refactor: extract tool execution loop from chat task main
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3402375710
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@ -125,6 +125,7 @@ from .chat_flow_runtime import (
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from .chat_flow_pending_writes import finalize_pending_append, finalize_pending_modify
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from .chat_flow_task_support import process_sub_agent_updates, wait_retry_delay, cancel_pending_tools
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from .chat_flow_tool_loop import execute_tool_calls
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async def handle_task_with_sender(terminal: WebTerminal, workspace: UserWorkspace, message, images, sender, client_sid, username: str, videos=None):
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"""处理任务并发送消息 - 集成token统计版本"""
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@ -1151,396 +1152,30 @@ async def handle_task_with_sender(terminal: WebTerminal, workspace: UserWorkspac
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consecutive_same_tool[tool_name] = 1
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last_tool_name = tool_name
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# 更新统计
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total_tool_calls += len(tool_calls)
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# 执行每个工具
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for tool_call in tool_calls:
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# 检查停止标志
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client_stop_info = get_stop_flag(client_sid, username)
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if client_stop_info:
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stop_requested = client_stop_info.get('stop', False) if isinstance(client_stop_info, dict) else client_stop_info
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if stop_requested:
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debug_log("在工具调用过程中检测到停止状态")
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tool_call_id = tool_call.get("id")
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function_name = tool_call.get("function", {}).get("name")
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# 通知前端该工具已被取消，避免界面卡住
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sender('update_action', {
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'preparing_id': tool_call_id,
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'status': 'cancelled',
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'result': {
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"success": False,
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"status": "cancelled",
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"message": "命令执行被用户取消",
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"tool": function_name
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}
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})
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# 在消息列表中记录取消结果，防止重新加载时仍显示运行中
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if tool_call_id:
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messages.append({
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"role": "tool",
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"tool_call_id": tool_call_id,
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"name": function_name,
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"content": "命令执行被用户取消",
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"metadata": {"status": "cancelled"}
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})
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sender('task_stopped', {
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'message': '命令执行被用户取消',
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'reason': 'user_stop'
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})
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clear_stop_flag(client_sid, username)
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return
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# 工具调用间隔控制
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current_time = time.time()
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if last_tool_call_time > 0:
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elapsed = current_time - last_tool_call_time
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if elapsed < TOOL_CALL_COOLDOWN:
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await asyncio.sleep(TOOL_CALL_COOLDOWN - elapsed)
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last_tool_call_time = time.time()
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function_name = tool_call["function"]["name"]
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arguments_str = tool_call["function"]["arguments"]
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tool_call_id = tool_call["id"]
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debug_log(f"准备解析JSON，工具: {function_name}, 参数长度: {len(arguments_str)}")
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debug_log(f"JSON参数前200字符: {arguments_str[:200]}")
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debug_log(f"JSON参数后200字符: {arguments_str[-200:]}")
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# 使用改进的参数解析方法
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if hasattr(web_terminal, 'api_client') and hasattr(web_terminal.api_client, '_safe_tool_arguments_parse'):
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success, arguments, error_msg = web_terminal.api_client._safe_tool_arguments_parse(arguments_str, function_name)
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if not success:
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debug_log(f"安全解析失败: {error_msg}")
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error_text = f'工具参数解析失败: {error_msg}'
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error_payload = {
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"success": False,
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"error": error_text,
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"error_type": "parameter_format_error",
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"tool_name": function_name,
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"tool_call_id": tool_call_id,
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"message": error_text
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}
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sender('error', {'message': error_text})
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sender('update_action', {
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'preparing_id': tool_call_id,
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'status': 'completed',
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'result': error_payload,
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'message': error_text
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})
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error_content = json.dumps(error_payload, ensure_ascii=False)
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web_terminal.context_manager.add_conversation(
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"tool",
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error_content,
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tool_call_id=tool_call_id,
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name=function_name
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)
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messages.append({
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"role": "tool",
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"tool_call_id": tool_call_id,
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"name": function_name,
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"content": error_content
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})
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continue
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debug_log(f"使用安全解析成功，参数键: {list(arguments.keys())}")
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else:
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# 回退到带有基本修复逻辑的解析
