agent-Specialization/server/_conversation_segment.py

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@app.route('/api/conversations', methods=['GET'])
@api_login_required
@with_terminal
def get_conversations(terminal: WebTerminal, workspace: UserWorkspace, username: str):
"""获取对话列表"""
try:
# 获取查询参数
limit = request.args.get('limit', 20, type=int)
offset = request.args.get('offset', 0, type=int)
# 限制参数范围
limit = max(1, min(limit, 100)) # 限制在1-100之间
offset = max(0, offset)
result = terminal.get_conversations_list(limit=limit, offset=offset)
if result["success"]:
return jsonify({
"success": True,
"data": result["data"]
})
else:
return jsonify({
"success": False,
"error": result.get("error", "Unknown error"),
"message": result.get("message", "获取对话列表失败")
}), 500
except Exception as e:
print(f"[API] 获取对话列表错误: {e}")
return jsonify({
"success": False,
"error": str(e),
"message": "获取对话列表时发生异常"
}), 500
@app.route('/api/conversations', methods=['POST'])
@api_login_required
@with_terminal
def create_conversation(terminal: WebTerminal, workspace: UserWorkspace, username: str):
"""创建新对话"""
try:
data = request.get_json() or {}
# 前端现在期望“新建对话”回到用户配置的默认模型/模式,
# 只有当客户端显式要求保留当前模式时才使用传入值。
preserve_mode = bool(data.get('preserve_mode'))
thinking_mode = data.get('thinking_mode') if preserve_mode and 'thinking_mode' in data else None
run_mode = data.get('mode') if preserve_mode and 'mode' in data else None
result = terminal.create_new_conversation(thinking_mode=thinking_mode, run_mode=run_mode)
if result["success"]:
session['run_mode'] = terminal.run_mode
session['thinking_mode'] = terminal.thinking_mode
# 广播对话列表更新事件
socketio.emit('conversation_list_update', {
'action': 'created',
'conversation_id': result["conversation_id"]
}, room=f"user_{username}")
# 广播当前对话切换事件
socketio.emit('conversation_changed', {
'conversation_id': result["conversation_id"],
'title': "新对话"
}, room=f"user_{username}")
return jsonify(result), 201
else:
return jsonify(result), 500
except Exception as e:
print(f"[API] 创建对话错误: {e}")
return jsonify({
"success": False,
"error": str(e),
"message": "创建对话时发生异常"
}), 500
@app.route('/api/conversations/<conversation_id>', methods=['GET'])
@api_login_required
@with_terminal
def get_conversation_info(terminal: WebTerminal, workspace: UserWorkspace, username: str, conversation_id):
"""获取特定对话信息"""
try:
# 通过ConversationManager直接获取对话数据
conversation_data = terminal.context_manager.conversation_manager.load_conversation(conversation_id)
if conversation_data:
# 提取关键信息,不返回完整消息内容(避免数据量过大)
info = {
"id": conversation_data["id"],
"title": conversation_data["title"],
"created_at": conversation_data["created_at"],
"updated_at": conversation_data["updated_at"],
"metadata": conversation_data["metadata"],
"messages_count": len(conversation_data.get("messages", []))
}
return jsonify({
"success": True,
"data": info
})
else:
return jsonify({
"success": False,
"error": "Conversation not found",
"message": f"对话 {conversation_id} 不存在"
}), 404
except Exception as e:
print(f"[API] 获取对话信息错误: {e}")
return jsonify({
"success": False,
"error": str(e),
"message": "获取对话信息时发生异常"
}), 500
@app.route('/api/conversations/<conversation_id>/load', methods=['PUT'])
@api_login_required
@with_terminal
def load_conversation(conversation_id, terminal: WebTerminal, workspace: UserWorkspace, username: str):
"""加载特定对话"""
try:
result = terminal.load_conversation(conversation_id)
if result["success"]:
# 广播对话切换事件
socketio.emit('conversation_changed', {
'conversation_id': conversation_id,
'title': result.get("title", "未知对话"),
'messages_count': result.get("messages_count", 0)
}, room=f"user_{username}")
# 广播系统状态更新(因为当前对话改变了)
status = terminal.get_status()
socketio.emit('status_update', status, room=f"user_{username}")
# 清理和重置相关UI状态
socketio.emit('conversation_loaded', {
'conversation_id': conversation_id,
'clear_ui': True # 提示前端清理当前UI状态
}, room=f"user_{username}")
return jsonify(result)
else:
return jsonify(result), 404 if "不存在" in result.get("message", "") else 500
except Exception as e:
print(f"[API] 加载对话错误: {e}")
return jsonify({
"success": False,
"error": str(e),
"message": "加载对话时发生异常"
}), 500
@app.route('/api/conversations/<conversation_id>', methods=['DELETE'])
@api_login_required
@with_terminal
def delete_conversation(conversation_id, terminal: WebTerminal, workspace: UserWorkspace, username: str):
"""删除特定对话"""
try:
# 检查是否是当前对话
is_current = (terminal.context_manager.current_conversation_id == conversation_id)
result = terminal.delete_conversation(conversation_id)
if result["success"]:
# 广播对话列表更新事件
socketio.emit('conversation_list_update', {
'action': 'deleted',
'conversation_id': conversation_id
}, room=f"user_{username}")
# 如果删除的是当前对话,广播对话清空事件
if is_current:
socketio.emit('conversation_changed', {
'conversation_id': None,
'title': None,
'cleared': True
}, room=f"user_{username}")
# 更新系统状态
status = terminal.get_status()
socketio.emit('status_update', status, room=f"user_{username}")
return jsonify(result)
else:
return jsonify(result), 404 if "不存在" in result.get("message", "") else 500
except Exception as e:
print(f"[API] 删除对话错误: {e}")
return jsonify({
"success": False,
"error": str(e),
"message": "删除对话时发生异常"
}), 500
@app.route('/api/conversations/search', methods=['GET'])
@api_login_required
@with_terminal
def search_conversations(terminal: WebTerminal, workspace: UserWorkspace, username: str):
"""搜索对话"""
try:
query = request.args.get('q', '').strip()
limit = request.args.get('limit', 20, type=int)
if not query:
return jsonify({
"success": False,
"error": "Missing query parameter",
"message": "请提供搜索关键词"
}), 400
# 限制参数范围
limit = max(1, min(limit, 50))
result = terminal.search_conversations(query, limit)
return jsonify({
"success": True,
"data": {
"results": result["results"],
"count": result["count"],
"query": query
}
})
except Exception as e:
print(f"[API] 搜索对话错误: {e}")
return jsonify({
"success": False,
"error": str(e),
"message": "搜索对话时发生异常"
}), 500
@app.route('/api/conversations/<conversation_id>/messages', methods=['GET'])
@api_login_required
@with_terminal
def get_conversation_messages(conversation_id, terminal: WebTerminal, workspace: UserWorkspace, username: str):
"""获取对话的消息历史(可选功能,用于调试或详细查看)"""
try:
# 获取完整对话数据
conversation_data = terminal.context_manager.conversation_manager.load_conversation(conversation_id)
if conversation_data:
messages = conversation_data.get("messages", [])
# 可选:限制消息数量,避免返回过多数据
limit = request.args.get('limit', type=int)
if limit:
messages = messages[-limit:] # 获取最后N条消息
return jsonify({
"success": True,
"data": {
"conversation_id": conversation_id,
"messages": messages,
"total_count": len(conversation_data.get("messages", []))
}
})
else:
return jsonify({
"success": False,
"error": "Conversation not found",
"message": f"对话 {conversation_id} 不存在"
}), 404
except Exception as e:
print(f"[API] 获取对话消息错误: {e}")
return jsonify({
"success": False,
"error": str(e),
"message": "获取对话消息时发生异常"
}), 500
@app.route('/api/conversations/<conversation_id>/compress', methods=['POST'])
@api_login_required
@with_terminal
def compress_conversation(conversation_id, terminal: WebTerminal, workspace: UserWorkspace, username: str):
"""压缩指定对话的大体积消息,生成压缩版新对话"""
try:
policy = resolve_admin_policy(get_current_user_record())
if policy.get("ui_blocks", {}).get("block_compress_conversation"):
return jsonify({"success": False, "error": "压缩对话已被管理员禁用"}), 403
normalized_id = conversation_id if conversation_id.startswith('conv_') else f"conv_{conversation_id}"
result = terminal.context_manager.compress_conversation(normalized_id)
if not result.get("success"):
status_code = 404 if "不存在" in result.get("error", "") else 400
return jsonify(result), status_code
new_conversation_id = result["compressed_conversation_id"]
load_result = terminal.load_conversation(new_conversation_id)
if load_result.get("success"):
socketio.emit('conversation_list_update', {
'action': 'compressed',
'conversation_id': new_conversation_id
}, room=f"user_{username}")
socketio.emit('conversation_changed', {
'conversation_id': new_conversation_id,
'title': load_result.get('title', '压缩后的对话'),
'messages_count': load_result.get('messages_count', 0)
}, room=f"user_{username}")
socketio.emit('conversation_loaded', {
'conversation_id': new_conversation_id,
'clear_ui': True
}, room=f"user_{username}")
response_payload = {
"success": True,
"compressed_conversation_id": new_conversation_id,
"compressed_types": result.get("compressed_types", []),
"system_message": result.get("system_message"),
"load_result": load_result
}
return jsonify(response_payload)
except Exception as e:
print(f"[API] 压缩对话错误: {e}")
return jsonify({
"success": False,
"error": str(e),
"message": "压缩对话时发生异常"
}), 500
@app.route('/api/sub_agents', methods=['GET'])
@api_login_required
@with_terminal
def list_sub_agents(terminal: WebTerminal, workspace: UserWorkspace, username: str):
"""返回当前对话的子智能体任务列表。"""
manager = getattr(terminal, "sub_agent_manager", None)
if not manager:
return jsonify({"success": True, "data": []})
try:
conversation_id = terminal.context_manager.current_conversation_id
data = manager.get_overview(conversation_id=conversation_id)
return jsonify({"success": True, "data": data})
except Exception as exc:
return jsonify({"success": False, "error": str(exc)}), 500
@app.route('/api/conversations/<conversation_id>/duplicate', methods=['POST'])
@api_login_required
@with_terminal
def duplicate_conversation(conversation_id, terminal: WebTerminal, workspace: UserWorkspace, username: str):
"""复制指定对话,生成新的对话副本"""
try:
result = terminal.context_manager.duplicate_conversation(conversation_id)
if not result.get("success"):
status_code = 404 if "不存在" in result.get("error", "") else 400
return jsonify(result), status_code
new_conversation_id = result["duplicate_conversation_id"]
load_result = terminal.load_conversation(new_conversation_id)
if load_result.get("success"):
socketio.emit('conversation_list_update', {
'action': 'duplicated',
'conversation_id': new_conversation_id
}, room=f"user_{username}")
socketio.emit('conversation_changed', {
'conversation_id': new_conversation_id,
'title': load_result.get('title', '复制的对话'),
'messages_count': load_result.get('messages_count', 0)
}, room=f"user_{username}")
socketio.emit('conversation_loaded', {
'conversation_id': new_conversation_id,
'clear_ui': True
}, room=f"user_{username}")
response_payload = {
"success": True,
"duplicate_conversation_id": new_conversation_id,
"load_result": load_result
}
return jsonify(response_payload)
