Add pre commit (#26)

deep_research/agent_deep_research/deep_research_agent.py

@@ -1,35 +1,46 @@
 # -*- coding: utf-8 -*-
 """Deep Research Agent"""
 # pylint: disable=too-many-lines, no-name-in-module
-import asyncio
-import json
 import os
-from copy import deepcopy
+import json
+import asyncio
+
+from typing import Type, Optional, Any, Tuple
 from datetime import datetime
-from typing import Any, Optional, Tuple, Type
+from copy import deepcopy
 
 import shortuuid
-from agentscope import logger, setup_logger
-from agentscope.agent import ReActAgent
-from agentscope.formatter import FormatterBase
-from agentscope.mcp import StatefulClientBase
-from agentscope.memory import MemoryBase
-from agentscope.message import Msg, TextBlock, ToolResultBlock, ToolUseBlock
-from agentscope.model import ChatModelBase
-from agentscope.tool import ToolResponse, view_text_file, write_text_file
+
 from pydantic import BaseModel
 
-from ..agent_deep_research.utils import (
-    get_dynamic_tool_call_json,
-    get_structure_output,
-    load_prompt_dict,
-    truncate_search_result,
-)
-from .built_in_prompt.promptmodule import (
-    FollowupJudge,
-    ReflectFailure,
+from built_in_prompt.promptmodule import (
     SubtasksDecomposition,
     WebExtraction,
+    FollowupJudge,
+    ReflectFailure,
+)
+from utils import (
+    truncate_search_result,
+    load_prompt_dict,
+    get_dynamic_tool_call_json,
+    get_structure_output,
+)
+from agentscope import logger, setup_logger
+from agentscope.mcp import StatefulClientBase
+from agentscope.agent import ReActAgent
+from agentscope.model import ChatModelBase
+from agentscope.formatter import FormatterBase
+from agentscope.memory import MemoryBase
+from agentscope.tool import (
+    ToolResponse,
+    view_text_file,
+    write_text_file,
+)
+from agentscope.message import (
+    Msg,
+    ToolUseBlock,
+    TextBlock,
+    ToolResultBlock,
 )
 
 _DEEP_RESEARCH_AGENT_DEFAULT_SYS_PROMPT = "You're a helpful assistant."
@@ -149,7 +160,7 @@ class DeepResearchAgent(ReActAgent):
         # register all necessary tools for deep research agent
         self.toolkit.register_tool_function(view_text_file)
         self.toolkit.register_tool_function(write_text_file)
-        asyncio.create_task(
+        asyncio.get_running_loop().create_task(
             self.toolkit.register_mcp_client(search_mcp_client),
         )
 
@@ -213,16 +224,12 @@ class DeepResearchAgent(ReActAgent):
             reasoning_prompt = self.prompt_dict["reasoning_prompt"].format_map(
                 {
                     "objective": self.current_subtask[-1].objective,
-                    "meta_planner_agent": (
-                        cur_plan
-                        if cur_plan
-                        else "There is no working meta_planner_agent now."
-                    ),
-                    "knowledge_gap": (
-                        f"## Knowledge Gaps:\n {cur_know_gap}"
-                        if cur_know_gap
-                        else ""
-                    ),
+                    "plan": cur_plan
+                    if cur_plan
+                    else "There is no working plan now.",
+                    "knowledge_gap": f"## Knowledge Gaps:\n {cur_know_gap}"
+                    if cur_know_gap
+                    else "",
                     "depth": len(self.current_subtask),
                 },
             )
@@ -300,7 +307,9 @@ class DeepResearchAgent(ReActAgent):
             # Async generator handling
             async for chunk in tool_res:
                 # Turn into a tool result block
-                tool_res_msg.content[0]["output"] = chunk.content  # type: ignore[index]
+                tool_res_msg.content[0][  # type: ignore[index]
+                    "output"
+                ] = chunk.content
 
                 # Skip the printing of the finish function call
                 if (
@@ -488,13 +497,14 @@ class DeepResearchAgent(ReActAgent):
 
     async def decompose_and_expand_subtask(self) -> ToolResponse:
         """Identify the knowledge gaps of the current subtask and generate a
-        working meta_planner_agent by subtask decomposition. The working meta_planner_agent includes
+        working meta_planner_agent by subtask decomposition.
+        The working meta_planner_agent includes
         necessary steps for task completion and expanded steps.
 
         Returns:
             ToolResponse:
-                The knowledge gaps and working meta_planner_agent of the current subtask
-                in JSON format.
+                The knowledge gaps and working meta_planner_agent
+                of the current subtask in JSON format.
         """
         if len(self.current_subtask) <= self.max_depth:
             decompose_sys_prompt = self.prompt_dict["decompose_sys_prompt"]
@@ -947,7 +957,8 @@ class DeepResearchAgent(ReActAgent):
 
         Returns:
             ToolResponse:
-                The reflection about meta_planner_agent rephrasing and subtask decomposition.
+                The reflection about meta_planner_agent
+                rephrasing and subtask decomposition.
         """
         reflect_sys_prompt = self.prompt_dict["reflect_sys_prompt"]
         conversation_history = ""