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try:
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arguments = json.loads(arguments_str) if arguments_str.strip() else {}
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debug_log(f"直接JSON解析成功，参数键: {list(arguments.keys())}")
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except json.JSONDecodeError as e:
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debug_log(f"原始JSON解析失败: {e}")
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# 尝试基本的JSON修复
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repaired_str = arguments_str.strip()
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repair_attempts = []
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# 修复1: 未闭合字符串
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if repaired_str.count('"') % 2 == 1:
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repaired_str += '"'
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repair_attempts.append("添加闭合引号")
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# 修复2: 未闭合JSON对象
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if repaired_str.startswith('{') and not repaired_str.rstrip().endswith('}'):
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repaired_str = repaired_str.rstrip() + '}'
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repair_attempts.append("添加闭合括号")
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# 修复3: 截断的JSON（移除不完整的最后一个键值对）
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if not repair_attempts: # 如果前面的修复都没用上
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last_comma = repaired_str.rfind(',')
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if last_comma > 0:
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repaired_str = repaired_str[:last_comma] + '}'
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repair_attempts.append("移除不完整的键值对")
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# 尝试解析修复后的JSON
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try:
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arguments = json.loads(repaired_str)
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debug_log(f"JSON修复成功: {', '.join(repair_attempts)}")
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debug_log(f"修复后参数键: {list(arguments.keys())}")
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except json.JSONDecodeError as repair_error:
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debug_log(f"JSON修复也失败: {repair_error}")
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debug_log(f"修复尝试: {repair_attempts}")
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debug_log(f"修复后内容前100字符: {repaired_str[:100]}")
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error_text = f'工具参数解析失败: {e}'
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error_payload = {
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"success": False,
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"error": error_text,
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"error_type": "parameter_format_error",
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"tool_name": function_name,
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"tool_call_id": tool_call_id,
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"message": error_text
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}
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sender('error', {'message': error_text})
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sender('update_action', {
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'preparing_id': tool_call_id,
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'status': 'completed',
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'result': error_payload,
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'message': error_text
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})
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error_content = json.dumps(error_payload, ensure_ascii=False)
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web_terminal.context_manager.add_conversation(
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"tool",
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error_content,
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tool_call_id=tool_call_id,
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name=function_name
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)
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messages.append({
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"role": "tool",
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"tool_call_id": tool_call_id,
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"name": function_name,
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"content": error_content
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})
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continue
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debug_log(f"执行工具: {function_name} (ID: {tool_call_id})")
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# 发送工具开始事件
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tool_display_id = f"tool_{iteration}_{function_name}_{time.time()}"
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monitor_snapshot = None
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snapshot_path = None
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memory_snapshot_type = None
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if function_name in MONITOR_FILE_TOOLS:
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snapshot_path = resolve_monitor_path(arguments)
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monitor_snapshot = capture_monitor_snapshot(web_terminal.file_manager, snapshot_path, MONITOR_SNAPSHOT_CHAR_LIMIT, debug_log)
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if monitor_snapshot:
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cache_monitor_snapshot(tool_display_id, 'before', monitor_snapshot)
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elif function_name in MONITOR_MEMORY_TOOLS:
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memory_snapshot_type = (arguments.get('memory_type') or 'main').lower()
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before_entries = None
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try:
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before_entries = resolve_monitor_memory(web_terminal.memory_manager._read_entries(memory_snapshot_type), MONITOR_MEMORY_ENTRY_LIMIT)
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except Exception as exc:
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debug_log(f"[MonitorSnapshot] 读取记忆失败: {memory_snapshot_type} ({exc})")
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if before_entries is not None:
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monitor_snapshot = {
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'memory_type': memory_snapshot_type,
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'entries': before_entries
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}
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cache_monitor_snapshot(tool_display_id, 'before', monitor_snapshot)
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sender('tool_start', {
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'id': tool_display_id,
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'name': function_name,
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'arguments': arguments,
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'preparing_id': tool_call_id,
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'monitor_snapshot': monitor_snapshot,
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'conversation_id': conversation_id
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})
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brief_log(f"调用了工具: {function_name}")
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await asyncio.sleep(0.3)
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start_time = time.time()
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# 执行工具
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tool_result = await web_terminal.handle_tool_call(function_name, arguments)
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debug_log(f"工具结果: {tool_result[:200]}...")