except Exception as e:
print(f"[API] 复制对话错误: {e}")
return jsonify({
"success": False,
"error": str(e),
"message": "复制对话时发生异常"
}), 500
@app.route('/api/conversations/<conversation_id>/review_preview', methods=['GET'])
@api_login_required
@with_terminal
def review_conversation_preview(conversation_id, terminal: WebTerminal, workspace: UserWorkspace, username: str):
"""生成对话回顾预览(不落盘,只返回前若干行文本)"""
policy = resolve_admin_policy(get_current_user_record())
if policy.get("ui_blocks", {}).get("block_conversation_review"):
return jsonify({"success": False, "error": "对话引用已被管理员禁用"}), 403
try:
current_id = terminal.context_manager.current_conversation_id
if conversation_id == current_id:
return jsonify({
"success": False,
"message": "无法引用当前对话"
}), 400
conversation_data = terminal.context_manager.conversation_manager.load_conversation(conversation_id)
if not conversation_data:
return jsonify({
"success": False,
"error": "Conversation not found",
"message": f"对话 {conversation_id} 不存在"
}), 404
limit = request.args.get('limit', default=20, type=int) or 20
lines = build_review_lines(conversation_data.get("messages", []), limit=limit)
return jsonify({
"success": True,
"data": {
"preview": lines,
"count": len(lines)
}
})
except Exception as e:
print(f"[API] 对话回顾预览错误: {e}")
return jsonify({
"success": False,
"error": str(e),
"message": "生成预览时发生异常"
}), 500
@app.route('/api/conversations/<conversation_id>/review', methods=['POST'])
@api_login_required
@with_terminal
def review_conversation(conversation_id, terminal: WebTerminal, workspace: UserWorkspace, username: str):
"""生成完整对话回顾 Markdown 文件"""
policy = resolve_admin_policy(get_current_user_record())
if policy.get("ui_blocks", {}).get("block_conversation_review"):
return jsonify({"success": False, "error": "对话引用已被管理员禁用"}), 403
try:
current_id = terminal.context_manager.current_conversation_id
if conversation_id == current_id:
return jsonify({
"success": False,
"message": "无法引用当前对话"
}), 400
conversation_data = terminal.context_manager.conversation_manager.load_conversation(conversation_id)
if not conversation_data:
return jsonify({
"success": False,
"error": "Conversation not found",
"message": f"对话 {conversation_id} 不存在"
}), 404
messages = conversation_data.get("messages", [])
lines = build_review_lines(messages)
content = "\n".join(lines) + "\n"
char_count = len(content)
uploads_dir = workspace.uploads_dir / "review"
uploads_dir.mkdir(parents=True, exist_ok=True)
title = conversation_data.get("title") or "untitled"
safe_title = _sanitize_filename_component(title)
timestamp = datetime.now().strftime("%Y%m%d%H%M%S")
filename = f"review_{safe_title}_{timestamp}.md"
target = uploads_dir / filename
target.write_text(content, encoding='utf-8')
return jsonify({
"success": True,
"data": {
"path": f"user_upload/review/{filename}",
"char_count": char_count
}
})
except Exception as e:
print(f"[API] 对话回顾生成错误: {e}")
return jsonify({
"success": False,
"error": str(e),
"message": "生成对话回顾时发生异常"
}), 500
@app.route('/api/conversations/statistics', methods=['GET'])
@api_login_required
@with_terminal
def get_conversations_statistics(terminal: WebTerminal, workspace: UserWorkspace, username: str):
"""获取对话统计信息"""
try:
stats = terminal.context_manager.get_conversation_statistics()
return jsonify({
"success": True,
"data": stats
})
except Exception as e:
print(f"[API] 获取对话统计错误: {e}")
return jsonify({
"success": False,
"error": str(e),
"message": "获取对话统计时发生异常"
}), 500
@app.route('/api/conversations/current', methods=['GET'])
@api_login_required
@with_terminal
def get_current_conversation(terminal: WebTerminal, workspace: UserWorkspace, username: str):
"""获取当前对话信息"""
current_id = terminal.context_manager.current_conversation_id
# 如果是临时ID返回空的对话信息
if not current_id or current_id.startswith('temp_'):
return jsonify({
"success": True,
"data": {
"id": current_id,
"title": "新对话",
"messages_count": 0,
"is_temporary": True
}
})
# 如果是真实的对话ID查找对话数据
try:
conversation_data = terminal.context_manager.conversation_manager.load_conversation(current_id)
if conversation_data:
return jsonify({
"success": True,
"data": {
"id": current_id,
"title": conversation_data.get("title", "未知对话"),
"messages_count": len(conversation_data.get("messages", [])),
"is_temporary": False
}
})
else:
return jsonify({
"success": False,
"error": "对话不存在"
}), 404
except Exception as e:
print(f"[API] 获取当前对话错误: {e}")
return jsonify({
"success": False,
"error": str(e)
}), 500
def process_message_task(terminal: WebTerminal, message: str, images, sender, client_sid, workspace: UserWorkspace, username: str):
"""在后台处理消息任务"""
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))
entry = stop_flags.get(client_sid)
if not isinstance(entry, dict):
entry = {'stop': False, 'task': None, 'terminal': None}
stop_flags[client_sid] = entry
entry['stop'] = False
entry['task'] = task
entry['terminal'] = terminal
try:
loop.run_until_complete(task)
except asyncio.CancelledError:
debug_log(f"任务 {client_sid} 被成功取消")
sender('task_stopped', {
'message': '任务已停止',
'reason': 'user_requested'
})
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)})
sender('task_complete', {
'total_iterations': 0,
'total_tool_calls': 0,
'auto_fix_attempts': 0,
'error': str(e)
})
finally:
# 清理任务引用
stop_flags.pop(client_sid, None)
def detect_malformed_tool_call(text):
"""检测文本中是否包含格式错误的工具调用"""
# 检测多种可能的工具调用格式
patterns = [
r'执行工具[:]\s*\w+<.*?tool.*?sep.*?>', # 执行工具: xxx<tool▼sep>
r'<\|?tool[_▼]?call[_▼]?start\|?>', # <tool_call_start>
r'```tool[_\s]?call', # ```tool_call 或 ```tool call
r'{\s*"tool":\s*"[^"]+",\s*"arguments"', # JSON格式的工具调用
r'function_calls?:\s*\[?\s*{', # function_call: [{
]
for pattern in patterns:
if re.search(pattern, text, re.IGNORECASE):
return True
# 检测特定的工具名称后跟JSON
tool_names = ['create_file', 'read_file', 'write_file_diff', 'delete_file',
'terminal_session', 'terminal_input', 'web_search',
'extract_webpage', 'save_webpage',
'run_python', 'run_command', 'focus_file', 'unfocus_file', 'sleep']
for tool in tool_names:
if tool in text and '{' in text:
# 可能是工具调用但格式错误
return True
return False
async def handle_task_with_sender(terminal: WebTerminal, workspace: UserWorkspace, message, images, sender, client_sid, username: str):
"""处理任务并发送消息 - 集成token统计版本"""
web_terminal = terminal
conversation_id = getattr(web_terminal.context_manager, "current_conversation_id", None)
# 如果是思考模式,重置状态
if web_terminal.thinking_mode:
web_terminal.api_client.start_new_task(force_deep=web_terminal.deep_thinking_mode)
state = get_thinking_state(web_terminal)
state["fast_streak"] = 0
state["force_next"] = False
state["suppress_next"] = False
# 添加到对话历史
history_len_before = len(getattr(web_terminal.context_manager, "conversation_history", []) or [])
is_first_user_message = history_len_before == 0
web_terminal.context_manager.add_conversation("user", message, images=images)
if is_first_user_message and getattr(web_terminal, "context_manager", None):
try:
personal_config = load_personalization_config(workspace.data_dir)
except Exception:
personal_config = {}
auto_title_enabled = personal_config.get("auto_generate_title", True)
if auto_title_enabled:
conv_id = getattr(web_terminal.context_manager, "current_conversation_id", None)
socketio.start_background_task(
generate_conversation_title_background,
web_terminal,
conv_id,
message,
username
)
# === 移除不在这里计算输入token改为在每次API调用前计算 ===
# 构建上下文和消息用于API调用
context = web_terminal.build_context()
messages = web_terminal.build_messages(context, message)
tools = web_terminal.define_tools()
# 开始新的AI消息
sender('ai_message_start', {})
# 增量保存相关变量
accumulated_response = "" # 累积的响应内容
is_first_iteration = True # 是否是第一次迭代
# 统计和限制变量
total_iterations = 0
total_tool_calls = 0
consecutive_same_tool = defaultdict(int)
last_tool_name = ""
auto_fix_attempts = 0
last_tool_call_time = 0
detected_tool_intent: Dict[str, str] = {}
# 设置最大迭代次数
max_iterations = MAX_ITERATIONS_PER_TASK
pending_append = None # {"path": str, "tool_call_id": str, "buffer": str, ...}
append_probe_buffer = ""
pending_modify = None # {"path": str, "tool_call_id": str, "buffer": str, ...}
modify_probe_buffer = ""
def extract_intent_from_partial(arg_str: str) -> Optional[str]:
"""从不完整的JSON字符串中粗略提取 intent 字段,容错用于流式阶段。"""
if not arg_str or "intent" not in arg_str:
return None
import re
# 匹配 "intent": "xxx" 形式,允许前面有换行或空格;宽松匹配未闭合的引号
match = re.search(r'"intent"\s*:\s*"([^"]{0,128})', arg_str, re.IGNORECASE | re.DOTALL)
if match:
return match.group(1)
return None
def resolve_monitor_path(args: Dict[str, Any], fallback: Optional[str] = None) -> Optional[str]:
candidates = [
args.get('path'),
args.get('target_path'),
args.get('file_path'),
args.get('destination_path'),
fallback
]
for candidate in candidates:
if isinstance(candidate, str):
trimmed = candidate.strip()
if trimmed:
return trimmed
return None
def resolve_monitor_memory(entries: Any) -> Optional[List[str]]:
if isinstance(entries, list):
return [str(item) for item in entries][:MONITOR_MEMORY_ENTRY_LIMIT]
return None
def capture_monitor_snapshot(path: Optional[str]) -> Optional[Dict[str, Any]]:
if not path:
return None
try:
read_result = web_terminal.file_manager.read_file(path)
except Exception as exc:
debug_log(f"[MonitorSnapshot] 读取文件失败: {path} ({exc})")
return None
if not isinstance(read_result, dict) or not read_result.get('success'):
return None
content = read_result.get('content')
if not isinstance(content, str):
content = ''
if len(content) > MONITOR_SNAPSHOT_CHAR_LIMIT:
content = content[:MONITOR_SNAPSHOT_CHAR_LIMIT]
return {
'path': read_result.get('path') or path,
'content': content
}
async def finalize_pending_append(response_text: str, stream_completed: bool, finish_reason: str = None) -> Dict:
"""在流式输出结束后处理追加写入"""
nonlocal pending_append, append_probe_buffer
result = {
"handled": False,
"success": False,
"summary": None,
"summary_message": None,
"tool_content": None,
"tool_call_id": None,
"path": None,
"forced": False,
"error": None,
"assistant_content": response_text,
"lines": 0,
"bytes": 0,
"finish_reason": finish_reason,
"appended_content": "",
"assistant_metadata": None
}
if not pending_append:
return result
state = pending_append
path = state.get("path")
tool_call_id = state.get("tool_call_id")
buffer = state.get("buffer", "")
start_marker = state.get("start_marker")
end_marker = state.get("end_marker")
start_idx = state.get("content_start")
end_idx = state.get("end_index")
display_id = state.get("display_id")
result.update({
"handled": True,
"path": path,
