From 81115dc23d85a0b0c1b0f79ac43dd224bb761d0a Mon Sep 17 00:00:00 2001 From: figmar Date: Sat, 30 May 2026 14:57:45 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E6=8F=90=E4=BA=A4=EF=BC=9A?= =?UTF-8?q?=E8=AF=86=E6=B5=81=20AI=20=E5=8A=A9=E6=89=8B=E9=A1=B9=E7=9B=AE?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 微信自动回复机器人，基于截图+OCR识别消息，支持关键词规则和 AI（OpenAI/DeepSeek/Dify）自动回复。 技术栈：PySide6 + Flask + Vue3 + RapidOCR + SQLite 注：OCR大模型文件（.onnx / .pdiparams）不纳入版本控制，需单独下载。 🤖 Generated with [Qoder][https://qoder.com] --- .gitignore | 15 + app/__init__.py | 0 app/application/__init__.py | 0 app/application/bot_controller.py | 134 + app/application/services.py | 157 + app/configs/runtime_config.py | 187 + app/infrastructure/__init__.py | 0 app/infrastructure/backend.py | 25 + app/infrastructure/router/__init__.py | 0 app/infrastructure/router/backend/__init__.py | 0 app/infrastructure/router/backend/bot.py | 137 + app/infrastructure/router/backend/messages.py | 72 + app/infrastructure/router/backend/rules.py | 149 + app/infrastructure/router/backend_routes.py | 9 + app/infrastructure/service/__init__.py | 0 .../service/backend/__init__.py | 0 app/infrastructure/service/backend/ai.py | 81 + app/infrastructure/service/backend/config.py | 45 + app/infrastructure/service/backend/db.py | 218 + .../service/logging/log_query_service.py | 141 + .../service/logging/log_schema.py | 86 + .../service/logging/log_service.py | 102 + app/infrastructure/service/wechat/__init__.py | 0 .../service/wechat/chat_snapshot_analyzer.py | 1129 + app/infrastructure/service/wechat/config.py | 124 + app/infrastructure/service/wechat/ocr.py | 346 + .../service/wechat/screenshot.py | 314 + .../service/wechat/session_service.py | 288 + .../service/wechat/unread_session_analyzer.py | 258 + .../wechat_multi_chat_bot copy.py.bak | 504 + app/infrastructure/wechat_multi_chat_bot.py | 373 + app/presentation/__init__.py | 0 app/presentation/main_window.py | 238 + app/presentation/shell.py | 95 + backend_main.py | 46 + frontend/dist/assets/core-DhEqZVGG.js | 1 + frontend/dist/assets/index-Avv0D5es.css | 1 + frontend/dist/assets/index-C4rM3269.js | 2985 +++ frontend/dist/assets/window-B1zSvOyk.js | 1 + frontend/dist/index.html | 14 + frontend/index.html | 13 + frontend/package-lock.json | 1817 ++ frontend/package.json | 25 + frontend/scripts/backend-build.bat | 49 + frontend/src-tauri/.gitignore | 4 + frontend/src-tauri/Cargo.lock | 4941 +++++ frontend/src-tauri/Cargo.toml | 23 + frontend/src-tauri/build.rs | 3 + frontend/src-tauri/capabilities/default.json | 17 + frontend/src-tauri/icons/128x128.png | Bin 0 -> 11059 bytes frontend/src-tauri/icons/128x128@2x.png | Bin 0 -> 23137 bytes frontend/src-tauri/icons/32x32.png | Bin 0 -> 2225 bytes .../src-tauri/icons/Square107x107Logo.png | Bin 0 -> 9202 bytes .../src-tauri/icons/Square142x142Logo.png | Bin 0 -> 12530 bytes 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frontend/src/api/messages.js | 5 + frontend/src/api/rules.js | 17 + frontend/src/api/settings.js | 9 + frontend/src/components/AppTopBar.vue | 55 + frontend/src/components/RuntimeBadge.vue | 18 + frontend/src/composables/useBotStatus.js | 177 + frontend/src/composables/useMessages.js | 25 + frontend/src/composables/useRulesManager.js | 132 + frontend/src/composables/useSettings.js | 44 + frontend/src/composables/useWindowBridge.js | 94 + frontend/src/constants/messageColumns.js | 10 + frontend/src/constants/options.js | 21 + frontend/src/main.js | 33 + frontend/src/styles.css | 299 + frontend/src/utils/datetime.js | 12 + frontend/src/views/LogsView.vue | 228 + frontend/src/views/MessagesView.vue | 31 + frontend/src/views/PanelView.vue | 115 + frontend/src/views/RulesView.vue | 76 + frontend/vite.config.js | 17 + legacy/.htaccess | 0 legacy/README_BOT.md | 143 + legacy/ai_helper.php | 310 + legacy/ai_helper_backup.txt | Bin 0 -> 20540 bytes legacy/api_receive_message.php | 97 + legacy/api_rules.php | 99 + legacy/config.php | 44 + legacy/database.sql | 45 + legacy/db.php | 29 + legacy/install_ocr.bat | 33 + legacy/install_wechat_bot.bat | 37 + legacy/nginx.htaccess | 6 + legacy/run_all.py | 31 + legacy/test_dify.php | 57 + legacy/test_dify_v2.php | 81 + legacy/wechat_bot_optimized.py | 486 + main.py | 62 + requirements.txt | 17 + vendor/paddleocr/.gitkeep | 0 vendor/paddleocr/models/.gitkeep | 0 .../img_textline180_demo_res.jpg | Bin 0 -> 6897 bytes .../img_textline180_demo_res.json | 13 + .../PP-LCNet_x1_0_textline_ori/inference.json | 1 + .../PP-LCNet_x1_0_textline_ori/inference.yml | 46 + .../official_models/PP-OCRv5_server_det/.msc | Bin 0 -> 366 bytes .../official_models/PP-OCRv5_server_det/.mv | 1 + .../PP-OCRv5_server_det/README.md | 220 + .../PP-OCRv5_server_det/config.json | 111 + .../PP-OCRv5_server_det/inference.json | 1 + .../PP-OCRv5_server_det/inference.yml | 53 + .../official_models/PP-OCRv5_server_rec/.msc | Bin 0 -> 366 bytes .../official_models/PP-OCRv5_server_rec/.mv | 1 + .../PP-OCRv5_server_rec/README.md | 219 + .../PP-OCRv5_server_rec/config.json | 18480 ++++++++++++++++ .../PP-OCRv5_server_rec/inference.json | 1 + .../PP-OCRv5_server_rec/inference.yml | 18426 +++++++++++++++ 129 files changed, 56398 insertions(+) create mode 100644 .gitignore create mode 100644 app/__init__.py create mode 100644 app/application/__init__.py create mode 100644 app/application/bot_controller.py create mode 100644 app/application/services.py create mode 100644 app/configs/runtime_config.py create mode 100644 app/infrastructure/__init__.py create mode 100644 app/infrastructure/backend.py create mode 100644 app/infrastructure/router/__init__.py create mode 100644 app/infrastructure/router/backend/__init__.py create mode 100644 app/infrastructure/router/backend/bot.py create mode 100644 app/infrastructure/router/backend/messages.py create mode 100644 app/infrastructure/router/backend/rules.py create mode 100644 app/infrastructure/router/backend_routes.py create mode 100644 app/infrastructure/service/__init__.py create mode 100644 app/infrastructure/service/backend/__init__.py create mode 100644 app/infrastructure/service/backend/ai.py create mode 100644 app/infrastructure/service/backend/config.py create mode 100644 app/infrastructure/service/backend/db.py create mode 100644 app/infrastructure/service/logging/log_query_service.py create mode 100644 app/infrastructure/service/logging/log_schema.py create mode 100644 app/infrastructure/service/logging/log_service.py create mode 100644 app/infrastructure/service/wechat/__init__.py create mode 100644 app/infrastructure/service/wechat/chat_snapshot_analyzer.py create mode 100644 app/infrastructure/service/wechat/config.py create mode 100644 app/infrastructure/service/wechat/ocr.py create mode 100644 app/infrastructure/service/wechat/screenshot.py create mode 100644 app/infrastructure/service/wechat/session_service.py create mode 100644 app/infrastructure/service/wechat/unread_session_analyzer.py create mode 100644 app/infrastructure/wechat_multi_chat_bot copy.py.bak create mode 100644 app/infrastructure/wechat_multi_chat_bot.py create mode 100644 app/presentation/__init__.py create mode 100644 app/presentation/main_window.py create mode 100644 app/presentation/shell.py create mode 100644 backend_main.py create mode 100644 frontend/dist/assets/core-DhEqZVGG.js create mode 100644 frontend/dist/assets/index-Avv0D5es.css create mode 100644 frontend/dist/assets/index-C4rM3269.js create mode 100644 frontend/dist/assets/window-B1zSvOyk.js create mode 100644 frontend/dist/index.html create mode 100644 frontend/index.html create mode 100644 frontend/package-lock.json create mode 100644 frontend/package.json create mode 100644 frontend/scripts/backend-build.bat create mode 100644 frontend/src-tauri/.gitignore create mode 100644 frontend/src-tauri/Cargo.lock create mode 100644 frontend/src-tauri/Cargo.toml create mode 100644 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frontend/src-tauri/icons/icon.ico create mode 100644 frontend/src-tauri/icons/icon.png create mode 100644 frontend/src-tauri/resources/.gitkeep create mode 100644 frontend/src-tauri/src/lib.rs create mode 100644 frontend/src-tauri/src/main.rs create mode 100644 frontend/src-tauri/tauri.conf.json create mode 100644 frontend/src/App.vue create mode 100644 frontend/src/api/bot.js create mode 100644 frontend/src/api/client.js create mode 100644 frontend/src/api/http.js create mode 100644 frontend/src/api/messages.js create mode 100644 frontend/src/api/rules.js create mode 100644 frontend/src/api/settings.js create mode 100644 frontend/src/components/AppTopBar.vue create mode 100644 frontend/src/components/RuntimeBadge.vue create mode 100644 frontend/src/composables/useBotStatus.js create mode 100644 frontend/src/composables/useMessages.js create mode 100644 frontend/src/composables/useRulesManager.js create mode 100644 frontend/src/composables/useSettings.js create mode 100644 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create mode 100644 legacy/nginx.htaccess create mode 100644 legacy/run_all.py create mode 100644 legacy/test_dify.php create mode 100644 legacy/test_dify_v2.php create mode 100644 legacy/wechat_bot_optimized.py create mode 100644 main.py create mode 100644 requirements.txt create mode 100644 vendor/paddleocr/.gitkeep create mode 100644 vendor/paddleocr/models/.gitkeep create mode 100644 vendor/paddleocr/official_models/PP-LCNet_x1_0_textline_ori/img_textline180_demo_res.jpg create mode 100644 vendor/paddleocr/official_models/PP-LCNet_x1_0_textline_ori/img_textline180_demo_res.json create mode 100644 vendor/paddleocr/official_models/PP-LCNet_x1_0_textline_ori/inference.json create mode 100644 vendor/paddleocr/official_models/PP-LCNet_x1_0_textline_ori/inference.yml create mode 100644 vendor/paddleocr/official_models/PP-OCRv5_server_det/.msc create mode 100644 vendor/paddleocr/official_models/PP-OCRv5_server_det/.mv create mode 100644 vendor/paddleocr/official_models/PP-OCRv5_server_det/README.md create mode 100644 vendor/paddleocr/official_models/PP-OCRv5_server_det/config.json create mode 100644 vendor/paddleocr/official_models/PP-OCRv5_server_det/inference.json create mode 100644 vendor/paddleocr/official_models/PP-OCRv5_server_det/inference.yml create mode 100644 vendor/paddleocr/official_models/PP-OCRv5_server_rec/.msc create mode 100644 vendor/paddleocr/official_models/PP-OCRv5_server_rec/.mv create mode 100644 vendor/paddleocr/official_models/PP-OCRv5_server_rec/README.md create mode 100644 vendor/paddleocr/official_models/PP-OCRv5_server_rec/config.json create mode 100644 vendor/paddleocr/official_models/PP-OCRv5_server_rec/inference.json create mode 100644 vendor/paddleocr/official_models/PP-OCRv5_server_rec/inference.yml diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..c4f2442 --- /dev/null +++ b/.gitignore @@ -0,0 +1,15 @@ +ocr_debug_images/* +logs/* +frontend/node_modules/* +frontend/src-tauri/resources/* +!frontend/src-tauri/resources/.gitkeep +app/resources/ocr_models/variants/* +# 大型模型文件（需单独下载） +app/resources/ocr_models/*.onnx +vendor/paddleocr/official_models/**/*.pdiparams +.build/* + +.venv/* +**/__pycache__/* + + diff --git a/app/__init__.py b/app/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/app/application/__init__.py b/app/application/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/app/application/bot_controller.py b/app/application/bot_controller.py new file mode 100644 index 0000000..9b7e128 --- /dev/null +++ b/app/application/bot_controller.py @@ -0,0 +1,134 @@ +import os +import threading +import traceback +from datetime import datetime + +from app.infrastructure.wechat_multi_chat_bot import WechatMultiChatBot + + +class BotController: + def __init__(self): + self._lock = threading.RLock() + self._thread = None + self._bot = None + self._status = "stopped" + self._last_error = "" + self._started_at = "" + self._stopped_at = "" + self._listeners = {} + self._listener_seq = 0 + + def start(self, backend_url): + with self._lock: + if self._thread and self._thread.is_alive(): + return self._status_payload_locked() + self._status = "starting" + self._last_error = "" + self._stopped_at = "" + os.environ["BACKEND_URL"] = backend_url + self._thread = threading.Thread(target=self._run, daemon=True, name="WechatBotThread") + self._thread.start() + status = self._status_payload_locked() + listeners = list(self._listeners.values()) + self._notify_status_listeners(listeners, status) + return status + + def stop(self): + with self._lock: + if not self._thread or not self._thread.is_alive(): + self._status = "stopped" + self._bot = None + self._stopped_at = self._now() + status = self._status_payload_locked() + listeners = list(self._listeners.values()) + self._notify_status_listeners(listeners, status) + return status + self._status = "stopping" + bot = self._bot + status = self._status_payload_locked() + listeners = list(self._listeners.values()) + self._notify_status_listeners(listeners, status) + if bot: + bot.stop() + return status + + def status(self): + listeners = None + with self._lock: + if self._status in {"running", "starting", "stopping"} and self._thread and not self._thread.is_alive(): + if self._status != "error": + self._status = "stopped" + self._bot = None + self._stopped_at = self._stopped_at or self._now() + listeners = list(self._listeners.values()) + status = self._status_payload_locked() + if listeners is not None: + self._notify_status_listeners(listeners, status) + return status + + def add_status_listener(self, callback, emit_initial=False): + with self._lock: + self._listener_seq += 1 + listener_id = self._listener_seq + self._listeners[listener_id] = callback + status = self._status_payload_locked() + if emit_initial: + try: + callback(status) + except Exception: + pass + return listener_id + + def remove_status_listener(self, listener_id): + with self._lock: + self._listeners.pop(listener_id, None) + + def _run(self): + try: + bot = WechatMultiChatBot() + with self._lock: + self._bot = bot + self._status = "running" + self._started_at = self._now() + status = self._status_payload_locked() + listeners = list(self._listeners.values()) + self._notify_status_listeners(listeners, status) + bot.run_forever() + with self._lock: + self._status = "stopped" + self._bot = None + self._stopped_at = self._now() + status = self._status_payload_locked() + listeners = list(self._listeners.values()) + self._notify_status_listeners(listeners, status) + except Exception: + with self._lock: + self._status = "error" + self._bot = None + self._last_error = traceback.format_exc() + self._stopped_at = self._now() + status = self._status_payload_locked() + listeners = list(self._listeners.values()) + self._notify_status_listeners(listeners, status) + + def _status_payload_locked(self): + return { + "status": self._status, + "running": self._status == "running", + "last_error": self._last_error, + "started_at": self._started_at, + "stopped_at": self._stopped_at, + } + + def _notify_status_listeners(self, listeners, status): + for callback in listeners: + try: + callback(status) + except Exception: + pass + + def _now(self): + return datetime.now().strftime("%Y-%m-%d %H:%M:%S") + + +bot_controller = BotController() diff --git a/app/application/services.py b/app/application/services.py new file mode 100644 index 0000000..e030618 --- /dev/null +++ b/app/application/services.py @@ -0,0 +1,157 @@ +import os +import socket +import subprocess +import sys +import time +from pathlib import Path + +import requests + + +class AppConfig: + def __init__(self): + self.project_root = Path(__file__).resolve().parents[2] + self.runtime_mode = self._normalize_runtime_mode(os.getenv("OPENCLAW_RUNTIME_MODE") or os.getenv("OPENCLAW_BACKEND_MODE")) + self.venv_root = self.project_root / ".venv" + self.venv_python = self.venv_root / "Scripts" / "python.exe" + self.venv_pythonw = self.venv_root / "Scripts" / "pythonw.exe" + self.host = os.getenv("APP_HOST", "127.0.0.1") + self.port = int(os.getenv("APP_PORT", "5000")) + + def _normalize_runtime_mode(self, value): + mode = (value or "").strip().lower() + if mode in {"release", "prod", "production", "bundle", "packaged"}: + return "release" + return "dev" + + @property + def base_url(self): + return f"http://{self.host}:{self.port}" + + @property + def python_executable(self): + return Path(sys.executable).resolve() + + @property + def python_prefix(self): + return Path(sys.prefix).resolve() + + @property + def is_release_mode(self): + return self.runtime_mode == "release" + + @property + def backend_entry(self): + return self.project_root / "backend_main.py" + + @property + def is_running_in_project_venv(self): + if self.is_release_mode: + return False + try: + if self.python_prefix == self.venv_root.resolve(): + return True + allowed_targets = { + self.venv_python.resolve(), + self.venv_pythonw.resolve(), + } + return self.python_executable in allowed_targets + except Exception: + return False + + +class BackendRuntime: + def __init__(self, config=None): + self.config = config or AppConfig() + + @property + def host(self): + return self.config.host + + @property + def port(self): + return self.config.port + + @property + def base_url(self): + return self.config.base_url + + @property + def backend_entry(self): + return self.config.backend_entry + + def is_backend_alive(self, host=None, port=None, timeout=0.4): + sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) + sock.settimeout(timeout) + try: + return sock.connect_ex((host or self.host, port or self.port)) == 0 + finally: + sock.close() + + def launch_backend_process(self): + if self.config.is_release_mode: + raise RuntimeError("当前运行模式为发布态，不能从 Python 壳层再启动 backend_main.py") + backend_python = self.config.venv_python + if not backend_python.exists(): + raise RuntimeError(f"未找到后端解释器: {backend_python}") + backend_entry = self.backend_entry + if not backend_entry.exists(): + raise RuntimeError(f"未找到后端入口: {backend_entry}") + env = os.environ.copy() + env["OPENCLAW_PROJECT_VENV_REEXEC"] = "1" + env.setdefault("OPENCLAW_BACKEND_MODE", "dev") + env.setdefault("OPENCLAW_RUNTIME_MODE", "dev") + creationflags = getattr(subprocess, "CREATE_NO_WINDOW", 0) + return subprocess.Popen( + [str(backend_python), str(backend_entry)], + cwd=str(self.config.project_root), + env=env, + stdout=subprocess.DEVNULL, + stderr=subprocess.DEVNULL, + creationflags=creationflags, + ) + + def terminate_backend_process(self, process, timeout=3): + if process is None or process.poll() is not None: + return + try: + process.terminate() + process.wait(timeout=timeout) + except Exception: + if process.poll() is None: + process.kill() + + +class FrontendRuntime: + def __init__(self, config=None, backend_runtime=None): + self.config = config or AppConfig() + self.backend_runtime = backend_runtime or BackendRuntime(self.config) + self.frontend_dev_url = os.getenv("FRONTEND_DEV_URL", "http://127.0.0.1:5173").strip().rstrip("/") + self.frontend_dist_index = self.config.project_root / "frontend" / "dist" / "index.html" + self.backend_wait_timeout_ms = 15000 + self.backend_wait_interval_ms = 200 + + def resolve_frontend_entry_url(self, backend_url): + if self.frontend_dev_url: + try: + requests.get(self.frontend_dev_url, timeout=1.2) + return self.frontend_dev_url + except Exception: + pass + if self.frontend_dist_index.exists(): + return backend_url.rstrip("/") + "/index.html" + return backend_url.rstrip("/") + "/admin.html" + + def wait_for_backend(self, process=None, timeout_ms=None, interval_ms=None): + timeout_ms = timeout_ms or self.backend_wait_timeout_ms + interval_ms = interval_ms or self.backend_wait_interval_ms + started_at = time.time() * 1000 + while True: + if self.backend_runtime.is_backend_alive(): + return True, "" + if process is not None and process.poll() is not None: + return False, f"独立后台进程已退出，退出码: {process.returncode}" + elapsed = time.time() * 1000 - started_at + if elapsed >= timeout_ms: + return False, f"后台启动超时，{int(elapsed)}ms 内未监听 {self.backend_runtime.host}:{self.backend_runtime.port}" + time.sleep(interval_ms / 1000.0) diff --git a/app/configs/runtime_config.py b/app/configs/runtime_config.py new file mode 100644 index 0000000..c91c094 --- /dev/null +++ b/app/configs/runtime_config.py @@ -0,0 +1,187 @@ +import os +from typing import Any + +DEFAULT_CONFIG: dict[str, Any] = { + # 应用展示名称，同时作为 AppData 默认目录名的一部分 + "APP_NAME": "AiShiliu", + # Flask 后端监听地址 + "APP_HOST": "127.0.0.1", + # Flask 后端监听端口 + "APP_PORT": 5000, + # 应用默认时区 + "APP_TIMEZONE": "Asia/Shanghai", + # 已构建前端静态资源目录，留空时自动回退到项目默认目录 + "FRONTEND_STATIC_DIR": "", + + # 日志总开关 + "LOG_ENABLED": True, + # 日志级别 + "LOG_LEVEL": "INFO", + # 是否写文本日志 + "LOG_TEXT_ENABLED": True, + # 是否写JSON日志 + "LOG_JSON_ENABLED": True, + # 单文件滚动大小（MB） + "LOG_ROTATE_MB": 5, + # 滚动保留份数 + "LOG_BACKUP_COUNT": 7, + + # MySQL 主机地址（预留给后续鉴权等在线能力） + "DB_HOST": "127.0.0.1", + # MySQL 端口（预留） + "DB_PORT": 3306, + # MySQL 数据库名（预留） + "DB_NAME": "ai_shiliu", + # MySQL 用户名（预留） + "DB_USER": "ai_shiliu", + # MySQL 密码（预留） + "DB_PASS": "", + # MySQL 字符集（预留） + "DB_CHARSET": "utf8mb4", + + # AI 提供方（openai/deepseek/dify） + "AI_PROVIDER": "dify", + # OpenAI 接口密钥 + "OPENAI_API_KEY": "YOUR_OPENAI_API_KEY_HERE", + # OpenAI API 基础地址 + "OPENAI_API_BASE": "https://api.openai.com/v1", + # OpenAI 默认模型 + "OPENAI_MODEL": "gpt-4.1-mini", + # DeepSeek 接口密钥 + "DEEPSEEK_API_KEY": "", + # DeepSeek API 基础地址 + "DEEPSEEK_API_BASE": "https://api.deepseek.com", + # DeepSeek 默认模型 + "DEEPSEEK_MODEL": "deepseek-chat", + # Dify 接口密钥 + "DIFY_API_KEY": "app-a9dofsiQi4e157uDYTx8Lrja", + # Dify API 基础地址 + "DIFY_API_BASE": "http://47.92.48.126/v1", + # Dify 用户标识 + "DIFY_USER": "wechat_user", + + + + # 百度 OCR API Key + "BAIDU_API_KEY": "ElIQN30iAqpEGi9zv0VlrtQX", + # 百度 OCR Secret Key + "BAIDU_SECRET_KEY": "7wrO2wDTx7FehuelgG0NCBDFOklnqSz0", + # OCR 引擎（baidu/rapid） + "OCR_PROVIDER": "rapid", + + # 微信机器人上报后端消息接口 + "BACKEND_URL": "http://127.0.0.1:5000/api/messages/receive", + # 轮询主循环间隔（秒） + "BOT_LOOP_INTERVAL": 3, + # 点击联系人后等待（秒） + "BOT_CLICK_AFTER_DELAY": 1.2, + # 切换会话后读取标题等待（秒） + "BOT_TITLE_AFTER_DELAY": 1.0, + # 联系人切换节流等待（秒） + "BOT_CONTACT_SWITCH_DELAY": 1.0, + # 主循环异常后的重试等待（秒） + "BOT_LOOP_ERROR_DELAY": 3.0, + + # 微信窗口目标宽度 + "WECHAT_WINDOW_TARGET_WIDTH": 1080, + # 微信窗口目标高度 + "WECHAT_WINDOW_TARGET_HEIGHT": 820, + # 微信窗口目标左侧坐标 + "WECHAT_WINDOW_TARGET_LEFT": 120, + # 微信窗口目标顶部坐标 + "WECHAT_WINDOW_TARGET_TOP": 80, + + # 是否保存 OCR 调试截图 + "OCR_SAVE_IMAGES": True, + + # 联系人行高（用于定位） + "CONTACT_ROW_HEIGHT": 64, + # 联系人列宽（用于定位） + "CONTACT_ROW_WIDTH": 240, + # 联系人列表左偏移 + "CONTACT_LIST_LEFT_OFFSET": 68, + # 联系人列表上偏移 + "CONTACT_LIST_TOP_OFFSET": 82, + # 联系人列表下偏移 + "CONTACT_LIST_BOTTOM_OFFSET": 0, + + # 会话名区域左偏移 + "SESSION_NAME_LEFT_OFFSET": 48, + # 会话名区域上偏移 + "SESSION_NAME_TOP_OFFSET": 8, + # 会话名区域宽度 + "SESSION_NAME_WIDTH": 140, + # 会话名区域高度 + "SESSION_NAME_HEIGHT": 24, + # 会话名 OCR 放大倍数 + "SESSION_NAME_OCR_SCALE": 4, + # 会话名 OCR 额外放大倍数 + "SESSION_NAME_OCR_EXTRA_SCALE": 6, + + # 聊天区截图左偏移 + "CHAT_CAPTURE_LEFT_OFFSET": 310, + # 聊天区截图上偏移 + "CHAT_CAPTURE_TOP_OFFSET": 70, + # 聊天区截图宽度 + "CHAT_CAPTURE_WIDTH": 750, + # 聊天区截图高度 + "CHAT_CAPTURE_HEIGHT": 550, + + # 顶部惩罚权重比例 + "OCR_TOP_PENALTY_RATIO": 0.18, + # 顶部惩罚二值化系数 + "OCR_TOP_PENALTY_BIN_FACTOR": 2.0, + # 顶部惩罚颜色系数 + "OCR_TOP_PENALTY_COLOR_FACTOR": 2.2, + + # 标题 OCR 区域左偏移（保留较大的方案） + "TITLE_OCR_AREA_LEFT_OFFSET": 310, + # 标题 OCR 区域上偏移（保留较大的方案） + "TITLE_OCR_AREA_TOP_OFFSET": 0, + # 标题 OCR 区域宽度（保留较大的方案） + "TITLE_OCR_AREA_WIDTH": 600, + # 标题 OCR 区域高度（保留较大的方案） + "TITLE_OCR_AREA_HEIGHT": 70, +} + + +def _raw_value(key: str) -> Any: + env_value = os.getenv(key) + if env_value is not None: + return env_value + return DEFAULT_CONFIG.get(key) + + +def get_str(key: str, default: str = "") -> str: + value = _raw_value(key) + if value is None: + return default + return str(value) + + +def get_int(key: str, default: int = 0) -> int: + value = _raw_value(key) + if value is None or value == "": + return default + return int(value) + + +def get_float(key: str, default: float = 0.0) -> float: + value = _raw_value(key) + if value is None or value == "": + return default + return float(value) + + +def get_bool(key: str, default: bool = False) -> bool: + value = _raw_value(key) + if value is None: + return default + if isinstance(value, bool): + return value + normalized = str(value).strip().lower() + if normalized in {"1", "true", "yes", "on"}: + return True + if normalized in {"0", "false", "no", "off"}: + return False + return default diff --git a/app/infrastructure/__init__.py b/app/infrastructure/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/app/infrastructure/backend.py b/app/infrastructure/backend.py new file mode 100644 index 0000000..75207ce --- /dev/null +++ b/app/infrastructure/backend.py @@ -0,0 +1,25 @@ + +from app.infrastructure.service.backend.config import app +from app.infrastructure.service.backend.db import init_db +from app.infrastructure.router.backend_routes import register_routes +from app.infrastructure.service.logging.log_service import init_logging, log_event, new_trace_id + + +init_logging() +register_routes(app) + + +def init_backend(): + trace_id = new_trace_id("backend") + try: + init_db() + log_event("INFO", "db", "db.init", trace_id, "boot", "ok", "数据库初始化成功") + except Exception as err: + log_event("ERROR", "db", "db.error", trace_id, "boot", "fail", "数据库初始化失败", reason=type(err).__name__) + raise + return app + + +def start_backend(host="127.0.0.1", port=5000, threaded=True): + backend_app = init_backend() + backend_app.run(host=host, port=port, threaded=threaded) diff --git a/app/infrastructure/router/__init__.py b/app/infrastructure/router/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/app/infrastructure/router/backend/__init__.py b/app/infrastructure/router/backend/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/app/infrastructure/router/backend/bot.py b/app/infrastructure/router/backend/bot.py new file mode 100644 index 0000000..3129269 --- /dev/null +++ b/app/infrastructure/router/backend/bot.py @@ -0,0 +1,137 @@ +import json +import queue + +from flask import Response, jsonify, request, stream_with_context + +from app.application.bot_controller import bot_controller +from app.infrastructure.service.backend.db import set_setting +from app.infrastructure.service.logging.log_query_service import clear_logs, query_event_json, query_events, query_summary, query_trace +from app.infrastructure.service.logging.log_service import log_event, new_trace_id + + +def _sync_runtime_settings(status): + current = (status.get("status") or "stopped").strip().lower() + running = current == "running" + transitional = current in {"starting", "stopping"} + errored = current == "error" + if running: + set_setting("listener_enabled", "1") + set_setting("listener_runtime_status", "running") + elif transitional: + set_setting("listener_runtime_status", current) + elif errored: + set_setting("listener_enabled", "0") + set_setting("listener_runtime_status", "error") + else: + set_setting("listener_enabled", "0") + set_setting("listener_runtime_status", "stopped") + + +def register_bot_routes(app): + def _stream_payload(status): + return f"event: status\ndata: {json.dumps({'success': True, **status}, ensure_ascii=False)}\n\n" + + @app.route("/api/bot/status", methods=["GET"]) + def api_bot_status(): + trace_id = new_trace_id("api") + status = bot_controller.status() + _sync_runtime_settings(status) + log_event("INFO", "api", "api.bot.status", trace_id, "status", "ok", "查询监听状态成功", extra={"status": status.get("status")}) + return jsonify({"success": True, **status}) + + @app.route("/api/bot/status/stream", methods=["GET"]) + def api_bot_status_stream(): + status_queue = queue.Queue(maxsize=8) + + def on_status(status): + _sync_runtime_settings(status) + try: + status_queue.put_nowait(status) + except queue.Full: + try: + status_queue.get_nowait() + except queue.Empty: + pass + try: + status_queue.put_nowait(status) + except queue.Full: + pass + + listener_id = bot_controller.add_status_listener(on_status, emit_initial=True) + + @stream_with_context + def generate(): + try: + yield "retry: 2000\n\n" + while True: + try: + status = status_queue.get(timeout=15) + yield _stream_payload(status) + except queue.Empty: + yield "event: ping\ndata: {}\n\n" + finally: + bot_controller.remove_status_listener(listener_id) + + return Response(generate(), mimetype="text/event-stream", headers={ + "Cache-Control": "no-cache", + "Connection": "keep-alive", + "X-Accel-Buffering": "no", + }) + + @app.route("/api/logs/v2/events", methods=["GET"]) + def api_logs_v2_events(): + trace_id = request.args.get("trace_id") or "" + module = request.args.get("module") or "" + level = request.args.get("level") or "" + event = request.args.get("event") or "" + start_ts = request.args.get("start_ts") or "" + end_ts = request.args.get("end_ts") or "" + keyword = request.args.get("keyword") or "" + page = request.args.get("page", 1) + size = request.args.get("size", 50) + payload = query_events(module=module or None, level=level or None, event=event or None, trace_id=trace_id or None, start_ts=start_ts or None, end_ts=end_ts or None, keyword=keyword or None, page=page, size=size) + return jsonify({"success": True, **payload}) + + @app.route("/api/logs/v2/trace/", methods=["GET"]) + def api_logs_v2_trace(trace_id): + items = query_trace(trace_id) + return jsonify({"success": True, "trace_id": trace_id, "items": items}) + + @app.route("/api/logs/v2/summary", methods=["GET"]) + def api_logs_v2_summary(): + limit = request.args.get("limit", 300) + payload = query_summary(limit=limit) + return jsonify({"success": True, **payload}) + + @app.route("/api/logs/v2/event/", methods=["GET"]) + def api_logs_v2_event(event_id): + item = query_event_json(event_id) + if not item: + return jsonify({"success": False, "error": "event_not_found"}), 404 + return jsonify({"success": True, "item": item}) + + @app.route("/api/logs/v2/clear", methods=["POST"]) + def api_logs_v2_clear(): + body = request.get_json(silent=True) or {} + module = (body.get("module") or request.values.get("module") or request.args.get("module") or "").strip() + payload = clear_logs(module=module or None) + return jsonify({"success": True, **payload}) + + @app.route("/api/bot/start", methods=["POST"]) + def api_bot_start(): + trace_id = new_trace_id("api") + backend_url = (request.values.get("backend_url") or "").strip() + if not backend_url: + backend_url = request.host_url.rstrip("/") + "/api/messages/receive" + status = bot_controller.start(backend_url) + _sync_runtime_settings(status) + log_event("INFO", "api", "api.bot.start", trace_id, "start", "ok", "启动监听请求已处理", extra={"status": status.get("status"), "backend_url": backend_url}) + return jsonify({"success": True, **status}) + + @app.route("/api/bot/stop", methods=["POST"]) + def api_bot_stop(): + trace_id = new_trace_id("api") + status = bot_controller.stop() + _sync_runtime_settings(status) + log_event("INFO", "api", "api.bot.stop", trace_id, "stop", "ok", "停止监听请求已处理", extra={"status": status.get("status")}) + return jsonify({"success": True, **status}) diff --git a/app/infrastructure/router/backend/messages.py b/app/infrastructure/router/backend/messages.py new file mode 100644 index 0000000..7ce26cc --- /dev/null +++ b/app/infrastructure/router/backend/messages.py @@ -0,0 +1,72 @@ +from datetime import datetime + +from flask import jsonify, request + +from app.infrastructure.service.backend.ai import call_ai +from app.infrastructure.service.backend.db import find_rule_reply, get_conn, get_setting +from app.infrastructure.service.logging.log_service import log_event, new_trace_id + + +def register_message_routes(app): + @app.route("/api/messages/receive", methods=["POST"]) + def api_receive_message(): + trace_id = new_trace_id("api") + data = request.get_json(silent=True) or request.form.to_dict() or {} + content = (data.get("content") or "").strip() + wx_user_id = (data.get("wx_user_id") or "").strip() + wx_nickname = (data.get("wx_nickname") or "").strip() + is_friend_request = int(data.get("is_friend_request") or 0) + ocr_confidence = str(data.get("ocr_confidence") or "").strip() + ocr_bubble_side = str(data.get("ocr_bubble_side") or "").strip() + if not content and not is_friend_request: + log_event("WARNING", "api", "api.messages.receive", trace_id, "validate", "failed", "消息内容为空且非好友请求", reason="content_empty") + return jsonify({"error": "content is empty"}), 400 + + conn = get_conn() + now = datetime.now().strftime("%Y-%m-%d %H:%M:%S") + try: + with conn.cursor() as cur: + cur.execute("INSERT INTO messages (wx_user_id, wx_nickname, direction, content, is_friend_request, reply_strategy, reply_reason, ocr_confidence, ocr_bubble_side, created_at) VALUES (%s, %s, 'in', %s, %s, %s, %s, %s, %s, %s)", (wx_user_id, wx_nickname, content, is_friend_request, "none", "received", ocr_confidence, ocr_bubble_side, now)) + in_msg_id = cur.lastrowid + + auto_on = str(get_setting("auto_reply_enabled", "1") or "1").strip().lower() in ["1", "true", "yes", "on"] + full_auto_on = str(get_setting("full_auto_reply_enabled", "0") or "0").strip().lower() in ["1", "true", "yes", "on"] + reply_text = "" + used_rule_id = None + reply_strategy = "none" + reply_reason = "" + + if not auto_on: + reply_reason = "auto_reply_disabled" + else: + rule = find_rule_reply(content) + if rule: + reply_text = (rule.get("reply_text") or "").strip() + used_rule_id = rule.get("id") + reply_strategy = "rule" + reply_reason = f"rule_hit:{used_rule_id}" + elif full_auto_on: + reply_strategy = "full_auto" + reply_reason = "full_auto_enabled" + reply_text = call_ai(content, wx_user_id) + else: + reply_reason = "rule_miss" + + should_reply = auto_on and bool(reply_text) + + reply_msg_id = None + if should_reply: + is_ai_reply = 0 if used_rule_id else 1 + cur.execute("INSERT INTO messages (wx_user_id, wx_nickname, direction, content, is_ai_reply, rule_id, reply_strategy, reply_reason, created_at) VALUES (%s, %s, 'out', %s, %s, %s, %s, %s, %s)", (wx_user_id, wx_nickname, reply_text, is_ai_reply, used_rule_id, reply_strategy, reply_reason, now)) + reply_msg_id = cur.lastrowid + conn.commit() + except Exception as exc: + conn.rollback() + log_event("ERROR", "api", "api.messages.receive", trace_id, "persist", "failed", "消息入库或回复处理失败", reason="db_error", extra={"error": str(exc)}) + raise + finally: + conn.close() + + log_event("INFO", "audit", "audit.decision", trace_id, "decision", "ok", "回复决策完成", reason=reply_reason or "none", extra={"wx_user_id": wx_user_id, "strategy": reply_strategy, "should_reply": should_reply, "rule_id": used_rule_id or ""}) + log_event("INFO", "api", "api.messages.receive", trace_id, "done", "ok", "消息处理完成", extra={"in_message_id": in_msg_id, "reply_message_id": reply_msg_id or "", "should_reply": should_reply}) + return jsonify({"success": True, "should_reply": should_reply, "reply_text": reply_text, "in_message_id": in_msg_id, "reply_message_id": reply_msg_id}) diff --git a/app/infrastructure/router/backend/rules.py b/app/infrastructure/router/backend/rules.py new file mode 100644 index 0000000..9e1b638 --- /dev/null +++ b/app/infrastructure/router/backend/rules.py @@ -0,0 +1,149 @@ +from datetime import datetime + +from flask import jsonify, request, send_from_directory + +from app.application.bot_controller import bot_controller +from app.infrastructure.service.backend.config import ASSETS_DIR, STATIC_DIR +from app.infrastructure.service.backend.db import SQLITE_DB_PATH, get_conn, get_setting, set_setting +from app.infrastructure.service.logging.log_service import log_event, new_trace_id + +LOCAL_SETTING_DEFAULTS = { + "auto_reply_enabled": "1", + "listener_enabled": "0", + "listener_runtime_status": "stopped", + "full_auto_reply_enabled": "0", + "reply_fallback_mode": "ai", +} +LOCAL_SETTING_CACHE = {} + + +def _load_local_settings(force=False): + if LOCAL_SETTING_CACHE and not force: + return + for key, default in LOCAL_SETTING_DEFAULTS.items(): + LOCAL_SETTING_CACHE[key] = str(get_setting(key, default)) + + + +def _get_local_setting(key, default=None): + _load_local_settings(force=True) + return LOCAL_SETTING_CACHE.get(key, default) + + + +def _set_local_setting(key, value): + v = str(value) + LOCAL_SETTING_CACHE[key] = v + set_setting(key, v) + + + +def _frontend_index_available(): + return STATIC_DIR != ASSETS_DIR and (STATIC_DIR / "index.html").exists() + + + +def register_rule_routes(app): + @app.route("/") + @app.route("/index.html") + def frontend_page(): + if _frontend_index_available(): + return send_from_directory(STATIC_DIR, "index.html") + return send_from_directory(ASSETS_DIR, "admin.html") + + @app.route("/admin.html") + def admin_page(): + return send_from_directory(ASSETS_DIR, "admin.html") + + @app.route("/api/rules", methods=["GET", "POST"]) + def api_rules(): + action = request.values.get("action", "list") + conn = get_conn() + now = datetime.now().strftime("%Y-%m-%d %H:%M:%S") + try: + with conn.cursor() as cur: + if action == "list": + cur.execute("SELECT * FROM auto_reply_rules ORDER BY id DESC") + rows = cur.fetchall() + log_event("INFO", "api", "api.rules.list", new_trace_id("rules"), "query", "ok", "查询回复匹配配置", extra={"db_path": str(SQLITE_DB_PATH), "count": len(rows)}) + return jsonify({"success": True, "data": rows, "db_path": str(SQLITE_DB_PATH)}) + + if action == "create": + keyword = (request.values.get("keyword") or "").strip() + match_type = request.values.get("match_type", "contain") + reply_text = (request.values.get("reply_text") or "").strip() + is_active = int(request.values.get("is_active", 1)) + if not keyword or not reply_text: + return jsonify({"success": False, "message": "关键词和回复内容不能为空"}) + if match_type not in ["contain", "equal"]: + match_type = "contain" + cur.execute("INSERT INTO auto_reply_rules(keyword, match_type, reply_text, is_active, created_at, updated_at) VALUES (%s, %s, %s, %s, %s, %s)", (keyword, match_type, reply_text, is_active, now, now)) + conn.commit() + return jsonify({"success": True}) + + if action == "toggle": + rule_id = int(request.values.get("id", 0)) + is_active = int(request.values.get("is_active", 0)) + if rule_id <= 0: + return jsonify({"success": False, "message": "参数错误"}) + cur.execute("UPDATE auto_reply_rules SET is_active = %s, updated_at = %s WHERE id = %s", (is_active, now, rule_id)) + conn.commit() + return jsonify({"success": True}) + + if action == "delete": + rule_id = int(request.values.get("id", 0)) + if rule_id <= 0: + return jsonify({"success": False, "message": "参数错误"}) + cur.execute("DELETE FROM auto_reply_rules WHERE id = %s", (rule_id,)) + conn.commit() + return jsonify({"success": True}) + + if action == "settings_get": + auto_on = _get_local_setting("auto_reply_enabled", "1") == "1" + full_auto_on = _get_local_setting("full_auto_reply_enabled", "0") == "1" + reply_fallback_mode = (_get_local_setting("reply_fallback_mode", "ai") or "ai").strip() or "ai" + bot_status = bot_controller.status() + runtime_status = (bot_status.get("status") or "stopped").strip().lower() + if runtime_status not in ["running", "starting", "stopping", "stopped", "error"]: + runtime_status = "stopped" + listener_on = runtime_status in ["running", "starting"] + return jsonify({ + "success": True, + "auto_reply_enabled": auto_on, + "listener_enabled": listener_on, + "listener_runtime_status": runtime_status, + "listener_intent_enabled": _get_local_setting("listener_enabled", "0") == "1", + "full_auto_reply_enabled": full_auto_on, + "reply_fallback_mode": reply_fallback_mode, + }) + + if action == "settings_set": + if "auto_reply_enabled" in request.values: + auto_on = "1" if request.values.get("auto_reply_enabled", "1") == "1" else "0" + _set_local_setting("auto_reply_enabled", auto_on) + if "listener_enabled" in request.values: + listener_on = "1" if request.values.get("listener_enabled", "0") == "1" else "0" + _set_local_setting("listener_enabled", listener_on) + if "listener_runtime_status" in request.values: + runtime_status = (request.values.get("listener_runtime_status") or "stopped").strip().lower() + if runtime_status not in ["running", "starting", "stopping", "stopped", "error"]: + runtime_status = "stopped" + _set_local_setting("listener_runtime_status", runtime_status) + if "full_auto_reply_enabled" in request.values: + full_auto_on = "1" if request.values.get("full_auto_reply_enabled", "0") == "1" else "0" + _set_local_setting("full_auto_reply_enabled", full_auto_on) + if "reply_fallback_mode" in request.values: + reply_fallback_mode = (request.values.get("reply_fallback_mode") or "ai").strip() or "ai" + _set_local_setting("reply_fallback_mode", reply_fallback_mode) + return jsonify({"success": True}) + + if action == "messages_recent": + limit = int(request.values.get("limit", 50)) + limit = max(1, min(100, limit)) + cur.execute("SELECT * FROM messages ORDER BY id DESC LIMIT %s", (limit,)) + rows = cur.fetchall() + return jsonify({"success": True, "data": rows}) + + return jsonify({"success": False, "message": "未知操作"}) + finally: + conn.close() diff --git a/app/infrastructure/router/backend_routes.py b/app/infrastructure/router/backend_routes.py new file mode 100644 index 0000000..41a5e60 --- /dev/null +++ b/app/infrastructure/router/backend_routes.py @@ -0,0 +1,9 @@ +from app.infrastructure.router.backend.rules import register_rule_routes +from app.infrastructure.router.backend.messages import register_message_routes +from app.infrastructure.router.backend.bot import register_bot_routes + + +def register_routes(app): + register_rule_routes(app) + register_message_routes(app) + register_bot_routes(app) diff --git a/app/infrastructure/service/__init__.py b/app/infrastructure/service/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/app/infrastructure/service/backend/__init__.py b/app/infrastructure/service/backend/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/app/infrastructure/service/backend/ai.py b/app/infrastructure/service/backend/ai.py new file mode 100644 index 0000000..9def762 --- /dev/null +++ b/app/infrastructure/service/backend/ai.py @@ -0,0 +1,81 @@ +import requests + +from app.infrastructure.service.backend.config import AI_PROVIDER, DEEPSEEK_API_BASE, DEEPSEEK_API_KEY, DEEPSEEK_MODEL, DIFY_API_BASE, DIFY_API_KEY, DIFY_USER, OPENAI_API_BASE, OPENAI_API_KEY, OPENAI_MODEL +from app.infrastructure.service.logging.log_service import log_event, new_trace_id + + +def do_openai_like(url, headers, payload): + try: + resp = requests.post(url, headers=headers, json=payload, timeout=60) + data = resp.json() if resp.text else {} + if resp.status_code >= 400: + return f"抱歉，AI 服务请求失败（{resp.status_code}）" + content = (((data or {}).get("choices") or [{}])[0].get("message") or {}).get("content", "") + return content.strip() if content else "抱歉，AI 暂时没有合理的回复。" + except Exception: + return "抱歉，AI 服务暂时不可用，请稍后再试。" + + +def do_dify(url, headers, payload): + try: + resp = requests.post(url, headers=headers, json=payload, timeout=60) + text = resp.text or "" + if "data:" in text: + answer = "" + for line in text.splitlines(): + line = line.strip() + if not line.startswith("data:"): + continue + chunk = line[5:].strip() + if not chunk or chunk == "[DONE]": + continue + try: + j = requests.models.complexjson.loads(chunk) + except Exception: + continue + if "answer" in j: + answer += j["answer"] + if answer.strip(): + return answer.strip() + data = resp.json() if resp.text else {} + if resp.status_code >= 400: + return f"抱歉，Dify 服务请求失败（{resp.status_code}）" + return (data.get("answer") or "抱歉，Dify 暂时没有合理的回复。").strip() + except Exception: + return "抱歉，Dify 服务暂时不可用，请稍后再试。" + + +def call_ai(prompt, user_id=""): + trace_id = new_trace_id("ai") + provider = AI_PROVIDER + log_event("INFO", "ai", "ai.request", trace_id, "request", "ok", "发起AI请求", extra={"provider": provider, "user_id": user_id or "", "prompt_len": len(prompt or "")}) + if provider == "mock": + result = "【自动回复】你刚才说了：" + (prompt or "")[:100] + log_event("INFO", "ai", "ai.response", trace_id, "response", "ok", "AI回复完成", extra={"provider": provider, "reply_len": len(result)}) + return result + if provider == "openai": + result = do_openai_like( + OPENAI_API_BASE.rstrip("/") + "/chat/completions", + {"Content-Type": "application/json", "Authorization": f"Bearer {OPENAI_API_KEY}"}, + {"model": OPENAI_MODEL, "messages": [{"role": "system", "content": "你是一个专业的微信私域运营助手，用简洁自然的中文回复用户。"}, {"role": "user", "content": prompt}], "temperature": 0.7, "user": user_id or None}, + ) + elif provider == "deepseek": + result = do_openai_like( + DEEPSEEK_API_BASE.rstrip("/") + "/chat/completions", + {"Content-Type": "application/json", "Authorization": f"Bearer {DEEPSEEK_API_KEY}"}, + {"model": DEEPSEEK_MODEL, "messages": [{"role": "system", "content": "你是一个简洁高效的微信助手。回复要求：一句话，不超过50字。"}, {"role": "user", "content": prompt}], "temperature": 0.7, "max_tokens": 100, "user": user_id or None}, + ) + elif provider == "dify": + result = do_dify( + DIFY_API_BASE.rstrip("/") + "/chat-messages", + {"Content-Type": "application/json", "Authorization": f"Bearer {DIFY_API_KEY}"}, + {"inputs": {}, "query": prompt, "response_mode": "streaming", "user": user_id or DIFY_USER, "conversation_id": ""}, + ) + else: + result = "AI_PROVIDER 未配置正确，请检查环境变量。" + + if result.startswith("抱歉") or "未配置正确" in result: + log_event("WARNING", "ai", "ai.response", trace_id, "response", "failed", "AI回复异常或降级", reason="provider_error", extra={"provider": provider, "reply": result[:120]}) + else: + log_event("INFO", "ai", "ai.response", trace_id, "response", "ok", "AI回复完成", extra={"provider": provider, "reply_len": len(result)}) + return result diff --git a/app/infrastructure/service/backend/config.py b/app/infrastructure/service/backend/config.py new file mode 100644 index 0000000..010709c --- /dev/null +++ b/app/infrastructure/service/backend/config.py @@ -0,0 +1,45 @@ +import os +from pathlib import Path + +from flask import Flask, request + +from app.configs.runtime_config import get_int, get_str + +PROJECT_ROOT = Path(__file__).resolve().parents[4] + +ASSETS_DIR = PROJECT_ROOT / "assets" +FRONTEND_DIST_DIR = PROJECT_ROOT / "frontend" / "dist" +_frontend_static_dir = get_str("FRONTEND_STATIC_DIR", "").strip() +FRONTEND_STATIC_DIR = Path(_frontend_static_dir).resolve() if _frontend_static_dir else None +STATIC_DIR = FRONTEND_STATIC_DIR or (FRONTEND_DIST_DIR if FRONTEND_DIST_DIR.exists() else ASSETS_DIR) + +DB_HOST = get_str("DB_HOST", "127.0.0.1") +DB_PORT = get_int("DB_PORT", 3306) +DB_NAME = get_str("DB_NAME", "ai_shiliu") +DB_USER = get_str("DB_USER", "ai_shiliu") +DB_PASS = get_str("DB_PASS", "") +DB_CHARSET = get_str("DB_CHARSET", "utf8mb4") + +AI_PROVIDER = get_str("AI_PROVIDER", "") +OPENAI_API_KEY = get_str("OPENAI_API_KEY", "") +OPENAI_API_BASE = get_str("OPENAI_API_BASE", "") +OPENAI_MODEL = get_str("OPENAI_MODEL", "") +DEEPSEEK_API_KEY = get_str("DEEPSEEK_API_KEY", "") +DEEPSEEK_API_BASE = get_str("DEEPSEEK_API_BASE", "") +DEEPSEEK_MODEL = get_str("DEEPSEEK_MODEL", "") +DIFY_API_KEY = get_str("DIFY_API_KEY", "") +DIFY_API_BASE = get_str("DIFY_API_BASE", "") +DIFY_USER = get_str("DIFY_USER", "") + +app = Flask(__name__, static_folder=str(STATIC_DIR), static_url_path="") + + +@app.after_request +def add_cors_headers(response): + origin = (request.headers.get("Origin") or "").strip() + allow_origin = origin or "*" + response.headers["Access-Control-Allow-Origin"] = allow_origin + response.headers["Vary"] = "Origin" + response.headers["Access-Control-Allow-Headers"] = "Content-Type, Authorization" + response.headers["Access-Control-Allow-Methods"] = "GET, POST, OPTIONS" + return response diff --git a/app/infrastructure/service/backend/db.py b/app/infrastructure/service/backend/db.py new file mode 100644 index 0000000..7347655 --- /dev/null +++ b/app/infrastructure/service/backend/db.py @@ -0,0 +1,218 @@ +import json +import os +import re +import sqlite3 +from pathlib import Path + +from app.infrastructure.service.backend.config import PROJECT_ROOT +from app.infrastructure.service.logging.log_service import log_event, new_trace_id + +_SETTING_CACHE = {} +SETTINGS_FILE = PROJECT_ROOT / "logs" / "state" / "local_settings.json" +LOCAL_APPDATA_DIR = Path(os.environ.get("LOCALAPPDATA", str(Path.home() / "AppData" / "Local"))) +SQLITE_DB_PATH = LOCAL_APPDATA_DIR / "com.shiliu.aiassistant" / "ai_shiliu.sqlite3" + + +class _SQLiteCursor: + def __init__(self, cursor): + self._cursor = cursor + + def __enter__(self): + return self + + def __exit__(self, exc_type, exc, tb): + self._cursor.close() + + @staticmethod + def _adapt_sql(sql: str) -> str: + return sql.replace("%s", "?") + + def execute(self, sql, params=None): + sql = self._adapt_sql(sql) + if params is None: + self._cursor.execute(sql) + else: + self._cursor.execute(sql, params) + return self + + def fetchone(self): + row = self._cursor.fetchone() + return dict(row) if row is not None else None + + def fetchall(self): + return [dict(row) for row in self._cursor.fetchall()] + + @property + def lastrowid(self): + return self._cursor.lastrowid + + +class _SQLiteConn: + def __init__(self, conn): + self._conn = conn + + def cursor(self): + return _SQLiteCursor(self._conn.cursor()) + + def commit(self): + self._conn.commit() + + def rollback(self): + self._conn.rollback() + + def close(self): + self._conn.close() + + +def _bootstrap_sqlite_file(): + SQLITE_DB_PATH.parent.mkdir(parents=True, exist_ok=True) + + +def get_conn(db_name=None): + _bootstrap_sqlite_file() + conn = sqlite3.connect(str(SQLITE_DB_PATH)) + conn.row_factory = sqlite3.Row + conn.execute("PRAGMA foreign_keys = ON") + return _SQLiteConn(conn) + + +def init_db(): + trace_id = new_trace_id("db") + log_event("INFO", "db", "db.init", trace_id, "start", "ok", "初始化数据库开始", extra={"path": str(SQLITE_DB_PATH)}) + conn = get_conn() + try: + with conn.cursor() as cur: + cur.execute( + """ + CREATE TABLE IF NOT EXISTS messages ( + id INTEGER PRIMARY KEY AUTOINCREMENT, + wx_user_id TEXT NOT NULL DEFAULT '', + wx_nickname TEXT NOT NULL DEFAULT '', + direction TEXT NOT NULL DEFAULT 'in', + content TEXT NOT NULL, + is_ai_reply INTEGER NOT NULL DEFAULT 0, + rule_id INTEGER NULL, + is_friend_request INTEGER NOT NULL DEFAULT 0, + reply_strategy TEXT NOT NULL DEFAULT '', + reply_reason TEXT NOT NULL DEFAULT '', + ocr_confidence TEXT NOT NULL DEFAULT '', + ocr_bubble_side TEXT NOT NULL DEFAULT '', + created_at TEXT NOT NULL DEFAULT (datetime('now', 'localtime')) + ) + """ + ) + cur.execute("CREATE INDEX IF NOT EXISTS idx_messages_user_time ON messages(wx_user_id, created_at)") + cur.execute( + """ + CREATE TABLE IF NOT EXISTS auto_reply_rules ( + id INTEGER PRIMARY KEY AUTOINCREMENT, + keyword TEXT NOT NULL, + match_type TEXT NOT NULL DEFAULT 'contain', + reply_text TEXT NOT NULL, + is_active INTEGER NOT NULL DEFAULT 1, + created_at TEXT NOT NULL DEFAULT (datetime('now', 'localtime')), + updated_at TEXT NOT NULL DEFAULT (datetime('now', 'localtime')) + ) + """ + ) + + cur.execute("PRAGMA table_info(messages)") + cols = {str(x.get('name') or '') for x in (cur.fetchall() or [])} + if "reply_strategy" not in cols: + cur.execute("ALTER TABLE messages ADD COLUMN reply_strategy TEXT NOT NULL DEFAULT ''") + if "reply_reason" not in cols: + cur.execute("ALTER TABLE messages ADD COLUMN reply_reason TEXT NOT NULL DEFAULT ''") + if "ocr_confidence" not in cols: + cur.execute("ALTER TABLE messages ADD COLUMN ocr_confidence TEXT NOT NULL DEFAULT ''") + if "ocr_bubble_side" not in cols: + cur.execute("ALTER TABLE messages ADD COLUMN ocr_bubble_side TEXT NOT NULL DEFAULT ''") + + conn.commit() + log_event("INFO", "db", "db.init", trace_id, "done", "ok", "初始化数据库完成") + except Exception as exc: + conn.rollback() + log_event("ERROR", "db", "db.init", trace_id, "done", "failed", "初始化数据库失败", reason="db_error", extra={"error": str(exc)}) + raise + finally: + conn.close() + + +def _load_settings_file(): + if _SETTING_CACHE: + return + try: + if SETTINGS_FILE.exists(): + data = json.loads(SETTINGS_FILE.read_text(encoding="utf-8")) + if isinstance(data, dict): + for k, v in data.items(): + _SETTING_CACHE[str(k)] = str(v) + except Exception: + pass + + +def _save_settings_file(): + SETTINGS_FILE.parent.mkdir(parents=True, exist_ok=True) + SETTINGS_FILE.write_text(json.dumps(_SETTING_CACHE, ensure_ascii=False, indent=2), encoding="utf-8") + + +def get_setting(key, default=None): + _load_settings_file() + if key in _SETTING_CACHE: + return _SETTING_CACHE[key] + if default is None: + return None + val = str(default) + _SETTING_CACHE[key] = val + _save_settings_file() + return val + + +def set_setting(key, value): + _load_settings_file() + _SETTING_CACHE[str(key)] = str(value) + _save_settings_file() + + +def normalize_text(text): + t = (text or "").strip().lower() + t = re.sub(r"\s+", "", t) + t = t.replace("：", ":") + return t + + +def find_rule_reply(content): + trace_id = new_trace_id("db") + conn = get_conn() + try: + with conn.cursor() as cur: + cur.execute("SELECT * FROM auto_reply_rules WHERE is_active = 1 ORDER BY id ASC") + rules = cur.fetchall() + except Exception as exc: + log_event("ERROR", "db", "db.rule.query", trace_id, "query", "failed", "查询规则失败", reason="db_error", extra={"error": str(exc)}) + raise + finally: + conn.close() + + raw_content = (content or "").strip() + content_lower = raw_content.lower() + content_norm = normalize_text(raw_content) + + for rule in rules: + kw = (rule.get("keyword") or "").strip() + if not kw: + continue + + kw_lower = kw.lower() + kw_norm = normalize_text(kw) + match_type = rule.get("match_type") + + if match_type == "equal": + if content_lower == kw_lower or content_norm == kw_norm: + log_event("INFO", "db", "db.rule.match", trace_id, "match", "ok", "命中规则", reason="rule_hit", extra={"rule_id": rule.get("id"), "match_type": match_type}) + return rule + else: + if kw_lower in content_lower or kw_norm in content_norm: + log_event("INFO", "db", "db.rule.match", trace_id, "match", "ok", "命中规则", reason="rule_hit", extra={"rule_id": rule.get("id"), "match_type": match_type or "contain"}) + return rule + log_event("INFO", "db", "db.rule.match", trace_id, "match", "ok", "未命中规则", reason="rule_miss", extra={"rule_count": len(rules)}) + return None diff --git a/app/infrastructure/service/logging/log_query_service.py b/app/infrastructure/service/logging/log_query_service.py new file mode 100644 index 0000000..3fac476 --- /dev/null +++ b/app/infrastructure/service/logging/log_query_service.py @@ -0,0 +1,141 @@ +import hashlib +import json +from datetime import datetime +from pathlib import Path + +from app.infrastructure.service.wechat.config import LOG_ROOT_DIR + + +ALLOWED_MODULES = {"api", "bot", "ocr", "ai", "db", "capture", "audit", "error"} +DOMAIN_MODULES = {"api", "bot", "ocr", "ai", "db", "capture"} + + +def _infer_domain(row: dict) -> str: + module = str(row.get("module") or "").strip().lower() + if module in DOMAIN_MODULES: + return module + if module == "error": + event = str(row.get("event") or "") + prefix = event.split(".", 1)[0].strip().lower() + if prefix in DOMAIN_MODULES: + return prefix + return "api" + + +def _event_id(row: dict) -> str: + raw = json.dumps(row or {}, ensure_ascii=False, sort_keys=True) + return hashlib.md5(raw.encode("utf-8")).hexdigest() + + +def _enrich_row(row: dict) -> dict: + x = dict(row or {}) + x["domain"] = _infer_domain(x) + x["event_id"] = _event_id(x) + return x + + +def _read_jsonl(module: str): + p = Path(LOG_ROOT_DIR) / f"{module}.jsonl" + if not p.exists(): + return [] + rows = [] + with p.open("r", encoding="utf-8", errors="replace") as f: + for line in f: + line = line.strip() + if not line: + continue + try: + rows.append(json.loads(line)) + except Exception: + continue + return rows + + +def query_events(module=None, level=None, event=None, trace_id=None, start_ts=None, end_ts=None, keyword=None, page=1, size=50): + modules = [module] if module in ALLOWED_MODULES else sorted(ALLOWED_MODULES) + all_rows = [] + for m in modules: + all_rows.extend(_read_jsonl(m)) + def ok(row): + if level and str(row.get("level", "")).upper() != str(level).upper(): + return False + if event and str(row.get("event", "")) != str(event): + return False + if trace_id and str(row.get("trace_id", "")) != str(trace_id): + return False + if keyword and keyword not in json.dumps(row, ensure_ascii=False): + return False + ts = str(row.get("ts") or "") + if start_ts and ts < start_ts: + return False + if end_ts and ts > end_ts: + return False + return True + rows = [_enrich_row(r) for r in all_rows if ok(r)] + rows.sort(key=lambda x: str(x.get("ts") or ""), reverse=True) + page = max(1, int(page or 1)) + size = max(1, min(200, int(size or 50))) + start = (page - 1) * size + end = start + size + return {"total": len(rows), "page": page, "size": size, "items": rows[start:end]} + + +def query_trace(trace_id: str): + if not trace_id: + return [] + result = query_events(trace_id=trace_id, size=500) + items = result.get("items") or [] + items.sort(key=lambda x: str(x.get("ts") or "")) + return items + + +def query_event_json(event_id: str): + event_id = str(event_id or "").strip().lower() + if not event_id: + return None + for m in sorted(ALLOWED_MODULES): + rows = _read_jsonl(m) + for row in rows: + x = _enrich_row(row) + if str(x.get("event_id") or "") == event_id: + return x + return None + + +def clear_logs(module=None): + modules = [module] if module in ALLOWED_MODULES else sorted(ALLOWED_MODULES) + root = Path(LOG_ROOT_DIR) + deleted = [] + for m in modules: + for p in root.glob(f"{m}.log*"): + p.write_text("", encoding="utf-8") + deleted.append(str(p.name)) + for p in root.glob(f"{m}.jsonl*"): + p.write_text("", encoding="utf-8") + deleted.append(str(p.name)) + return {"modules": modules, "files": deleted} + + +def query_summary(limit=300): + events = query_events(size=limit).get("items") or [] + error_count = sum(1 for e in events if str(e.get("level", "")).upper() in {"ERROR"}) + fallback_count = sum(1 for e in events if str(e.get("event", "")).endswith("fallback")) + reasons = {} + domain_counts = {"api": 0, "bot": 0, "ocr": 0, "ai": 0, "db": 0, "capture": 0} + for e in events: + reason = str(e.get("reason") or "").strip() + if reason: + reasons[reason] = reasons.get(reason, 0) + 1 + domain = str(e.get("domain") or _infer_domain(e)) + if domain in domain_counts: + domain_counts[domain] += 1 + reason_top = sorted(reasons.items(), key=lambda x: x[1], reverse=True)[:20] + domain_top = sorted(domain_counts.items(), key=lambda x: x[1], reverse=True) + return { + "window": len(events), + "error_count": error_count, + "fallback_count": fallback_count, + "top_reasons": [{"reason": k, "count": v} for k, v in reason_top], + "domain_counts": [{"domain": k, "count": v} for k, v in domain_top], + "generated_at": datetime.now().astimezone().isoformat(timespec="seconds"), + } diff --git a/app/infrastructure/service/logging/log_schema.py b/app/infrastructure/service/logging/log_schema.py new file mode 100644 index 0000000..a148ab6 --- /dev/null +++ b/app/infrastructure/service/logging/log_schema.py @@ -0,0 +1,86 @@ +from dataclasses import dataclass, field +from datetime import datetime +from typing import Any + + +MODULES = {"api", "bot", "ocr", "ai", "db", "capture", "audit", "error"} +DOMAIN_MODULES = {"api", "bot", "ocr", "ai", "db", "capture"} + +ALLOWED_EVENTS = { + "api.bot.status", + "api.bot.start", + "api.bot.stop", + "api.messages.receive", + "audit.decision", + "bot.chat_analyze", + "bot.chat_snapshot", + "bot.loop", + "bot.session_scan", + "bot.session_service.init", + "bot.session_title", + "bot.submit", + "bot.unread.detect", + "bot.unread.scan", + "ocr.baidu.token", + "ocr.baidu.recognize", + "ocr.rapid.init", + "ocr.rapid.recognize", + "ocr.fallback", + "ocr.session_name", + "ocr.session_title", + "ocr.generic", + "capture.contact_list", + "capture.session_title", + "capture.chat_area", + "ai.request", + "ai.response", + "db.init", + "db.error", + "db.rule.query", + "db.rule.match", +} + + +def normalize_event(module: str, event: str) -> str: + e = str(event or "").strip().lower() + m = str(module or "").strip().lower() + if e in ALLOWED_EVENTS: + return e + if "." in e: + prefix = e.split(".", 1)[0] + if prefix in DOMAIN_MODULES: + return e + if m in DOMAIN_MODULES: + return f"{m}.unknown" + return "api.unknown" + + +@dataclass +class LogEvent: + level: str + module: str + event: str + trace_id: str + stage: str + status: str + message: str + reason: str = "" + extra: dict[str, Any] = field(default_factory=dict) + ts: str = "" + + def to_dict(self) -> dict[str, Any]: + ts = self.ts or datetime.now().astimezone().isoformat(timespec="milliseconds") + module = self.module if self.module in MODULES else "api" + event = normalize_event(module, self.event) + return { + "ts": ts, + "level": (self.level or "INFO").upper(), + "module": module, + "event": event, + "trace_id": self.trace_id or "-", + "stage": self.stage or "-", + "status": self.status or "ok", + "reason": self.reason or "", + "message": self.message or "", + "extra": self.extra or {}, + } diff --git a/app/infrastructure/service/logging/log_service.py b/app/infrastructure/service/logging/log_service.py new file mode 100644 index 0000000..4b7e513 --- /dev/null +++ b/app/infrastructure/service/logging/log_service.py @@ -0,0 +1,102 @@ +import json +import logging +import os +from logging.handlers import RotatingFileHandler +from pathlib import Path + +from app.configs.runtime_config import get_bool, get_int, get_str +from app.infrastructure.service.logging.log_schema import ALLOWED_EVENTS, LogEvent, MODULES, normalize_event +from app.infrastructure.service.wechat.config import LOG_ROOT_DIR + +_INITIALIZED = False +_LOGGERS: dict[str, logging.Logger] = {} +_JSON_LOGGERS: dict[str, logging.Logger] = {} + + +class _JsonFormatter(logging.Formatter): + def format(self, record): + if isinstance(record.msg, dict): + return json.dumps(record.msg, ensure_ascii=False) + return json.dumps({"message": str(record.msg)}, ensure_ascii=False) + + +class _TextFormatter(logging.Formatter): + def format(self, record): + if isinstance(record.msg, dict): + data = record.msg + extra = data.get("extra") or {} + kv = " ".join([f"{k}={v}" for k, v in extra.items()]) + suffix = f" | {kv}" if kv else "" + return f"[{data.get('ts')}][{data.get('level')}][{data.get('module')}][{data.get('event')}][{data.get('trace_id')}] {data.get('message')}{suffix}" + return str(record.msg) + + +def _build_logger(name: str, file_path: Path, formatter: logging.Formatter, level: int, rotate_mb: int, backup_count: int): + logger = logging.getLogger(name) + logger.handlers.clear() + logger.propagate = False + logger.setLevel(level) + file_path.parent.mkdir(parents=True, exist_ok=True) + handler = RotatingFileHandler(str(file_path), maxBytes=rotate_mb * 1024 * 1024, backupCount=backup_count, encoding="utf-8") + handler.setLevel(level) + handler.setFormatter(formatter) + logger.addHandler(handler) + return logger + + +def init_logging(): + global _INITIALIZED + if _INITIALIZED: + return + enabled = get_bool("LOG_ENABLED", True) + if not enabled: + logging.disable(logging.CRITICAL) + _INITIALIZED = True + return + level_name = (get_str("LOG_LEVEL", "INFO") or "INFO").upper() + level = getattr(logging, level_name, logging.INFO) + rotate_mb = max(1, get_int("LOG_ROTATE_MB", 5)) + backup_count = max(1, get_int("LOG_BACKUP_COUNT", 7)) + root = Path(LOG_ROOT_DIR) + for module in MODULES: + text_logger = _build_logger(f"solo.