agent-Specialization/server/chat_flow.py
JOJO 72a49a7c8d fix: 修复对话计时器持久化、子智能体工具美化与状态查询,统一后台通知池
- 新增 server/work_timer.py,在对话真正空闲(无前台任务、无后台子智能体/后台命令/压缩)时持久化 work_timer,并同步内存副本,解决刷新后计时器回退问题。
- server/chat_flow_task_main.py / chat_flow.py / tasks/models.py 在任务结束/取消时按空闲判定决定是否持久化。
- 前端 lifecycle.ts 在仍有后台任务时不提前停止计时器。
- 子智能体工具(create/terminate/get_status)渲染美化,task 参数放在顶部元信息区。
- 子智能体状态查询支持返回「已完成」「已终止」「不存在」;修复 wait_for_completion 在 final_result 就绪前返回导致的「ID 被占用」误报。
- 统一后台完成通知池 poll_completion_notifications,合并子智能体与后台 run_command 两路轮询,避免逐条触发工作循环与单工作区互斥冲突。
- 删除本次新增的各类 debug_log / notify_pool_log 调用及辅助脚本。
2026-06-25 04:16:44 +08:00

294 lines
11 KiB
Python

from __future__ import annotations
import sys
import os
PROJECT_ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), os.pardir))
if PROJECT_ROOT not in sys.path:
sys.path.insert(0, PROJECT_ROOT)
import asyncio
import json
import time
import re
import zipfile
from collections import defaultdict, Counter, deque
from datetime import datetime, timedelta
from pathlib import Path
from typing import Dict, Any, Optional, List, Tuple
from flask import Blueprint, request, jsonify, session
from werkzeug.utils import secure_filename
from config import (
OUTPUT_FORMATS,
AUTO_FIX_TOOL_CALL,
AUTO_FIX_MAX_ATTEMPTS,
MAX_ITERATIONS_PER_TASK,
MAX_CONSECUTIVE_SAME_TOOL,
MAX_TOTAL_TOOL_CALLS,
TOOL_CALL_COOLDOWN,
MAX_UPLOAD_SIZE,
DEFAULT_CONVERSATIONS_LIMIT,
MAX_CONVERSATIONS_LIMIT,
CONVERSATIONS_DIR,
DEFAULT_RESPONSE_MAX_TOKENS,
DEFAULT_PROJECT_PATH,
LOGS_DIR,
AGENT_VERSION,
THINKING_FAST_INTERVAL,
PROJECT_MAX_STORAGE_MB,
PROJECT_MAX_STORAGE_BYTES,
UPLOAD_SCAN_LOG_SUBDIR,
)
from modules.personalization_manager import (
load_personalization_config,
save_personalization_config,
THINKING_INTERVAL_MIN,
THINKING_INTERVAL_MAX,
)
from modules.sub_agent.state import TERMINAL_STATUSES as SUB_AGENT_TERMINAL_STATUSES
from modules.upload_security import UploadSecurityError
from modules.user_manager import UserWorkspace
from modules.usage_tracker import QUOTA_DEFAULTS
from core.web_terminal import WebTerminal
from utils.tool_result_formatter import format_tool_result_for_context
from utils.conversation_manager import ConversationManager
from config.model_profiles import get_model_context_window, get_model_profile
from .auth_helpers import api_login_required, resolve_admin_policy, get_current_user_record, get_current_username
from .context import with_terminal, get_gui_manager, get_upload_guard, build_upload_error_response, ensure_conversation_loaded, reset_system_state, get_user_resources, get_or_create_usage_tracker
from .work_timer import finalize_conversation_work_timer
from .utils_common import (
build_review_lines,
debug_log,
log_backend_chunk,
log_frontend_chunk,
log_streaming_debug_entry,
brief_log,
DEBUG_LOG_FILE,
CHUNK_BACKEND_LOG_FILE,
CHUNK_FRONTEND_LOG_FILE,
STREAMING_DEBUG_LOG_FILE,
)
from .security import rate_limited, format_tool_result_notice, compact_web_search_result, consume_socket_token, prune_socket_tokens, validate_csrf_request, requires_csrf_protection, get_csrf_token
from .monitor import cache_monitor_snapshot, get_cached_monitor_snapshot