"tool_call_id": tool_call_id,
"display_id": display_id
})
if path is None or tool_call_id is None:
error_msg = "append_to_file 状态不完整缺少路径或ID。"
debug_log(error_msg)
result["error"] = error_msg
result["summary_message"] = error_msg
result["tool_content"] = json.dumps({
"success": False,
"error": error_msg
}, ensure_ascii=False)
if display_id:
sender('update_action', {
'id': display_id,
'status': 'failed',
'preparing_id': tool_call_id,
'message': error_msg
})
pending_append = None
return result
if start_idx is None:
error_msg = f"未检测到格式正确的开始标识 {start_marker}"
debug_log(error_msg)
result["error"] = error_msg
result["summary_message"] = error_msg
result["tool_content"] = json.dumps({
"success": False,
"path": path,
"error": error_msg
}, ensure_ascii=False)
if display_id:
sender('update_action', {
'id': display_id,
'status': 'failed',
'preparing_id': tool_call_id,
'message': error_msg
})
pending_append = None
return result
forced = False
if end_idx is None:
forced = True
# 查找下一个<<<,否则使用整个缓冲结尾
remaining = buffer[start_idx:]
next_marker = remaining.find("<<<", len(end_marker))
if next_marker != -1:
end_idx = start_idx + next_marker
else:
end_idx = len(buffer)
content = buffer[start_idx:end_idx]
if content.startswith('\n'):
content = content[1:]
if not content:
error_msg = "未检测到需要追加的内容,请严格按照<<<APPEND:path>>>...<<<END_APPEND>>>格式输出。"
debug_log(error_msg)
result["error"] = error_msg
result["forced"] = forced
result["tool_content"] = json.dumps({
"success": False,
"path": path,
"error": error_msg
}, ensure_ascii=False)
if display_id:
sender('update_action', {
'id': display_id,
'status': 'failed',
'preparing_id': tool_call_id,
'message': error_msg
})
pending_append = None
return result
assistant_message_lines = []
if start_marker:
assistant_message_lines.append(start_marker)
assistant_message_lines.append(content)
if not forced and end_marker:
assistant_message_lines.append(end_marker)
assistant_message_text = "\n".join(assistant_message_lines)
result["assistant_content"] = assistant_message_text
assistant_metadata = {
"append_payload": {
"path": path,
"tool_call_id": tool_call_id,
"forced": forced,
"has_end_marker": not forced
}
}
result["assistant_metadata"] = assistant_metadata
write_result = web_terminal.file_manager.append_file(path, content)
if write_result.get("success"):
bytes_written = len(content.encode('utf-8'))
line_count = content.count('\n')
if content and not content.endswith('\n'):
line_count += 1
summary = f"已向 {path} 追加 {line_count} 行({bytes_written} 字节)"
if forced:
summary += "。未检测到 <<<END_APPEND>>> 标记,系统已在流结束处完成写入。如内容未完成,请重新调用 append_to_file 并按标准格式补充;如已完成,可继续后续步骤。"
result.update({
"success": True,
"summary": summary,
"summary_message": summary,
"forced": forced,
"lines": line_count,
"bytes": bytes_written,
"appended_content": content,
"tool_content": json.dumps({
"success": True,
"path": path,
"lines": line_count,
"bytes": bytes_written,
"forced": forced,
"message": summary,
"finish_reason": finish_reason
}, ensure_ascii=False)
})
assistant_meta_payload = result["assistant_metadata"]["append_payload"]
assistant_meta_payload["lines"] = line_count
assistant_meta_payload["bytes"] = bytes_written
assistant_meta_payload["success"] = True
summary_payload = {
"success": True,
"path": path,
"lines": line_count,
"bytes": bytes_written,
"forced": forced,
"message": summary
}
if display_id:
sender('update_action', {
'id': display_id,
'status': 'completed',
'result': summary_payload,
'preparing_id': tool_call_id,
'message': summary
})
# 更新聚焦文件内容
if path in web_terminal.focused_files:
refreshed = web_terminal.file_manager.read_file(path)
if refreshed.get("success"):
web_terminal.focused_files[path] = refreshed["content"]
debug_log(f"聚焦文件已刷新: {path}")
debug_log(f"追加写入完成: {summary}")
else:
error_msg = write_result.get("error", "追加写入失败")
result.update({
"error": error_msg,
"summary_message": error_msg,
"forced": forced,
"appended_content": content,
"tool_content": json.dumps({
"success": False,
"path": path,
"error": error_msg,
"finish_reason": finish_reason
}, ensure_ascii=False)
})
debug_log(f"追加写入失败: {error_msg}")
if result["assistant_metadata"]:
assistant_meta_payload = result["assistant_metadata"]["append_payload"]
assistant_meta_payload["lines"] = content.count('\n') + (0 if content.endswith('\n') or not content else 1)
assistant_meta_payload["bytes"] = len(content.encode('utf-8'))
assistant_meta_payload["success"] = False
failure_payload = {
"success": False,
"path": path,
"error": error_msg,
"forced": forced
}
if display_id:
sender('update_action', {
'id': display_id,
'status': 'completed',
'result': failure_payload,
'preparing_id': tool_call_id,
'message': error_msg
})
pending_append = None
append_probe_buffer = ""
if hasattr(web_terminal, "pending_append_request"):
web_terminal.pending_append_request = None
return result
async def finalize_pending_modify(response_text: str, stream_completed: bool, finish_reason: str = None) -> Dict:
"""在流式输出结束后处理修改写入"""
nonlocal pending_modify, modify_probe_buffer
result = {
"handled": False,
"success": False,
"path": None,
"tool_call_id": None,
"display_id": None,
"total_blocks": 0,
"completed_blocks": [],
"failed_blocks": [],
"forced": False,
"details": [],
"error": None,
"assistant_content": response_text,
"assistant_metadata": None,
"tool_content": None,
"summary_message": None,
"finish_reason": finish_reason
}
if not pending_modify:
return result
state = pending_modify
path = state.get("path")
tool_call_id = state.get("tool_call_id")
display_id = state.get("display_id")
start_marker = state.get("start_marker")
end_marker = state.get("end_marker")
buffer = state.get("buffer", "")
raw_buffer = state.get("raw_buffer", "")
end_index = state.get("end_index")
result.update({
"handled": True,
"path": path,
"tool_call_id": tool_call_id,
"display_id": display_id
})
if not state.get("start_seen"):
error_msg = "未检测到格式正确的 <<<MODIFY:path>>> 标记。"
debug_log(error_msg)
result["error"] = error_msg
result["summary_message"] = error_msg
result["tool_content"] = json.dumps({
"success": False,
"path": path,
"error": error_msg,
"finish_reason": finish_reason
}, ensure_ascii=False)
if display_id:
sender('update_action', {
'id': display_id,
'status': 'failed',
'preparing_id': tool_call_id,
'message': error_msg
})
if hasattr(web_terminal, "pending_modify_request"):
web_terminal.pending_modify_request = None
pending_modify = None
modify_probe_buffer = ""
return result
forced = end_index is None
apply_text = buffer if forced else buffer[:end_index]
raw_content = raw_buffer if forced else raw_buffer[:len(start_marker) + end_index + len(end_marker)]
if raw_content:
result["assistant_content"] = raw_content
blocks_info = []
block_reports = {}
detected_indices = set()
block_pattern = re.compile(r"\[replace:(\d+)\](.*?)\[/replace\]", re.DOTALL)
structure_warnings: List[str] = []
structure_detail_entries: List[Dict] = []
def record_structure_warning(message: str, hint: Optional[str] = None):
"""记录结构性缺陷,便于给出更具体的反馈。"""
if message in structure_warnings:
return
structure_warnings.append(message)
structure_detail_entries.append({
"index": 0,
"status": "failed",
"reason": message,
"removed_lines": 0,
"added_lines": 0,
"hint": hint or "请严格按照模板输出:[replace:n] + <<OLD>>/<<NEW>> + [/replace],并使用 <<<END_MODIFY>>> 收尾。"
})
def extract_segment(body: str, tag: str):
marker = f"<<{tag}>>"
end_tag = "<<END>>"
start_pos = body.find(marker)
if start_pos == -1:
return None, f"缺少 {marker}"
start_pos += len(marker)
if body[start_pos:start_pos+2] == "\r\n":
start_pos += 2
elif body[start_pos:start_pos+1] == "\n":
start_pos += 1
end_pos = body.find(end_tag, start_pos)
if end_pos == -1:
return None, f"缺少 {end_tag}"
segment = body[start_pos:end_pos]
return segment, None
for match in block_pattern.finditer(apply_text):
try:
index = int(match.group(1))
except ValueError:
continue
body = match.group(2)
if index in detected_indices:
continue
detected_indices.add(index)
block_reports[index] = {
"index": index,
"status": "pending",
"reason": None,
"removed_lines": 0,
"added_lines": 0,
"hint": None
}
old_content, old_error = extract_segment(body, "OLD")
new_content, new_error = extract_segment(body, "NEW")
if old_error or new_error:
reason = old_error or new_error
block_reports[index]["status"] = "failed"
block_reports[index]["reason"] = reason
blocks_info.append({
"index": index,
"old": old_content,
"new": new_content,
"error": old_error or new_error
})
if not blocks_info:
has_replace_start = bool(re.search(r"\[replace:\s*\d+\]", apply_text))
has_replace_end = "[/replace]" in apply_text
has_old_tag = "<<OLD>>" in apply_text
has_new_tag = "<<NEW>>" in apply_text
if has_replace_start and not has_replace_end:
record_structure_warning("检测到 [replace:n] 标记但缺少对应的 [/replace] 结束标记。")
if has_replace_end and not has_replace_start:
record_structure_warning("检测到 [/replace] 结束标记但缺少对应的 [replace:n] 起始标记。")
old_tags = len(re.findall(r"<<OLD>>", apply_text))
completed_old_tags = len(re.findall(r"<<OLD>>[\s\S]*?<<END>>", apply_text))
if old_tags and completed_old_tags < old_tags:
record_structure_warning("检测到 <<OLD>> 段落但未看到对应的 <<END>> 结束标记。")
new_tags = len(re.findall(r"<<NEW>>", apply_text))
completed_new_tags = len(re.findall(r"<<NEW>>[\s\S]*?<<END>>", apply_text))
if new_tags and completed_new_tags < new_tags:
record_structure_warning("检测到 <<NEW>> 段落但未看到对应的 <<END>> 结束标记。")
if (has_replace_start or has_replace_end or has_old_tag or has_new_tag) and not structure_warnings:
record_structure_warning("检测到部分补丁标记,但整体结构不完整,请严格按照模板填写所有标记。")
total_blocks = len(blocks_info)
result["total_blocks"] = total_blocks
if forced:
debug_log("未检测到 <<<END_MODIFY>>>,将在流结束处执行已识别的修改块。")
result["forced"] = True
blocks_to_apply = [
{"index": block["index"], "old": block["old"], "new": block["new"]}
for block in blocks_info
if block["error"] is None and block["old"] is not None and block["new"] is not None
]
# 记录格式残缺的块
for block in blocks_info:
if block["error"]:
idx = block["index"]
block_reports[idx]["status"] = "failed"
block_reports[idx]["reason"] = block["error"]
block_reports[idx]["hint"] = "请检查补丁块的 OLD/NEW 标记是否完整,必要时复用 terminal_snapshot 或终端命令重新调整。"
apply_result = {}
if blocks_to_apply:
apply_result = web_terminal.file_manager.apply_modify_blocks(path, blocks_to_apply)
else:
apply_result = {"success": False, "completed": [], "failed": [], "results": [], "write_performed": False, "error": None}
block_result_map = {item["index"]: item for item in apply_result.get("results", [])}
for block in blocks_info:
idx = block["index"]
report = block_reports.get(idx)
if report is None:
continue
if report["status"] == "failed":
continue
block_apply = block_result_map.get(idx)
if not block_apply:
report["status"] = "failed"
report["reason"] = "未执行,可能未找到匹配原文"
report["hint"] = report.get("hint") or "请确认 OLD 文本与文件内容完全一致;若多次失败,可改用终端命令/Python 进行精准替换。"
continue
status = block_apply.get("status")
report["removed_lines"] = block_apply.get("removed_lines", 0)
report["added_lines"] = block_apply.get("added_lines", 0)
if block_apply.get("hint"):
report["hint"] = block_apply.get("hint")
if status == "success":
report["status"] = "completed"
elif status == "not_found":
report["status"] = "failed"
report["reason"] = block_apply.get("reason") or "未找到匹配的原文"
if not report.get("hint"):
report["hint"] = "请使用 terminal_snapshot/grep -n 校验原文,或在说明后改用 run_command/python 精确替换。"
else:
report["status"] = "failed"
report["reason"] = block_apply.get("reason") or "替换失败"
if not report.get("hint"):
report["hint"] = block_apply.get("hint") or "若多次尝试仍失败,可考虑利用终端命令或 Python 小脚本完成此次修改。"
completed_blocks = sorted([idx for idx, rep in block_reports.items() if rep["status"] == "completed"])
failed_blocks = sorted([idx for idx, rep in block_reports.items() if rep["status"] != "completed"])
result["completed_blocks"] = completed_blocks
result["failed_blocks"] = failed_blocks
details = sorted(block_reports.values(), key=lambda x: x["index"])
if structure_detail_entries:
details = structure_detail_entries + details
result["details"] = details
summary_parts = []
if total_blocks == 0:
summary_parts.append("未检测到有效的修改块,未执行任何修改。")
summary_parts.extend(structure_warnings)
else:
if not completed_blocks and failed_blocks:
summary_parts.append(f"共检测到 {total_blocks} 个修改块,全部未执行。")
elif completed_blocks and not failed_blocks:
summary_parts.append(f"{total_blocks} 个修改块全部完成。")
else:
summary_parts.append(
f"共检测到 {total_blocks} 个修改块,其中成功 {len(completed_blocks)} 个,失败 {len(failed_blocks)} 个。"
)
if forced:
summary_parts.append("未检测到 <<<END_MODIFY>>> 标记,系统已在流结束处执行补丁。")
if apply_result.get("error"):
summary_parts.append(apply_result["error"])
matching_note = "提示:补丁匹配基于完整文本,包含注释和空白符,请确保 <<<OLD>>> 段落与文件内容逐字一致。如果修改成功,请忽略,如果失败,请明确原文后再次尝试。"
summary_parts.append(matching_note)
summary_message = " ".join(summary_parts).strip()
result["summary_message"] = summary_message
result["success"] = bool(completed_blocks) and not failed_blocks and apply_result.get("error") is None
tool_payload = {
"success": result["success"],
"path": path,
"total_blocks": total_blocks,
"completed": completed_blocks,
"failed": [
{
"index": rep["index"],
"reason": rep.get("reason"),
"hint": rep.get("hint")
}
for rep in result["details"] if rep["status"] != "completed"
],
"forced": forced,
"message": summary_message,
"finish_reason": finish_reason,
"details": result["details"]
}
if apply_result.get("error"):
tool_payload["error"] = apply_result["error"]
result["tool_content"] = json.dumps(tool_payload, ensure_ascii=False)
result["assistant_metadata"] = {
"modify_payload": {
"path": path,
"total_blocks": total_blocks,
"completed": completed_blocks,
"failed": failed_blocks,
"forced": forced,
"details": result["details"]
}
}
if display_id:
sender('update_action', {
'id': display_id,
'status': 'completed' if result["success"] else 'failed',
'result': tool_payload,
'preparing_id': tool_call_id,
'message': summary_message
})
if path in web_terminal.focused_files and tool_payload.get("success"):
refreshed = web_terminal.file_manager.read_file(path)
if refreshed.get("success"):
web_terminal.focused_files[path] = refreshed["content"]
debug_log(f"聚焦文件已刷新: {path}")
pending_modify = None
modify_probe_buffer = ""
if hasattr(web_terminal, "pending_modify_request"):
web_terminal.pending_modify_request = None
return result
async def process_sub_agent_updates(
messages: List[Dict],
inline: bool = False,
after_tool_call_id: Optional[str] = None
):
"""轮询子智能体任务并通知前端,并把结果插入当前对话上下文。"""
manager = getattr(web_terminal, "sub_agent_manager", None)
if not manager:
return
try:
updates = manager.poll_updates()
debug_log(f"[SubAgent] poll inline={inline} updates={len(updates)}")
except Exception as exc:
debug_log(f"子智能体状态检查失败: {exc}")
return
for update in updates:
message = update.get("system_message")
if not message:
continue
task_id = update.get("task_id")
debug_log(f"[SubAgent] update task={task_id} inline={inline} msg={message}")
web_terminal._record_sub_agent_message(message, task_id, inline=inline)
debug_log(f"[SubAgent] recorded task={task_id}, 计算插入位置")
insert_index = len(messages)
if after_tool_call_id:
for idx, msg in enumerate(messages):
if msg.get("role") == "tool" and msg.get("tool_call_id") == after_tool_call_id:
insert_index = idx + 1
break
messages.insert(insert_index, {
"role": "system",
"content": message,
"metadata": {"sub_agent_notice": True, "inline": inline, "task_id": task_id}
})
debug_log(f"[SubAgent] 插入系统消息位置: {insert_index}")
sender('system_message', {
'content': message,
'inline': inline
})
maybe_mark_failure_from_message(web_terminal, message)
for iteration in range(max_iterations):
total_iterations += 1
debug_log(f"\n--- 迭代 {iteration + 1}/{max_iterations} 开始 ---")
# 检查是否超过总工具调用限制
if total_tool_calls >= MAX_TOTAL_TOOL_CALLS:
debug_log(f"已达到最大工具调用次数限制 ({MAX_TOTAL_TOOL_CALLS})")
sender('system_message', {
'content': f'⚠️ 已达到最大工具调用次数限制 ({MAX_TOTAL_TOOL_CALLS}),任务结束。'
})
mark_force_thinking(web_terminal, reason="tool_limit")
break
apply_thinking_schedule(web_terminal)
full_response = ""
tool_calls = []
current_thinking = ""
detected_tools = {}
last_usage_payload = None
# 状态标志
in_thinking = False
thinking_started = False
thinking_ended = False
text_started = False
text_has_content = False
text_streaming = False
text_chunk_index = 0
last_text_chunk_time: Optional[float] = None
# 计数器
chunk_count = 0
reasoning_chunks = 0
content_chunks = 0
tool_chunks = 0
append_break_triggered = False
append_result = {"handled": False}
modify_break_triggered = False
modify_result = {"handled": False}
last_finish_reason = None
thinking_expected = web_terminal.api_client.get_current_thinking_mode()
debug_log(f"思考模式: {thinking_expected}")
quota_allowed = True
quota_info = {}
if hasattr(web_terminal, "record_model_call"):
quota_allowed, quota_info = web_terminal.record_model_call(bool(thinking_expected))
if not quota_allowed:
quota_type = 'thinking' if thinking_expected else 'fast'
socketio.emit('quota_notice', {
'type': quota_type,
'reset_at': quota_info.get('reset_at'),
'limit': quota_info.get('limit'),
'count': quota_info.get('count')
}, room=f"user_{getattr(web_terminal, 'username', '')}")
sender('quota_exceeded', {
'type': quota_type,
'reset_at': quota_info.get('reset_at')
})
sender('error', {
'message': "配额已达到上限,暂时无法继续调用模型。",
'quota': quota_info
})
return
print(f"[API] 第{iteration + 1}次调用 (总工具调用: {total_tool_calls}/{MAX_TOTAL_TOOL_CALLS})")
# 收集流式响应
async for chunk in web_terminal.api_client.chat(messages, tools, stream=True):
chunk_count += 1
# 检查停止标志
client_stop_info = stop_flags.get(client_sid)
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(f"检测到停止请求,中断流处理")
if pending_append:
append_result = await finalize_pending_append(full_response, False, finish_reason="user_stop")
break
if pending_modify:
modify_result = await finalize_pending_modify(full_response, False, finish_reason="user_stop")
break
# 先尝试记录 usage有些平台会在最后一个 chunk 里携带 usage 但 choices 为空)
usage_info = chunk.get("usage")
if usage_info:
last_usage_payload = usage_info
if "choices" not in chunk:
debug_log(f"Chunk {chunk_count}: 无choices字段")
continue
if not chunk.get("choices"):
debug_log(f"Chunk {chunk_count}: choices为空列表")
continue
choice = chunk["choices"][0]
if not usage_info and isinstance(choice, dict) and choice.get("usage"):
# 兼容部分供应商将 usage 放在 choice 内的格式(例如部分 Kimi/Qwen 返回)
last_usage_payload = choice.get("usage")
delta = choice.get("delta", {})
finish_reason = choice.get("finish_reason")
if finish_reason:
last_finish_reason = finish_reason
# 处理思考内容
if "reasoning_content" in delta:
reasoning_content = delta["reasoning_content"]
if reasoning_content:
reasoning_chunks += 1
debug_log(f" 思考内容 #{reasoning_chunks}: {len(reasoning_content)} 字符")
if not thinking_started:
in_thinking = True
thinking_started = True
sender('thinking_start', {})
await asyncio.sleep(0.05)
current_thinking += reasoning_content
sender('thinking_chunk', {'content': reasoning_content})
# 处理正常内容
if "content" in delta:
content = delta["content"]
if content:
content_chunks += 1
debug_log(f" 正式内容 #{content_chunks}: {repr(content[:100] if content else 'None')}")
if in_thinking and not thinking_ended:
in_thinking = False
thinking_ended = True
sender('thinking_end', {'full_content': current_thinking})
await asyncio.sleep(0.1)
expecting_modify = bool(pending_modify) or bool(getattr(web_terminal, "pending_modify_request", None))
expecting_append = bool(pending_append) or bool(getattr(web_terminal, "pending_append_request", None))
if pending_modify:
if not pending_modify.get("start_seen"):
probe_buffer = pending_modify.get("probe_buffer", "") + content
if len(probe_buffer) > 10000:
probe_buffer = probe_buffer[-10000:]
marker = pending_modify.get("start_marker")
marker_index = probe_buffer.find(marker)
if marker_index == -1:
pending_modify["probe_buffer"] = probe_buffer
continue
after_marker = marker_index + len(marker)
remainder = probe_buffer[after_marker:]
pending_modify["buffer"] = remainder
pending_modify["raw_buffer"] = marker + remainder
pending_modify["start_seen"] = True
pending_modify["detected_blocks"] = set()
pending_modify["probe_buffer"] = ""
if pending_modify.get("display_id"):
sender('update_action', {
'id': pending_modify["display_id"],
'status': 'running',
'preparing_id': pending_modify.get("tool_call_id"),
'message': f"正在修改 {pending_modify['path']}..."
})
else:
pending_modify["buffer"] += content
pending_modify["raw_buffer"] += content
if pending_modify.get("start_seen"):
block_text = pending_modify["buffer"]
for match in re.finditer(r"\[replace:(\d+)\]", block_text):
try:
block_index = int(match.group(1))
except ValueError:
continue
detected_blocks = pending_modify.setdefault("detected_blocks", set())
if block_index not in detected_blocks:
detected_blocks.add(block_index)
if pending_modify.get("display_id"):
sender('update_action', {
'id': pending_modify["display_id"],
'status': 'running',
'preparing_id': pending_modify.get("tool_call_id"),
'message': f"正在对 {pending_modify['path']} 进行第 {block_index} 处修改..."