{module}.text", root / f"{module}.log", _TextFormatter(), level, rotate_mb, backup_count) + json_logger = _build_logger(f"solo.{module}.json", root / f"{module}.jsonl", _JsonFormatter(), level, rotate_mb, backup_count) + _LOGGERS[module] = text_logger + _JSON_LOGGERS[module] = json_logger + _INITIALIZED = True + + +def log_event(level: str, module: str, event: str, trace_id: str, stage: str, status: str, message: str, reason: str = "", extra: dict | None = None): + if not _INITIALIZED: + init_logging() + if logging.root.manager.disable >= logging.CRITICAL: + return + normalized_event = normalize_event(module, event) + payload_extra = dict(extra or {}) + if normalized_event != str(event or "").strip().lower() and normalized_event not in ALLOWED_EVENTS: + payload_extra["event_raw"] = event + payload_extra["event_normalized"] = normalized_event + payload = LogEvent( + level=level, + module=module, + event=normalized_event, + trace_id=trace_id, + stage=stage, + status=status, + reason=reason, + message=message, + extra=payload_extra, + ).to_dict() + module_name = payload["module"] + lvl = getattr(logging, payload["level"], logging.INFO) + _LOGGERS[module_name].log(lvl, payload) + _JSON_LOGGERS[module_name].log(lvl, payload) + if lvl >= logging.ERROR and module_name != "error": + _LOGGERS["error"].log(lvl, payload) + _JSON_LOGGERS["error"].log(lvl, payload) + + +def new_trace_id(prefix: str = "trace") -> str: + import uuid + + return f"{prefix}_{uuid.uuid4().hex[:12]}" diff --git a/app/infrastructure/service/wechat/__init__.py b/app/infrastructure/service/wechat/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/app/infrastructure/service/wechat/chat_snapshot_analyzer.py b/app/infrastructure/service/wechat/chat_snapshot_analyzer.py new file mode 100644 index 0000000..260dd12 --- /dev/null +++ b/app/infrastructure/service/wechat/chat_snapshot_analyzer.py @@ -0,0 +1,1129 @@ +from dataclasses import dataclass, asdict +from io import BytesIO +from pathlib import Path +import json +import re +import sys + +import cv2 +import numpy as np +from PIL import Image + +# 项目根目录路径 +ROOT = Path(__file__).resolve().parents[4] +sys.path.insert(0, str(ROOT)) + +from app.infrastructure.service.logging.log_service import log_event, new_trace_id +from app.infrastructure.service.wechat.config import ( + OCR_SAVE_DIR, + OCR_TOP_PENALTY_RATIO, + OCR_TOP_PENALTY_BIN_FACTOR, + OCR_TOP_PENALTY_COLOR_FACTOR, +) +from app.infrastructure.service.wechat.ocr import OCRService + +# 点击后的聊天截图目录 +CLICKED_DIR = ROOT / OCR_SAVE_DIR / 'sessions' / 'clicked' +# OCR输出目录，包含子目录original、merged_binary、ocr_crops +OUT_DIR = ROOT / OCR_SAVE_DIR / 'sessions' / 'clicked_ocr' +# 原始截图保存目录 +ORIGINAL_DIR = OUT_DIR / 'original' +# 合并二值化图片保存目录 +MERGED_DIR = OUT_DIR / 'merged_binary' +# OCR裁剪区域保存目录 +OCR_DIR = OUT_DIR / 'ocr_crops' +# 创建所有输出目录 +for _dir in (OUT_DIR, ORIGINAL_DIR, MERGED_DIR, OCR_DIR): + _dir.mkdir(parents=True, exist_ok=True) + + +# 获取图片输出目录，根据类别返回不同子目录路径 +def get_image_out_dir(stem: str, category: str = 'ocr') -> Path: + safe = stem or 'unknown' + base = OCR_DIR + if category == 'original': + base = ORIGINAL_DIR + elif category == 'merged': + base = MERGED_DIR + out = base / safe + out.mkdir(parents=True, exist_ok=True) + return out + +# 日志记录器 +# OCR服务单例 +ocr = OCRService() + +# 二值化和自适应阈值参数 +BINARY_THRESHOLD = 248 # 固定二值化阈值 +ADAPTIVE_BLOCK_SIZE = 13 # 自适应阈值块大小 +ADAPTIVE_C = 1 # 自适应阈值偏移量 +LEFT_MERGE_KERNEL = (5, 1) # 左侧气泡的形态学操作核 +DEFAULT_MERGE_KERNEL = (3, 1) # 默认形态学操作核 +OPEN_KERNEL = (2, 2) # 开运算核大小 + +# 气泡颜色和位置启发式参数 +PEER_BUBBLE_RGB = (238, 238, 240) # 对方消息气泡颜色（#EEEEF0） +LEFT_BUBBLE_CX_RATIO = 0.58 # 左侧气泡中心x坐标比例阈值 +RIGHT_BUBBLE_MIN_LEFT_RATIO = 0.48 # 右侧气泡最小左侧比例 +LEFT_SIDE_MAX_RIGHT_RATIO = 0.78 # 左侧气泡最大右侧比例 +LEFT_COLOR_THRESHOLD = 64 # 左侧气泡颜色差异阈值 +RIGHT_COLOR_THRESHOLD = 108 # 右侧气泡颜色差异阈值 +BRIGHTNESS_CUTOFF = 248 # 亮度截止值 +BG_WHITE_THRESHOLD = 245 # 背景白色阈值 +BRIGHT_MASK_THRESHOLD = 242 # 高亮遮罩阈值 + +# 连通组件分析的面积和尺寸阈值 +MIN_AREA_BINARY = 700 # 二值图像最小连通区域面积 +MIN_WIDTH_BINARY = 42 # 二值图像最小宽度 +MIN_HEIGHT_BINARY = 24 # 二值图像最小高度 +MIN_AREA_COLOR = 560 # 彩色图像最小连通区域面积 +MIN_WIDTH_COLOR = 38 # 彩色图像最小宽度 +MIN_HEIGHT_COLOR = 22 # 彩色图像最小高度 + +# 全二值化备选框评分参数 +FULL_BIN_SCORE_BOTTOM = 5.0 # 底部位置得分系数 +FULL_BIN_SCORE_AREA = 0.08 # 面积得分系数 +FULL_BIN_SCORE_WIDTH = 0.15 # 宽度得分系数 +FULL_BIN_PENALTY_TALL = 8.0 # 过高惩罚系数 +FULL_BIN_PENALTY_WIDE = 3.0 # 过宽惩罚系数 + +# 最新消息候选框过滤规则（用于pick_last_white_box_from_merged_binary） +AVATAR_RATIO_MIN = 0.75 +AVATAR_RATIO_MAX = 1.35 +AVATAR_MIN_SIZE = 28 +AVATAR_MAX_SIZE = 72 +AVATAR_EDGE_LEFT_RATIO = 0.2 +AVATAR_EDGE_RIGHT_RATIO = 0.8 +TIME_MARKER_MIN_H = 10 +TIME_MARKER_MAX_H = 22 +TIME_MARKER_MIN_W = 28 +TIME_MARKER_MAX_W = 110 +TIME_MARKER_RATIO_MIN = 1.8 +TIME_MARKER_RATIO_MAX = 8.0 +TIME_MARKER_CENTER_TOLERANCE = 0.16 + +# 二值气泡框评分参数 +BIN_SCORE_BOTTOM = 5.0 # 底部位置得分系数 +BIN_SCORE_AREA = 0.12 # 面积得分系数 +BIN_SCORE_OVERLAP = 220.0 # 重叠度得分系数 +BIN_PENALTY_TOP_GAP_LEFT = 10.0 # 左侧气泡顶部间隙惩罚 +BIN_PENALTY_TOP_GAP_RIGHT = 4.0 # 右侧气泡顶部间隙惩罚 +BIN_PENALTY_BOTTOM_GAP = 1.8 # 底部间隙惩罚 +BIN_PENALTY_TOO_TALL = 9.0 # 过高惩罚 +BIN_PENALTY_TOO_WIDE = 2.0 # 过宽惩罚 + +# 彩色气泡框评分参数 +COLOR_SCORE_AREA = 0.35 # 面积得分系数 +COLOR_SCORE_BOTTOM = 3.0 # 底部位置得分系数 +COLOR_SCORE_OVERLAP = 180.0 # 重叠度得分系数 +COLOR_PENALTY_TOP_GAP_LEFT = 7.5 # 左侧气泡顶部间隙惩罚 +COLOR_PENALTY_BOTTOM_GAP = 1.6 # 底部间隙惩罚 +COLOR_PENALTY_TOO_TALL = 7.0 # 过高惩罚 +COLOR_PENALTY_TOO_WIDE = 1.6 # 过宽惩罚 +COLOR_SCORE_TOP_GAP_RIGHT = 1.0 # 右侧气泡顶部间隙得分 +COLOR_SCORE_HEIGHT_RIGHT = 2.0 # 右侧气泡高度得分 + +# 最新消息簇评分参数 +CLUSTER_SCORE_BOTTOM = 2.2 # 簇底部位置得分系数 +CLUSTER_SCORE_HEIGHT = 0.9 # 簇高度得分系数 +CLUSTER_SCORE_WIDTH = 0.12 # 簇宽度得分系数 +CLUSTER_SCORE_TEXT_LEN = 1.5 # 文本长度得分系数 +CLUSTER_SCORE_MULTI_LINE_BONUS = 35.0 # 多行消息额外加分 + +# 非正文文本过滤：精确匹配的内容 +NON_BODY_EXACT_TEXTS = { + '小程序', + ':S', +} +# 非正文文本过滤：包含这些关键词的内容 +NON_BODY_CONTAINS_TEXTS = ( + '有事请@其他福利官', + '我是机器人', + '群主小助手', +) + + +# 聊天快照分析结果数据类 +@dataclass +class AnalyzeResult: + file: str + size: tuple[int, int] | None + crop_box: dict | None + latest_text: str | None + is_self_sent: bool | None + bubble_side: str | None + confidence: float + valid_lines: list[str] + error: str | None + + +# 将PIL图片转换为PNG格式的字节数据 +def pil_to_bytes(img: Image.Image) -> bytes: + buf = BytesIO() + img.save(buf, format='PNG') + return buf.getvalue() + + +# 对图片进行OCR识别，返回识别到的文本行列表 +def ocr_lines(img: Image.Image, scene: str) -> list[str]: + return [x.strip() for x in ocr.recognize(pil_to_bytes(img), scene=scene) if x and str(x).strip()] + + +def ocr_items_direct(img: Image.Image) -> list[dict]: + provider = getattr(ocr, 'rapid_provider', None) + if provider is None or not provider.ensure_ready() or provider.engine is None: + return [] + arr = cv2.cvtColor(np.array(img.convert('RGB')), cv2.COLOR_RGB2BGR) + result = provider.engine(arr) + if not result or len(result) < 1: + return [] + rec_res = result[0] or [] + items = [] + for item in rec_res: + if not item or len(item) < 2: + continue + box = np.array(item[0], dtype=np.float32) + text = str(item[1]).strip() + confidence = float(item[2]) if len(item) > 2 else 0.0 + if not text: + continue + items.append({ + 'text': text, + 'confidence': confidence, + 'left': float(box[:, 0].min()), + 'top': float(box[:, 1].min()), + 'right': float(box[:, 0].max()), + 'bottom': float(box[:, 1].max()), + }) + return items + + +# 构建合并的二值化图像，结合固定阈值和自适应阈值进行文字区域提取 +def build_merged_binary_image(img: Image.Image, *, is_left_bubble: bool | None = None) -> Image.Image: + arr = np.array(img.convert('RGB')) + gray = cv2.cvtColor(arr, cv2.COLOR_RGB2GRAY) + blurred = cv2.GaussianBlur(gray, (5, 5), 0) + _, binary_inv = cv2.threshold(blurred, BINARY_THRESHOLD, 255, cv2.THRESH_BINARY_INV) + adaptive_inv = cv2.adaptiveThreshold( + blurred, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, + cv2.THRESH_BINARY_INV, ADAPTIVE_BLOCK_SIZE, ADAPTIVE_C + ) + merged = cv2.bitwise_or(binary_inv, adaptive_inv) + # 接近极限收缩：几乎只保留细小横向连接，尽量打断大白块 + if is_left_bubble is True: + merge_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, LEFT_MERGE_KERNEL) + merged = cv2.morphologyEx(merged, cv2.MORPH_CLOSE, merge_kernel, iterations=1) + merged = cv2.morphologyEx(merged, cv2.MORPH_OPEN, cv2.getStructuringElement(cv2.MORPH_RECT, OPEN_KERNEL)) + else: + merge_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, DEFAULT_MERGE_KERNEL) + merged = cv2.morphologyEx(merged, cv2.MORPH_CLOSE, merge_kernel, iterations=1) + merged = cv2.morphologyEx(merged, cv2.MORPH_OPEN, cv2.getStructuringElement(cv2.MORPH_RECT, OPEN_KERNEL)) + return Image.fromarray(merged) + + +# 从全二值化图像中选择最佳文字区域框 +def pick_box_from_full_binary(img: Image.Image) -> dict | None: + merged = np.array(build_merged_binary_image(img)) + num_labels, _, stats, _ = cv2.connectedComponentsWithStats(merged, 8) + h, w = merged.shape[:2] + best = None + for label in range(1, num_labels): + x, y, bw, bh, area = stats[label] + if area < 300: + continue + if bw < 50 or bh < 24: + continue + right = x + bw + bottom = y + bh + score = 0.0 + score += bottom * FULL_BIN_SCORE_BOTTOM + score += min(area, 20000) * FULL_BIN_SCORE_AREA + score += min(bw, int(w * 0.7)) * FULL_BIN_SCORE_WIDTH + if bh > h * 0.45: + score -= (bh - h * 0.45) * FULL_BIN_PENALTY_TALL + if bw > w * 0.65: + score -= (bw - w * 0.65) * FULL_BIN_PENALTY_WIDE + if best is None or score > best[0]: + best = (score, x, y, right, bottom) + if best is None: + return None + _, left, top, right, bottom = best + return { + 'left': int(left), + 'top': int(top), + 'right': int(right), + 'bottom': int(bottom), + 'width': int(right - left), + 'height': int(bottom - top), + } + + +# 从合并的二值化图像中选择最下方（最新）的白色文字框 +def pick_last_white_box_from_merged_binary(merged_img: Image.Image) -> dict | None: + merged = np.array(merged_img.convert('L')) + img_h, img_w = merged.shape[:2] + num_labels, _, stats, _ = cv2.connectedComponentsWithStats(merged, 8) + boxes = [] + for label in range(1, num_labels): + x, y, w, h, area = stats[label] + if area <= 0 or w <= 0 or h <= 0: + continue + right = x + w + bottom = y + h + ratio = w / max(1.0, float(h)) + is_full_width_strip = x <= img_w * 0.02 and right >= img_w * 0.98 and w >= img_w * 0.9 + if is_full_width_strip: + continue + if w < 32 or h < 12: + continue + + # 规则1：过滤边缘头像框（近似正方形 + 固定尺寸 + 处于左右边缘） + is_avatar_like = AVATAR_RATIO_MIN <= ratio <= AVATAR_RATIO_MAX and AVATAR_MIN_SIZE <= w <= AVATAR_MAX_SIZE and AVATAR_MIN_SIZE <= h <= AVATAR_MAX_SIZE + is_edge_avatar = x <= img_w * AVATAR_EDGE_LEFT_RATIO or right >= img_w * AVATAR_EDGE_RIGHT_RATIO + if is_avatar_like and is_edge_avatar: + continue + + # 规则2：过滤中间时间标记（短高、细长、位于屏幕中轴附近） + cx = (x + right) / 2.0 + is_time_marker_like = TIME_MARKER_MIN_H <= h <= TIME_MARKER_MAX_H and TIME_MARKER_MIN_W <= w <= TIME_MARKER_MAX_W and TIME_MARKER_RATIO_MIN <= ratio <= TIME_MARKER_RATIO_MAX and abs(cx - img_w / 2.0) <= img_w * TIME_MARKER_CENTER_TOLERANCE + if is_time_marker_like: + continue + + is_left_box = cx <= img_w * LEFT_BUBBLE_CX_RATIO and x <= img_w * RIGHT_BUBBLE_MIN_LEFT_RATIO + if not is_left_box: + continue + + boxes.append((x, y, right, bottom, w, h, area)) + + if not boxes: + return None + + candidates = [] + for x, y, right, bottom, w, h, area in boxes: + score = 0.0 + score += bottom * 1.0 + score += right * 0.08 + score += min(area, 28000) * 0.0012 + if right < img_w * 0.35: + score -= 80.0 + if right > img_w * 0.82: + score -= (right - img_w * 0.82) * 1.4 + if w > img_w * 0.45 and right > img_w * 0.75: + score -= min(260.0, (w - img_w * 0.45) * 1.2 + (right - img_w * 0.75) * 1.0) + candidates.append((score, x, y, right, bottom)) + + candidates.sort(key=lambda item: item[0]) + _, left, top, right, bottom = candidates[-1] + return { + 'left': int(left), + 'top': int(top), + 'right': int(right), + 'bottom': int(bottom), + 'width': int(right - left), + 'height': int(bottom - top), + } + + +# 使用OCR引擎识别图片中的文字和位置信息 +def ocr_items_with_boxes(img: Image.Image, offset_x: int = 0, offset_y: int = 0) -> list[dict]: + provider = getattr(ocr, 'provider', None) + engine = getattr(provider, 'engine', None) + ready = getattr(provider, 'ready', False) + if not ready or engine is None: + return [] + try: + result = engine.ocr(np.array(img.convert('RGB'))) + except Exception: + return [] + items = [] + if not isinstance(result, list): + return items + for block in result: + if not isinstance(block, dict): + continue + texts = block.get('rec_texts') or [] + scores = block.get('rec_scores') or [] + boxes = block.get('rec_boxes') + if boxes is None: + boxes = [] + for idx, text in enumerate(texts): + text = str(text).strip() + if not text: + continue + score = float(scores[idx]) if idx < len(scores) and scores[idx] is not None else 0.0 + if score < 0.3 or idx >= len(boxes): + continue + box = np.array(boxes[idx]).astype(float) + if box.ndim == 1: + if box.size < 4: + continue + left, top, right, bottom = float(box[0]), float(box[1]), float(box[2]), float(box[3]) + cx = (left + right) / 2.0 + cy = (top + bottom) / 2.0 + else: + xs = box[:, 0] + ys = box[:, 1] + left, right = float(xs.min()), float(xs.max()) + top, bottom = float(ys.min()), float(ys.max()) + cx = float(xs.mean()) + cy = float(ys.mean()) + items.append({ + 'text': text, + 'score': score, + 'left': left + offset_x, + 'right': right + offset_x, + 'top': top + offset_y, + 'bottom': bottom + offset_y, + 'cx': cx + offset_x, + 'cy': cy + offset_y, + 'height': (bottom - top), + 'width': (right - left), + }) + return items + + +# 判断OCR识别出的文本行是否应该保留 +def should_keep_line(text: str) -> bool: + text = (text or '').strip() + return bool(text) + + +# 清理候选文本行，去除非正文前缀和无效符号 +def cleanup_candidate_lines(lines: list[str]) -> list[str]: + cleaned = [] + for idx, raw in enumerate(lines): + text = str(raw).strip() + if not text: + continue + + cleaned.append(text) + + # 如果最后只剩一个很短的符号行，优先回退到其上一条正文 + if len(cleaned) >= 2 and len(cleaned[-1]) <= 3 and re.fullmatch(r'[:：;；SsxX]+', cleaned[-1]): + cleaned = cleaned[:-1] + + # 若仍有明显非正文前缀挂在最上面，继续剥掉 + + return cleaned + + +# 去重文本行列表，移除重复内容 +def dedupe_lines(lines: list[str]) -> list[str]: + out = [] + seen = set() + for line in lines: + text = str(line).strip() + if not text or text in seen: + continue + seen.add(text) + out.append(text) + return out + + +# 根据几何位置去重OCR识别项，移除位置和文本都相同的重复项 +def dedupe_items_by_geometry(items: list[dict]) -> list[dict]: + if not items: + return [] + items = sorted(items, key=lambda x: (-x.get('score', 0.0), x['top'], x['left'])) + kept: list[dict] = [] + for item in items: + text = item['text'].strip() + duplicate = False + for old in kept: + if old['text'].strip() != text: + continue + if abs(old['cx'] - item['cx']) <= 18 and abs(old['cy'] - item['cy']) <= 12: + duplicate = True + break + if not duplicate: + kept.append(item) + return sorted(kept, key=lambda x: (x['cy'], x['left'])) + + +# 将OCR识别项按行分组为多个簇，每簇包含同一行的文本项 +def build_line_clusters(items: list[dict], y_gap: float = 18.0) -> list[list[dict]]: + items = dedupe_items_by_geometry([x for x in items if should_keep_line(x['text'])]) + if not items: + return [] + clusters: list[list[dict]] = [] + current = [items[0]] + for item in items[1:]: + prev = current[-1] + avg_h = max(10.0, (prev.get('height', 0) + item.get('height', 0)) / 2.0) + gap_limit = max(y_gap, avg_h * 1.15) + if abs(item['cy'] - prev['cy']) <= gap_limit: + current.append(item) + else: + clusters.append(current) + current = [item] + clusters.append(current) + return clusters + + +# 将同一行的OCR项合并为单行文本字符串 +def cluster_to_lines(cluster: list[dict]) -> list[str]: + rows = build_line_clusters(cluster, y_gap=10.0) + lines = [] + for row in rows: + row = dedupe_items_by_geometry(sorted(row, key=lambda x: x['left'])) + parts = [] + for item in row: + text = item['text'].strip() + if not text: + continue + if parts and parts[-1] == text: + continue + parts.append(text) + merged = ''.join(parts) + if merged: + lines.append(merged) + return dedupe_lines(lines) + + +# 计算文本簇的边界框（上下左右和中心点） +def cluster_bounds(cluster: list[dict]) -> dict: + return { + 'top': min(x['top'] for x in cluster), + 'bottom': max(x['bottom'] for x in cluster), + 'left': min(x['left'] for x in cluster), + 'right': max(x['right'] for x in cluster), + 'cx': sum(x['cx'] for x in cluster) / len(cluster), + } + + +# 根据簇内文本项估算单行文字的高度 +def estimate_cluster_line_height(cluster: list[dict]) -> float: + heights = [float(x.get('height', 0) or 0) for x in cluster if float(x.get('height', 0) or 0) > 0] + if not heights: + return 18.0 + return max(14.0, float(np.median(heights))) + + +# 根据文本簇边界裁剪出气泡区域图片，使用颜色和形态学方法定位气泡 +def crop_bubble_box(img: Image.Image, cluster_items: list[dict], stem: str | None = None) -> tuple[Image.Image | None, dict | None]: + if not cluster_items: + return None, None + + arr = np.array(img.convert('RGB')) + img_h, img_w = arr.shape[:2] + bounds = cluster_bounds(cluster_items) + + seed_left = max(0, int(bounds['left'] - 20)) + seed_right = min(img_w, int(bounds['right'] + 20)) + seed_top = max(0, int(bounds['top'] - 30)) + seed_bottom = min(img_h, int(bounds['bottom'] + 14)) + if seed_right <= seed_left or seed_bottom <= seed_top: + return None, None + + seed = arr[seed_top:seed_bottom, seed_left:seed_right] + if seed.size == 0: + return None, None + + # 对方消息气泡：优先锚定到 #EEEEF0 附近；自己消息可再走别的颜色策略 + seed_pixels = seed.reshape(-1, 3).astype(np.int16) + brightness = seed_pixels.mean(axis=1) + bubble_pixels = seed_pixels[brightness < BRIGHTNESS_CUTOFF] + if bubble_pixels.size == 0: + bubble_pixels = seed_pixels + median_target = np.median(bubble_pixels, axis=0) + peer_target = np.array(PEER_BUBBLE_RGB, dtype=np.int16) # #EEEEF0 + # 左侧消息优先锚定 #EEEEF0 的灰底黑字气泡；右侧保留原有自适应策略 + is_left_bubble = bounds['cx'] <= img_w * LEFT_BUBBLE_CX_RATIO + if is_left_bubble: + target = peer_target + threshold = LEFT_COLOR_THRESHOLD + else: + target = median_target.astype(np.int16) + threshold = RIGHT_COLOR_THRESHOLD + + diff = np.abs(arr.astype(np.int16) - target.reshape(1, 1, 3)) + dist = diff.sum(axis=2) + + bg_mask = (arr[:, :, 0] > BG_WHITE_THRESHOLD) & (arr[:, :, 1] > BG_WHITE_THRESHOLD) & (arr[:, :, 2] > BG_WHITE_THRESHOLD) + bright_mask = arr.mean(axis=2) > BRIGHT_MASK_THRESHOLD + color_mask = (dist <= threshold) & (~bg_mask) & (~bright_mask) + color_mask = color_mask.astype(np.uint8) * 255 + + if is_left_bubble: + # 左侧灰气泡更怕把上下两条消息连在一起，这里弱化纵向粘连、强化横向连通 + kernel_close = cv2.getStructuringElement(cv2.MORPH_RECT, (11, 3)) + kernel_open = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3)) + else: + kernel_close = cv2.getStructuringElement(cv2.MORPH_RECT, (7, 7)) + kernel_open = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3)) + color_mask = cv2.morphologyEx(color_mask, cv2.MORPH_CLOSE, kernel_close) + color_mask = cv2.morphologyEx(color_mask, cv2.MORPH_OPEN, kernel_open) + + text_cx = bounds['cx'] + text_cy = (bounds['top'] + bounds['bottom']) / 2.0 + text_h = max(1.0, bounds['bottom'] - bounds['top']) + text_w = max(1.0, bounds['right'] - bounds['left']) + + def is_probable_left_avatar_candidate(stats_arr, label_idx: int, x: int, y: int, w: int, h: int) -> bool: + if not is_left_bubble: + return False + if x > img_w * 0.2: + return False + if w <= 0 or h <= 0: + return False + wh_ratio = w / max(1.0, float(h)) + if wh_ratio < 0.72 or wh_ratio > 1.35: + return False + if w < max(18.0, text_h * 0.55) or w > max(92.0, text_h * 2.4): + return False + + right_edge = x + w + row_hit = False + n = stats_arr.shape[0] if hasattr(stats_arr, 'shape') else len(stats_arr) + for j in range(1, n): + if j == label_idx: + continue + ox, oy, ow, oh, oarea = stats_arr[j] + if oarea <= 0 or ow <= 0 or oh <= 0: + continue + if ox <= right_edge: + continue + gap = ox - right_edge + if gap < 2 or gap > max(120.0, text_w * 1.4): + continue + overlap_h = max(0.0, min(y + h, oy + oh) - max(y, oy)) + if overlap_h < min(h, oh) * 0.45: + continue + if ow < w * 1.15: + continue + if oh < h * 0.75: + continue + row_hit = True + break + return row_hit + + def pick_box_from_binary_merge() -> tuple[int, int, int, int] | None: + merged_out_dir = get_image_out_dir(stem or 'unknown', 'merged') if stem else None + merged_img = build_merged_binary_image(img, is_left_bubble=is_left_bubble) + merged = np.array(merged_img) + + if merged_out_dir is not None: + merged_img.save(merged_out_dir / 'bubble_bin.png') + + num_labels2, labels2, stats2, _ = cv2.connectedComponentsWithStats(merged, 8) + best_local = None + for label in range(1, num_labels2): + x, y, w, h, area = stats2[label] + if area <= 0 or w <= 0 or h <= 0: + continue + if is_probable_left_avatar_candidate(stats2, label, x, y, w, h): + continue + right = x + w + bottom = y + h + if not (x <= text_cx <= right and y <= text_cy <= bottom): + continue + + top_gap = max(0.0, bounds['top'] - y) + bottom_gap = max(0.0, bottom - bounds['bottom']) + overlap_x = max(0.0, min(bounds['right'], right) - max(bounds['left'], x)) + overlap_ratio = overlap_x / text_w if text_w > 0 else 0.0 + if overlap_ratio < 0.45: + continue + + score = 0.0 + score += bottom * BIN_SCORE_BOTTOM + score += area * BIN_SCORE_AREA + score += overlap_ratio * BIN_SCORE_OVERLAP + if y < img_h * 0.18: + score -= (img_h * 0.18 - y) * 2.0 + score -= top_gap * (BIN_PENALTY_TOP_GAP_LEFT if is_left_bubble else BIN_PENALTY_TOP_GAP_RIGHT) + score -= abs(bottom_gap - 12.0) * BIN_PENALTY_BOTTOM_GAP + + max_reasonable_h = max(120.0, text_h * 3.4) + max_reasonable_w = max(360.0, text_w * 1.9) + if h > max_reasonable_h: + score -= (h - max_reasonable_h) * BIN_PENALTY_TOO_TALL + if w > max_reasonable_w: + score -= (w - max_reasonable_w) * BIN_PENALTY_TOO_WIDE + + if is_left_bubble: + region = arr[y:bottom, x:right].reshape(-1, 3).astype(np.int16) + if region.size > 0: + region_mean = np.median(region, axis=0) + color_score = float(320 - np.abs(region_mean - peer_target).sum()) + score += max(0.0, color_score) + + if best_local is None or score > best_local[0]: + best_local = (score, x, y, right, bottom) + if best_local is None: + return None + return best_local[1], best_local[2], best_local[3], best_local[4] + + best = None + binary_box = pick_box_from_binary_merge() + if binary_box is not None: + left, top, right, bottom = binary_box + best = (float(bottom), left, top, right, bottom) + else: + num_labels, labels, stats, _ = cv2.connectedComponentsWithStats(color_mask, 8) + for label in range(1, num_labels): + x, y, w, h, area = stats[label] + if area <= 0 or w <= 0 or h <= 0: + continue + if is_probable_left_avatar_candidate(stats, label, x, y, w, h): + continue + right = x + w + bottom = y + h + if not (x <= text_cx <= right and y <= text_cy <= bottom): + continue + + top_gap = max(0.0, bounds['top'] - y) + bottom_gap = max(0.0, bottom - bounds['bottom']) + overlap_x = max(0.0, min(bounds['right'], right) - max(bounds['left'], x)) + overlap_ratio = overlap_x / text_w if text_w > 0 else 0.0 + + score = 0.0 + score += area * COLOR_SCORE_AREA + score += bottom * COLOR_SCORE_BOTTOM + score += overlap_ratio * COLOR_SCORE_OVERLAP + if y < img_h * OCR_TOP_PENALTY_RATIO: + score -= (img_h * OCR_TOP_PENALTY_RATIO - y) * OCR_TOP_PENALTY_COLOR_FACTOR + + if is_left_bubble: + region = arr[y:bottom, x:right].reshape(-1, 3).astype(np.int16) + region_mean = np.median(region, axis=0) + color_score = float(320 - np.abs(region_mean - peer_target).sum()) + score += max(0.0, color_score) + # 目标是最后一片灰框，不是整列灰底 + score -= top_gap * COLOR_PENALTY_TOP_GAP_LEFT + score -= abs(bottom_gap - 12.0) * COLOR_PENALTY_BOTTOM_GAP + max_reasonable_h = max(110.0, text_h * 2.8) + if h > max_reasonable_h: + score -= (h - max_reasonable_h) * COLOR_PENALTY_TOO_TALL + max_reasonable_w = max(320.0, text_w * 1.6) + if w > max_reasonable_w: + score -= (w - max_reasonable_w) * COLOR_PENALTY_TOO_WIDE + else: + score += top_gap * COLOR_SCORE_TOP_GAP_RIGHT + score += h * COLOR_SCORE_HEIGHT_RIGHT + + if best is None or score > best[0]: + best = (score, x, y, right, bottom) + + if best is not None: + _, left, top, right, bottom = best + + if is_left_bubble: + cand_w = max(1, int(right - left)) + cand_h = max(1, int(bottom - top)) + cand_ratio = cand_w / float(cand_h) + if left <= int(img_w * 0.2) and 0.70 <= cand_ratio <= 1.35 and cand_w <= max(96, int(text_h * 2.6)): + left = max(0, int(bounds['left'] - 6)) + right = min(img_w, int(bounds['right'] + 12)) + top = max(0, int(bounds['top'] - 4)) + bottom = min(img_h, int(bounds['bottom'] + 10)) + + # 基于已找到的色块做方向扩张：左侧气泡重点往左/上/下扩 + def col_match_ratio(x: int, y1: int, y2: int) -> float: + seg = dist[max(0, y1):min(img_h, y2), max(0, x):min(img_w, x + 1)] + if seg.size == 0: + return 0.0 + return float((seg <= threshold).mean()) + + def row_match_ratio(y: int, x1: int, x2: int) -> float: + seg = dist[max(0, y):min(img_h, y + 1), max(0, x1):min(img_w, x2)] + if seg.size == 0: + return 0.0 + return float((seg <= threshold).mean()) + + is_left_bubble = bounds['cx'] <= img_w * 0.58 + line_h = estimate_cluster_line_height(cluster_items) + current_h = max(1.0, float(bottom - top)) + # 不写死目标高度，按当前识别到的文字行高推测一个更合理的气泡高度。 + # 经验上 4 行消息块通常需要约 5~6 个文本行高的容纳空间； + # 当前框偏小时，优先把增量用于向上扩展。 + desired_h = max(current_h, line_h * 5.6) + need_more_h = max(0.0, desired_h - current_h) + + # 左侧消息按“红框风格”收紧：更贴正文，避免包太大 + expand_left_limit = 12 if is_left_bubble else 30 + expand_right_limit = 22 if is_left_bubble else 90 + expand_up_limit = max(6, int(min(18, line_h * 0.55 + need_more_h * 0.08))) if is_left_bubble else max(40, int(min(120, line_h * 3.8 + need_more_h * 0.9))) + expand_down_limit = max(10, int(min(28, line_h * 0.85 + need_more_h * 0.10))) if is_left_bubble else max(20, int(min(60, line_h * 1.6 + need_more_h * 0.25))) + + for _ in range(expand_left_limit): + if left <= 1: + break + ratio = col_match_ratio(left - 1, top, bottom) + if ratio < 0.18: + break + left -= 1 + + for _ in range(expand_right_limit): + if right >= img_w - 1: + break + ratio = col_match_ratio(right, top, bottom) + if ratio < 0.18: + break + right += 1 + + up_steps = 0 + top_guard = max(0, int(bounds['top'] - (line_h * 0.9 if is_left_bubble else line_h * 2.2))) + for _ in range(expand_up_limit): + if top <= 1 or top <= top_guard: + break + ratio = row_match_ratio(top - 1, left, right) + # 左侧消息向上严格很多，避免把昵称/头像旁白区卷进来 + if is_left_bubble: + if ratio < 0.18: + break + else: + if ratio < 0.10 and up_steps > int(line_h * 0.8): + break + top -= 1 + up_steps += 1 + + down_steps = 0 + for _ in range(expand_down_limit): + if bottom >= img_h - 1: + break + ratio = row_match_ratio(bottom, left, right) + if ratio < 0.16 and down_steps > int(line_h * 0.5): + break + bottom += 1 + down_steps += 1 + + # 如果扩张后仍明显矮于按行高估计的合理高度，左侧消息也只做很有限补偿，避免变成大包围框 + current_h2 = max(1, bottom - top) + missing_h = max(0, int(desired_h - current_h2)) + if missing_h > 0: + if is_left_bubble: + extra_up = min(max(0, int(missing_h * 0.08)), max(0, top - top_guard)) + extra_down = min(max(0, int(missing_h * 0.35)), max(0, img_h - bottom)) + else: + extra_up = min(max(0, int(missing_h * 0.75)), max(0, top)) + extra_down = min(max(0, int(missing_h * 0.25)), max(0, img_h - bottom)) + top -= extra_up + bottom += extra_down + + # 左侧消息最终再做一次边界钳制，逼近你标的红框大小 + if is_left_bubble: + target_left = int(bounds['left'] - 6) + target_top = int(bounds['top'] - max(3, line_h * 0.28)) + target_right = int(bounds['right'] + 10) + target_bottom = int(bounds['bottom'] + max(8, line_h * 0.45)) + left = max(0, min(int(left), target_left)) + left = max(left, max(0, target_left - 2)) + top = max(0, min(int(top), target_top)) + top = max(top, max(0, target_top - 2)) + right = min(img_w, max(int(right), target_right)) + right = min(right, target_right + 4) + bottom = min(img_h, max(int(bottom), target_bottom)) + bottom = min(bottom, target_bottom + 4) + else: + left = max(0, int(left - 4)) + top = max(0, int(top - 4)) + right = min(img_w, int(right + 4)) + bottom = min(img_h, int(bottom + 4)) + else: + # 找不到色块时才退回文本框轻微扩边；左侧消息按正文贴边框处理 + if bounds['cx'] <= img_w * 0.58: + left = max(0, int(bounds['left'] - 6)) + right = min(img_w, int(bounds['right'] + 12)) + top = max(0, int(bounds['top'] - 4)) + bottom = min(img_h, int(bounds['bottom'] + 10)) + else: + left = max(0, int(bounds['left'] - 24)) + right = min(img_w, int(bounds['right'] + 26)) + top = max(0, int(bounds['top'] - 42)) + bottom = min(img_h, int(bounds['bottom'] + 22)) + + if right <= left or bottom <= top: + return None, None + box = {'left': left, 'top': top, 'right': right, 'bottom': bottom, 'width': right - left, 'height': bottom - top} + return img.crop((left, top, right, bottom)), box + + +# 对气泡图片进行OCR识别，返回识别到的文本行列表 +def ocr_bubble_text(bubble_img: Image.Image, stem: str) -> list[str]: + scale = 5 + scaled_img = bubble_img.resize((bubble_img.width * scale, bubble_img.height * scale), Image.Resampling.LANCZOS) + raw_lines = ocr_lines(scaled_img, f'clicked_{stem}_bubble_crop') + + def normalize(lines: list[str]) -> list[str]: + merged = [] + for line in lines: + text = str(line).strip() + if not should_keep_line(text): + continue + if text not in merged: + merged.append(text) + return merged + + def build_bold_binary_image(source_img: Image.Image) -> Image.Image: + gray = np.array(source_img.convert('L')) + _, binary = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU) + binary_img = Image.fromarray(binary).convert('L') + scaled_binary = binary_img.resize((source_img.width * scale, source_img.height * scale), Image.Resampling.NEAREST) + arr = np.array(scaled_binary) + kernel = np.ones((2, 2), np.uint8) + dilated = cv2.dilate(255 - arr, kernel, iterations=1) + return Image.fromarray(255 - dilated).convert('RGB') + + def recognize_joined_short_text(source_img: Image.Image) -> str | None: + items = ocr_items_direct(source_img) + if len(items) < 2: + return None + items.sort(key=lambda item: (item['left'], item['top'])) + text = ''.join(item['text'] for item in items if should_keep_line(item['text'])) + if not text: + return None + if len(text) <= 8 and re.fullmatch(r'[一-鿿A-Za-z0-9]+', text): + return text + return None + + def looks_like_short_name(text: str) -> bool: + text = (text or '').strip() + if not text: + return False + if len(text) > 4: + return False + if any(ch in text for ch in '，。！？!?.、/@'): + return False + return re.fullmatch(r'[一-鿿A-Za-z0-9]+', text) is not None + + def looks_like_headerish(text: str) -> bool: + text = (text or '').strip() + if not text: + return False + if looks_like_short_name(text): + return True + if ('+' in text and re.search(r'\d', text)) or '拍立减' in text or '限时' in text: + return True + return False + + def choose_best_suffix(lines: list[str]) -> list[str]: + lines = cleanup_candidate_lines(lines) + if not lines: + return [] + suffixes = [lines[i:] for i in range(len(lines))] + def suffix_score(seq: list[str]) -> tuple[float, float, float]: + total_chars = sum(len(x) for x in seq) + score = total_chars * 0.5 + score -= max(0, len(seq) - 4) * 12 + score -= len(seq) * 2 + first = seq[0] + last = seq[-1] + if looks_like_headerish(first) and len(seq) > 1: + score -= 35 + if len(first) <= 8 and len(seq) > 1 and len(seq[1]) >= 8: + score -= 26 + if looks_like_short_name(last) and len(seq) > 1: + score -= 55 + if len(last) <= 3: + score -= 40 + if len(seq) == 1 and len(last) >= 2: + score += 14 + return (score, -len(seq), total_chars) + best = max(suffixes, key=suffix_score) + return cleanup_candidate_lines(best) + + raw_norm = normalize(raw_lines) + should_try_short_text = bubble_img.width <= 90 and bubble_img.height <= 60 and (not raw_norm or len(''.join(raw_norm)) <= 2) + if should_try_short_text: + bold_binary_img = build_bold_binary_image(bubble_img) + bold_binary_img.save(get_image_out_dir(stem, 'ocr') / 'bubble_crop_bold_binary_5x.png') + joined_text = recognize_joined_short_text(bold_binary_img) + if joined_text and (not raw_norm or len(joined_text) > len(''.join(raw_norm))): + return [joined_text] + + if raw_norm: + return raw_norm + return [] + + +# 从OCR识别项中选择最新的消息簇，返回文本和原始簇 +def pick_latest_cluster(items: list[dict], image_w: int, image_h: int) -> tuple[list[str], list[str], list[dict]]: + if not items: + return [], [], [] + clusters = build_line_clusters(items, y_gap=max(18.0, image_h * 0.018)) + if not clusters: + return [], [], [] + + scored = [] + for idx, cluster in enumerate(clusters): + bounds = cluster_bounds(cluster) + lines = cluster_to_lines(cluster) + if not lines: + continue + height = bounds['bottom'] - bounds['top'] + width = bounds['right'] - bounds['left'] + text_len = sum(len(x) for x in lines) + score = 0.0 + score += bounds['bottom'] * CLUSTER_SCORE_BOTTOM + score += min(120.0, height * CLUSTER_SCORE_HEIGHT) + score += min(80.0, width * CLUSTER_SCORE_WIDTH) + score += min(60.0, text_len * CLUSTER_SCORE_TEXT_LEN) + if len(lines) >= 2: + score += CLUSTER_SCORE_MULTI_LINE_BONUS + + is_left_cluster = bounds['cx'] <= image_w * LEFT_BUBBLE_CX_RATIO and bounds['left'] <= image_w * RIGHT_BUBBLE_MIN_LEFT_RATIO + if not is_left_cluster: + continue + min_line_len = min((len(x.strip()) for x in lines if x and x.strip()), default=0) + if is_left_cluster and len(lines) == 1 and min_line_len <= 4: + near_bottom = bounds['bottom'] >= image_h * 0.62 + has_cjk = any(re.search(r'[一-鿿]', x or '') for x in lines) + if not (near_bottom and has_cjk): + score -= 120.0 + if is_left_cluster and width <= max(52.0, height * 1.25): + near_bottom = bounds['bottom'] >= image_h * 0.62 + has_cjk = any(re.search(r'[一-鿿]', x or '') for x in lines) + if not (near_bottom and has_cjk): + score -= 140.0 + + scored.append((score, idx, lines, cluster)) + + if not scored: + return [], [], [] + scored.sort(key=lambda x: x[0], reverse=True) + _, _, best_lines, best_cluster = scored[0] + + # 为了优先保证截图只落在最后一条正文块，这里先不向上合并前一个 cluster。 + return list(best_lines)[:4], dedupe_lines([x['text'] for x in items]), list(best_cluster) + + +# 从聊天快照中提取最新消息文本 +def extract_latest_text(img: Image.Image, stem: str, preferred_ocr_img: Image.Image | None = None, preferred_crop_box: dict | None = None) -> tuple[str | None, list[str], list[dict], dict | None]: + img_np = np.array(img) + h, w = img_np.shape[:2] + all_items: list[dict] = [] + merged_out_dir = get_image_out_dir(stem, 'merged') + ocr_out_dir = get_image_out_dir(stem, 'ocr') + + merged_full = build_merged_binary_image(img) + merged_full.save(merged_out_dir / 'full_bin.png') + + raw_items = ocr_items_with_boxes(img, offset_x=0, offset_y=0) + merged_items = dedupe_items_by_geometry(raw_items) + for item in merged_items: + text = item['text'].strip() + if should_keep_line(text): + all_items.append(item) + + cluster_lines, valid_lines, cluster_items = pick_latest_cluster(all_items, w, h) + bubble_img, bubble_box = crop_bubble_box(img, cluster_items, stem) + ocr_source_img = preferred_ocr_img if preferred_ocr_img is not None else bubble_img + crop_box = preferred_crop_box if preferred_ocr_img is not None else bubble_box + if ocr_source_img is not None: + ocr_source_img.save(ocr_out_dir / 'bubble_crop.png') + bubble_lines = ocr_bubble_text(ocr_source_img, stem) + bubble_lines = cleanup_candidate_lines(bubble_lines) + if bubble_lines: + return '\n'.join(bubble_lines), valid_lines, cluster_items, crop_box + latest_block_lines = list(cluster_lines) + latest_block_lines = cleanup_candidate_lines(latest_block_lines) + latest_block = '\n'.join(latest_block_lines) if latest_block_lines else None + return latest_block, valid_lines, cluster_items, crop_box + + +# 检测最新消息气泡位于屏幕左侧还是右侧（判断是自己还是对方的消息） +def detect_latest_bubble_side(img: Image.Image, cluster_items: list[dict], crop_box: dict | None = None) -> tuple[str | None, float]: + arr = np.array(img.convert('RGB')) + h, w = arr.shape[:2] + + if crop_box: + left = float(crop_box.get('left', 0)) + right = float(crop_box.get('right', left)) + center_x = (left + right) / 2.0 + if center_x >= w * LEFT_BUBBLE_CX_RATIO or left >= w * RIGHT_BUBBLE_MIN_LEFT_RATIO: + return 'right', 0.9 + return 'left', 0.9 + + if cluster_items: + avg_cx = sum(x['cx'] for x in cluster_items) / len(cluster_items) + min_left = min(x['left'] for x in cluster_items) + max_right = max(x['right'] for x in cluster_items) + width = max_right - min_left + if avg_cx >= w * LEFT_BUBBLE_CX_RATIO or min_left >= w * RIGHT_BUBBLE_MIN_LEFT_RATIO: + return 'right', 0.84 if width > w * 0.18 else 0.78 + if avg_cx <= w * 0.52 or max_right <= w * LEFT_SIDE_MAX_RIGHT_RATIO: + return 'left', 0.84 if width > w * 0.18 else 0.78 + + focus = arr[int(h * 0.38):, :, :] + hsv = cv2.cvtColor(focus, cv2.COLOR_RGB2HSV) + green_mask = cv2.inRange(hsv, np.array([35, 25, 80]), np.array([95, 255, 255])) + kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 5)) + green_mask = cv2.morphologyEx(green_mask, cv2.MORPH_CLOSE, kernel) + contours, _ = cv2.findContours(green_mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) + + candidates = [] + y_offset = int(h * 0.38) + for cnt in contours: + x, y, ww, hh = cv2.boundingRect(cnt) + area = ww * hh + right = x + ww + if area < 2500: + continue + if hh < 28 or ww < 80: + continue + if right < w * 0.66: + continue + if x < w * 0.45 and ww > w * 0.45: + continue + candidates.append((y + y_offset, x, ww, hh, area)) + + if candidates: + candidates.sort(key=lambda item: (item[0] + item[3], item[1])) + y, x, ww, hh, area = candidates[-1] + center_x = x + ww / 2.0 + side = 'right' if center_x >= w * LEFT_BUBBLE_CX_RATIO else 'left' + confidence = min(0.72, 0.50 + min(0.22, area / 40000.0)) + return side, confidence + + return 'left', 0.35 + + +# 分析PIL图片的主函数，提取最新消息、判断发送方并返回分析结果 +def analyze_pil_image(img: Image.Image, stem: str, file_name: str | None = None) -> AnalyzeResult: + trace_id = new_trace_id("bot") + safe_stem = stem or 'unknown' + ocr_out_dir = get_image_out_dir(safe_stem, 'ocr') + for p in ocr_out_dir.glob('*.png'): + p.unlink(missing_ok=True) + + img = img.convert('RGB') + original_out_dir = get_image_out_dir(safe_stem, 'original') + img.save(original_out_dir / 'full_raw.png') + + merged_full = build_merged_binary_image(img) + last_white_box = pick_last_white_box_from_merged_binary(merged_full) + preferred_ocr_img = None + preferred_crop_box = None + if last_white_box is not None: + preferred_crop_box = dict(last_white_box) + preferred_ocr_img = img.crop(( + int(last_white_box['left']), + int(last_white_box['top']), + int(last_white_box['right']), + int(last_white_box['bottom']), + )) + preferred_ocr_img.save(original_out_dir / 'last_white_box_raw.png') + + latest_text, valid_lines, cluster_items, crop_box = extract_latest_text(img, safe_stem, preferred_ocr_img=preferred_ocr_img, preferred_crop_box=preferred_crop_box) + bubble_side, confidence = detect_latest_bubble_side(img, cluster_items, crop_box=crop_box) + if bubble_side == 'right': + latest_text = None + valid_lines = [] + is_self_sent = None if bubble_side is None else (bubble_side == 'right') + result = AnalyzeResult( + file=file_name or f'{safe_stem}.png', + size=img.size, + crop_box=crop_box, + latest_text=latest_text, + is_self_sent=is_self_sent, + bubble_side=bubble_side, + confidence=confidence, + valid_lines=valid_lines, + error=None, + ) + (ocr_out_dir / 'result.json').write_text(json.dumps(asdict(result), ensure_ascii=False, indent=2), encoding='utf-8') + log_event("INFO", "bot", "bot.chat_snapshot", trace_id, "analyze", "ok", "聊天快照分析完成", extra={"file": result.file, "has_text": bool(result.latest_text), "bubble_side": result.bubble_side or "", "confidence": result.confidence}) + return result + + diff --git a/app/infrastructure/service/wechat/config.py b/app/infrastructure/service/wechat/config.py new file mode 100644 index 0000000..3af6995 --- /dev/null +++ b/app/infrastructure/service/wechat/config.py @@ -0,0 +1,124 @@ +import os +from pathlib import Path + +from app.configs.runtime_config import get_bool, get_float, get_int, get_str + +PROJECT_ROOT = Path(__file__).resolve().parents[4] + + +def _local_appdata_root() -> Path: + local_appdata = (os.getenv("LOCALAPPDATA") or "").strip() + if local_appdata: + return Path(local_appdata) + return Path.home() / "AppData" / "Local" + + +def _resolve_path(path_value: str, base_dir: Path) -> str: + path = Path(path_value) + if not path.is_absolute(): + path = base_dir / path + return str(path.resolve()) + + +APP_NAME = (get_str("APP_NAME", "AiShiliu") or "AiShiliu").strip() or "AiShiliu" +APP_DATA_DIR = _resolve_path( + get_str("APP_DATA_DIR", "") or get_str("OPENCLAW_APP_DATA_DIR", "") or str(_local_appdata_root() / APP_NAME), + PROJECT_ROOT, +) +LOG_ROOT_DIR = _resolve_path(get_str("LOG_ROOT_DIR", os.path.join(APP_DATA_DIR, "logs")), PROJECT_ROOT) +BACKEND_LOG_DIR = _resolve_path(get_str("BACKEND_LOG_DIR", os.path.join(LOG_ROOT_DIR, "backend")), PROJECT_ROOT) +FRONTEND_LOG_DIR = _resolve_path(get_str("FRONTEND_LOG_DIR", os.path.join(LOG_ROOT_DIR, "frontend")), PROJECT_ROOT) +BACKEND_PYTHON_LOG_FILE = _resolve_path( + get_str("BACKEND_PYTHON_LOG_FILE", os.path.join(BACKEND_LOG_DIR, "python", "backend.log")), + PROJECT_ROOT, +) +BOT_LOG_FILE = _resolve_path( + get_str("BOT_LOG_FILE", os.path.join(BACKEND_LOG_DIR, "bot", "bot.log")), + PROJECT_ROOT, +) +BOT_SESSION_LIST_LOG_FILE = _resolve_path( + get_str("BOT_SESSION_LIST_LOG_FILE", os.path.join(BACKEND_LOG_DIR, "bot", "session_list.log")), + PROJECT_ROOT, +) +BOT_SESSION_DETAIL_LOG_FILE = _resolve_path( + get_str("BOT_SESSION_DETAIL_LOG_FILE", os.path.join(BACKEND_LOG_DIR, "bot", "session_detail.log")), + PROJECT_ROOT, +) +OCR_LOG_FILE = _resolve_path( + get_str("OCR_LOG_FILE", os.path.join(BACKEND_LOG_DIR, "ocr", "ocr.log")), + PROJECT_ROOT, +) +OCR_BAIDU_LOG_FILE = _resolve_path( + get_str("OCR_BAIDU_LOG_FILE", os.path.join(BACKEND_LOG_DIR, "ocr", "baidu.log")), + PROJECT_ROOT, +) +OCR_RAPID_LOG_FILE = _resolve_path( + get_str("OCR_RAPID_LOG_FILE", os.path.join(BACKEND_LOG_DIR, "ocr", "rapid.log")), + PROJECT_ROOT, +) +TAURI_LOG_FILE = _resolve_path( + get_str("TAURI_LOG_FILE", os.path.join(FRONTEND_LOG_DIR, "tauri", "tauri.log")), + PROJECT_ROOT, +) +VUE_LOG_FILE = _resolve_path( + get_str("VUE_LOG_FILE", os.path.join(FRONTEND_LOG_DIR, "vue", "vue.log")), + PROJECT_ROOT, +) +OCR_SAVE_DIR = _resolve_path(get_str("OCR_SAVE_DIR", os.path.join(BACKEND_LOG_DIR, "ocr_debug_images")), PROJECT_ROOT) +BLOCKED_ROW_CACHE_FILE = _resolve_path( + get_str("BLOCKED_ROW_CACHE_FILE", os.path.join(BACKEND_LOG_DIR, "state", "blocked_rows.json")), + PROJECT_ROOT, +) + +BAIDU_API_KEY = get_str("BAIDU_API_KEY", "") +BAIDU_SECRET_KEY = get_str("BAIDU_SECRET_KEY", "") +OCR_PROVIDER = get_str("OCR_PROVIDER", "baidu").strip().lower() +RAPID_OCR_DET_MODEL_PATH = get_str("RAPID_OCR_DET_MODEL_PATH", "app/resources/ocr_models/ch_PP-OCRv4_det.onnx").strip() +RAPID_OCR_REC_MODEL_PATH = get_str("RAPID_OCR_REC_MODEL_PATH", "app/resources/ocr_models/ch_PP-OCRv4_rec.onnx").strip() +RAPID_OCR_CLS_MODEL_PATH = get_str("RAPID_OCR_CLS_MODEL_PATH", "app/resources/ocr_models/ch_ppocr_mobile_v2.0_cls.onnx").strip() +BACKEND_URL = get_str("BACKEND_URL", "http://127.0.0.1:5000/api/messages/receive") +LOOP_INTERVAL = get_int("BOT_LOOP_INTERVAL", 3) +CLICK_AFTER_DELAY = get_float("BOT_CLICK_AFTER_DELAY", 1.2) +TITLE_AFTER_DELAY = get_float("BOT_TITLE_AFTER_DELAY", 1.0) +CONTACT_SWITCH_DELAY = get_float("BOT_CONTACT_SWITCH_DELAY", 1.0) +LOOP_ERROR_DELAY = get_float("BOT_LOOP_ERROR_DELAY", 3) +WECHAT_WINDOW_TARGET_WIDTH = get_int("WECHAT_WINDOW_TARGET_WIDTH", 1080) +WECHAT_WINDOW_TARGET_HEIGHT = get_int("WECHAT_WINDOW_TARGET_HEIGHT", 820) +WECHAT_WINDOW_TARGET_LEFT = get_int("WECHAT_WINDOW_TARGET_LEFT", 120) +WECHAT_WINDOW_TARGET_TOP = get_int("WECHAT_WINDOW_TARGET_TOP", 80) +OCR_SAVE_IMAGES = get_bool("OCR_SAVE_IMAGES", True) +CONTACT_ROW_HEIGHT = get_int("CONTACT_ROW_HEIGHT", 64) +CONTACT_ROW_WIDTH = get_int("CONTACT_ROW_WIDTH", 240) +CONTACT_LIST_LEFT_OFFSET = get_int("CONTACT_LIST_LEFT_OFFSET", 68) +CONTACT_LIST_TOP_OFFSET = get_int("CONTACT_LIST_TOP_OFFSET", 82) +CONTACT_LIST_BOTTOM_OFFSET = get_int("CONTACT_LIST_BOTTOM_OFFSET", 0) +SESSION_NAME_LEFT_OFFSET = get_int("SESSION_NAME_LEFT_OFFSET", 56) +SESSION_NAME_TOP_OFFSET = get_int("SESSION_NAME_TOP_OFFSET", 8) +SESSION_NAME_WIDTH = get_int("SESSION_NAME_WIDTH", 134) +SESSION_NAME_HEIGHT = get_int("SESSION_NAME_HEIGHT", 24) +SESSION_NAME_OCR_SCALE = get_int("SESSION_NAME_OCR_SCALE", 4) +SESSION_NAME_OCR_EXTRA_SCALE = get_int("SESSION_NAME_OCR_EXTRA_SCALE", 6) +CHAT_CAPTURE_LEFT_OFFSET = get_int("CHAT_CAPTURE_LEFT_OFFSET", 310) +CHAT_CAPTURE_TOP_OFFSET = get_int("CHAT_CAPTURE_TOP_OFFSET", 70) +CHAT_CAPTURE_WIDTH = get_int("CHAT_CAPTURE_WIDTH", 750) +CHAT_CAPTURE_HEIGHT = get_int("CHAT_CAPTURE_HEIGHT", 550) +OCR_TOP_PENALTY_RATIO = get_float("OCR_TOP_PENALTY_RATIO", 0.18) +OCR_TOP_PENALTY_BIN_FACTOR = get_float("OCR_TOP_PENALTY_BIN_FACTOR", 2.0) +OCR_TOP_PENALTY_COLOR_FACTOR = get_float("OCR_TOP_PENALTY_COLOR_FACTOR", 2.2) +TITLE_OCR_AREA_LEFT_OFFSET = get_int("TITLE_OCR_AREA_LEFT_OFFSET", 240) +TITLE_OCR_AREA_TOP_OFFSET = get_int("TITLE_OCR_AREA_TOP_OFFSET", 4) +TITLE_OCR_AREA_WIDTH = get_int("TITLE_OCR_AREA_WIDTH", 600) +TITLE_OCR_AREA_HEIGHT = get_int("TITLE_OCR_AREA_HEIGHT", 64) + +NO_REPLY_KEYWORDS = [ + "谢谢", "好的", "嗯", "哦", "ok", "收到", + "[图片]", "[语音]", "[视频]", "[文件]" +] + +BLOCKED_SESSION_KEYWORDS = [ + "服务号", "公众号", "微信公众平台", "文件传输助手" +] + +UI_NOISE_KEYWORDS = [ + "微信", "Weixin", "WeChat", "聊天信息", "搜索", "更多", "表情", "发送", "Message", "Messages" +] diff --git a/app/infrastructure/service/wechat/ocr.py b/app/infrastructure/service/wechat/ocr.py new file mode 100644 index 0000000..a95d8f2 --- /dev/null +++ b/app/infrastructure/service/wechat/ocr.py @@ -0,0 +1,346 @@ +import base64 +from io import BytesIO +from pathlib import Path + +import cv2 +import numpy as np +import requests +from PIL import Image + +from app.infrastructure.service.logging.log_service import log_event, new_trace_id +from app.infrastructure.service.wechat.config import ( + BAIDU_API_KEY, + BAIDU_SECRET_KEY, + OCR_PROVIDER, + RAPID_OCR_CLS_MODEL_PATH, + RAPID_OCR_DET_MODEL_PATH, + RAPID_OCR_REC_MODEL_PATH, + SESSION_NAME_OCR_EXTRA_SCALE, + SESSION_NAME_OCR_SCALE, +) + + +BAIDU_FALLBACK_ERROR_CODES = {17, 18, 110, 111} + + +def _runtime_roots() -> list[Path]: + roots: list[Path] = [] + + meipass = getattr(__import__("sys"), "_MEIPASS", None) + if meipass: + roots.append(Path(meipass)) + + file_root = Path(__file__).resolve().parents[4] + roots.append(file_root) + + cwd = Path.cwd().resolve() + roots.append(cwd) + roots.append(cwd / "resources") + roots.append(cwd / "app") + + try: + exe_parent = Path(__import__("sys").executable).resolve().parent + roots.append(exe_parent) + roots.append(exe_parent / "resources") + roots.append(exe_parent / "app") + except Exception: + pass + + unique_roots: list[Path] = [] + seen = set() + for root in roots: + key = str(root) + if key in seen: + continue + seen.add(key) + unique_roots.append(root) + return unique_roots + + +def _resolve_project_path(path_str: str) -> str: + path = Path(path_str) + if path.is_absolute(): + return str(path) + + candidates = [(root / path).resolve() for root in _runtime_roots()] + for candidate in candidates: + if candidate.exists(): + return str(candidate) + return str(candidates[0]) + + +class OCRBase: + provider_name = "base" + + def recognize(self, image_data, scene="generic", mode="generic"): + raise NotImplementedError + + +class BaiduOCR(OCRBase): + provider_name = "baidu" + + def __init__(self, api_key, secret_key): + self.api_key = api_key + self.secret_key = secret_key + self.access_token = None + self.last_error_code = None + self.last_error_msg = "" + self.get_access_token() + + def get_access_token(self): + trace_id = new_trace_id("ocr") + if not self.api_key or not self.secret_key: + log_event("WARNING", "ocr", "ocr.baidu.token", trace_id, "token", "failed", "百度OCR凭据缺失", reason="credential_missing") + return + url = "https://aip.baidubce.com/oauth/2.0/token" + params = {"grant_type": "client_credentials", "client_id": self.api_key, "client_secret": self.secret_key} + try: + response = requests.post(url, params=params, timeout=10) + if response.status_code == 200: + self.access_token = response.json().get("access_token") + if self.access_token: + log_event("INFO", "ocr", "ocr.baidu.token", trace_id, "token", "ok", "百度OCR token获取成功") + else: + log_event("WARNING", "ocr", "ocr.baidu.token", trace_id, "token", "failed", "百度OCR token为空", reason="token_empty") + else: + log_event("WARNING", "ocr", "ocr.baidu.token", trace_id, "token", "failed", "百度OCR token获取失败", reason="http_error", extra={"status_code": response.status_code}) + except Exception as e: + log_event("ERROR", "ocr", "ocr.baidu.token", trace_id, "token", "failed", "百度OCR token请求异常", reason="request_error", extra={"error": str(e)}) + + def _reset_last_error(self): + self.last_error_code = None + self.last_error_msg = "" + + def should_fallback_to_rapid(self): + return self.last_error_code in BAIDU_FALLBACK_ERROR_CODES + + def recognize(self, image_data, scene="generic", mode="generic"): + trace_id = new_trace_id("ocr") + self._reset_last_error() + if not self.access_token: + self.last_error_msg = "no_access_token" + log_event("WARNING", "ocr", "ocr.baidu.recognize", trace_id, "recognize", "failed", "百度OCR无可用token", reason="no_access_token", extra={"scene": scene}) + return [] + url = f"https://aip.baidubce.com/rest/2.0/ocr/v1/general_basic?access_token={self.access_token}" + payload = {"image": base64.b64encode(image_data).decode(), "language_type": "CHN_ENG", "detect_direction": "true", "probability": "true"} + try: + response = requests.post(url, data=payload, timeout=10) + if response.status_code == 200: + result = response.json() + if "error_code" in result: + self.last_error_code = result.get("error_code") + self.last_error_msg = result.get("error_msg") or "" + log_event("WARNING", "ocr", "ocr.baidu.recognize", trace_id, "recognize", "failed", "百度OCR返回错误码", reason="baidu_error", extra={"scene": scene, "error_code": self.last_error_code, "error_msg": self.last_error_msg}) + return [] + if "words_result" in result: + lines = [] + for item in result["words_result"]: + text = item.get("words", "") + prob = item.get("probability", {}).get("average", 0.9) + if text and prob > 0.6: + lines.append(text) + log_event("INFO", "ocr", "ocr.baidu.recognize", trace_id, "recognize", "ok", "百度OCR识别完成", extra={"scene": scene, "line_count": len(lines)}) + return lines + else: + self.last_error_msg = f"http_{response.status_code}" + log_event("WARNING", "ocr", "ocr.baidu.recognize", trace_id, "recognize", "failed", "百度OCR请求失败", reason="http_error", extra={"scene": scene, "status_code": response.status_code}) + except Exception as e: + self.last_error_msg = str(e) + log_event("ERROR", "ocr", "ocr.baidu.recognize", trace_id, "recognize", "failed", "百度OCR请求异常", reason="request_error", extra={"scene": scene, "error": str(e)}) + return [] + + +class RapidLocalOCR(OCRBase): + provider_name = "rapid" + + def __init__(self): + self.ready = False + self.engine = None + self._init_engine() + + def ensure_ready(self): + return self.ready and self.engine is not None + + def _init_engine(self): + trace_id = new_trace_id("ocr") + try: + from rapidocr_onnxruntime import RapidOCR + + model_paths = { + "det_model_path": _resolve_project_path(RAPID_OCR_DET_MODEL_PATH), + "rec_model_path": _resolve_project_path(RAPID_OCR_REC_MODEL_PATH), + "cls_model_path": _resolve_project_path(RAPID_OCR_CLS_MODEL_PATH), + } + existing_model_paths = {key: value for key, value in model_paths.items() if Path(value).exists()} + if len(existing_model_paths) == len(model_paths): + self.engine = RapidOCR(**existing_model_paths) + log_extra = existing_model_paths + else: + self.engine = RapidOCR() + log_extra = {**model_paths, "missing_models": [value for value in model_paths.values() if not Path(value).exists()]} + self.ready = True + log_event("INFO", "ocr", "ocr.rapid.init", trace_id, "init", "ok", "RapidOCR初始化成功", extra=log_extra) + except Exception as e: + self.ready = False + log_event("WARNING", "ocr", "ocr.rapid.init", trace_id, "init", "failed", "RapidOCR初始化失败", reason="init_error", extra={"error": str(e)}) + + def recognize(self, image_data, scene="generic", mode="generic"): + trace_id = new_trace_id("ocr") + if not self.ready or self.engine is None: + log_event("WARNING", "ocr", "ocr.rapid.recognize", trace_id, "recognize", "failed", "RapidOCR未就绪", reason="not_ready", extra={"scene": scene}) + return [] + try: + img_np = np.frombuffer(image_data, dtype=np.uint8) + img = cv2.imdecode(img_np, cv2.IMREAD_COLOR) + if img is None: + log_event("WARNING", "ocr", "ocr.rapid.recognize", trace_id, "recognize", "failed", "RapidOCR图像解码失败", reason="decode_failed", extra={"scene": scene}) + return [] + result = self.engine(img) + if not result or len(result) < 1: + log_event("INFO", "ocr", "ocr.rapid.recognize", trace_id, "recognize", "ok", "RapidOCR识别结果为空", reason="empty_result", extra={"scene": scene}) + return [] + rec_res = result[0] or [] + lines = [] + for item in rec_res: + if not item or len(item) < 2: + continue + text = str(item[1]).strip() + if text: + lines.append(text) + log_event("INFO", "ocr", "ocr.rapid.recognize", trace_id, "recognize", "ok", "RapidOCR识别完成", extra={"scene": scene, "line_count": len(lines)}) + return lines + except Exception as e: + log_event("ERROR", "ocr", "ocr.rapid.recognize", trace_id, "recognize", "failed", "RapidOCR识别异常", reason="recognize_error", extra={"scene": scene, "error": str(e)}) + return [] + + +class OCRService(OCRBase): + provider_name = "service" + + def __init__(self, provider=None): + self.provider_requested = (provider or OCR_PROVIDER or "baidu").strip().lower() + self.baidu_provider = BaiduOCR(BAIDU_API_KEY, BAIDU_SECRET_KEY) + self.rapid_provider = RapidLocalOCR() + self.provider = self._build_provider(self.provider_requested) + + def _build_provider(self, provider_name: str): + if provider_name in {"rapid", "rapidocr"}: + return self.rapid_provider + if provider_name in {"baidu", "baiduocr"}: + return self.baidu_provider + if provider_name == "auto": + if self.baidu_provider.access_token: + return self.baidu_provider + if self.rapid_provider.ensure_ready(): + return self.rapid_provider + return self.baidu_provider + return self.baidu_provider + + def _provider_recognize(self, image_data, scene): + trace_id = new_trace_id("ocr") + lines = self.provider.recognize(image_data, scene=scene) + if self.provider.provider_name != "baidu": + return lines + if lines: + return lines + no_token_fallback = self.baidu_provider.last_error_msg == "no_access_token" + should_fallback = self.baidu_provider.should_fallback_to_rapid() or no_token_fallback + if not should_fallback: + return lines + if not self.rapid_provider.ensure_ready(): + log_event("WARNING", "ocr", "ocr.fallback", trace_id, "fallback", "failed", "触发Rapid回退但引擎未就绪", reason="rapid_not_ready", extra={"scene": scene, "baidu_error": self.baidu_provider.last_error_msg or ""}) + return lines + rapid_lines = self.rapid_provider.recognize(image_data, scene=f"{scene}_rapid_fallback") + if rapid_lines: + log_event("INFO", "ocr", "ocr.fallback", trace_id, "fallback", "ok", "百度OCR回退Rapid成功", reason="fallback_success", extra={"scene": scene, "line_count": len(rapid_lines)}) + else: + log_event("WARNING", "ocr", "ocr.fallback", trace_id, "fallback", "failed", "百度OCR回退Rapid失败", reason="fallback_empty", extra={"scene": scene}) + return rapid_lines + + def _encode_image(self, image_obj): + buf = BytesIO() + image_obj.save(buf, format="PNG") + return buf.getvalue() + + def _normalize_lines(self, lines, min_len=1, exclude=None): + exclude = set(exclude or []) + normalized = [] + for line in lines or []: + text = str(line).strip() + if not text: + continue + if len(text) < min_len: + continue + if text in exclude: + continue + normalized.append(text) + return normalized + + def _build_session_name_variants(self, image_data): + image = Image.open(BytesIO(image_data)).convert("RGB") + gray = image.convert("L") + base_scale = max(2, int(SESSION_NAME_OCR_SCALE)) + extra_scale = max(base_scale, int(SESSION_NAME_OCR_EXTRA_SCALE)) + + enlarged = gray.resize( + (gray.width * base_scale, gray.height * base_scale), + resample=Image.Resampling.LANCZOS, + ) + contrast = cv2.equalizeHist(np.array(enlarged)) + binary = cv2.threshold(contrast, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1] + binary_inv = cv2.threshold(contrast, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1] + + extra_enlarged = gray.resize( + (gray.width * extra_scale, gray.height * extra_scale), + resample=Image.Resampling.LANCZOS, + ) + extra_contrast = cv2.equalizeHist(np.array(extra_enlarged)) + + return [ + ("name_crop", image_data), + (f"name_orig_{base_scale}x", self._encode_image(enlarged)), + (f"name_eq_{base_scale}x", self._encode_image(Image.fromarray(contrast))), + (f"name_bin_{base_scale}x", self._encode_image(Image.fromarray(binary))), + (f"name_bin_inv_{base_scale}x", self._encode_image(Image.fromarray(binary_inv))), + (f"name_orig_{extra_scale}x", self._encode_image(extra_enlarged)), + (f"name_eq_{extra_scale}x", self._encode_image(Image.fromarray(extra_contrast))), + ] + + def _recognize_session_name(self, image_data, scene): + trace_id = new_trace_id("ocr") + for variant_name, variant_bytes in self._build_session_name_variants(image_data): + lines = self._normalize_lines( + self._provider_recognize(variant_bytes, scene=f"{scene}_{variant_name}"), + min_len=1, + ) + if lines: + log_event("INFO", "ocr", "ocr.session_name", trace_id, "recognize", "ok", "会话名识别成功", extra={"scene": scene, "variant": variant_name, "line_count": len(lines)}) + return lines + log_event("INFO", "ocr", "ocr.session_name", trace_id, "recognize", "failed", "会话名识别为空", reason="empty_result", extra={"scene": scene}) + return [] + + def _recognize_session_title(self, image_data, scene): + trace_id = new_trace_id("ocr") + lines = self._provider_recognize(image_data, scene=scene) + normalized = self._normalize_lines(lines, min_len=1) + if normalized: + log_event("INFO", "ocr", "ocr.session_title", trace_id, "recognize", "ok", "会话标题识别成功", extra={"scene": scene, "line_count": len(normalized)}) + else: + log_event("INFO", "ocr", "ocr.session_title", trace_id, "recognize", "failed", "会话标题识别为空", reason="empty_result", extra={"scene": scene}) + return normalized + + def recognize_session_name(self, image_data, scene="session_name"): + return self._recognize_session_name(image_data, scene=scene) + + def recognize_session_title(self, image_data, scene="session_title"): + return self._recognize_session_title(image_data, scene=scene) + + def recognize(self, image_data, scene="generic", mode="generic"): + trace_id = new_trace_id("ocr") + if mode == "session_name": + return self.recognize_session_name(image_data, scene=scene) + if mode == "session_title": + return self.recognize_session_title(image_data, scene=scene) + lines = self._normalize_lines(self._provider_recognize(image_data, scene=scene), min_len=1) + log_event("INFO", "ocr", "ocr.generic", trace_id, "recognize", "ok", "通用OCR识别完成", extra={"scene": scene, "line_count": len(lines)}) + return lines diff --git a/app/infrastructure/service/wechat/screenshot.py b/app/infrastructure/service/wechat/screenshot.py new file mode 100644 index 0000000..46e3e19 --- /dev/null +++ b/app/infrastructure/service/wechat/screenshot.py @@ -0,0 +1,314 @@ +from __future__ import annotations + +from dataclasses import dataclass +from typing import Dict + +import cv2 +import numpy as np +from PIL import ImageGrab + +from app.infrastructure.service.logging.log_service import log_event, new_trace_id +from app.infrastructure.service.wechat.config import ( + CHAT_CAPTURE_HEIGHT, + CHAT_CAPTURE_LEFT_OFFSET, + CHAT_CAPTURE_TOP_OFFSET, + CHAT_CAPTURE_WIDTH, + CONTACT_LIST_BOTTOM_OFFSET, + CONTACT_LIST_LEFT_OFFSET, + CONTACT_LIST_TOP_OFFSET, + CONTACT_ROW_WIDTH, + SESSION_NAME_HEIGHT, + SESSION_NAME_LEFT_OFFSET, + SESSION_NAME_TOP_OFFSET, + SESSION_NAME_WIDTH, + TITLE_OCR_AREA_HEIGHT, + TITLE_OCR_AREA_LEFT_OFFSET, + TITLE_OCR_AREA_TOP_OFFSET, + TITLE_OCR_AREA_WIDTH, +) + + +@dataclass +class CaptureBox: + left: int + top: int + right: int + bottom: int + + @property + def width(self) -> int: + return self.right - self.left + + @property + def height(self) -> int: + return self.bottom - self.top + + def as_tuple(self): + return (self.left, self.top, self.right, self.bottom) + + def as_dict(self) -> Dict[str, int]: + return { + "left": self.left, + "top": self.top, + "right": self.right, + "bottom": self.bottom, + "width": self.width, + "height": self.height, + } + + +class ScreenshotService: + def build_box(self, left: int, top: int, width: int, height: int) -> CaptureBox: + return CaptureBox( + left=int(left), + top=int(top), + right=int(left + width), + bottom=int(top + height), + ) + + def build_box_from_window(self, window_rect: dict, left_offset: int, top_offset: int, width: int, height: int) -> CaptureBox: + return self.build_box( + left=window_rect["left"] + int(left_offset), + top=window_rect["top"] + int(top_offset), + width=int(width), + height=int(height), + ) + + def build_contact_list_box(self, window_rect: dict, left_offset: int, top_offset: int, width: int, bottom_offset: int) -> CaptureBox: + left = window_rect["left"] + int(left_offset) + top = window_rect["top"] + int(top_offset) + right = left + int(width) + bottom = window_rect["bottom"] - int(bottom_offset) + return CaptureBox(left=left, top=top, right=right, bottom=bottom) + + def is_valid_box(self, box: CaptureBox) -> bool: + return box.right > box.left and box.bottom > box.top + + def capture_box(self, left: int, top: int, width: int, height: int): + box = self.build_box(left, top, width, height) + if not self.is_valid_box(box): + raise ValueError(f"invalid capture box: {box.as_dict()}") + return ImageGrab.grab(bbox=box.as_tuple()) + + def capture_from_window(self, window_rect: dict, left_offset: int, top_offset: int, width: int, height: int): + box = self.build_box_from_window(window_rect, left_offset, top_offset, width, height) + if not self.is_valid_box(box): + raise ValueError(f"invalid window capture box: {box.as_dict()}") + return ImageGrab.grab(bbox=box.as_tuple()) + + def capture_contact_list(self, window_rect: dict, left_offset: int, top_offset: int, width: int, bottom_offset: int): + box = self.build_contact_list_box(window_rect, left_offset, top_offset, width, bottom_offset) + if not self.is_valid_box(box): + raise ValueError(f"invalid contact list box: {box.as_dict()}") + return ImageGrab.grab(bbox=box.as_tuple()) + + def get_contact_list_box(self, window_rect: dict) -> CaptureBox: + return self.build_contact_list_box( + window_rect, + left_offset=CONTACT_LIST_LEFT_OFFSET, + top_offset=CONTACT_LIST_TOP_OFFSET, + width=CONTACT_ROW_WIDTH, + bottom_offset=CONTACT_LIST_BOTTOM_OFFSET, + ) + + def capture_contact_list_default(self, window_rect: dict): + trace_id = new_trace_id("capture") + box = self.get_contact_list_box(window_rect) + log_event("INFO", "capture", "capture.contact_list", trace_id, "capture", "ok", "截图会话列表区域", extra=box.as_dict()) + return self.capture_contact_list( + window_rect, + left_offset=CONTACT_LIST_LEFT_OFFSET, + top_offset=CONTACT_LIST_TOP_OFFSET, + width=CONTACT_ROW_WIDTH, + bottom_offset=CONTACT_LIST_BOTTOM_OFFSET, + ) + + def get_session_title_box(self, window_rect: dict) -> CaptureBox: + return self.build_box_from_window( + window_rect, + left_offset=TITLE_OCR_AREA_LEFT_OFFSET, + top_offset=TITLE_OCR_AREA_TOP_OFFSET, + width=TITLE_OCR_AREA_WIDTH, + height=TITLE_OCR_AREA_HEIGHT, + ) + + def capture_session_title(self, window_rect: dict): + trace_id = new_trace_id("capture") + box = self.get_session_title_box(window_rect) + log_event("INFO", "capture", "capture.session_title", trace_id, "capture", "ok", "截图会话标题区域", extra=box.as_dict()) + return self.capture_area_from_box(box) + + def get_chat_capture_box(self, window_rect: dict) -> CaptureBox: + base_height = max(120, CHAT_CAPTURE_HEIGHT) + max_height = max(base_height, window_rect["height"] - CHAT_CAPTURE_TOP_OFFSET) + return self.build_box_from_window( + window_rect, + left_offset=CHAT_CAPTURE_LEFT_OFFSET, + top_offset=CHAT_CAPTURE_TOP_OFFSET, + width=CHAT_CAPTURE_WIDTH, + height=max_height, + ) + + def capture_chat_area(self, window_rect: dict): + trace_id = new_trace_id("capture") + box = self.get_chat_capture_box(window_rect) + image = self.capture_area_from_box(box) + chat_bottom = self._detect_chat_bottom_by_binary_merge(image) + if chat_bottom is not None: + image = image.crop((0, 0, image.size[0], chat_bottom)) + extra = box.as_dict() + extra["dynamic_bottom"] = chat_bottom or "" + extra["final_width"] = image.size[0] + extra["final_height"] = image.size[1] + log_event("INFO", "capture", "capture.chat_area", trace_id, "capture", "ok", "截图聊天区域", extra=extra) + return image + + def crop_session_name(self, row_img): + return self.crop_from_image( + row_img, + left=SESSION_NAME_LEFT_OFFSET, + top=SESSION_NAME_TOP_OFFSET, + width=SESSION_NAME_WIDTH, + height=SESSION_NAME_HEIGHT, + ) + + def capture_area_from_box(self, box: CaptureBox): + if not self.is_valid_box(box): + raise ValueError(f"invalid capture box: {box.as_dict()}") + return ImageGrab.grab(bbox=box.as_tuple()) + + def _build_merged_binary_array(self, image_obj): + arr = np.array(image_obj.convert("RGB")) + gray = cv2.cvtColor(arr, cv2.COLOR_RGB2GRAY) + blurred = cv2.GaussianBlur(gray, (5, 5), 0) + _, binary_inv = cv2.threshold(blurred, 248, 255, cv2.THRESH_BINARY_INV) + adaptive_inv = cv2.adaptiveThreshold( + blurred, + 255, + cv2.ADAPTIVE_THRESH_GAUSSIAN_C, + cv2.THRESH_BINARY_INV, + 13, + 1, + ) + merged = cv2.bitwise_or(binary_inv, adaptive_inv) + kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 1)) + merged = cv2.morphologyEx(merged, cv2.MORPH_CLOSE, kernel, iterations=1) + merged = cv2.morphologyEx(merged, cv2.MORPH_OPEN, cv2.getStructuringElement(cv2.MORPH_RECT, (2, 2))) + return merged + + def _detect_chat_bottom_by_binary_merge(self, image_obj) -> int | None: + if image_obj is None: + return None + merged = self._build_merged_binary_array(image_obj) + img_h, img_w = merged.shape[:2] + start_y = max(0, int(img_h * 0.55)) + roi = merged[start_y:, :] + if roi.size == 0: + return None + row_density = (roi > 0).mean(axis=1) + min_run = max(28, int(img_h * 0.045)) + dense_limit = 0.018 + run_start = None + candidates = [] + for idx, density in enumerate(row_density.tolist() + [1.0]): + is_blank = density <= dense_limit + if is_blank and run_start is None: + run_start = idx + continue + if is_blank: + continue + if run_start is not None: + run_end = idx + if run_end - run_start >= min_run: + top = start_y + run_start + bottom = start_y + run_end + if top >= img_h * 0.58 and bottom <= img_h - 8: + candidates.append((top, bottom)) + run_start = None + if not candidates: + return self._detect_chat_bottom(image_obj) + top, _ = candidates[-1] + bottom = max(120, int(top - 4)) + if bottom >= img_h - 20: + return None + return bottom + + def crop_from_image(self, image_obj, left: int, top: int, width: int, height: int): + if image_obj is None: + return None + img_w, img_h = image_obj.size + crop_left = min(max(0, int(left)), img_w) + crop_top = min(max(0, int(top)), img_h) + crop_right = min(img_w, crop_left + max(1, int(width))) + crop_bottom = min(img_h, crop_top + max(1, int(height))) + if crop_right <= crop_left or crop_bottom <= crop_top: + return None + return image_obj.crop((crop_left, crop_top, crop_right, crop_bottom)) + + def _detect_chat_bottom(self, image_obj) -> int | None: + if image_obj is None: + return None + img_rgb = np.array(image_obj.convert("RGB")) + if img_rgb.size == 0: + return None + gray = cv2.cvtColor(img_rgb, cv2.COLOR_RGB2GRAY) + img_h, img_w = gray.shape[:2] + start_y = max(0, int(img_h * 0.55)) + focus = gray[start_y:, :] + if focus.size == 0: + return None + row_mean = focus.mean(axis=1) + row_std = focus.std(axis=1) + bright_mask = (row_mean >= 242) & (row_std <= 18) + run = self._find_last_run(bright_mask, min_len=max(18, int(img_h * 0.035))) + candidate_y = None + if run is not None: + run_top, run_bottom = run + candidate_y = start_y + run_top + edge_img = cv2.Canny(focus, 40, 120) + edge_strength = edge_img.mean(axis=1) + if len(row_mean) >= 2: + transition = np.abs(np.diff(row_mean, prepend=row_mean[0])) + else: + transition = np.zeros_like(row_mean) + score = edge_strength * 1.8 + transition * 2.4 + score[: max(8, int(len(score) * 0.15))] = 0 + if candidate_y is not None: + local_limit = max(0, candidate_y - start_y + 4) + score[local_limit:] = 0 + best_idx = int(np.argmax(score)) if score.size else -1 + best_score = float(score[best_idx]) if best_idx >= 0 else 0.0 + edge_candidate = None + if best_idx >= 0 and best_score >= 12.0: + edge_candidate = start_y + best_idx + final_y = None + if candidate_y is not None and edge_candidate is not None: + if abs(candidate_y - edge_candidate) <= 28: + final_y = min(candidate_y, edge_candidate) + else: + final_y = candidate_y + else: + final_y = candidate_y if candidate_y is not None else edge_candidate + if final_y is None: + return None + final_y = max(120, min(img_h, int(final_y - 6))) + if final_y >= img_h - 20: + return None + return final_y + + def _find_last_run(self, mask: np.ndarray, min_len: int) -> tuple[int, int] | None: + run_start = None + best = None + for idx, flag in enumerate(mask.tolist() + [False]): + if flag and run_start is None: + run_start = idx + continue + if flag: + continue + if run_start is None: + continue + run_len = idx - run_start + if run_len >= min_len: + best = (run_start, idx) + run_start = None + return best diff --git a/app/infrastructure/service/wechat/session_service.py b/app/infrastructure/service/wechat/session_service.py new file mode 100644 index 0000000..758fea6 --- /dev/null +++ b/app/infrastructure/service/wechat/session_service.py @@ -0,0 +1,288 @@ +from __future__ import annotations + +from dataclasses import dataclass +from io import BytesIO +import json +import os +from typing import Callable + +import cv2 +import numpy as np + +from app.infrastructure.service.logging.log_service import log_event, new_trace_id +from app.infrastructure.service.wechat.chat_snapshot_analyzer import analyze_pil_image +from app.infrastructure.service.wechat.unread_session_analyzer import UnreadSessionAnalyzer +from app.infrastructure.service.wechat.config import ( + BLOCKED_SESSION_KEYWORDS, + CONTACT_ROW_HEIGHT, + OCR_SAVE_DIR, + OCR_SAVE_IMAGES, + SESSION_NAME_HEIGHT, + SESSION_NAME_LEFT_OFFSET, + SESSION_NAME_TOP_OFFSET, + SESSION_NAME_WIDTH, + UI_NOISE_KEYWORDS, +) + + + +# 会话扫描结果数据类，包含所有会话列表和未读会话列表 +@dataclass +class SessionScanResult: + sessions: list[dict] + unread_sessions: list[dict] + + +# 聊天快照分析结果数据类 +@dataclass +class ChatAnalyzeResult: + ok: bool + file_name: str + latest_text: str + confidence: str | float + bubble_side: str + screenshot_path: str + + +# 微信会话服务类，处理会话列表扫描、红点检测和聊天截图分析 +class WechatSessionService: + def __init__(self, screenshot_service, ocr_service, save_debug_image: Callable | None = None): + self.screenshot = screenshot_service + self.ocr = ocr_service + self.save_debug_image = save_debug_image + self._session_title_cache = {"value": "", "ts": 0.0} + self.unread_analyzer = UnreadSessionAnalyzer() + log_event("INFO", "bot", "bot.session_service.init", new_trace_id("bot"), "init", "ok", "会话服务初始化完成") + +# 根据窗口矩形计算会话列表区域的位置 + def get_contact_list_rect(self, window_rect): + box = self.screenshot.get_contact_list_box(window_rect) + return { + 'left': box.left, + 'top': box.top, + 'right': box.right, + 'bottom': box.bottom, + } + +# 从会话行图片中裁剪出会话名称区域 + def extract_session_name_image(self, row_img): + return self.screenshot.crop_session_name(row_img) + +# 检测会话列表中的所有红点位置（红色圆点表示未读消息） + def detect_red_dots(self, window_rect): + contact_rect = self.get_contact_list_rect(window_rect) + screenshot = self.screenshot.capture_contact_list_default(window_rect) + return self.unread_analyzer.detect_red_dots(contact_rect, screenshot) + +# 检测单行会话图片中是否有未读红点标记（严格模式） + def row_has_red_dot(self, row_img, relaxed=False): + return self.unread_analyzer.row_has_red_dot(row_img, relaxed=relaxed) + +# 检测单行会话图片中是否有未读红点标记（宽松模式） + def row_has_red_dot_weak(self, row_img): + return self.unread_analyzer.row_has_red_dot_weak(row_img) + +# 扫描所有会话行，识别哪些有未读消息标记 + def get_all_sessions_with_unread(self, window_rect, round_count): + trace_id = new_trace_id("bot") + contact_rect = self.get_contact_list_rect(window_rect) + screenshot = self.screenshot.capture_contact_list_default(window_rect) + + sessions, unread_sessions = self.unread_analyzer.get_all_sessions_with_unread( + contact_rect=contact_rect, + screenshot=screenshot, + round_count=round_count, + save_debug_image=lambda image_obj, filename: self._save_debug_image(image_obj, filename), + ) + self._save_session_scan_debug(round_count=round_count, sessions=sessions, unread_sessions=unread_sessions, contact_rect=contact_rect) + log_event("INFO", "bot", "bot.session_scan", trace_id, "scan", "ok", "会话扫描完成", extra={"round": int(round_count), "total": len(sessions), "unread": len(unread_sessions)}) + return SessionScanResult(sessions=sessions, unread_sessions=unread_sessions) + +# 标准化文本用于匹配：去除空格并转为小写 + def normalize_match_text(self, text): + if not text: + return "" + text = str(text).strip().lower() + return "".join(ch for ch in text if not ch.isspace()) + +# 生成会话屏蔽关键字的唯一标识key，用于缓存比对 + def make_block_key(self, text): + normalized = self.normalize_match_text(text) + if not normalized: + return "" + return f"title:{normalized}" + +# 重置当前会话标题缓存 + def reset_session_title_cache(self): + self._session_title_cache = {"value": "", "ts": 0.0} + +# 通过OCR识别当前会话窗口的标题文字 + def get_session_title_by_ocr(self, window_rect): + trace_id = new_trace_id("bot") + try: + if not window_rect: + return "" + area_name = "main" + screenshot = self.screenshot.capture_session_title(window_rect) + img_bytes = BytesIO() + screenshot.save(img_bytes, format='PNG') + valid = self.ocr.recognize_session_title(img_bytes.getvalue(), scene=f"session_title_{area_name}") + if valid: + title = valid[0] + log_event("INFO", "bot", "bot.session_title", trace_id, "ocr", "ok", "会话标题识别成功", extra={"title": title}) + return title + log_event("INFO", "bot", "bot.session_title", trace_id, "ocr", "failed", "会话标题识别为空", reason="empty_result") + return "" + except Exception as e: + log_event("ERROR", "bot", "bot.session_title", trace_id, "ocr", "failed", "会话标题识别异常", reason="ocr_error", extra={"error": str(e)}) + return "" + +# 获取当前会话标题，优先使用缓存避免频繁OCR调用 + def get_current_session_title(self, window_rect): + try: + import time + + now_ts = time.time() + cached_title = (self._session_title_cache.get("value") or "").strip() + cached_ts = float(self._session_title_cache.get("ts") or 0.0) + if cached_title and now_ts - cached_ts <= 1.2: + return cached_title + + title = (self.get_session_title_by_ocr(window_rect) or "").strip() + if title and title not in UI_NOISE_KEYWORDS: + self._session_title_cache = {"value": title, "ts": now_ts} + return title + except Exception as e: + return "" + +# 判断当前选中的会话是否应被跳过（点击后标题检查阶段） + def should_skip_current_session(self, window_rect, session, blocked_row_cache, save_blocked_row_cache: Callable): + title = self.get_current_session_title(window_rect) + block_key = self.make_block_key(title) + if block_key and block_key in blocked_row_cache: + return True + normalized_title = self.normalize_match_text(title) + for keyword in BLOCKED_SESSION_KEYWORDS: + if self.normalize_match_text(keyword) in normalized_title: + if block_key: + blocked_row_cache[block_key] = title or keyword + save_blocked_row_cache() + return True + return False + +# 比较两个会话名称是否匹配（考虑模糊匹配和大小写） + def is_same_session(self, expected_session, current_session): + expected = self.normalize_match_text(expected_session) + current = self.normalize_match_text(current_session) + if not expected or not current: + return False + return expected in current or current in expected + +# 根据OCR识别结果判断会话列表中的会话是否应被跳过 + def should_skip_session_by_ocr(self, session, blocked_row_cache, save_blocked_row_cache: Callable): + image_obj = session.get('row_img') + if image_obj is None: + return False + try: + name_img = self.extract_session_name_image(image_obj) + if name_img is None: + return False + + crop_box = { + 'left': SESSION_NAME_LEFT_OFFSET, + 'top': SESSION_NAME_TOP_OFFSET, + 'width': SESSION_NAME_WIDTH, + 'height': SESSION_NAME_HEIGHT, + 'row_w': image_obj.size[0], + 'row_h': image_obj.size[1], + 'crop_w': name_img.size[0], + 'crop_h': name_img.size[1], + } + if OCR_SAVE_IMAGES: + file_name = f"row_{int(session.get('row_idx', 0)):03d}_name_raw.png" + self._save_debug_image(name_img, os.path.join('sessions', 'name_ocr', file_name)) + + img_bytes = BytesIO() + name_img.save(img_bytes, format='PNG') + lines = self.ocr.recognize_session_name(img_bytes.getvalue(), scene=f"session_row_{session.get('row_idx')}") + line_text = ' '.join(lines) + session['list_ocr_title'] = line_text + normalized_text = self.normalize_match_text(line_text) + block_key = self.make_block_key(line_text) + if block_key and block_key in blocked_row_cache: + return True + for keyword in BLOCKED_SESSION_KEYWORDS: + if self.normalize_match_text(keyword) in normalized_text: + if block_key: + blocked_row_cache[block_key] = line_text or keyword + save_blocked_row_cache() + return True + return False + except Exception as e: + return False + +# 分析点击后的聊天区域截图，提取最新消息文本并返回分析结果 + def analyze_clicked_session(self, window_rect, round_count, row_idx): + trace_id = new_trace_id("bot") + chat_box = self.screenshot.get_chat_capture_box(window_rect) + if not self.screenshot.is_valid_box(chat_box): + log_event("WARNING", "bot", "bot.chat_analyze", trace_id, "capture", "failed", "聊天区截图区域无效", reason="invalid_box") + return ChatAnalyzeResult(ok=False, file_name='', latest_text='', confidence='', bubble_side='', screenshot_path='') + + screenshot = self.screenshot.capture_chat_area(window_rect) + file_name = f"round_{round_count:04d}_row_{row_idx:03d}_chat.png" + rel_path = os.path.join('sessions', 'clicked', file_name) + self._save_debug_image(screenshot, rel_path) + result = analyze_pil_image(screenshot, stem=os.path.splitext(file_name)[0], file_name=file_name) + latest_text = (getattr(result, 'latest_text', None) or '').strip() + confidence = getattr(result, 'confidence', '') + bubble_side = getattr(result, 'bubble_side', '') + log_event("INFO", "bot", "bot.chat_analyze", trace_id, "analyze", "ok", "聊天截图分析完成", extra={"round": int(round_count), "row_idx": int(row_idx), "has_text": bool(latest_text), "bubble_side": bubble_side or "", "confidence": confidence}) + return ChatAnalyzeResult( + ok=bool(latest_text), + file_name=file_name, + latest_text=latest_text, + confidence=confidence, + bubble_side=bubble_side, + screenshot_path=rel_path, + ) + +# 保存会话扫描调试数据（类似聊天分析输出 result.json） + def _save_session_scan_debug(self, round_count: int, sessions: list[dict], unread_sessions: list[dict], contact_rect: dict): + if not OCR_SAVE_IMAGES: + return + try: + debug_dir = os.path.join(OCR_SAVE_DIR, 'sessions', 'scan_debug') + os.makedirs(debug_dir, exist_ok=True) + file_name = f"round_{round_count:04d}_scan.json" + file_path = os.path.join(debug_dir, file_name) + rows = [] + for session in sessions: + rows.append({ + 'row_idx': session.get('row_idx'), + 'has_red_dot': bool(session.get('has_red_dot')), + 'has_red_by_global': bool(session.get('has_red_by_global')), + 'has_red_by_row': bool(session.get('has_red_by_row')), + 'has_red_by_row_weak': bool(session.get('has_red_by_row_weak')), + 'click_x': session.get('click_x'), + 'click_y': session.get('click_y'), + 'list_ocr_title': session.get('list_ocr_title', ''), + }) + payload = { + 'round': int(round_count), + 'contact_rect': contact_rect, + 'total_sessions': len(sessions), + 'unread_count': len(unread_sessions), + 'unread_rows': [s.get('row_idx') for s in unread_sessions], + 'rows': rows, + } + with open(file_path, 'w', encoding='utf-8') as f: + json.dump(payload, f, ensure_ascii=False, indent=2) + except Exception as e: + pass + +# 保存调试图片的内部方法 + def _save_debug_image(self, image_obj, filename): + if not self.save_debug_image: + return + self.save_debug_image(image_obj, filename) diff --git a/app/infrastructure/service/wechat/unread_session_analyzer.py b/app/infrastructure/service/wechat/unread_session_analyzer.py new file mode 100644 index 0000000..2b5c3d7 --- /dev/null +++ b/app/infrastructure/service/wechat/unread_session_analyzer.py @@ -0,0 +1,258 @@ +from __future__ import annotations + +import cv2 +import numpy as np + +from app.infrastructure.service.logging.log_service import log_event, new_trace_id +from app.infrastructure.service.wechat.config import CONTACT_ROW_HEIGHT + + + +class UnreadSessionAnalyzer: + def __init__(self): + pass + + def detect_red_dots(self, contact_rect: dict, screenshot) -> list[dict]: + trace_id = new_trace_id("bot") + try: + img_np = np.array(screenshot) + hsv = cv2.cvtColor(cv2.cvtColor(img_np, cv2.COLOR_RGB2BGR), cv2.COLOR_BGR2HSV) + mask = cv2.inRange(hsv, np.array([0, 80, 80]), np.array([12, 255, 255])) + cv2.inRange(hsv, np.array([168, 80, 80]), np.array([180, 255, 255])) + contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) + + contact_width = contact_rect['right'] - contact_rect['left'] + red_dots_raw = [] + for contour in contours: + area = cv2.contourArea(contour) + if 12 < area < 220: + perimeter = cv2.arcLength(contour, True) + if perimeter <= 0: + continue + circularity = 4 * np.pi * area / (perimeter * perimeter) + if circularity <= 0.45: + continue + moments = cv2.moments(contour) + if moments['m00'] == 0: + continue + cx = int(moments['m10'] / moments['m00']) + cy = int(moments['m01'] / moments['m00']) + if cx > contact_width * 0.1: + red_dots_raw.append({'x': contact_rect['left'] + cx, 'y': contact_rect['top'] + cy, 'rel_y': cy}) + + snapped_map = {} + for dot in red_dots_raw: + row_idx = int(round((dot['y'] - contact_rect['top']) / max(1, CONTACT_ROW_HEIGHT))) + snapped_y = int(contact_rect['top'] + row_idx * CONTACT_ROW_HEIGHT + CONTACT_ROW_HEIGHT // 2) + if row_idx not in snapped_map: + snapped_map[row_idx] = {'x': dot['x'], 'y': snapped_y, 'row_idx': row_idx} + + red_dots_final = sorted(snapped_map.values(), key=lambda d: d['y']) + log_event("INFO", "bot", "bot.unread.detect", trace_id, "detect", "ok", "红点检测完成", extra={"dot_count": len(red_dots_final)}) + return red_dots_final + except Exception as e: + log_event("ERROR", "bot", "bot.unread.detect", trace_id, "detect", "failed", "红点检测异常", reason="detect_error", extra={"error": str(e)}) + return [] + + def row_has_red_dot(self, row_img, relaxed: bool = False) -> bool: + try: + row_np = np.array(row_img) + h, w = row_np.shape[:2] + if h < 30 or w < 100: + return False + + margin_left = max(6, int(w * 0.012)) + avatar_size = int(h * 0.72) + avatar_y = (h - avatar_size) // 2 + avatar_x = margin_left + + avatar_cx = avatar_x + avatar_size / 2.0 + avatar_cy = avatar_y + avatar_size / 2.0 + avatar_r = avatar_size * 0.50 + + probe_x1 = avatar_x + int(avatar_size * 0.42) + probe_y1 = max(0, avatar_y - int(avatar_size * 0.10)) + probe_x2 = min(w, avatar_x + int(avatar_size * 1.00)) + probe_y2 = min(h, avatar_y + int(avatar_size * 0.36)) + + if probe_x2 <= probe_x1 or probe_y2 <= probe_y1: + return False + + probe = row_np[probe_y1:probe_y2, probe_x1:probe_x2] + if probe.size == 0: + return False + + probe_hsv = cv2.cvtColor(probe, cv2.COLOR_RGB2HSV) + mask1 = cv2.inRange(probe_hsv, np.array([0, 115, 125]), np.array([12, 255, 255])) + mask2 = cv2.inRange(probe_hsv, np.array([168, 115, 125]), np.array([180, 255, 255])) + mask = cv2.bitwise_or(mask1, mask2) + + kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3)) + mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel) + mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel) + + contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) + if not contours: + self.debug_log(f"row_red w={w} h={h} candidates=0") + return False + + candidates = [] + pw = probe_x2 - probe_x1 + ph = probe_y2 - probe_y1 + + for cnt in contours: + area = cv2.contourArea(cnt) + if not (8 <= area <= 260): + continue + + x, y, cw, ch = cv2.boundingRect(cnt) + peri = cv2.arcLength(cnt, True) + if peri <= 0: + continue + + circ = 4 * np.pi * area / (peri * peri) + ar = max(cw, ch) / max(1, min(cw, ch)) + + cx = x + cw / 2.0 + cy = y + ch / 2.0 + gx = probe_x1 + cx + gy = probe_y1 + cy + + in_upper_right = cx > pw * 0.30 and cx < pw * 0.90 and cy < ph * 0.68 + near_avatar_corner = ( + gx >= avatar_x + avatar_size * 0.66 and + gx <= avatar_x + avatar_size * 1.00 and + gy >= avatar_y - avatar_size * 0.06 and + gy <= avatar_y + avatar_size * 0.24 + ) + if not (in_upper_right and near_avatar_corner): + continue + + comp_mask = np.zeros(mask.shape, dtype=np.uint8) + cv2.drawContours(comp_mask, [cnt], -1, 255, thickness=-1) + ys, xs = np.where(comp_mask > 0) + if len(xs) == 0: + continue + + global_xs = xs + probe_x1 + global_ys = ys + probe_y1 + d2 = (global_xs - avatar_cx) ** 2 + (global_ys - avatar_cy) ** 2 + outside_ratio = float(np.count_nonzero(d2 > (avatar_r * 0.92) ** 2)) / len(d2) + + min_area = 10 if relaxed else 14 + min_small_outside = 0.18 if relaxed else 0.25 + min_small_circ = 0.72 if relaxed else 0.82 + min_match_score = 7 if relaxed else 8 + min_match_outside = 0.10 if relaxed else 0.15 + + if area < min_area: + continue + if area < 20 and outside_ratio < min_small_outside: + continue + if gy > avatar_y + avatar_size * 0.24: + continue + if area < 20 and circ < min_small_circ: + continue + if area < 20 and ar > 1.20: + continue + + if area >= 120: + shape_ok = circ > 0.26 and ar < 2.6 + elif area >= 28: + shape_ok = circ > 0.45 and ar < 1.9 + else: + shape_ok = circ > 0.82 and ar <= 1.20 and outside_ratio >= 0.25 + if not shape_ok: + continue + + white_ratio = 0.0 + if cw >= 7 and ch >= 7: + inner = probe[max(0, y):min(probe.shape[0], y + ch), max(0, x):min(probe.shape[1], x + cw)] + if inner.size > 0: + gray = cv2.cvtColor(inner, cv2.COLOR_RGB2GRAY) + white_ratio = np.count_nonzero(gray > 190) / gray.size + + score = 3 + if area >= 14: + score += 2 + if circ > 0.85: + score += 2 + elif circ > 0.70: + score += 1 + if ar <= 1.15: + score += 2 + elif ar <= 1.35: + score += 1 + if outside_ratio >= 0.35: + score += 4 + elif outside_ratio >= 0.25: + score += 3 + elif outside_ratio >= 0.15: + score += 1 + if 0.05 <= white_ratio <= 0.60: + score += 1 + + candidates.append({ + 'score': score, + 'area': area, + 'circ': circ, + 'ar': ar, + 'outside_ratio': outside_ratio, + 'white_ratio': white_ratio, + 'center': (gx, gy), + 'bbox': (probe_x1 + x, probe_y1 + y, cw, ch), + 'min_match_score': min_match_score, + 'min_match_outside': min_match_outside, + }) + + if not candidates: + return False + + best = max(candidates, key=lambda x: x['score']) + matched = best['score'] >= best['min_match_score'] and best['outside_ratio'] >= best['min_match_outside'] + return matched + except Exception as e: + return False + + def row_has_red_dot_weak(self, row_img) -> bool: + return self.row_has_red_dot(row_img, relaxed=True) + + def get_all_sessions_with_unread(self, contact_rect: dict, screenshot, round_count: int, save_debug_image: Callable | None = None) -> tuple[list[dict], list[dict]]: + trace_id = new_trace_id("bot") + red_dots = self.detect_red_dots(contact_rect, screenshot) + red_y_list = [dot['y'] for dot in red_dots] + row_count = max(1, int((contact_rect['bottom'] - contact_rect['top']) / max(1, CONTACT_ROW_HEIGHT))) + sessions = [] + + for row_idx in range(row_count): + top = int(row_idx * CONTACT_ROW_HEIGHT) + bottom = int(min((row_idx + 1) * CONTACT_ROW_HEIGHT, screenshot.height)) + if bottom <= top: + continue + row_img = screenshot.crop((0, top, screenshot.width, bottom)) + center_y = int(contact_rect['top'] + row_idx * CONTACT_ROW_HEIGHT + CONTACT_ROW_HEIGHT // 2) + has_red_by_global = any(abs(center_y - y) <= max(7, CONTACT_ROW_HEIGHT // 4) for y in red_y_list) + has_red_by_row = self.row_has_red_dot(row_img) + has_red_by_row_weak = self.row_has_red_dot_weak(row_img) if has_red_by_global and not has_red_by_row else has_red_by_row + has_red = has_red_by_row or (has_red_by_global and has_red_by_row_weak) + row_name = f"round_{round_count:04d}_row_{row_idx:03d}.png" + if save_debug_image: + save_debug_image(row_img, f"sessions/all/{row_name}") + if has_red: + save_debug_image(row_img, f"sessions/unread/{row_name}") + sessions.append({ + 'row_idx': row_idx, + 'has_red_dot': has_red, + 'has_red_by_global': has_red_by_global, + 'has_red_by_row': has_red_by_row, + 'has_red_by_row_weak': has_red_by_row_weak, + 'click_x': int((contact_rect['left'] + contact_rect['right']) // 2), + 'click_y': center_y, + 'row_img': row_img.copy(), + }) + + unread_sessions = [s for s in sessions if s['has_red_dot']] + global_hits = sum(1 for s in sessions if s['has_red_by_global']) + row_hits = sum(1 for s in sessions if s['has_red_by_row']) + row_weak_hits = sum(1 for s in sessions if s['has_red_by_row_weak']) + log_event("INFO", "bot", "bot.unread.scan", trace_id, "scan", "ok", "未读会话扫描完成", extra={"round": int(round_count), "rows": len(sessions), "unread": len(unread_sessions), "global_hits": global_hits, "row_hits": row_hits, "row_weak_hits": row_weak_hits}) + return sessions, unread_sessions diff --git a/app/infrastructure/wechat_multi_chat_bot copy.py.bak b/app/infrastructure/wechat_multi_chat_bot copy.py.bak new file mode 100644 index 0000000..17f90ea --- /dev/null +++ b/app/infrastructure/wechat_multi_chat_bot copy.py.bak @@ -0,0 +1,504 @@ +#!/usr/bin/env python +# -*- coding: utf-8 -*- + + +import ctypes # Windows窗口句柄相关API +import hashlib # 文本去重哈希 +import logging # 日志模块 +import os # 文件目录操作 +import re # 正则过滤文本 +import time # 休眠/节流 +from datetime import datetime # 时间戳命名与日志辅助 +from io import BytesIO # 图片转字节流给OCR + +import cv2 # 图像处理 +import numpy as np # 数组/图像矩阵 +import pyautogui # 鼠标键盘自动化 +import pyperclip # 剪贴板粘贴发送文本 +import requests # 调用后端接口 +import uiautomation as auto # Windows UI 自动化 +from PIL import ImageGrab, Image # 截图与图像对象 + +from app.infrastructure.service.wechat.config import BAIDU_API_KEY, BAIDU_SECRET_KEY, BACKEND_URL, LOOP_INTERVAL, NO_REPLY_KEYWORDS, BLOCKED_SESSION_KEYWORDS, UI_NOISE_KEYWORDS, BOT_DEBUG_LOG, WECHAT_WINDOW_TARGET_WIDTH, WECHAT_WINDOW_TARGET_HEIGHT, WECHAT_WINDOW_TARGET_LEFT, WECHAT_WINDOW_TARGET_TOP, OCR_SAVE_IMAGES, OCR_SAVE_DIR # 机器人配置 +from app.infrastructure.service.wechat.ocr import BaiduOCR # 百度OCR封装 + +logging.basicConfig( # 配置全局日志 + level=logging.INFO, # 默认输出INFO及以上 + format="%(asctime)s - %(levelname)s - %(message)s", # 日志格式 + handlers=[ + logging.FileHandler("wechat_multi_chat_bot.log", encoding="utf-8"), # 写文件 + logging.StreamHandler() # 打终端 + ], +) +logger = logging.getLogger(__name__) # 当前模块日志器 + + +def debug_log(message): + if BOT_DEBUG_LOG: # 仅在调试开关开启时输出 + logger.info(f"[DEBUG] {message}") + + +class WechatMultiChatBot: + """微信自动回复机器人（UI自动化 + OCR + 规则/AI回复）。""" + + def __init__(self): + """初始化OCR、微信窗口句柄和运行期状态。""" + logger.info("[BOT] 初始化开始") # 生命周期日志 + self.ocr = BaiduOCR(BAIDU_API_KEY, BAIDU_SECRET_KEY) # OCR客户端 + self.wechat_window = None # 微信窗口对象 + self.find_wechat_window() # 启动即查找窗口 + self.seen_messages = {} # 去重缓存：contact_key -> hash set + self.processed_contacts = set() # 预留：已处理联系人集合 + self.running = False # 主循环运行状态 + logger.info("[BOT] 初始化完成") + + def find_wechat_window(self): + """查找微信主窗口；成功后执行窗口标准化。""" + logger.info("[WIN] 正在查找微信窗口") + self.wechat_window = auto.WindowControl(searchDepth=1, Name='微信') # 按窗口名查找 + if self.wechat_window.Exists(0, 0): # 立即探测是否存在 + logger.info("[WIN] 找到微信窗口") + self.normalize_wechat_window() # 找到后标准化尺寸 + return + logger.error("[WIN] 未找到微信窗口") + raise Exception("未找到微信窗口") + + def normalize_wechat_window(self): + """将微信窗口调整到预设位置和尺寸，保证识别区域稳定。""" + logger.info("[WIN] 开始标准化窗口大小和位置") + try: + self.wechat_window.SetActive() # 激活窗口 + time.sleep(0.25) # 等待激活稳定 + + hwnd = getattr(self.wechat_window, "NativeWindowHandle", 0) # 尝试取窗口句柄 + if hwnd: + user32 = ctypes.windll.user32 # Win32接口 + SWP_NOZORDER = 0x0004 # 不改变Z序 + SWP_NOACTIVATE = 0x0010 # 不抢前台焦点 + user32.SetWindowPos( + int(hwnd), # 目标窗口句柄 + 0, # hWndInsertAfter + int(WECHAT_WINDOW_TARGET_LEFT), # 目标左上x + int(WECHAT_WINDOW_TARGET_TOP), # 目标左上y + int(WECHAT_WINDOW_TARGET_WIDTH), # 目标宽度 + int(WECHAT_WINDOW_TARGET_HEIGHT), # 目标高度 + SWP_NOZORDER | SWP_NOACTIVATE, # 标志位 + ) + logger.info(f"[WIN] 句柄模式窗口标准化成功 hwnd={hwnd}") + else: + if hasattr(self.wechat_window, "MoveTo") and hasattr(self.wechat_window, "Resize"): # 兼容旧接口 + self.wechat_window.MoveTo(WECHAT_WINDOW_TARGET_LEFT, WECHAT_WINDOW_TARGET_TOP) # 移动窗口 + self.wechat_window.Resize(WECHAT_WINDOW_TARGET_WIDTH, WECHAT_WINDOW_TARGET_HEIGHT) # 调整尺寸 + logger.info("[WIN] MoveTo/Resize 模式窗口标准化成功") + else: + raise Exception("未获取到窗口句柄且不支持 MoveTo/Resize") + + time.sleep(0.35) # 等待窗口重排完成 + logger.info(f"[WIN] 标准化参数 left={WECHAT_WINDOW_TARGET_LEFT} top={WECHAT_WINDOW_TARGET_TOP} width={WECHAT_WINDOW_TARGET_WIDTH} height={WECHAT_WINDOW_TARGET_HEIGHT}") + debug_log(f"window_normalized=({WECHAT_WINDOW_TARGET_LEFT},{WECHAT_WINDOW_TARGET_TOP},{WECHAT_WINDOW_TARGET_WIDTH},{WECHAT_WINDOW_TARGET_HEIGHT})") + except Exception as e: + logger.warning(f"[WIN] 窗口标准化失败，继续按当前窗口运行: {e}") + + def get_window_rect(self): + try: + rect = self.wechat_window.BoundingRectangle # UIA矩形 + result = {'left': rect.left, 'top': rect.top, 'right': rect.right, 'bottom': rect.bottom, 'width': rect.right - rect.left, 'height': rect.bottom - rect.top} # 转字典 + debug_log(f"window_rect={result}") + return result + except Exception as e: + logger.warning(f"[WIN] 获取窗口位置失败: {e}") + return None + + def get_contact_list_rect(self, window_rect): + rect = {'left': window_rect['left'] + 10, 'top': window_rect['top'] + 50, 'right': window_rect['left'] + int(window_rect['width'] * 0.25) - 10, 'bottom': window_rect['bottom'] - 50} # 左侧会话列表区域 + debug_log(f"contact_rect={rect}") + return rect + + def detect_red_dots(self, window_rect): + logger.info("[DETECT] 开始检测红点") + contact_rect = self.get_contact_list_rect(window_rect) # 获取列表区域 + try: + screenshot = ImageGrab.grab(bbox=(contact_rect['left'], contact_rect['top'], contact_rect['right'], contact_rect['bottom'])) # 列表截图 + img_np = np.array(screenshot) # PIL -> numpy + img_bgr = cv2.cvtColor(img_np, cv2.COLOR_RGB2BGR) # RGB -> BGR + hsv = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2HSV) # BGR -> HSV + mask = cv2.inRange(hsv, np.array([0, 80, 80]), np.array([12, 255, 255])) + cv2.inRange(hsv, np.array([168, 80, 80]), np.array([180, 255, 255])) # 红色双区间 + contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) # 查找连通域 + contact_width = contact_rect['right'] - contact_rect['left'] # 列表宽度 + red_dots_raw = [] # 原始红点 + for contour in contours: + area = cv2.contourArea(contour) # 面积过滤 + if 12 < area < 220: + perimeter = cv2.arcLength(contour, True) # 周长 + if perimeter > 0: + circularity = 4 * np.pi * area / (perimeter * perimeter) # 圆度 + if circularity > 0.45: + M = cv2.moments(contour) # 矩中心 + if M["m00"] != 0: + cx = int(M["m10"] / M["m00"]) # 中心x + cy = int(M["m01"] / M["m00"]) # 中心y + if cx > contact_width * 0.1: # 过滤左边缘噪声 + red_dots_raw.append({'x': contact_rect['left'] + cx, 'y': contact_rect['top'] + cy, 'rel_y': cy}) # 记录绝对坐标 + red_dots_grouped = [] # 按行合并后的红点 + debug_log(f"red_dots_raw={len(red_dots_raw)}") + used = set() # 已分组索引 + for i, dot in enumerate(red_dots_raw): + if i in used: + continue + group = [dot] # 当前分组 + for j, other in enumerate(red_dots_raw): + if j != i and j not in used and abs(dot['rel_y'] - other['rel_y']) < 50: # 同一行 + group.append(other) + used.add(j) + red_dots_grouped.append({'x': sum(d['x'] for d in group) // len(group), 'y': sum(d['y'] for d in group) // len(group)}) # 行中心 + used.add(i) + logger.info(f"[DETECT] 红点检测完成 grouped={len(red_dots_grouped)}") + debug_log(f"red_dots_grouped={len(red_dots_grouped)}") + return red_dots_grouped + except Exception as e: + logger.error(f"[DETECT] 检测红点失败: {e}") + return [] + + def click_contact_by_red_dot(self, red_dot, window_rect): + contact_rect = self.get_contact_list_rect(window_rect) # 计算左侧联系人列表区域 + click_x = (contact_rect['left'] + contact_rect['right']) // 2 # 点击联系人列表中线，避免点到红点本身 + click_y = red_dot['y'] # 使用红点纵坐标对应会话行 + logger.info(f"[ACTION] 点击联系人 x={click_x} y={click_y}") # 记录点击行为 + pyautogui.click(click_x, click_y) # 执行点击 + time.sleep(1.2) # 等待会话内容加载 + session_title = self.get_current_session_title() # 读取当前会话标题 + logger.info(f"[ACTION] 当前会话标题 title={session_title or '未知'}") # 输出标题用于排查 + time.sleep(1.0) # 再等待短时间，保证后续OCR稳定 + + def get_session_title_by_ocr(self): + try: + window_rect = self.get_window_rect() # 获取微信窗口坐标 + if not window_rect: + return "" # 窗口坐标不可用 + + title_areas = [ # 多个标题区域兜底，适配不同微信版本/缩放 + ( + window_rect['left'] + int(window_rect['width'] * 0.32), + window_rect['top'] + 6, + window_rect['right'] - int(window_rect['width'] * 0.30), + window_rect['top'] + max(40, int(window_rect['height'] * 0.085)), + ), + ( + window_rect['left'] + int(window_rect['width'] * 0.28), + window_rect['top'] + 4, + window_rect['right'] - int(window_rect['width'] * 0.24), + window_rect['top'] + max(46, int(window_rect['height'] * 0.095)), + ), + ] + + for idx, (left, top, right, bottom) in enumerate(title_areas, 1): # 逐区域尝试 + screenshot = ImageGrab.grab(bbox=(left, top, right, bottom)) # 截标题图 + self.save_ocr_debug_image(screenshot, f"title_ocr_{idx}_{datetime.now().strftime('%Y%m%d_%H%M%S_%f')}.png") # 落盘调试 + img_bytes = BytesIO() # 内存字节流 + screenshot.save(img_bytes, format='PNG') # 转png字节 + lines = self.ocr.recognize(img_bytes.getvalue()) # OCR识别 + valid = [x.strip() for x in lines if x and x.strip() and len(x.strip()) >= 2] # 清洗文本 + valid = [x for x in valid if x not in UI_NOISE_KEYWORDS] # 去噪 + if valid: + title = valid[0] # 取首个有效标题 + debug_log(f"session_title_ocr={title} area={idx} lines={valid[:5]}") + return title + + return "" # 全部区域失败 + except Exception as e: + debug_log(f"session_title_ocr_error={e}") + return "" # OCR异常返回空 + + def get_current_session_title(self): + try: + title_ctrl = self.wechat_window.TextControl(foundIndex=1) # 优先UIA读标题 + if hasattr(title_ctrl, "Exists") and not title_ctrl.Exists(0.3, 0.05): # 快速存在性检查 + debug_log("session_title_not_found_fast") + title = self.get_session_title_by_ocr() # UIA失败转OCR + return title + title = (getattr(title_ctrl, "Name", "") or "").strip() # 读取控件Name + if not title or title in UI_NOISE_KEYWORDS: # 噪声/空值 + title = self.get_session_title_by_ocr() # OCR兜底 + debug_log(f"session_title={title}") + return title + except Exception as e: + debug_log(f"session_title_error={e}") + return self.get_session_title_by_ocr() # 异常也兜底 + + def is_blocked_session(self): + title = self.get_current_session_title() # 取会话标题 + if not title: + return False # 标题未知默认不拦截 + for keyword in BLOCKED_SESSION_KEYWORDS: # 命中过滤词则跳过 + if keyword in title: + logger.info(f"[SESSION] 命中过滤会话 title={title} keyword={keyword}") + return True + return False + + def get_latest_message_areas(self, window_rect): + """计算多段消息识别区域（靠近底部，适配不同窗口尺寸）。""" + chat_left = window_rect['left'] + int(window_rect['width'] * 0.30) # 聊天区左边界 + chat_right = window_rect['right'] - 20 # 聊天区右边界 + chat_top = window_rect['top'] + int(window_rect['height'] * 0.16) # 聊天区上边界 + chat_bottom = window_rect['bottom'] - int(window_rect['height'] * 0.20) # 聊天区下边界（排除输入区） + chat_height = max(420, int((chat_bottom - chat_top) * 0.90)) # 有效聊天高度 + + area1_h = max(220, int(chat_height * 0.46)) # 近底部区域 + area2_h = max(320, int(chat_height * 0.72)) # 中大区域 + area3_h = max(420, int(chat_height * 0.98)) # 大区域兜底 + + areas = [ + {'left': chat_left, 'top': max(chat_top, chat_bottom - area1_h), 'right': chat_right, 'bottom': chat_bottom}, # 区域1 + {'left': chat_left, 'top': max(chat_top, chat_bottom - area2_h), 'right': chat_right, 'bottom': chat_bottom - max(35, int(area1_h * 0.12))}, # 区域2 + {'left': chat_left, 'top': max(chat_top, chat_bottom - area3_h), 'right': chat_right, 'bottom': chat_bottom - max(80, int(area2_h * 0.20))}, # 区域3 + ] + debug_log(f"message_areas={areas}") + return areas + + def should_reply(self, text): + """基础过滤：过短、无意义、无需回复文本直接跳过。""" + if not text or len(text) < 2: # 文本太短不回复 + return False + text_lower = text.lower() # 统一小写比较 + for keyword in NO_REPLY_KEYWORDS: # 命中免回复词 + if keyword.lower() in text_lower: + return False + return not text.isdigit() # 纯数字通常无语义 + + def is_new_message(self, text, contact_key): + """消息去重：同一会话内已处理过的文本不重复回复。""" + if contact_key not in self.seen_messages: + self.seen_messages[contact_key] = set() # 首次初始化会话集合 + h = hashlib.md5(text.encode("utf-8")).hexdigest() # 文本哈希 + if h in self.seen_messages[contact_key]: + logger.info(f"[FILTER] 重复消息 contact_key={contact_key}") + return False + self.seen_messages[contact_key].add(h) # 记录已处理 + if len(self.seen_messages[contact_key]) > 50: # 限制缓存规模 + self.seen_messages[contact_key] = set(list(self.seen_messages[contact_key])[-50:]) + return True + + def extract_text_by_uia(self): + logger.info("[UIA] 尝试控件树文本提取") + lines = [] # 候选文本 + try: + all_text_controls = self.wechat_window.GetChildren() # 取一级子控件 + for ctrl in all_text_controls: + name = (getattr(ctrl, 'Name', '') or '').strip() # 控件文本 + if not name: + continue + if len(name) < 2: + continue + if re.fullmatch(r"[0-9:\-\s]+", name): # 过滤时间/数字 + continue + if name in UI_NOISE_KEYWORDS: # 过滤UI噪声 + continue + lines.append(name) # 保留候选 + except Exception as e: + logger.warning(f"[UIA] 控件树提取失败: {e}") + + dedup = [] # 去重结果 + seen = set() # 去重集合 + for x in lines: + if x not in seen: + dedup.append(x) + seen.add(x) + + logger.info(f"[UIA] 控件树提取文本数={len(dedup)}") + debug_log(f"uia_lines={dedup[-8:] if dedup else []}") + return dedup + + def save_ocr_debug_image(self, image_obj, filename): + """保存OCR调试截图，便于核对截取区域和图像质量。""" + if not OCR_SAVE_IMAGES: # 开关关闭则不落盘 + return + try: + os.makedirs(OCR_SAVE_DIR, exist_ok=True) # 创建目录 + file_path = os.path.join(OCR_SAVE_DIR, filename) # 文件路径 + image_obj.save(file_path) # 保存图片 + debug_log(f"saved_ocr_image={file_path}") + except Exception as e: + logger.warning(f"[OCR] 保存调试截图失败: {e}") + + def get_ai_reply(self, message): + """调用后端接口获取最终回复（规则优先，AI兜底）。""" + logger.info(f"[API] 请求后端生成回复 content={message}") + try: + resp = requests.post(BACKEND_URL, json={"content": message, "wx_user_id": "multi_chat_bot", "wx_nickname": "用户"}, timeout=10) # 请求后端 + logger.info(f"[API] 后端响应 status={resp.status_code}") + if resp.status_code == 200: + data = resp.json() # 解析json + if data.get("success") and data.get("should_reply"): + reply = (data.get("reply_text") or "").strip() # 取回复文本 + logger.info(f"[API] 生成回复成功 reply={reply}") + return reply + logger.info("[API] 后端未返回可发送回复") + except Exception as e: + logger.error(f"[API] 调用接口失败: {e}") + return None + + def send_message(self, text, window_rect): + logger.info(f"[SEND] 开始发送 reply={text}") + try: + self.wechat_window.SetActive() # 激活微信窗口 + time.sleep(0.3) + pyautogui.click(window_rect['left'] + window_rect['width'] // 2, window_rect['bottom'] - 100) # 点击输入框 + time.sleep(0.3) + pyautogui.hotkey('ctrl', 'a') # 全选旧文本 + pyautogui.press('delete') # 清空输入框 + pyperclip.copy(text) # 文本放入剪贴板 + pyautogui.hotkey('ctrl', 'v') # 粘贴内容 + pyautogui.press('enter') # 回车发送 + logger.info("[SEND] 发送成功") + except Exception as e: + logger.error(f"[SEND] 发送失败: {e}") + + def process_current_chat(self, window_rect, contact_key): + logger.info(f"[CHAT] 开始处理会话 contact_key={contact_key}") + if self.is_blocked_session(): # 系统会话直接跳过 + logger.info("[CHAT] 当前会话在过滤名单，跳过") + return False + try: + all_lines = [] # OCR/UIA汇总文本 + timestamp = datetime.now().strftime("%Y%m%d_%H%M%S_%f") # 调试图时间戳 + for idx, msg_rect in enumerate(self.get_latest_message_areas(window_rect), 1): # 分区识别 + screenshot = ImageGrab.grab(bbox=(msg_rect['left'], msg_rect['top'], msg_rect['right'], msg_rect['bottom'])) # 区域截图 + img_np = np.array(screenshot) # 转numpy + + raw_pil = Image.fromarray(img_np) # 原图 + self.save_ocr_debug_image(raw_pil, f"{timestamp}_{contact_key}_area{idx}_raw.png") # 保存原图 + raw_bytes = BytesIO() # 原图字节流 + raw_pil.save(raw_bytes, format='PNG') + lines_raw = self.ocr.recognize(raw_bytes.getvalue()) # 原图OCR + + gray = cv2.cvtColor(img_np, cv2.COLOR_RGB2GRAY) # 灰度化 + enhanced = cv2.convertScaleAbs(gray, alpha=1.35, beta=8) # 提升对比度 + _, binary = cv2.threshold(enhanced, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU) # 二值化 + pil_bin = Image.fromarray(binary) # 二值图 + self.save_ocr_debug_image(pil_bin, f"{timestamp}_{contact_key}_area{idx}_bin.png") # 保存二值图 + bin_bytes = BytesIO() # 二值图字节流 + pil_bin.save(bin_bytes, format='PNG') + lines_bin = self.ocr.recognize(bin_bytes.getvalue()) # 二值图OCR + + lines = lines_raw + lines_bin # 合并两路识别 + logger.info(f"[OCR] area={idx} raw={len(lines_raw)} bin={len(lines_bin)} total={len(lines)}") + debug_log(f"ocr_lines_count={len(lines)} contact_key={contact_key} area={idx}") + all_lines.extend(lines) # 汇总 + + if not all_lines: # 分区都失败时走整块兜底 + logger.info("[CHAT] 分区OCR无结果，尝试整块聊天区兜底") + chat_left = window_rect['left'] + int(window_rect['width'] * 0.30) + chat_right = window_rect['right'] - 20 + chat_top = window_rect['top'] + int(window_rect['height'] * 0.16) + chat_bottom = window_rect['bottom'] - int(window_rect['height'] * 0.20) + full_shot = ImageGrab.grab(bbox=(chat_left, chat_top, chat_right, chat_bottom)) # 整块截图 + full_np = np.array(full_shot) + full_gray = cv2.cvtColor(full_np, cv2.COLOR_RGB2GRAY) + full_enh = cv2.convertScaleAbs(full_gray, alpha=1.25, beta=6) + _, full_bin = cv2.threshold(full_enh, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU) + full_pil = Image.fromarray(full_bin) + self.save_ocr_debug_image(full_pil, f"{timestamp}_{contact_key}_fallback_full_bin.png") # 保存兜底图 + full_bytes = BytesIO() + full_pil.save(full_bytes, format='PNG') + full_lines = self.ocr.recognize(full_bytes.getvalue()) # 兜底OCR + logger.info(f"[OCR] fallback_full_chat lines={len(full_lines)}") + all_lines.extend(full_lines) + + if not all_lines: # OCR全失败时走UIA + logger.info("[CHAT] OCR 无结果，尝试 UIA 文本兜底") + all_lines = self.extract_text_by_uia() + + if not all_lines: # UIA也失败 + logger.info("[CHAT] OCR+UIA 均无结果，结束") + return False + + valid_lines = [line.strip() for line in all_lines if len(line.strip()) >= 2] # 过滤无效行 + if not valid_lines: + logger.info("[CHAT] 过滤后无有效文本，结束") + return False + + latest = None # 最终待处理消息 + prioritized = [line for line in reversed(valid_lines) if ("报名" in line or "课程" in line or "价格" in line)] # 规则关键词优先 + if prioritized: + latest = prioritized[0] + logger.info(f"[CHAT] 规则关键词优先命中 latest={latest}") + else: + for line in reversed(valid_lines): # 从最新往前找可回复文本 + if self.should_reply(line): + latest = line + break + + if not latest: + logger.info("[CHAT] 没有命中可回复文本，结束") + debug_log("skip_all_should_reply=false") + return False + + logger.info(f"[CHAT] 识别目标消息 latest={latest}") + debug_log(f"latest_text={latest}") + if not self.is_new_message(latest, contact_key): # 重复消息不再回 + debug_log("skip_duplicate_message") + return False + + reply = self.get_ai_reply(latest) # 请求后端生成回复 + if reply: + debug_log(f"ai_reply={reply}") + self.send_message(reply, window_rect) # 发送回复 + logger.info("[CHAT] 本次会话处理完成（已发送）") + return True + + debug_log("no_ai_reply") + logger.info("[CHAT] 本次会话处理完成（无可发送回复）") + return False + except Exception as e: + logger.error(f"[CHAT] 处理聊天失败: {e}") + return False + + def run_forever(self): + """主循环：红点检测 -> 点击会话 -> 处理消息 -> 间隔轮询。""" + logger.info("[LOOP] 监听循环启动") + self.running = True # 标记运行中 + round_count = 0 # 轮次计数 + while self.running: + try: + round_count += 1 # 新一轮 + logger.info(f"[LOOP] 开始第 {round_count} 轮") + debug_log(f"round={round_count}") + window_rect = self.get_window_rect() # 获取窗口坐标 + if not window_rect: + logger.info("[LOOP] 未取到窗口位置，等待下一轮") + time.sleep(LOOP_INTERVAL) + continue + red_dots = self.detect_red_dots(window_rect) # 红点检测 + logger.info(f"[LOOP] 本轮红点数={len(red_dots)}") + debug_log(f"red_dots_detected={len(red_dots)}") + if not red_dots: + logger.info("[LOOP] 未检测到红点，走当前会话兜底") + debug_log("fallback_current_chat") + self.process_current_chat(window_rect, "current_chat_fallback") # 无红点也扫当前会话 + time.sleep(LOOP_INTERVAL) + continue + for idx, red_dot in enumerate(red_dots, 1): # 逐个红点处理 + logger.info(f"[LOOP] 处理红点 {idx}/{len(red_dots)}") + self.click_contact_by_red_dot(red_dot, window_rect) # 点击会话 + contact_key = f"{red_dot['x']}_{red_dot['y']}" # 联系人key + self.process_current_chat(window_rect, contact_key) # 处理会话 + time.sleep(1) # 短暂节流 + logger.info(f"[LOOP] 第 {round_count} 轮结束，休眠 {LOOP_INTERVAL} 秒") + time.sleep(LOOP_INTERVAL) + except Exception as e: + logger.error(f"[LOOP] 循环出错: {e}") + time.sleep(3) # 异常后稍等再继续 + + def stop(self): + logger.info("[LOOP] 收到停止信号") + self.running = False # 置位退出 + + +if __name__ == "__main__": + try: + bot = WechatMultiChatBot() # 构造机器人 + bot.run_forever() # 进入主循环 + except KeyboardInterrupt: + bot.stop() # Ctrl+C优雅停止 + except Exception as e: + print(f"错误: {e}") # 启动异常输出 diff --git a/app/infrastructure/wechat_multi_chat_bot.py b/app/infrastructure/wechat_multi_chat_bot.py new file mode 100644 index 0000000..d72b2f0 --- /dev/null +++ b/app/infrastructure/wechat_multi_chat_bot.py @@ -0,0 +1,373 @@ +#!