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execution_time = time.time() - start_time
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if execution_time < 1.5:
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await asyncio.sleep(1.5 - execution_time)
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# 更新工具状态
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result_data = {}
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try:
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result_data = json.loads(tool_result)
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except:
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result_data = {'output': tool_result}
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tool_failed = detect_tool_failure(result_data)
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action_status = 'completed'
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action_message = None
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awaiting_flag = False
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if function_name in {"write_file", "edit_file"}:
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diff_path = result_data.get("path") or arguments.get("file_path")
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summary = result_data.get("summary") or result_data.get("message")
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if summary:
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action_message = summary
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debug_log(f"{function_name} 执行完成: {summary or '无摘要'}")
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if function_name == "wait_sub_agent":
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system_msg = result_data.get("system_message")
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if system_msg:
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messages.append({
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"role": "system",
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"content": system_msg
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})
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sender('system_message', {
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'content': system_msg,
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'inline': False
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})
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maybe_mark_failure_from_message(web_terminal, system_msg)
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monitor_snapshot_after = None
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if function_name in MONITOR_FILE_TOOLS:
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result_path = None
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if isinstance(result_data, dict):
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result_path = resolve_monitor_path(result_data)
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if not result_path:
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candidate_path = result_data.get('path')
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if isinstance(candidate_path, str) and candidate_path.strip():
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result_path = candidate_path.strip()
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if not result_path:
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result_path = resolve_monitor_path(arguments, snapshot_path) or snapshot_path
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monitor_snapshot_after = capture_monitor_snapshot(web_terminal.file_manager, result_path, MONITOR_SNAPSHOT_CHAR_LIMIT, debug_log)
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elif function_name in MONITOR_MEMORY_TOOLS:
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memory_after_type = str(
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arguments.get('memory_type')
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or (isinstance(result_data, dict) and result_data.get('memory_type'))
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or memory_snapshot_type
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or 'main'
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).lower()
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after_entries = None
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try:
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after_entries = resolve_monitor_memory(web_terminal.memory_manager._read_entries(memory_after_type), MONITOR_MEMORY_ENTRY_LIMIT)
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except Exception as exc:
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debug_log(f"[MonitorSnapshot] 读取记忆失败(after): {memory_after_type} ({exc})")
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if after_entries is not None:
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monitor_snapshot_after = {
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'memory_type': memory_after_type,
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'entries': after_entries
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}
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update_payload = {
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'id': tool_display_id,
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'status': action_status,
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'result': result_data,
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'preparing_id': tool_call_id,
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'conversation_id': conversation_id
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}
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if action_message:
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update_payload['message'] = action_message
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if awaiting_flag:
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update_payload['awaiting_content'] = True