})
if pending_modify.get("start_seen"):
end_pos = pending_modify["buffer"].find(pending_modify["end_marker"])
if end_pos != -1:
pending_modify["end_index"] = end_pos
modify_break_triggered = True
debug_log("检测到<<<END_MODIFY>>>,即将终止流式输出并应用修改")
break
continue
elif expecting_modify:
modify_probe_buffer += content
if len(modify_probe_buffer) > 10000:
modify_probe_buffer = modify_probe_buffer[-10000:]
marker_match = re.search(r"<<<MODIFY:\s*([\s\S]*?)>>>", modify_probe_buffer)
if marker_match:
detected_raw_path = marker_match.group(1)
detected_path = detected_raw_path.strip()
marker_full = marker_match.group(0)
after_marker_index = modify_probe_buffer.find(marker_full) + len(marker_full)
remainder = modify_probe_buffer[after_marker_index:]
modify_probe_buffer = ""
if not detected_path:
debug_log("检测到 MODIFY 起始标记但路径为空,忽略。")
continue
pending_modify = {
"path": detected_path,
"tool_call_id": None,
"buffer": remainder,
"raw_buffer": marker_full + remainder,
"start_marker": marker_full,
"end_marker": "<<<END_MODIFY>>>",
"start_seen": True,
"end_index": None,
"display_id": None,
"detected_blocks": set()
}
if hasattr(web_terminal, "pending_modify_request"):
web_terminal.pending_modify_request = {"path": detected_path}
debug_log(f"直接检测到modify起始标记构建修改缓冲: {detected_path}")
end_pos = pending_modify["buffer"].find(pending_modify["end_marker"])
if end_pos != -1:
pending_modify["end_index"] = end_pos
modify_break_triggered = True
debug_log("检测到<<<END_MODIFY>>>,即将终止流式输出并应用修改")
break
continue
if pending_append:
pending_append["buffer"] += content
if pending_append.get("content_start") is None:
marker_index = pending_append["buffer"].find(pending_append["start_marker"])
if marker_index != -1:
pending_append["content_start"] = marker_index + len(pending_append["start_marker"])
debug_log(f"检测到追加起始标识: {pending_append['start_marker']}")
if pending_append.get("content_start") is not None:
end_index = pending_append["buffer"].find(
pending_append["end_marker"],
pending_append["content_start"]
)
if end_index != -1:
pending_append["end_index"] = end_index
append_break_triggered = True
debug_log("检测到<<<END_APPEND>>>,即将终止流式输出并写入文件")
break
# 继续累积追加内容
continue
elif expecting_append:
append_probe_buffer += content
# 限制缓冲区大小防止过长
if len(append_probe_buffer) > 10000:
append_probe_buffer = append_probe_buffer[-10000:]
marker_match = re.search(r"<<<APPEND:\s*([\s\S]*?)>>>", append_probe_buffer)
if marker_match:
detected_raw_path = marker_match.group(1)
detected_path = detected_raw_path.strip()
if not detected_path:
append_probe_buffer = append_probe_buffer[marker_match.end():]
continue
marker_full = marker_match.group(0)
after_marker_index = append_probe_buffer.find(marker_full) + len(marker_full)
remainder = append_probe_buffer[after_marker_index:]
append_probe_buffer = ""
pending_append = {
"path": detected_path,
"tool_call_id": None,
"buffer": remainder,
"start_marker": marker_full,
"end_marker": "<<<END_APPEND>>>",
"content_start": 0,
"end_index": None,
"display_id": None
}
if hasattr(web_terminal, "pending_append_request"):
web_terminal.pending_append_request = {"path": detected_path}
debug_log(f"直接检测到append起始标记构建追加缓冲: {detected_path}")
# 检查是否立即包含结束标记
if pending_append["buffer"]:
end_index = pending_append["buffer"].find(pending_append["end_marker"], pending_append["content_start"])
if end_index != -1:
pending_append["end_index"] = end_index
append_break_triggered = True
debug_log("检测到<<<END_APPEND>>>,即将终止流式输出并写入文件")
break
continue
if not text_started:
text_started = True
text_streaming = True
sender('text_start', {})
brief_log("模型输出了内容")
await asyncio.sleep(0.05)
if not pending_append:
full_response += content
accumulated_response += content
text_has_content = True
emit_time = time.time()
elapsed = 0.0 if last_text_chunk_time is None else emit_time - last_text_chunk_time
last_text_chunk_time = emit_time
text_chunk_index += 1
log_backend_chunk(
conversation_id,
iteration + 1,
text_chunk_index,
elapsed,
len(content),
content[:32]
)
sender('text_chunk', {
'content': content,
'index': text_chunk_index,
'elapsed': elapsed
})
# 收集工具调用 - 实时发送准备状态
if "tool_calls" in delta:
tool_chunks += 1
for tc in delta["tool_calls"]:
found = False
for existing in tool_calls:
if existing.get("index") == tc.get("index"):
if "function" in tc and "arguments" in tc["function"]:
arg_chunk = tc["function"]["arguments"]
existing_fn = existing.get("function", {})
existing_args = existing_fn.get("arguments", "")
existing_fn["arguments"] = (existing_args or "") + arg_chunk
existing["function"] = existing_fn
combined_args = existing_fn.get("arguments", "")
tool_id = existing.get("id") or tc.get("id")
tool_name = (
existing_fn.get("name")
or tc.get("function", {}).get("name", "")
)
intent_value = extract_intent_from_partial(combined_args)
if (
intent_value
and tool_id
and detected_tool_intent.get(tool_id) != intent_value
):
detected_tool_intent[tool_id] = intent_value
brief_log(f"[intent] 增量提取 {tool_name}: {intent_value}")
sender('tool_intent', {
'id': tool_id,
'name': tool_name,
'intent': intent_value,
'conversation_id': conversation_id
})
debug_log(f" 发送工具意图: {tool_name} -> {intent_value}")
await asyncio.sleep(0.01)
found = True
break
if not found and tc.get("id"):
tool_id = tc["id"]
tool_name = tc.get("function", {}).get("name", "")
arguments_str = tc.get("function", {}).get("arguments", "") or ""
# 新工具检测到,立即发送准备事件
if tool_id not in detected_tools and tool_name:
detected_tools[tool_id] = tool_name
# 尝试提前提取 intent
intent_value = None
if arguments_str:
intent_value = extract_intent_from_partial(arguments_str)
if intent_value:
detected_tool_intent[tool_id] = intent_value
brief_log(f"[intent] 预提取 {tool_name}: {intent_value}")
# 立即发送工具准备中事件
brief_log(f"[tool] 准备调用 {tool_name} (id={tool_id}) intent={intent_value or '-'}")
sender('tool_preparing', {
'id': tool_id,
'name': tool_name,
'message': f'准备调用 {tool_name}...',
'intent': intent_value,
'conversation_id': conversation_id
})
debug_log(f" 发送工具准备事件: {tool_name}")
await asyncio.sleep(0.1)
tool_calls.append({
"id": tool_id,
"index": tc.get("index"),
"type": "function",
"function": {
"name": tool_name,
"arguments": arguments_str
}
})
# 尝试从增量参数中抽取 intent并单独推送
if tool_id and arguments_str:
intent_value = extract_intent_from_partial(arguments_str)
if intent_value and detected_tool_intent.get(tool_id) != intent_value:
detected_tool_intent[tool_id] = intent_value
sender('tool_intent', {
'id': tool_id,
'name': tool_name,
'intent': intent_value,
'conversation_id': conversation_id
})
debug_log(f" 发送工具意图: {tool_name} -> {intent_value}")
await asyncio.sleep(0.01)
debug_log(f" 新工具: {tool_name}")
# 检查是否被停止
client_stop_info = stop_flags.get(client_sid)
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("任务在流处理完成后检测到停止状态")
return
# === API响应完成后只计算输出token ===
if last_usage_payload:
try:
web_terminal.context_manager.apply_usage_statistics(last_usage_payload)
debug_log(
f"Usage统计: prompt={last_usage_payload.get('prompt_tokens', 0)}, "
f"completion={last_usage_payload.get('completion_tokens', 0)}, "
f"total={last_usage_payload.get('total_tokens', 0)}"
)
except Exception as e:
debug_log(f"Usage统计更新失败: {e}")
else:
debug_log("未获取到usage字段跳过token统计更新")
# 流结束后的处理
debug_log(f"\n流结束统计:")
debug_log(f" 总chunks: {chunk_count}")
debug_log(f" 思考chunks: {reasoning_chunks}")
debug_log(f" 内容chunks: {content_chunks}")
debug_log(f" 工具chunks: {tool_chunks}")
debug_log(f" 收集到的思考: {len(current_thinking)} 字符")
debug_log(f" 收集到的正文: {len(full_response)} 字符")
debug_log(f" 收集到的工具: {len(tool_calls)}")
if not append_result["handled"] and pending_append:
append_result = await finalize_pending_append(full_response, True, finish_reason=last_finish_reason)
if not modify_result["handled"] and pending_modify:
modify_result = await finalize_pending_modify(full_response, True, finish_reason=last_finish_reason)
# 结束未完成的流
if in_thinking and not thinking_ended:
sender('thinking_end', {'full_content': current_thinking})
await asyncio.sleep(0.1)
# 确保text_end事件被发送
if text_started and text_has_content and not append_result["handled"] and not modify_result["handled"]:
debug_log(f"发送text_end事件完整内容长度: {len(full_response)}")
sender('text_end', {'full_content': full_response})
await asyncio.sleep(0.1)
text_streaming = False
if full_response.strip():
debug_log(f"流式文本内容长度: {len(full_response)} 字符")
if append_result["handled"]:
append_metadata = append_result.get("assistant_metadata")
append_content_text = append_result.get("assistant_content")
if append_content_text:
web_terminal.context_manager.add_conversation(
"assistant",
append_content_text,
metadata=append_metadata
)
debug_log("💾 增量保存:追加正文快照")
payload_info = append_metadata.get("append_payload") if append_metadata else {}
sender('append_payload', {
'path': payload_info.get("path") or append_result.get("path"),
'forced': payload_info.get("forced", False),
'lines': payload_info.get("lines"),
'bytes': payload_info.get("bytes"),
'tool_call_id': payload_info.get("tool_call_id") or append_result.get("tool_call_id"),
'success': payload_info.get("success", append_result.get("success", False)),
'conversation_id': conversation_id
})
if append_result["tool_content"]:
tool_call_id = append_result.get("tool_call_id") or f"append_{int(time.time() * 1000)}"
system_notice = format_tool_result_notice("append_to_file", tool_call_id, append_result["tool_content"])
web_terminal.context_manager.add_conversation("system", system_notice)
append_result["tool_call_id"] = tool_call_id
debug_log("💾 增量保存append_to_file 工具结果system 通知)")
finish_reason = append_result.get("finish_reason")
path_for_prompt = append_result.get("path")
need_follow_prompt = (
finish_reason == "length" or
append_result.get("forced") or
not append_result.get("success")
)
if need_follow_prompt and path_for_prompt:
prompt_lines = [
f"append_to_file 在处理 {path_for_prompt} 时未完成,需要重新发起写入。"
]
if finish_reason == "length":
prompt_lines.append(
"上一次输出达到系统单次输出上限,已写入的内容已保存。"
)
if append_result.get("forced"):
prompt_lines.append(
"收到的内容缺少 <<<END_APPEND>>> 标记,系统依据流式结束位置落盘。"
)
if not append_result.get("success"):
prompt_lines.append("系统未能识别有效的追加标记。")
prompt_lines.append(
"请再次调用 append_to_file 工具获取新的写入窗口,并在工具调用的输出中遵循以下格式:"
)
prompt_lines.append(f"<<<APPEND:{path_for_prompt}>>>")
prompt_lines.append("...填写剩余正文,如内容已完成可留空...")