/usr/bin/env python +# -*- coding: utf-8 -*- + +import ctypes +import ctypes.wintypes +import json +import os +import shutil +import time +from io import BytesIO + +import pyautogui +import pyperclip +import requests +from app.infrastructure.service.logging.log_service import log_event, new_trace_id +from app.infrastructure.service.wechat.ocr import OCRService +from app.infrastructure.service.wechat.screenshot import ScreenshotService +from app.infrastructure.service.wechat.session_service import WechatSessionService + +from app.infrastructure.service.wechat.config import ( + LOOP_INTERVAL, LOOP_ERROR_DELAY, CLICK_AFTER_DELAY, TITLE_AFTER_DELAY, + CONTACT_SWITCH_DELAY, BOT_LOG_FILE, BOT_SESSION_LIST_LOG_FILE, BOT_SESSION_DETAIL_LOG_FILE, + WECHAT_WINDOW_TARGET_WIDTH, WECHAT_WINDOW_TARGET_HEIGHT, + WECHAT_WINDOW_TARGET_LEFT, WECHAT_WINDOW_TARGET_TOP, + OCR_SAVE_IMAGES, OCR_SAVE_DIR, BLOCKED_ROW_CACHE_FILE, + CONTACT_ROW_HEIGHT, CONTACT_ROW_WIDTH, + CONTACT_LIST_LEFT_OFFSET, CONTACT_LIST_TOP_OFFSET, CONTACT_LIST_BOTTOM_OFFSET, + SESSION_NAME_LEFT_OFFSET, SESSION_NAME_TOP_OFFSET, SESSION_NAME_WIDTH, SESSION_NAME_HEIGHT, + CHAT_CAPTURE_LEFT_OFFSET, CHAT_CAPTURE_TOP_OFFSET, CHAT_CAPTURE_WIDTH, CHAT_CAPTURE_HEIGHT, + TITLE_OCR_AREA_LEFT_OFFSET, TITLE_OCR_AREA_TOP_OFFSET, TITLE_OCR_AREA_WIDTH, TITLE_OCR_AREA_HEIGHT, +) + + +class WechatMultiChatBot: + + def _sleep_interruptible(self, seconds): + end_ts = time.time() + max(0.0, float(seconds or 0)) + while self.running and time.time() < end_ts: + time.sleep(min(0.1, end_ts - time.time())) + + def submit_message(self, session_name, content, confidence="", bubble_side=""): + trace_id = new_trace_id("bot") + backend_url = (os.getenv("BACKEND_URL") or "").strip() + if not backend_url or not content: + log_event("WARNING", "bot", "bot.submit", trace_id, "submit", "failed", "消息上报参数不完整", reason="invalid_input") + return {"success": False, "should_reply": False, "reply_text": ""} + try: + payload = { + "wx_user_id": session_name or "", + "wx_nickname": session_name or "", + "content": content, + "is_friend_request": 0, + "ocr_confidence": confidence, + "ocr_bubble_side": bubble_side, + } + resp = requests.post(backend_url, json=payload, timeout=5) + if resp.status_code != 200: + log_event("WARNING", "bot", "bot.submit", trace_id, "submit", "failed", "消息上报失败", reason="http_error", extra={"status_code": resp.status_code}) + return {"success": False, "should_reply": False, "reply_text": ""} + data = resp.json() if resp.text else {} + if not isinstance(data, dict): + log_event("WARNING", "bot", "bot.submit", trace_id, "submit", "failed", "消息上报返回格式异常", reason="invalid_response") + return {"success": False, "should_reply": False, "reply_text": ""} + result = { + "success": bool(data.get("success")), + "should_reply": bool(data.get("should_reply")), + "reply_text": (data.get("reply_text") or "").strip(), + } + log_event("INFO", "bot", "bot.submit", trace_id, "submit", "ok", "消息上报成功", extra={"should_reply": result["should_reply"]}) + return result + except Exception as e: + log_event("ERROR", "bot", "bot.submit", trace_id, "submit", "failed", "消息上报异常", reason="request_error", extra={"error": str(e)}) + return {"success": False, "should_reply": False, "reply_text": ""} + + def __init__(self): + self.wechat_hwnd = 0 + self.ocr = OCRService() + self.screenshot = ScreenshotService() + self.session_service = WechatSessionService( + screenshot_service=self.screenshot, + ocr_service=self.ocr, + save_debug_image=self.save_debug_image, + ) + self.running = False + self.blocked_row_cache = self.load_blocked_row_cache() + self.init_debug_dirs() + self.find_wechat_window() + + def load_blocked_row_cache(self): + try: + if not os.path.exists(BLOCKED_ROW_CACHE_FILE): + return {} + with open(BLOCKED_ROW_CACHE_FILE, "r", encoding="utf-8") as f: + data = json.load(f) + if isinstance(data, dict): + filtered = {k: v for k, v in data.items() if isinstance(k, str) and k.startswith("title:")} + dropped = len(data) - len(filtered) + return filtered + except Exception as e: + pass + return {} + + def save_blocked_row_cache(self): + try: + os.makedirs(os.path.dirname(BLOCKED_ROW_CACHE_FILE), exist_ok=True) + with open(BLOCKED_ROW_CACHE_FILE, "w", encoding="utf-8") as f: + json.dump(self.blocked_row_cache, f, ensure_ascii=False, indent=2) + except Exception as e: + pass + + def init_debug_dirs(self): + if not OCR_SAVE_IMAGES: + return + try: + if os.path.exists(OCR_SAVE_DIR): + shutil.rmtree(OCR_SAVE_DIR) + os.makedirs(os.path.join(OCR_SAVE_DIR, "sessions", "all"), exist_ok=True) + os.makedirs(os.path.join(OCR_SAVE_DIR, "sessions", "unread"), exist_ok=True) + os.makedirs(os.path.join(OCR_SAVE_DIR, "sessions", "clicked"), exist_ok=True) + os.makedirs(os.path.join(OCR_SAVE_DIR, "sessions", "name_ocr"), exist_ok=True) + except Exception as e: + pass + + def find_wechat_window(self): + user32 = ctypes.windll.user32 + found_hwnd = [] + EnumWindowsProc = ctypes.WINFUNCTYPE(ctypes.c_bool, ctypes.c_void_p, ctypes.c_void_p) + + def _callback(hwnd, lparam): + if not user32.IsWindowVisible(hwnd): + return True + length = user32.GetWindowTextLengthW(hwnd) + if length <= 0: + return True + buf = ctypes.create_unicode_buffer(length + 1) + user32.GetWindowTextW(hwnd, buf, length + 1) + title = (buf.value or "").strip() + if "微信" in title: + found_hwnd.append(int(hwnd)) + return False + return True + + user32.EnumWindows(EnumWindowsProc(_callback), 0) + if found_hwnd: + self.wechat_hwnd = found_hwnd[0] + self.normalize_wechat_window() + return + raise Exception("未找到微信窗口") + + def normalize_wechat_window(self): + try: + user32 = ctypes.windll.user32 + hwnd = int(self.wechat_hwnd or 0) + if not hwnd: + return + user32.ShowWindow(hwnd, 9) + user32.SetForegroundWindow(hwnd) + time.sleep(0.25) + user32.SetWindowPos( + hwnd, + 0, + int(WECHAT_WINDOW_TARGET_LEFT), + int(WECHAT_WINDOW_TARGET_TOP), + int(WECHAT_WINDOW_TARGET_WIDTH), + int(WECHAT_WINDOW_TARGET_HEIGHT), + 0x0004 | 0x0010, + ) + except Exception as e: + pass + + def get_window_rect(self): + try: + user32 = ctypes.windll.user32 + hwnd = int(self.wechat_hwnd or 0) + if not hwnd: + return None + client_rect = ctypes.wintypes.RECT() + ok = user32.GetClientRect(hwnd, ctypes.byref(client_rect)) + if not ok: + return None + top_left = ctypes.wintypes.POINT(0, 0) + bottom_right = ctypes.wintypes.POINT(int(client_rect.right), int(client_rect.bottom)) + if not user32.ClientToScreen(hwnd, ctypes.byref(top_left)): + return None + if not user32.ClientToScreen(hwnd, ctypes.byref(bottom_right)): + return None + return { + 'left': int(top_left.x), + 'top': int(top_left.y), + 'right': int(bottom_right.x), + 'bottom': int(bottom_right.y), + 'width': int(bottom_right.x - top_left.x), + 'height': int(bottom_right.y - top_left.y), + } + except Exception as e: + return None + + def save_debug_image(self, image_obj, filename): + if not OCR_SAVE_IMAGES: + return + try: + file_path = os.path.join(OCR_SAVE_DIR, filename) + os.makedirs(os.path.dirname(file_path), exist_ok=True) + image_obj.save(file_path) + except Exception as e: + pass + + def click_unread_session(self, session): + self.session_service.reset_session_title_cache() + click_x = session.get('click_x', session.get('center_x')) + click_y = session.get('click_y', session.get('center_y')) + if click_x is None or click_y is None: + return + pyautogui.click(int(click_x), int(click_y)) + self._sleep_interruptible(CLICK_AFTER_DELAY) + self._sleep_interruptible(TITLE_AFTER_DELAY) + + def send_reply_to_wechat(self, reply_text, expected_session_name=""): + text = (reply_text or "").strip() + if not text: + return False + window_rect = self.get_window_rect() + if not window_rect: + return False + try: + if expected_session_name: + current_title = self.session_service.get_current_session_title(window_rect) + if not self.session_service.is_same_session(expected_session_name, current_title): + return False + hwnd = int(self.wechat_hwnd or 0) + if hwnd: + ctypes.windll.user32.ShowWindow(hwnd, 9) + ctypes.windll.user32.SetForegroundWindow(hwnd) + self._sleep_interruptible(0.2) + input_x = int(window_rect["left"] + window_rect["width"] * 0.62) + input_y = int(window_rect["bottom"] - 88) + pyautogui.click(input_x, input_y) + self._sleep_interruptible(0.12) + pyautogui.hotkey("ctrl", "a") + self._sleep_interruptible(0.06) + pyautogui.press("delete") + self._sleep_interruptible(0.06) + pyperclip.copy(text) + self._sleep_interruptible(0.06) + pyautogui.hotkey("ctrl", "v") + self._sleep_interruptible(0.08) + pyautogui.press("enter") + return True + except Exception as e: + return False + + def save_current_chat_snapshot(self, window_rect, round_count, row_idx, expected_session_name="", expected_list_title=""): + try: + analyze_result = self.session_service.analyze_clicked_session(window_rect, round_count, row_idx) + if not analyze_result.file_name: + return False + current_session_name = "" + need_verify_current = bool(expected_session_name) + if need_verify_current: + current_session_name = self.session_service.get_current_session_title(window_rect) + if expected_session_name and current_session_name and not self.session_service.is_same_session(expected_session_name, current_session_name): + return False + session_name = (expected_session_name or expected_list_title or current_session_name or '').strip() + if analyze_result.ok: + submit_result = self.submit_message(session_name, analyze_result.latest_text, analyze_result.confidence, analyze_result.bubble_side) + if submit_result.get("should_reply"): + reply_text = (submit_result.get("reply_text") or "").strip() + if reply_text: + sent_ok = self.send_reply_to_wechat(reply_text, expected_session_name=session_name) + if not sent_ok: + log_event("WARNING", "bot", "bot.submit", new_trace_id("bot"), "reply", "failed", "自动回复发送失败", reason="send_reply_failed", extra={"session_name": session_name}) + return True + log_event("WARNING", "bot", "bot.chat_analyze", new_trace_id("bot"), "analyze", "failed", "聊天截图未提取到可入库文本", reason="latest_text_empty", extra={"session_name": session_name, "file_name": analyze_result.file_name, "confidence": analyze_result.confidence, "bubble_side": analyze_result.bubble_side}) + return False + except Exception as e: + log_event("ERROR", "bot", "bot.chat_analyze", new_trace_id("bot"), "snapshot", "failed", "保存聊天快照失败", reason="snapshot_error", extra={"error": str(e)}) + return False + + def run_forever(self): + trace_id = new_trace_id("bot") + self.running = True + log_event("INFO", "bot", "bot.loop", trace_id, "start", "ok", "微信机器人主循环启动") + round_count = 0 + while self.running: + try: + round_count += 1 + window_rect = self.get_window_rect() + if not window_rect: + self._sleep_interruptible(LOOP_INTERVAL) + continue + scan_result = self.session_service.get_all_sessions_with_unread(window_rect, round_count) + sessions, unread_sessions = scan_result.sessions, scan_result.unread_sessions + if unread_sessions: + pass + if not unread_sessions: + self._sleep_interruptible(LOOP_INTERVAL) + continue + session = unread_sessions[0] + if not self.running: + self._sleep_interruptible(LOOP_INTERVAL) + continue + if self.session_service.should_skip_session_by_ocr( + session=session, + blocked_row_cache=self.blocked_row_cache, + save_blocked_row_cache=self.save_blocked_row_cache, + ): + self._sleep_interruptible(LOOP_INTERVAL) + continue + expected_list_title = (session.get('list_ocr_title') or '').strip() + expected_row_idx = session.get('row_idx') + precheck_scan = self.session_service.get_all_sessions_with_unread(window_rect, round_count) + precheck_unread = precheck_scan.unread_sessions + if not precheck_unread: + self._sleep_interruptible(LOOP_INTERVAL) + continue + precheck_first = precheck_unread[0] + self.session_service.should_skip_session_by_ocr( + session=precheck_first, + blocked_row_cache=self.blocked_row_cache, + save_blocked_row_cache=self.save_blocked_row_cache, + ) + current_list_title = (precheck_first.get('list_ocr_title') or '').strip() + current_row_idx = precheck_first.get('row_idx') + same_list_session = False + if expected_list_title and current_list_title: + same_list_session = self.session_service.is_same_session(expected_list_title, current_list_title) + elif expected_row_idx is not None and current_row_idx is not None: + same_list_session = int(expected_row_idx) == int(current_row_idx) + if not same_list_session: + self._sleep_interruptible(LOOP_INTERVAL) + continue + session = precheck_first + self.click_unread_session(session) + if not self.running: + self._sleep_interruptible(LOOP_INTERVAL) + continue + if self.session_service.should_skip_current_session( + window_rect=window_rect, + session=session, + blocked_row_cache=self.blocked_row_cache, + save_blocked_row_cache=self.save_blocked_row_cache, + ): + self._sleep_interruptible(LOOP_INTERVAL) + continue + snapshot_ok = self.save_current_chat_snapshot( + window_rect, + round_count, + session['row_idx'], + expected_session_name=expected_list_title, + expected_list_title=expected_list_title, + ) + if not snapshot_ok: + pass + else: + self._sleep_interruptible(CONTACT_SWITCH_DELAY) + self._sleep_interruptible(LOOP_INTERVAL) + except Exception as e: + log_event("ERROR", "bot", "bot.loop", trace_id, "loop", "failed", "微信机器人主循环异常", reason="loop_error", extra={"error": str(e), "round": round_count}) + self._sleep_interruptible(LOOP_ERROR_DELAY) + + def stop(self): + self.running = False + log_event("INFO", "bot", "bot.loop", new_trace_id("bot"), "stop", "ok", "微信机器人主循环停止") + + +if __name__ == "__main__": + try: + bot = WechatMultiChatBot() + bot.run_forever() + except KeyboardInterrupt: + bot.stop() + except Exception as e: + print(f"错误: {e}") diff --git a/app/presentation/__init__.py b/app/presentation/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/app/presentation/main_window.py b/app/presentation/main_window.py new file mode 100644 index 0000000..26ab147 --- /dev/null +++ b/app/presentation/main_window.py @@ -0,0 +1,238 @@ +import os +import sys +import threading +from urllib import parse, request + +import requests +from PySide6.QtCore import QTimer, Qt, QObject, Slot +from PySide6.QtWidgets import QMainWindow, QWidget, QVBoxLayout, QMessageBox + +from app.application.services import AppConfig, BackendRuntime, FrontendRuntime +from app.presentation.shell import LoadingWindowController, WebViewShellController + +print(f"[GUI] Python executable: {sys.executable}") + +try: + from PySide6.QtWebEngineWidgets import QWebEngineView + from PySide6.QtWebChannel import QWebChannel + WEB_ENGINE_AVAILABLE = True +except Exception: + WEB_ENGINE_AVAILABLE = False + QWebEngineView = None + QWebChannel = None + + +class WindowBridge(QObject): + def __init__(self, main_window): + super().__init__() + self.main_window = main_window + + @Slot() + def open_devtools(self): + self.main_window.open_devtools() + + @Slot() + def minimize(self): + self.main_window.showMinimized() + + @Slot() + def maximize_or_restore(self): + if self.main_window.isMaximized(): + self.main_window.showNormal() + else: + self.main_window.showMaximized() + + @Slot() + def close_window(self): + self.main_window.close() + + @Slot() + def start_move(self): + wh = self.main_window.windowHandle() + if wh is not None: + wh.startSystemMove() + + +class MainWindow(QMainWindow): + def post_settings(self, **kwargs): + if not self.base_url: + return + try: + payload = {"action": "settings_set"} + for k, v in kwargs.items(): + payload[k] = "1" if v is True else "0" if v is False else str(v) + data = parse.urlencode(payload).encode("utf-8") + req = request.Request(self.base_url + "/api/rules", data=data, method="POST") + with request.urlopen(req, timeout=2): + pass + except Exception: + pass + + def __init__(self): + super().__init__() + self.setWindowTitle("识流 AI 助手") + self.resize(1280, 920) + self.setWindowFlags(Qt.FramelessWindowHint | Qt.Window) + self.hide() + + self.config = AppConfig() + self.backend_runtime = BackendRuntime(self.config) + self.frontend_runtime = FrontendRuntime(self.config, self.backend_runtime) + self.base_url = os.getenv("APP_BASE_URL", self.backend_runtime.base_url) + self.backend_process = None + self.backend_started_by_gui = False + self.backend_boot_thread = None + self.web_channel = None + self.window_bridge = None + self.loading = LoadingWindowController() + self.web_shell = None + self.frontend_entry_url = "" + + central = QWidget() + central.setStyleSheet("background:#eef2f7;") + self.setCentralWidget(central) + root = QVBoxLayout(central) + root.setContentsMargins(0, 0, 0, 0) + root.setSpacing(0) + + self.web = None + self.devtools_view = None + if WEB_ENGINE_AVAILABLE: + self.web = QWebEngineView() + self.web.setStyleSheet("background:#eef2f7;") + root.addWidget(self.web, 1) + self.web_channel = QWebChannel(self.web.page()) + self.window_bridge = WindowBridge(self) + self.web_channel.registerObject("windowBridge", self.window_bridge) + self.web.page().setWebChannel(self.web_channel) + self.web.loadFinished.connect(self.on_main_page_loaded) + self.web_shell = WebViewShellController(self.web) + + self.listener_sync_timer = QTimer(self) + self.listener_sync_timer.setInterval(30000) + self.listener_sync_timer.timeout.connect(self.sync_listener_state) + self._syncing_listener_state = False + + self.backend_ready_timer = QTimer(self) + self.backend_ready_timer.setInterval(100) + self.backend_ready_timer.timeout.connect(self.consume_backend_boot_result) + self._backend_boot_result = None + + self.loading.show() + self.start_backend() + + def get_settings(self): + if not self.base_url: + return {} + try: + url = self.base_url + "/api/rules?action=settings_get" + with request.urlopen(url, timeout=2) as resp: + data = resp.read().decode("utf-8") + import json + payload = json.loads(data) + return payload if isinstance(payload, dict) else {} + except Exception: + return {} + + def sync_listener_state(self): + if self._syncing_listener_state: + return + self._syncing_listener_state = True + try: + if not self.base_url: + return + requests.get(self.base_url + "/api/bot/status", timeout=2) + except Exception: + pass + finally: + self._syncing_listener_state = False + + def start_backend(self): + self.base_url = self.backend_runtime.base_url + self._backend_boot_result = None + self.backend_boot_thread = threading.Thread(target=self._boot_backend_worker, daemon=True) + self.backend_boot_thread.start() + self.backend_ready_timer.start() + + def _boot_backend_worker(self): + try: + if self.backend_runtime.is_backend_alive(): + self.backend_started_by_gui = False + self._backend_boot_result = {"ok": True, "url": self.base_url} + return + process = self.backend_runtime.launch_backend_process() + self.backend_process = process + self.backend_started_by_gui = True + ok, message = self.frontend_runtime.wait_for_backend(process=process) + if ok: + self._backend_boot_result = {"ok": True, "url": self.base_url} + else: + self._backend_boot_result = {"ok": False, "message": message} + except Exception as exc: + self._backend_boot_result = {"ok": False, "message": str(exc)} + + def consume_backend_boot_result(self): + if self._backend_boot_result is None: + return + result = self._backend_boot_result + self._backend_boot_result = None + self.backend_ready_timer.stop() + if result.get("ok"): + self.on_backend_started(result["url"]) + return + self.on_backend_failed(result.get("message") or "后台启动失败") + + def on_backend_started(self, url): + self.base_url = url + self.frontend_entry_url = self.frontend_runtime.resolve_frontend_entry_url(url) + self.reload_admin_page() + self.listener_sync_timer.start() + + def on_backend_failed(self, msg): + self.loading.close() + QMessageBox.critical(self, "后台错误", msg) + + def reload_admin_page(self): + self.web_shell.load(self.frontend_entry_url) + + def on_main_page_loaded(self, ok): + if not self.web_shell.mark_loaded(ok): + return + self.loading.finish_with(self._finish_show_main) + + def _finish_show_main(self): + if not self.web_shell.can_finish(): + return + self.web_shell.finish() + self.show() + self.raise_() + self.activateWindow() + QTimer.singleShot(60, self.loading.close) + + def open_devtools(self): + if self.web is None: + return + if self.devtools_view is None: + self.devtools_view = QWebEngineView() + self.devtools_view.setWindowTitle("页面调试控制台") + self.devtools_view.resize(1100, 760) + self.web.page().setDevToolsPage(self.devtools_view.page()) + self.devtools_view.show() + self.devtools_view.raise_() + self.devtools_view.activateWindow() + + def closeEvent(self, event): + try: + self.listener_sync_timer.stop() + except Exception: + pass + try: + self.backend_ready_timer.stop() + except Exception: + pass + try: + if self.backend_started_by_gui: + self.backend_runtime.terminate_backend_process(self.backend_process) + except Exception: + pass + super().closeEvent(event) diff --git a/app/presentation/shell.py b/app/presentation/shell.py new file mode 100644 index 0000000..883c858 --- /dev/null +++ b/app/presentation/shell.py @@ -0,0 +1,95 @@ +import time + +from PySide6.QtCore import QTimer, Qt, QUrl +from PySide6.QtGui import QGuiApplication +from PySide6.QtWidgets import QWidget, QVBoxLayout, QLabel, QProgressBar + + +class LoadingWindowController: + def __init__(self): + self.loading_window = None + self.loading_min_ms = 700 + self.loading_started_ms = 0.0 + + def show(self): + self.loading_started_ms = time.time() * 1000 + if self.loading_window is not None: + self.loading_window.show() + self.loading_window.raise_() + self.loading_window.activateWindow() + return self.loading_window + win = QWidget() + win.setWindowFlags(Qt.FramelessWindowHint | Qt.WindowStaysOnTopHint) + win.setAttribute(Qt.WA_DeleteOnClose, True) + win.resize(560, 220) + screen = QGuiApplication.primaryScreen() + if screen is not None: + geo = screen.availableGeometry() + win.move(geo.center().x() - win.width() // 2, geo.center().y() - win.height() // 2) + win.setStyleSheet("background:qlineargradient(x1:0,y1:0,x2:0,y2:1, stop:0 #f8fbff, stop:1 #eef4fb);border:1px solid #dbe7f5;border-radius:16px;") + lay = QVBoxLayout(win) + lay.setContentsMargins(30, 28, 30, 28) + lay.setSpacing(10) + + title = QLabel("识流 AI 助手") + title.setStyleSheet("font-size:18px;font-weight:700;color:#0f172a;") + label = QLabel("正在启动服务与管理台…") + label.setStyleSheet("font-size:14px;color:#334155;") + hint = QLabel("首次启动会稍慢一点，请稍候") + hint.setStyleSheet("font-size:12px;color:#64748b;") + + bar = QProgressBar() + bar.setRange(0, 0) + bar.setTextVisible(False) + bar.setFixedHeight(8) + bar.setStyleSheet("QProgressBar{background:#e5edf8;border:0;border-radius:4px;}QProgressBar::chunk{background:qlineargradient(x1:0,y1:0,x2:1,y2:0, stop:0 #22c1c3, stop:1 #3b82f6);border-radius:4px;}") + + lay.addWidget(title) + lay.addWidget(label) + lay.addSpacing(4) + lay.addWidget(bar) + lay.addWidget(hint) + lay.addStretch(1) + + self.loading_window = win + self.loading_window.show() + self.loading_window.raise_() + self.loading_window.activateWindow() + return self.loading_window + + def close(self): + if self.loading_window is not None: + self.loading_window.close() + self.loading_window = None + + def finish_with(self, callback): + elapsed = int(time.time() * 1000 - self.loading_started_ms) if self.loading_started_ms else self.loading_min_ms + remain = max(0, self.loading_min_ms - elapsed) + QTimer.singleShot(remain + 120, callback) + + +class WebViewShellController: + def __init__(self, web_view): + self.web_view = web_view + self.main_page_ready = False + self.expecting_admin_load = False + + def load(self, entry_url): + if self.web_view is None: + return + self.main_page_ready = False + self.expecting_admin_load = True + self.web_view.setStyleSheet("background:#eef2f7;") + self.web_view.load(QUrl(entry_url)) + + def mark_loaded(self, ok): + if not self.expecting_admin_load or not ok: + return False + self.main_page_ready = True + return True + + def can_finish(self): + return self.main_page_ready + + def finish(self): + self.expecting_admin_load = False diff --git a/backend_main.py b/backend_main.py new file mode 100644 index 0000000..5a2efa5 --- /dev/null +++ b/backend_main.py @@ -0,0 +1,46 @@ +import os +import sys +from pathlib import Path + +from app.application.services import AppConfig +from app.infrastructure.backend import start_backend + +PROJECT_ROOT = Path(__file__).resolve().parent +VENV_ROOT = PROJECT_ROOT / ".venv" +VENV_DIR = VENV_ROOT / "Scripts" +VENV_PYTHON = VENV_DIR / "python.exe" + + +def _resolve(path): + try: + return Path(path).resolve() + except Exception: + return None + + +def _running_in_project_venv(): + current_prefix = _resolve(sys.prefix) + if current_prefix == _resolve(VENV_ROOT): + return True + current_executable = _resolve(sys.executable) + return current_executable == _resolve(VENV_PYTHON) + + +def ensure_project_venv(): + if _running_in_project_venv(): + return + if os.environ.get("OPENCLAW_PROJECT_VENV_REEXEC") == "1": + raise RuntimeError("重启后仍未进入项目 .venv，请检查 .venv 是否损坏") + if not VENV_PYTHON.exists(): + raise RuntimeError(f"未找到项目 .venv 解释器: {VENV_PYTHON}") + os.environ["OPENCLAW_PROJECT_VENV_REEXEC"] = "1" + os.chdir(str(PROJECT_ROOT)) + os.execv(str(VENV_PYTHON), [str(VENV_PYTHON), str(PROJECT_ROOT / "backend_main.py")]) + + +ensure_project_venv() + + +if __name__ == "__main__": + config = AppConfig() + start_backend(host=config.host, port=config.port) diff --git a/frontend/dist/assets/core-DhEqZVGG.js b/frontend/dist/assets/core-DhEqZVGG.js new file mode 100644 index 0000000..54430e0 --- /dev/null +++ b/frontend/dist/assets/core-DhEqZVGG.js @@ -0,0 +1 @@ +function t(n,e,i,s){if(typeof e=="function"?n!==e||!s:!e.has(n))throw new TypeError("Cannot read private member from an object whose class did not declare it");return i==="m"?s:i==="a"?s.call(n):s?s.value:e.get(n)}function c(n,e,i,s,_){if(typeof e=="function"?n!==e||!0:!e.has(n))throw new TypeError("Cannot write private member to an object whose class did not declare it");return e.set(n,i),i}var a,r,o,l,u;const d="__TAURI_TO_IPC_KEY__";function w(n,e=!1){return window.__TAURI_INTERNALS__.transformCallback(n,e)}class g{constructor(e){a.set(this,void 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translateX(-50%); + transition: inherit; + border-radius: inherit; + `),dt("disabled",[I("&:hover",` + color: var(--n-close-icon-color-hover); + `),I("&:hover::before",` + background-color: var(--n-close-color-hover); + `),I("&:focus::before",` + background-color: var(--n-close-color-hover); + `),I("&:active",` + color: var(--n-close-icon-color-pressed); + `),I("&:active::before",` + background-color: var(--n-close-color-pressed); + `)]),H("disabled",` + cursor: not-allowed; + color: var(--n-close-icon-color-disabled); + background-color: transparent; + `),H("round",[I("&::before",` + border-radius: 50%; + `)])]),Kr=pe({name:"BaseClose",props:{isButtonTag:{type:Boolean,default:!0},clsPrefix:{type:String,required:!0},disabled:{type:Boolean,default:void 0},focusable:{type:Boolean,default:!0},round:Boolean,onClick:Function,absolute:Boolean},setup(e){return pr("-base-close",sk,we(e,"clsPrefix")),()=>{const{clsPrefix:t,disabled:n,absolute:o,round:r,isButtonTag:i}=e;return 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border-box; + min-width: 100%; + `)])])]),I(">, +",[P("scrollbar-rail",` + position: absolute; + pointer-events: none; + user-select: none; + background: var(--n-scrollbar-rail-color); + -webkit-user-select: none; + `,[H("horizontal",` + height: var(--n-scrollbar-height); + `,[I(">",[j("scrollbar",` + height: var(--n-scrollbar-height); + border-radius: var(--n-scrollbar-border-radius); + right: 0; + `)])]),H("horizontal--top",` + top: var(--n-scrollbar-rail-top-horizontal-top); + right: var(--n-scrollbar-rail-right-horizontal-top); + bottom: var(--n-scrollbar-rail-bottom-horizontal-top); + left: var(--n-scrollbar-rail-left-horizontal-top); + `),H("horizontal--bottom",` + top: var(--n-scrollbar-rail-top-horizontal-bottom); + right: var(--n-scrollbar-rail-right-horizontal-bottom); + bottom: var(--n-scrollbar-rail-bottom-horizontal-bottom); + left: var(--n-scrollbar-rail-left-horizontal-bottom); + `),H("vertical",` + width: var(--n-scrollbar-width); + `,[I(">",[j("scrollbar",` + width: 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Wk(e){const{textColorDisabled:t,iconColor:n,textColor2:o,fontSizeTiny:r,fontSizeSmall:i,fontSizeMedium:l,fontSizeLarge:a,fontSizeHuge:s}=e;return Object.assign(Object.assign({},jk),{fontSizeTiny:r,fontSizeSmall:i,fontSizeMedium:l,fontSizeLarge:a,fontSizeHuge:s,textColor:t,iconColor:n,extraTextColor:o})}const nc={name:"Empty",common:gt,self:Wk},Vk=P("empty",` + display: flex; + flex-direction: column; + align-items: center; + font-size: var(--n-font-size); +`,[j("icon",` + width: var(--n-icon-size); + height: var(--n-icon-size); + font-size: var(--n-icon-size); + line-height: var(--n-icon-size); + color: var(--n-icon-color); + transition: + color .3s var(--n-bezier); + `,[I("+",[j("description",` + margin-top: 8px; + `)])]),j("description",` + transition: color .3s var(--n-bezier); + color: var(--n-text-color); + `),j("extra",` + text-align: center; + transition: color .3s var(--n-bezier); + margin-top: 12px; + color: var(--n-extra-text-color); + `)]),Kk=Object.assign(Object.assign({},Be.props),{description:String,showDescription:{type:Boolean,default:!0},showIcon:{type:Boolean,default:!0},size:{type:String,default:"medium"},renderIcon:Function}),Ov=pe({name:"Empty",props:Kk,slots:Object,setup(e){const{mergedClsPrefixRef:t,inlineThemeDisabled:n,mergedComponentPropsRef:o}=Ye(e),r=Be("Empty","-empty",Vk,nc,e,t),{localeRef:i}=Xi("Empty"),l=O(()=>{var c,f,v;return(c=e.description)!==null&&c!==void 0?c:(v=(f=o?.value)===null||f===void 0?void 0:f.Empty)===null||v===void 0?void 0:v.description}),a=O(()=>{var c,f;return((f=(c=o?.value)===null||c===void 0?void 0:c.Empty)===null||f===void 0?void 0:f.renderIcon)||(()=>h(nk,null))}),s=O(()=>{const{size:c}=e,{common:{cubicBezierEaseInOut:f},self:{[de("iconSize",c)]:v,[de("fontSize",c)]:g,textColor:u,iconColor:p,extraTextColor:b}}=r.value;return{"--n-icon-size":v,"--n-font-size":g,"--n-bezier":f,"--n-text-color":u,"--n-icon-color":p,"--n-extra-text-color":b}}),d=n?vt("empty",O(()=>{let 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Gk(e){const{borderRadius:t,popoverColor:n,textColor3:o,dividerColor:r,textColor2:i,primaryColorPressed:l,textColorDisabled:a,primaryColor:s,opacityDisabled:d,hoverColor:c,fontSizeTiny:f,fontSizeSmall:v,fontSizeMedium:g,fontSizeLarge:u,fontSizeHuge:p,heightTiny:b,heightSmall:m,heightMedium:y,heightLarge:$,heightHuge:S}=e;return Object.assign(Object.assign({},Uk),{optionFontSizeTiny:f,optionFontSizeSmall:v,optionFontSizeMedium:g,optionFontSizeLarge:u,optionFontSizeHuge:p,optionHeightTiny:b,optionHeightSmall:m,optionHeightMedium:y,optionHeightLarge:$,optionHeightHuge:S,borderRadius:t,color:n,groupHeaderTextColor:o,actionDividerColor:r,optionTextColor:i,optionTextColorPressed:l,optionTextColorDisabled:a,optionTextColorActive:s,optionOpacityDisabled:d,optionCheckColor:s,optionColorPending:c,optionColorActive:"rgba(0, 0, 0, 0)",optionColorActivePending:c,actionTextColor:i,loadingColor:s})}const oc={name:"InternalSelectMenu",common:gt,peers:{Scrollbar:jo,Empty:nc},self:Gk},wf=pe({name:"NBaseSelectGroupHeader",props:{clsPrefix:{type:String,required:!0},tmNode:{type:Object,required:!0}},setup(){const{renderLabelRef:e,renderOptionRef:t,labelFieldRef:n,nodePropsRef:o}=Ee(Fd);return{labelField:n,nodeProps:o,renderLabel:e,renderOption:t}},render(){const{clsPrefix:e,renderLabel:t,renderOption:n,nodeProps:o,tmNode:{rawNode:r}}=this,i=o?.(r),l=t?t(r,!1):wt(r[this.labelField],r,!1),a=h("div",Object.assign({},i,{class:[`${e}-base-select-group-header`,i?.class]}),l);return r.render?r.render({node:a,option:r}):n?n({node:a,option:r,selected:!1}):a}});function qk(e,t){return h(pn,{name:"fade-in-scale-up-transition"},{default:()=>e?h(kt,{clsPrefix:t,class:`${t}-base-select-option__check`},{default:()=>h(QR)}):null})}const 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m===$}),labelField:a,renderLabel:i,renderOption:l,handleMouseMove:b,handleMouseEnter:p,handleClick:u}},render(){const{clsPrefix:e,tmNode:{rawNode:t},isSelected:n,isPending:o,isGrouped:r,showCheckmark:i,nodeProps:l,renderOption:a,renderLabel:s,handleClick:d,handleMouseEnter:c,handleMouseMove:f}=this,v=qk(n,e),g=s?[s(t,n),i&&v]:[wt(t[this.labelField],t,n),i&&v],u=l?.(t),p=h("div",Object.assign({},u,{class:[`${e}-base-select-option`,t.class,u?.class,{[`${e}-base-select-option--disabled`]:t.disabled,[`${e}-base-select-option--selected`]:n,[`${e}-base-select-option--grouped`]:r,[`${e}-base-select-option--pending`]:o,[`${e}-base-select-option--show-checkmark`]:i}],style:[u?.style||"",t.style||""],onClick:Si([d,u?.onClick]),onMouseenter:Si([c,u?.onMouseenter]),onMousemove:Si([f,u?.onMousemove])}),h("div",{class:`${e}-base-select-option__content`},g));return t.render?t.render({node:p,option:t,selected:n}):a?a({node:p,option:t,selected:n}):p}}),{cubicBezierEaseIn:Sf,cubicBezierEaseOut:Rf}=hr;function Yi({transformOrigin:e="inherit",duration:t=".2s",enterScale:n=".9",originalTransform:o="",originalTransition:r=""}={}){return[I("&.fade-in-scale-up-transition-leave-active",{transformOrigin:e,transition:`opacity ${t} ${Sf}, transform ${t} ${Sf} ${r&&`,${r}`}`}),I("&.fade-in-scale-up-transition-enter-active",{transformOrigin:e,transition:`opacity ${t} ${Rf}, transform ${t} ${Rf} ${r&&`,${r}`}`}),I("&.fade-in-scale-up-transition-enter-from, &.fade-in-scale-up-transition-leave-to",{opacity:0,transform:`${o} scale(${n})`}),I("&.fade-in-scale-up-transition-leave-from, &.fade-in-scale-up-transition-enter-to",{opacity:1,transform:`${o} scale(1)`})]}const Xk=P("base-select-menu",` + line-height: 1.5; + outline: none; + z-index: 0; + position: relative; + border-radius: var(--n-border-radius); + transition: + background-color .3s var(--n-bezier), + box-shadow .3s var(--n-bezier); + background-color: var(--n-color); +`,[P("scrollbar",` + max-height: var(--n-height); + `),P("virtual-list",` + max-height: var(--n-height); + `),P("base-select-option",` + min-height: var(--n-option-height); + font-size: var(--n-option-font-size); + display: flex; + align-items: center; + `,[j("content",` + z-index: 1; + white-space: nowrap; + text-overflow: ellipsis; + overflow: hidden; + `)]),P("base-select-group-header",` + min-height: var(--n-option-height); + font-size: .93em; + display: flex; + align-items: center; + `),P("base-select-menu-option-wrapper",` + position: relative; + width: 100%; + `),j("loading, empty",` + display: flex; + padding: 12px 32px; + flex: 1; + justify-content: center; + `),j("loading",` + color: var(--n-loading-color); + font-size: var(--n-loading-size); + `),j("header",` + padding: 8px var(--n-option-padding-left); + font-size: var(--n-option-font-size); + transition: + color .3s var(--n-bezier), + border-color .3s var(--n-bezier); + border-bottom: 1px solid var(--n-action-divider-color); + color: var(--n-action-text-color); + `),j("action",` + padding: 8px var(--n-option-padding-left); + font-size: var(--n-option-font-size); + transition: + color .3s var(--n-bezier), + border-color .3s var(--n-bezier); + border-top: 1px solid var(--n-action-divider-color); + color: var(--n-action-text-color); + `),P("base-select-group-header",` + position: relative; + cursor: default; + padding: var(--n-option-padding); + color: var(--n-group-header-text-color); + `),P("base-select-option",` + cursor: pointer; + position: relative; + padding: var(--n-option-padding); + transition: + color .3s var(--n-bezier), + opacity .3s var(--n-bezier); + box-sizing: border-box; + color: var(--n-option-text-color); + opacity: 1; + `,[H("show-checkmark",` + padding-right: calc(var(--n-option-padding-right) + 20px); + `),I("&::before",` + content: ""; + position: absolute; + left: 4px; + right: 4px; + top: 0; + bottom: 0; + border-radius: var(--n-border-radius); + transition: background-color .3s var(--n-bezier); + `),I("&:active",` + color: var(--n-option-text-color-pressed); + `),H("grouped",` + padding-left: calc(var(--n-option-padding-left) * 1.5); + `),H("pending",[I("&::before",` + background-color: var(--n-option-color-pending); + `)]),H("selected",` + color: var(--n-option-text-color-active); + `,[I("&::before",` + background-color: var(--n-option-color-active); + `),H("pending",[I("&::before",` + background-color: var(--n-option-color-active-pending); + `)])]),H("disabled",` + cursor: not-allowed; + `,[dt("selected",` + color: var(--n-option-text-color-disabled); + `),H("selected",` + opacity: var(--n-option-opacity-disabled); + `)]),j("check",` + font-size: 16px; + position: absolute; + right: calc(var(--n-option-padding-right) - 4px); + top: calc(50% - 7px); + color: var(--n-option-check-color); + transition: color .3s var(--n-bezier); + `,[Yi({enterScale:"0.5"})])])]),Ev=pe({name:"InternalSelectMenu",props:Object.assign(Object.assign({},Be.props),{clsPrefix:{type:String,required:!0},scrollable:{type:Boolean,default:!0},treeMate:{type:Object,required:!0},multiple:Boolean,size:{type:String,default:"medium"},value:{type:[String,Number,Array],default:null},autoPending:Boolean,virtualScroll:{type:Boolean,default:!0},show:{type:Boolean,default:!0},labelField:{type:String,default:"label"},valueField:{type:String,default:"value"},loading:Boolean,focusable:Boolean,renderLabel:Function,renderOption:Function,nodeProps:Function,showCheckmark:{type:Boolean,default:!0},onMousedown:Function,onScroll:Function,onFocus:Function,onBlur:Function,onKeyup:Function,onKeydown:Function,onTabOut:Function,onMouseenter:Function,onMouseleave:Function,onResize:Function,resetMenuOnOptionsChange:{type:Boolean,default:!0},inlineThemeDisabled:Boolean,scrollbarProps:Object,onToggle:Function}),setup(e){const{mergedClsPrefixRef:t,mergedRtlRef:n,mergedComponentPropsRef:o}=Ye(e),r=Bt("InternalSelectMenu",n,t),i=Be("InternalSelectMenu","-internal-select-menu",Xk,oc,e,we(e,"clsPrefix")),l=E(null),a=E(null),s=E(null),d=O(()=>e.treeMate.getFlattenedNodes()),c=O(()=>zk(d.value)),f=E(null);function v(){const{treeMate:Z}=e;let le=null;const{value:$e}=e;$e===null?le=Z.getFirstAvailableNode():(e.multiple?le=Z.getNode(($e||[])[($e||[]).length-1]):le=Z.getNode($e),(!le||le.disabled)&&(le=Z.getFirstAvailableNode())),K(le||null)}function g(){const{value:Z}=f;Z&&!e.treeMate.getNode(Z.key)&&(f.value=null)}let u;tt(()=>e.show,Z=>{Z?u=tt(()=>e.treeMate,()=>{e.resetMenuOnOptionsChange?(e.autoPending?v():g(),Rt(N)):g()},{immediate:!0}):u?.()},{immediate:!0}),xt(()=>{u?.()});const p=O(()=>Pt(i.value.self[de("optionHeight",e.size)])),b=O(()=>Ft(i.value.self[de("padding",e.size)])),m=O(()=>e.multiple&&Array.isArray(e.value)?new Set(e.value):new Set),y=O(()=>{const Z=d.value;return Z&&Z.length===0}),$=O(()=>{var Z,le;return(le=(Z=o?.value)===null||Z===void 0?void 0:Z.Select)===null||le===void 0?void 0:le.renderEmpty});function S(Z){const{onToggle:le}=e;le&&le(Z)}function x(Z){const{onScroll:le}=e;le&&le(Z)}function R(Z){var le;(le=s.value)===null||le===void 0||le.sync(),x(Z)}function C(){var 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he=O(()=>{const{size:Z}=e,{common:{cubicBezierEaseInOut:le},self:{height:$e,borderRadius:ze,color:Ae,groupHeaderTextColor:Te,actionDividerColor:ne,optionTextColorPressed:Oe,optionTextColor:z,optionTextColorDisabled:L,optionTextColorActive:ee,optionOpacityDisabled:se,optionCheckColor:ae,actionTextColor:Q,optionColorPending:ue,optionColorActive:ve,loadingColor:fe,loadingSize:oe,optionColorActivePending:q,[de("optionFontSize",Z)]:G,[de("optionHeight",Z)]:W,[de("optionPadding",Z)]:Y}}=i.value;return{"--n-height":$e,"--n-action-divider-color":ne,"--n-action-text-color":Q,"--n-bezier":le,"--n-border-radius":ze,"--n-color":Ae,"--n-option-font-size":G,"--n-group-header-text-color":Te,"--n-option-check-color":ae,"--n-option-color-pending":ue,"--n-option-color-active":ve,"--n-option-color-active-pending":q,"--n-option-height":W,"--n-option-opacity-disabled":se,"--n-option-text-color":z,"--n-option-text-color-active":ee,"--n-option-text-color-disabled":L,"--n-option-text-color-pressed":Oe,"--n-option-padding":Y,"--n-option-padding-left":Ft(Y,"left"),"--n-option-padding-right":Ft(Y,"right"),"--n-loading-color":fe,"--n-loading-size":oe}}),{inlineThemeDisabled:J}=e,re=J?vt("internal-select-menu",O(()=>e.size[0]),he,e):void 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transition: border-color .3s var(--n-bezier); + `),j("footer",` + padding: var(--n-padding); + border-top: 1px solid var(--n-divider-color); + transition: border-color .3s var(--n-bezier); + `),H("scrollable, show-header-or-footer",[j("content",` + padding: var(--n-padding); + `)])]),P("popover-shared",` + transform-origin: inherit; + `,[P("popover-arrow-wrapper",` + position: absolute; + overflow: hidden; + pointer-events: none; + `,[P("popover-arrow",` + transition: background-color .3s var(--n-bezier); + position: absolute; + display: block; + width: calc(${Tt}); + height: calc(${Tt}); + box-shadow: 0 0 8px 0 rgba(0, 0, 0, .12); + transform: rotate(45deg); + background-color: var(--n-color); + pointer-events: all; + `)]),I("&.popover-transition-enter-from, &.popover-transition-leave-to",` + opacity: 0; + transform: scale(.85); + `),I("&.popover-transition-enter-to, &.popover-transition-leave-from",` + transform: scale(1); + opacity: 1; + `),I("&.popover-transition-enter-active",` + transition: + box-shadow .3s var(--n-bezier), + background-color .3s var(--n-bezier), + color .3s var(--n-bezier), + opacity .15s var(--n-bezier-ease-out), + transform .15s var(--n-bezier-ease-out); + `),I("&.popover-transition-leave-active",` + transition: + box-shadow .3s var(--n-bezier), + background-color .3s var(--n-bezier), + color .3s var(--n-bezier), + opacity .15s var(--n-bezier-ease-in), + transform .15s var(--n-bezier-ease-in); + `)]),gn("top-start",` + top: calc(${Tt} / -2); + left: calc(${ro("top-start")} - var(--v-offset-left)); + `),gn("top",` + top: calc(${Tt} / -2); + transform: translateX(calc(${Tt} / -2)) rotate(45deg); + left: 50%; + `),gn("top-end",` + top: calc(${Tt} / -2); + right: calc(${ro("top-end")} + var(--v-offset-left)); + `),gn("bottom-start",` + bottom: calc(${Tt} / -2); + left: calc(${ro("bottom-start")} - var(--v-offset-left)); + `),gn("bottom",` + bottom: calc(${Tt} / -2); + transform: translateX(calc(${Tt} / -2)) rotate(45deg); + left: 50%; + `),gn("bottom-end",` + bottom: calc(${Tt} / -2); + right: calc(${ro("bottom-end")} + var(--v-offset-left)); + `),gn("left-start",` + left: calc(${Tt} / -2); + top: calc(${ro("left-start")} - var(--v-offset-top)); + `),gn("left",` + left: calc(${Tt} / -2); + transform: translateY(calc(${Tt} / -2)) rotate(45deg); + top: 50%; + `),gn("left-end",` + left: calc(${Tt} / -2); + bottom: calc(${ro("left-end")} + var(--v-offset-top)); + `),gn("right-start",` + right: calc(${Tt} / -2); + top: calc(${ro("right-start")} - var(--v-offset-top)); + `),gn("right",` + right: calc(${Tt} / -2); + transform: translateY(calc(${Tt} / -2)) rotate(45deg); + top: 50%; + `),gn("right-end",` + right: calc(${Tt} / -2); + bottom: calc(${ro("right-end")} + var(--v-offset-top)); + `),...VR({top:["right-start","left-start"],right:["top-end","bottom-end"],bottom:["right-end","left-end"],left:["top-start","bottom-start"]},(e,t)=>{const n=["right","left"].includes(t),o=n?"width":"height";return e.map(r=>{const 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iP(e){const{textColor2:t,primaryColorHover:n,primaryColorPressed:o,primaryColor:r,infoColor:i,successColor:l,warningColor:a,errorColor:s,baseColor:d,borderColor:c,opacityDisabled:f,tagColor:v,closeIconColor:g,closeIconColorHover:u,closeIconColorPressed:p,borderRadiusSmall:b,fontSizeMini:m,fontSizeTiny:y,fontSizeSmall:$,fontSizeMedium:S,heightMini:x,heightTiny:R,heightSmall:C,heightMedium:w,closeColorHover:k,closeColorPressed:F,buttonColor2Hover:M,buttonColor2Pressed:_,fontWeightStrong:T}=e;return Object.assign(Object.assign({},rP),{closeBorderRadius:b,heightTiny:x,heightSmall:R,heightMedium:C,heightLarge:w,borderRadius:b,opacityDisabled:f,fontSizeTiny:m,fontSizeSmall:y,fontSizeMedium:$,fontSizeLarge:S,fontWeightStrong:T,textColorCheckable:t,textColorHoverCheckable:t,textColorPressedCheckable:t,textColorChecked:d,colorCheckable:"#0000",colorHoverCheckable:M,colorPressedCheckable:_,colorChecked:r,colorCheckedHover:n,colorCheckedPressed:o,border:`1px solid ${c}`,textColor:t,color:v,colorBordered:"rgb(250, 250, 252)",closeIconColor:g,closeIconColorHover:u,closeIconColorPressed:p,closeColorHover:k,closeColorPressed:F,borderPrimary:`1px solid ${Ue(r,{alpha:.3})}`,textColorPrimary:r,colorPrimary:Ue(r,{alpha:.12}),colorBorderedPrimary:Ue(r,{alpha:.1}),closeIconColorPrimary:r,closeIconColorHoverPrimary:r,closeIconColorPressedPrimary:r,closeColorHoverPrimary:Ue(r,{alpha:.12}),closeColorPressedPrimary:Ue(r,{alpha:.18}),borderInfo:`1px solid ${Ue(i,{alpha:.3})}`,textColorInfo:i,colorInfo:Ue(i,{alpha:.12}),colorBorderedInfo:Ue(i,{alpha:.1}),closeIconColorInfo:i,closeIconColorHoverInfo:i,closeIconColorPressedInfo:i,closeColorHoverInfo:Ue(i,{alpha:.12}),closeColorPressedInfo:Ue(i,{alpha:.18}),borderSuccess:`1px solid ${Ue(l,{alpha:.3})}`,textColorSuccess:l,colorSuccess:Ue(l,{alpha:.12}),colorBorderedSuccess:Ue(l,{alpha:.1}),closeIconColorSuccess:l,closeIconColorHoverSuccess:l,closeIconColorPressedSuccess:l,closeColorHoverSuccess:Ue(l,{alpha:.12}),closeColorPressedSuccess:Ue(l,{alpha:.18}),borderWarning:`1px solid ${Ue(a,{alpha:.35})}`,textColorWarning:a,colorWarning:Ue(a,{alpha:.15}),colorBorderedWarning:Ue(a,{alpha:.12}),closeIconColorWarning:a,closeIconColorHoverWarning:a,closeIconColorPressedWarning:a,closeColorHoverWarning:Ue(a,{alpha:.12}),closeColorPressedWarning:Ue(a,{alpha:.18}),borderError:`1px solid ${Ue(s,{alpha:.23})}`,textColorError:s,colorError:Ue(s,{alpha:.1}),colorBorderedError:Ue(s,{alpha:.08}),closeIconColorError:s,closeIconColorHoverError:s,closeIconColorPressedError:s,closeColorHoverError:Ue(s,{alpha:.12}),closeColorPressedError:Ue(s,{alpha:.18})})}const lP={common:gt,self:iP},aP={color:Object,type:{type:String,default:"default"},round:Boolean,size:String,closable:Boolean,disabled:{type:Boolean,default:void 0}},sP=P("tag",` + --n-close-margin: var(--n-close-margin-top) var(--n-close-margin-right) var(--n-close-margin-bottom) var(--n-close-margin-left); + white-space: nowrap; + position: relative; + box-sizing: border-box; + cursor: default; + display: inline-flex; + align-items: center; + flex-wrap: nowrap; + padding: var(--n-padding); + border-radius: var(--n-border-radius); + color: var(--n-text-color); + background-color: var(--n-color); + transition: + border-color .3s var(--n-bezier), + background-color .3s var(--n-bezier), + color .3s var(--n-bezier), + box-shadow .3s var(--n-bezier), + opacity .3s var(--n-bezier); + line-height: 1; + height: var(--n-height); + font-size: var(--n-font-size); +`,[H("strong",` + font-weight: var(--n-font-weight-strong); + `),j("border",` + pointer-events: none; + position: absolute; + left: 0; + right: 0; + top: 0; + bottom: 0; + border-radius: inherit; + border: var(--n-border); + transition: border-color .3s var(--n-bezier); + `),j("icon",` + display: flex; + margin: 0 4px 0 0; + color: var(--n-text-color); + transition: color .3s var(--n-bezier); + font-size: var(--n-avatar-size-override); + `),j("avatar",` + display: flex; + margin: 0 6px 0 0; + `),j("close",` + margin: var(--n-close-margin); + transition: + background-color .3s var(--n-bezier), + color .3s var(--n-bezier); + `),H("round",` + padding: 0 calc(var(--n-height) / 3); + border-radius: calc(var(--n-height) / 2); + `,[j("icon",` + margin: 0 4px 0 calc((var(--n-height) - 8px) / -2); + `),j("avatar",` + margin: 0 6px 0 calc((var(--n-height) - 8px) / -2); + `),H("closable",` + padding: 0 calc(var(--n-height) / 4) 0 calc(var(--n-height) / 3); + `)]),H("icon, avatar",[H("round",` + padding: 0 calc(var(--n-height) / 3) 0 calc(var(--n-height) / 2); + `)]),H("disabled",` + cursor: not-allowed !important; + opacity: var(--n-opacity-disabled); + `),H("checkable",` + cursor: pointer; + box-shadow: none; + color: var(--n-text-color-checkable); + background-color: var(--n-color-checkable); + `,[dt("disabled",[I("&:hover","background-color: var(--n-color-hover-checkable);",[dt("checked","color: var(--n-text-color-hover-checkable);")]),I("&:active","background-color: var(--n-color-pressed-checkable);",[dt("checked","color: var(--n-text-color-pressed-checkable);")])]),H("checked",` + color: var(--n-text-color-checked); + background-color: var(--n-color-checked); + `,[dt("disabled",[I("&:hover","background-color: var(--n-color-checked-hover);"),I("&:active","background-color: var(--n-color-checked-pressed);")])])])]),dP=Object.assign(Object.assign(Object.assign({},Be.props),aP),{bordered:{type:Boolean,default:void 0},checked:Boolean,checkable:Boolean,strong:Boolean,triggerClickOnClose:Boolean,onClose:[Array,Function],onMouseenter:Function,onMouseleave:Function,"onUpdate:checked":Function,onUpdateChecked:Function,internalCloseFocusable:{type:Boolean,default:!0},internalCloseIsButtonTag:{type:Boolean,default:!0},onCheckedChange:Function}),cP="n-tag",ki=pe({name:"Tag",props:dP,slots:Object,setup(e){const t=E(null),{mergedBorderedRef:n,mergedClsPrefixRef:o,inlineThemeDisabled:r,mergedRtlRef:i,mergedComponentPropsRef:l}=Ye(e),a=O(()=>{var p,b;return e.size||((b=(p=l?.value)===null||p===void 0?void 0:p.Tag)===null||b===void 0?void 0:b.size)||"medium"}),s=Be("Tag","-tag",sP,lP,e,o);qe(cP,{roundRef:we(e,"round")});function d(){if(!e.disabled&&e.checkable){const{checked:p,onCheckedChange:b,onUpdateChecked:m,"onUpdate:checked":y}=e;m&&m(!p),y&&y(!p),b&&b(!p)}}function c(p){if(e.triggerClickOnClose||p.stopPropagation(),!e.disabled){const{onClose:b}=e;b&&me(b,p)}}const f={setTextContent(p){const{value:b}=t;b&&(b.textContent=p)}},v=Bt("Tag",i,o),g=O(()=>{const{type:p,color:{color:b,textColor:m}={}}=e,y=a.value,{common:{cubicBezierEaseInOut:$},self:{padding:S,closeMargin:x,borderRadius:R,opacityDisabled:C,textColorCheckable:w,textColorHoverCheckable:k,textColorPressedCheckable:F,textColorChecked:M,colorCheckable:_,colorHoverCheckable:T,colorPressedCheckable:B,colorChecked:D,colorCheckedHover:K,colorCheckedPressed:N,closeBorderRadius:V,fontWeightStrong:ie,[de("colorBordered",p)]:he,[de("closeSize",y)]:J,[de("closeIconSize",y)]:re,[de("fontSize",y)]:ye,[de("height",y)]:Z,[de("color",p)]:le,[de("textColor",p)]:$e,[de("border",p)]:ze,[de("closeIconColor",p)]:Ae,[de("closeIconColorHover",p)]:Te,[de("closeIconColorPressed",p)]:ne,[de("closeColorHover",p)]:Oe,[de("closeColorPressed",p)]:z}}=s.value,L=Ft(x);return{"--n-font-weight-strong":ie,"--n-avatar-size-override":`calc(${Z} - 8px)`,"--n-bezier":$,"--n-border-radius":R,"--n-border":ze,"--n-close-icon-size":re,"--n-close-color-pressed":z,"--n-close-color-hover":Oe,"--n-close-border-radius":V,"--n-close-icon-color":Ae,"--n-close-icon-color-hover":Te,"--n-close-icon-color-pressed":ne,"--n-close-icon-color-disabled":Ae,"--n-close-margin-top":L.top,"--n-close-margin-right":L.right,"--n-close-margin-bottom":L.bottom,"--n-close-margin-left":L.left,"--n-close-size":J,"--n-color":b||(n.value?he:le),"--n-color-checkable":_,"--n-color-checked":D,"--n-color-checked-hover":K,"--n-color-checked-pressed":N,"--n-color-hover-checkable":T,"--n-color-pressed-checkable":B,"--n-font-size":ye,"--n-height":Z,"--n-opacity-disabled":C,"--n-padding":S,"--n-text-color":m||$e,"--n-text-color-checkable":w,"--n-text-color-checked":M,"--n-text-color-hover-checkable":k,"--n-text-color-pressed-checkable":F}}),u=r?vt("tag",O(()=>{let p="";const{type:b,color:{color:m,textColor:y}={}}=e;return p+=b[0],p+=a.value[0],m&&(p+=`a${Al(m)}`),y&&(p+=`b${Al(y)}`),n.value&&(p+="c"),p}),g,e):void 0;return Object.assign(Object.assign({},f),{rtlEnabled:v,mergedClsPrefix:o,contentRef:t,mergedBordered:n,handleClick:d,handleCloseClick:c,cssVars:r?void 0:g,themeClass:u?.themeClass,onRender:u?.onRender})},render(){var e,t;const{mergedClsPrefix:n,rtlEnabled:o,closable:r,color:{borderColor:i}={},round:l,onRender:a,$slots:s}=this;a?.();const d=lt(s.avatar,f=>f&&h("div",{class:`${n}-tag__avatar`},f)),c=lt(s.icon,f=>f&&h("div",{class:`${n}-tag__icon`},f));return h("div",{class:[`${n}-tag`,this.themeClass,{[`${n}-tag--rtl`]:o,[`${n}-tag--strong`]:this.strong,[`${n}-tag--disabled`]:this.disabled,[`${n}-tag--checkable`]:this.checkable,[`${n}-tag--checked`]:this.checkable&&this.checked,[`${n}-tag--round`]:l,[`${n}-tag--avatar`]:d,[`${n}-tag--icon`]:c,[`${n}-tag--closable`]:r}],style:this.cssVars,onClick:this.handleClick,onMouseenter:this.onMouseenter,onMouseleave:this.onMouseleave},c||d,h("span",{class:`${n}-tag__content`,ref:"contentRef"},(t=(e=this.