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if monitor_snapshot_after:
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update_payload['monitor_snapshot_after'] = monitor_snapshot_after
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cache_monitor_snapshot(tool_display_id, 'after', monitor_snapshot_after)
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sender('update_action', update_payload)
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if function_name in ['create_file', 'delete_file', 'rename_file', 'create_folder']:
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if not web_terminal.context_manager._is_host_mode_without_safety():
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structure = web_terminal.context_manager.get_project_structure()
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sender('file_tree_update', structure)
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# ===== 增量保存：立即保存工具结果 =====
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metadata_payload = None
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tool_images = None
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tool_videos = None
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if isinstance(result_data, dict):
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# 特殊处理 web_search：保留可供前端渲染的精简结构，以便历史记录复现搜索结果
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if function_name == "web_search":
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try:
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tool_result_content = json.dumps(compact_web_search_result(result_data), ensure_ascii=False)
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except Exception:
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tool_result_content = tool_result
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else:
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tool_result_content = format_tool_result_for_context(function_name, result_data, tool_result)
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metadata_payload = {"tool_payload": result_data}
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else:
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tool_result_content = tool_result
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tool_message_content = tool_result_content
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# view_image: 将图片直接附加到 tool 结果中（不再插入 user 消息）
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if function_name == "view_image" and getattr(web_terminal, "pending_image_view", None):
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inj = web_terminal.pending_image_view
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web_terminal.pending_image_view = None
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if (
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not tool_failed
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and isinstance(result_data, dict)
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and result_data.get("success") is not False
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):
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img_path = inj.get("path") if isinstance(inj, dict) else None
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if img_path:
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text_part = tool_result_content if isinstance(tool_result_content, str) else ""
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tool_message_content = web_terminal.context_manager._build_content_with_images(
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text_part,
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[img_path]
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)
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tool_images = [img_path]
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if metadata_payload is None:
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metadata_payload = {}
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metadata_payload["tool_image_path"] = img_path
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sender('system_message', {
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'content': f'系统已按模型请求将图片附加到工具结果: {img_path}'
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})
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# view_video: 将视频直接附加到 tool 结果中（不再插入 user 消息）
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if function_name == "view_video" and getattr(web_terminal, "pending_video_view", None):
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inj = web_terminal.pending_video_view
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web_terminal.pending_video_view = None
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if (
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not tool_failed
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and isinstance(result_data, dict)
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and result_data.get("success") is not False
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):
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video_path = inj.get("path") if isinstance(inj, dict) else None
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if video_path:
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text_part = tool_result_content if isinstance(tool_result_content, str) else ""
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video_payload = [video_path]
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tool_message_content = web_terminal.context_manager._build_content_with_images(
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text_part,
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[],
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video_payload
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)
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tool_videos = [video_path]
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if metadata_payload is None:
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metadata_payload = {}
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metadata_payload["tool_video_path"] = video_path
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sender('system_message', {
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'content': f'系统已按模型请求将视频附加到工具结果: {video_path}'
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})
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# 立即保存工具结果
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web_terminal.context_manager.add_conversation(
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"tool",
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tool_result_content,
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tool_call_id=tool_call_id,
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name=function_name,
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metadata=metadata_payload,
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images=tool_images,
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videos=tool_videos
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)
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debug_log(f"💾 增量保存：工具结果 {function_name}")
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system_message = result_data.get("system_message") if isinstance(result_data, dict) else None
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if system_message:
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web_terminal._record_sub_agent_message(system_message, result_data.get("task_id"), inline=False)
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maybe_mark_failure_from_message(web_terminal, system_message)
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# 添加到消息历史（用于API继续对话）
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messages.append({
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"role": "tool",
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"tool_call_id": tool_call_id,
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"name": function_name,
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"content": tool_message_content
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})
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if function_name not in {'write_file', 'edit_file'}:
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await process_sub_agent_updates(messages=messages, inline=True, after_tool_call_id=tool_call_id, web_terminal=web_terminal, sender=sender, debug_log=debug_log, maybe_mark_failure_from_message=maybe_mark_failure_from_message)
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await asyncio.sleep(0.2)
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if tool_failed:
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mark_force_thinking(web_terminal, reason=f"{function_name}_failed")
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tool_loop_result = await execute_tool_calls(
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web_terminal=web_terminal,
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tool_calls=tool_calls,
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sender=sender,
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messages=messages,
|
||||
client_sid=client_sid,
|
||||
username=username,
|
||||
iteration=iteration,
|
||||
conversation_id=conversation_id,
|
||||
last_tool_call_time=last_tool_call_time,
|
||||
process_sub_agent_updates=process_sub_agent_updates,
|
||||
maybe_mark_failure_from_message=maybe_mark_failure_from_message,
|
||||
mark_force_thinking=mark_force_thinking,
|
||||
get_stop_flag=get_stop_flag,
|
||||
clear_stop_flag=clear_stop_flag,
|
||||
)
|
||||
last_tool_call_time = tool_loop_result.get("last_tool_call_time", last_tool_call_time)
|
||||
if tool_loop_result.get("stopped"):
|
||||
return
|
||||
|
||||
# 标记不再是第一次迭代
|
||||
is_first_iteration = False
|
||||
|
||||
408
server/chat_flow_tool_loop.py
Normal file
408
server/chat_flow_tool_loop.py
Normal file
@ -0,0 +1,408 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import json
|
||||
import time
|
||||
from typing import Optional
|
||||
|
||||
from .utils_common import debug_log, brief_log
|
||||
from .state import MONITOR_FILE_TOOLS, MONITOR_MEMORY_TOOLS, MONITOR_SNAPSHOT_CHAR_LIMIT, MONITOR_MEMORY_ENTRY_LIMIT
|
||||
from .monitor import cache_monitor_snapshot
|
||||
from .security import compact_web_search_result
|
||||
from .chat_flow_helpers import detect_tool_failure
|
||||
from .chat_flow_runner_helpers import resolve_monitor_path, resolve_monitor_memory, capture_monitor_snapshot
|
||||
from utils.tool_result_formatter import format_tool_result_for_context
|
||||
from config import TOOL_CALL_COOLDOWN
|
||||
|
||||
|
||||
async def execute_tool_calls(*, web_terminal, tool_calls, sender, messages, client_sid: str, username: str, iteration: int, conversation_id: Optional[str], last_tool_call_time: float, process_sub_agent_updates, maybe_mark_failure_from_message, mark_force_thinking, get_stop_flag, clear_stop_flag):
|
||||
# 执行每个工具
|
||||
for tool_call in tool_calls:
|
||||
# 检查停止标志
|
||||
client_stop_info = get_stop_flag(client_sid, username)
|
||||
if client_stop_info:
|
||||
stop_requested = client_stop_info.get('stop', False) if isinstance(client_stop_info, dict) else client_stop_info
|
||||
if stop_requested:
|
||||
debug_log("在工具调用过程中检测到停止状态")
|
||||
tool_call_id = tool_call.get("id")
|
||||
function_name = tool_call.get("function", {}).get("name")
|
||||
# 通知前端该工具已被取消，避免界面卡住
|
||||
sender('update_action', {
|
||||
'preparing_id': tool_call_id,
|
||||
'status': 'cancelled',
|
||||
'result': {
|
||||
"success": False,
|
||||
"status": "cancelled",
|
||||
"message": "命令执行被用户取消",
|
||||
"tool": function_name
|
||||
}
|
||||
})
|
||||
# 在消息列表中记录取消结果，防止重新加载时仍显示运行中
|
||||
if tool_call_id:
|
||||
messages.append({
|
||||
"role": "tool",
|
||||
"tool_call_id": tool_call_id,
|
||||
"name": function_name,
|
||||
"content": "命令执行被用户取消",
|
||||
"metadata": {"status": "cancelled"}
|
||||
})
|
||||
sender('task_stopped', {
|