prompt_lines.append("<<<END_APPEND>>>")
prompt_lines.append("不要在普通回复中粘贴上述标记,必须通过 append_to_file 工具发送。")
follow_prompt = "\n".join(prompt_lines)
messages.append({
"role": "system",
"content": follow_prompt
})
web_terminal.context_manager.add_conversation("system", follow_prompt)
debug_log("已注入追加任务提示")
if append_result["handled"] and append_result.get("forced") and append_result.get("success"):
mark_force_thinking(web_terminal, reason="append_forced_finish")
if append_result["handled"] and not append_result.get("success"):
sender('system_message', {
'content': f'⚠️ 追加写入失败:{append_result.get("error")}'
})
maybe_mark_failure_from_message(web_terminal, f'⚠️ 追加写入失败:{append_result.get("error")}')
mark_force_thinking(web_terminal, reason="append_failed")
if modify_result["handled"]:
modify_metadata = modify_result.get("assistant_metadata")
modify_content_text = modify_result.get("assistant_content")
if modify_content_text:
web_terminal.context_manager.add_conversation(
"assistant",
modify_content_text,
metadata=modify_metadata
)
debug_log("💾 增量保存:修改正文快照")
payload_info = modify_metadata.get("modify_payload") if modify_metadata else {}
sender('modify_payload', {
'path': payload_info.get("path") or modify_result.get("path"),
'total': payload_info.get("total_blocks") or modify_result.get("total_blocks"),
'completed': payload_info.get("completed") or modify_result.get("completed_blocks"),
'failed': payload_info.get("failed") or modify_result.get("failed_blocks"),
'forced': payload_info.get("forced", modify_result.get("forced", False)),
'success': modify_result.get("success", False),
'conversation_id': conversation_id
})
if modify_result["tool_content"]:
tool_call_id = modify_result.get("tool_call_id") or f"modify_{int(time.time() * 1000)}"
system_notice = format_tool_result_notice("modify_file", tool_call_id, modify_result["tool_content"])
web_terminal.context_manager.add_conversation("system", system_notice)
modify_result["tool_call_id"] = tool_call_id
debug_log("💾 增量保存modify_file 工具结果system 通知)")
path_for_prompt = modify_result.get("path")
failed_blocks = modify_result.get("failed_blocks") or []
need_follow_prompt = modify_result.get("forced") or bool(failed_blocks)
if need_follow_prompt and path_for_prompt:
prompt_lines = [
f"modify_file 在处理 {path_for_prompt} 时未完成,需要重新发起补丁。"
]
if modify_result.get("forced"):
prompt_lines.append(
"刚才的内容缺少 <<<END_MODIFY>>> 标记,系统仅应用了已识别的部分。"
)
if failed_blocks:
failed_text = "".join(str(idx) for idx in failed_blocks)
prompt_lines.append(f"以下补丁未成功:第 {failed_text} 处。")
prompt_lines.append(
"请再次调用 modify_file 工具,并在新的工具调用中按以下模板提供完整补丁:"
)
prompt_lines.append(f"<<<MODIFY:{path_for_prompt}>>>")
prompt_lines.append("[replace:序号]")
prompt_lines.append("<<OLD>>")
prompt_lines.append("...原文(必须逐字匹配,包含全部缩进、空格和换行)...")
prompt_lines.append("<<END>>")
prompt_lines.append("<<NEW>>")
prompt_lines.append("...新内容,可留空表示清空,注意保持结构完整...")
prompt_lines.append("<<END>>")
prompt_lines.append("[/replace]")
prompt_lines.append("<<<END_MODIFY>>>")
prompt_lines.append("请勿在普通回复中直接粘贴补丁,必须通过 modify_file 工具发送。")
follow_prompt = "\n".join(prompt_lines)
messages.append({
"role": "system",
"content": follow_prompt
})
web_terminal.context_manager.add_conversation("system", follow_prompt)
debug_log("已注入修改任务提示")
if modify_result["handled"] and modify_result.get("failed_blocks"):
mark_force_thinking(web_terminal, reason="modify_partial_failure")
if modify_result["handled"] and modify_result.get("forced") and modify_result.get("success"):
mark_force_thinking(web_terminal, reason="modify_forced_finish")
if modify_result["handled"] and not modify_result.get("success"):
error_message = modify_result.get("summary_message") or modify_result.get("error") or "修改操作未成功,请根据提示重新执行。"
sender('system_message', {
'content': f'⚠️ 修改操作存在未完成的内容:{error_message}'
})
maybe_mark_failure_from_message(web_terminal, f'⚠️ 修改操作存在未完成的内容:{error_message}')
mark_force_thinking(web_terminal, reason="modify_failed")
if web_terminal.api_client.last_call_used_thinking and current_thinking:
web_terminal.api_client.current_task_thinking = current_thinking or ""
if web_terminal.api_client.current_task_first_call:
web_terminal.api_client.current_task_first_call = False
update_thinking_after_call(web_terminal)
# 检测是否有格式错误的工具调用
if not tool_calls and full_response and AUTO_FIX_TOOL_CALL and not append_result["handled"] and not modify_result["handled"]:
if detect_malformed_tool_call(full_response):
auto_fix_attempts += 1
if auto_fix_attempts <= AUTO_FIX_MAX_ATTEMPTS:
debug_log(f"检测到格式错误的工具调用,尝试自动修复 (尝试 {auto_fix_attempts}/{AUTO_FIX_MAX_ATTEMPTS})")
fix_message = "你使用了错误的格式输出工具调用。请使用正确的工具调用格式而不是直接输出JSON。根据当前进度继续执行任务。"
sender('system_message', {
'content': f'⚠️ 自动修复: {fix_message}'
})
maybe_mark_failure_from_message(web_terminal, f'⚠️ 自动修复: {fix_message}')
messages.append({
"role": "user",
"content": fix_message
})
await asyncio.sleep(1)
continue
else:
debug_log(f"自动修复尝试已达上限 ({AUTO_FIX_MAX_ATTEMPTS})")
sender('system_message', {
'content': f'⌘ 工具调用格式错误,自动修复失败。请手动检查并重试。'
})
maybe_mark_failure_from_message(web_terminal, '⌘ 工具调用格式错误,自动修复失败。请手动检查并重试。')
break
# 构建助手消息用于API继续对话
assistant_content_parts = []
if full_response:
assistant_content_parts.append(full_response)
elif append_result["handled"] and append_result["assistant_content"]:
assistant_content_parts.append(append_result["assistant_content"])
elif modify_result["handled"] and modify_result.get("assistant_content"):
assistant_content_parts.append(modify_result["assistant_content"])
assistant_content = "\n".join(assistant_content_parts) if assistant_content_parts else ""
# 添加到消息历史用于API继续对话不保存到文件
assistant_message = {
"role": "assistant",
"content": assistant_content,
"tool_calls": tool_calls
}
if current_thinking:
assistant_message["reasoning_content"] = current_thinking
messages.append(assistant_message)
if assistant_content or current_thinking or tool_calls:
web_terminal.context_manager.add_conversation(
"assistant",
assistant_content,
tool_calls=tool_calls if tool_calls else None,
reasoning_content=current_thinking or None
)
# 为下一轮迭代重置流状态标志,但保留 full_response 供上面保存使用
text_streaming = False
text_started = False
text_has_content = False
full_response = ""
if append_result["handled"] and append_result.get("tool_content"):
tool_call_id = append_result.get("tool_call_id") or f"append_{int(time.time() * 1000)}"
system_notice = format_tool_result_notice("append_to_file", tool_call_id, append_result["tool_content"])
messages.append({
"role": "system",
"content": system_notice
})
append_result["tool_call_id"] = tool_call_id
debug_log("已将 append_to_file 工具结果以 system 形式追加到对话上下文")
if modify_result["handled"] and modify_result.get("tool_content"):
tool_call_id = modify_result.get("tool_call_id") or f"modify_{int(time.time() * 1000)}"
system_notice = format_tool_result_notice("modify_file", tool_call_id, modify_result["tool_content"])
messages.append({
"role": "system",
"content": system_notice
})
modify_result["tool_call_id"] = tool_call_id
debug_log("已将 modify_file 工具结果以 system 形式追加到对话上下文")
force_continue = append_result["handled"] or modify_result["handled"]
if force_continue:
if append_result["handled"]:
debug_log("append_to_file 已处理,继续下一轮以让模型返回确认回复")
elif modify_result["handled"]:
debug_log("modify_file 已处理,继续下一轮以让模型返回确认回复")
else:
debug_log("补丁处理完成,继续下一轮以获取模型回复")
continue
if not tool_calls:
debug_log("没有工具调用,结束迭代")
break
# 检查连续相同工具调用
for tc in tool_calls:
tool_name = tc["function"]["name"]
if tool_name == last_tool_name:
consecutive_same_tool[tool_name] += 1
if consecutive_same_tool[tool_name] >= MAX_CONSECUTIVE_SAME_TOOL:
debug_log(f"警告: 连续调用相同工具 {tool_name} 已达 {MAX_CONSECUTIVE_SAME_TOOL}")
sender('system_message', {
'content': f'⚠️ 检测到重复调用 {tool_name} 工具 {MAX_CONSECUTIVE_SAME_TOOL} 次,可能存在循环。'
})
maybe_mark_failure_from_message(web_terminal, f'⚠️ 检测到重复调用 {tool_name} 工具 {MAX_CONSECUTIVE_SAME_TOOL} 次,可能存在循环。')
if consecutive_same_tool[tool_name] >= MAX_CONSECUTIVE_SAME_TOOL + 2:
debug_log(f"终止: 工具 {tool_name} 调用次数过多")
sender('system_message', {
'content': f'⌘ 工具 {tool_name} 重复调用过多,任务终止。'
})
maybe_mark_failure_from_message(web_terminal, f'⌘ 工具 {tool_name} 重复调用过多,任务终止。')
break
else:
consecutive_same_tool.clear()
consecutive_same_tool[tool_name] = 1
last_tool_name = tool_name
# 更新统计
total_tool_calls += len(tool_calls)
# 执行每个工具
for tool_call in tool_calls:
# 检查停止标志
client_stop_info = stop_flags.get(client_sid)
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")
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(snapshot_path)
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))
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 == "write_file_diff":
diff_path = result_data.get("path") or arguments.get("path")
summary = result_data.get("summary") or result_data.get("message")
if summary:
action_message = summary
debug_log(f"write_file_diff 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(result_path)
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))
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)
# 更新UI状态
if function_name in ['focus_file', 'unfocus_file', 'write_file_diff']:
sender('focused_files_update', web_terminal.get_focused_files_info())
if function_name in ['create_file', 'delete_file', 'rename_file', 'create_folder']:
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
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
# 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
)
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)
todo_note = result_data.get("system_note") if isinstance(result_data, dict) else None
if todo_note:
web_terminal.context_manager.add_conversation("system", todo_note)
maybe_mark_failure_from_message(web_terminal, todo_note)
# 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_result_content
})
# 处理图片注入:必须紧跟在对应的 tool 消息之后,且工具成功时才插入
if (
function_name == "view_image"
and getattr(web_terminal, "pending_image_view", None)
and not tool_failed
and (isinstance(result_data, dict) and result_data.get("success") is not False)
):
inj = web_terminal.pending_image_view
web_terminal.pending_image_view = None