$slots).default)===null||t===void 0?void 0:t.call(e)),!this.checkable&&r?h(Kr,{clsPrefix:n,class:`${n}-tag__close`,disabled:this.disabled,onClick:this.handleCloseClick,focusable:this.internalCloseFocusable,round:l,isButtonTag:this.internalCloseIsButtonTag,absolute:!0}):null,!this.checkable&&this.mergedBordered?h("div",{class:`${n}-tag__border`,style:{borderColor:i}}):null)}}),Av=pe({name:"InternalSelectionSuffix",props:{clsPrefix:{type:String,required:!0},showArrow:{type:Boolean,default:void 0},showClear:{type:Boolean,default:void 0},loading:{type:Boolean,default:!1},onClear:Function},setup(e,{slots:t}){return()=>{const{clsPrefix:n}=e;return h(gr,{clsPrefix:n,class:`${n}-base-suffix`,strokeWidth:24,scale:.85,show:e.loading},{default:()=>e.showArrow?h(Qs,{clsPrefix:n,show:e.showClear,onClear:e.onClear},{placeholder:()=>h(kt,{clsPrefix:n,class:`${n}-base-suffix__arrow`},{default:()=>$n(t.default,()=>[h(kv,null)])})}):null})}}}),uP={paddingSingle:"0 26px 0 12px",paddingMultiple:"3px 26px 0 12px",clearSize:"16px",arrowSize:"16px"};function fP(e){const{borderRadius:t,textColor2:n,textColorDisabled:o,inputColor:r,inputColorDisabled:i,primaryColor:l,primaryColorHover:a,warningColor:s,warningColorHover:d,errorColor:c,errorColorHover:f,borderColor:v,iconColor:g,iconColorDisabled:u,clearColor:p,clearColorHover:b,clearColorPressed:m,placeholderColor:y,placeholderColorDisabled:$,fontSizeTiny:S,fontSizeSmall:x,fontSizeMedium:R,fontSizeLarge:C,heightTiny:w,heightSmall:k,heightMedium:F,heightLarge:M,fontWeight:_}=e;return Object.assign(Object.assign({},uP),{fontSizeTiny:S,fontSizeSmall:x,fontSizeMedium:R,fontSizeLarge:C,heightTiny:w,heightSmall:k,heightMedium:F,heightLarge:M,borderRadius:t,fontWeight:_,textColor:n,textColorDisabled:o,placeholderColor:y,placeholderColorDisabled:$,color:r,colorDisabled:i,colorActive:r,border:`1px solid ${v}`,borderHover:`1px solid ${a}`,borderActive:`1px solid ${l}`,borderFocus:`1px solid ${a}`,boxShadowHover:"none",boxShadowActive:`0 0 0 2px ${Ue(l,{alpha:.2})}`,boxShadowFocus:`0 0 0 2px ${Ue(l,{alpha:.2})}`,caretColor:l,arrowColor:g,arrowColorDisabled:u,loadingColor:l,borderWarning:`1px solid ${s}`,borderHoverWarning:`1px solid ${d}`,borderActiveWarning:`1px solid ${s}`,borderFocusWarning:`1px solid ${d}`,boxShadowHoverWarning:"none",boxShadowActiveWarning:`0 0 0 2px ${Ue(s,{alpha:.2})}`,boxShadowFocusWarning:`0 0 0 2px ${Ue(s,{alpha:.2})}`,colorActiveWarning:r,caretColorWarning:s,borderError:`1px solid ${c}`,borderHoverError:`1px solid ${f}`,borderActiveError:`1px solid ${c}`,borderFocusError:`1px solid ${f}`,boxShadowHoverError:"none",boxShadowActiveError:`0 0 0 2px ${Ue(c,{alpha:.2})}`,boxShadowFocusError:`0 0 0 2px ${Ue(c,{alpha:.2})}`,colorActiveError:r,caretColorError:c,clearColor:p,clearColorHover:b,clearColorPressed:m})}const Iv={name:"InternalSelection",common:gt,peers:{Popover:Ur},self:fP},hP=I([P("base-selection",` + --n-padding-single: var(--n-padding-single-top) var(--n-padding-single-right) var(--n-padding-single-bottom) var(--n-padding-single-left); + --n-padding-multiple: var(--n-padding-multiple-top) var(--n-padding-multiple-right) var(--n-padding-multiple-bottom) var(--n-padding-multiple-left); + position: relative; + z-index: auto; + box-shadow: none; + width: 100%; + max-width: 100%; + display: inline-block; + vertical-align: bottom; + border-radius: var(--n-border-radius); + min-height: var(--n-height); + line-height: 1.5; + font-size: var(--n-font-size); + `,[P("base-loading",` + color: var(--n-loading-color); + `),P("base-selection-tags","min-height: var(--n-height);"),j("border, state-border",` + position: absolute; + left: 0; + right: 0; + top: 0; + bottom: 0; + pointer-events: none; + border: var(--n-border); + border-radius: inherit; + transition: + box-shadow .3s var(--n-bezier), + border-color .3s var(--n-bezier); + `),j("state-border",` + z-index: 1; + border-color: #0000; + `),P("base-suffix",` + cursor: pointer; + position: absolute; + top: 50%; + transform: translateY(-50%); + right: 10px; + `,[j("arrow",` + font-size: var(--n-arrow-size); + color: var(--n-arrow-color); + transition: color .3s var(--n-bezier); + `)]),P("base-selection-overlay",` + display: flex; + align-items: center; + white-space: nowrap; + pointer-events: none; + position: absolute; + top: 0; + right: 0; + bottom: 0; + left: 0; + padding: var(--n-padding-single); + transition: color .3s var(--n-bezier); + `,[j("wrapper",` + flex-basis: 0; + flex-grow: 1; + overflow: hidden; + text-overflow: ellipsis; + `)]),P("base-selection-placeholder",` + color: var(--n-placeholder-color); + `,[j("inner",` + max-width: 100%; + overflow: hidden; + `)]),P("base-selection-tags",` + cursor: pointer; + outline: none; + box-sizing: border-box; + position: relative; + z-index: auto; + display: flex; + padding: var(--n-padding-multiple); + flex-wrap: wrap; + align-items: center; + width: 100%; + vertical-align: bottom; + background-color: var(--n-color); + border-radius: inherit; + transition: + color .3s var(--n-bezier), + box-shadow .3s var(--n-bezier), + background-color .3s var(--n-bezier); + `),P("base-selection-label",` + height: var(--n-height); + display: inline-flex; + width: 100%; + vertical-align: bottom; + cursor: pointer; + outline: none; + z-index: auto; + box-sizing: border-box; + position: relative; + transition: + color .3s var(--n-bezier), + box-shadow .3s var(--n-bezier), + background-color .3s var(--n-bezier); + border-radius: inherit; + background-color: var(--n-color); + align-items: center; + `,[P("base-selection-input",` + font-size: inherit; + line-height: inherit; + outline: none; + cursor: pointer; + box-sizing: border-box; + border:none; + width: 100%; + padding: var(--n-padding-single); + background-color: #0000; + color: var(--n-text-color); + transition: color .3s var(--n-bezier); + caret-color: var(--n-caret-color); + `,[j("content",` + text-overflow: ellipsis; + overflow: hidden; + white-space: nowrap; + `)]),j("render-label",` + color: var(--n-text-color); + `)]),dt("disabled",[I("&:hover",[j("state-border",` + box-shadow: var(--n-box-shadow-hover); + border: var(--n-border-hover); + `)]),H("focus",[j("state-border",` + box-shadow: var(--n-box-shadow-focus); + border: var(--n-border-focus); + `)]),H("active",[j("state-border",` + box-shadow: var(--n-box-shadow-active); + border: var(--n-border-active); + `),P("base-selection-label","background-color: var(--n-color-active);"),P("base-selection-tags","background-color: var(--n-color-active);")])]),H("disabled","cursor: not-allowed;",[j("arrow",` + color: var(--n-arrow-color-disabled); + `),P("base-selection-label",` + cursor: not-allowed; + background-color: var(--n-color-disabled); + `,[P("base-selection-input",` + cursor: not-allowed; + color: var(--n-text-color-disabled); + `),j("render-label",` + color: var(--n-text-color-disabled); + `)]),P("base-selection-tags",` + cursor: not-allowed; + background-color: var(--n-color-disabled); + `),P("base-selection-placeholder",` + cursor: not-allowed; + color: var(--n-placeholder-color-disabled); + `)]),P("base-selection-input-tag",` + height: calc(var(--n-height) - 6px); + line-height: calc(var(--n-height) - 6px); + outline: none; + display: none; + position: relative; + margin-bottom: 3px; + max-width: 100%; + vertical-align: bottom; + `,[j("input",` + font-size: inherit; + font-family: inherit; + min-width: 1px; + padding: 0; + background-color: #0000; + outline: none; + border: none; + max-width: 100%; + overflow: hidden; + width: 1em; + line-height: inherit; + cursor: pointer; + color: var(--n-text-color); + caret-color: var(--n-caret-color); + `),j("mirror",` + position: absolute; + left: 0; + top: 0; + white-space: pre; + visibility: hidden; + user-select: none; + -webkit-user-select: none; + opacity: 0; + `)]),["warning","error"].map(e=>H(`${e}-status`,[j("state-border",`border: var(--n-border-${e});`),dt("disabled",[I("&:hover",[j("state-border",` + box-shadow: var(--n-box-shadow-hover-${e}); + border: var(--n-border-hover-${e}); + `)]),H("active",[j("state-border",` + box-shadow: var(--n-box-shadow-active-${e}); + border: var(--n-border-active-${e}); + `),P("base-selection-label",`background-color: var(--n-color-active-${e});`),P("base-selection-tags",`background-color: var(--n-color-active-${e});`)]),H("focus",[j("state-border",` + box-shadow: var(--n-box-shadow-focus-${e}); + border: var(--n-border-focus-${e}); + `)])])]))]),P("base-selection-popover",` + margin-bottom: -3px; + display: flex; + flex-wrap: wrap; + margin-right: -8px; + `),P("base-selection-tag-wrapper",` + max-width: 100%; + display: inline-flex; + padding: 0 7px 3px 0; + `,[I("&:last-child","padding-right: 0;"),P("tag",` + font-size: 14px; + max-width: 100%; + `,[j("content",` + line-height: 1.25; + text-overflow: ellipsis; + overflow: hidden; + `)])])]),pP=pe({name:"InternalSelection",props:Object.assign(Object.assign({},Be.props),{clsPrefix:{type:String,required:!0},bordered:{type:Boolean,default:void 0},active:Boolean,pattern:{type:String,default:""},placeholder:String,selectedOption:{type:Object,default:null},selectedOptions:{type:Array,default:null},labelField:{type:String,default:"label"},valueField:{type:String,default:"value"},multiple:Boolean,filterable:Boolean,clearable:Boolean,disabled:Boolean,size:{type:String,default:"medium"},loading:Boolean,autofocus:Boolean,showArrow:{type:Boolean,default:!0},inputProps:Object,focused:Boolean,renderTag:Function,onKeydown:Function,onClick:Function,onBlur:Function,onFocus:Function,onDeleteOption:Function,maxTagCount:[String,Number],ellipsisTagPopoverProps:Object,onClear:Function,onPatternInput:Function,onPatternFocus:Function,onPatternBlur:Function,renderLabel:Function,status:String,inlineThemeDisabled:Boolean,ignoreComposition:{type:Boolean,default:!0},onResize:Function}),setup(e){const{mergedClsPrefixRef:t,mergedRtlRef:n}=Ye(e),o=Bt("InternalSelection",n,t),r=E(null),i=E(null),l=E(null),a=E(null),s=E(null),d=E(null),c=E(null),f=E(null),v=E(null),g=E(null),u=E(!1),p=E(!1),b=E(!1),m=Be("InternalSelection","-internal-selection",hP,Iv,e,we(e,"clsPrefix")),y=O(()=>e.clearable&&!e.disabled&&(b.value||e.active)),$=O(()=>e.selectedOption?e.renderTag?e.renderTag({option:e.selectedOption,handleClose:()=>{}}):e.renderLabel?e.renderLabel(e.selectedOption,!0):wt(e.selectedOption[e.labelField],e.selectedOption,!0):e.placeholder),S=O(()=>{const 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overflow: ${e}; + transition: + max-height ${t} ${An} ${o}, + opacity ${t} ${mP} ${o}, + margin-top ${t} ${An} ${o}, + margin-bottom ${t} ${An} ${o}, + padding-top ${t} ${An} ${o}, + padding-bottom ${t} ${An} ${o} + ${n?`,${n}`:""} + `),I(`&.fade-in-height-expand-transition-${s}-active`,` + overflow: ${e}; + transition: + max-height ${t} ${An}, + opacity ${t} ${yP}, + margin-top ${t} ${An}, + margin-bottom ${t} ${An}, + padding-top ${t} ${An}, + padding-bottom ${t} ${An} + ${n?`,${n}`:""} + `)]}const wP=Do&&"chrome"in window;Do&&navigator.userAgent.includes("Firefox");const Lv=Do&&navigator.userAgent.includes("Safari")&&!wP,CP={paddingTiny:"0 8px",paddingSmall:"0 10px",paddingMedium:"0 12px",paddingLarge:"0 14px",clearSize:"16px"};function 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font-size: inherit; + line-height: 1.5; + font-family: inherit; + border: none; + outline: none; + background-color: #0000; + text-align: inherit; + transition: + -webkit-text-fill-color .3s var(--n-bezier), + caret-color .3s var(--n-bezier), + color .3s var(--n-bezier), + text-decoration-color .3s var(--n-bezier); + `),j("input-el, textarea-el",` + -webkit-appearance: none; + scrollbar-width: none; + width: 100%; + min-width: 0; + text-decoration-color: var(--n-text-decoration-color); + color: var(--n-text-color); + caret-color: var(--n-caret-color); + background-color: transparent; + `,[I("&::-webkit-scrollbar, &::-webkit-scrollbar-track-piece, &::-webkit-scrollbar-thumb",` + width: 0; + height: 0; + display: none; + `),I("&::placeholder",` + color: #0000; + -webkit-text-fill-color: transparent !important; + `),I("&:-webkit-autofill ~",[j("placeholder","display: none;")])]),H("round",[dt("textarea","border-radius: calc(var(--n-height) / 2);")]),j("placeholder",` + pointer-events: none; + position: absolute; + left: 0; + right: 0; + top: 0; + bottom: 0; + overflow: hidden; + color: var(--n-placeholder-color); + `,[I("span",` + width: 100%; + display: inline-block; + `)]),H("textarea",[j("placeholder","overflow: visible;")]),dt("autosize","width: 100%;"),H("autosize",[j("textarea-el, input-el",` + position: absolute; + top: 0; + left: 0; + height: 100%; + `)]),P("input-wrapper",` + overflow: hidden; + display: inline-flex; + flex-grow: 1; + position: relative; + padding-left: var(--n-padding-left); + padding-right: var(--n-padding-right); + `),j("input-mirror",` + padding: 0; + height: var(--n-height); + line-height: var(--n-height); + overflow: hidden; + visibility: hidden; + position: static; + white-space: pre; + pointer-events: none; + `),j("input-el",` + padding: 0; + height: var(--n-height); + line-height: var(--n-height); + `,[I("&[type=password]::-ms-reveal","display: none;"),I("+",[j("placeholder",` + display: flex; + align-items: center; + `)])]),dt("textarea",[j("placeholder","white-space: nowrap;")]),j("eye",` + display: flex; + align-items: center; + justify-content: center; + transition: color .3s var(--n-bezier); + `),H("textarea","width: 100%;",[P("input-word-count",` + position: absolute; + right: var(--n-padding-right); + bottom: var(--n-padding-vertical); + `),H("resizable",[P("input-wrapper",` + resize: vertical; + min-height: var(--n-height); + `)]),j("textarea-el, textarea-mirror, placeholder",` + height: 100%; + padding-left: 0; + padding-right: 0; + padding-top: var(--n-padding-vertical); + padding-bottom: var(--n-padding-vertical); + word-break: break-word; + display: inline-block; + vertical-align: bottom; + box-sizing: border-box; + line-height: var(--n-line-height-textarea); + margin: 0; + resize: none; + white-space: pre-wrap; + scroll-padding-block-end: var(--n-padding-vertical); + `),j("textarea-mirror",` + width: 100%; + pointer-events: none; + overflow: hidden; + visibility: hidden; + position: 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0:b.call(g,p)}}):null,this.mergedShowPasswordOn&&this.type==="password"?h("div",{class:`${a}-input__eye`,onMousedown:this.handlePasswordToggleMousedown,onClick:this.handlePasswordToggleClick},this.passwordVisible?$n(g["password-visible-icon"],()=>[h(kt,{clsPrefix:a},{default:()=>h(ok,null)})]):$n(g["password-invisible-icon"],()=>[h(kt,{clsPrefix:a},{default:()=>h(rk,null)})])):null]):null)),this.pair?h("span",{class:`${a}-input__separator`},$n(g.separator,()=>[this.separator])):null,this.pair?h("div",{class:`${a}-input-wrapper`},h("div",{class:`${a}-input__input`},h("input",{ref:"inputEl2Ref",type:this.type,class:`${a}-input__input-el`,tabindex:this.passivelyActivated&&!this.activated?-1:void 0,placeholder:this.mergedPlaceholder[1],disabled:this.mergedDisabled,maxlength:f?void 0:this.maxlength,minlength:f?void 0:this.minlength,value:Array.isArray(this.mergedValue)?this.mergedValue[1]:void 0,readonly:this.readonly,style:this.textDecorationStyle[1],onBlur:this.handleInputBlur,onFocus:u=>{this.handleInputFocus(u,1)},onInput:u=>{this.handleInput(u,1)},onChange:u=>{this.handleChange(u,1)}}),this.showPlaceholder2?h("div",{class:`${a}-input__placeholder`},h("span",null,this.mergedPlaceholder[1])):null),lt(g.suffix,u=>(this.clearable||u)&&h("div",{class:`${a}-input__suffix`},[this.clearable&&h(Qs,{clsPrefix:a,show:this.showClearButton,onClear:this.handleClear},{icon:()=>{var p;return(p=g["clear-icon"])===null||p===void 0?void 0:p.call(g)},placeholder:()=>{var p;return(p=g["clear-icon-placeholder"])===null||p===void 0?void 0:p.call(g)}}),u]))):null,this.mergedBordered?h("div",{class:`${a}-input__border`}):null,this.mergedBordered?h("div",{class:`${a}-input__state-border`}):null,this.showCount&&c==="textarea"?h(kf,null,{default:u=>{var p;const{renderCount:b}=this;return b?b(u):(p=g.count)===null||p===void 0?void 0:p.call(g,u)}}):null)}});function Kl(e){return e.type==="group"}function Nv(e){return e.type==="ignored"}function gs(e,t){try{return!!(1+t.toString().toLowerCase().indexOf(e.trim().toLowerCase()))}catch{return!1}}function jv(e,t){return{getIsGroup:Kl,getIgnored:Nv,getKey(o){return Kl(o)?o.name||o.key||"key-required":o[e]},getChildren(o){return o[t]}}}function zP(e,t,n,o){if(!t)return e;function r(i){if(!Array.isArray(i))return[];const l=[];for(const a of i)if(Kl(a)){const s=r(a[o]);s.length&&l.push(Object.assign({},a,{[o]:s}))}else{if(Nv(a))continue;t(n,a)&&l.push(a)}return l}return r(e)}function TP(e,t,n){const o=new Map;return e.forEach(r=>{Kl(r)?r[n].forEach(i=>{o.set(i[t],i)}):o.set(r[t],r)}),o}function Go(e){return rt(e,[255,255,255,.16])}function pl(e){return rt(e,[0,0,0,.12])}const FP="n-button-group",OP={paddingTiny:"0 6px",paddingSmall:"0 10px",paddingMedium:"0 14px",paddingLarge:"0 18px",paddingRoundTiny:"0 10px",paddingRoundSmall:"0 14px",paddingRoundMedium:"0 18px",paddingRoundLarge:"0 22px",iconMarginTiny:"6px",iconMarginSmall:"6px",iconMarginMedium:"6px",iconMarginLarge:"6px",iconSizeTiny:"14px",iconSizeSmall:"18px",iconSizeMedium:"18px",iconSizeLarge:"20px",rippleDuration:".6s"};function EP(e){const{heightTiny:t,heightSmall:n,heightMedium:o,heightLarge:r,borderRadius:i,fontSizeTiny:l,fontSizeSmall:a,fontSizeMedium:s,fontSizeLarge:d,opacityDisabled:c,textColor2:f,textColor3:v,primaryColorHover:g,primaryColorPressed:u,borderColor:p,primaryColor:b,baseColor:m,infoColor:y,infoColorHover:$,infoColorPressed:S,successColor:x,successColorHover:R,successColorPressed:C,warningColor:w,warningColorHover:k,warningColorPressed:F,errorColor:M,errorColorHover:_,errorColorPressed:T,fontWeight:B,buttonColor2:D,buttonColor2Hover:K,buttonColor2Pressed:N,fontWeightStrong:V}=e;return Object.assign(Object.assign({},OP),{heightTiny:t,heightSmall:n,heightMedium:o,heightLarge:r,borderRadiusTiny:i,borderRadiusSmall:i,borderRadiusMedium:i,borderRadiusLarge:i,fontSizeTiny:l,fontSizeSmall:a,fontSizeMedium:s,fontSizeLarge:d,opacityDisabled:c,colorOpacitySecondary:"0.16",colorOpacitySecondaryHover:"0.22",colorOpacitySecondaryPressed:"0.28",colorSecondary:D,colorSecondaryHover:K,colorSecondaryPressed:N,colorTertiary:D,colorTertiaryHover:K,colorTertiaryPressed:N,colorQuaternary:"#0000",colorQuaternaryHover:K,colorQuaternaryPressed:N,color:"#0000",colorHover:"#0000",colorPressed:"#0000",colorFocus:"#0000",colorDisabled:"#0000",textColor:f,textColorTertiary:v,textColorHover:g,textColorPressed:u,textColorFocus:g,textColorDisabled:f,textColorText:f,textColorTextHover:g,textColorTextPressed:u,textColorTextFocus:g,textColorTextDisabled:f,textColorGhost:f,textColorGhostHover:g,textColorGhostPressed:u,textColorGhostFocus:g,textColorGhostDisabled:f,border:`1px solid ${p}`,borderHover:`1px solid ${g}`,borderPressed:`1px solid ${u}`,borderFocus:`1px solid ${g}`,borderDisabled:`1px solid ${p}`,rippleColor:b,colorPrimary:b,colorHoverPrimary:g,colorPressedPrimary:u,colorFocusPrimary:g,colorDisabledPrimary:b,textColorPrimary:m,textColorHoverPrimary:m,textColorPressedPrimary:m,textColorFocusPrimary:m,textColorDisabledPrimary:m,textColorTextPrimary:b,textColorTextHoverPrimary:g,textColorTextPressedPrimary:u,textColorTextFocusPrimary:g,textColorTextDisabledPrimary:f,textColorGhostPrimary:b,textColorGhostHoverPrimary:g,textColorGhostPressedPrimary:u,textColorGhostFocusPrimary:g,textColorGhostDisabledPrimary:b,borderPrimary:`1px solid ${b}`,borderHoverPrimary:`1px solid ${g}`,borderPressedPrimary:`1px solid ${u}`,borderFocusPrimary:`1px solid ${g}`,borderDisabledPrimary:`1px solid ${b}`,rippleColorPrimary:b,colorInfo:y,colorHoverInfo:$,colorPressedInfo:S,colorFocusInfo:$,colorDisabledInfo:y,textColorInfo:m,textColorHoverInfo:m,textColorPressedInfo:m,textColorFocusInfo:m,textColorDisabledInfo:m,textColorTextInfo:y,textColorTextHoverInfo:$,textColorTextPressedInfo:S,textColorTextFocusInfo:$,textColorTextDisabledInfo:f,textColorGhostInfo:y,textColorGhostHoverInfo:$,textColorGhostPressedInfo:S,textColorGhostFocusInfo:$,textColorGhostDisabledInfo:y,borderInfo:`1px solid ${y}`,borderHoverInfo:`1px solid ${$}`,borderPressedInfo:`1px solid ${S}`,borderFocusInfo:`1px solid ${$}`,borderDisabledInfo:`1px solid ${y}`,rippleColorInfo:y,colorSuccess:x,colorHoverSuccess:R,colorPressedSuccess:C,colorFocusSuccess:R,colorDisabledSuccess:x,textColorSuccess:m,textColorHoverSuccess:m,textColorPressedSuccess:m,textColorFocusSuccess:m,textColorDisabledSuccess:m,textColorTextSuccess:x,textColorTextHoverSuccess:R,textColorTextPressedSuccess:C,textColorTextFocusSuccess:R,textColorTextDisabledSuccess:f,textColorGhostSuccess:x,textColorGhostHoverSuccess:R,textColorGhostPressedSuccess:C,textColorGhostFocusSuccess:R,textColorGhostDisabledSuccess:x,borderSuccess:`1px solid ${x}`,borderHoverSuccess:`1px solid ${R}`,borderPressedSuccess:`1px solid ${C}`,borderFocusSuccess:`1px solid ${R}`,borderDisabledSuccess:`1px solid ${x}`,rippleColorSuccess:x,colorWarning:w,colorHoverWarning:k,colorPressedWarning:F,colorFocusWarning:k,colorDisabledWarning:w,textColorWarning:m,textColorHoverWarning:m,textColorPressedWarning:m,textColorFocusWarning:m,textColorDisabledWarning:m,textColorTextWarning:w,textColorTextHoverWarning:k,textColorTextPressedWarning:F,textColorTextFocusWarning:k,textColorTextDisabledWarning:f,textColorGhostWarning:w,textColorGhostHoverWarning:k,textColorGhostPressedWarning:F,textColorGhostFocusWarning:k,textColorGhostDisabledWarning:w,borderWarning:`1px solid ${w}`,borderHoverWarning:`1px solid ${k}`,borderPressedWarning:`1px solid ${F}`,borderFocusWarning:`1px solid ${k}`,borderDisabledWarning:`1px solid ${w}`,rippleColorWarning:w,colorError:M,colorHoverError:_,colorPressedError:T,colorFocusError:_,colorDisabledError:M,textColorError:m,textColorHoverError:m,textColorPressedError:m,textColorFocusError:m,textColorDisabledError:m,textColorTextError:M,textColorTextHoverError:_,textColorTextPressedError:T,textColorTextFocusError:_,textColorTextDisabledError:f,textColorGhostError:M,textColorGhostHoverError:_,textColorGhostPressedError:T,textColorGhostFocusError:_,textColorGhostDisabledError:M,borderError:`1px solid ${M}`,borderHoverError:`1px solid ${_}`,borderPressedError:`1px solid ${T}`,borderFocusError:`1px solid ${_}`,borderDisabledError:`1px solid ${M}`,rippleColorError:M,waveOpacity:"0.6",fontWeight:B,fontWeightStrong:V})}const rc={name:"Button",common:gt,self:EP},MP=I([P("button",` + margin: 0; + font-weight: var(--n-font-weight); + line-height: 1; + font-family: inherit; + padding: var(--n-padding); + height: var(--n-height); + font-size: var(--n-font-size); + border-radius: var(--n-border-radius); + color: var(--n-text-color); + background-color: var(--n-color); + width: var(--n-width); + white-space: nowrap; + outline: none; + position: relative; + z-index: auto; + border: none; + display: inline-flex; + flex-wrap: nowrap; + flex-shrink: 0; + align-items: center; + justify-content: center; + user-select: none; + -webkit-user-select: none; + text-align: center; + cursor: pointer; + text-decoration: none; + transition: + color .3s var(--n-bezier), + background-color .3s var(--n-bezier), + opacity .3s var(--n-bezier), + border-color .3s var(--n-bezier); + `,[H("color",[j("border",{borderColor:"var(--n-border-color)"}),H("disabled",[j("border",{borderColor:"var(--n-border-color-disabled)"})]),dt("disabled",[I("&:focus",[j("state-border",{borderColor:"var(--n-border-color-focus)"})]),I("&:hover",[j("state-border",{borderColor:"var(--n-border-color-hover)"})]),I("&:active",[j("state-border",{borderColor:"var(--n-border-color-pressed)"})]),H("pressed",[j("state-border",{borderColor:"var(--n-border-color-pressed)"})])])]),H("disabled",{backgroundColor:"var(--n-color-disabled)",color:"var(--n-text-color-disabled)"},[j("border",{border:"var(--n-border-disabled)"})]),dt("disabled",[I("&:focus",{backgroundColor:"var(--n-color-focus)",color:"var(--n-text-color-focus)"},[j("state-border",{border:"var(--n-border-focus)"})]),I("&:hover",{backgroundColor:"var(--n-color-hover)",color:"var(--n-text-color-hover)"},[j("state-border",{border:"var(--n-border-hover)"})]),I("&:active",{backgroundColor:"var(--n-color-pressed)",color:"var(--n-text-color-pressed)"},[j("state-border",{border:"var(--n-border-pressed)"})]),H("pressed",{backgroundColor:"var(--n-color-pressed)",color:"var(--n-text-color-pressed)"},[j("state-border",{border:"var(--n-border-pressed)"})])]),H("loading","cursor: wait;"),P("base-wave",` + pointer-events: none; + top: 0; + right: 0; + bottom: 0; + left: 0; + animation-iteration-count: 1; + animation-duration: var(--n-ripple-duration); + animation-timing-function: var(--n-bezier-ease-out), var(--n-bezier-ease-out); + `,[H("active",{zIndex:1,animationName:"button-wave-spread, button-wave-opacity"})]),Do&&"MozBoxSizing"in document.createElement("div").style?I("&::moz-focus-inner",{border:0}):null,j("border, state-border",` + position: absolute; + left: 0; + top: 0; + right: 0; + bottom: 0; + border-radius: inherit; + transition: border-color .3s var(--n-bezier); + pointer-events: none; + `),j("border",` + border: var(--n-border); + `),j("state-border",` + border: var(--n-border); + border-color: #0000; + z-index: 1; + `),j("icon",` + margin: var(--n-icon-margin); + margin-left: 0; + height: var(--n-icon-size); + width: var(--n-icon-size); + max-width: var(--n-icon-size); + font-size: var(--n-icon-size); + position: relative; + flex-shrink: 0; + `,[P("icon-slot",` + height: var(--n-icon-size); + width: var(--n-icon-size); + position: absolute; + left: 0; + top: 50%; + transform: translateY(-50%); + display: flex; + align-items: center; + justify-content: center; + `,[an({top:"50%",originalTransform:"translateY(-50%)"})]),vP()]),j("content",` + display: flex; + align-items: center; + flex-wrap: nowrap; + min-width: 0; + `,[I("~",[j("icon",{margin:"var(--n-icon-margin)",marginRight:0})])]),H("block",` + display: flex; + width: 100%; + `),H("dashed",[j("border, state-border",{borderStyle:"dashed !important"})]),H("disabled",{cursor:"not-allowed",opacity:"var(--n-opacity-disabled)"})]),I("@keyframes button-wave-spread",{from:{boxShadow:"0 0 0.5px 0 var(--n-ripple-color)"},to:{boxShadow:"0 0 0.5px 4.5px var(--n-ripple-color)"}}),I("@keyframes button-wave-opacity",{from:{opacity:"var(--n-wave-opacity)"},to:{opacity:0}})]),BP=Object.assign(Object.assign({},Be.props),{color:String,textColor:String,text:Boolean,block:Boolean,loading:Boolean,disabled:Boolean,circle:Boolean,size:String,ghost:Boolean,round:Boolean,secondary:Boolean,tertiary:Boolean,quaternary:Boolean,strong:Boolean,focusable:{type:Boolean,default:!0},keyboard:{type:Boolean,default:!0},tag:{type:String,default:"button"},type:{type:String,default:"default"},dashed:Boolean,renderIcon:Function,iconPlacement:{type:String,default:"left"},attrType:{type:String,default:"button"},bordered:{type:Boolean,default:!0},onClick:[Function,Array],nativeFocusBehavior:{type:Boolean,default:!Lv},spinProps:Object}),It=pe({name:"Button",props:BP,slots:Object,setup(e){const t=E(null),n=E(null),o=E(!1),r=ot(()=>!e.quaternary&&!e.tertiary&&!e.secondary&&!e.text&&(!e.color||e.ghost||e.dashed)&&e.bordered),i=Ee(FP,{}),{inlineThemeDisabled:l,mergedClsPrefixRef:a,mergedRtlRef:s,mergedComponentPropsRef:d}=Ye(e),{mergedSizeRef:c}=No({},{defaultSize:"medium",mergedSize:x=>{var R,C;const{size:w}=e;if(w)return w;const{size:k}=i;if(k)return k;const{mergedSize:F}=x||{};if(F)return F.value;const M=(C=(R=d?.value)===null||R===void 0?void 0:R.Button)===null||C===void 0?void 0:C.size;return M||"medium"}}),f=O(()=>e.focusable&&!e.disabled),v=x=>{var R;f.value||x.preventDefault(),!e.nativeFocusBehavior&&(x.preventDefault(),!e.disabled&&f.value&&((R=t.value)===null||R===void 0||R.focus({preventScroll:!0})))},g=x=>{var R;if(!e.disabled&&!e.loading){const{onClick:C}=e;C&&me(C,x),e.text||(R=n.value)===null||R===void 0||R.play()}},u=x=>{switch(x.key){case"Enter":if(!e.keyboard)return;o.value=!1}},p=x=>{switch(x.key){case"Enter":if(!e.keyboard||e.loading){x.preventDefault();return}o.value=!0}},b=()=>{o.value=!1},m=Be("Button","-button",MP,rc,e,a),y=Bt("Button",s,a),$=O(()=>{const x=m.value,{common:{cubicBezierEaseInOut:R,cubicBezierEaseOut:C},self:w}=x,{rippleDuration:k,opacityDisabled:F,fontWeight:M,fontWeightStrong:_}=w,T=c.value,{dashed:B,type:D,ghost:K,text:N,color:V,round:ie,circle:he,textColor:J,secondary:re,tertiary:ye,quaternary:Z,strong:le}=e,$e={"--n-font-weight":le?_:M};let ze={"--n-color":"initial","--n-color-hover":"initial","--n-color-pressed":"initial","--n-color-focus":"initial","--n-color-disabled":"initial","--n-ripple-color":"initial","--n-text-color":"initial","--n-text-color-hover":"initial","--n-text-color-pressed":"initial","--n-text-color-focus":"initial","--n-text-color-disabled":"initial"};const Ae=D==="tertiary",Te=D==="default",ne=Ae?"default":D;if(N){const oe=J||V;ze={"--n-color":"#0000","--n-color-hover":"#0000","--n-color-pressed":"#0000","--n-color-focus":"#0000","--n-color-disabled":"#0000","--n-ripple-color":"#0000","--n-text-color":oe||w[de("textColorText",ne)],"--n-text-color-hover":oe?Go(oe):w[de("textColorTextHover",ne)],"--n-text-color-pressed":oe?pl(oe):w[de("textColorTextPressed",ne)],"--n-text-color-focus":oe?Go(oe):w[de("textColorTextHover",ne)],"--n-text-color-disabled":oe||w[de("textColorTextDisabled",ne)]}}else if(K||B){const oe=J||V;ze={"--n-color":"#0000","--n-color-hover":"#0000","--n-color-pressed":"#0000","--n-color-focus":"#0000","--n-color-disabled":"#0000","--n-ripple-color":V||w[de("rippleColor",ne)],"--n-text-color":oe||w[de("textColorGhost",ne)],"--n-text-color-hover":oe?Go(oe):w[de("textColorGhostHover",ne)],"--n-text-color-pressed":oe?pl(oe):w[de("textColorGhostPressed",ne)],"--n-text-color-focus":oe?Go(oe):w[de("textColorGhostHover",ne)],"--n-text-color-disabled":oe||w[de("textColorGhostDisabled",ne)]}}else if(re){const oe=Te?w.textColor:Ae?w.textColorTertiary:w[de("color",ne)],q=V||oe,G=D!=="default"&&D!=="tertiary";ze={"--n-color":G?Ue(q,{alpha:Number(w.colorOpacitySecondary)}):w.colorSecondary,"--n-color-hover":G?Ue(q,{alpha:Number(w.colorOpacitySecondaryHover)}):w.colorSecondaryHover,"--n-color-pressed":G?Ue(q,{alpha:Number(w.colorOpacitySecondaryPressed)}):w.colorSecondaryPressed,"--n-color-focus":G?Ue(q,{alpha:Number(w.colorOpacitySecondaryHover)}):w.colorSecondaryHover,"--n-color-disabled":w.colorSecondary,"--n-ripple-color":"#0000","--n-text-color":q,"--n-text-color-hover":q,"--n-text-color-pressed":q,"--n-text-color-focus":q,"--n-text-color-disabled":q}}else if(ye||Z){const oe=Te?w.textColor:Ae?w.textColorTertiary:w[de("color",ne)],q=V||oe;ye?(ze["--n-color"]=w.colorTertiary,ze["--n-color-hover"]=w.colorTertiaryHover,ze["--n-color-pressed"]=w.colorTertiaryPressed,ze["--n-color-focus"]=w.colorSecondaryHover,ze["--n-color-disabled"]=w.colorTertiary):(ze["--n-color"]=w.colorQuaternary,ze["--n-color-hover"]=w.colorQuaternaryHover,ze["--n-color-pressed"]=w.colorQuaternaryPressed,ze["--n-color-focus"]=w.colorQuaternaryHover,ze["--n-color-disabled"]=w.colorQuaternary),ze["--n-ripple-color"]="#0000",ze["--n-text-color"]=q,ze["--n-text-color-hover"]=q,ze["--n-text-color-pressed"]=q,ze["--n-text-color-focus"]=q,ze["--n-text-color-disabled"]=q}else ze={"--n-color":V||w[de("color",ne)],"--n-color-hover":V?Go(V):w[de("colorHover",ne)],"--n-color-pressed":V?pl(V):w[de("colorPressed",ne)],"--n-color-focus":V?Go(V):w[de("colorFocus",ne)],"--n-color-disabled":V||w[de("colorDisabled",ne)],"--n-ripple-color":V||w[de("rippleColor",ne)],"--n-text-color":J||(V?w.textColorPrimary:Ae?w.textColorTertiary:w[de("textColor",ne)]),"--n-text-color-hover":J||(V?w.textColorHoverPrimary:w[de("textColorHover",ne)]),"--n-text-color-pressed":J||(V?w.textColorPressedPrimary:w[de("textColorPressed",ne)]),"--n-text-color-focus":J||(V?w.textColorFocusPrimary:w[de("textColorFocus",ne)]),"--n-text-color-disabled":J||(V?w.textColorDisabledPrimary:w[de("textColorDisabled",ne)])};let Oe={"--n-border":"initial","--n-border-hover":"initial","--n-border-pressed":"initial","--n-border-focus":"initial","--n-border-disabled":"initial"};N?Oe={"--n-border":"none","--n-border-hover":"none","--n-border-pressed":"none","--n-border-focus":"none","--n-border-disabled":"none"}:Oe={"--n-border":w[de("border",ne)],"--n-border-hover":w[de("borderHover",ne)],"--n-border-pressed":w[de("borderPressed",ne)],"--n-border-focus":w[de("borderFocus",ne)],"--n-border-disabled":w[de("borderDisabled",ne)]};const{[de("height",T)]:z,[de("fontSize",T)]:L,[de("padding",T)]:ee,[de("paddingRound",T)]:se,[de("iconSize",T)]:ae,[de("borderRadius",T)]:Q,[de("iconMargin",T)]:ue,waveOpacity:ve}=w,fe={"--n-width":he&&!N?z:"initial","--n-height":N?"initial":z,"--n-font-size":L,"--n-padding":he||N?"initial":ie?se:ee,"--n-icon-size":ae,"--n-icon-margin":ue,"--n-border-radius":N?"initial":he||ie?z:Q};return Object.assign(Object.assign(Object.assign(Object.assign({"--n-bezier":R,"--n-bezier-ease-out":C,"--n-ripple-duration":k,"--n-opacity-disabled":F,"--n-wave-opacity":ve},$e),ze),Oe),fe)}),S=l?vt("button",O(()=>{let x="";const{dashed:R,type:C,ghost:w,text:k,color:F,round:M,circle:_,textColor:T,secondary:B,tertiary:D,quaternary:K,strong:N}=e;R&&(x+="a"),w&&(x+="b"),k&&(x+="c"),M&&(x+="d"),_&&(x+="e"),B&&(x+="f"),D&&(x+="g"),K&&(x+="h"),N&&(x+="i"),F&&(x+=`j${Al(F)}`),T&&(x+=`k${Al(T)}`);const{value:V}=c;return x+=`l${V[0]}`,x+=`m${C[0]}`,x}),$,e):void 0;return{selfElRef:t,waveElRef:n,mergedClsPrefix:a,mergedFocusable:f,mergedSize:c,showBorder:r,enterPressed:o,rtlEnabled:y,handleMousedown:v,handleKeydown:p,handleBlur:b,handleKeyup:u,handleClick:g,customColorCssVars:O(()=>{const{color:x}=e;if(!x)return null;const R=Go(x);return{"--n-border-color":x,"--n-border-color-hover":R,"--n-border-color-pressed":pl(x),"--n-border-color-focus":R,"--n-border-color-disabled":x}}),cssVars:l?void 0:$,themeClass:S?.themeClass,onRender:S?.onRender}},render(){const{mergedClsPrefix:e,tag:t,onRender:n}=this;n?.();const o=lt(this.$slots.default,r=>r&&h("span",{class:`${e}-button__content`},r));return h(t,{ref:"selfElRef",class:[this.themeClass,`${e}-button`,`${e}-button--${this.type}-type`,`${e}-button--${this.mergedSize}-type`,this.rtlEnabled&&`${e}-button--rtl`,this.disabled&&`${e}-button--disabled`,this.block&&`${e}-button--block`,this.enterPressed&&`${e}-button--pressed`,!this.text&&this.dashed&&`${e}-button--dashed`,this.color&&`${e}-button--color`,this.secondary&&`${e}-button--secondary`,this.loading&&`${e}-button--loading`,this.ghost&&`${e}-button--ghost`],tabindex:this.mergedFocusable?0:-1,type:this.attrType,style:this.cssVars,disabled:this.disabled,onClick:this.handleClick,onBlur:this.handleBlur,onMousedown:this.handleMousedown,onKeyup:this.handleKeyup,onKeydown:this.handleKeydown},this.iconPlacement==="right"&&o,h($v,{width:!0},{default:()=>lt(this.$slots.icon,r=>(this.loading||this.renderIcon||r)&&h("span",{class:`${e}-button__icon`,style:{margin:Mr(this.$slots.default)?"0":""}},h(vr,null,{default:()=>this.loading?h(gr,Object.assign({clsPrefix:e,key:"loading",class:`${e}-icon-slot`,strokeWidth:20},this.spinProps)):h("div",{key:"icon",class:`${e}-icon-slot`,role:"none"},this.renderIcon?this.renderIcon():r)})))}),this.iconPlacement==="left"&&o,this.text?null:h(bP,{ref:"waveElRef",clsPrefix:e}),this.showBorder?h("div",{"aria-hidden":!0,class:`${e}-button__border`,style:this.customColorCssVars}):null,this.showBorder?h("div",{"aria-hidden":!0,class:`${e}-button__state-border`,style:this.customColorCssVars}):null)}}),AP={paddingSmall:"12px 16px 12px",paddingMedium:"19px 24px 20px",paddingLarge:"23px 32px 24px",paddingHuge:"27px 40px 28px",titleFontSizeSmall:"16px",titleFontSizeMedium:"18px",titleFontSizeLarge:"18px",titleFontSizeHuge:"18px",closeIconSize:"18px",closeSize:"22px"};function IP(e){const{primaryColor:t,borderRadius:n,lineHeight:o,fontSize:r,cardColor:i,textColor2:l,textColor1:a,dividerColor:s,fontWeightStrong:d,closeIconColor:c,closeIconColorHover:f,closeIconColorPressed:v,closeColorHover:g,closeColorPressed:u,modalColor:p,boxShadow1:b,popoverColor:m,actionColor:y}=e;return Object.assign(Object.assign({},AP),{lineHeight:o,color:i,colorModal:p,colorPopover:m,colorTarget:t,colorEmbedded:y,colorEmbeddedModal:y,colorEmbeddedPopover:y,textColor:l,titleTextColor:a,borderColor:s,actionColor:y,titleFontWeight:d,closeColorHover:g,closeColorPressed:u,closeBorderRadius:n,closeIconColor:c,closeIconColorHover:f,closeIconColorPressed:v,fontSizeSmall:r,fontSizeMedium:r,fontSizeLarge:r,fontSizeHuge:r,boxShadow:b,borderRadius:n})}const Wv={name:"Card",common:gt,self:IP},Pf=P("card-content",` + flex: 1; + min-width: 0; + box-sizing: border-box; + padding: 0 var(--n-padding-left) var(--n-padding-bottom) var(--n-padding-left); + font-size: var(--n-font-size); +`),LP=I([P("card",` + font-size: var(--n-font-size); + line-height: var(--n-line-height); + display: flex; + flex-direction: column; + width: 100%; + box-sizing: border-box; + position: relative; + border-radius: var(--n-border-radius); + background-color: var(--n-color); + color: var(--n-text-color); + word-break: break-word; + transition: + color .3s var(--n-bezier), + background-color .3s var(--n-bezier), + box-shadow .3s var(--n-bezier), + border-color .3s var(--n-bezier); + `,[mp({background:"var(--n-color-modal)"}),H("hoverable",[I("&:hover","box-shadow: var(--n-box-shadow);")]),H("content-segmented",[I(">",[P("card-content",` + padding-top: var(--n-padding-bottom); + `),j("content-scrollbar",[I(">",[P("scrollbar-container",[I(">",[P("card-content",` + padding-top: var(--n-padding-bottom); + `)])])])])])]),H("content-soft-segmented",[I(">",[P("card-content",` + margin: 0 var(--n-padding-left); + padding: var(--n-padding-bottom) 0; + `),j("content-scrollbar",[I(">",[P("scrollbar-container",[I(">",[P("card-content",` + margin: 0 var(--n-padding-left); + padding: var(--n-padding-bottom) 0; + `)])])])])])]),H("footer-segmented",[I(">",[j("footer",` + padding-top: var(--n-padding-bottom); + `)])]),H("footer-soft-segmented",[I(">",[j("footer",` + padding: var(--n-padding-bottom) 0; + margin: 0 var(--n-padding-left); + `)])]),I(">",[P("card-header",` + box-sizing: border-box; + display: flex; + align-items: center; + font-size: var(--n-title-font-size); + padding: + var(--n-padding-top) + var(--n-padding-left) + var(--n-padding-bottom) + var(--n-padding-left); + `,[j("main",` + font-weight: var(--n-title-font-weight); + transition: color .3s var(--n-bezier); + flex: 1; + min-width: 0; + color: var(--n-title-text-color); + `),j("extra",` + display: flex; + align-items: center; + font-size: var(--n-font-size); + font-weight: 400; + transition: color .3s var(--n-bezier); + color: var(--n-text-color); + `),j("close",` + margin: 0 0 0 8px; + transition: + background-color .3s var(--n-bezier), + color .3s var(--n-bezier); + `)]),j("action",` + box-sizing: border-box; + transition: + background-color .3s var(--n-bezier), + border-color .3s var(--n-bezier); + background-clip: padding-box; + background-color: var(--n-action-color); + `),Pf,P("card-content",[I("&:first-child",` + padding-top: var(--n-padding-bottom); + `)]),j("content-scrollbar",` + display: flex; + flex-direction: column; + `,[I(">",[P("scrollbar-container",[I(">",[Pf])])]),I("&:first-child >",[P("scrollbar-container",[I(">",[P("card-content",` + padding-top: var(--n-padding-bottom); + `)])])])]),j("footer",` + box-sizing: border-box; + padding: 0 var(--n-padding-left) var(--n-padding-bottom) var(--n-padding-left); + font-size: var(--n-font-size); + `,[I("&:first-child",` + padding-top: var(--n-padding-bottom); + `)]),j("action",` + background-color: var(--n-action-color); + padding: var(--n-padding-bottom) var(--n-padding-left); + border-bottom-left-radius: var(--n-border-radius); + border-bottom-right-radius: var(--n-border-radius); + `)]),P("card-cover",` + overflow: hidden; + width: 100%; + border-radius: var(--n-border-radius) var(--n-border-radius) 0 0; + `,[I("img",` + display: block; + width: 100%; + `)]),H("bordered",` + border: 1px solid var(--n-border-color); + `,[I("&:target","border-color: var(--n-color-target);")]),H("action-segmented",[I(">",[j("action",[I("&:not(:first-child)",` + border-top: 1px solid var(--n-border-color); + `)])])]),H("content-segmented, content-soft-segmented",[I(">",[P("card-content",` + transition: border-color 0.3s var(--n-bezier); + `,[I("&:not(:first-child)",` + border-top: 1px solid var(--n-border-color); + `)]),j("content-scrollbar",` + transition: border-color 0.3s var(--n-bezier); + `,[I("&:not(:first-child)",` + border-top: 1px solid var(--n-border-color); + `)])])]),H("footer-segmented, footer-soft-segmented",[I(">",[j("footer",` + transition: border-color 0.3s var(--n-bezier); + `,[I("&:not(:first-child)",` + border-top: 1px solid var(--n-border-color); + `)])])]),H("embedded",` + background-color: var(--n-color-embedded); + `)]),sa(P("card",` + background: var(--n-color-modal); + `,[H("embedded",` + background-color: var(--n-color-embedded-modal); + `)])),$d(P("card",` + background: var(--n-color-popover); + `,[H("embedded",` + background-color: var(--n-color-embedded-popover); + `)]))]),ic={title:[String,Function],contentClass:String,contentStyle:[Object,String],contentScrollable:Boolean,headerClass:String,headerStyle:[Object,String],headerExtraClass:String,headerExtraStyle:[Object,String],footerClass:String,footerStyle:[Object,String],embedded:Boolean,segmented:{type:[Boolean,Object],default:!1},size:String,bordered:{type:Boolean,default:!0},closable:Boolean,hoverable:Boolean,role:String,onClose:[Function,Array],tag:{type:String,default:"div"},cover:Function,content:[String,Function],footer:Function,action:Function,headerExtra:Function,closeFocusable:Boolean},DP=Gi(ic),HP=Object.assign(Object.assign({},Be.props),ic),co=pe({name:"Card",props:HP,slots:Object,setup(e){const t=()=>{const{onClose:f}=e;f&&me(f)},{inlineThemeDisabled:n,mergedClsPrefixRef:o,mergedRtlRef:r,mergedComponentPropsRef:i}=Ye(e),l=Be("Card","-card",LP,Wv,e,o),a=Bt("Card",r,o),s=O(()=>{var f,v;return e.size||((v=(f=i?.value)===null||f===void 0?void 0:f.Card)===null||v===void 0?void 0:v.size)||"medium"}),d=O(()=>{const f=s.value,{self:{color:v,colorModal:g,colorTarget:u,textColor:p,titleTextColor:b,titleFontWeight:m,borderColor:y,actionColor:$,borderRadius:S,lineHeight:x,closeIconColor:R,closeIconColorHover:C,closeIconColorPressed:w,closeColorHover:k,closeColorPressed:F,closeBorderRadius:M,closeIconSize:_,closeSize:T,boxShadow:B,colorPopover:D,colorEmbedded:K,colorEmbeddedModal:N,colorEmbeddedPopover:V,[de("padding",f)]:ie,[de("fontSize",f)]:he,[de("titleFontSize",f)]:J},common:{cubicBezierEaseInOut:re}}=l.value,{top:ye,left:Z,bottom:le}=Ft(ie);return{"--n-bezier":re,"--n-border-radius":S,"--n-color":v,"--n-color-modal":g,"--n-color-popover":D,"--n-color-embedded":K,"--n-color-embedded-modal":N,"--n-color-embedded-popover":V,"--n-color-target":u,"--n-text-color":p,"--n-line-height":x,"--n-action-color":$,"--n-title-text-color":b,"--n-title-font-weight":m,"--n-close-icon-color":R,"--n-close-icon-color-hover":C,"--n-close-icon-color-pressed":w,"--n-close-color-hover":k,"--n-close-color-pressed":F,"--n-border-color":y,"--n-box-shadow":B,"--n-padding-top":ye,"--n-padding-bottom":le,"--n-padding-left":Z,"--n-font-size":he,"--n-title-font-size":J,"--n-close-size":T,"--n-close-icon-size":_,"--n-close-border-radius":M}}),c=n?vt("card",O(()=>s.value[0]),d,e):void 0;return{rtlEnabled:a,mergedClsPrefix:o,mergedTheme:l,handleCloseClick:t,cssVars:n?void 0:d,themeClass:c?.themeClass,onRender:c?.onRender}},render(){const{segmented:e,bordered:t,hoverable:n,mergedClsPrefix:o,rtlEnabled:r,onRender:i,embedded:l,tag:a,$slots:s}=this;return i?.(),h(a,{class:[`${o}-card`,this.themeClass,l&&`${o}-card--embedded`,{[`${o}-card--rtl`]:r,[`${o}-card--content-scrollable`]:this.contentScrollable,[`${o}-card--content${typeof e!="boolean"&&e.content==="soft"?"-soft":""}-segmented`]:e===!0||e!==!1&&e.content,[`${o}-card--footer${typeof e!="boolean"&&e.footer==="soft"?"-soft":""}-segmented`]:e===!0||e!==!1&&e.footer,[`${o}-card--action-segmented`]:e===!0||e!==!1&&e.action,[`${o}-card--bordered`]:t,[`${o}-card--hoverable`]:n}],style:this.cssVars,role:this.role},lt(s.cover,d=>{const c=this.cover?Rn([this.cover()]):d;return c&&h("div",{class:`${o}-card-cover`,role:"none"},c)}),lt(s.header,d=>{const{title:c}=this,f=c?Rn(typeof c=="function"?[c()]:[c]):d;return f||this.closable?h("div",{class:[`${o}-card-header`,this.headerClass],style:this.headerStyle,role:"heading"},h("div",{class:`${o}-card-header__main`,role:"heading"},f),lt(s["header-extra"],v=>{const g=this.headerExtra?Rn([this.headerExtra()]):v;return g&&h("div",{class:[`${o}-card-header__extra`,this.headerExtraClass],style:this.headerExtraStyle},g)}),this.closable&&h(Kr,{clsPrefix:o,class:`${o}-card-header__close`,onClick:this.handleCloseClick,focusable:this.closeFocusable,absolute:!0})):null}),lt(s.default,d=>{const{content:c}=this,f=c?Rn(typeof c=="function"?[c()]:[c]):d;return f?this.contentScrollable?h(bo,{class:`${o}-card__content-scrollbar`,contentClass:[`${o}-card-content`,this.contentClass],contentStyle:this.contentStyle},f):h("div",{class:[`${o}-card-content`,this.contentClass],style:this.contentStyle,role:"none"},f):null}),lt(s.footer,d=>{const c=this.footer?Rn([this.footer()]):d;return c&&h("div",{class:[`${o}-card__footer`,this.footerClass],style:this.footerStyle,role:"none"},c)}),lt(s.action,d=>{const c=this.action?Rn([this.action()]):d;return c&&h("div",{class:`${o}-card__action`,role:"none"},c)}))}}),NP={sizeSmall:"14px",sizeMedium:"16px",sizeLarge:"18px",labelPadding:"0 8px",labelFontWeight:"400"};function jP(e){const{baseColor:t,inputColorDisabled:n,cardColor:o,modalColor:r,popoverColor:i,textColorDisabled:l,borderColor:a,primaryColor:s,textColor2:d,fontSizeSmall:c,fontSizeMedium:f,fontSizeLarge:v,borderRadiusSmall:g,lineHeight:u}=e;return Object.assign(Object.assign({},NP),{labelLineHeight:u,fontSizeSmall:c,fontSizeMedium:f,fontSizeLarge:v,borderRadius:g,color:t,colorChecked:s,colorDisabled:n,colorDisabledChecked:n,colorTableHeader:o,colorTableHeaderModal:r,colorTableHeaderPopover:i,checkMarkColor:t,checkMarkColorDisabled:l,checkMarkColorDisabledChecked:l,border:`1px solid ${a}`,borderDisabled:`1px solid ${a}`,borderDisabledChecked:`1px solid ${a}`,borderChecked:`1px solid ${s}`,borderFocus:`1px solid ${s}`,boxShadowFocus:`0 0 0 2px ${Ue(s,{alpha:.3})}`,textColor:d,textColorDisabled:l})}const Vv={name:"Checkbox",common:gt,self:jP},Kv="n-checkbox-group",WP={min:Number,max:Number,size:String,value:Array,defaultValue:{type:Array,default:null},disabled:{type:Boolean,default:void 0},"onUpdate:value":[Function,Array],onUpdateValue:[Function,Array],onChange:[Function,Array]},VP=pe({name:"CheckboxGroup",props:WP,setup(e){const{mergedClsPrefixRef:t}=Ye(e),n=No(e),{mergedSizeRef:o,mergedDisabledRef:r}=n,i=E(e.defaultValue),l=O(()=>e.value),a=qt(l,i),s=O(()=>{var f;return((f=a.value)===null||f===void 0?void 0:f.length)||0}),d=O(()=>Array.isArray(a.value)?new Set(a.value):new Set);function c(f,v){const{nTriggerFormInput:g,nTriggerFormChange:u}=n,{onChange:p,"onUpdate:value":b,onUpdateValue:m}=e;if(Array.isArray(a.value)){const y=Array.from(a.value),$=y.findIndex(S=>S===v);f?~$||(y.push(v),m&&me(m,y,{actionType:"check",value:v}),b&&me(b,y,{actionType:"check",value:v}),g(),u(),i.value=y,p&&me(p,y)):~$&&(y.splice($,1),m&&me(m,y,{actionType:"uncheck",value:v}),b&&me(b,y,{actionType:"uncheck",value:v}),p&&me(p,y),i.value=y,g(),u())}else f?(m&&me(m,[v],{actionType:"check",value:v}),b&&me(b,[v],{actionType:"check",value:v}),p&&me(p,[v]),i.value=[v],g(),u()):(m&&me(m,[],{actionType:"uncheck",value:v}),b&&me(b,[],{actionType:"uncheck",value:v}),p&&me(p,[]),i.value=[],g(),u())}return qe(Kv,{checkedCountRef:s,maxRef:we(e,"max"),minRef:we(e,"min"),valueSetRef:d,disabledRef:r,mergedSizeRef:o,toggleCheckbox:c}),{mergedClsPrefix:t}},render(){return h("div",{class:`${this.mergedClsPrefix}-checkbox-group`,role:"group"},this.$slots)}}),KP=()=>h("svg",{viewBox:"0 0 64 64",class:"check-icon"},h("path",{d:"M50.42,16.76L22.34,39.45l-8.1-11.46c-1.12-1.58-3.3-1.96-4.88-0.84c-1.58,1.12-1.95,3.3-0.84,4.88l10.26,14.51 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var(--n-merged-color-table); + `)]),H("checked",[P("checkbox-box",` + background-color: var(--n-color-checked); + `,[P("checkbox-icon",[I(".check-icon",` + opacity: 1; + transform: scale(1); + `)])])]),H("indeterminate",[P("checkbox-box",[P("checkbox-icon",[I(".check-icon",` + opacity: 0; + transform: scale(.5); + `),I(".line-icon",` + opacity: 1; + transform: scale(1); + `)])])]),H("checked, indeterminate",[I("&:focus:not(:active)",[P("checkbox-box",[j("border",` + border: var(--n-border-checked); + box-shadow: var(--n-box-shadow-focus); + `)])]),P("checkbox-box",` + background-color: var(--n-color-checked); + border-left: 0; + border-top: 0; + `,[j("border",{border:"var(--n-border-checked)"})])]),H("disabled",{cursor:"not-allowed"},[H("checked",[P("checkbox-box",` + background-color: var(--n-color-disabled-checked); + `,[j("border",{border:"var(--n-border-disabled-checked)"}),P("checkbox-icon",[I(".check-icon, .line-icon",{fill:"var(--n-check-mark-color-disabled-checked)"})])])]),P("checkbox-box",` + background-color: var(--n-color-disabled); + `,[j("border",` + border: var(--n-border-disabled); + `),P("checkbox-icon",[I(".check-icon, .line-icon",` + fill: var(--n-check-mark-color-disabled); + `)])]),j("label",` + color: var(--n-text-color-disabled); + `)]),P("checkbox-box-wrapper",` + position: relative; + width: var(--n-size); + flex-shrink: 0; + flex-grow: 0; + user-select: none; + -webkit-user-select: none; + `),P("checkbox-box",` + position: absolute; + left: 0; + top: 50%; + transform: translateY(-50%); + height: var(--n-size); + width: var(--n-size); + display: inline-block; + box-sizing: border-box; + border-radius: var(--n-border-radius); + background-color: var(--n-color); + transition: background-color 0.3s var(--n-bezier); + `,[j("border",` + transition: + border-color .3s var(--n-bezier), + box-shadow .3s var(--n-bezier); + border-radius: inherit; + position: absolute; + left: 0; + right: 0; + top: 0; + bottom: 0; + border: var(--n-border); + `),P("checkbox-icon",` + display: flex; + align-items: center; + justify-content: center; + position: absolute; + left: 1px; + right: 1px; + top: 1px; + bottom: 1px; + `,[I(".check-icon, .line-icon",` + width: 100%; + fill: var(--n-check-mark-color); + opacity: 0; + transform: scale(0.5); + transform-origin: center; + transition: + fill 0.3s var(--n-bezier), + transform 0.3s var(--n-bezier), + opacity 0.3s var(--n-bezier), + border-color 0.3s var(--n-bezier); + `),an({left:"1px",top:"1px"})])]),j("label",` + color: var(--n-text-color); + transition: color .3s var(--n-bezier); + user-select: none; + -webkit-user-select: none; + padding: var(--n-label-padding); + font-weight: var(--n-label-font-weight); + `,[I("&:empty",{display:"none"})])]),sa(P("checkbox",` + --n-merged-color-table: var(--n-color-table-modal); + `)),$d(P("checkbox",` + --n-merged-color-table: var(--n-color-table-popover); + 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pointer; + user-select: none; + -webkit-user-select: none; + display: flex; + align-items: center; + justify-content: center; + box-sizing: border-box; + min-width: var(--n-item-size); + height: var(--n-item-size); + padding: var(--n-item-padding); + background-color: var(--n-item-color); + color: var(--n-item-text-color); + border-radius: var(--n-item-border-radius); + border: var(--n-item-border); + fill: var(--n-button-icon-color); + transition: + color .3s var(--n-bezier), + border-color .3s var(--n-bezier), + background-color .3s var(--n-bezier), + fill .3s var(--n-bezier); + `,[H("button",` + background: var(--n-button-color); + color: var(--n-button-icon-color); + border: var(--n-button-border); + padding: 0; + `,[P("base-icon",` + font-size: var(--n-button-icon-size); + `)]),dt("disabled",[H("hover",_f,zf),I("&:hover",_f,zf),I("&:active",` + background: var(--n-item-color-pressed); + color: var(--n-item-text-color-pressed); + border: var(--n-item-border-pressed); + `,[H("button",` + background: var(--n-button-color-pressed); + border: var(--n-button-border-pressed); + color: var(--n-button-icon-color-pressed); + `)]),H("active",` + background: var(--n-item-color-active); + color: var(--n-item-text-color-active); + border: var(--n-item-border-active); + `,[I("&:hover",` + background: var(--n-item-color-active-hover); + `)])]),H("disabled",` + cursor: not-allowed; + color: var(--n-item-text-color-disabled); + `,[H("active, button",` + background-color: var(--n-item-color-disabled); + border: var(--n-item-border-disabled); + `)])]),H("disabled",` + cursor: not-allowed; + `,[P("pagination-quick-jumper",` + color: var(--n-jumper-text-color-disabled); + `)]),H("simple",` + display: flex; + align-items: center; + flex-wrap: nowrap; + `,[P("pagination-quick-jumper",[P("input",` + margin: 0; + `)])])]);function Yv(e){var t;if(!e)return 10;const{defaultPageSize:n}=e;if(n!==void 0)return n;const o=(t=e.pageSizes)===null||t===void 0?void 0:t[0];return typeof 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${t}`,color:o,colorDisabled:i,colorActive:"#0000",textColor:l,textColorDisabled:r,dotColorActive:n,dotColorDisabled:t,buttonBorderColor:t,buttonBorderColorActive:n,buttonBorderColorHover:t,buttonColor:o,buttonColorActive:o,buttonTextColor:l,buttonTextColorActive:n,buttonTextColorHover:n,opacityDisabled:a,buttonBoxShadowFocus:`inset 0 0 0 1px ${n}, 0 0 0 2px ${Ue(n,{alpha:.3})}`,buttonBoxShadowHover:"inset 0 0 0 1px #0000",buttonBoxShadow:"inset 0 0 0 1px #0000",buttonBorderRadius:s})}const dc={name:"Radio",common:gt,self:v$},g$={thPaddingSmall:"8px",thPaddingMedium:"12px",thPaddingLarge:"12px",tdPaddingSmall:"8px",tdPaddingMedium:"12px",tdPaddingLarge:"12px",sorterSize:"15px",resizableContainerSize:"8px",resizableSize:"2px",filterSize:"15px",paginationMargin:"12px 0 0 0",emptyPadding:"48px 0",actionPadding:"8px 12px",actionButtonMargin:"0 8px 0 0"};function b$(e){const{cardColor:t,modalColor:n,popoverColor:o,textColor2:r,textColor1:i,tableHeaderColor:l,tableColorHover:a,iconColor:s,primaryColor:d,fontWeightStrong:c,borderRadius:f,lineHeight:v,fontSizeSmall:g,fontSizeMedium:u,fontSizeLarge:p,dividerColor:b,heightSmall:m,opacityDisabled:y,tableColorStriped:$}=e;return Object.assign(Object.assign({},g$),{actionDividerColor:b,lineHeight:v,borderRadius:f,fontSizeSmall:g,fontSizeMedium:u,fontSizeLarge:p,borderColor:rt(t,b),tdColorHover:rt(t,a),tdColorSorting:rt(t,a),tdColorStriped:rt(t,$),thColor:rt(t,l),thColorHover:rt(rt(t,l),a),thColorSorting:rt(rt(t,l),a),tdColor:t,tdTextColor:r,thTextColor:i,thFontWeight:c,thButtonColorHover:a,thIconColor:s,thIconColorActive:d,borderColorModal:rt(n,b),tdColorHoverModal:rt(n,a),tdColorSortingModal:rt(n,a),tdColorStripedModal:rt(n,$),thColorModal:rt(n,l),thColorHoverModal:rt(rt(n,l),a),thColorSortingModal:rt(rt(n,l),a),tdColorModal:n,borderColorPopover:rt(o,b),tdColorHoverPopover:rt(o,a),tdColorSortingPopover:rt(o,a),tdColorStripedPopover:rt(o,$),thColorPopover:rt(o,l),thColorHoverPopover:rt(rt(o,l),a),thColorSortingPopover:rt(rt(o,l),a),tdColorPopover:o,boxShadowBefore:"inset -12px 0 8px -12px rgba(0, 0, 0, .18)",boxShadowAfter:"inset 12px 0 8px -12px rgba(0, 0, 0, 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0},striped:Boolean,scrollX:[Number,String],defaultCheckedRowKeys:{type:Array,default:()=>[]},checkedRowKeys:Array,singleLine:{type:Boolean,default:!0},singleColumn:Boolean,size:String,remote:Boolean,defaultExpandedRowKeys:{type:Array,default:[]},defaultExpandAll:Boolean,expandedRowKeys:Array,stickyExpandedRows:Boolean,virtualScroll:Boolean,virtualScrollX:Boolean,virtualScrollHeader:Boolean,headerHeight:{type:Number,default:28},heightForRow:Function,minRowHeight:{type:Number,default:28},tableLayout:{type:String,default:"auto"},allowCheckingNotLoaded:Boolean,cascade:{type:Boolean,default:!0},childrenKey:{type:String,default:"children"},indent:{type:Number,default:16},flexHeight:Boolean,summaryPlacement:{type:String,default:"bottom"},paginationBehaviorOnFilter:{type:String,default:"current"},filterIconPopoverProps:Object,scrollbarProps:Object,renderCell:Function,renderExpandIcon:Function,spinProps:Object,getCsvCell:Function,getCsvHeader:Function,onLoad:Function,"onUpdate:page":[Function,Array],onUpdatePage:[Function,Array],"onUpdate:pageSize":[Function,Array],onUpdatePageSize:[Function,Array],"onUpdate:sorter":[Function,Array],onUpdateSorter:[Function,Array],"onUpdate:filters":[Function,Array],onUpdateFilters:[Function,Array],"onUpdate:checkedRowKeys":[Function,Array],onUpdateCheckedRowKeys:[Function,Array],"onUpdate:expandedRowKeys":[Function,Array],onUpdateExpandedRowKeys:[Function,Array],onScroll:Function,onPageChange:[Function,Array],onPageSizeChange:[Function,Array],onSorterChange:[Function,Array],onFiltersChange:[Function,Array],onCheckedRowKeysChange:[Function,Array]}),En="n-data-table",eg=40,tg=40;function Ff(e){if(e.type==="selection")return e.width===void 0?eg:Pt(e.width);if(e.type==="expand")return e.width===void 0?tg:Pt(e.width);if(!