from .extensions import socketio
from .state import (
MONITOR_FILE_TOOLS,
MONITOR_MEMORY_TOOLS,
MONITOR_SNAPSHOT_CHAR_LIMIT,
MONITOR_MEMORY_ENTRY_LIMIT,
RATE_LIMIT_BUCKETS,
FAILURE_TRACKERS,
pending_socket_tokens,
usage_trackers,
MONITOR_SNAPSHOT_CACHE,
MONITOR_SNAPSHOT_CACHE_LIMIT,
PROJECT_STORAGE_CACHE,
PROJECT_STORAGE_CACHE_TTL_SECONDS,
RECENT_UPLOAD_EVENT_LIMIT,
RECENT_UPLOAD_FEED_LIMIT,
THINKING_FAILURE_KEYWORDS,
TITLE_PROMPT_PATH,
get_last_active_ts,
user_manager,
container_manager,
custom_tool_registry,
user_terminals,
terminal_rooms,
connection_users,
stop_flags,
get_stop_flag,
set_stop_flag,
clear_stop_flag,
)
from .chat_flow_helpers import (
detect_malformed_tool_call as _detect_malformed_tool_call,
detect_tool_failure,
get_thinking_state,
mark_force_thinking as _mark_force_thinking,
mark_suppress_thinking,
apply_thinking_schedule as _apply_thinking_schedule,
update_thinking_after_call as _update_thinking_after_call,
maybe_mark_failure_from_message as _maybe_mark_failure_from_message,
generate_conversation_title_background as _generate_conversation_title_background,
)
from .chat_flow_runner import handle_task_with_sender
conversation_bp = Blueprint('conversation', __name__)
def generate_conversation_title_background(web_terminal: WebTerminal, conversation_id: str, user_message: str, username: str):
"""在后台生成对话标题并更新索引、推送给前端。"""
return _generate_conversation_title_background(
web_terminal=web_terminal,
conversation_id=conversation_id,
user_message=user_message,
username=username,
socketio_instance=socketio,
title_prompt_path=TITLE_PROMPT_PATH,
debug_logger=debug_log,
)
def mark_force_thinking(terminal: WebTerminal, reason: str = ""):
return _mark_force_thinking(terminal, reason=reason, debug_logger=debug_log)
def apply_thinking_schedule(terminal: WebTerminal):
return _apply_thinking_schedule(terminal, default_interval=THINKING_FAST_INTERVAL, debug_logger=debug_log)
def update_thinking_after_call(terminal: WebTerminal):
return _update_thinking_after_call(terminal, debug_logger=debug_log)
def maybe_mark_failure_from_message(terminal: WebTerminal, content: Optional[str]):
return _maybe_mark_failure_from_message(
terminal,
content,
failure_keywords=THINKING_FAILURE_KEYWORDS,
debug_logger=debug_log,
)
def detect_malformed_tool_call(text):
return _detect_malformed_tool_call(text)
def process_message_task(terminal: WebTerminal, message: str, images, sender, client_sid, workspace: UserWorkspace, username: str, videos=None):
"""在后台处理消息任务"""
videos = videos or []
auto_user_message_event = bool(getattr(terminal, "_auto_user_message_event", False))
try:
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
# 创建可取消的任务
task = loop.create_task(
handle_task_with_sender(
terminal,
workspace,
message,
images,
sender,
client_sid,
username,
videos,
auto_user_message_event=auto_user_message_event,
)
)
entry = get_stop_flag(client_sid, username)
if not isinstance(entry, dict):
entry = {'stop': False, 'task': None, 'terminal': None, 'loop': None}
entry['stop'] = False
entry['task'] = task
entry['terminal'] = terminal
entry['loop'] = loop
set_stop_flag(client_sid, username, entry)