injected_text = "这是一条系统控制发送的信息,并非用户主动发送,目的是返回你需要查看的图片。"
# 记录到对话历史
web_terminal.context_manager.add_conversation(
"user",
injected_text,
images=[inj["path"]],
metadata={"system_injected_image": True}
)
# 同步到当前消息列表(直接带多模态 content保证顺序为 tool_call -> tool -> (系统代发)user
content_payload = web_terminal.context_manager._build_content_with_images(
injected_text,
[inj["path"]]
)
messages.append({
"role": "user",
"content": content_payload,
"metadata": {"system_injected_image": True}
})
# 提示前端
sender('system_message', {
'content': f'系统已按模型请求插入图片: {inj.get("path")}'
})
if function_name != 'write_file_diff':
await process_sub_agent_updates(messages, inline=True, after_tool_call_id=tool_call_id)
await asyncio.sleep(0.2)
if tool_failed:
mark_force_thinking(web_terminal, reason=f"{function_name}_failed")
# 标记不再是第一次迭代
is_first_iteration = False
# 最终统计
debug_log(f"\n{'='*40}")
debug_log(f"任务完成统计:")
debug_log(f" 总迭代次数: {total_iterations}")
debug_log(f" 总工具调用: {total_tool_calls}")
debug_log(f" 自动修复尝试: {auto_fix_attempts}")
debug_log(f" 累积响应: {len(accumulated_response)} 字符")
debug_log(f"{'='*40}\n")
# 发送完成事件
sender('task_complete', {
'total_iterations': total_iterations,
'total_tool_calls': total_tool_calls,
'auto_fix_attempts': auto_fix_attempts
})
@socketio.on('send_command')
def handle_command(data):
"""处理系统命令"""
command = data.get('command', '')
username, terminal, _ = get_terminal_for_sid(request.sid)
if not terminal:
emit('error', {'message': 'System not initialized'})
return
record_user_activity(username)
if command.startswith('/'):
command = command[1:]
parts = command.split(maxsplit=1)
cmd = parts[0].lower()
if cmd == "clear":
terminal.context_manager.conversation_history.clear()
if terminal.thinking_mode:
terminal.api_client.start_new_task(force_deep=terminal.deep_thinking_mode)
emit('command_result', {
'command': cmd,
'success': True,
'message': '对话已清除'
})
elif cmd == "status":
status = terminal.get_status()
# 添加终端状态
if terminal.terminal_manager:
terminal_status = terminal.terminal_manager.list_terminals()
status['terminals'] = terminal_status
emit('command_result', {
'command': cmd,
'success': True,
'data': status
})
elif cmd == "terminals":
# 列出终端会话
if terminal.terminal_manager:
result = terminal.terminal_manager.list_terminals()
emit('command_result', {
'command': cmd,
'success': True,
'data': result
})
else:
emit('command_result', {
'command': cmd,
'success': False,
'message': '终端系统未初始化'
})
else:
emit('command_result', {
'command': cmd,
'success': False,
'message': f'未知命令: {cmd}'
})
@app.route('/api/conversations/<conversation_id>/token-statistics', methods=['GET'])
@api_login_required
@with_terminal
def get_conversation_token_statistics(conversation_id, terminal: WebTerminal, workspace: UserWorkspace, username: str):
"""获取特定对话的token统计"""
try:
stats = terminal.context_manager.get_conversation_token_statistics(conversation_id)
if stats:
return jsonify({
"success": True,
"data": stats
})
else:
return jsonify({
"success": False,
"error": "Conversation not found",
"message": f"对话 {conversation_id} 不存在"
}), 404
except Exception as e:
print(f"[API] 获取token统计错误: {e}")
return jsonify({
"success": False,
"error": str(e),
"message": "获取token统计时发生异常"
}), 500
@app.route('/api/conversations/<conversation_id>/tokens', methods=['GET'])
@api_login_required
@with_terminal
def get_conversation_tokens(conversation_id, terminal: WebTerminal, workspace: UserWorkspace, username: str):
"""获取对话的当前完整上下文token数包含所有动态内容"""
try:
current_tokens = terminal.context_manager.get_current_context_tokens(conversation_id)
return jsonify({
"success": True,
"data": {
"total_tokens": current_tokens
}
})
except Exception as e:
return jsonify({
"success": False,
"error": str(e)
}), 500
def calculate_directory_size(root: Path) -> int:
if not root.exists():
return 0
total = 0
stack = [root]
while stack:
current = stack.pop()
try:
with os.scandir(current) as iterator:
for entry in iterator:
try:
if entry.is_symlink():
continue
if entry.is_file(follow_symlinks=False):
total += entry.stat(follow_symlinks=False).st_size
elif entry.is_dir(follow_symlinks=False):
stack.append(Path(entry.path))
except (OSError, FileNotFoundError, PermissionError):
continue
except (NotADirectoryError, FileNotFoundError, PermissionError, OSError):
continue
return total
def iso_datetime_from_epoch(epoch: Optional[float]) -> Optional[str]:
if not epoch:
return None
try:
return datetime.utcfromtimestamp(epoch).replace(microsecond=0).isoformat() + "Z"
except (ValueError, OSError):
return None
def compute_workspace_storage(workspace: UserWorkspace) -> Dict[str, Any]:
project_bytes = calculate_directory_size(workspace.project_path)
data_bytes = calculate_directory_size(workspace.data_dir)
logs_bytes = calculate_directory_size(workspace.logs_dir)
quarantine_bytes = calculate_directory_size(workspace.quarantine_dir)
uploads_bytes = calculate_directory_size(workspace.uploads_dir)
backups_bytes = calculate_directory_size(workspace.data_dir / "backups")
usage_percent = None
if PROJECT_MAX_STORAGE_BYTES:
usage_percent = round(project_bytes / PROJECT_MAX_STORAGE_BYTES * 100, 2) if project_bytes else 0.0
status = "ok"
if usage_percent is not None:
if usage_percent >= 95:
status = "critical"
elif usage_percent >= 80:
status = "warning"
return {
"project_bytes": project_bytes,
"data_bytes": data_bytes,
"logs_bytes": logs_bytes,
"quarantine_bytes": quarantine_bytes,
"uploads_bytes": uploads_bytes,
"backups_bytes": backups_bytes,
"total_bytes": project_bytes + data_bytes + logs_bytes + quarantine_bytes,
"limit_bytes": PROJECT_MAX_STORAGE_BYTES,
"usage_percent": usage_percent,
"status": status,
}
def collect_usage_snapshot(username: str, workspace: UserWorkspace, role: Optional[str]) -> Dict[str, Any]:
tracker = get_or_create_usage_tracker(username, workspace)
stats = tracker.get_stats()
quotas = stats.get("quotas") or {}
windows = stats.get("windows") or {}
snapshot: Dict[str, Any] = {}
for metric in ("fast", "thinking", "search"):
window_meta = windows.get(metric) or {}
quota_meta = quotas.get(metric) or {}
default_limit = QUOTA_DEFAULTS.get("default", {}).get(metric, {}).get("limit", 0)
snapshot[metric] = {
"count": int(window_meta.get("count", 0) or 0),
"window_start": window_meta.get("window_start"),
"reset_at": window_meta.get("reset_at") or quota_meta.get("reset_at"),
"limit": quota_meta.get("limit", default_limit),
}
snapshot["role"] = role or quotas.get("role") or "user"
return snapshot
def _read_token_totals_file(workspace: UserWorkspace) -> Dict[str, int]:
path = workspace.data_dir / "token_totals.json"
if not path.exists():
return {"input_tokens": 0, "output_tokens": 0, "total_tokens": 0}
try:
with open(path, 'r', encoding='utf-8') as fh:
payload = json.load(fh) or {}
input_tokens = int(payload.get("input_tokens") or payload.get("total_input_tokens") or 0)
output_tokens = int(payload.get("output_tokens") or payload.get("total_output_tokens") or 0)
total_tokens = int(payload.get("total_tokens") or (input_tokens + output_tokens))
return {
"input_tokens": input_tokens,
"output_tokens": output_tokens,
"total_tokens": total_tokens,
}
except (OSError, json.JSONDecodeError, ValueError) as exc:
print(f"[admin] 解析 token_totals.json 失败 ({workspace.username}): {exc}")
return {"input_tokens": 0, "output_tokens": 0, "total_tokens": 0}
def _collect_conversation_token_totals(workspace: UserWorkspace) -> Dict[str, int]:
try:
manager = ConversationManager(base_dir=workspace.data_dir)
stats = manager.get_statistics() or {}
token_stats = stats.get("token_statistics") or {}
input_tokens = int(token_stats.get("total_input_tokens") or 0)
output_tokens = int(token_stats.get("total_output_tokens") or 0)
total_tokens = int(token_stats.get("total_tokens") or (input_tokens + output_tokens))
return {
"input_tokens": input_tokens,
"output_tokens": output_tokens,
"total_tokens": total_tokens,
}
except Exception as exc:
print(f"[admin] 读取 legacy token 统计失败 ({workspace.username}): {exc}")
return {"input_tokens": 0, "output_tokens": 0, "total_tokens": 0}
def collect_user_token_statistics(workspace: UserWorkspace) -> Dict[str, int]:
"""汇总单个用户在所有对话中的token累计数据。"""
file_totals = _read_token_totals_file(workspace)
legacy_totals = _collect_conversation_token_totals(workspace)
return {
"input_tokens": max(file_totals["input_tokens"], legacy_totals["input_tokens"]),
"output_tokens": max(file_totals["output_tokens"], legacy_totals["output_tokens"]),
"total_tokens": max(file_totals["total_tokens"], legacy_totals["total_tokens"]),
}
def compute_usage_leaders(users: List[Dict[str, Any]], metric: str, top_n: int = 5) -> List[Dict[str, Any]]:
ranked = sorted(
(
{
"username": entry["username"],
"count": entry.get("usage", {}).get(metric, {}).get("count", 0),
"limit": entry.get("usage", {}).get(metric, {}).get("limit"),
}
for entry in users
),
key=lambda item: item["count"],
reverse=True,
)
return [row for row in ranked[:top_n] if row["count"]]
def collect_user_snapshots(handle_map: Dict[str, Dict[str, Any]]) -> Dict[str, Any]:
user_map = user_manager.list_users()
items: List[Dict[str, Any]] = []
role_counter: Counter = Counter()
usage_totals = {"fast": 0, "thinking": 0, "search": 0}
token_totals = {"input_tokens": 0, "output_tokens": 0, "total_tokens": 0}
storage_total_bytes = 0
quarantine_total_bytes = 0
now = time.time()
for username, record in user_map.items():
workspace = user_manager.ensure_user_workspace(username)
storage = compute_workspace_storage(workspace)
usage = collect_usage_snapshot(username, workspace, record.role)
tokens = collect_user_token_statistics(workspace)
storage_total_bytes += storage["total_bytes"]
quarantine_total_bytes += storage["quarantine_bytes"]
for metric in usage_totals:
usage_totals[metric] += usage.get(metric, {}).get("count", 0)
for key in token_totals:
token_totals[key] += tokens.get(key, 0)
normalized_role = (record.role or "user").lower()
role_counter[normalized_role] += 1
handle = handle_map.get(username)
handle_last = handle.get("last_active") if handle else None
last_active = get_last_active_ts(username, handle_last)
idle_seconds = max(0.0, now - last_active) if last_active else None