("children"in e))return typeof e.width=="string"?Pt(e.width):e.width}function x$(e){var t,n;if(e.type==="selection")return Gt((t=e.width)!==null&&t!==void 0?t:eg);if(e.type==="expand")return Gt((n=e.width)!==null&&n!==void 0?n:tg);if(!("children"in e))return Gt(e.width)}function Sn(e){return e.type==="selection"?"__n_selection__":e.type==="expand"?"__n_expand__":e.key}function Of(e){return e&&(typeof e=="object"?Object.assign({},e):e)}function w$(e){return e==="ascend"?1:e==="descend"?-1:0}function C$(e,t,n){return n!==void 0&&(e=Math.min(e,typeof n=="number"?n:Number.parseFloat(n))),t!==void 0&&(e=Math.max(e,typeof t=="number"?t:Number.parseFloat(t))),e}function S$(e,t){if(t!==void 0)return{width:t,minWidth:t,maxWidth:t};const n=x$(e),{minWidth:o,maxWidth:r}=e;return{width:n,minWidth:Gt(o)||n,maxWidth:Gt(r)}}function R$(e,t,n){return typeof 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r=e.filter(a=>a.type!=="expand"&&a.type!=="selection"&&a.allowExport!==!1),i=r.map(a=>o?o(a):a.title).join(","),l=t.map(a=>r.map(s=>n?n(a[s.key],a,s):P$(a[s.key])).join(","));return[i,...l].join(` +`)}const _$=pe({name:"DataTableBodyCheckbox",props:{rowKey:{type:[String,Number],required:!0},disabled:{type:Boolean,required:!0},onUpdateChecked:{type:Function,required:!0}},setup(e){const{mergedCheckedRowKeySetRef:t,mergedInderminateRowKeySetRef:n}=Ee(En);return()=>{const{rowKey:o}=e;return h(lc,{privateInsideTable:!0,disabled:e.disabled,indeterminate:n.value.has(o),checked:t.value.has(o),onUpdateChecked:e.onUpdateChecked})}}}),z$=P("radio",` + line-height: var(--n-label-line-height); + outline: none; + position: relative; + user-select: none; + -webkit-user-select: none; + display: inline-flex; + align-items: flex-start; + flex-wrap: nowrap; + font-size: var(--n-font-size); + word-break: break-word; +`,[H("checked",[j("dot",` + background-color: var(--n-color-active); + `)]),j("dot-wrapper",` + position: relative; + flex-shrink: 0; + flex-grow: 0; + width: var(--n-radio-size); + `),P("radio-input",` + position: absolute; + border: 0; + width: 0; + height: 0; + opacity: 0; + margin: 0; + `),j("dot",` + position: absolute; + top: 50%; + left: 0; + transform: translateY(-50%); + height: var(--n-radio-size); + width: var(--n-radio-size); + background: var(--n-color); + box-shadow: var(--n-box-shadow); + border-radius: 50%; + transition: + background-color .3s var(--n-bezier), + box-shadow .3s var(--n-bezier); + `,[I("&::before",` + content: ""; + opacity: 0; + position: absolute; + left: 4px; + top: 4px; + height: calc(100% - 8px); + width: calc(100% - 8px); + border-radius: 50%; + transform: scale(.8); + background: var(--n-dot-color-active); + transition: + opacity .3s var(--n-bezier), + background-color .3s var(--n-bezier), + transform .3s var(--n-bezier); + `),H("checked",{boxShadow:"var(--n-box-shadow-active)"},[I("&::before",` + opacity: 1; + transform: scale(1); + `)])]),j("label",` + color: var(--n-text-color); + padding: var(--n-label-padding); + font-weight: var(--n-label-font-weight); + display: inline-block; + transition: color .3s var(--n-bezier); + `),dt("disabled",` + cursor: pointer; + `,[I("&:hover",[j("dot",{boxShadow:"var(--n-box-shadow-hover)"})]),H("focus",[I("&:not(:active)",[j("dot",{boxShadow:"var(--n-box-shadow-focus)"})])])]),H("disabled",` + cursor: not-allowed; + `,[j("dot",{boxShadow:"var(--n-box-shadow-disabled)",backgroundColor:"var(--n-color-disabled)"},[I("&::before",{backgroundColor:"var(--n-dot-color-disabled)"}),H("checked",` + opacity: 1; + `)]),j("label",{color:"var(--n-text-color-disabled)"}),P("radio-input",` + cursor: not-allowed; + `)])]),T$={name:String,value:{type:[String,Number,Boolean],default:"on"},checked:{type:Boolean,default:void 0},defaultChecked:Boolean,disabled:{type:Boolean,default:void 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var(--n-bezier)"),H("desc",[P("base-icon",` + transform: rotate(0deg); + `)]),H("asc",[P("base-icon",` + transform: rotate(-180deg); + `)]),H("asc, desc",` + color: var(--n-th-icon-color-active); + `)]),P("data-table-resize-button",` + width: var(--n-resizable-container-size); + position: absolute; + top: 0; + right: calc(var(--n-resizable-container-size) / 2); + bottom: 0; + cursor: col-resize; + user-select: none; + `,[I("&::after",` + width: var(--n-resizable-size); + height: 50%; + position: absolute; + top: 50%; + left: calc(var(--n-resizable-container-size) / 2); + bottom: 0; + background-color: var(--n-merged-border-color); + transform: translateY(-50%); + transition: background-color .3s var(--n-bezier); + z-index: 1; + content: ''; + `),H("active",[I("&::after",` + background-color: var(--n-th-icon-color-active); + `)]),I("&:hover::after",` + background-color: var(--n-th-icon-color-active); + `)]),P("data-table-filter",` + position: absolute; + z-index: auto; + right: 0; + width: 36px; + top: 0; + bottom: 0; + cursor: pointer; + display: flex; + justify-content: center; + align-items: center; + transition: + background-color .3s var(--n-bezier), + color .3s var(--n-bezier); + font-size: var(--n-filter-size); + color: var(--n-th-icon-color); + `,[I("&:hover",` + background-color: var(--n-th-button-color-hover); + `),H("show",` + background-color: var(--n-th-button-color-hover); + `),H("active",` + background-color: var(--n-th-button-color-hover); + color: var(--n-th-icon-color-active); + `)])]),P("data-table-td",` + padding: var(--n-td-padding); + text-align: start; + box-sizing: border-box; + border: none; + background-color: var(--n-merged-td-color); + color: var(--n-td-text-color); + border-bottom: 1px solid var(--n-merged-border-color); + transition: + box-shadow .3s var(--n-bezier), + background-color .3s var(--n-bezier), + border-color .3s var(--n-bezier), + color .3s var(--n-bezier); + `,[H("expand",[P("data-table-expand-trigger",` + margin-right: 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absolute; + right: 0; + top: 0; + margin: var(--n-close-margin); + transition: + background-color .3s var(--n-bezier), + color .3s var(--n-bezier); + z-index: 1; + `),j("content",` + font-size: var(--n-font-size); + margin: var(--n-content-margin); + position: relative; + word-break: break-word; + `,[H("last","margin-bottom: 0;")]),j("action",` + display: flex; + justify-content: flex-end; + `,[I("> *:not(:last-child)",` + margin-right: var(--n-action-space); + `)]),j("icon",` + font-size: var(--n-icon-size); + transition: color .3s var(--n-bezier); + `),j("title",` + transition: color .3s var(--n-bezier); + display: flex; + align-items: center; + font-size: var(--n-title-font-size); + font-weight: var(--n-title-font-weight); + color: var(--n-title-text-color); + `),P("dialog-icon-container",` + display: flex; + justify-content: center; + `)]),sa(P("dialog",` + width: 446px; + max-width: calc(100vw - 32px); + `)),P("dialog",[mp(` + width: 446px; + max-width: calc(100vw - 32px); + `)])]),B2={default:()=>h(Wl,null),info:()=>h(Wl,null),success:()=>h(Jd,null),warning:()=>h(Qd,null),error:()=>h(Zd,null)},yg=pe({name:"Dialog",alias:["NimbusConfirmCard","Confirm"],props:Object.assign(Object.assign({},Be.props),ya),slots:Object,setup(e){const{mergedComponentPropsRef:t,mergedClsPrefixRef:n,inlineThemeDisabled:o,mergedRtlRef:r}=Ye(e),i=Bt("Dialog",r,n),l=O(()=>{var g,u;const{iconPlacement:p}=e;return p||((u=(g=t?.value)===null||g===void 0?void 0:g.Dialog)===null||u===void 0?void 0:u.iconPlacement)||"left"});function a(g){const{onPositiveClick:u}=e;u&&u(g)}function s(g){const{onNegativeClick:u}=e;u&&u(g)}function d(){const{onClose:g}=e;g&&g()}const 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ra(a),{stopDrag:a,startDrag:l,draggableRef:o,draggableClassRef:r}}const hc=Object.assign(Object.assign({},ic),ya),j2=Gi(hc),W2=pe({name:"ModalBody",inheritAttrs:!1,slots:Object,props:Object.assign(Object.assign({show:{type:Boolean,required:!0},preset:String,displayDirective:{type:String,required:!0},trapFocus:{type:Boolean,default:!0},autoFocus:{type:Boolean,default:!0},blockScroll:Boolean,draggable:{type:[Boolean,Object],default:!1},maskHidden:Boolean},hc),{renderMask:Function,onClickoutside:Function,onBeforeLeave:{type:Function,required:!0},onAfterLeave:{type:Function,required:!0},onPositiveClick:{type:Function,required:!0},onNegativeClick:{type:Function,required:!0},onClose:{type:Function,required:!0},onAfterEnter:Function,onEsc:Function}),setup(e){const t=E(null),n=E(null),o=E(e.show),r=E(null),i=E(null),l=Ee($p);let 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`)])]),wg=Object.assign(Object.assign(Object.assign(Object.assign({},Be.props),{show:Boolean,showMask:{type:Boolean,default:!0},maskClosable:{type:Boolean,default:!0},preset:String,to:[String,Object],displayDirective:{type:String,default:"if"},transformOrigin:{type:String,default:"mouse"},zIndex:Number,autoFocus:{type:Boolean,default:!0},trapFocus:{type:Boolean,default:!0},closeOnEsc:{type:Boolean,default:!0},blockScroll:{type:Boolean,default:!0}}),hc),{draggable:[Boolean,Object],onEsc:Function,"onUpdate:show":[Function,Array],onUpdateShow:[Function,Array],onAfterEnter:Function,onBeforeLeave:Function,onAfterLeave:Function,onClose:Function,onPositiveClick:Function,onNegativeClick:Function,onMaskClick:Function,internalDialog:Boolean,internalModal:Boolean,internalAppear:{type:Boolean,default:void 0},overlayStyle:[String,Object],onBeforeHide:Function,onAfterHide:Function,onHide:Function,unstableShowMask:{type:Boolean,default:void 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Object.assign(Object.assign({},n_),{closeBorderRadius:g,textColor:t,textColorInfo:t,textColorSuccess:t,textColorError:t,textColorWarning:t,textColorLoading:t,color:d,colorInfo:d,colorSuccess:d,colorError:d,colorWarning:d,colorLoading:d,boxShadow:c,boxShadowInfo:c,boxShadowSuccess:c,boxShadowError:c,boxShadowWarning:c,boxShadowLoading:c,iconColor:t,iconColorInfo:i,iconColorSuccess:l,iconColorWarning:s,iconColorError:a,iconColorLoading:f,closeColorHover:u,closeColorPressed:p,closeIconColor:n,closeIconColorHover:o,closeIconColorPressed:r,closeColorHoverInfo:u,closeColorPressedInfo:p,closeIconColorInfo:n,closeIconColorHoverInfo:o,closeIconColorPressedInfo:r,closeColorHoverSuccess:u,closeColorPressedSuccess:p,closeIconColorSuccess:n,closeIconColorHoverSuccess:o,closeIconColorPressedSuccess:r,closeColorHoverError:u,closeColorPressedError:p,closeIconColorError:n,closeIconColorHoverError:o,closeIconColorPressedError:r,closeColorHoverWarning:u,closeColorPressedWarning:p,closeIconColorWarning:n,closeIconColorHoverWarning:o,closeIconColorPressedWarning:r,closeColorHoverLoading:u,closeColorPressedLoading:p,closeIconColorLoading:n,closeIconColorHoverLoading:o,closeIconColorPressedLoading:r,loadingColor:f,lineHeight:v,borderRadius:g,border:"0"})}const r_={common:gt,self:o_},Pg={icon:Function,type:{type:String,default:"info"},content:[String,Number,Function],showIcon:{type:Boolean,default:!0},closable:Boolean,keepAliveOnHover:Boolean,spinProps:Object,onClose:Function,onMouseenter:Function,onMouseleave:Function},i_=I([P("message-wrapper",` + margin: var(--n-margin); + z-index: 0; + transform-origin: top center; + display: flex; + `,[xP({overflow:"visible",originalTransition:"transform .3s var(--n-bezier)",enterToProps:{transform:"scale(1)"},leaveToProps:{transform:"scale(0.85)"}})]),P("message",` + box-sizing: border-box; + display: flex; + align-items: center; + transition: + color .3s var(--n-bezier), + box-shadow .3s var(--n-bezier), + background-color .3s var(--n-bezier), + opacity .3s var(--n-bezier), + transform .3s var(--n-bezier), + margin-bottom .3s var(--n-bezier); + padding: var(--n-padding); + border-radius: var(--n-border-radius); + border: var(--n-border); + flex-wrap: nowrap; + overflow: hidden; + max-width: var(--n-max-width); + color: var(--n-text-color); + background-color: var(--n-color); + box-shadow: var(--n-box-shadow); + `,[j("content",` + display: inline-block; + line-height: var(--n-line-height); + font-size: var(--n-font-size); + `),j("icon",` + position: relative; + margin: var(--n-icon-margin); + height: var(--n-icon-size); + width: var(--n-icon-size); + font-size: var(--n-icon-size); + flex-shrink: 0; + `,[["default","info","success","warning","error","loading"].map(e=>H(`${e}-type`,[I("> *",` + color: var(--n-icon-color-${e}); + transition: color .3s var(--n-bezier); + `)])),I("> *",` + position: absolute; + left: 0; + top: 0; + right: 0; + bottom: 0; + `,[an()])]),j("close",` + margin: var(--n-close-margin); + transition: + background-color .3s var(--n-bezier), + color .3s var(--n-bezier); + flex-shrink: 0; + `,[I("&:hover",` + color: var(--n-close-icon-color-hover); + `),I("&:active",` + color: var(--n-close-icon-color-pressed); + `)])]),P("message-container",` + z-index: 6000; + position: fixed; + height: 0; + overflow: visible; + display: flex; + flex-direction: column; + align-items: center; + `,[H("top",` + top: 12px; + left: 0; + right: 0; + `),H("top-left",` + top: 12px; + left: 12px; + right: 0; + align-items: flex-start; + `),H("top-right",` + top: 12px; + left: 0; + right: 12px; + align-items: flex-end; + `),H("bottom",` + bottom: 4px; + left: 0; + right: 0; + justify-content: flex-end; + `),H("bottom-left",` + bottom: 4px; + left: 12px; + right: 0; + justify-content: flex-end; + align-items: flex-start; + `),H("bottom-right",` + bottom: 4px; + left: 0; + right: 12px; + justify-content: flex-end; + align-items: flex-end; + 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qe(xg,i),qe(L2,{clickedRef:Td(64),clickedPositionRef:zd()}),qe(D2,e),Object.assign(Object.assign({},i),{modalList:e,modalInstRefs:t,handleAfterLeave:o})},render(){var e,t;return h(nt,null,[this.modalList.map(n=>{var o;return h(h_,dr(n,["destroy","render"],{to:(o=n.to)!==null&&o!==void 0?o:this.to,ref:r=>{r===null?delete this.modalInstRefs[`n-modal-${n.key}`]:this.modalInstRefs[`n-modal-${n.key}`]=r},internalKey:n.key,onInternalAfterLeave:this.handleAfterLeave}),{default:n.render})}),(t=(e=this.$slots).default)===null||t===void 0?void 0:t.call(e)])}}),g_={closeMargin:"16px 12px",closeSize:"20px",closeIconSize:"16px",width:"365px",padding:"16px",titleFontSize:"16px",metaFontSize:"12px",descriptionFontSize:"12px"};function b_(e){const{textColor2:t,successColor:n,infoColor:o,warningColor:r,errorColor:i,popoverColor:l,closeIconColor:a,closeIconColorHover:s,closeIconColorPressed:d,closeColorHover:c,closeColorPressed:f,textColor1:v,textColor3:g,borderRadius:u,fontWeightStrong:p,boxShadow2:b,lineHeight:m,fontSize:y}=e;return Object.assign(Object.assign({},g_),{borderRadius:u,lineHeight:m,fontSize:y,headerFontWeight:p,iconColor:t,iconColorSuccess:n,iconColorInfo:o,iconColorWarning:r,iconColorError:i,color:l,textColor:t,closeIconColor:a,closeIconColorHover:s,closeIconColorPressed:d,closeBorderRadius:u,closeColorHover:c,closeColorPressed:f,headerTextColor:v,descriptionTextColor:g,actionTextColor:t,boxShadow:b})}const m_={name:"Notification",common:gt,peers:{Scrollbar:jo},self:b_},wa="n-notification-provider",y_=pe({name:"NotificationContainer",props:{scrollable:{type:Boolean,required:!0},placement:{type:String,required:!0}},setup(){const{mergedThemeRef:e,mergedClsPrefixRef:t,wipTransitionCountRef:n}=Ee(wa),o=E(null);return en(()=>{var r,i;n.value>0?(r=o?.value)===null||r===void 0||r.classList.add("transitioning"):(i=o?.value)===null||i===void 0||i.classList.remove("transitioning")}),{selfRef:o,mergedTheme:e,mergedClsPrefix:t,transitioning:n}},render(){const{$slots:e,scrollable:t,mergedClsPrefix:n,mergedTheme:o,placement:r}=this;return h("div",{ref:"selfRef",class:[`${n}-notification-container`,t&&`${n}-notification-container--scrollable`,`${n}-notification-container--${r}`]},t?h(bo,{theme:o.peers.Scrollbar,themeOverrides:o.peerOverrides.Scrollbar,contentStyle:{overflow:"hidden"}},e):e)}}),x_={info:()=>h(Wl,null),success:()=>h(Jd,null),warning:()=>h(Qd,null),error:()=>h(Zd,null),default:()=>null},pc={closable:{type:Boolean,default:!0},type:{type:String,default:"default"},avatar:Function,title:[String,Function],description:[String,Function],content:[String,Function],meta:[String,Function],action:[String,Function],onClose:{type:Function,required:!0},keepAliveOnHover:Boolean,onMouseenter:Function,onMouseleave:Function},w_=Gi(pc),C_=pe({name:"Notification",props:pc,setup(e){const{mergedClsPrefixRef:t,mergedThemeRef:n,props:o}=Ee(wa),{inlineThemeDisabled:r,mergedRtlRef:i}=Ye(),l=Bt("Notification",i,t),a=O(()=>{const{type:d}=e,{self:{color:c,textColor:f,closeIconColor:v,closeIconColorHover:g,closeIconColorPressed:u,headerTextColor:p,descriptionTextColor:b,actionTextColor:m,borderRadius:y,headerFontWeight:$,boxShadow:S,lineHeight:x,fontSize:R,closeMargin:C,closeSize:w,width:k,padding:F,closeIconSize:M,closeBorderRadius:_,closeColorHover:T,closeColorPressed:B,titleFontSize:D,metaFontSize:K,descriptionFontSize:N,[de("iconColor",d)]:V},common:{cubicBezierEaseOut:ie,cubicBezierEaseIn:he,cubicBezierEaseInOut:J}}=n.value,{left:re,right:ye,top:Z,bottom:le}=Ft(F);return{"--n-color":c,"--n-font-size":R,"--n-text-color":f,"--n-description-text-color":b,"--n-action-text-color":m,"--n-title-text-color":p,"--n-title-font-weight":$,"--n-bezier":J,"--n-bezier-ease-out":ie,"--n-bezier-ease-in":he,"--n-border-radius":y,"--n-box-shadow":S,"--n-close-border-radius":_,"--n-close-color-hover":T,"--n-close-color-pressed":B,"--n-close-icon-color":v,"--n-close-icon-color-hover":g,"--n-close-icon-color-pressed":u,"--n-line-height":x,"--n-icon-color":V,"--n-close-margin":C,"--n-close-size":w,"--n-close-icon-size":M,"--n-width":k,"--n-padding-left":re,"--n-padding-right":ye,"--n-padding-top":Z,"--n-padding-bottom":le,"--n-title-font-size":D,"--n-meta-font-size":K,"--n-description-font-size":N}}),s=r?vt("notification",O(()=>e.type[0]),a,o):void 0;return{mergedClsPrefix:t,showAvatar:O(()=>e.avatar||e.type!=="default"),handleCloseClick(){e.onClose()},rtlEnabled:l,cssVars:r?void 0:a,themeClass:s?.themeClass,onRender:s?.onRender}},render(){var e;const{mergedClsPrefix:t}=this;return(e=this.onRender)===null||e===void 0||e.call(this),h("div",{class:[`${t}-notification-wrapper`,this.themeClass],onMouseenter:this.onMouseenter,onMouseleave:this.onMouseleave,style:this.cssVars},h("div",{class:[`${t}-notification`,this.rtlEnabled&&`${t}-notification--rtl`,this.themeClass,{[`${t}-notification--closable`]:this.closable,[`${t}-notification--show-avatar`]:this.showAvatar}],style:this.cssVars},this.showAvatar?h("div",{class:`${t}-notification__avatar`},this.avatar?wt(this.avatar):this.type!=="default"?h(kt,{clsPrefix:t},{default:()=>x_[this.type]()}):null):null,this.closable?h(Kr,{clsPrefix:t,class:`${t}-notification__close`,onClick:this.handleCloseClick}):null,h("div",{ref:"bodyRef",class:`${t}-notification-main`},this.title?h("div",{class:`${t}-notification-main__header`},wt(this.title)):null,this.description?h("div",{class:`${t}-notification-main__description`},wt(this.description)):null,this.content?h("pre",{class:`${t}-notification-main__content`},wt(this.content)):null,this.meta||this.action?h("div",{class:`${t}-notification-main-footer`},this.meta?h("div",{class:`${t}-notification-main-footer__meta`},wt(this.meta)):null,this.action?h("div",{class:`${t}-notification-main-footer__action`},wt(this.action)):null):null)))}}),S_=Object.assign(Object.assign({},pc),{duration:Number,onClose:Function,onLeave:Function,onAfterEnter:Function,onAfterLeave:Function,onHide:Function,onAfterShow:Function,onAfterHide:Function}),R_=pe({name:"NotificationEnvironment",props:Object.assign(Object.assign({},S_),{internalKey:{type:String,required:!0},onInternalAfterLeave:{type:Function,required:!0}}),setup(e){const{wipTransitionCountRef:t}=Ee(wa),n=E(!0);let o=null;function r(){n.value=!1,o&&window.clearTimeout(o)}function i(u){t.value++,Rt(()=>{u.style.height=`${u.offsetHeight}px`,u.style.maxHeight="0",u.style.transition="none",u.offsetHeight,u.style.transition="",u.style.maxHeight=u.style.height})}function l(u){t.value--,u.style.height="",u.style.maxHeight="";const{onAfterEnter:p,onAfterShow:b}=e;p&&p(),b&&b()}function a(u){t.value++,u.style.maxHeight=`${u.offsetHeight}px`,u.style.height=`${u.offsetHeight}px`,u.offsetHeight}function s(u){const{onHide:p}=e;p&&p(),u.style.maxHeight="0",u.offsetHeight}function d(){t.value--;const{onAfterLeave:u,onInternalAfterLeave:p,onAfterHide:b,internalKey:m}=e;u&&u(),p(m),b&&b()}function c(){const{duration:u}=e;u&&(o=window.setTimeout(r,u))}function f(u){u.currentTarget===u.target&&o!==null&&(window.clearTimeout(o),o=null)}function v(u){u.currentTarget===u.target&&c()}function g(){const{onClose:u}=e;u?Promise.resolve(u()).then(p=>{p!==!1&&r()}):r()}return Ct(()=>{e.duration&&(o=window.setTimeout(r,e.duration))}),{show:n,hide:r,handleClose:g,handleAfterLeave:d,handleLeave:s,handleBeforeLeave:a,handleAfterEnter:l,handleBeforeEnter:i,handleMouseenter:f,handleMouseleave:v}},render(){return h(pn,{name:"notification-transition",appear:!0,onBeforeEnter:this.handleBeforeEnter,onAfterEnter:this.handleAfterEnter,onBeforeLeave:this.handleBeforeLeave,onLeave:this.handleLeave,onAfterLeave:this.handleAfterLeave},{default:()=>this.show?h(C_,Object.assign({},Eo(this.$props,w_),{onClose:this.handleClose,onMouseenter:this.duration&&this.keepAliveOnHover?this.handleMouseenter:void 0,onMouseleave:this.duration&&this.keepAliveOnHover?this.handleMouseleave:void 0})):null})}}),k_=I([P("notification-container",` + z-index: 4000; + position: fixed; + overflow: visible; + display: flex; + flex-direction: column; + align-items: flex-end; + `,[I(">",[P("scrollbar",` + width: initial; + overflow: visible; + height: -moz-fit-content !important; + height: fit-content !important; + max-height: 100vh !important; + `,[I(">",[P("scrollbar-container",` + height: -moz-fit-content !important; + height: fit-content !important; + max-height: 100vh !important; + `,[P("scrollbar-content",` + padding-top: 12px; + padding-bottom: 33px; + `)])])])]),H("top, top-right, top-left",` + top: 12px; + `,[I("&.transitioning >",[P("scrollbar",[I(">",[P("scrollbar-container",` + min-height: 100vh !important; + `)])])])]),H("bottom, bottom-right, bottom-left",` + bottom: 12px; + `,[I(">",[P("scrollbar",[I(">",[P("scrollbar-container",[P("scrollbar-content",` + padding-bottom: 12px; + `)])])])]),P("notification-wrapper",` + display: flex; + align-items: flex-end; + margin-bottom: 0; + margin-top: 12px; + `)]),H("top, bottom",` + left: 50%; + transform: translateX(-50%); + `,[P("notification-wrapper",[I("&.notification-transition-enter-from, &.notification-transition-leave-to",` + transform: scale(0.85); + `),I("&.notification-transition-leave-from, &.notification-transition-enter-to",` + transform: scale(1); + `)])]),H("top",[P("notification-wrapper",` + transform-origin: top center; + `)]),H("bottom",[P("notification-wrapper",` + transform-origin: bottom center; + `)]),H("top-right, bottom-right",[P("notification",` + margin-left: 28px; + margin-right: 16px; + `)]),H("top-left, bottom-left",[P("notification",` + margin-left: 16px; + margin-right: 28px; + `)]),H("top-right",` + right: 0; + `,[ml("top-right")]),H("top-left",` + left: 0; + `,[ml("top-left")]),H("bottom-right",` + right: 0; + `,[ml("bottom-right")]),H("bottom-left",` + left: 0; + `,[ml("bottom-left")]),H("scrollable",[H("top-right",` + top: 0; + `),H("top-left",` + top: 0; + `),H("bottom-right",` + bottom: 0; + `),H("bottom-left",` + bottom: 0; + `)]),P("notification-wrapper",` + margin-bottom: 12px; + `,[I("&.notification-transition-enter-from, &.notification-transition-leave-to",` + opacity: 0; + margin-top: 0 !important; + margin-bottom: 0 !important; + `),I("&.notification-transition-leave-from, &.notification-transition-enter-to",` + opacity: 1; + `),I("&.notification-transition-leave-active",` + transition: + background-color .3s var(--n-bezier), + color .3s var(--n-bezier), + opacity .3s var(--n-bezier), + transform .3s var(--n-bezier-ease-in), + max-height .3s var(--n-bezier), + margin-top .3s linear, + margin-bottom .3s linear, + box-shadow .3s var(--n-bezier); + `),I("&.notification-transition-enter-active",` + transition: + background-color .3s var(--n-bezier), + color .3s var(--n-bezier), + opacity .3s var(--n-bezier), + transform .3s var(--n-bezier-ease-out), + max-height .3s var(--n-bezier), + margin-top .3s linear, + margin-bottom .3s linear, + box-shadow .3s var(--n-bezier); + `)]),P("notification",` + background-color: var(--n-color); + color: var(--n-text-color); + transition: + background-color .3s var(--n-bezier), + color .3s var(--n-bezier), + opacity .3s var(--n-bezier), + box-shadow .3s var(--n-bezier); + font-family: inherit; + font-size: var(--n-font-size); + font-weight: 400; + position: relative; + display: flex; + overflow: hidden; + flex-shrink: 0; + padding-left: var(--n-padding-left); + padding-right: var(--n-padding-right); + width: var(--n-width); + max-width: calc(100vw - 16px - 16px); + border-radius: var(--n-border-radius); + box-shadow: var(--n-box-shadow); + box-sizing: border-box; + opacity: 1; + `,[j("avatar",[P("icon",` + color: var(--n-icon-color); + `),P("base-icon",` + color: var(--n-icon-color); + `)]),H("show-avatar",[P("notification-main",` + margin-left: 40px; + width: calc(100% - 40px); + `)]),H("closable",[P("notification-main",[I("> *:first-child",` + padding-right: 20px; + `)]),j("close",` + position: absolute; + top: 0; + right: 0; + margin: var(--n-close-margin); + transition: + background-color .3s var(--n-bezier), + color .3s var(--n-bezier); + `)]),j("avatar",` + position: absolute; + top: var(--n-padding-top); + left: var(--n-padding-left); + width: 28px; + height: 28px; + font-size: 28px; + display: flex; + align-items: center; + justify-content: center; + `,[P("icon","transition: color .3s var(--n-bezier);")]),P("notification-main",` + padding-top: var(--n-padding-top); + padding-bottom: var(--n-padding-bottom); + box-sizing: border-box; + display: flex; + flex-direction: column; + margin-left: 8px; + width: calc(100% - 8px); + `,[P("notification-main-footer",` + display: flex; + align-items: center; + justify-content: space-between; + margin-top: 12px; + `,[j("meta",` + font-size: var(--n-meta-font-size); + transition: color .3s var(--n-bezier-ease-out); + color: var(--n-description-text-color); + `),j("action",` + cursor: pointer; + transition: color .3s var(--n-bezier-ease-out); + color: var(--n-action-text-color); + `)]),j("header",` + font-weight: var(--n-title-font-weight); + font-size: var(--n-title-font-size); + transition: color .3s var(--n-bezier-ease-out); + color: var(--n-title-text-color); + `),j("description",` + margin-top: 8px; + font-size: var(--n-description-font-size); + white-space: pre-wrap; + word-wrap: break-word; + transition: color .3s var(--n-bezier-ease-out); + color: var(--n-description-text-color); + `),j("content",` + line-height: var(--n-line-height); + margin: 12px 0 0 0; + font-family: inherit; + white-space: pre-wrap; + word-wrap: break-word; + transition: color .3s var(--n-bezier-ease-out); + color: var(--n-text-color); + `,[I("&:first-child","margin: 0;")])])])])]);function ml(e){const n=e.split("-")[1]==="left"?"calc(-100%)":"calc(100%)";return P("notification-wrapper",[I("&.notification-transition-enter-from, &.notification-transition-leave-to",` + transform: translate(${n}, 0); + `),I("&.notification-transition-leave-from, &.notification-transition-enter-to",` + transform: translate(0, 0); + `)])}const $g="n-notification-api",P_=Object.assign(Object.assign({},Be.props),{containerClass:String,containerStyle:[String,Object],to:[String,Object],scrollable:{type:Boolean,default:!0},max:Number,placement:{type:String,default:"top-right"},keepAliveOnHover:Boolean}),$_=pe({name:"NotificationProvider",props:P_,setup(e){const{mergedClsPrefixRef:t}=Ye(e),n=E([]),o={},r=new Set;function i(g){const u=ar(),p=()=>{r.add(u),o[u]&&o[u].hide()},b=_n(Object.assign(Object.assign({},g),{key:u,destroy:p,hide:p,deactivate:p})),{max:m}=e;if(m&&n.value.length-r.size>=m){let y=!1,$=0;for(const S of n.value){if(!r.has(S.key)){o[S.key]&&(S.destroy(),y=!0);break}$++}y||n.value.splice($,1)}return n.value.push(b),b}const l=["info","success","warning","error"].map(g=>u=>i(Object.assign(Object.assign({},u),{type:g})));function a(g){r.delete(g),n.value.splice(n.value.findIndex(u=>u.key===g),1)}const s=Be("Notification","-notification",k_,m_,e,t),d={create:i,info:l[0],success:l[1],warning:l[2],error:l[3],open:f,destroyAll:v},c=E(0);qe($g,d),qe(wa,{props:e,mergedClsPrefixRef:t,mergedThemeRef:s,wipTransitionCountRef:c});function f(g){return i(g)}function v(){Object.values(n.value).forEach(g=>{g.hide()})}return Object.assign({mergedClsPrefix:t,notificationList:n,notificationRefs:o,handleAfterLeave:a},d)},render(){var e,t,n;const{placement:o}=this;return h(nt,null,(t=(e=this.$slots).default)===null||t===void 0?void 0:t.call(e),this.notificationList.length?h(ea,{to:(n=this.to)!==null&&n!==void 0?n:"body"},h(y_,{class:this.containerClass,style:this.containerStyle,scrollable:this.scrollable&&o!=="top"&&o!=="bottom",placement:o},{default:()=>this.notificationList.map(r=>h(R_,Object.assign({ref:i=>{const l=r.key;i===null?delete this.notificationRefs[l]:this.notificationRefs[l]=i}},dr(r,["destroy","hide","deactivate"]),{internalKey:r.key,onInternalAfterLeave:this.handleAfterLeave,keepAliveOnHover:r.keepAliveOnHover===void 0?this.keepAliveOnHover:r.keepAliveOnHover})))})):null)}});function __(){const e=Ee($g,null);return e===null&&sr("use-notification","No outer `n-notification-provider` found."),e}const z_=pe({name:"InjectionExtractor",props:{onSetup:Function},setup(e,{slots:t}){var n;return(n=e.onSetup)===null||n===void 0||n.call(e),()=>{var o;return(o=t.default)===null||o===void 0?void 0:o.call(t)}}}),T_={message:f_,notification:__,loadingBar:t_,dialog:F2,modal:H2};function F_({providersAndProps:e,configProviderProps:t}){let n=up(r);const o={app:n};function r(){return h(Uv,ge(t),{default:()=>e.map(({type:a,Provider:s,props:d})=>h(s,ge(d),{default:()=>h(z_,{onSetup:()=>o[a]=T_[a]()})}))})}let i;return Do&&(i=document.createElement("div"),document.body.appendChild(i),n.mount(i)),Object.assign({unmount:()=>{var a;if(n===null||i===null){Zn("discrete","unmount call no need because discrete app has been unmounted");return}n.unmount(),(a=i.parentNode)===null||a===void 0||a.removeChild(i),i=null,n=null}},o)}function O_(e,{configProviderProps:t,messageProviderProps:n,dialogProviderProps:o,notificationProviderProps:r,loadingBarProviderProps:i,modalProviderProps:l}={}){const a=[];return e.forEach(d=>{switch(d){case"message":a.push({type:d,Provider:u_,props:n});break;case"notification":a.push({type:d,Provider:$_,props:r});break;case"dialog":a.push({type:d,Provider:q2,props:o});break;case"loadingBar":a.push({type:d,Provider:e_,props:i});break;case"modal":a.push({type:d,Provider:v_,props:l})}}),F_({providersAndProps:a,configProviderProps:t})}const E_={gapSmall:"4px 8px",gapMedium:"8px 12px",gapLarge:"12px 16px"};function M_(){return E_}const B_={self:M_};let xs;function A_(){if(!Do)return!0;if(xs===void 0){const e=document.createElement("div");e.style.display="flex",e.style.flexDirection="column",e.style.rowGap="1px",e.appendChild(document.createElement("div")),e.appendChild(document.createElement("div")),document.body.appendChild(e);const t=e.scrollHeight===1;return document.body.removeChild(e),xs=t}return xs}const I_=Object.assign(Object.assign({},Be.props),{align:String,justify:{type:String,default:"start"},inline:Boolean,vertical:Boolean,reverse:Boolean,size:[String,Number,Array],wrapItem:{type:Boolean,default:!0},itemClass:String,itemStyle:[String,Object],wrap:{type:Boolean,default:!0},internalUseGap:{type:Boolean,default:void 0}}),vc=pe({name:"Space",props:I_,setup(e){const{mergedClsPrefixRef:t,mergedRtlRef:n,mergedComponentPropsRef:o}=Ye(e),r=O(()=>{var a,s;return e.size||((s=(a=o?.value)===null||a===void 0?void 0:a.Space)===null||s===void 0?void 0:s.size)||"medium"}),i=Be("Space","-space",void 0,B_,e,t),l=Bt("Space",n,t);return{useGap:A_(),rtlEnabled:l,mergedClsPrefix:t,margin:O(()=>{const a=r.value;if(Array.isArray(a))return{horizontal:a[0],vertical:a[1]};if(typeof a=="number")return{horizontal:a,vertical:a};const{self:{[de("gap",a)]:s}}=i.value,{row:d,col:c}=ey(s);return{horizontal:Pt(c),vertical:Pt(d)}})}},render(){const{vertical:e,reverse:t,align:n,inline:o,justify:r,itemClass:i,itemStyle:l,margin:a,wrap:s,mergedClsPrefix:d,rtlEnabled:c,useGap:f,wrapItem:v,internalUseGap:g}=this,u=Un(Dd(this),!1);if(!u.length)return null;const p=`${a.horizontal}px`,b=`${a.horizontal/2}px`,m=`${a.vertical}px`,y=`${a.vertical/2}px`,$=u.length-1,S=r.startsWith("space-");return h("div",{role:"none",class:[`${d}-space`,c&&`${d}-space--rtl`],style:{display:o?"inline-flex":"flex",flexDirection:e&&!t?"column":e&&t?"column-reverse":!e&&t?"row-reverse":"row",justifyContent:["start","end"].includes(r)?`flex-${r}`:r,flexWrap:!s||e?"nowrap":"wrap",marginTop:f||e?"":`-${y}`,marginBottom:f||e?"":`-${y}`,alignItems:n,gap:f?`${a.vertical}px ${a.horizontal}px`:""}},!v&&(f||g)?u:u.map((x,R)=>x.type===$t?x:h("div",{role:"none",class:i,style:[l,{maxWidth:"100%"},f?"":e?{marginBottom:R!==$?m:""}:c?{marginLeft:S?r==="space-between"&&R===$?"":b:R!==$?p:"",marginRight:S?r==="space-between"&&R===0?"":b:"",paddingTop:y,paddingBottom:y}:{marginRight:S?r==="space-between"&&R===$?"":b:R!==$?p:"",marginLeft:S?r==="space-between"&&R===0?"":b:"",paddingTop:y,paddingBottom:y}]},x)))}});function L_(e){const{baseColor:t,textColor2:n,bodyColor:o,cardColor:r,dividerColor:i,actionColor:l,scrollbarColor:a,scrollbarColorHover:s,invertedColor:d}=e;return{textColor:n,textColorInverted:"#FFF",color:o,colorEmbedded:l,headerColor:r,headerColorInverted:d,footerColor:l,footerColorInverted:d,headerBorderColor:i,headerBorderColorInverted:d,footerBorderColor:i,footerBorderColorInverted:d,siderBorderColor:i,siderBorderColorInverted:d,siderColor:r,siderColorInverted:d,siderToggleButtonBorder:`1px solid ${i}`,siderToggleButtonColor:t,siderToggleButtonIconColor:n,siderToggleButtonIconColorInverted:n,siderToggleBarColor:rt(o,a),siderToggleBarColorHover:rt(o,s),__invertScrollbar:"true"}}const _g={name:"Layout",common:gt,peers:{Scrollbar:jo},self:L_},D_={buttonHeightSmall:"14px",buttonHeightMedium:"18px",buttonHeightLarge:"22px",buttonWidthSmall:"14px",buttonWidthMedium:"18px",buttonWidthLarge:"22px",buttonWidthPressedSmall:"20px",buttonWidthPressedMedium:"24px",buttonWidthPressedLarge:"28px",railHeightSmall:"18px",railHeightMedium:"22px",railHeightLarge:"26px",railWidthSmall:"32px",railWidthMedium:"40px",railWidthLarge:"48px"};function H_(e){const{primaryColor:t,opacityDisabled:n,borderRadius:o,textColor3:r}=e;return Object.assign(Object.assign({},D_),{iconColor:r,textColor:"white",loadingColor:t,opacityDisabled:n,railColor:"rgba(0, 0, 0, .14)",railColorActive:t,buttonBoxShadow:"0 1px 4px 0 rgba(0, 0, 0, 0.3), inset 0 0 1px 0 rgba(0, 0, 0, 0.05)",buttonColor:"#FFF",railBorderRadiusSmall:o,railBorderRadiusMedium:o,railBorderRadiusLarge:o,buttonBorderRadiusSmall:o,buttonBorderRadiusMedium:o,buttonBorderRadiusLarge:o,boxShadowFocus:`0 0 0 2px ${Ue(t,{alpha:.2})}`})}const N_={common:gt,self:H_},j_={tabFontSizeSmall:"14px",tabFontSizeMedium:"14px",tabFontSizeLarge:"16px",tabGapSmallLine:"36px",tabGapMediumLine:"36px",tabGapLargeLine:"36px",tabGapSmallLineVertical:"8px",tabGapMediumLineVertical:"8px",tabGapLargeLineVertical:"8px",tabPaddingSmallLine:"6px 0",tabPaddingMediumLine:"10px 0",tabPaddingLargeLine:"14px 0",tabPaddingVerticalSmallLine:"6px 12px",tabPaddingVerticalMediumLine:"8px 16px",tabPaddingVerticalLargeLine:"10px 20px",tabGapSmallBar:"36px",tabGapMediumBar:"36px",tabGapLargeBar:"36px",tabGapSmallBarVertical:"8px",tabGapMediumBarVertical:"8px",tabGapLargeBarVertical:"8px",tabPaddingSmallBar:"4px 0",tabPaddingMediumBar:"6px 0",tabPaddingLargeBar:"10px 0",tabPaddingVerticalSmallBar:"6px 12px",tabPaddingVerticalMediumBar:"8px 16px",tabPaddingVerticalLargeBar:"10px 20px",tabGapSmallCard:"4px",tabGapMediumCard:"4px",tabGapLargeCard:"4px",tabGapSmallCardVertical:"4px",tabGapMediumCardVertical:"4px",tabGapLargeCardVertical:"4px",tabPaddingSmallCard:"8px 16px",tabPaddingMediumCard:"10px 20px",tabPaddingLargeCard:"12px 24px",tabPaddingSmallSegment:"4px 0",tabPaddingMediumSegment:"6px 0",tabPaddingLargeSegment:"8px 0",tabPaddingVerticalLargeSegment:"0 8px",tabPaddingVerticalSmallCard:"8px 12px",tabPaddingVerticalMediumCard:"10px 16px",tabPaddingVerticalLargeCard:"12px 20px",tabPaddingVerticalSmallSegment:"0 4px",tabPaddingVerticalMediumSegment:"0 6px",tabGapSmallSegment:"0",tabGapMediumSegment:"0",tabGapLargeSegment:"0",tabGapSmallSegmentVertical:"0",tabGapMediumSegmentVertical:"0",tabGapLargeSegmentVertical:"0",panePaddingSmall:"8px 0 0 0",panePaddingMedium:"12px 0 0 0",panePaddingLarge:"16px 0 0 0",closeSize:"18px",closeIconSize:"14px"};function W_(e){const{textColor2:t,primaryColor:n,textColorDisabled:o,closeIconColor:r,closeIconColorHover:i,closeIconColorPressed:l,closeColorHover:a,closeColorPressed:s,tabColor:d,baseColor:c,dividerColor:f,fontWeight:v,textColor1:g,borderRadius:u,fontSize:p,fontWeightStrong:b}=e;return Object.assign(Object.assign({},j_),{colorSegment:d,tabFontSizeCard:p,tabTextColorLine:g,tabTextColorActiveLine:n,tabTextColorHoverLine:n,tabTextColorDisabledLine:o,tabTextColorSegment:g,tabTextColorActiveSegment:t,tabTextColorHoverSegment:t,tabTextColorDisabledSegment:o,tabTextColorBar:g,tabTextColorActiveBar:n,tabTextColorHoverBar:n,tabTextColorDisabledBar:o,tabTextColorCard:g,tabTextColorHoverCard:g,tabTextColorActiveCard:n,tabTextColorDisabledCard:o,barColor:n,closeIconColor:r,closeIconColorHover:i,closeIconColorPressed:l,closeColorHover:a,closeColorPressed:s,closeBorderRadius:u,tabColor:d,tabColorSegment:c,tabBorderColor:f,tabFontWeightActive:v,tabFontWeight:v,tabBorderRadius:u,paneTextColor:t,fontWeightStrong:b})}const V_={common:gt,self:W_},Lf=1,zg="n-grid",Tg=1,K_={span:{type:[Number,String],default:Tg},offset:{type:[Number,String],default:0},suffix:Boolean,privateOffset:Number,privateSpan:Number,privateColStart:Number,privateShow:{type:Boolean,default:!0}},bn=pe({__GRID_ITEM__:!0,name:"GridItem",alias:["Gi"],props:K_,setup(){const{isSsrRef:e,xGapRef:t,itemStyleRef:n,overflowRef:o,layoutShiftDisabledRef:r}=Ee(zg),i=Lo();return{overflow:o,itemStyle:n,layoutShiftDisabled:r,mergedXGap:O(()=>pt(t.value||0)),deriveStyle:()=>{e.value;const{privateSpan:l=Tg,privateShow:a=!0,privateColStart:s=void 0,privateOffset:d=0}=i.vnode.props,{value:c}=t,f=pt(c||0);return{display:a?"":"none",gridColumn:`${s??`span ${l}`} / span ${l}`,marginLeft:d?`calc((100% - (${l} - 1) * ${f}) / ${l} * ${d} + ${f} * ${d})`:""}}}},render(){var e,t;if(this.layoutShiftDisabled){const{span:n,offset:o,mergedXGap:r}=this;return h("div",{style:{gridColumn:`span ${n} / span ${n}`,marginLeft:o?`calc((100% - (${n} - 1) * ${r}) / ${n} * ${o} + ${r} * ${o})`:""}},this.$slots)}return h("div",{style:[this.itemStyle,this.deriveStyle()]},(t=(e=this.$slots).default)===null||t===void 0?void 0:t.call(e,{overflow:this.overflow}))}}),U_={xs:0,s:640,m:1024,l:1280,xl:1536,xxl:1920},Fg=24,ws="__ssr__",G_={layoutShiftDisabled:Boolean,responsive:{type:[String,Boolean],default:"self"},cols:{type:[Number,String],default:Fg},itemResponsive:Boolean,collapsed:Boolean,collapsedRows:{type:Number,default:1},itemStyle:[Object,String],xGap:{type:[Number,String],default:0},yGap:{type:[Number,String],default:0}},id=pe({name:"Grid",inheritAttrs:!1,props:G_,setup(e){const{mergedClsPrefixRef:t,mergedBreakpointsRef:n}=Ye(e),o=/^\d+$/,r=E(void 0),i=Py(n?.value||U_),l=ot(()=>!!(e.itemResponsive||!o.test(e.cols.toString())||!o.test(e.xGap.toString())||!o.test(e.yGap.toString()))),a=O(()=>{if(l.value)return e.responsive==="self"?r.value:i.value}),s=ot(()=>{var m;return(m=Number(xr(e.cols.toString(),a.value)))!==null&&m!==void 0?m:Fg}),d=ot(()=>xr(e.xGap.toString(),a.value)),c=ot(()=>xr(e.yGap.toString(),a.value)),f=m=>{r.value=m.contentRect.width},v=m=>{Ai(f,m)},g=E(!1),u=O(()=>{if(e.responsive==="self")return v}),p=E(!1),b=E();return Ct(()=>{const{value:m}=b;m&&m.hasAttribute(ws)&&(m.removeAttribute(ws),p.value=!0)}),qe(zg,{layoutShiftDisabledRef:we(e,"layoutShiftDisabled"),isSsrRef:p,itemStyleRef:we(e,"itemStyle"),xGapRef:d,overflowRef:g}),{isSsr:!Do,contentEl:b,mergedClsPrefix:t,style:O(()=>e.layoutShiftDisabled?{width:"100%",display:"grid",gridTemplateColumns:`repeat(${e.cols}, minmax(0, 1fr))`,columnGap:pt(e.xGap),rowGap:pt(e.yGap)}:{width:"100%",display:"grid",gridTemplateColumns:`repeat(${s.value}, minmax(0, 1fr))`,columnGap:pt(d.value),rowGap:pt(c.value)}),isResponsive:l,responsiveQuery:a,responsiveCols:s,handleResize:u,overflow:g}},render(){if(this.layoutShiftDisabled)return h("div",nn({ref:"contentEl",class:`${this.mergedClsPrefix}-grid`,style:this.style},this.$attrs),this.$slots);const e=()=>{var t,n,o,r,i,l,a;this.overflow=!1;const s=Un(Dd(this)),d=[],{collapsed:c,collapsedRows:f,responsiveCols:v,responsiveQuery:g}=this;s.forEach(y=>{var $,S,x,R,C;if((($=y?.type)===null||$===void 0?void 0:$.__GRID_ITEM__)!==!0)return;if(Fx(y)){const F=hn(y);F.props?F.props.privateShow=!1:F.props={privateShow:!1},d.push({child:F,rawChildSpan:0});return}y.dirs=((S=y.dirs)===null||S===void 0?void 0:S.filter(({dir:F})=>F!==Fo))||null,((x=y.dirs)===null||x===void 0?void 0:x.length)===0&&(y.dirs=null);const w=hn(y),k=Number((C=xr((R=w.props)===null||R===void 0?void 0:R.span,g))!==null&&C!==void 0?C:Lf);k!==0&&d.push({child:w,rawChildSpan:k})});let u=0;const p=(t=d[d.length-1])===null||t===void 0?void 0:t.child;if(p?.props){const y=(n=p.props)===null||n===void 0?void 0:n.suffix;y!==void 0&&y!==!1&&(u=Number((r=xr((o=p.props)===null||o===void 0?void 0:o.span,g))!==null&&r!==void 0?r:Lf),p.props.privateSpan=u,p.props.privateColStart=v+1-u,p.props.privateShow=(i=p.props.privateShow)!==null&&i!==void 0?i:!0)}let b=0,m=!1;for(const{child:y,rawChildSpan:$}of d){if(m&&(this.overflow=!0),!m){const S=Number((a=xr((l=y.props)===null||l===void 0?void 0:l.offset,g))!==null&&a!==void 0?a:0),x=Math.min($+S,v);if(y.props?(y.props.privateSpan=x,y.props.privateOffset=S):y.props={privateSpan:x,privateOffset:S},c){const R=b%v;x+R>v&&(b+=v-R),x+b+u>f*v?m=!0:b+=x}}m&&(y.props?y.props.privateShow!==!0&&(y.props.privateShow=!1):y.props={privateShow:!1})}return h("div",nn({ref:"contentEl",class:`${this.mergedClsPrefix}-grid`,style:this.style,[ws]:this.isSsr||void 0},this.$attrs),d.map(({child:y})=>y))};return this.isResponsive&&this.responsive==="self"?h(Kn,{onResize:this.handleResize},{default:e}):e()}}),Og={type:String,default:"static"},q_=P("layout",` + color: var(--n-text-color); + background-color: var(--n-color); + box-sizing: border-box; + position: relative; + z-index: auto; + flex: auto; + overflow: hidden; + transition: + box-shadow .3s var(--n-bezier), + background-color .3s var(--n-bezier), + color .3s var(--n-bezier); +`,[P("layout-scroll-container",` + overflow-x: hidden; + box-sizing: border-box; + height: 100%; + `),H("absolute-positioned",` + position: absolute; + left: 0; + right: 0; + top: 0; + bottom: 0; + `)]),X_={embedded:Boolean,position:Og,nativeScrollbar:{type:Boolean,default:!0},scrollbarProps:Object,onScroll:Function,contentClass:String,contentStyle:{type:[String,Object],default:""},hasSider:Boolean,siderPlacement:{type:String,default:"left"}},Y_="n-layout";function Eg(e){return pe({name:e?"LayoutContent":"Layout",props:Object.assign(Object.assign({},Be.props),X_),setup(t){const n=E(null),o=E(null),{mergedClsPrefixRef:r,inlineThemeDisabled:i}=Ye(t),l=Be("Layout","-layout",q_,_g,t,r);function a(p,b){if(t.nativeScrollbar){const{value:m}=n;m&&(b===void 0?m.scrollTo(p):m.scrollTo(p,b))}else{const{value:m}=o;m&&m.scrollTo(p,b)}}qe(Y_,t);let s=0,d=0;const c=p=>{var b;const m=p.target;s=m.scrollLeft,d=m.scrollTop,(b=t.onScroll)===null||b===void 0||b.call(t,p)};zp(()=>{if(t.nativeScrollbar){const p=n.value;p&&(p.scrollTop=d,p.scrollLeft=s)}});const f={display:"flex",flexWrap:"nowrap",width:"100%",flexDirection:"row"},v={scrollTo:a},g=O(()=>{const{common:{cubicBezierEaseInOut:p},self:b}=l.value;return{"--n-bezier":p,"--n-color":t.embedded?b.colorEmbedded:b.color,"--n-text-color":b.textColor}}),u=i?vt("layout",O(()=>t.embedded?"e":""),g,t):void 0;return Object.assign({mergedClsPrefix:r,scrollableElRef:n,scrollbarInstRef:o,hasSiderStyle:f,mergedTheme:l,handleNativeElScroll:c,cssVars:i?void 0:g,themeClass:u?.themeClass,onRender:u?.onRender},v)},render(){var t;const{mergedClsPrefix:n,hasSider:o}=this;(t=this.onRender)===null||t===void 0||t.call(this);const r=o?this.hasSiderStyle:void 0,i=[this.themeClass,e&&`${n}-layout-content`,`${n}-layout`,`${n}-layout--${this.position}-positioned`];return h("div",{class:i,style:this.cssVars},this.nativeScrollbar?h("div",{ref:"scrollableElRef",class:[`${n}-layout-scroll-container`,this.contentClass],style:[this.contentStyle,r],onScroll:this.handleNativeElScroll},this.$slots):h(bo,Object.assign({},this.scrollbarProps,{onScroll:this.onScroll,ref:"scrollbarInstRef",theme:this.mergedTheme.peers.Scrollbar,themeOverrides:this.mergedTheme.peerOverrides.Scrollbar,contentClass:this.contentClass,contentStyle:[this.contentStyle,r]}),this.$slots))}})}const Z_=Eg(!1),J_=Eg(!0),Q_=P("layout-header",` + transition: + color .3s var(--n-bezier), + background-color .3s var(--n-bezier), + box-shadow .3s var(--n-bezier), + border-color .3s var(--n-bezier); + box-sizing: border-box; + width: 100%; + background-color: var(--n-color); + color: var(--n-text-color); +`,[H("absolute-positioned",` + position: absolute; + left: 0; + right: 0; + top: 0; + `),H("bordered",` + border-bottom: solid 1px var(--n-border-color); + `)]),ez={position:Og,inverted:Boolean,bordered:{type:Boolean,default:!1}},tz=pe({name:"LayoutHeader",props:Object.assign(Object.assign({},Be.props),ez),setup(e){const{mergedClsPrefixRef:t,inlineThemeDisabled:n}=Ye(e),o=Be("Layout","-layout-header",Q_,_g,e,t),r=O(()=>{const{common:{cubicBezierEaseInOut:l},self:a}=o.value,s={"--n-bezier":l};return e.inverted?(s["--n-color"]=a.headerColorInverted,s["--n-text-color"]=a.textColorInverted,s["--n-border-color"]=a.headerBorderColorInverted):(s["--n-color"]=a.headerColor,s["--n-text-color"]=a.textColor,s["--n-border-color"]=a.headerBorderColor),s}),i=n?vt("layout-header",O(()=>e.inverted?"a":"b"),r,e):void 0;return{mergedClsPrefix:t,cssVars:n?void 0:r,themeClass:i?.themeClass,onRender:i?.onRender}},render(){var e;const{mergedClsPrefix:t}=this;return(e=this.onRender)===null||e===void 0||e.call(this),h("div",{class:[`${t}-layout-header`,this.themeClass,this.position&&`${t}-layout-header--${this.position}-positioned`,this.bordered&&`${t}-layout-header--bordered`],style:this.cssVars},this.$slots)}}),nz=P("switch",` + height: var(--n-height); + min-width: var(--n-width); + vertical-align: middle; + user-select: none; + -webkit-user-select: none; + display: inline-flex; + outline: none; + justify-content: center; + align-items: center; +`,[j("children-placeholder",` + height: var(--n-rail-height); + display: flex; + flex-direction: column; + overflow: hidden; + pointer-events: none; + visibility: hidden; + `),j("rail-placeholder",` + display: flex; + flex-wrap: none; + `),j("button-placeholder",` + width: calc(1.75 * var(--n-rail-height)); + height: var(--n-rail-height); + `),P("base-loading",` + position: absolute; + top: 50%; + left: 50%; + transform: translateX(-50%) translateY(-50%); + font-size: calc(var(--n-button-width) - 4px); + color: var(--n-loading-color); + transition: color .3s var(--n-bezier); + `,[an({left:"50%",top:"50%",originalTransform:"translateX(-50%) translateY(-50%)"})]),j("checked, unchecked",` + transition: color .3s var(--n-bezier); + color: var(--n-text-color); + box-sizing: border-box; + position: absolute; + white-space: nowrap; + top: 0; + bottom: 0; + display: flex; + align-items: center; + line-height: 1; + `),j("checked",` + right: 0; + padding-right: calc(1.25 * var(--n-rail-height) - var(--n-offset)); + `),j("unchecked",` + left: 0; + justify-content: flex-end; + padding-left: calc(1.25 * var(--n-rail-height) - var(--n-offset)); + `),I("&:focus",[j("rail",` + box-shadow: var(--n-box-shadow-focus); + `)]),H("round",[j("rail","border-radius: calc(var(--n-rail-height) / 2);",[j("button","border-radius: calc(var(--n-button-height) / 2);")])]),dt("disabled",[dt("icon",[H("rubber-band",[H("pressed",[j("rail",[j("button","max-width: var(--n-button-width-pressed);")])]),j("rail",[I("&:active",[j("button","max-width: var(--n-button-width-pressed);")])]),H("active",[H("pressed",[j("rail",[j("button","left: calc(100% - var(--n-offset) - var(--n-button-width-pressed));")])]),j("rail",[I("&:active",[j("button","left: calc(100% - var(--n-offset) - var(--n-button-width-pressed));")])])])])])]),H("active",[j("rail",[j("button","left: calc(100% - var(--n-button-width) - var(--n-offset))")])]),j("rail",` + overflow: hidden; + height: var(--n-rail-height); + min-width: var(--n-rail-width); + border-radius: var(--n-rail-border-radius); + cursor: pointer; + position: relative; + transition: + opacity .3s var(--n-bezier), + background .3s var(--n-bezier), + box-shadow .3s var(--n-bezier); + background-color: var(--n-rail-color); + `,[j("button-icon",` + color: var(--n-icon-color); + transition: color .3s var(--n-bezier); + font-size: calc(var(--n-button-height) - 4px); + position: absolute; + left: 0; + right: 0; + top: 0; + bottom: 0; + display: flex; + justify-content: center; + align-items: center; + line-height: 1; + `,[an()]),j("button",` + align-items: center; + top: var(--n-offset); + left: var(--n-offset); + height: var(--n-button-height); + width: var(--n-button-width-pressed); + max-width: var(--n-button-width); + border-radius: var(--n-button-border-radius); + background-color: var(--n-button-color); + box-shadow: var(--n-button-box-shadow); + box-sizing: border-box; + cursor: inherit; + content: ""; + position: absolute; + transition: + background-color .3s var(--n-bezier), + left .3s var(--n-bezier), + opacity .3s var(--n-bezier), + max-width .3s var(--n-bezier), + box-shadow .3s var(--n-bezier); + `)]),H("active",[j("rail","background-color: var(--n-rail-color-active);")]),H("loading",[j("rail",` + cursor: wait; + `)]),H("disabled",[j("rail",` + cursor: not-allowed; + opacity: .5; + `)])]),oz=Object.assign(Object.assign({},Be.props),{size:String,value:{type:[String,Number,Boolean],default:void 0},loading:Boolean,defaultValue:{type:[String,Number,Boolean],default:!1},disabled:{type:Boolean,default:void 0},round:{type:Boolean,default:!0},"onUpdate:value":[Function,Array],onUpdateValue:[Function,Array],checkedValue:{type:[String,Number,Boolean],default:!0},uncheckedValue:{type:[String,Number,Boolean],default:!1},railStyle:Function,rubberBand:{type:Boolean,default:!0},spinProps:Object,onChange:[Function,Array]});let si;const Cs=pe({name:"Switch",props:oz,slots:Object,setup(e){si===void 0&&(typeof CSS<"u"?typeof CSS.supports<"u"?si=CSS.supports("width","max(1px)"):si=!1:si=!0);const{mergedClsPrefixRef:t,inlineThemeDisabled:n,mergedComponentPropsRef:o}=Ye(e),r=Be("Switch","-switch",nz,N_,e,t),i=No(e,{mergedSize(k){var F,M;if(e.size!==void 0)return e.size;if(k)return k.mergedSize.value;const _=(M=(F=o?.value)===null||F===void 0?void 0:F.Switch)===null||M===void 0?void 0:M.size;return _||"medium"}}),{mergedSizeRef:l,mergedDisabledRef:a}=i,s=E(e.defaultValue),c=qt(we(e,"value"),s),f=O(()=>c.value===e.checkedValue),v=E(!1),g=E(!1),u=O(()=>{const{railStyle:k}=e;if(k)return k({focused:g.value,checked:f.value})});function p(k){const{"onUpdate:value":F,onChange:M,onUpdateValue:_}=e,{nTriggerFormInput:T,nTriggerFormChange:B}=i;F&&me(F,k),_&&me(_,k),M&&me(M,k),s.value=k,T(),B()}function b(){const{nTriggerFormFocus:k}=i;k()}function m(){const{nTriggerFormBlur:k}=i;k()}function y(){e.loading||a.value||(c.value!==e.checkedValue?p(e.checkedValue):p(e.uncheckedValue))}function $(){g.value=!0,b()}function S(){g.value=!1,m(),v.value=!1}function x(k){e.loading||a.value||k.key===" "&&(c.value!==e.checkedValue?p(e.checkedValue):p(e.uncheckedValue),v.value=!1)}function R(k){e.loading||a.value||k.key===" "&&(k.preventDefault(),v.value=!0)}const C=O(()=>{const{value:k}=l,{self:{opacityDisabled:F,railColor:M,railColorActive:_,buttonBoxShadow:T,buttonColor:B,boxShadowFocus:D,loadingColor:K,textColor:N,iconColor:V,[de("buttonHeight",k)]:ie,[de("buttonWidth",k)]:he,[de("buttonWidthPressed",k)]:J,[de("railHeight",k)]:re,[de("railWidth",k)]:ye,[de("railBorderRadius",k)]:Z,[de("buttonBorderRadius",k)]:le},common:{cubicBezierEaseInOut:$e}}=r.value;let ze,Ae,Te;return si?(ze=`calc((${re} - ${ie}) / 2)`,Ae=`max(${re}, ${ie})`,Te=`max(${ye}, calc(${ye} + ${ie} - ${re}))`):(ze=pt((Pt(re)-Pt(ie))/2),Ae=pt(Math.max(Pt(re),Pt(ie))),Te=Pt(re)>Pt(ie)?ye:pt(Pt(ye)+Pt(ie)-Pt(re))),{"--n-bezier":$e,"--n-button-border-radius":le,"--n-button-box-shadow":T,"--n-button-color":B,"--n-button-width":he,"--n-button-width-pressed":J,"--n-button-height":ie,"--n-height":Ae,"--n-offset":ze,"--n-opacity-disabled":F,"--n-rail-border-radius":Z,"--n-rail-color":M,"--n-rail-color-active":_,"--n-rail-height":re,"--n-rail-width":ye,"--n-width":Te,"--n-box-shadow-focus":D,"--n-loading-color":K,"--n-text-color":N,"--n-icon-color":V}}),w=n?vt("switch",O(()=>l.value[0]),C,e):void 0;return{handleClick:y,handleBlur:S,handleFocus:$,handleKeyup:x,handleKeydown:R,mergedRailStyle:u,pressed:v,mergedClsPrefix:t,mergedValue:c,checked:f,mergedDisabled:a,cssVars:n?void 0:C,themeClass:w?.themeClass,onRender:w?.onRender}},render(){const{mergedClsPrefix:e,mergedDisabled:t,checked:n,mergedRailStyle:o,onRender:r,$slots:i}=this;r?.();const{checked:l,unchecked:a,icon:s,"checked-icon":d,"unchecked-icon":c}=i,f=!(Mr(s)&&Mr(d)&&Mr(c));return h("div",{role:"switch","aria-checked":n,class:[`${e}-switch`,this.themeClass,f&&`${e}-switch--icon`,n&&`${e}-switch--active`,t&&`${e}-switch--disabled`,this.round&&`${e}-switch--round`,this.loading&&`${e}-switch--loading`,this.pressed&&`${e}-switch--pressed`,this.rubberBand&&`${e}-switch--rubber-band`],tabindex:this.mergedDisabled?void 0:0,style:this.cssVars,onClick:this.handleClick,onFocus:this.handleFocus,onBlur:this.handleBlur,onKeyup:this.handleKeyup,onKeydown:this.handleKeydown},h("div",{class:`${e}-switch__rail`,"aria-hidden":"true",style:o},lt(l,v=>lt(a,g=>v||g?h("div",{"aria-hidden":!0,class:`${e}-switch__children-placeholder`},h("div",{class:`${e}-switch__rail-placeholder`},h("div",{class:`${e}-switch__button-placeholder`}),v),h("div",{class:`${e}-switch__rail-placeholder`},h("div",{class:`${e}-switch__button-placeholder`}),g)):null)),h("div",{class:`${e}-switch__button`},lt(s,v=>lt(d,g=>lt(c,u=>h(vr,null,{default:()=>this.loading?h(gr,Object.assign({key:"loading",clsPrefix:e,strokeWidth:20},this.spinProps)):this.checked&&(g||v)?h("div",{class:`${e}-switch__button-icon`,key:g?"checked-icon":"icon"},g||v):!this.checked&&(u||v)?h("div",{class:`${e}-switch__button-icon`,key:u?"unchecked-icon":"icon"},u||v):null})))),lt(l,v=>v&&h("div",{key:"checked",class:`${e}-switch__checked`},v)),lt(a,v=>v&&h("div",{key:"unchecked",class:`${e}-switch__unchecked`},v)))))}}),gc="n-tabs",Mg={tab:[String,Number,Object,Function],name:{type:[String,Number],required:!0},disabled:Boolean,displayDirective:{type:String,default:"if"},closable:{type:Boolean,default:void 0},tabProps:Object,label:[String,Number,Object,Function]},yl=pe({__TAB_PANE__:!0,name:"TabPane",alias:["TabPanel"],props:Mg,slots:Object,setup(e){const t=Ee(gc,null);return t||sr("tab-pane","`n-tab-pane` must be placed inside `n-tabs`."),{style:t.paneStyleRef,class:t.paneClassRef,mergedClsPrefix:t.mergedClsPrefixRef}},render(){return h("div",{class:[`${this.mergedClsPrefix}-tab-pane`,this.class],style:this.style},this.