||||
'message': '命令执行被用户取消',
|
||||
'reason': 'user_stop'
|
||||
})
|
||||
clear_stop_flag(client_sid, username)
|
||||
return
|
||||
|
||||
# 工具调用间隔控制
|
||||
current_time = time.time()
|
||||
if last_tool_call_time > 0:
|
||||
elapsed = current_time - last_tool_call_time
|
||||
if elapsed < TOOL_CALL_COOLDOWN:
|
||||
await asyncio.sleep(TOOL_CALL_COOLDOWN - elapsed)
|
||||
last_tool_call_time = time.time()
|
||||
|
||||
function_name = tool_call["function"]["name"]
|
||||
arguments_str = tool_call["function"]["arguments"]
|
||||
tool_call_id = tool_call["id"]
|
||||
|
||||
|
||||
debug_log(f"准备解析JSON，工具: {function_name}, 参数长度: {len(arguments_str)}")
|
||||
debug_log(f"JSON参数前200字符: {arguments_str[:200]}")
|
||||
debug_log(f"JSON参数后200字符: {arguments_str[-200:]}")
|
||||
|
||||
# 使用改进的参数解析方法
|
||||
if hasattr(web_terminal, 'api_client') and hasattr(web_terminal.api_client, '_safe_tool_arguments_parse'):
|
||||
success, arguments, error_msg = web_terminal.api_client._safe_tool_arguments_parse(arguments_str, function_name)
|
||||
if not success:
|
||||
debug_log(f"安全解析失败: {error_msg}")
|
||||
error_text = f'工具参数解析失败: {error_msg}'
|
||||
error_payload = {
|
||||
"success": False,
|
||||
"error": error_text,
|
||||
"error_type": "parameter_format_error",
|
||||
"tool_name": function_name,
|
||||
"tool_call_id": tool_call_id,
|
||||
"message": error_text
|
||||
}
|
||||
sender('error', {'message': error_text})
|
||||
sender('update_action', {
|
||||
'preparing_id': tool_call_id,
|
||||
'status': 'completed',
|
||||
'result': error_payload,
|
||||
'message': error_text
|
||||
})
|
||||
error_content = json.dumps(error_payload, ensure_ascii=False)
|
||||
web_terminal.context_manager.add_conversation(
|
||||
"tool",
|
||||
error_content,
|
||||
tool_call_id=tool_call_id,
|
||||
name=function_name
|
||||
)
|
||||
messages.append({
|
||||
"role": "tool",
|
||||
"tool_call_id": tool_call_id,
|
||||
"name": function_name,
|
||||
"content": error_content
|
||||
})
|
||||
continue
|
||||
debug_log(f"使用安全解析成功，参数键: {list(arguments.keys())}")
|
||||
else:
|
||||
# 回退到带有基本修复逻辑的解析
|
||||
try:
|
||||
arguments = json.loads(arguments_str) if arguments_str.strip() else {}
|
||||
debug_log(f"直接JSON解析成功，参数键: {list(arguments.keys())}")
|
||||
except json.JSONDecodeError as e:
|
||||
debug_log(f"原始JSON解析失败: {e}")
|
||||
# 尝试基本的JSON修复
|
||||
repaired_str = arguments_str.strip()
|
||||
repair_attempts = []
|
||||
|
||||
# 修复1: 未闭合字符串
|
||||
if repaired_str.count('"') % 2 == 1:
|
||||
repaired_str += '"'
|
||||
repair_attempts.append("添加闭合引号")
|
||||
|
||||
# 修复2: 未闭合JSON对象
|
||||
if repaired_str.startswith('{') and not repaired_str.rstrip().endswith('}'):
|
||||
repaired_str = repaired_str.rstrip() + '}'
|
||||
repair_attempts.append("添加闭合括号")
|
||||
|
||||
# 修复3: 截断的JSON（移除不完整的最后一个键值对）
|
||||
if not repair_attempts: # 如果前面的修复都没用上
|
||||
last_comma = repaired_str.rfind(',')
|
||||
if last_comma > 0:
|
||||
repaired_str = repaired_str[:last_comma] + '}'
|
||||
repair_attempts.append("移除不完整的键值对")
|
||||
|
||||
# 尝试解析修复后的JSON
|
||||
try:
|
||||
arguments = json.loads(repaired_str)
|
||||
debug_log(f"JSON修复成功: {', '.join(repair_attempts)}")
|
||||
debug_log(f"修复后参数键: {list(arguments.keys())}")
|
||||
except json.JSONDecodeError as repair_error:
|
||||
debug_log(f"JSON修复也失败: {repair_error}")
|
||||
debug_log(f"修复尝试: {repair_attempts}")
|
||||
debug_log(f"修复后内容前100字符: {repaired_str[:100]}")
|
||||
error_text = f'工具参数解析失败: {e}'
|
||||
error_payload = {
|
||||
"success": False,
|
||||
"error": error_text,
|
||||
"error_type": "parameter_format_error",
|
||||
"tool_name": function_name,
|
||||
"tool_call_id": tool_call_id,
|
||||
"message": error_text
|
||||
}
|
||||
sender('error', {'message': error_text})
|
||||
sender('update_action', {
|
||||
'preparing_id': tool_call_id,
|
||||
'status': 'completed',
|
||||
'result': error_payload,
|
||||
'message': error_text
|
||||
})
|
||||
error_content = json.dumps(error_payload, ensure_ascii=False)
|
||||
web_terminal.context_manager.add_conversation(
|
||||
"tool",
|
||||
error_content,
|
||||
tool_call_id=tool_call_id,
|
||||
name=function_name
|
||||
)
|
||||
messages.append({
|
||||
"role": "tool",
|
||||
"tool_call_id": tool_call_id,
|
||||
"name": function_name,
|
||||
"content": error_content
|
||||
})
|
||||
continue
|
||||
|
||||
debug_log(f"执行工具: {function_name} (ID: {tool_call_id})")
|
||||
|
||||
# 发送工具开始事件
|
||||
tool_display_id = f"tool_{iteration}_{function_name}_{time.time()}"
|
||||
monitor_snapshot = None
|
||||
snapshot_path = None
|
||||
memory_snapshot_type = None
|
||||
if function_name in MONITOR_FILE_TOOLS:
|
||||
snapshot_path = resolve_monitor_path(arguments)
|
||||
monitor_snapshot = capture_monitor_snapshot(web_terminal.file_manager, snapshot_path, MONITOR_SNAPSHOT_CHAR_LIMIT, debug_log)
|
||||
if monitor_snapshot:
|
||||
cache_monitor_snapshot(tool_display_id, 'before', monitor_snapshot)
|
||||
elif function_name in MONITOR_MEMORY_TOOLS:
|
||||
memory_snapshot_type = (arguments.get('memory_type') or 'main').lower()
|
||||
before_entries = None
|
||||
try:
|
||||
before_entries = resolve_monitor_memory(web_terminal.memory_manager._read_entries(memory_snapshot_type), MONITOR_MEMORY_ENTRY_LIMIT)
|
||||
except Exception as exc:
|
||||
debug_log(f"[MonitorSnapshot] 读取记忆失败: {memory_snapshot_type} ({exc})")
|
||||
if before_entries is not None:
|
||||
monitor_snapshot = {
|
||||
'memory_type': memory_snapshot_type,
|
||||
'entries': before_entries
|
||||
}
|
||||
cache_monitor_snapshot(tool_display_id, 'before', monitor_snapshot)
|
||||
|
||||
sender('tool_start', {
|
||||
'id': tool_display_id,
|
||||
'name': function_name,
|
||||
'arguments': arguments,
|
||||
'preparing_id': tool_call_id,
|
||||
'monitor_snapshot': monitor_snapshot,
|
||||
'conversation_id': conversation_id
|
||||
})
|
||||
brief_log(f"调用了工具: {function_name}")
|
||||
|
||||
await asyncio.sleep(0.3)
|
||||
start_time = time.time()
|
||||
|
||||
# 执行工具
|
||||
tool_result = await web_terminal.handle_tool_call(function_name, arguments)
|
||||
debug_log(f"工具结果: {tool_result[:200]}...")