items.append({
"username": username,
"email": record.email,
"role": record.role or "user",
"created_at": record.created_at,
"invite_code": record.invite_code,
"storage": storage,
"usage": usage,
"tokens": tokens,
"workspace": {
"project_path": str(workspace.project_path),
"data_dir": str(workspace.data_dir),
"logs_dir": str(workspace.logs_dir),
"uploads_dir": str(workspace.uploads_dir),
},
"status": {
"online": handle is not None,
"container_mode": handle.get("mode") if handle else None,
"last_active": iso_datetime_from_epoch(last_active),
"idle_seconds": idle_seconds,
},
})
items.sort(key=lambda entry: entry["username"])
return {
"items": items,
"roles": dict(role_counter),
"usage_totals": usage_totals,
"token_totals": token_totals,
"storage_total_bytes": storage_total_bytes,
"quarantine_total_bytes": quarantine_total_bytes,
"active_users": sum(1 for entry in items if entry["status"]["online"]),
"total_users": len(items),
}
def collect_container_snapshots(handle_map: Dict[str, Dict[str, Any]]) -> Dict[str, Any]:
items: List[Dict[str, Any]] = []
cpu_values: List[float] = []
mem_percent_values: List[float] = []
total_mem_used = 0
total_mem_limit = 0
total_net_rx = 0
total_net_tx = 0
docker_count = 0
failure_count = 0
now = time.time()
for username, handle in sorted(handle_map.items()):
try:
status = container_manager.get_container_status(username)
except Exception as exc:
status = {
"username": username,
"mode": handle.get("mode"),
"error": str(exc),
"workspace_path": handle.get("workspace_path"),
}
stats = status.get("stats") or {}
state = status.get("state") or {}
if status.get("mode") == "docker":
docker_count += 1
last_active = get_last_active_ts(username, handle.get("last_active"))
idle_seconds = max(0.0, now - last_active) if last_active else None
entry = {
"username": username,
"mode": status.get("mode", handle.get("mode")),
"workspace_path": status.get("workspace_path") or handle.get("workspace_path"),
"container_name": status.get("container_name") or handle.get("container_name"),
"created_at": iso_datetime_from_epoch(status.get("created_at") or handle.get("created_at")),
"last_active": iso_datetime_from_epoch(status.get("last_active") or last_active),
"idle_seconds": idle_seconds,
"stats": stats,
"state": state,
"error": status.get("error"),
}
if entry["error"] or (state and not state.get("running", True)):
failure_count += 1
mem_info = stats.get("memory") or {}
net_info = stats.get("net_io") or {}
cpu_val = stats.get("cpu_percent")
mem_percent = mem_info.get("percent")
mem_used = mem_info.get("used_bytes")
mem_limit = mem_info.get("limit_bytes")
rx_bytes = net_info.get("rx_bytes")
tx_bytes = net_info.get("tx_bytes")
if isinstance(cpu_val, (int, float)):
cpu_values.append(cpu_val)
if isinstance(mem_percent, (int, float)):
mem_percent_values.append(mem_percent)
if isinstance(mem_used, (int, float)):
total_mem_used += mem_used
if isinstance(mem_limit, (int, float)):
total_mem_limit += mem_limit
if isinstance(rx_bytes, (int, float)):
total_net_rx += rx_bytes
if isinstance(tx_bytes, (int, float)):
total_net_tx += tx_bytes
items.append(entry)
active_total = len(handle_map)
summary = {
"active": active_total,
"docker": docker_count,
"host": active_total - docker_count,
"issues": failure_count,
"max_containers": container_manager.max_containers,
"available_slots": max(0, container_manager.max_containers - active_total) if container_manager.max_containers > 0 else None,
"avg_cpu_percent": round(sum(cpu_values) / len(cpu_values), 2) if cpu_values else None,
"avg_mem_percent": round(sum(mem_percent_values) / len(mem_percent_values), 2) if mem_percent_values else None,
"total_mem_used_bytes": total_mem_used,
"total_mem_limit_bytes": total_mem_limit,
"net_rx_bytes": total_net_rx,
"net_tx_bytes": total_net_tx,
}
return {"items": items, "summary": summary}
def parse_upload_line(line: str) -> Optional[Dict[str, Any]]:
marker = "UPLOAD_AUDIT "
idx = line.find(marker)
if idx == -1:
return None
payload = line[idx + len(marker):].strip()
try:
data = json.loads(payload)
except json.JSONDecodeError:
return None
timestamp_value = data.get("timestamp")
timestamp_dt = None
if isinstance(timestamp_value, str):
try:
timestamp_dt = datetime.fromisoformat(timestamp_value)
except ValueError:
timestamp_dt = None
data["_dt"] = timestamp_dt
return data
def collect_upload_events(limit: int = RECENT_UPLOAD_EVENT_LIMIT) -> List[Dict[str, Any]]:
base_dir = (Path(LOGS_DIR).expanduser().resolve() / UPLOAD_SCAN_LOG_SUBDIR).resolve()
events: List[Dict[str, Any]] = []
if not base_dir.exists():
return []
for log_file in sorted(base_dir.glob('*.log')):
buffer: deque = deque(maxlen=limit)
try:
with open(log_file, 'r', encoding='utf-8') as fh:
for line in fh:
if 'UPLOAD_AUDIT' not in line:
continue
buffer.append(line.strip())
except OSError:
continue
for raw in buffer:
event = parse_upload_line(raw)
if event:
events.append(event)
events.sort(key=lambda item: item.get('_dt') or datetime.min, reverse=True)
return events[:limit]
def summarize_upload_events(events: List[Dict[str, Any]], quarantine_total_bytes: int) -> Dict[str, Any]:
now = datetime.utcnow()
cutoff = now - timedelta(hours=24)
last_24h = [evt for evt in events if evt.get('_dt') and evt['_dt'] >= cutoff]
accepted_24h = sum(1 for evt in last_24h if evt.get('accepted'))
blocked_24h = len(last_24h) - accepted_24h
skipped_24h = sum(1 for evt in last_24h if ((evt.get('scan') or {}).get('status') == 'skipped'))
source_counter = Counter((evt.get('source') or 'unknown') for evt in events)
sanitized_events: List[Dict[str, Any]] = []
for evt in events[:RECENT_UPLOAD_FEED_LIMIT]:
sanitized_events.append({k: v for k, v in evt.items() if k != '_dt'})
return {
"stats": {
"total_tracked": len(events),
"last_24h": len(last_24h),
"accepted_last_24h": accepted_24h,
"blocked_last_24h": blocked_24h,
"skipped_scan_last_24h": skipped_24h,
"quarantine_bytes": quarantine_total_bytes,
},
"recent_events": sanitized_events,
"sources": [{"source": src, "count": count} for src, count in source_counter.most_common()],
}
def summarize_invite_codes(codes: List[Dict[str, Any]]) -> Dict[str, int]:
active = consumed = unlimited = 0
for code in codes:
remaining = code.get('remaining')
if remaining is None:
unlimited += 1
elif remaining > 0:
active += 1
else:
consumed += 1
return {
"total": len(codes),
"active": active,
"consumed": consumed,
"unlimited": unlimited,
}
def build_admin_dashboard_snapshot() -> Dict[str, Any]:
handle_map = container_manager.list_containers()
user_data = collect_user_snapshots(handle_map)
container_data = collect_container_snapshots(handle_map)
invite_codes = user_manager.list_invite_codes()
upload_events = collect_upload_events()
uploads_summary = summarize_upload_events(upload_events, user_data['quarantine_total_bytes'])
overview = {
"generated_at": datetime.utcnow().replace(microsecond=0).isoformat() + "Z",
"totals": {
"users": user_data['total_users'],
"active_users": user_data['active_users'],
"containers_active": container_data['summary']['active'],
"containers_max": container_data['summary']['max_containers'],
"available_container_slots": container_data['summary']['available_slots'],
},
"roles": user_data['roles'],
"usage_totals": user_data['usage_totals'],
"token_totals": user_data['token_totals'],
"usage_leaders": {
metric: compute_usage_leaders(user_data['items'], metric)
for metric in ("fast", "thinking", "search")
},
"storage": {
"total_bytes": user_data['storage_total_bytes'],
"per_user_limit_bytes": PROJECT_MAX_STORAGE_BYTES,
"project_max_mb": PROJECT_MAX_STORAGE_MB,
"warning_users": [
{
"username": entry['username'],
"usage_percent": entry['storage']['usage_percent'],
"status": entry['storage']['status'],
}
for entry in user_data['items']
if entry['storage']['status'] != 'ok'
],
},
"containers": container_data['summary'],
"invites": summarize_invite_codes(invite_codes),
"uploads": uploads_summary['stats'],
}
return {
"generated_at": overview['generated_at'],
"overview": overview,
"users": user_data['items'],
"containers": container_data['items'],
"invites": {
"summary": summarize_invite_codes(invite_codes),
"codes": invite_codes,
},
"uploads": uploads_summary,
}
def initialize_system(path: str, thinking_mode: bool = False):
"""初始化系统(多用户版本仅负责写日志和配置)"""
# 清空或创建调试日志
DEBUG_LOG_FILE.parent.mkdir(parents=True, exist_ok=True)
with DEBUG_LOG_FILE.open('w', encoding='utf-8') as f:
f.write(f"调试日志开始 - {datetime.now()}\n")
f.write(f"项目路径: {path}\n")
f.write(f"思考模式: {'思考模式' if thinking_mode else '快速模式'}\n")
f.write(f"自动修复: {'开启' if AUTO_FIX_TOOL_CALL else '关闭'}\n")
f.write(f"最大迭代: {MAX_ITERATIONS_PER_TASK}\n")
f.write(f"最大工具调用: {MAX_TOTAL_TOOL_CALLS}\n")
f.write("="*80 + "\n")
print(f"[Init] 初始化Web系统...")
print(f"[Init] 项目路径: {path}")
print(f"[Init] 运行模式: {'思考模式(首次思考,后续快速)' if thinking_mode else '快速模式(无思考)'}")
print(f"[Init] 自动修复: {'开启' if AUTO_FIX_TOOL_CALL else '关闭'}")
print(f"[Init] 调试日志: {DEBUG_LOG_FILE}")
app.config['DEFAULT_THINKING_MODE'] = thinking_mode
app.config['DEFAULT_RUN_MODE'] = "thinking" if thinking_mode else "fast"
print(f"{OUTPUT_FORMATS['success']} Web系统初始化完成多用户模式")
def run_server(path: str, thinking_mode: bool = False, port: int = DEFAULT_PORT, debug: bool = False):
"""运行Web服务器"""
initialize_system(path, thinking_mode)
start_background_jobs()
socketio.run(
app,
host='0.0.0.0',
port=port,
debug=debug,
use_reloader=debug,
allow_unsafe_werkzeug=True
)
def parse_arguments():
parser = argparse.ArgumentParser(description="AI Agent Web Server")
parser.add_argument(
"--path",
default=str(Path(DEFAULT_PROJECT_PATH).resolve()),
help="项目工作目录(默认使用 config.DEFAULT_PROJECT_PATH"
)
parser.add_argument(
"--port",
type=int,
default=DEFAULT_PORT,
help=f"监听端口(默认 {DEFAULT_PORT}"
)
parser.add_argument(
"--debug",
action="store_true",
help="开发模式,启用 Flask/Socket.IO 热重载"
)
parser.add_argument(
"--thinking-mode",
action="store_true",
help="启用思考模式(首次请求使用 reasoning"
)
return parser.parse_args()
if __name__ == "__main__":
args = parse_arguments()
run_server(
path=args.path,
thinking_mode=args.thinking_mode,
port=args.port,
debug=args.debug
)