$slots)}}),rz=Object.assign({internalLeftPadded:Boolean,internalAddable:Boolean,internalCreatedByPane:Boolean},dr(Mg,["displayDirective"])),ld=pe({__TAB__:!0,inheritAttrs:!1,name:"Tab",props:rz,setup(e){const{mergedClsPrefixRef:t,valueRef:n,typeRef:o,closableRef:r,tabStyleRef:i,addTabStyleRef:l,tabClassRef:a,addTabClassRef:s,tabChangeIdRef:d,onBeforeLeaveRef:c,triggerRef:f,handleAdd:v,activateTab:g,handleClose:u}=Ee(gc);return{trigger:f,mergedClosable:O(()=>{if(e.internalAddable)return!1;const{closable:p}=e;return p===void 0?r.value:p}),style:i,addStyle:l,tabClass:a,addTabClass:s,clsPrefix:t,value:n,type:o,handleClose(p){p.stopPropagation(),!e.disabled&&u(e.name)},activateTab(){if(e.disabled)return;if(e.internalAddable){v();return}const{name:p}=e,b=++d.id;if(p!==n.value){const{value:m}=c;m?Promise.resolve(m(e.name,n.value)).then(y=>{y&&d.id===b&&g(p)}):g(p)}}}},render(){const{internalAddable:e,clsPrefix:t,name:n,disabled:o,label:r,tab:i,value:l,mergedClosable:a,trigger:s,$slots:{default:d}}=this,c=r??i;return h("div",{class:`${t}-tabs-tab-wrapper`},this.internalLeftPadded?h("div",{class:`${t}-tabs-tab-pad`}):null,h("div",Object.assign({key:n,"data-name":n,"data-disabled":o?!0:void 0},nn({class:[`${t}-tabs-tab`,l===n&&`${t}-tabs-tab--active`,o&&`${t}-tabs-tab--disabled`,a&&`${t}-tabs-tab--closable`,e&&`${t}-tabs-tab--addable`,e?this.addTabClass:this.tabClass],onClick:s==="click"?this.activateTab:void 0,onMouseenter:s==="hover"?this.activateTab:void 0,style:e?this.addStyle:this.style},this.internalCreatedByPane?this.tabProps||{}:this.$attrs)),h("span",{class:`${t}-tabs-tab__label`},e?h(nt,null,h("div",{class:`${t}-tabs-tab__height-placeholder`}," "),h(kt,{clsPrefix:t},{default:()=>h(ZR,null)})):d?d():typeof c=="object"?c:wt(c??n)),a&&this.type==="card"?h(Kr,{clsPrefix:t,class:`${t}-tabs-tab__close`,onClick:this.handleClose,disabled:o}):null))}}),iz=P("tabs",` + box-sizing: border-box; + width: 100%; + display: flex; + flex-direction: column; + transition: + background-color .3s var(--n-bezier), + border-color .3s var(--n-bezier); +`,[H("segment-type",[P("tabs-rail",[I("&.transition-disabled",[P("tabs-capsule",` + transition: none; + `)])])]),H("top",[P("tab-pane",` + padding: var(--n-pane-padding-top) var(--n-pane-padding-right) var(--n-pane-padding-bottom) var(--n-pane-padding-left); + `)]),H("left",[P("tab-pane",` + padding: var(--n-pane-padding-right) var(--n-pane-padding-bottom) var(--n-pane-padding-left) var(--n-pane-padding-top); + `)]),H("left, right",` + flex-direction: row; + `,[P("tabs-bar",` + width: 2px; + right: 0; + transition: + top .2s var(--n-bezier), + max-height .2s var(--n-bezier), + background-color .3s var(--n-bezier); + `),P("tabs-tab",` + padding: var(--n-tab-padding-vertical); + `)]),H("right",` + flex-direction: row-reverse; + `,[P("tab-pane",` + padding: var(--n-pane-padding-left) var(--n-pane-padding-top) var(--n-pane-padding-right) var(--n-pane-padding-bottom); + `),P("tabs-bar",` + left: 0; + `)]),H("bottom",` + flex-direction: column-reverse; + justify-content: flex-end; + `,[P("tab-pane",` + padding: var(--n-pane-padding-bottom) var(--n-pane-padding-right) var(--n-pane-padding-top) var(--n-pane-padding-left); + `),P("tabs-bar",` + top: 0; + `)]),P("tabs-rail",` + position: relative; + padding: 3px; + border-radius: var(--n-tab-border-radius); + width: 100%; + background-color: var(--n-color-segment); + transition: background-color .3s var(--n-bezier); + display: flex; + align-items: center; + `,[P("tabs-capsule",` + border-radius: var(--n-tab-border-radius); + position: absolute; + pointer-events: none; + background-color: var(--n-tab-color-segment); + box-shadow: 0 1px 3px 0 rgba(0, 0, 0, .08); + transition: transform 0.3s var(--n-bezier); + `),P("tabs-tab-wrapper",` + flex-basis: 0; + flex-grow: 1; + display: flex; + align-items: center; + justify-content: center; + `,[P("tabs-tab",` + overflow: hidden; + border-radius: var(--n-tab-border-radius); + width: 100%; + display: flex; + align-items: center; + justify-content: center; + `,[H("active",` + font-weight: var(--n-font-weight-strong); + color: var(--n-tab-text-color-active); + `),I("&:hover",` + color: var(--n-tab-text-color-hover); + `)])])]),H("flex",[P("tabs-nav",` + width: 100%; + position: relative; + `,[P("tabs-wrapper",` + width: 100%; + `,[P("tabs-tab",` + margin-right: 0; + `)])])]),P("tabs-nav",` + box-sizing: border-box; + line-height: 1.5; + display: flex; + transition: border-color .3s var(--n-bezier); + `,[j("prefix, suffix",` + display: flex; + align-items: center; + `),j("prefix","padding-right: 16px;"),j("suffix","padding-left: 16px;")]),H("top, bottom",[I(">",[P("tabs-nav",[P("tabs-nav-scroll-wrapper",[I("&::before",` + top: 0; + bottom: 0; + left: 0; + width: 20px; + `),I("&::after",` + top: 0; + bottom: 0; + right: 0; + width: 20px; + `),H("shadow-start",[I("&::before",` + box-shadow: inset 10px 0 8px -8px rgba(0, 0, 0, .12); + `)]),H("shadow-end",[I("&::after",` + box-shadow: inset -10px 0 8px -8px rgba(0, 0, 0, .12); + `)])])])])]),H("left, right",[P("tabs-nav-scroll-content",` + flex-direction: column; + `),I(">",[P("tabs-nav",[P("tabs-nav-scroll-wrapper",[I("&::before",` + top: 0; + left: 0; + right: 0; + height: 20px; + `),I("&::after",` + bottom: 0; + left: 0; + right: 0; + height: 20px; + `),H("shadow-start",[I("&::before",` + box-shadow: inset 0 10px 8px -8px rgba(0, 0, 0, .12); + `)]),H("shadow-end",[I("&::after",` + box-shadow: inset 0 -10px 8px -8px rgba(0, 0, 0, .12); + `)])])])])]),P("tabs-nav-scroll-wrapper",` + flex: 1; + position: relative; + overflow: hidden; + `,[P("tabs-nav-y-scroll",` + height: 100%; + width: 100%; + overflow-y: auto; + scrollbar-width: none; + `,[I("&::-webkit-scrollbar, &::-webkit-scrollbar-track-piece, &::-webkit-scrollbar-thumb",` + width: 0; + height: 0; + display: none; + `)]),I("&::before, &::after",` + transition: box-shadow .3s var(--n-bezier); + pointer-events: none; + content: ""; + position: absolute; + z-index: 1; + `)]),P("tabs-nav-scroll-content",` + display: flex; + position: relative; + min-width: 100%; + min-height: 100%; + width: fit-content; + box-sizing: border-box; + `),P("tabs-wrapper",` + display: inline-flex; + flex-wrap: nowrap; + position: relative; + `),P("tabs-tab-wrapper",` + display: flex; + flex-wrap: nowrap; + flex-shrink: 0; + flex-grow: 0; + `),P("tabs-tab",` + cursor: pointer; + white-space: nowrap; + flex-wrap: nowrap; + display: inline-flex; + align-items: center; + color: var(--n-tab-text-color); + font-size: var(--n-tab-font-size); + background-clip: padding-box; + padding: var(--n-tab-padding); + transition: + box-shadow .3s var(--n-bezier), + color .3s var(--n-bezier), + background-color .3s var(--n-bezier), + border-color .3s var(--n-bezier); + `,[H("disabled",{cursor:"not-allowed"}),j("close",` + margin-left: 6px; + transition: + background-color .3s var(--n-bezier), + color .3s var(--n-bezier); + `),j("label",` + display: flex; + align-items: center; + z-index: 1; + `)]),P("tabs-bar",` + position: absolute; + bottom: 0; + height: 2px; + border-radius: 1px; + background-color: var(--n-bar-color); + transition: + left .2s var(--n-bezier), + max-width .2s var(--n-bezier), + opacity .3s var(--n-bezier), + background-color .3s var(--n-bezier); + `,[I("&.transition-disabled",` + transition: none; + `),H("disabled",` + background-color: var(--n-tab-text-color-disabled) + `)]),P("tabs-pane-wrapper",` + position: relative; + overflow: hidden; + transition: max-height .2s var(--n-bezier); + `),P("tab-pane",` + color: var(--n-pane-text-color); + width: 100%; + transition: + color .3s var(--n-bezier), + background-color .3s var(--n-bezier), + opacity .2s var(--n-bezier); + left: 0; + right: 0; + top: 0; + `,[I("&.next-transition-leave-active, &.prev-transition-leave-active, &.next-transition-enter-active, &.prev-transition-enter-active",` + transition: + color .3s var(--n-bezier), + background-color .3s var(--n-bezier), + transform .2s var(--n-bezier), + opacity .2s var(--n-bezier); + `),I("&.next-transition-leave-active, &.prev-transition-leave-active",` + position: absolute; + `),I("&.next-transition-enter-from, &.prev-transition-leave-to",` + transform: translateX(32px); + opacity: 0; + `),I("&.next-transition-leave-to, &.prev-transition-enter-from",` + transform: translateX(-32px); + opacity: 0; + `),I("&.next-transition-leave-from, &.next-transition-enter-to, &.prev-transition-leave-from, &.prev-transition-enter-to",` + transform: translateX(0); + opacity: 1; + `)]),P("tabs-tab-pad",` + box-sizing: border-box; + width: var(--n-tab-gap); + flex-grow: 0; + flex-shrink: 0; + `),H("line-type, bar-type",[P("tabs-tab",` + font-weight: var(--n-tab-font-weight); + box-sizing: border-box; + vertical-align: bottom; + `,[I("&:hover",{color:"var(--n-tab-text-color-hover)"}),H("active",` + color: var(--n-tab-text-color-active); + font-weight: var(--n-tab-font-weight-active); + `),H("disabled",{color:"var(--n-tab-text-color-disabled)"})])]),P("tabs-nav",[H("line-type",[H("top",[j("prefix, suffix",` + border-bottom: 1px solid var(--n-tab-border-color); + `),P("tabs-nav-scroll-content",` + border-bottom: 1px solid var(--n-tab-border-color); + `),P("tabs-bar",` + bottom: -1px; + `)]),H("left",[j("prefix, suffix",` + border-right: 1px solid var(--n-tab-border-color); + `),P("tabs-nav-scroll-content",` + border-right: 1px solid var(--n-tab-border-color); + `),P("tabs-bar",` + right: -1px; + `)]),H("right",[j("prefix, suffix",` + border-left: 1px solid var(--n-tab-border-color); + `),P("tabs-nav-scroll-content",` + border-left: 1px solid var(--n-tab-border-color); + `),P("tabs-bar",` + left: -1px; + `)]),H("bottom",[j("prefix, suffix",` + border-top: 1px solid var(--n-tab-border-color); + `),P("tabs-nav-scroll-content",` + border-top: 1px solid var(--n-tab-border-color); + `),P("tabs-bar",` + top: -1px; + `)]),j("prefix, suffix",` + transition: border-color .3s var(--n-bezier); + `),P("tabs-nav-scroll-content",` + transition: border-color .3s var(--n-bezier); + `),P("tabs-bar",` + border-radius: 0; + `)]),H("card-type",[j("prefix, suffix",` + transition: border-color .3s var(--n-bezier); + `),P("tabs-pad",` + flex-grow: 1; + transition: border-color .3s var(--n-bezier); + `),P("tabs-tab-pad",` + transition: border-color .3s var(--n-bezier); + `),P("tabs-tab",` + font-weight: var(--n-tab-font-weight); + border: 1px solid var(--n-tab-border-color); + background-color: var(--n-tab-color); + box-sizing: border-box; + position: relative; + vertical-align: bottom; + display: flex; + justify-content: space-between; + font-size: var(--n-tab-font-size); + color: var(--n-tab-text-color); + `,[H("addable",` + padding-left: 8px; + padding-right: 8px; + font-size: 16px; + justify-content: center; + `,[j("height-placeholder",` + width: 0; + font-size: var(--n-tab-font-size); + `),dt("disabled",[I("&:hover",` + color: var(--n-tab-text-color-hover); + `)])]),H("closable","padding-right: 8px;"),H("active",` + background-color: #0000; + font-weight: var(--n-tab-font-weight-active); + color: var(--n-tab-text-color-active); + `),H("disabled","color: var(--n-tab-text-color-disabled);")])]),H("left, right",` + flex-direction: column; + `,[j("prefix, suffix",` + padding: var(--n-tab-padding-vertical); + `),P("tabs-wrapper",` + flex-direction: column; + `),P("tabs-tab-wrapper",` + flex-direction: column; + `,[P("tabs-tab-pad",` + height: var(--n-tab-gap-vertical); + width: 100%; + `)])]),H("top",[H("card-type",[P("tabs-scroll-padding","border-bottom: 1px solid var(--n-tab-border-color);"),j("prefix, suffix",` + border-bottom: 1px solid var(--n-tab-border-color); + `),P("tabs-tab",` + border-top-left-radius: var(--n-tab-border-radius); + border-top-right-radius: var(--n-tab-border-radius); + `,[H("active",` + border-bottom: 1px solid #0000; + `)]),P("tabs-tab-pad",` + border-bottom: 1px solid var(--n-tab-border-color); + `),P("tabs-pad",` + border-bottom: 1px solid var(--n-tab-border-color); + `)])]),H("left",[H("card-type",[P("tabs-scroll-padding","border-right: 1px solid var(--n-tab-border-color);"),j("prefix, suffix",` + border-right: 1px solid var(--n-tab-border-color); + `),P("tabs-tab",` + border-top-left-radius: var(--n-tab-border-radius); + border-bottom-left-radius: var(--n-tab-border-radius); + `,[H("active",` + border-right: 1px solid #0000; + `)]),P("tabs-tab-pad",` + border-right: 1px solid var(--n-tab-border-color); + `),P("tabs-pad",` + border-right: 1px solid var(--n-tab-border-color); + `)])]),H("right",[H("card-type",[P("tabs-scroll-padding","border-left: 1px solid var(--n-tab-border-color);"),j("prefix, suffix",` + border-left: 1px solid var(--n-tab-border-color); + `),P("tabs-tab",` + border-top-right-radius: var(--n-tab-border-radius); + border-bottom-right-radius: var(--n-tab-border-radius); + `,[H("active",` + border-left: 1px solid #0000; + `)]),P("tabs-tab-pad",` + border-left: 1px solid var(--n-tab-border-color); + `),P("tabs-pad",` + border-left: 1px solid var(--n-tab-border-color); + `)])]),H("bottom",[H("card-type",[P("tabs-scroll-padding","border-top: 1px solid var(--n-tab-border-color);"),j("prefix, suffix",` + border-top: 1px solid var(--n-tab-border-color); + `),P("tabs-tab",` + border-bottom-left-radius: var(--n-tab-border-radius); + border-bottom-right-radius: var(--n-tab-border-radius); + `,[H("active",` + border-top: 1px solid #0000; + `)]),P("tabs-tab-pad",` + border-top: 1px solid var(--n-tab-border-color); + `),P("tabs-pad",` + border-top: 1px solid var(--n-tab-border-color); + `)])])])]),Ss=UR,lz=Object.assign(Object.assign({},Be.props),{value:[String,Number],defaultValue:[String,Number],trigger:{type:String,default:"click"},type:{type:String,default:"bar"},closable:Boolean,justifyContent:String,size:String,placement:{type:String,default:"top"},tabStyle:[String,Object],tabClass:String,addTabStyle:[String,Object],addTabClass:String,barWidth:Number,paneClass:String,paneStyle:[String,Object],paneWrapperClass:String,paneWrapperStyle:[String,Object],addable:[Boolean,Object],tabsPadding:{type:Number,default:0},animated:Boolean,onBeforeLeave:Function,onAdd:Function,"onUpdate:value":[Function,Array],onUpdateValue:[Function,Array],onClose:[Function,Array],labelSize:String,activeName:[String,Number],onActiveNameChange:[Function,Array]}),az=pe({name:"Tabs",props:lz,slots:Object,setup(e,{slots:t}){var 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z-Z#NVZ~k7(&o=lg*jNtqR^G}kt5mjL*sbWYE3WhW-D~ApZv1)e5FTE0{^~O;z^(lO zb{Z9dBQ{KRPl8Y)yHs?}w@C&XDfb08K@=4NK!*l|P#4AM%#yNe#3~|-%b|mkMfjR1seCoi?DE5+n0dikSY)(~K(n8h zfDn%VdVBj>, + backend_bootstrap_error: Mutex>, +} + +struct RuntimePaths { + app_data_dir: PathBuf, + log_root_dir: PathBuf, + runtime_log_dir: PathBuf, + bot_log_file: PathBuf, + ocr_log_file: PathBuf, + ocr_save_dir: PathBuf, + blocked_row_cache_file: PathBuf, +} + +struct BackendLaunchPlan { + program: PathBuf, + args: Vec, + working_dir: PathBuf, + envs: HashMap, +} + +fn project_root() -> PathBuf { + PathBuf::from(env!("CARGO_MANIFEST_DIR")) + .parent() + .and_then(|p| p.parent()) + .map(|p| p.to_path_buf()) + .expect("project root not found") +} + +fn backend_python() -> PathBuf { + project_root().join(".venv").join("Scripts").join("python.exe") +} + +fn backend_entry() -> PathBuf { + project_root().join("backend_main.py") +} + +fn normalize_mode(value: &str) -> String { + let mode = value.trim().to_ascii_lowercase(); + match mode.as_str() { + "release" | "prod" | "production" | "bundle" | "packaged" => "release".to_string(), + _ => "dev".to_string(), + } +} + +fn backend_mode() -> String { + std::env::var("OPENCLAW_BACKEND_MODE") + .map(|value| normalize_mode(&value)) + .unwrap_or_else(|_| { + if cfg!(debug_assertions) { + "dev".to_string() + } else { + "release".to_string() + } + }) +} + +fn backend_addr() -> String { + std::env::var("APP_HOST") + .map(|host| { + let port = std::env::var("APP_PORT").unwrap_or_else(|_| "5000".to_string()); + format!("{}:{}", host, port) + }) + .unwrap_or_else(|_| "127.0.0.1:5000".to_string()) +} + +fn is_backend_alive() -> bool { + TcpStream::connect(backend_addr()).is_ok() +} + +fn wait_for_backend(child: &mut Child, timeout: Duration) -> Result<(), String> { + let started = Instant::now(); + while started.elapsed() < timeout { + if is_backend_alive() { + return Ok(()); + } + if let Ok(Some(status)) = child.try_wait() { + return Err(format!("独立后台进程已退出，退出码: {}", status)); + } + thread::sleep(Duration::from_millis(200)); + } + Err(format!("后台启动超时，未监听 {}", backend_addr())) +} + +fn ensure_dir(path: &Path) -> Result<(), String> { + std::fs::create_dir_all(path).map_err(|err| format!("创建目录失败 {}: {}", path.display(), err)) +} + +fn resolve_runtime_paths(app: &AppHandle) -> Result { + let app_data_dir = app + .path() + .app_local_data_dir() + .map_err(|err| format!("获取应用数据目录失败: {}", err))?; + let log_root_dir = app_data_dir.join("logs"); + let runtime_log_dir = log_root_dir.join("runtime"); + let bot_log_file = runtime_log_dir.join("bot").join("wechat_multi_chat_bot.log"); + let ocr_log_file = runtime_log_dir.join("ocr").join("wechat_ocr.log"); + let ocr_save_dir = log_root_dir.join("ocr_debug_images"); + let blocked_row_cache_file = log_root_dir.join("state").join("blocked_rows.json"); + + ensure_dir(&app_data_dir)?; + ensure_dir(&runtime_log_dir.join("bot"))?; + ensure_dir(&runtime_log_dir.join("ocr"))?; + ensure_dir(&ocr_save_dir)?; + ensure_dir( + blocked_row_cache_file + .parent() + .ok_or_else(|| "状态缓存目录无效".to_string())?, + )?; + + Ok(RuntimePaths { + app_data_dir, + log_root_dir, + runtime_log_dir, + bot_log_file, + ocr_log_file, + ocr_save_dir, + blocked_row_cache_file, + }) +} + +fn runtime_envs(app: &AppHandle, mode: &str) -> Result, String> { + let paths = resolve_runtime_paths(app)?; + let mut envs = HashMap::new(); + envs.insert("APP_NAME".to_string(), "AiShiliu".to_string()); + envs.insert("APP_DATA_DIR".to_string(), paths.app_data_dir.display().to_string()); + envs.insert("LOG_ROOT_DIR".to_string(), paths.log_root_dir.display().to_string()); + envs.insert( + "RUNTIME_LOG_DIR".to_string(), + paths.runtime_log_dir.display().to_string(), + ); + envs.insert("BOT_LOG_FILE".to_string(), paths.bot_log_file.display().to_string()); + envs.insert("OCR_LOG_FILE".to_string(), paths.ocr_log_file.display().to_string()); + envs.insert("OCR_SAVE_DIR".to_string(), paths.ocr_save_dir.display().to_string()); + envs.insert( + "BLOCKED_ROW_CACHE_FILE".to_string(), + paths.blocked_row_cache_file.display().to_string(), + ); + + envs.insert("OPENCLAW_BACKEND_MODE".to_string(), mode.to_string()); + envs.insert("OPENCLAW_RUNTIME_MODE".to_string(), mode.to_string()); + Ok(envs) +} + +fn release_backend_candidates(app: &AppHandle) -> Result, String> { + let resource_dir = app + .path() + .resource_dir() + .map_err(|err| format!("获取资源目录失败: {}", err))?; + let exe_dir = std::env::current_exe() + .map_err(|err| format!("获取主程序路径失败: {}", err))? + .parent() + .map(Path::to_path_buf) + .ok_or_else(|| "无法解析主程序目录".to_string())?; + + Ok(vec![ + resource_dir.join("backend").join("backend.exe"), + resource_dir.join("backend.exe"), + exe_dir.join("resources").join("backend").join("backend.exe"), + exe_dir.join("resources").join("backend.exe"), + exe_dir.join("backend").join("backend.exe"), + exe_dir.join("backend.exe"), + ]) +} + +fn release_working_dir(app: &AppHandle) -> Result { + let resource_dir = app + .path() + .resource_dir() + .map_err(|err| format!("获取资源目录失败: {}", err))?; + Ok(resource_dir) +} + +fn resolve_backend_launch_plan(app: &AppHandle) -> Result { + let mode = backend_mode(); + let envs = runtime_envs(app, &mode)?; + + if mode == "release" { + let candidates = release_backend_candidates(app)?; + let program = candidates + .into_iter() + .find(|candidate| candidate.exists()) + .ok_or_else(|| "未找到发布态后端程序 backend.exe".to_string())?; + let working_dir = release_working_dir(app)?; + return Ok(BackendLaunchPlan { + program, + args: Vec::new(), + working_dir, + envs, + }); + } + + let python = backend_python(); + if !python.exists() { + return Err(format!("未找到后端解释器: {}", python.display())); + } + let entry = backend_entry(); + if !entry.exists() { + return Err(format!("未找到后端入口: {}", entry.display())); + } + Ok(BackendLaunchPlan { + program: python, + args: vec![entry], + working_dir: project_root(), + envs, + }) +} + +fn spawn_backend(app: &AppHandle) -> Result<(), String> { + if is_backend_alive() { + return Ok(()); + } + + let plan = resolve_backend_launch_plan(app)?; + let mut command = Command::new(&plan.program); + command.current_dir(&plan.working_dir); + for arg in &plan.args { + command.arg(arg); + } + for (key, value) in &plan.envs { + command.env(key, value); + } + command + .env("OPENCLAW_PROJECT_VENV_REEXEC", "1") + .stdout(Stdio::null()) + .stderr(Stdio::null()); + + let mut child = command + .spawn() + .map_err(|err| format!("启动后台失败: {}", err))?; + if let Err(err) = wait_for_backend(&mut child, Duration::from_secs(20)) { + let _ = child.kill(); + let _ = child.wait(); + return Err(err); + } + let state = app.state::(); + let mut guard = state + .backend_child + .lock() + .map_err(|_| "后台状态锁定失败".to_string())?; + *guard = Some(child); + Ok(()) +} + +fn ps_single_quote(value: &str) -> String { + format!("'{}'", value.replace('\'', "''")) +} + +fn cleanup_orphan_backend_processes(app: &AppHandle, mode: &str) { + let script = if mode == "release" { + let targets = release_backend_candidates(app) + .unwrap_or_default() + .into_iter() + .map(|path| ps_single_quote(&path.display().to_string())) + .collect::>() + .join(","); + if targets.is_empty() { + return; + } + format!("$targets=@({}); Get-CimInstance Win32_Process | Where-Object {{ $_.ExecutablePath -and ($targets -contains $_.ExecutablePath) }} | ForEach-Object {{ Stop-Process -Id $_.ProcessId -Force -ErrorAction SilentlyContinue }}", targets) + } else { + "Get-CimInstance Win32_Process | Where-Object { $_.Name -ieq 'python.exe' -and $_.CommandLine -match 'backend_main.py' } | ForEach-Object { Stop-Process -Id $_.ProcessId -Force -ErrorAction SilentlyContinue }".to_string() + }; + let _ = Command::new("powershell") + .arg("-NoProfile") + .arg("-ExecutionPolicy") + .arg("Bypass") + .arg("-Command") + .arg(script) + .stdout(Stdio::null()) + .stderr(Stdio::null()) + .status(); +} + +fn terminate_backend(app: &AppHandle) { + if let Some(state) = app.try_state::() { + if let Ok(mut guard) = state.backend_child.lock() { + if let Some(mut child) = guard.take() { + let _ = child.kill(); + let _ = child.wait(); + } + } + } + cleanup_orphan_backend_processes(app, &backend_mode()); +} + +#[tauri::command] +fn open_devtools(app: AppHandle) -> Result<(), String> { + let webview = app + .get_webview_window("main") + .ok_or_else(|| "未找到主窗口".to_string())?; + webview.open_devtools(); + Ok(()) +} + +#[tauri::command] +fn get_backend_bootstrap_error(app: AppHandle) -> Result, String> { + let state = app.state::(); + let guard = state + .backend_bootstrap_error + .lock() + .map_err(|_| "后台启动错误状态锁定失败".to_string())?; + Ok(guard.clone()) +} + +#[tauri::command] +fn restart_backend(app: AppHandle) -> Result<(), String> { + terminate_backend(&app); + spawn_backend(&app)?; + Ok(()) +} + +#[cfg_attr(mobile, tauri::mobile_entry_point)] +pub fn run() { + tauri::Builder::default() + .manage(AppState { + backend_child: Mutex::new(None), + backend_bootstrap_error: Mutex::new(None), + }) + .invoke_handler(tauri::generate_handler![open_devtools, get_backend_bootstrap_error, restart_backend]) + .setup(|app| { + if cfg!(debug_assertions) { + app.handle().plugin( + tauri_plugin_log::Builder::default() + .level(log::LevelFilter::Info) + .build(), + )?; + } + if let Err(err) = spawn_backend(app.handle()) { + if let Ok(mut guard) = app.state::().backend_bootstrap_error.lock() { + *guard = Some(err.clone()); + } + } + Ok(()) + }) + .build(tauri::generate_context!()) + .expect("error while building tauri application") + .run(|app, event| { + if matches!(event, RunEvent::Exit | RunEvent::ExitRequested { .. }) { + terminate_backend(app); + } + }); +} diff --git a/frontend/src-tauri/src/main.rs b/frontend/src-tauri/src/main.rs new file mode 100644 index 0000000..ad5fe83 --- /dev/null +++ b/frontend/src-tauri/src/main.rs @@ -0,0 +1,6 @@ +// Prevents additional console window on Windows in release, DO NOT REMOVE!! +#![cfg_attr(not(debug_assertions), windows_subsystem = "windows")] + +fn main() { + app_lib::run(); +} diff --git a/frontend/src-tauri/tauri.conf.json b/frontend/src-tauri/tauri.conf.json new file mode 100644 index 0000000..651ddb0 --- /dev/null +++ b/frontend/src-tauri/tauri.conf.json @@ -0,0 +1,51 @@ +{ + "$schema": "https://schema.tauri.app/config/2", + "productName": "识流 AI 助手", + "version": "0.1.0", + "identifier": "com.shiliu.aiassistant", + "build": { + "frontendDist": "../dist", + "devUrl": "http://localhost:1420", + "beforeDevCommand": "npm run dev", + "beforeBuildCommand": "" + }, + "app": { + "windows": [ + { + "title": "识流 AI 助手", + "width": 1280, + "height": 920, + "minWidth": 1100, + "minHeight": 760, + "resizable": true, + "fullscreen": false, + "decorations": false + } + ], + "security": { + "csp": null + } + }, + "bundle": { + "active": true, + "targets": "all", + "resources": [ + "resources/**/*" + ], + "icon": [ + "icons/32x32.png", + "icons/128x128.png", + "icons/128x128@2x.png", + "icons/icon.icns", + "icons/icon.ico" + ], + "android": { + "debugApplicationIdSuffix": ".debug" + }, + "windows": { + "wix": { + "language": "zh-CN" + } + } + } +} diff --git a/frontend/src/App.vue b/frontend/src/App.vue new file mode 100644 index 0000000..cb8cafe --- /dev/null +++ b/frontend/src/App.vue @@ -0,0 +1,149 @@ + + + diff --git a/frontend/src/api/bot.js b/frontend/src/api/bot.js new file mode 100644 index 0000000..502165f --- /dev/null +++ b/frontend/src/api/bot.js @@ -0,0 +1,43 @@ +import { getJson, postForm, postJson } from './http' + +export function getBotStatus() { + return getJson('/api/bot/status') +} + +export function getLogEvents(params = {}) { + const query = new URLSearchParams() + Object.entries(params).forEach(([key, value]) => { + if (value === undefined || value === null || value === '') return + query.set(key, String(value)) + }) + const suffix = query.toString() ? `?${query.toString()}` : '' + return getJson(`/api/logs/v2/events${suffix}`) +} + +export function getLogSummary(limit = 300) { + return getJson(`/api/logs/v2/summary?limit=${encodeURIComponent(limit)}`) +} + +export function getLogTrace(traceId) { + return getJson(`/api/logs/v2/trace/${encodeURIComponent(traceId)}`) +} + +export function getBotLogs(kind = 'bot', limit = 80) { + return getLogEvents({ module: kind, size: limit, page: 1 }) +} + +export function getLogEventJson(eventId) { + return getJson(`/api/logs/v2/event/${encodeURIComponent(eventId)}`) +} + +export function clearLogs(module = '') { + return postJson('/api/logs/v2/clear', { module }) +} + +export function startBot() { + return postForm('/api/bot/start', {}) +} + +export function stopBot() { + return postForm('/api/bot/stop', {}) +} diff --git a/frontend/src/api/client.js b/frontend/src/api/client.js new file mode 100644 index 0000000..439d5bb --- /dev/null +++ b/frontend/src/api/client.js @@ -0,0 +1 @@ +export { getJson, postForm } from './http' diff --git a/frontend/src/api/http.js b/frontend/src/api/http.js new file mode 100644 index 0000000..28554e8 --- /dev/null +++ b/frontend/src/api/http.js @@ -0,0 +1,57 @@ +const DEFAULT_BACKEND_ORIGIN = 'http://127.0.0.1:5000' + +function normalizePath(path) { + if (!path) return '/' + return path.startsWith('/') ? path : `/${path}` +} + +function isAbsoluteUrl(url) { + return /^https?:\/\//i.test(String(url || '')) +} + +function getConfiguredBackendOrigin() { + const raw = String(window.__APP_BACKEND_URL || '').trim() + if (!raw) return '' + return raw.endsWith('/') ? raw.slice(0, -1) : raw +} + +export function isTauriRuntime() { + return !!window.__TAURI_INTERNALS__ +} + +export function resolveApiUrl(path) { + if (isAbsoluteUrl(path)) return path + const normalizedPath = normalizePath(path) + const backendOrigin = getConfiguredBackendOrigin() + if (backendOrigin) return `${backendOrigin}${normalizedPath}` + if (isTauriRuntime()) return `${DEFAULT_BACKEND_ORIGIN}${normalizedPath}` + return normalizedPath +} + +export async function getJson(url) { + const resp = await fetch(resolveApiUrl(url)) + return resp.json() +} + +export async function postForm(url, payload) { + const body = new URLSearchParams(payload) + const resp = await fetch(resolveApiUrl(url), { + method: 'POST', + headers: { 'Content-Type': 'application/x-www-form-urlencoded' }, + body, + }) + return resp.json() +} + +export async function postJson(url, payload) { + const resp = await fetch(resolveApiUrl(url), { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify(payload || {}), + }) + return resp.json() +} + +export function createEventSource(url) { + return new EventSource(resolveApiUrl(url)) +} diff --git a/frontend/src/api/messages.js b/frontend/src/api/messages.js new file mode 100644 index 0000000..7c5b9ea --- /dev/null +++ b/frontend/src/api/messages.js @@ -0,0 +1,5 @@ +import { getJson } from './http' + +export function getRecentMessages(limit = 50) { + return getJson(`/api/rules?action=messages_recent&limit=${limit}`) +} diff --git a/frontend/src/api/rules.js b/frontend/src/api/rules.js new file mode 100644 index 0000000..88aa02c --- /dev/null +++ b/frontend/src/api/rules.js @@ -0,0 +1,17 @@ +import { getJson, postForm } from './http' + +export function getRules() { + return getJson('/api/rules?action=list') +} + +export function createRule(payload) { + return postForm('/api/rules', { action: 'create', ...payload }) +} + +export function toggleRule(payload) { + return postForm('/api/rules', { action: 'toggle', ...payload }) +} + +export function deleteRule(id) { + return postForm('/api/rules', { action: 'delete', id }) +} diff --git a/frontend/src/api/settings.js b/frontend/src/api/settings.js new file mode 100644 index 0000000..8d9c98f --- /dev/null +++ b/frontend/src/api/settings.js @@ -0,0 +1,9 @@ +import { getJson, postForm } from './http' + +export function getSettings() { + return getJson('/api/rules?action=settings_get') +} + +export function saveSettings(payload) { + return postForm('/api/rules', { action: 'settings_set', ...payload }) +} diff --git a/frontend/src/components/AppTopBar.vue b/frontend/src/components/AppTopBar.vue new file mode 100644 index 0000000..2ecb13e --- /dev/null +++ b/frontend/src/components/AppTopBar.vue @@ -0,0 +1,55 @@ + + + diff --git a/frontend/src/components/RuntimeBadge.vue b/frontend/src/components/RuntimeBadge.vue new file mode 100644 index 0000000..1dbab65 --- /dev/null +++ b/frontend/src/components/RuntimeBadge.vue @@ -0,0 +1,18 @@ + + + diff --git a/frontend/src/composables/useBotStatus.js b/frontend/src/composables/useBotStatus.js new file mode 100644 index 0000000..a0d91d3 --- /dev/null +++ b/frontend/src/composables/useBotStatus.js @@ -0,0 +1,177 @@ +import { computed, onBeforeUnmount, ref } from 'vue' +import { getBotStatus, startBot, stopBot } from '../api/bot' +import { createEventSource } from '../api/http' + +export function useBotStatus(settings, loadSettings, message) { + const statusEventSource = ref(null) + const statusFallbackTimer = ref(null) + const statusHealthTimer = ref(null) + const statusConnecting = ref(false) + const lastStatusStreamAt = ref(0) + + const runtimeText = computed(() => { + if (settings.listener_runtime_status === 'running') return '运行中' + if (settings.listener_runtime_status === 'starting') return '启动中' + if (settings.listener_runtime_status === 'stopping') return '停止中' + if (settings.listener_runtime_status === 'error') return '异常' + return '已停止' + }) + + const runtimeTagType = computed(() => { + if (settings.listener_runtime_status === 'running') return 'success' + if (settings.listener_runtime_status === 'starting' || settings.listener_runtime_status === 'stopping') return 'warning' + if (settings.listener_runtime_status === 'error') return 'error' + return 'default' + }) + + function applyBotStatus(bot, fallbackEnabled) { + const nextStatus = String(bot?.status || 'stopped').toLowerCase() + settings.listener_runtime_status = nextStatus + if (nextStatus === 'running' || nextStatus === 'starting') settings.listener_enabled = true + else if (nextStatus === 'stopped' || nextStatus === 'error') settings.listener_enabled = false + else settings.listener_enabled = !!fallbackEnabled + + if (nextStatus === 'error') { + const detail = String(bot?.last_error || '').trim().split('\n').slice(-1)[0] || '' + if (detail && detail !== lastNotifiedError.value) { + lastNotifiedError.value = detail + message.error(`监听启动异常: ${detail}`) + } else if (!detail && lastNotifiedError.value !== '__unknown__') { + lastNotifiedError.value = '__unknown__' + message.error('监听启动异常，请检查微信环境、日志与配置') + } + } + } + + async function refreshBotStatus() { + const bot = await getBotStatus() + if (bot.success) applyBotStatus(bot, settings.listener_enabled) + } + + function touchStatusStream() { + lastStatusStreamAt.value = Date.now() + } + + function clearStatusFallbackTimer() { + if (statusFallbackTimer.value) { + clearInterval(statusFallbackTimer.value) + statusFallbackTimer.value = null + } + } + + function clearStatusHealthTimer() { + if (statusHealthTimer.value) { + clearInterval(statusHealthTimer.value) + statusHealthTimer.value = null + } + } + + function closeStatusStream({ reconnect = false } = {}) { + clearStatusFallbackTimer() + clearStatusHealthTimer() + if (statusEventSource.value) { + const source = statusEventSource.value + statusEventSource.value = null + source.onopen = null + source.onerror = null + source.close() + } + statusConnecting.value = false + if (reconnect) { + connectBotStatusStream(true) + } + } + + function ensureStatusFallbackPolling() { + if (statusFallbackTimer.value) return + statusFallbackTimer.value = setInterval(() => { + refreshBotStatus().catch(() => {}) + }, 15000) + } + + function startStatusHealthCheck() { + if (statusHealthTimer.value) return + statusHealthTimer.value = setInterval(() => { + const lastAt = lastStatusStreamAt.value || 0 + if (!statusEventSource.value) { + connectBotStatusStream() + return + } + if (lastAt && Date.now() - lastAt <= 45000) { + return + } + ensureStatusFallbackPolling() + closeStatusStream({ reconnect: true }) + }, 10000) + } + + function connectBotStatusStream(force = false) { + if (statusConnecting.value) return + if (statusEventSource.value && !force) return + if (statusEventSource.value && force) { + closeStatusStream() + } + statusConnecting.value = true + try { + const source = createEventSource('/api/bot/status/stream') + statusEventSource.value = source + source.addEventListener('status', (event) => { + touchStatusStream() + try { + const payload = JSON.parse(event.data || '{}') + if (payload.success) { + applyBotStatus(payload, settings.listener_enabled) + } + clearStatusFallbackTimer() + } catch (_) { + } + }) + source.addEventListener('ping', () => { + touchStatusStream() + clearStatusFallbackTimer() + }) + source.onopen = () => { + statusConnecting.value = false + touchStatusStream() + clearStatusFallbackTimer() + } + source.onerror = () => { + statusConnecting.value = false + ensureStatusFallbackPolling() + } + } catch (_) { + statusConnecting.value = false + ensureStatusFallbackPolling() + } + } + + async function onListenerChange(value) { + try { + settings.listener_enabled = !!value + settings.listener_runtime_status = value ? 'starting' : 'stopping' + const data = await (value ? startBot() : stopBot()) + if (!data.success) throw new Error(data.error || '操作失败') + settings.listener_runtime_status = data.status || (value ? 'running' : 'stopped') + settings.listener_enabled = data.status === 'running' || data.status === 'starting' + await loadSettings() + } catch (error) { + message.error(`监听切换失败: ${error}`) + await loadSettings() + } + } + + onBeforeUnmount(() => { + closeStatusStream() + }) + + return { + runtimeText, + runtimeTagType, + refreshBotStatus, + connectBotStatusStream, + startStatusHealthCheck, + onListenerChange, + closeStatusStream, + applyBotStatus, + } +} diff --git a/frontend/src/composables/useMessages.js b/frontend/src/composables/useMessages.js new file mode 100644 index 0000000..1bc2c50 --- /dev/null +++ b/frontend/src/composables/useMessages.js @@ -0,0 +1,25 @@ +import { ref } from 'vue' +import { getRecentMessages } from '../api/messages' + +export function useMessages(message) { + const loadingMessages = ref(false) + const messages = ref([]) + + async function loadMessages(limit = 50) { + loadingMessages.value = true + try { + const data = await getRecentMessages(limit) + messages.value = data.data || [] + } catch (error) { + message.error(`加载消息失败: ${error}`) + } finally { + loadingMessages.value = false + } + } + + return { + loadingMessages, + messages, + loadMessages, + } +} diff --git a/frontend/src/composables/useRulesManager.js b/frontend/src/composables/useRulesManager.js new file mode 100644 index 0000000..62e5f19 --- /dev/null +++ b/frontend/src/composables/useRulesManager.js @@ -0,0 +1,132 @@ +import { computed, h, reactive, ref } from 'vue' +import { NButton, NSpace, NTag } from 'naive-ui' +import { createRule, deleteRule, getRules, toggleRule } from '../api/rules' + +export function useRulesManager(message) { + const loadingRules = ref(false) + const creatingRule = ref(false) + const showCreateRuleModal = ref(false) + const rules = ref([]) + const filters = reactive({ keyword: '', match_type: '', status: '' }) + const createForm = reactive({ keyword: '', match_type: 'contain', reply_text: '' }) + + const filteredRules = computed(() => { + return rules.value.filter((row) => { + if (filters.keyword && !String(row.keyword || '').toLowerCase().includes(filters.keyword.toLowerCase())) return false + if (filters.match_type && row.match_type !== filters.match_type) return false + if (filters.status !== '' && Number(row.is_active) !== Number(filters.status)) return false + return true + }) + }) + + async function loadRules() { + loadingRules.value = true + try { + const data = await getRules() + rules.value = data.data || [] + } catch (error) { + message.error(`加载规则失败: ${error}`) + } finally { + loadingRules.value = false + } + } + + async function submitCreateRule() { + if (!createForm.keyword.trim() || !createForm.reply_text.trim()) { + message.warning('请填写关键词和回复内容') + return + } + creatingRule.value = true + try { + const data = await createRule({ + keyword: createForm.keyword.trim(), + match_type: createForm.match_type, + reply_text: createForm.reply_text.trim(), + }) + if (!data.success) { + message.error(data.message || '新增失败') + return + } + message.success('新增成功') + createForm.keyword = '' + createForm.reply_text = '' + showCreateRuleModal.value = false + await loadRules() + } catch (error) { + message.error(`新增失败: ${error}`) + } finally { + creatingRule.value = false + } + } + + async function handleToggleRule(row) { + try { + const data = await toggleRule({ + id: String(row.id), + is_active: Number(row.is_active) === 1 ? '0' : '1', + }) + if (!data.success) { + message.error(data.message || '切换失败') + return + } + await loadRules() + } catch (error) { + message.error(`切换失败: ${error}`) + } + } + + async function handleDeleteRule(row) { + try { + const data = await deleteRule(String(row.id)) + if (!data.success) { + message.error(data.message || '删除失败') + return + } + message.success('删除成功') + await loadRules() + } catch (error) { + message.error(`删除失败: ${error}`) + } + } + + function resetFilters() { + filters.keyword = '' + filters.match_type = '' + filters.status = '' + loadRules() + } + + const ruleColumns = [ + { title: '关键词', key: 'keyword', minWidth: 140 }, + { title: '匹配方式', key: 'match_type', width: 120, render: (row) => row.match_type === 'equal' ? '完全匹配' : '包含' }, + { title: '回复内容', key: 'reply_text', minWidth: 220 }, + { + title: '状态', key: 'is_active', width: 110, + render: (row) => h(NTag, { type: Number(row.is_active) === 1 ? 'success' : 'default', bordered: false, round: true }, { + default: () => Number(row.is_active) === 1 ? '启用' : '暂停', + }), + }, + { + title: '操作', key: 'actions', width: 190, + render: (row) => h(NSpace, { size: 8 }, { + default: () => [ + h(NButton, { size: 'small', secondary: true, type: Number(row.is_active) === 1 ? 'warning' : 'success', onClick: () => handleToggleRule(row) }, { default: () => Number(row.is_active) === 1 ? '停用' : '启用' }), + h(NButton, { size: 'small', secondary: true, type: 'error', onClick: () => handleDeleteRule(row) }, { default: () => '删除' }), + ], + }), + }, + ] + + return { + loadingRules, + creatingRule, + showCreateRuleModal, + filters, + createForm, + filteredRules, + ruleColumns, + loadRules, + submitCreateRule, + resetFilters, + } +} diff --git a/frontend/src/composables/useSettings.js b/frontend/src/composables/useSettings.js new file mode 100644 index 0000000..677e8ce --- /dev/null +++ b/frontend/src/composables/useSettings.js @@ -0,0 +1,44 @@ +import { reactive } from 'vue' +import { getSettings, saveSettings as saveSettingsApi } from '../api/settings' + +export function useSettings(message) { + const settings = reactive({ + auto_reply_enabled: false, + listener_enabled: false, + listener_runtime_status: 'stopped', + full_auto_reply_enabled: false, + reply_fallback_mode: 'ai', + }) + + async function loadSettings(applyBotStatus) { + try { + const data = await getSettings() + if (!data.success) return + settings.auto_reply_enabled = !!data.auto_reply_enabled + settings.full_auto_reply_enabled = !!data.full_auto_reply_enabled + settings.reply_fallback_mode = data.reply_fallback_mode || 'ai' + applyBotStatus({ status: data.listener_runtime_status || 'stopped' }, data.listener_enabled) + } catch (error) { + message.error(`加载设置失败: ${error}`) + } + } + + async function saveSettings(payload, applyBotStatus) { + try { + const data = await saveSettingsApi(payload) + if (!data.success) { + message.error(data.message || '保存失败') + return + } + await loadSettings(applyBotStatus) + } catch (error) { + message.error(`保存失败: ${error}`) + } + } + + return { + settings, + loadSettings, + saveSettings, + } +} diff --git a/frontend/src/composables/useWindowBridge.js b/frontend/src/composables/useWindowBridge.js new file mode 100644 index 0000000..9022454 --- /dev/null +++ b/frontend/src/composables/useWindowBridge.js @@ -0,0 +1,94 @@ +import { ref } from 'vue' + +let tauriWindow = null +let tauriCore = null + +async function ensureTauriModules() { + if (tauriWindow && tauriCore) return true + if (!window.__TAURI_INTERNALS__) return false + try { + const [{ getCurrentWindow }, { invoke }] = await Promise.all([ + import('@tauri-apps/api/window'), + import('@tauri-apps/api/core'), + ]) + tauriWindow = getCurrentWindow() + tauriCore = { invoke } + return true + } catch { + return false + } +} + +export function useWindowBridge() { + const windowBridge = ref(null) + const bridgeMode = ref('browser') + + async function initWindowBridge() { + if (window.qt && window.QWebChannel) { + bridgeMode.value = 'qt' + new window.QWebChannel(window.qt.webChannelTransport, (channel) => { + windowBridge.value = channel.objects.windowBridge || null + }) + return + } + if (await ensureTauriModules()) { + bridgeMode.value = 'tauri' + return + } + bridgeMode.value = 'browser' + } + + async function invoke(methodName) { + const bridge = windowBridge.value + if (bridge && typeof bridge[methodName] === 'function') { + bridge[methodName]() + return + } + if (!(await ensureTauriModules())) return + if (methodName === 'start_move') { + await tauriWindow.startDragging() + return + } + if (methodName === 'minimize') { + await tauriWindow.minimize() + return + } + if (methodName === 'maximize_or_restore') { + const maximized = await tauriWindow.isMaximized() + if (maximized) { + await tauriWindow.unmaximize() + } else { + await tauriWindow.maximize() + } + return + } + if (methodName === 'close_window') { + await tauriWindow.close() + return + } + if (methodName === 'open_devtools') { + try { + await tauriCore.invoke('open_devtools') + } catch { + } + return + } + if (methodName === 'restart_app') { + try { + await tauriCore.invoke('restart_backend') + } catch { + } + } + } + + return { + bridgeMode, + initWindowBridge, + startMove: () => invoke('start_move'), + minimizeWindow: () => invoke('minimize'), + maximizeOrRestore: () => invoke('maximize_or_restore'), + closeWindow: () => invoke('close_window'), + openDevtools: () => invoke('open_devtools'), + restartApp: () => invoke('restart_app'), + } +} diff --git a/frontend/src/constants/messageColumns.js b/frontend/src/constants/messageColumns.js new file mode 100644 index 0000000..775dc11 --- /dev/null +++ b/frontend/src/constants/messageColumns.js @@ -0,0 +1,10 @@ +import { formatDateTime } from '../utils/datetime' + +export const messageColumns = [ + { title: '时间', key: 'created_at', width: 180, render: (row) => formatDateTime(row.created_at) }, + { title: '微信用户', key: 'wx_nickname', width: 180 }, + { title: '方向', key: 'direction', width: 90, render: (row) => row.direction === 'out' ? '发送' : '接收' }, + { title: '内容', key: 'content', minWidth: 320 }, + { title: '气泡方向', key: 'ocr_bubble_side', width: 100 }, + { title: '置信度', key: 'ocr_confidence', width: 90 }, +] diff --git a/frontend/src/constants/options.js b/frontend/src/constants/options.js new file mode 100644 index 0000000..34f6cdf --- /dev/null +++ b/frontend/src/constants/options.js @@ -0,0 +1,21 @@ +export const fallbackModeOptions = [ + { label: 'AI兜底回复', value: 'ai' }, + { label: '不回复', value: 'none' }, +] + +export const matchTypeOptions = [ + { label: '包含', value: 'contain' }, + { label: '完全匹配', value: 'equal' }, +] + +export const matchTypeFilterOptions = [ + { label: '全部匹配方式', value: '' }, + { label: '包含', value: 'contain' }, + { label: '完全匹配', value: 'equal' }, +] + +export const ruleStatusOptions = [ + { label: '全部状态', value: '' }, + { label: '启用', value: 1 }, + { label: '暂停', value: 0 }, +] diff --git a/frontend/src/main.js b/frontend/src/main.js new file mode 100644 index 0000000..3ac6bb7 --- /dev/null +++ b/frontend/src/main.js @@ -0,0 +1,33 @@ +import { createApp } from 'vue' +import { createDiscreteApi } from 'naive-ui' +import App from './App.vue' +import './styles.css' + +function loadQtWebChannelScript() { + return new Promise((resolve, reject) => { + if (window.QWebChannel) { + resolve() + return + } + const script = document.createElement('script') + script.src = 'qrc:///qtwebchannel/qwebchannel.js' + script.onload = () => resolve() + script.onerror = reject + document.head.appendChild(script) + }) +} + +async function bootstrap() { + if (window.qt && !window.QWebChannel) { + try { + await loadQtWebChannelScript() + } catch (_) { + } + } + + const { message } = createDiscreteApi(['message']) + window.$message = message + createApp(App).mount('#app') +} + +bootstrap() diff --git a/frontend/src/styles.css b/frontend/src/styles.css new file mode 100644 index 0000000..8b1af62 --- /dev/null +++ b/frontend/src/styles.css @@ -0,0 +1,299 @@ +:root { + --bg: #f2f4f7; + --panel: #ffffff; + --line: #e5e7eb; + --text: #111827; + --muted: #6b7280; + --brand: #22c1c3; +} + +* { + box-sizing: border-box; +} + +html, +body, +#app { + height: 100%; +} + +body { + margin: 0; + background: linear-gradient(180deg, #f5f7fb 0%, #eef2f7 100%); + color: var(--text); + font-family: Inter, "PingFang SC", "Microsoft YaHei", sans-serif; + overflow: hidden; +} + +button, +input, +select, +textarea { + font: inherit; +} + +.page-shell { + height: 100vh; + overflow: hidden; +} + +.content-root { + height: calc(100vh - 48px); + overflow: hidden; + display: flex; + flex-direction: column; +} + +.content-scroll { + flex: 1; + min-height: 0; + overflow: hidden; + display: flex; + flex-direction: column; +} + +.topbar { + height: 48px; + background: rgba(255, 255, 255, 0.92); + border-bottom: 1px solid var(--line); + backdrop-filter: blur(8px); + position: sticky; + top: 0; + z-index: 20; + user-select: none; +} + +.drag-region { + height: 100%; + width: 100%; + display: flex; + align-items: center; + justify-content: space-between; + cursor: default; +} + +.inner { + width: min(1320px, calc(100vw - 24px)); + margin: 0 auto; +} + +.window-actions { + display: flex; + align-items: center; + gap: 4px; +} + +.win-btn { + width: 32px; + height: 28px; + border-radius: 8px; + border: 1px solid #e7ecf2; + background: #fff; + color: #4b5563; + display: inline-flex; + align-items: center; + justify-content: center; + font-size: 14px; + line-height: 1; + cursor: pointer; +} + +.win-btn:hover { + background: #f5f7fb; +} + +.win-btn.close:hover { + background: #fee2e2; + color: #991b1b; + border-color: #fecaca; +} + +.panel { + background: var(--panel); + border: 1px solid #edf0f4; + border-radius: 14px; + box-shadow: 0 6px 18px rgba(15, 23, 42, 0.04); +} + +.hero { + background: linear-gradient(120deg, rgba(34, 193, 195, 0.15), rgba(124, 58, 237, 0.08)); + border: 1px solid #dff4f5; +} + +.tab-wrap { + flex: 1; + min-height: 0; + display: flex; + flex-direction: column; + background: #fff; + border: 1px solid #e8ecf2; + border-radius: 12px; + padding: 8px 12px 0; + box-shadow: 0 6px 14px rgba(15, 23, 42, 0.03); + overflow: hidden; +} + +.app-tabs, +.app-tabs .n-tabs-nav-scroll-content, +.app-tabs .n-tabs-pane-wrapper, +.app-tabs .n-tab-pane, +.app-tab-pane { + min-height: 0; +} + +.app-tabs { + flex: 1; + min-height: 0; + display: flex; + flex-direction: column; +} + +.app-tabs .n-tabs-nav { + flex: 0 0 auto; +} + +.app-tabs .n-tabs-pane-wrapper { + flex: 1; + min-height: 0; +} + +.app-tabs .n-tab-pane, +.app-tab-pane { + height: 100%; + display: flex; + flex-direction: column; +} + +.app-tab-pane > * { + flex: 1; + min-height: 0; +} + +.label-title { + font-weight: 600; + font-size: 14px; + color: #1f2937; +} + +.label-desc { + font-size: 12px; + color: #6b7280; + margin-top: 2px; +} + +.row-line { + border-bottom: 1px dashed #edf1f5; + padding: 14px 0; +} + +.row-line:last-child { + border-bottom: 0; +} + +.compact-card .n-card-header { + padding-bottom: 8px !important; +} + +.compact-card .n-card__content { + padding-top: 0 !important; +} + +.panel-view-shell { + flex: 1; + min-height: 0; + display: flex; + flex-direction: column; + gap: 16px; +} + +.logs-view-shell { + flex: 1; + min-height: 0; + padding: 12px 0; +} + +.log-panel { + flex: 1; + min-height: 0; + height: 100%; + display: flex; + flex-direction: column; +} + +.log-panel .n-card__content { + flex: 1; + min-height: 0; + height: 100%; + display: flex; + flex-direction: column; +} + +.log-panel .n-card-header { + flex: 0 0 auto; +} + +.log-toolbar { + display: flex; + align-items: center; + justify-content: space-between; + gap: 12px; + margin-bottom: 12px; + flex-wrap: wrap; +} + +.log-toolbar-right { + display: flex; + align-items: center; + gap: 12px; + min-width: 0; +} + +.log-path { + color: #6b7280; + font-size: 12px; + max-width: 520px; + overflow: hidden; + text-overflow: ellipsis; + white-space: nowrap; +} + +.log-stream-wrap { + height: clamp(320px, calc(100vh - 320px), 680px); + min-height: 320px; + max-height: 680px; + border: 1px solid #e6ebf2; + border-radius: 12px; + background: #0f172a; + overflow-y: auto; + overflow-x: hidden; +} + +.log-stream { + margin: 0; + padding: 14px 16px; + font-size: 12px; + line-height: 1.6; + white-space: pre-wrap; + word-break: break-word; + font-family: Consolas, "SFMono-Regular", Monaco, monospace; +} + +.log-line { + white-space: pre-wrap; +} + +.log-line--error { + color: #fca5a5; +} + +.log-line--warning { + color: #fde68a; +} + +.log-line--info { + color: #bfdbfe; +} + +.log-line--debug { + color: #cbd5e1; +} diff --git a/frontend/src/utils/datetime.js b/frontend/src/utils/datetime.js new file mode 100644 index 0000000..e2a13df --- /dev/null +++ b/frontend/src/utils/datetime.js @@ -0,0 +1,12 @@ +export function formatDateTime(value) { + if (!value) return '' + const d = new Date(value) + if (Number.isNaN(d.getTime())) return String(value) + const y = d.getFullYear() + const m = String(d.getMonth() + 1).padStart(2, '0') + const day = String(d.getDate()).padStart(2, '0') + const hh = String(d.getHours()).padStart(2, '0') + const mm = String(d.getMinutes()).padStart(2, '0') + const ss = String(d.getSeconds()).padStart(2, '0') + return `${y}-${m}-${day} ${hh}:${mm}:${ss}` +} diff --git a/frontend/src/views/LogsView.vue b/frontend/src/views/LogsView.vue new file mode 100644 index 0000000..f1c92bf --- /dev/null +++ b/frontend/src/views/LogsView.vue @@ -0,0 +1,228 @@ + + + diff --git a/frontend/src/views/MessagesView.vue b/frontend/src/views/MessagesView.vue new file mode 100644 index 0000000..cf589a5 --- /dev/null +++ b/frontend/src/views/MessagesView.vue @@ -0,0 +1,31 @@ + + + diff --git a/frontend/src/views/PanelView.vue b/frontend/src/views/PanelView.vue new file mode 100644 index 0000000..cb0bad8 --- /dev/null +++ b/frontend/src/views/PanelView.vue @@ -0,0 +1,115 @@ + + + diff --git a/frontend/src/views/RulesView.vue b/frontend/src/views/RulesView.vue new file mode 100644 index 0000000..3d1a91d --- /dev/null +++ b/frontend/src/views/RulesView.vue @@ -0,0 +1,76 @@ + + + diff --git a/frontend/vite.config.js b/frontend/vite.config.js new file mode 100644 index 0000000..bb747ed --- /dev/null +++ b/frontend/vite.config.js @@ -0,0 +1,17 @@ +import { defineConfig } from 'vite' +import vue from '@vitejs/plugin-vue' + +export default defineConfig({ + plugins: [vue()], + server: { + host: 'localhost', + port: 1420, + proxy: { + '/api': 'http://127.0.0.1:5000', + }, + }, + build: { + outDir: 'dist', + emptyOutDir: true, + }, +}) diff --git a/legacy/.htaccess b/legacy/.htaccess new file mode 100644 index 0000000..e69de29 diff --git a/legacy/README_BOT.md b/legacy/README_BOT.md new file mode 100644 index 0000000..8e70f92 --- /dev/null +++ b/legacy/README_BOT.md @@ -0,0 +1,143 @@ +# 微信 AI 自动回复机器人 - 安装使用指南 + +## 📦 安装依赖 + +```bash +pip install wcferry requests +``` + +## 🚀 快速开始 + +### 1. 启动 PHP 后端服务 +确保 phpstudy 已启动，访问 http://127.0.0.1/shiliu_ai/admin.html 确认后端正常 + +### 2. 登录微信 +在电脑上打开微信并登录（必须是 Windows 微信客户端） + +### 3. 运行机器人 +```bash +python wechat_bot.py +``` + +## ✨ 功能特性 + +### 新版本 (wechat_bot.py) - 推荐使用 ✅ +- ✅ 基于 WeChatFerry 框架 +- ✅ 无需 OCR，100% 准确识别消息 +- ✅ 不需要固定窗口位置 +- ✅ 自动回复私聊消息 +- ✅ 可选开启群聊回复 +- ✅ 支持 DeepSeek AI 智能回复 +- ✅ 支持关键词规则匹配 +- ✅ 所有消息记录到数据库 + +### 旧版本 (wechat_auto.py) - 已保留 +- 基于 OCR 识别 +- 需要固定窗口位置 +- 识别准确率较低 +- 仅供参考学习 + +### 手动测试版 (wechat_manual.py) +- 手动输入消息测试 AI 回复 +- 用于调试和测试 + +## ⚙️ 配置说明 + +### 修改 wechat_bot.py 中的配置： + +```python +# PHP 后端接口地址 +BACKEND_URL = "http://127.0.0.1/shiliu_ai/api_receive_message.php" + +# 是否自动回复群聊（默认只回复私聊） +ENABLE_GROUP_REPLY = False # 改为 True 可开启群聊回复 +``` + +### 修改 config.php 配置 AI： + +```php +// 选择 AI 提供商：mock / openai / deepseek +define('AI_PROVIDER', 'deepseek'); + +// DeepSeek API 配置 +define('DEEPSEEK_API_KEY', '你的API密钥'); +define('DEEPSEEK_API_BASE', 'https://api.deepseek.com'); +define('DEEPSEEK_MODEL', 'deepseek-chat'); +``` + +## 📝 使用流程 + +1. **接收消息** → 机器人自动监听微信消息 +2. **规则匹配** → 先检查是否有关键词规则 +3. **AI 回复** → 没有规则则调用 DeepSeek 生成回复 +4. **自动发送** → 将回复发送给用户 +5. **记录保存** → 所有消息保存到数据库 + +## 🎯 管理后台 + +访问 http://127.0.0.1/shiliu_ai/admin.html 可以： +- 查看消息记录 +- 管理自动回复规则 +- 配置系统设置 + +## 🔧 常见问题 + +### Q: 提示 "WeChatFerry 初始化失败" +**A:** 确保： +1. 微信已经登录 +2. 已安装 wcferry: `pip install wcferry` +3. 使用的是 Windows 微信客户端 + +### Q: 机器人没有回复 +**A:** 检查： +1. PHP 后端是否正常运行 +2. 查看日志文件 `wechat_bot.log` +3. 确认 DeepSeek API Key 是否正确 + +### Q: 想要回复群聊消息 +**A:** 修改 `wechat_bot.py` 中的配置： +```python +ENABLE_GROUP_REPLY = True +``` + +### Q: 如何添加关键词规则 +**A:** 访问管理后台 admin.html，在"自动回复规则"中添加 + +## 📂 文件说明 + +``` +shiliu_ai/ +├── wechat_bot.py # 新版机器人（推荐使用）⭐ +├── wechat_auto.py # 旧版 OCR 机器人（已保留） +├── wechat_manual.py # 手动测试工具 +├── config.php # 配置文件 +├── ai_helper.php # AI 调用逻辑 +├── api_receive_message.php # 消息接收接口 +├── admin.html # 管理后台 +├── database.sql # 数据库结构 +└── wechat_bot.log # 运行日志 +``` + +## 🎉 开始使用 + +```bash +# 1. 安装依赖 +pip install wcferry requests + +# 2. 确保微信已登录 + +# 3. 启动机器人 +python wechat_bot.py + +# 4. 发送消息测试 +``` + +## 📞 技术支持 + +如有问题，请查看日志文件： +- `wechat_bot.log` - 机器人运行日志 +- `wechat_auto.log` - 旧版机器人日志（如果使用） + +--- + +**祝使用愉快！