|
||||
|
||||
execution_time = time.time() - start_time
|
||||
if execution_time < 1.5:
|
||||
await asyncio.sleep(1.5 - execution_time)
|
||||
|
||||
# 更新工具状态
|
||||
result_data = {}
|
||||
try:
|
||||
result_data = json.loads(tool_result)
|
||||
except:
|
||||
result_data = {'output': tool_result}
|
||||
tool_failed = detect_tool_failure(result_data)
|
||||
|
||||
action_status = 'completed'
|
||||
action_message = None
|
||||
awaiting_flag = False
|
||||
|
||||
if function_name in {"write_file", "edit_file"}:
|
||||
diff_path = result_data.get("path") or arguments.get("file_path")
|
||||
summary = result_data.get("summary") or result_data.get("message")
|
||||
if summary:
|
||||
action_message = summary
|
||||
debug_log(f"{function_name} 执行完成: {summary or '无摘要'}")
|
||||
|
||||
if function_name == "wait_sub_agent":
|
||||
system_msg = result_data.get("system_message")
|
||||
if system_msg:
|
||||
messages.append({
|
||||
"role": "system",
|
||||
"content": system_msg
|
||||
})
|
||||
sender('system_message', {
|
||||
'content': system_msg,
|
||||
'inline': False
|
||||
})
|
||||
maybe_mark_failure_from_message(web_terminal, system_msg)
|
||||
monitor_snapshot_after = None
|
||||
if function_name in MONITOR_FILE_TOOLS:
|
||||
result_path = None
|
||||
if isinstance(result_data, dict):
|
||||
result_path = resolve_monitor_path(result_data)
|
||||
if not result_path:
|
||||
candidate_path = result_data.get('path')
|
||||
if isinstance(candidate_path, str) and candidate_path.strip():
|
||||
result_path = candidate_path.strip()
|
||||
if not result_path:
|
||||
result_path = resolve_monitor_path(arguments, snapshot_path) or snapshot_path
|
||||
monitor_snapshot_after = capture_monitor_snapshot(web_terminal.file_manager, result_path, MONITOR_SNAPSHOT_CHAR_LIMIT, debug_log)
|
||||
elif function_name in MONITOR_MEMORY_TOOLS:
|
||||
memory_after_type = str(
|
||||
arguments.get('memory_type')
|
||||
or (isinstance(result_data, dict) and result_data.get('memory_type'))
|
||||
or memory_snapshot_type
|
||||
or 'main'
|
||||
).lower()
|
||||
after_entries = None
|
||||
try:
|
||||
after_entries = resolve_monitor_memory(web_terminal.memory_manager._read_entries(memory_after_type), MONITOR_MEMORY_ENTRY_LIMIT)
|
||||
except Exception as exc:
|
||||
debug_log(f"[MonitorSnapshot] 读取记忆失败(after): {memory_after_type} ({exc})")
|
||||
if after_entries is not None:
|
||||
monitor_snapshot_after = {
|
||||
'memory_type': memory_after_type,
|
||||
'entries': after_entries
|
||||
}
|
||||
|
||||
update_payload = {
|
||||
'id': tool_display_id,
|
||||
'status': action_status,
|
||||
'result': result_data,
|
||||
'preparing_id': tool_call_id,
|
||||
'conversation_id': conversation_id
|
||||
}
|
||||
if action_message:
|
||||
update_payload['message'] = action_message
|
||||
if awaiting_flag:
|
||||
update_payload['awaiting_content'] = True
|
||||
if monitor_snapshot_after:
|
||||
update_payload['monitor_snapshot_after'] = monitor_snapshot_after
|
||||
cache_monitor_snapshot(tool_display_id, 'after', monitor_snapshot_after)
|
||||
|
||||
sender('update_action', update_payload)
|
||||
|
||||
if function_name in ['create_file', 'delete_file', 'rename_file', 'create_folder']:
|
||||
if not web_terminal.context_manager._is_host_mode_without_safety():
|
||||
structure = web_terminal.context_manager.get_project_structure()
|
||||
sender('file_tree_update', structure)
|
||||
|
||||
# ===== 增量保存：立即保存工具结果 =====
|
||||
metadata_payload = None
|
||||
tool_images = None
|
||||
tool_videos = None
|
||||
if isinstance(result_data, dict):
|
||||
# 特殊处理 web_search：保留可供前端渲染的精简结构，以便历史记录复现搜索结果
|
||||
if function_name == "web_search":
|
||||
try:
|
||||
tool_result_content = json.dumps(compact_web_search_result(result_data), ensure_ascii=False)
