
     store: BaseStore | None = None,
+    shell_env: dict[str, str] | None = None,
 ) -> tuple[Pregel, CompositeBackend]:
     """Create a CLI-configured agent with custom workspace_root for shell commands.
 
@@ -393,6 +398,8 @@ def create_custom_cli_agent(
         workspace_root: Working directory for shell commands. If None, uses Path.cwd().
         checkpointer: Optional checkpointer for persisting conversation state
         store: Optional BaseStore for persisting user preferences and agent memory
+        shell_env: Optional custom environment variables to pass to ShellMiddleware.
+                   These will be merged with os.environ. Custom vars take precedence.
 
     Returns:
         2-tuple of (agent_graph, composite_backend)
@@ -440,15 +447,18 @@ def create_custom_cli_agent(
         # Add shell middleware (only in local mode)
         if enable_shell:
             # Create environment for shell commands
-            # Restore user's original LANGSMITH_PROJECT so their code traces separately
-            shell_env = os.environ.copy()
+            # Start with a copy of current environment
+            final_shell_env = os.environ.copy()
+            # Merge custom environment variables if provided (custom vars take precedence)
+            if shell_env:
+                final_shell_env.update(shell_env)
             # Use custom workspace_root if provided, otherwise use current directory
             shell_workspace = workspace_root if workspace_root is not None else str(Path.cwd())
 
             agent_middleware.append(
                 ShellMiddleware(
                     workspace_root=shell_workspace,
-                    env=shell_env,
+                    env=final_shell_env,
                 )
             )
     else:

agent/prompt_loader.py

@@ -69,7 +69,7 @@ def format_datetime_by_language(language: str) -> str:
             return utc_now.strftime("%Y-%m-%d %H:%M:%S") + " UTC"
 
 
-async def load_system_prompt_async(project_dir: str, language: str = None, system_prompt: str=None, robot_type: str = "general_agent", bot_id: str="", user_identifier: str = "") -> str:
+async def load_system_prompt_async(project_dir: str, language: str = None, system_prompt: str=None, robot_type: str = "general_agent", bot_id: str="", user_identifier: str = "", trace_id: str = "") -> str:
     """异步版本的系统prompt加载
 
     Args:
@@ -79,6 +79,7 @@ async def load_system_prompt_async(project_dir: str, language: str = None, syste
         robot_type: 机器人类型，取值 agent/catalog_agent
         bot_id: 机器人ID
         user_identifier: 用户标识符
+        trace_id: 请求追踪ID，用于日志追踪
 
     Returns:
         str: 加载到的系统提示词内容
@@ -127,7 +128,8 @@ async def load_system_prompt_async(project_dir: str, language: str = None, syste
             language=language_display,
             user_identifier=user_identifier,
             datetime=datetime_str,
-            agent_dir_path="."
+            agent_dir_path=".",
+            trace_id=trace_id or ""
         )
     elif system_prompt:
         prompt = system_prompt.format(language=language_display, user_identifier=user_identifier, datetime=datetime_str)

prompt/system_prompt_deep_agent.md

@@ -47,7 +47,7 @@ When executing scripts from SKILL.md files, you MUST convert relative paths to a
 
 - **`{agent_dir_path}/skills/`** - Skill packages with embedded scripts
 - **`{agent_dir_path}/dataset/`** - Store file datasets and document data
-- **`{agent_dir_path}/scripts/`** - Place generated executable scripts here (not skill scripts)
+- **`{agent_dir_path}/executable_code/`** - Place generated executable scripts here (not skill scripts)
 - **`{agent_dir_path}/download/`** - Store downloaded files and content
 
 **Path Examples:**