try:
loop.run_until_complete(task)
except asyncio.CancelledError:
debug_log(f"[ChatFlow] 任务被成功取消: client_sid={client_sid}")
# 检测是否仍有后台任务在跑,通知前端保持停止按钮
has_running_sub_agents = False
has_running_background_commands = False
conversation_id = getattr(getattr(terminal, 'context_manager', None), 'current_conversation_id', None)
if conversation_id:
sub_agent_manager = getattr(terminal, 'sub_agent_manager', None)
if sub_agent_manager:
try:
sub_agent_manager.reconcile_task_states(conversation_id=conversation_id)
for task_info in sub_agent_manager.tasks.values():
if task_info.get('conversation_id') != conversation_id:
continue
status = task_info.get('status')
if status not in SUB_AGENT_TERMINAL_STATUSES.union({"terminated"}):
has_running_sub_agents = True
break
except Exception as exc:
debug_log(f"[Task] 取消时检查后台子智能体失败: {exc}")
bg_manager = getattr(terminal, 'background_command_manager', None)
if bg_manager:
try:
bg_manager.reconcile_stale_records(conversation_id=conversation_id)
waiting_items = bg_manager.list_waiting_items(conversation_id)
if waiting_items:
has_running_background_commands = True
except Exception as exc:
debug_log(f"[Task] 取消时检查后台命令失败: {exc}")
debug_log(
f"[ChatFlow] 任务取消,最终停止事件由 _run_chat_task 发送: client_sid={client_sid}, "
f"has_running_sub_agents={has_running_sub_agents}, "
f"has_running_background_commands={has_running_background_commands}"
)
# 取消时:仅当对话真正空闲(没有后台子智能体/后台命令还在跑)
# 才把 work_timer 标记为完成,否则后台工作继续期间计时器应保持运行。
try:
if terminal and conversation_id:
finalized = finalize_conversation_work_timer(
terminal,
conversation_id,
finished_at=datetime.now().isoformat(),
)
except Exception as exc:
debug_log(f"[ChatFlow] 取消时标记 work_timer 完成失败: {exc}")
# task_stopped 事件统一在 _run_chat_task finally 中发送,避免重复
reset_system_state(terminal)
loop.close()
except Exception as e:
# 【新增】错误时确保对话状态不丢失
try:
if terminal and terminal.context_manager:
# 尝试保存当前对话状态
terminal.context_manager.auto_save_conversation()
debug_log("错误恢复:对话状态已保存")
except Exception as save_error:
debug_log(f"错误恢复:保存对话状态失败: {save_error}")
# 原有的错误处理逻辑
print(f"[Task] 错误: {e}")
debug_log(f"任务处理错误: {e}")
import traceback
traceback.print_exc()
sender('error', {
'message': str(e),
'conversation_id': getattr(getattr(terminal, "context_manager", None), "current_conversation_id", None),
'task_id': getattr(terminal, "task_id", None) or client_sid,
'client_sid': client_sid
})
sender('task_complete', {
'total_iterations': 0,
'total_tool_calls': 0,
'auto_fix_attempts': 0,
'error': str(e)
})
finally:
# 清理任务引用
clear_stop_flag(client_sid, username)
# === 统一对外入口 ===
def start_chat_task(terminal, message: str, images: Any, sender, client_sid: str, workspace, username: str, videos: Any = None):
"""在线程模式下启动对话任务,供 Socket 事件调用。"""
return socketio.start_background_task(
process_message_task,
terminal,
message,
images,
sender,
client_sid,
workspace,
username,
videos
)
def run_chat_task_sync(terminal, message: str, images: Any, sender, client_sid: str, workspace, username: str, videos: Any = None):
"""同步执行(测试/CLI 使用)。"""
return process_message_task(terminal, message, images, sender, client_sid, workspace, username, videos)