|
||||
except Exception:
|
||||
tool_result_content = tool_result
|
||||
else:
|
||||
tool_result_content = format_tool_result_for_context(function_name, result_data, tool_result)
|
||||
metadata_payload = {"tool_payload": result_data}
|
||||
else:
|
||||
tool_result_content = tool_result
|
||||
tool_message_content = tool_result_content
|
||||
|
||||
# view_image: 将图片直接附加到 tool 结果中（不再插入 user 消息）
|
||||
if function_name == "view_image" and getattr(web_terminal, "pending_image_view", None):
|
||||
inj = web_terminal.pending_image_view
|
||||
web_terminal.pending_image_view = None
|
||||
if (
|
||||
not tool_failed
|
||||
and isinstance(result_data, dict)
|
||||
and result_data.get("success") is not False
|
||||
):
|
||||
img_path = inj.get("path") if isinstance(inj, dict) else None
|
||||
if img_path:
|
||||
text_part = tool_result_content if isinstance(tool_result_content, str) else ""
|
||||
tool_message_content = web_terminal.context_manager._build_content_with_images(
|
||||
text_part,
|
||||
[img_path]
|
||||
)
|
||||
tool_images = [img_path]
|
||||
if metadata_payload is None:
|
||||
metadata_payload = {}
|
||||
metadata_payload["tool_image_path"] = img_path
|
||||
sender('system_message', {
|
||||
'content': f'系统已按模型请求将图片附加到工具结果: {img_path}'
|
||||
})
|
||||
|
||||
# view_video: 将视频直接附加到 tool 结果中（不再插入 user 消息）
|
||||
if function_name == "view_video" and getattr(web_terminal, "pending_video_view", None):
|
||||
inj = web_terminal.pending_video_view
|
||||
web_terminal.pending_video_view = None
|
||||
if (
|
||||
not tool_failed
|
||||
and isinstance(result_data, dict)
|
||||
and result_data.get("success") is not False
|
||||
):
|
||||
video_path = inj.get("path") if isinstance(inj, dict) else None
|
||||
if video_path:
|
||||
text_part = tool_result_content if isinstance(tool_result_content, str) else ""
|
||||
video_payload = [video_path]
|
||||
tool_message_content = web_terminal.context_manager._build_content_with_images(
|
||||
text_part,
|
||||
[],
|
||||
video_payload
|
||||
)
|
||||
tool_videos = [video_path]
|
||||
if metadata_payload is None:
|
||||
metadata_payload = {}
|
||||
metadata_payload["tool_video_path"] = video_path
|
||||
sender('system_message', {
|
||||
'content': f'系统已按模型请求将视频附加到工具结果: {video_path}'
|
||||
})
|
||||
|
||||
# 立即保存工具结果
|
||||
web_terminal.context_manager.add_conversation(
|
||||
"tool",
|
||||
tool_result_content,
|
||||
tool_call_id=tool_call_id,
|
||||
name=function_name,
|
||||
metadata=metadata_payload,
|
||||
images=tool_images,
|
||||
videos=tool_videos
|
||||
)
|
||||
debug_log(f"💾 增量保存：工具结果 {function_name}")
|
||||
system_message = result_data.get("system_message") if isinstance(result_data, dict) else None
|
||||
if system_message:
|
||||
web_terminal._record_sub_agent_message(system_message, result_data.get("task_id"), inline=False)
|
||||
maybe_mark_failure_from_message(web_terminal, system_message)
|
||||
|
||||
# 添加到消息历史（用于API继续对话）
|
||||
messages.append({
|
||||
"role": "tool",
|
||||
"tool_call_id": tool_call_id,
|
||||
"name": function_name,
|
||||
"content": tool_message_content
|
||||
})
|
||||
|
||||
if function_name not in {'write_file', 'edit_file'}:
|
||||
await process_sub_agent_updates(messages=messages, inline=True, after_tool_call_id=tool_call_id, web_terminal=web_terminal, sender=sender, debug_log=debug_log, maybe_mark_failure_from_message=maybe_mark_failure_from_message)
|
||||
|
||||
await asyncio.sleep(0.2)
|
||||
|
||||
if tool_failed:
|
||||
mark_force_thinking(web_terminal, reason=f"{function_name}_failed")
|
||||
|
||||
|
||||
return {"stopped": False, "last_tool_call_time": last_tool_call_time}
|
||||
Loading…
Reference in New Issue
Block a user