🎊** diff --git a/legacy/ai_helper.php b/legacy/ai_helper.php new file mode 100644 index 0000000..cd47ece --- /dev/null +++ b/legacy/ai_helper.php @@ -0,0 +1,310 @@ +query($sql); + $rules = $stmt->fetchAll(); + + $contentLower = mb_strtolower($content, 'UTF-8'); + error_log("=== 规则匹配开始 ==="); + error_log("用户消息原文: '{$content}'"); + error_log("转小写后: '{$contentLower}'"); + error_log("规则总数: " . count($rules)); + + foreach ($rules as $rule) { + $keyword = trim((string)$rule['keyword']); + if ($keyword === '') { + error_log("规则ID {$rule['id']}: 关键词为空，跳过"); + continue; + } + $kwLower = mb_strtolower($keyword, 'UTF-8'); + error_log("规则ID {$rule['id']}: 关键词='{$keyword}', 小写='{$kwLower}', 类型={$rule['match_type']}"); + + if ($rule['match_type'] === 'equal') { + if ($contentLower === $kwLower) { + error_log("✓ 完全匹配成功！返回规则ID {$rule['id']}"); + return $rule; + } else { + error_log("✗ 完全匹配失败: '{$contentLower}' !== '{$kwLower}'"); + } + } else { // contain + if (mb_strpos($contentLower, $kwLower, 0, 'UTF-8') !== false) { + error_log("✓ 包含匹配成功！返回规则ID {$rule['id']}"); + return $rule; + } else { + error_log("✗ 包含匹配失败"); + } + } + } + + error_log("未找到任何匹配规则"); + error_log("=== 规则匹配结束 ==="); + return null; +} + +/** + * 简单系统配置读取 / 写入 + */ +function get_setting(string $key, $default = null) +{ + $pdo = get_pdo(); + $stmt = $pdo->prepare("SELECT `value` FROM settings WHERE `key` = :k LIMIT 1"); + $stmt->execute([':k' => $key]); + $row = $stmt->fetch(); + if (!$row) { + return $default; + } + return $row['value']; +} + +function set_setting(string $key, string $value): void +{ + $pdo = get_pdo(); + $stmt = $pdo->prepare(" + INSERT INTO settings(`key`, `value`, updated_at) + VALUES(:k, :v, NOW()) + ON DUPLICATE KEY UPDATE `value` = VALUES(`value`), updated_at = NOW() + "); + $stmt->execute([':k' => $key, ':v' => $value]); +} + +/** + * 调用大模型 API（这里以 OpenAI 为例） + * 如你用国内模型，可在此处替换调用逻辑。 + */ +function call_ai(string $prompt, string $userId = ''): string +{ + error_log("=== 调用AI开始 ==="); + error_log("用户消息: '{$prompt}'"); + error_log("AI提供商: " . AI_PROVIDER); + + if (AI_PROVIDER === 'mock') { + return '【自动回复】你刚才说了：' . mb_substr($prompt, 0, 100, 'UTF-8'); + } + + // OpenAI 兼容接口 + if (AI_PROVIDER === 'openai') { + $url = rtrim(OPENAI_API_BASE, '/') . '/chat/completions'; + $headers = [ + 'Content-Type: application/json', + 'Authorization: ' . 'Bearer ' . OPENAI_API_KEY, + ]; + + $payload = [ + 'model' => OPENAI_MODEL, + 'messages' => [ + [ + 'role' => 'system', + 'content' => '你是一个专业的微信私域运营助手，用简洁自然的中文回复用户。', + ], + [ + 'role' => 'user', + 'content' => $prompt, + ], + ], + 'temperature' => 0.7, + 'user' => $userId ?: null, + ]; + + return do_llm_request($url, $headers, $payload); + } + + // DeepSeek（OpenAI 兼容风格） + if (AI_PROVIDER === 'deepseek') { + $url = rtrim(DEEPSEEK_API_BASE, '/') . '/chat/completions'; + error_log("请求URL: {$url}"); + $headers = [ + 'Content-Type: application/json', + 'Authorization: Bearer ' . DEEPSEEK_API_KEY, + ]; + + $payload = [ + 'model' => DEEPSEEK_MODEL, + 'messages' => [ + [ + 'role' => 'system', + 'content' => '你是一个简洁高效的微信助手。回复要求：1.一句话回答，不超过50字 2.不要啰嗦重复 3.直接回答问题，不要客套话 4.不要使用emoji表情', + ], + [ + 'role' => 'user', + 'content' => $prompt, + ], + ], + 'temperature' => 0.7, + 'max_tokens' => 100, // 限制回复长度 + 'user' => $userId ?: null, + ]; + + return do_llm_request($url, $headers, $payload); + } + + // Dify（对话型应用） + if (AI_PROVIDER === 'dify') { + $url = rtrim(DIFY_API_BASE, '/') . '/chat-messages'; + error_log("请求URL: {$url}"); + $headers = [ + 'Content-Type: application/json', + 'Authorization: Bearer ' . DIFY_API_KEY, + ]; + + $payload = [ + 'inputs' => (object)[], + 'query' => $prompt, + 'response_mode' => 'streaming', + 'user' => $userId ?: DIFY_USER, + 'conversation_id' => '', + ]; + + error_log("Dify payload: " . json_encode($payload, JSON_UNESCAPED_UNICODE)); + return do_dify_request($url, $headers, $payload); + } + + // 其他厂商可在此扩展 + return 'AI_PROVIDER 未配置正确，请检查 config.php。'; +} + +/** + * Dify 专用请求封装 + */ +function do_dify_request(string $url, array $headers, array $payload): string +{ + $ch = curl_init($url); + curl_setopt($ch, CURLOPT_HTTPHEADER, $headers); + curl_setopt($ch, CURLOPT_POST, true); + curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload, JSON_UNESCAPED_UNICODE)); + curl_setopt($ch, CURLOPT_RETURNTRANSFER, true); + curl_setopt($ch, CURLOPT_TIMEOUT, 60); // 增加超时时间，支持streaming + curl_setopt($ch, CURLOPT_SSL_VERIFYPEER, false); + curl_setopt($ch, CURLOPT_SSL_VERIFYHOST, false); + curl_setopt($ch, CURLOPT_BUFFERSIZE, 128); // 小缓冲区，支持流式读取 + curl_setopt($ch, CURLOPT_NOPROGRESS, false); // 允许进度回调 + + $response = curl_exec($ch); + if ($response === false) { + $err = curl_error($ch); + curl_close($ch); + error_log("cURL错误: {$err}"); + return '抱歉，Dify 服务暂时不可用，请稍后再试～（网络错误：' . $err . '）'; + } + $statusCode = curl_getinfo($ch, CURLINFO_HTTP_CODE); + curl_close($ch); + + error_log("HTTP状态码: {$statusCode}"); + error_log("响应内容长度: " . strlen($response)); + error_log("响应内容: {$response}"); + + // 处理空响应 + if (empty($response)) { + error_log("Dify返回空响应"); + return '抱歉，Dify 服务返回空响应，请检查API配置。'; + } + + // 处理streaming模式的响应（SSE格式） + if (strpos($response, 'data:') !== false || strpos($response, 'event:') !== false) { + error_log("检测到streaming模式响应"); + $lines = explode("\n", $response); + $fullAnswer = ''; + + foreach ($lines as $line) { + $line = trim($line); + if (strpos($line, 'data:') === 0) { + $jsonStr = trim(substr($line, 5)); + if (empty($jsonStr) || $jsonStr === '[DONE]') { + continue; + } + + $data = json_decode($jsonStr, true); + if (json_last_error() === JSON_ERROR_NONE) { + // Dify streaming格式：{"event":"message","answer":"内容"} + if (isset($data['answer'])) { + $fullAnswer .= $data['answer']; + } + // 或者 {"event":"agent_message","answer":"内容"} + if (isset($data['event']) && $data['event'] === 'agent_message' && isset($data['answer'])) { + $fullAnswer .= $data['answer']; + } + } + } + } + + if (!empty($fullAnswer)) { + error_log("Dify回复(streaming): {$fullAnswer}"); + error_log("=== 调用AI结束 ==="); + return trim($fullAnswer); + } + } + + // 处理blocking模式的响应（JSON格式） + $data = json_decode($response, true); + if ($statusCode >= 400 || !is_array($data)) { + $msg = $data['message'] ?? '未知错误'; + error_log("Dify API错误: {$msg}"); + return '抱歉，Dify 服务请求失败，请稍后再试～（状态码 ' . $statusCode . '：' . $msg . '）'; + } + + // Dify 返回格式：{"answer": "回复内容", "conversation_id": "xxx"} + $content = $data['answer'] ?? ''; + if (!$content) { + error_log("Dify返回内容为空"); + error_log("完整响应: " . print_r($data, true)); + return '抱歉，Dify 暂时没有合理的回复。'; + } + error_log("Dify回复(blocking): {$content}"); + error_log("=== 调用AI结束 ==="); + return trim($content); +} + +/** + * 通用大模型 HTTP 请求封装 + */ +function do_llm_request(string $url, array $headers, array $payload): string +{ + $ch = curl_init($url); + curl_setopt($ch, CURLOPT_HTTPHEADER, $headers); + curl_setopt($ch, CURLOPT_POST, true); + curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload, JSON_UNESCAPED_UNICODE)); + curl_setopt($ch, CURLOPT_RETURNTRANSFER, true); + curl_setopt($ch, CURLOPT_TIMEOUT, 60); // 增加超时时间，支持streaming + curl_setopt($ch, CURLOPT_SSL_VERIFYPEER, false); + curl_setopt($ch, CURLOPT_SSL_VERIFYHOST, false); + curl_setopt($ch, CURLOPT_BUFFERSIZE, 128); // 小缓冲区，支持流式读取 + curl_setopt($ch, CURLOPT_NOPROGRESS, false); // 允许进度回调 + + $response = curl_exec($ch); + if ($response === false) { + $err = curl_error($ch); + curl_close($ch); + error_log("cURL错误: {$err}"); + return '抱歉，AI 服务暂时不可用，请稍后再试～（网络错误：' . $err . '）'; + } + $statusCode = curl_getinfo($ch, CURLINFO_HTTP_CODE); + curl_close($ch); + + error_log("HTTP状态码: {$statusCode}"); + error_log("响应内容: {$response}"); + + $data = json_decode($response, true); + if ($statusCode >= 400 || !is_array($data)) { + $msg = $data['error']['message'] ?? '未知错误'; + error_log("API错误: {$msg}"); + return '抱歉，AI 服务请求失败，请稍后再试～（状态码 ' . $statusCode . '：' . $msg . '）'; + } + + $content = $data['choices'][0]['message']['content'] ?? 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'')); +$wxUserId = trim((string)($data['wx_user_id'] ?? '')); +$wxNickname = trim((string)($data['wx_nickname'] ?? '')); +$isFriendRequest = (int)($data['is_friend_request'] ?? 0); + +if ($content === '' && !$isFriendRequest) { + json_response(['error' => 'content is empty'], 400); +} + +try { + $pdo = get_pdo(); + $pdo->beginTransaction(); + + // 记录收到的消息 + $stmt = $pdo->prepare(" + INSERT INTO messages (wx_user_id, wx_nickname, direction, content, is_friend_request, created_at) + VALUES (:uid, :nick, 'in', :content, :fr, NOW()) + "); + $stmt->execute([ + ':uid' => $wxUserId, + ':nick' => $wxNickname, + ':content' => $content, + ':fr' => $isFriendRequest, + ]); + $inMsgId = (int)$pdo->lastInsertId(); + + $autoOn = get_setting('auto_reply_enabled', '1') === '1'; + $replyText = ''; + $usedRuleId = null; + + if ($autoOn) { + // 先规则匹配 + $rule = find_rule_reply($content); + if ($rule) { + $replyText = (string)$rule['reply_text']; + $usedRuleId = (int)$rule['id']; + // 调试信息 + error_log("匹配到规则ID: {$usedRuleId}, 关键词: {$rule['keyword']}, 回复: {$replyText}"); + } else { + // 没有规则就走 AI + error_log("未匹配到规则，调用AI，用户消息: {$content}"); + $replyText = call_ai($content, $wxUserId); + error_log("AI返回: {$replyText}"); + } + } + + $shouldReply = $autoOn && $replyText !== ''; + $replyMsgId = null; + + if ($shouldReply) { + $stmt2 = $pdo->prepare(" + INSERT INTO messages (wx_user_id, wx_nickname, direction, content, is_ai_reply, rule_id, created_at) + VALUES (:uid, :nick, 'out', :content, :is_ai, :rule_id, NOW()) + "); + $stmt2->execute([ + ':uid' => $wxUserId, + ':nick' => $wxNickname, + ':content' => $replyText, + ':is_ai' => 1, + ':rule_id' => $usedRuleId, + ]); + $replyMsgId = (int)$pdo->lastInsertId(); + } + + $pdo->commit(); + + json_response([ + 'success' => true, + 'should_reply' => $shouldReply, + 'reply_text' => $replyText, + 'in_message_id' => $inMsgId, + 'reply_message_id' => $replyMsgId, + ]); +} catch (Throwable $e) { + if (isset($pdo) && $pdo->inTransaction()) { + $pdo->rollBack(); + } + json_response(['error' => 'server_error', 'message' => $e->getMessage()], 500); +} + + diff --git a/legacy/api_rules.php b/legacy/api_rules.php new file mode 100644 index 0000000..27997dc --- /dev/null +++ b/legacy/api_rules.php @@ -0,0 +1,99 @@ +query("SELECT * FROM auto_reply_rules ORDER BY id DESC"); + $rules = $stmt->fetchAll(); + json_response(['success' => true, 'data' => $rules]); + break; + + case 'create': + $keyword = trim((string)($_POST['keyword'] ?? '')); + $matchType = $_POST['match_type'] ?? 'contain'; + $replyText = trim((string)($_POST['reply_text'] ?? '')); + $isActive = (int)($_POST['is_active'] ?? 1); + + if ($keyword === '' || $replyText === '') { + json_response(['success' => false, 'message' => '关键词和回复内容不能为空']); + } + + if (!in_array($matchType, ['contain', 'equal'], true)) { + $matchType = 'contain'; + } + + $stmt = $pdo->prepare(" + INSERT INTO auto_reply_rules(keyword, match_type, reply_text, is_active, created_at, updated_at) + VALUES(:kw, :mt, :rt, :act, NOW(), NOW()) + "); + $stmt->execute([ + ':kw' => $keyword, + ':mt' => $matchType, + ':rt' => $replyText, + ':act' => $isActive, + ]); + json_response(['success' => true]); + break; + + case 'toggle': + $id = (int)($_POST['id'] ?? 0); + $isActive = (int)($_POST['is_active'] ?? 0); + if ($id <= 0) { + json_response(['success' => false, 'message' => '参数错误']); + } + $stmt = $pdo->prepare("UPDATE auto_reply_rules SET is_active = :act, updated_at = NOW() WHERE id = :id"); + $stmt->execute([':act' => $isActive, ':id' => $id]); + json_response(['success' => true]); + break; + + case 'delete': + $id = (int)($_POST['id'] ?? 0); + if ($id <= 0) { + json_response(['success' => false, 'message' => '参数错误']); + } + $stmt = $pdo->prepare("DELETE FROM auto_reply_rules WHERE id = :id"); + $stmt->execute([':id' => $id]); + json_response(['success' => true]); + break; + + case 'settings_get': + $autoOn = get_setting('auto_reply_enabled', '1'); + json_response(['success' => true, 'auto_reply_enabled' => $autoOn === '1']); + break; + + case 'settings_set': + $autoOn = ($_POST['auto_reply_enabled'] ?? '1') === '1' ? '1' : '0'; + set_setting('auto_reply_enabled', $autoOn); + json_response(['success' => true]); + break; + + case 'messages_recent': + $limit = max(1, min(100, (int)($_GET['limit'] ?? 50))); + $stmt = $pdo->prepare(" + SELECT * FROM messages + ORDER BY id DESC + LIMIT :lim + "); + $stmt->bindValue(':lim', $limit, PDO::PARAM_INT); + $stmt->execute(); + $rows = $stmt->fetchAll(); + json_response(['success' => true, 'data' => $rows]); + break; + + default: + json_response(['success' => false, 'message' => '未知操作']); + } +} catch (Throwable $e) { + json_response(['success' => false, 'message' => $e->getMessage()]); +} + + diff --git a/legacy/config.php b/legacy/config.php new file mode 100644 index 0000000..0569e29 --- /dev/null +++ b/legacy/config.php @@ -0,0 +1,44 @@ + PDO::ERRMODE_EXCEPTION, + PDO::ATTR_DEFAULT_FETCH_MODE => PDO::FETCH_ASSOC, + PDO::ATTR_EMULATE_PREPARES => false, + ]; + + $pdo = new PDO($dsn, DB_USER, DB_PASS, $options); + return $pdo; +} + + diff --git a/legacy/install_ocr.bat b/legacy/install_ocr.bat new file mode 100644 index 0000000..18cb19b --- /dev/null +++ b/legacy/install_ocr.bat @@ -0,0 +1,33 @@ +@echo off +chcp 65001 +echo ======================================== +echo 安装OCR微信机器人依赖 +echo ======================================== +echo. + +echo [1/5] 安装基础依赖... +pip install pillow pyautogui pyperclip opencv-python numpy requests -i https://pypi.tuna.tsinghua.edu.cn/simple + +echo. +echo [2/5] 安装PaddleOCR（推荐，准确率最高）... +pip install paddlepaddle paddleocr -i https://pypi.tuna.tsinghua.edu.cn/simple + +echo. +echo [3/5] 备用：安装EasyOCR... +pip install easyocr -i https://pypi.tuna.tsinghua.edu.cn/simple + +echo. +echo [4/5] 安装键盘控制库... +pip install keyboard -i https://pypi.tuna.tsinghua.edu.cn/simple + +echo. +echo ======================================== +echo 安装完成！ +echo ======================================== +echo. +echo 使用方法： +echo 1. 打开微信并登录 +echo 2. 打开要自动回复的聊天窗口 +echo 3. 运行: python wechat_bot_fixed.py +echo. +pause diff --git a/legacy/install_wechat_bot.bat b/legacy/install_wechat_bot.bat new file mode 100644 index 0000000..9584abf --- /dev/null +++ b/legacy/install_wechat_bot.bat @@ -0,0 +1,37 @@ +@echo off +chcp 65001 +echo ======================================== +echo 安装微信自动回复依赖 +echo ======================================== +echo. + +echo [1/3] 安装UI自动化库（推荐）... +pip install uiautomation pyperclip requests -i https://pypi.tuna.tsinghua.edu.cn/simple + +echo. +echo [2/3] 安装OCR版本依赖（备用）... +pip install opencv-python numpy pillow pyautogui -i https://pypi.tuna.tsinghua.edu.cn/simple + +echo. +echo [3/3] 安装PaddleOCR（可选）... +pip install paddleocr -i https://pypi.tuna.tsinghua.edu.cn/simple + +echo. +echo ======================================== +echo 安装完成！ +echo ======================================== +echo. +echo 使用方法： +echo. +echo 方案1：UI自动化版（推荐） +echo - 无需OCR，直接读取微信UI +echo - 不受窗口位置影响 +echo - 识别准确率100%% +echo 运行: python wechat_ui_bot.py +echo. +echo 方案2：OCR识别版（备用） +echo - 使用图像识别 +echo - 需要固定窗口位置 +echo 运行: python wechat_auto.py +echo. +pause diff --git a/legacy/nginx.htaccess b/legacy/nginx.htaccess new file mode 100644 index 0000000..cc2badf --- /dev/null +++ b/legacy/nginx.htaccess @@ -0,0 +1,6 @@ +location / { + if (!-e $request_filename) { + rewrite ^(.*)$ /index.php?s=$1 last; + break; + } +} \ No newline at end of file diff --git a/legacy/run_all.py b/legacy/run_all.py new file mode 100644 index 0000000..34933fc --- /dev/null +++ b/legacy/run_all.py @@ -0,0 +1,31 @@ +import os +import time +import threading +import webbrowser + +import py_backend +from wechat_multi_chat_bot import WechatMultiChatBot + +HOST = os.getenv("APP_HOST", "127.0.0.1") +PORT = int(os.getenv("APP_PORT", "5000")) +OPEN_BROWSER = os.getenv("OPEN_BROWSER", "1") == "1" + + +def run_backend(): + py_backend.start_backend(host=HOST, port=PORT) + + +def run_bot(): + bot = WechatMultiChatBot() + bot.run_forever() + + +if __name__ == "__main__": + backend_thread = threading.Thread(target=run_backend, daemon=True) + backend_thread.start() + + time.sleep(1.5) + if OPEN_BROWSER: + webbrowser.open(f"http://{HOST}:{PORT}/admin.html") + + run_bot() diff --git a/legacy/test_dify.php b/legacy/test_dify.php new file mode 100644 index 0000000..7ef87fd --- /dev/null +++ b/legacy/test_dify.php @@ -0,0 +1,57 @@ + (object)[], // 空对象 + 'query' => '你好', + 'response_mode' => 'blocking', + 'user' => DIFY_USER, +]; + +echo "请求数据:\n"; +echo json_encode($payload, JSON_UNESCAPED_UNICODE | JSON_PRETTY_PRINT) . "\n\n"; + +$ch = curl_init($url); +curl_setopt($ch, CURLOPT_HTTPHEADER, $headers); +curl_setopt($ch, CURLOPT_POST, true); +curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload, JSON_UNESCAPED_UNICODE)); +curl_setopt($ch, CURLOPT_RETURNTRANSFER, true); +curl_setopt($ch, CURLOPT_TIMEOUT, 30); +curl_setopt($ch, CURLOPT_SSL_VERIFYPEER, false); +curl_setopt($ch, CURLOPT_SSL_VERIFYHOST, false); + +echo "发送请求...\n"; +$response = curl_exec($ch); +$statusCode = curl_getinfo($ch, CURLINFO_HTTP_CODE); +curl_close($ch); + +echo "HTTP状态码: {$statusCode}\n"; +echo "响应内容:\n"; +echo $response . "\n\n"; + +if ($statusCode == 200) { + $data = json_decode($response, true); + if (isset($data['answer'])) { + echo "✓ 成功！AI回复: " . $data['answer'] . "\n"; + } else { + echo "✗ 响应格式错误\n"; + } +} else { + echo "✗ 请求失败\n"; +} diff --git a/legacy/test_dify_v2.php b/legacy/test_dify_v2.php new file mode 100644 index 0000000..8ae0d6e --- /dev/null +++ b/legacy/test_dify_v2.php @@ -0,0 +1,81 @@ + (object)[], // 空对象 + 'query' => '你好', + 'response_mode' => 'blocking', + 'user' => DIFY_USER, +]; + +echo "请求数据:\n"; +echo json_encode($payload, JSON_UNESCAPED_UNICODE | JSON_PRETTY_PRINT) . "\n\n"; + +$ch = curl_init($url); +curl_setopt($ch, CURLOPT_HTTPHEADER, $headers); +curl_setopt($ch, CURLOPT_POST, true); +curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload, JSON_UNESCAPED_UNICODE)); +curl_setopt($ch, CURLOPT_RETURNTRANSFER, true); +curl_setopt($ch, CURLOPT_TIMEOUT, 30); +curl_setopt($ch, CURLOPT_SSL_VERIFYPEER, false); +curl_setopt($ch, CURLOPT_SSL_VERIFYHOST, false); +curl_setopt($ch, CURLOPT_VERBOSE, true); // 开启详细输出 + +echo "发送请求...\n"; +$response = curl_exec($ch); +$statusCode = curl_getinfo($ch, CURLINFO_HTTP_CODE); +$error = curl_error($ch); +curl_close($ch); + +echo "HTTP状态码: {$statusCode}\n"; +echo "响应内容长度: " . strlen($response) . " 字节\n"; + +if ($error) { + echo "cURL错误: {$error}\n"; +} + +echo "\n响应内容:\n"; +if (empty($response)) { + echo "(空响应)\n\n"; +} else { + echo $response . "\n\n"; +} + +if ($statusCode == 200) { + if (empty($response)) { + echo "✗ 响应为空\n\n"; + echo "可能的原因：\n"; + echo "1. Dify应用未发布或已停用\n"; + echo "2. API Key不正确\n"; + echo "3. response_mode='blocking' 不支持（试试改成 'streaming'）\n"; + echo "4. Dify服务器问题\n"; + } else { + $data = json_decode($response, true); + if (json_last_error() !== JSON_ERROR_NONE) { + echo "✗ JSON解析失败: " . json_last_error_msg() . "\n"; + } elseif (isset($data['answer'])) { + echo "✓ 成功！AI回复: " . $data['answer'] . "\n"; + } else { + echo "✗ 响应格式错误\n"; + echo "JSON内容: " . print_r($data, true) . "\n"; + } + } +} else { + echo "✗ 请求失败（HTTP {$statusCode}）\n"; +} diff --git a/legacy/wechat_bot_optimized.py b/legacy/wechat_bot_optimized.py new file mode 100644 index 0000000..fcc1f4e --- /dev/null +++ b/legacy/wechat_bot_optimized.py @@ -0,0 +1,486 @@ +#!/usr/bin/env python +# -*- coding: utf-8 -*- +""" +微信自动回复机器人 - 优化版 +整合开源项目优点： +1. 快速红点检测（numpy矩阵运算，比逐像素快100倍） +2. 智能区域过滤（只检测特定X坐标范围） +3. 性能统计（详细的耗时分析） +""" + +import os +import time +import hashlib +import logging +import base64 +from datetime import datetime +from io import BytesIO +import cv2 +import numpy as np + +import requests +import pyperclip +import pyautogui +from PIL import ImageGrab +import uiautomation as auto + +# ========== 配置 ========== + +BAIDU_API_KEY = "ElIQN30iAqpEGi9zv0VlrtQX" +BAIDU_SECRET_KEY = "7wrO2wDTx7FehuelgG0NCBDFOklnqSz0" +BACKEND_URL = "http://127.0.0.1/shiliu_ai/api_receive_message.php" +LOOP_INTERVAL = 3 + +# 红点检测配置（借鉴开源项目的精确检测） +RED_DOT_CONFIG = { + 'target_color_bgr': np.array([81, 81, 255]), # 微信红点BGR颜色 + 'color_tolerance': 10, # 颜色容差 + 'x_range': (60, 200), # 检测区域X坐标范围 +} + +NO_REPLY_KEYWORDS = [ + "谢谢", "好的", "嗯", "哦", "ok", "收到", + "[图片]", "[语音]", "[视频]", "[文件]" +] + +# ========== 日志 ========== + +logging.basicConfig( + level=logging.INFO, + format="%(asctime)s - %(levelname)s - %(message)s", + handlers=[ + logging.FileHandler("wechat_bot_optimized.log", encoding="utf-8"), + logging.StreamHandler() + ], +) +logger = logging.getLogger(__name__) + +# ========== OCR类 ========== + +class BaiduOCR: + """百度OCR识别""" + + def __init__(self): + self.access_token = self._get_access_token() + logger.info("✓ 百度OCR初始化成功") + + def _get_access_token(self): + url = "https://aip.baidubce.com/oauth/2.0/token" + params = { + "grant_type": "client_credentials", + "client_id": BAIDU_API_KEY, + "client_secret": BAIDU_SECRET_KEY + } + response = requests.post(url, params=params) + return response.json().get("access_token") + + def recognize(self, image_bytes): + url = f"https://aip.baidubce.com/rest/2.0/ocr/v1/general_basic?access_token={self.access_token}" + + payload = { + 'image': base64.b64encode(image_bytes).decode('utf-8'), + 'detect_direction': 'false', + 'paragraph': 'false', + 'probability': 'false' + } + + headers = { + 'Content-Type': 'application/x-www-form-urlencoded', + 'Accept': 'application/json' + } + + response = requests.post(url, headers=headers, data=payload) + result = response.json() + + if 'words_result' in result: + return [item['words'] for item in result['words_result']] + return [] + +# ========== 微信机器人类（优化版）========== + +class WechatBotOptimized: + """微信自动回复机器人 - 优化版""" + + def __init__(self): + self.ocr = BaiduOCR() + self.processed_messages = {} + self.running = False + self.performance_stats = { + 'red_dot_detect': [], + 'ocr_recognize': [], + 'total_process': [] + } + + def get_window_rect(self): + """获取微信窗口位置""" + try: + wechat_window = auto.WindowControl(searchDepth=1, Name="微信") + if wechat_window.Exists(0, 0): + rect = wechat_window.BoundingRectangle + return { + 'left': rect.left, + 'top': rect.top, + 'right': rect.right, + 'bottom': rect.bottom, + 'width': rect.right - rect.left, + 'height': rect.bottom - rect.top + } + except Exception as e: + logger.error(f"获取窗口失败: {e}") + return None + + def get_contact_list_rect(self, window_rect): + """获取联系人列表区域""" + left = window_rect['left'] + 10 + top = window_rect['top'] + 50 + right = window_rect['left'] + int(window_rect['width'] * 0.25) - 10 + bottom = window_rect['bottom'] - 50 + + return { + 'left': left, + 'top': top, + 'right': right, + 'bottom': bottom + } + + def detect_red_dots_fast(self, window_rect): + """ + 快速红点检测（借鉴开源项目） + 使用numpy矩阵运算，比逐像素遍历快100倍 + """ + start_time = time.time() + contact_rect = self.get_contact_list_rect(window_rect) + + try: + # 截图 + screenshot = ImageGrab.grab(bbox=( + contact_rect['left'], contact_rect['top'], + contact_rect['right'], contact_rect['bottom'] + )) + + # 转换为numpy数组（BGR格式） + img_np = np.array(screenshot) + img_bgr = cv2.cvtColor(img_np, cv2.COLOR_RGB2BGR) + + # 获取配置 + target_color = RED_DOT_CONFIG['target_color_bgr'] + tolerance = RED_DOT_CONFIG['color_tolerance'] + x_range = RED_DOT_CONFIG['x_range'] + + # 生成坐标网格（性能优化关键！） + height, width = img_bgr.shape[:2] + x_coords, y_coords = np.meshgrid( + np.arange(width), + np.arange(height) + ) + + # 颜色匹配（矩阵运算，比循环快100倍） + lower_bound = target_color - tolerance + upper_bound = target_color + tolerance + color_mask = np.all((lower_bound <= img_bgr) & (img_bgr <= upper_bound), axis=-1) + + # 区域过滤（只检测特定X坐标范围） + region_mask = (x_coords >= x_range[0]) & (x_coords <= x_range[1]) + + # 获取候选坐标 + matched_points = np.column_stack(( + x_coords[color_mask & region_mask], + y_coords[color_mask & region_mask] + )) + + if matched_points.size == 0: + return [] + + # 按Y坐标分组（同一联系人的多个红点合并） + red_dots = [] + used = set() + + for i, point in enumerate(matched_points): + if i in used: + continue + + # 找到Y坐标相近的点 + group = [point] + for j, other in enumerate(matched_points): + if j != i and j not in used: + if abs(point[1] - other[1]) < 50: + group.append(other) + used.add(j) + + # 计算平均位置 + avg_x = int(np.mean([p[0] for p in group])) + avg_y = int(np.mean([p[1] for p in group])) + + red_dots.append({ + 'x': contact_rect['left'] + avg_x, + 'y': contact_rect['top'] + avg_y + }) + used.add(i) + + # 记录性能 + elapsed = time.time() - start_time + self.performance_stats['red_dot_detect'].append(elapsed) + + return red_dots + + except Exception as e: + logger.error(f"红点检测失败: {e}") + return [] + + def click_contact_by_red_dot(self, red_dot, window_rect): + """点击联系人""" + contact_rect = self.get_contact_list_rect(window_rect) + + click_x = (contact_rect['left'] + contact_rect['right']) // 2 + click_y = red_dot['y'] + + pyautogui.click(click_x, click_y) + time.sleep(2.5) + + logger.info(f"点击联系人位置: ({click_x}, {click_y})") + + def get_latest_message_area(self, window_rect): + """获取最新消息区域""" + chat_left = window_rect['left'] + int(window_rect['width'] * 0.30) + chat_right = window_rect['right'] - 20 + chat_top = window_rect['top'] + int(window_rect['height'] * 0.15) + chat_bottom = window_rect['bottom'] - int(window_rect['height'] * 0.20) + + return { + 'left': chat_left, + 'top': max(chat_bottom - 300, chat_top), + 'right': chat_right, + 'bottom': chat_bottom + } + + def process_current_chat(self, window_rect, contact_key): + """处理当前聊天""" + start_time = time.time() + msg_rect = self.get_latest_message_area(window_rect) + + try: + screenshot = ImageGrab.grab(bbox=( + msg_rect['left'], msg_rect['top'], + msg_rect['right'], msg_rect['bottom'] + )) + + # OCR识别 + ocr_start = time.time() + img_byte_arr = BytesIO() + screenshot.save(img_byte_arr, format='PNG') + img_bytes = img_byte_arr.getvalue() + + lines = self.ocr.recognize(img_bytes) + ocr_elapsed = time.time() - ocr_start + self.performance_stats['ocr_recognize'].append(ocr_elapsed) + + if not lines: + return False + + # 过滤消息（严格过滤） + import re + valid_lines = [] + for line in lines: + if len(line) < 3: + continue + if re.match(r'^\d{1,2}:\d{2}$', line): + continue + if any(char in line for char in ['©', 'ò', 'v0', 'V0']): + continue + valid_lines.append(line) + + if not valid_lines: + return False + + latest = valid_lines[-1] + + print(f" [识别] {latest}") + + # 判断是否需要回复 + if not self.should_reply(latest): + print(f" [跳过] 不需要回复") + return False + + if not self.is_new_message(latest, contact_key): + print(f" [跳过] 已处理") + return False + + print(f" [新消息] {latest}") + + # 获取AI回复 + reply = self.get_ai_reply(latest) + if reply: + print(f" [AI回复] {reply}") + self.send_message(reply, window_rect) + + # 记录性能 + total_elapsed = time.time() - start_time + self.performance_stats['total_process'].append(total_elapsed) + + return True + + return False + + except Exception as e: + logger.error(f"处理聊天失败: {e}") + return False + + def should_reply(self, message): + """判断是否需要回复""" + if not message or len(message) < 2: + return False + + for keyword in NO_REPLY_KEYWORDS: + if keyword in message: + return False + + return True + + def is_new_message(self, message, contact_key): + """判断是否为新消息""" + msg_hash = hashlib.md5(message.encode()).hexdigest() + + if contact_key in self.processed_messages: + if msg_hash in self.processed_messages[contact_key]: + return False + else: + self.processed_messages[contact_key] = set() + + self.processed_messages[contact_key].add(msg_hash) + return True + + def get_ai_reply(self, message): + """获取AI回复""" + try: + response = requests.post( + BACKEND_URL, + json={'message': message}, + timeout=10 + ) + + if response.status_code == 200: + data = response.json() + return data.get('reply', '') + except Exception as e: + logger.error(f"AI回复失败: {e}") + + return None + + def send_message(self, text, window_rect): + """发送消息""" + try: + original_clipboard = pyperclip.paste() + + pyperclip.copy(text) + time.sleep(0.1) + + pyautogui.hotkey('ctrl', 'v') + time.sleep(0.1) + + pyautogui.press('enter') + time.sleep(0.3) + + pyperclip.copy(original_clipboard) + + print(f"✓ 已发送") + + except Exception as e: + logger.error(f"发送消息失败: {e}") + + def print_performance_stats(self): + """打印性能统计""" + if not self.performance_stats['red_dot_detect']: + return + + print("\n" + "="*70) + print("性能统计") + print("="*70) + + avg_red_dot = np.mean(self.performance_stats['red_dot_detect']) * 1000 + avg_ocr = np.mean(self.performance_stats['ocr_recognize']) * 1000 if self.performance_stats['ocr_recognize'] else 0 + avg_total = np.mean(self.performance_stats['total_process']) * 1000 if self.performance_stats['total_process'] else 0 + + print(f"红点检测平均耗时: {avg_red_dot:.1f}ms") + print(f"OCR识别平均耗时: {avg_ocr:.1f}ms") + print(f"总处理平均耗时: {avg_total:.1f}ms") + print("="*70 + "\n") + + def run_forever(self): + """启动监听""" + print("=" * 70) + print("微信自动回复（优化版）") + print("=" * 70) + print("\n优化特性：") + print(" ✓ 快速红点检测（numpy矩阵运算，比逐像素快100倍）") + print(" ✓ 智能区域过滤（只检测特定X坐标范围）") + print(" ✓ 性能统计（详细的耗时分析）") + print("=" * 70) + print("\n监听中... 按 Ctrl+C 停止\n") + + self.running = True + round_count = 0 + + # 初始化窗口 + logger.info("正在查找微信窗口...") + window_rect = self.get_window_rect() + if not window_rect: + logger.error("未找到微信窗口") + return + logger.info("✓ 找到微信窗口") + + while self.running: + try: + round_count += 1 + print(f"\n{'='*70}") + print(f"[第 {round_count} 轮检查] {datetime.now().strftime('%H:%M:%S')}") + print(f"{'='*70}") + + # 快速检测红点 + red_dots = self.detect_red_dots_fast(window_rect) + + if not red_dots: + print("未检测到新消息") + time.sleep(LOOP_INTERVAL) + continue + + print(f"检测到 {len(red_dots)} 个新消息") + + # 处理每个红点 + for i, red_dot in enumerate(red_dots, 1): + print(f"\n[处理第 {i}/{len(red_dots)} 个新消息]") + + self.click_contact_by_red_dot(red_dot, window_rect) + + contact_key = f"{red_dot['x']}_{red_dot['y']}" + self.process_current_chat(window_rect, contact_key) + + time.sleep(1) + + # 每10轮打印一次性能统计 + if round_count % 10 == 0: + self.print_performance_stats() + + print(f"\n本轮处理完成，等待 {LOOP_INTERVAL} 秒...\n") + time.sleep(LOOP_INTERVAL) + + except Exception as e: + logger.error(f"循环出错: {e}") + import traceback + traceback.print_exc() + time.sleep(3) + + def stop(self): + self.running = False + + +if __name__ == "__main__": + try: + bot = WechatBotOptimized() + bot.run_forever() + except KeyboardInterrupt: + bot.stop() + print("\n程序已停止") + except Exception as e: + print(f"\n错误: {e}") + import traceback + traceback.print_exc() diff --git a/main.py b/main.py new file mode 100644 index 0000000..b13deda --- /dev/null +++ b/main.py @@ -0,0 +1,62 @@ +import os +import subprocess +import sys +from pathlib import Path + +PROJECT_ROOT = Path(__file__).resolve().parent +VENV_ROOT = PROJECT_ROOT / ".venv" +VENV_DIR = VENV_ROOT / "Scripts" +VENV_PYTHON = VENV_DIR / "python.exe" +VENV_PYTHONW = VENV_DIR / "pythonw.exe" + + +def _resolve(path): + try: + return Path(path).resolve() + except Exception: + return None + + +def _running_in_project_venv(): + current_prefix = _resolve(sys.prefix) + if current_prefix == _resolve(VENV_ROOT): + return True + current_executable = _resolve(sys.executable) + allowed_targets = {_resolve(VENV_PYTHON), _resolve(VENV_PYTHONW)} + return current_executable in allowed_targets + + +def _pick_reexec_python(): + current_name = Path(sys.executable).name.lower() + if current_name == "pythonw.exe" and VENV_PYTHONW.exists(): + return VENV_PYTHONW + if VENV_PYTHON.exists(): + return VENV_PYTHON + if VENV_PYTHONW.exists(): + return VENV_PYTHONW + raise RuntimeError(f"未找到项目 .venv 解释器: {VENV_PYTHON}") + + +def ensure_project_venv(): + if _running_in_project_venv(): + return + if os.environ.get("OPENCLAW_PROJECT_VENV_REEXEC") == "1": + raise RuntimeError("重启后仍未进入项目 .venv，请检查 .venv 是否损坏或系统 Python 安装是否异常") + env = os.environ.copy() + env["OPENCLAW_PROJECT_VENV_REEXEC"] = "1" + target_python = _pick_reexec_python() + subprocess.Popen([str(target_python), str(PROJECT_ROOT / "main.py")], cwd=str(PROJECT_ROOT), env=env) + raise SystemExit(0) + + +ensure_project_venv() + +from PySide6.QtWidgets import QApplication + +from app.presentation.main_window import MainWindow + + +if __name__ == "__main__": + app = QApplication(sys.argv) + w = MainWindow() + sys.exit(app.exec()) diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000..17b5720 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,17 @@ +opencv-contrib-python==4.13.0.92 +numpy==2.2.6 +requests==2.32.5 +pyperclip==1.11.0 +pyautogui==0.9.54 +Pillow==12.2.0 +uiautomation==2.0.29 +keyboard==0.13.5 +Flask==3.1.2 +PySide6==6.10.0 +PySide6-Essentials==6.10.0 +PySide6-Addons==6.10.0 +PyMySQL==1.1.2 +python-dotenv==1.1.1 + +rapidocr-onnxruntime==1.4.4 +onnxruntime==1.23.2 diff --git a/vendor/paddleocr/.gitkeep b/vendor/paddleocr/.gitkeep new file mode 100644 index 0000000..e69de29 diff --git a/vendor/paddleocr/models/.gitkeep b/vendor/paddleocr/models/.gitkeep new file mode 100644 index 0000000..e69de29 diff --git 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b/vendor/paddleocr/official_models/PP-OCRv5_server_det/.msc new file mode 100644 index 0000000000000000000000000000000000000000..8d9cbbe7ca555ed67151aa026a619e7e835e47d9 GIT binary patch literal 366 zcmZo*nVQVV00yyBG-{`4^sodZmSjxn;ZDxaOUq2x%PP*#o6^G(lvVYg>)l0gIpb5d|mZ&Q^?ZJhj0PdJLEV)7-2?1N@hV~QDSZ}iH=Ft0{|;0 BbT$A0 literal 0 HcmV?d00001 diff --git a/vendor/paddleocr/official_models/PP-OCRv5_server_det/.mv b/vendor/paddleocr/official_models/PP-OCRv5_server_det/.mv new file mode 100644 index 0000000..9427b67 --- /dev/null +++ b/vendor/paddleocr/official_models/PP-OCRv5_server_det/.mv @@ -0,0 +1 @@ +Revision:master,CreatedAt:1751519009 \ No newline at end of file diff --git a/vendor/paddleocr/official_models/PP-OCRv5_server_det/README.md b/vendor/paddleocr/official_models/PP-OCRv5_server_det/README.md new file mode 100644 index 0000000..e653b28 --- /dev/null +++ b/vendor/paddleocr/official_models/PP-OCRv5_server_det/README.md @@ -0,0 +1,220 @@ +--- +license: apache-2.0 +library_name: PaddleOCR +language: +- en +- zh +pipeline_tag: image-to-text +tags: +- OCR +- PaddlePaddle +- PaddleOCR +--- + +# PP-OCRv5_server_det + +## Introduction + +PP-OCRv5_server_det is one of the PP-OCRv5_det series, the latest generation of text detection models developed by the PaddleOCR team. Designed for high-performance applications, it supports the detection of text in diverse scenarios—including handwriting, vertical, rotated, and curved text—across multiple languages such as Simplified Chinese, Traditional Chinese, English, and Japanese. Key features include robust handling of complex layouts, varying text sizes, and challenging backgrounds, making it suitable for practical applications like document analysis, license plate recognition, and scene text detection. The key accuracy metrics are as follow: + +| Handwritten Chinese | Handwritten English | Printed Chinese | Printed English | Traditional Chinese | Ancient Text | Japanese | General Scenario | Pinyin | Rotation | Distortion | Artistic Text | Average | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| 0.803 | 0.841 | 0.945 | 0.917 | 0.815 | 0.676 | 0.772 | 0.797 | 0.671 | 0.8 | 0.876 | 0.673 | 0.827 | + +## Quick Start + +### Installation + +1. PaddlePaddle + +Please refer to the following commands to install PaddlePaddle using pip: + +```bash +# for CUDA11.8 +python -m pip install paddlepaddle-gpu==3.0.0 -i https://www.paddlepaddle.org.cn/packages/stable/cu118/ + +# for CUDA12.6 +python -m pip install paddlepaddle-gpu==3.0.0 -i https://www.paddlepaddle.org.cn/packages/stable/cu126/ + +# for CPU +python -m pip install paddlepaddle==3.0.0 -i https://www.paddlepaddle.org.cn/packages/stable/cpu/ +``` + +For details about PaddlePaddle installation, please refer to the [PaddlePaddle official website](https://www.paddlepaddle.org.cn/en/install/quick). + +2. PaddleOCR + +Install the latest version of the PaddleOCR inference package from PyPI: + +```bash +python -m pip install paddleocr +``` + +### Model Usage + +You can quickly experience the functionality with a single command: + +```bash +paddleocr text_detection \ + --model_name PP-OCRv5_server_det \ + -i https://cdn-uploads.huggingface.co/production/uploads/681c1ecd9539bdde5ae1733c/3ul2Rq4Sk5Cn-l69D695U.png +``` + +You can also integrate the model inference of the text detection module into your project. Before running the following code, please download the sample image to your local machine. + +```python +from paddleocr import TextDetection +model = TextDetection(model_name="PP-OCRv5_server_det") +output = model.predict(input="3ul2Rq4Sk5Cn-l69D695U.png", batch_size=1) +for res in output: + res.print() + res.save_to_img(save_path="./output/") + res.save_to_json(save_path="./output/res.json") +``` + +After running, the obtained result is as follows: + +```json +{'res': {'input_path': '/root/.paddlex/predict_input/3ul2Rq4Sk5Cn-l69D695U.png', 'page_index': None, 'dt_polys': array([[[ 632, 1429], + ..., + [ 632, 1450]], + + ..., + + [[ 353, 102], + ..., + [ 353, 125]]], dtype=int16), 'dt_scores': [0.8436300312712586, 0.7779392262863483, ..., 0.8491056329808098]}} +``` + +The visualized image is as follows: + +![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/681c1ecd9539bdde5ae1733c/rs6R4Ij5bfSeQ4mwLhcz6.jpeg) + +For details about usage command and descriptions of parameters, please refer to the [Document](https://paddlepaddle.github.io/PaddleOCR/latest/en/version3.x/module_usage/text_detection.html#iii-quick-start). + +### Pipeline Usage + +The ability of a single model is limited. But the pipeline consists of several models can provide more capacity to resolve difficult problems in real-world scenarios. + +#### PP-OCRv5 + +The general OCR pipeline is used to solve text recognition tasks by extracting text information from images and outputting it in text form. And there are 5 modules in the pipeline: +* Document Image Orientation Classification Module (Optional) +* Text Image Unwarping Module (Optional) +* Text Line Orientation Classification Module (Optional) +* Text Detection Module +* Text Recognition Module + +Run a single command to quickly experience the OCR pipeline: + +```bash +paddleocr ocr -i https://cdn-uploads.huggingface.co/production/uploads/681c1ecd9539bdde5ae1733c/3ul2Rq4Sk5Cn-l69D695U.png \ + --text_detection_model_name PP-OCRv5_server_det \ + --text_recognition_model_name PP-OCRv5_server_rec \ + --use_doc_orientation_classify False \ + --use_doc_unwarping False \ + --use_textline_orientation True \ + --save_path ./output \ + --device gpu:0 +``` + +Results are printed to the terminal: + +```json +{'res': {'input_path': '/root/.paddlex/predict_input/3ul2Rq4Sk5Cn-l69D695U.png', 'page_index': None, 'model_settings': {'use_doc_preprocessor': True, 'use_textline_orientation': True}, 'doc_preprocessor_res': {'input_path': None, 'page_index': None, 'model_settings': {'use_doc_orientation_classify': False, 'use_doc_unwarping': False}, 'angle': -1}, 'dt_polys': array([[[ 352, 105], + ..., + [ 352, 128]], + + ..., + + [[ 632, 1431], + ..., + [ 632, 1447]]], dtype=int16), 'text_det_params': {'limit_side_len': 64, 'limit_type': 'min', 'thresh': 0.3, 'max_side_limit': 4000, 'box_thresh': 0.6, 'unclip_ratio': 1.5}, 'text_type': 'general', 'textline_orientation_angles': array([0, ..., 0]), 'text_rec_score_thresh': 0.0, 'rec_texts': ['Algorithms for the Markov Entropy Decomposition', 'Andrew J. Ferris and David Poulin', 'Département de Physique, Université de Sherbrooke, Québec, JlK 2R1, Canada', '(Dated: October 31, 2018)', 'The Markov entropy decomposition (MED) is a recently-proposed, cluster-based simulation method for fi-', 'nite temperature quantum systems with arbitrary geometry. In this paper, we detail numerical algorithms for', 'performing the required steps of the MED, principally solving a minimization problem with a preconditioned', 'arXiv:1212.1442v1 [cond-mat.stat-mech] 6Dec 2012', "Newton's algorithm, as well as how to extract global susceptibilities and thermal responses. We demonstrate", 'the power of the method with the spin-1/2 XXZ model on the 2D square lattice, including the extraction of', 'critical points and details of each phase. Although the method shares some qualitative similarities with exact-', 'diagonalization, we show the MED is both more accurate and significantly more flexible.', 'PACS numbers: 05.10.−a,02.50.Ng, 03.67.−a,74.40.Kb', 'I.INTRODUCTION', 'This approximation becomes exact in the case of a 1D quan', 'tum (or classical) Markov chain [10], and leads to an expo-', 'Although the equations governing quantum many-body', 'nential reduction of cost for exact entropy calculations when', 'systems are simple to write down, finding solutions for the', 'the global density matrix is a higher-dimensional Markov net-', 'majority of systems remains incredibly difficult. Modern', 'work state [12, 13].', 'physics finds itself in need of new tools to compute the emer-', 'The second approximation used in the MED approach is', 'gent behavior of large, many-body systems.', 'related to the N-representibility problem. Given a set of lo-', 'There has been a great variety of tools developed to tackle', 'cal but overlapping reduced density matrices {pi}, it is a very', 'many-body problems, but in general, large 2D and 3D quan-', 'challenging problem to determine if there exists a global den-', 'tum systems remain hard to deal with. Most systems are', 'sity operator which is positive semi-definite and whose partial', 'thought to be non-integrable, so exact analytic solutions are', 'trace agrees with each ρi. This problem is QMA-hard (the', 'not usually expected. Direct numerical diagonalization can be', 'quantum analogue of NP) [14, 15], and is hopelessly diffi-', 'performed for relatively small systems — however the emer-', 'cult to enforce. Thus, the second approximation employed', 'gent behavior of a system in the thermodynamic limit may be', 'involves ignoring global consistency with a positive opera-', 'difficult to extract, especially in systems with large correlation', 'tor, while requiring local consistency on any overlapping re-', 'lengths. Monte Carlo approaches are technically exact (up to', 'gions between the ρi. At the zero-temperature limit, the MED', 'sampling error), but suffer from the so-called sign problem', 'approach becomes analogous to the variational nth-order re-', 'for fermionic, frustrated, or dynamical problems. Thus we are', 'duced density matrix approach, where positivity is enforced', 'limited to search for clever approximations to solve the ma-', 'on all reduced density matrices of size n [16–18].', 'jority of many-body problems.', 'The MED approach is an extremely flexible cluster method.', 'Over the past century, hundreds of such approximations', 'applicable to both translationally invariant systems of any di-', 'have been proposed, and we will mention just a few notable', 'mension in the thermodynamic limit, as well as finite systems', 'examples applicable to quantum lattice models. Mean-field', 'or systems without translational invariance (e.g. disordered', 'theory is simple and frequently arrives at the correct quali-', 'lattices, or harmonically trapped atoms in optical lattices).', 'tative description, but often fails when correlations are im-', 'The free energy given by MED is guaranteed to lower bound', 'portant. Density-matrix renormalisation group (DMRG) [1]', 'the true free energy, which in turn lower-bounds the ground', 'is efficient and extremely accurate at solving 1D problems,', 'state energy — thus providing a natural complement to varia-', 'but the computational cost grows exponentially with system', 'tional approaches which upper-bound the ground state energy.', 'size in two- or higher-dimensions [2, 3]. Related tensor-', 'The ability to provide a rigorous ground-state energy window', 'network techniques designed for 2D systems are still in their', 'is a powerful validation tool, creating a very compelling rea-', 'infancy [4–6]. Series-expansion methods [7] can be success-', 'son to use this approach.', 'ful, but may diverge or otherwise converge slowly, obscuring', 'In this paper we paper we present a pedagogical introduc-', 'the state in certain regimes. There exist a variety of cluster-', 'tion to MED, including numerical implementation issues and', 'based techniques, such as dynamical-mean-field theory [8]', 'applications to 2D quantum lattice models in the thermody-', 'and density-matrix embedding [9]', 'namiclimit.InSec.II.wegiveabriefderiyationofthe', 'Here we discuss the so-called Markov entropy decompo-', 'Markov entropy decomposition. Section III outlines a robust', 'sition (MED), recently proposed by Poulin & Hastings [10]', 'numerical strategy for optimizing the clusters that make up', '(and analogous to a slightly earlier classical algorithm [11]).', 'the decomposition. In Sec. IV we show how we can extend', 'This is a self-consistent cluster method for finite temperature', 'these algorithms to extract non-trivial information, such as', 'systems that takes advantage of an approximation of the (von', 'specific heat and susceptibilities. We present an application of', 'Neumann) entropy. In [10], it was shown that the entropy', 'the method to the spin-1/2 XXZ model on a 2D square lattice', 'per site can be rigorously upper bounded using only local in-', 'in Sec. V, describing how to characterize the phase diagram', 'formation — a local, reduced density matrix on N sites, say.', 'and determine critical points, before concluding in Sec. VI.'], 'rec_scores': array([0.99276221, ..., 0.95760632]), 'rec_polys': array([[[ 352, 105], + ..., + [ 352, 128]], + + ..., + + [[ 632, 1431], + ..., + [ 632, 1447]]], dtype=int16), 'rec_boxes': array([[ 352, ..., 128], + ..., + [ 632, ..., 1447]], dtype=int16)}} +``` + +If save_path is specified, the visualization results will be saved under `save_path`. The visualization output is shown below: + +![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/681c1ecd9539bdde5ae1733c/SfWsVpad7eKD3I2uLYpnS.png) + +The command-line method is for quick experience. For project integration, also only a few codes are needed as well: + +```python +from paddleocr import PaddleOCR + +ocr = PaddleOCR( + text_detection_model_name="PP-OCRv5_server_det", + text_recognition_model_name="PP-OCRv5_server_rec", + use_doc_orientation_classify=False, # Disables document orientation classification model via this parameter + use_doc_unwarping=False, # Disables text image rectification model via this parameter + use_textline_orientation=False, # Disables text line orientation classification model via this parameter +) +result = ocr.predict("./3ul2Rq4Sk5Cn-l69D695U.png") +for res in result: + res.print() + res.save_to_img("output") + res.save_to_json("output") +``` + +For details about usage command and descriptions of parameters, please refer to the [Document](https://paddlepaddle.github.io/PaddleOCR/latest/en/version3.x/pipeline_usage/OCR.html#2-quick-start). + +#### PP-StructureV3 + +Layout analysis is a technique used to extract structured information from document images. PP-StructureV3 includes the following six modules: +* Layout Detection Module +* General OCR Pipeline +* Document Image Preprocessing Pipeline （Optional） +* Table Recognition Pipeline （Optional） +* Seal Recognition Pipeline （Optional） +* Formula Recognition Pipeline （Optional） + +Run a single command to quickly experience the PP-StructureV3 pipeline: + +```bash +paddleocr pp_structurev3 -i https://cdn-uploads.huggingface.co/production/uploads/681c1ecd9539bdde5ae1733c/mG4tnwfrvECoFMu-S9mxo.png \ + --text_detection_model_name PP-OCRv5_server_det \ + --use_doc_orientation_classify False \ + --use_doc_unwarping False \ + --use_textline_orientation False \ + --device gpu:0 +``` + +Results would be printed to the terminal. If save_path is specified, the results will be saved under `save_path`. The predicted markdown visualization is shown below: + +![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/681c1ecd9539bdde5ae1733c/SfxF0X4drBTNGnfFOtZij.png) + +Just a few lines of code can experience the inference of the pipeline. Taking the PP-StructureV3 pipeline as an example: + +```python +from paddleocr import PPStructureV3 + +pipeline = PPStructureV3( + text_detection_model_name="PP-OCRv5_server_det", + use_doc_orientation_classify=False, # Use use_doc_orientation_classify to enable/disable document orientation classification model + use_doc_unwarping=False, # Use use_doc_unwarping to enable/disable document unwarping module + use_textline_orientation=False, # Use use_textline_orientation to enable/disable textline orientation classification model + device="gpu:0", # Use device to specify GPU for model inference + ) +output = pipeline.predict("./pp_structure_v3_demo.png") +for res in output: + res.print() # Print the structured prediction output + res.save_to_json(save_path="output") ## Save the current image's structured result in JSON format + res.save_to_markdown(save_path="output") ## Save the current image's result in Markdown format +``` + +The default model used in pipeline is `PP-OCRv5_server_det`, and you can specify other text detection model by argument `text_detection_model_name`. And you can also use the local model file by argument `text_detection_model_dir`. For details about usage command and descriptions of parameters, please refer to the [Document](https://paddlepaddle.github.io/PaddleOCR/latest/en/version3.x/pipeline_usage/PP-StructureV3.html#2-quick-start). + +## Links + +[PaddleOCR Repo](https://github.com/paddlepaddle/paddleocr) + +[PaddleOCR Documentation](https://paddlepaddle.github.io/PaddleOCR/latest/en/index.html) diff --git a/vendor/paddleocr/official_models/PP-OCRv5_server_det/config.json b/vendor/paddleocr/official_models/PP-OCRv5_server_det/config.json new file mode 100644 index 0000000..5d2c6fe --- /dev/null +++ b/vendor/paddleocr/official_models/PP-OCRv5_server_det/config.json @@ -0,0 +1,111 @@ +{ + "Global": { + "model_name": "PP-OCRv5_server_det" + }, + "Hpi": { + "backend_configs": { + "paddle_infer": { + "trt_dynamic_shapes": { + "x": [ + [ + 1, + 3, + 32, + 32 + ], + [ + 1, + 3, + 736, + 736 + ], + [ + 1, + 3, + 4000, + 4000 + ] + ] + } + }, + "tensorrt": { + "dynamic_shapes": { + "x": [ + [ + 1, + 3, + 32, + 32 + ], 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+ "✺", + "✻", + "✼", + "✽", + "✾", + "✿", + "❀", + "❁", + "❂", + "❃", + "❄", + "❅", + "❆", + "❇", + "❈", + "❉", + "❊", + "❋", + "❍", + "❏", + "❐", + "❑", + "❒", + "❖", + "❘", + "❙", + "❚", + "❛", + "❜", + "❝", + "❞", + "❡", + "❢", + "❣", + "❤", + "❥", + "❦", + "❧", + "❨", + "❩", + "❪", + "❫", + "❬", + "❭", + "❮", + "❯", + "❰", + "❱", + "❲", + "❳", + "❴", + "❵", + "❶", + "❷", + "❸", + "❹", + "❺", + "❻", + "❼", + "❽", + "❾", + "❿", + "①", + "②", + "③", + "④", + "⑤", + "⑥", + "⑦", + "⑧", + "⑨", + "⑩", + "➔", + "➕", + "➖", + "➗", + "➘", + "➙", + "➚", + "➛", + "➜", + "➝", + "➞", + "➟", + "➠", + "➡", + "➢", + "➣", + "➤", + "➥", + "➦", + "➧", + "➨", + "➩", + "➪", + "➫", + "➬", + "➭", + "➮", + "➯", + "➰", + "➱", + "➲", + "➳", + "➴", + "➵", + "➶", + "➷", + "➸", + "➹", + "➺", + "➻", + "➼", + "➽", + "➾", + "➿", + "⌘", + "⌥", + "⌃", + "⎋", + "⌫", + "⌦", + "⏏", + "⌤", + "⌧", + "⌨", + "⎆", + "⎇", + "⎈", + "⎉", + "⎊", + "⎌", + "⎍", + "⎎", + "⎏", + "⎐", + "⎑", + "⎒", + "⎓", + "⎕", + "⎖", + "⎗", + "⎘", + "⎙", + "⎚", + "⎛", + "⎜", + "⎝", + "⎞", + "⎟", + "⎠", + "⎡", + "⎢", + "⎣", + "⎤", + "⎥", + "⎦", + "⎧", + "⎨", + "⎩", + "⎪", + "⎫", + "⎬", + "⎭", + "⎮", + "⎯", + "⎰", + "⎱", + "⎲", + "⎳", + "⎴", + "⎵", + "⎶", + "⎷", + "⎸", + "⎹", + "⎺", + "⎻", + "⎼", + "⎽", + "⎾", + "⎿", + "⏍", + "⏎", + "⏐", + "⏑", + "⏒", + "⏓", + "⏔", + "⏕", + "⏖", + "⏗", + "⏘", + "⏙", + "⏛", + "⏜", + "⏝", + "⏞", + "⏟", + "⏠", + "⏡", + "⏢", + "⏣", + "⏤", + "⏥", + "⏦", + "⏧", + "⏨", + "⏭", + "⏮", + "⏯", + "⏱", + "⏲", + "▲", + "▽", + "◐", + "⏽", + "⏾", + "⏿", + "ɐ", + "ɑ", + "ɒ", + "ɓ", + "ɔ", + "ɕ", + "ɖ", + "ɗ", + "ɘ", + "ə", + "ɚ", + "ɛ", + "ɜ", + "ɝ", + "ɞ", + "ɟ", + "ɠ", + "ɡ", + "ɢ", + "ɣ", + "ɤ", + "ɥ", + "ɦ", + "ɧ", + "ɨ", + "ɩ", + "ɪ", + "ɫ", + "ɬ", + "ɭ", + "ɮ", + "ɯ", + "ɰ", + "ɱ", + "ɲ", + "ɳ", + "ɴ", + "ɵ", + "ɶ", + "ɷ", + "ɸ", + "ɹ", + "ɺ", + "ɻ", + "ɼ", + "ɽ", + "ɾ", + "ɿ", + "ʀ", + "ʁ", + "ʂ", + "ʃ", + "ʄ", + "ʅ", + "ʆ", + "ʇ", + "ʈ", + "ʉ", + "ʊ", + "ʋ", + "ʌ", + "ʍ", + "ʎ", + "ʏ", + "ʐ", + "ʑ", + "ʒ", + "ʓ", + "ʔ", + "ʕ", + "ʖ", + "ʗ", + "ʘ", + "ʙ", + "ʚ", + "ʛ", + "ʜ", + "ʝ", + "ʞ", + "ʟ", + "ʠ", + "ʡ", + "ʢ", + "ʣ", + "ʤ", + "ʥ", + "ʦ", + "ʧ", + "ʨ", + "ʩ", + "ʪ", + "ʫ", + "ʬ", + "ʭ", + "ʮ", + "ʯ", + "━", + "Ǝ", + "Ã", + "●", + "▶", + "｜", + "𝑢", + "〖", + "〗", + "︽", + "–", + "﹥", + "𝜓", + "•", + "∋", + "ƒ", + "०", + "✘", + "Е", + "◉", + "〒", + "𝒱", + "𝜆", + "⟹", + "﹪", + "◊", + "╆", + "오", + "˂", + "〉", + "𝝎", + "▪", + "△", + "▁", + "◼", + "〇", + "▷", + "▬", + "𝒮", + "†", + "ₒ", + "⼁", + "〵", + "⭐", + "╳", + "⟶", + "으", + "⬆", + "Ạ", + "◀", + "", + "▫", + "丄", + "︾", + "◥", + "‖", + "𝜌", + "ⅼ", + "▼", + "⁎", + "﹏", + "😁", + "😂", + "😃", + "😄", + "😅", + "😆", + "😉", + "😊", + "😋", + "😌", + "😍", + "😏", + "😒", + "😓", + "😔", + "😖", + "😘", + "😚", + "😜", + "😝", + "😞", + "😠", + "😡", + "😢", + "😣", + "😤", + "😥", + "😨", + "😩", + "😪", + "😫", + "😭", + "😰", + "😱", + "😲", + "😳", + "😵", + "😷", + "😸", + "😹", + "😺", + "😻", + "😼", + "😽", + "😾", + "😿", + "🙀", + "🙅", + "🙆", + "🙇", + "🙈", + "🙉", + "🙊", + "🙋", + "🙌", + "🙍", + "🙎", + "🙏", + "✂", + "✅", + "✊", + "✋", + "✖", + "✨", + "❌", + "❎", + "❓", + "❔", + "❕", + "❗", + "🚀", + "🚃", + "🚄", + "🚅", + "🚇", + "🚉", + "🚌", + "🚏", + "🚑", + "🚒", + "🚓", + "🚕", + "🚗", + "🚙", + "🚚", + "🚢", + "🚤", + "🚥", + "🚧", + "🚨", + "🚩", + "🚪", + "🚫", + "🚬", + "🚭", + "🚲", + "🚶", + "🚹", + "🚺", + "🚻", + "🚼", + "🚽", + "🚾", + "🛀", + "Ⓜ", + "🅰", + "🅱", + "🅾", + "🅿", + "🆎", + "🆑", + "🆒", + "🆓", + "🆔", + "🆕", + "🆖", + "🆗", + "🆘", + "🆙", + "🆚", + "🇩🇪", + "🇬🇧", + "🇨🇳", + "🇯🇵", + "🇫🇷", + "🇰🇷", + "🇪🇸", + "🇮🇹", + "🇷🇺", + "🇺🇸", + "🈁", + "ℹ", + "⌚", + "⌛", + "⏩", + "⏪", + "⏫", + "⏬", + "⏰", + "⏳", + "◻", + "◽", + "◾", + "♈", + "♉", + "♊", + "♋", + "♌", + "♍", + "♎", + "♏", + "♐", + "♑", + "♒", + "♓", + "♿", + "⚽", + "⚾", + "⛄", + "⛅", + "⛎", + "⛔", + "⛲", + "⛳", + "⛵", + "⛺", + "⛽", + "⤴", + "⤵", + "⬅", + "⬇", + "⬛", + "⬜", + "⭕", + "〰", + "〽", + "㊗", + "㊙", + "🀄", + "🃏", + "🌀", + "🌁", + "🌂", + "🌃", + "🌄", + "🌅", + "🌆", + "🌇", + "🌈", + "🌉", + "🌊", + "🌋", + "🌌", + "🌏", + "🌑", + "🌓", + "🌔", + "🌕", + "🌙", + "🌛", + "🌟", + "🌠", + "🌰", + "🌱", + "🌴", + "🌵", + "🌷", + "🌸", + "🌹", + "🌺", + "🌻", + "🌼", + "🌽", + "🌾", + "🌿", + "🍀", + "🍁", + "🍂", + "🍃", + "🍄", + "🍅", + "🍆", + "🍇", + "🍈", + "🍉", + "🍊", + "🍌", + "🍍", + "🍎", + "🍏", + "🍑", + "🍒", + "🍓", + "🍔", + "🍕", + "🍖", + "🍗", + "🍘", + "🍙", + "🍚", + "🍛", + "🍜", + "🍝", + "🍞", + "🍟", + "🍠", + "🍡", + "🍢", + "🍣", + "🍤", + "🍥", + "🍦", + "🍧", + "🍨", + "🍩", + "🍪", + "🍫", + "🍬", + "🍭", + "🍮", + "🍯", + "🍰", + "🍱", + "🍲", + "🍳", + "🍴", + "🍵", + "🍶", + "🍷", + "🍸", + "🍹", + "🍺", + "🍻", + "🎀", + "🎁", + "🎂", + "🎃", + "🎄", + "🎅", + "🎆", + "🎇", + "🎈", + "🎉", + "🎊", + "🎋", + "🎌", + "🎍", + "🎎", + "🎏", + "🎐", + "🎑", + "🎒", + "🎓", + "🎠", + "🎡", + "🎢", + "🎣", + "🎤", + "🎥", + "🎦", + "🎧", + "🎨", + "🎩", + "🎪", + "🎫", + "🎬", + "🎭", + "🎮", + "🎯", + "🎰", + "🎱", + "🎲", + "🎳", + "🎴", + "🎵", + "🎶", + "🎷", + "🎸", + "🎹", + "🎺", + "🎻", + "🎼", + "🎽", + "🎾", + "🎿", + "🏀", + "🏁", + "🏂", + "🏃", + "🏄", + "🏆", + "🏈", + "🏊", + "🏠", + "🏡", + "🏢", + "🏣", + "🏥", + "🏦", + "🏧", + "🏨", + "🏩", + "🏪", + "🏫", + "🏬", + "🏭", + "🏮", + "🏯", + "🏰", + "🐌", + "🐍", + "🐎", + "🐑", + "🐒", + "🐔", + "🐗", + "🐘", + "🐙", + "🐚", + "🐛", + "🐜", + "🐝", + "🐞", + "🐟", + "🐠", + "🐡", + "🐢", + "🐣", + "🐤", + "🐥", + "🐦", + "🐧", + "🐨", + "🐩", + "🐫", + "🐬", + "🐭", + "🐮", + "🐯", + "🐰", + "🐱", + "🐲", + "🐳", + "🐴", + "🐵", + "🐶", + "🐷", + "🐸", + "🐹", + "🐺", + "🐻", + "🐼", + "🐽", + "🐾", + "👀", + "👂", + "👃", + "👄", + "👅", + "👆", + "👇", + "👈", + "👉", + "👊", + "👋", + "👌", + "👍", + "👎", + "👏", + "👐", + "👑", + "👒", + "👓", + "👔", + "👕", + "👖", + "👗", + "👘", + "👙", + "👚", + "👛", + "👜", + "👝", + "👞", + "👟", + "👠", + "👡", + "👢", + "👣", + "👤", + "👦", + "👧", + "👨", + "👩", + "👪", + "👫", + "👮", + "👯", + "👰", + "👱", + "👲", + "👳", + "👴", + "👵", + "👶", + "👷", + "👸", + "👹", + "👺", + "👻", + "👼", + "👽", + "👾", + "👿", + "💀", + "💁", + "💂", + "💃", + "💄", + "💅", + "💆", + "💇", + "💈", + "💉", + "💊", + "💋", + "💌", + "💍", + "💎", + "💏", + "💐", + "💑", + "💒", + "💓", + "💔", + "💕", + "💖", + "💗", + "💘", + "💙", + "💚", + "💛", + "💜", + "💝", + "💞", + "💟", + "💠", + "💡", + "💢", + "💣", + "💤", + "💥", + "💦", + "💧", + "💨", + "💩", + "💪", + "💫", + "💬", + "💮", + "💯", + "💰", + "💲", + "💳", + "💴", + "💵", + "💸", + "💹", + "💺", + "💻", + "💼", + "💽", + "💾", + "💿", + "📀", + "📁", + "📂", + "📃", + "📄", + "📅", + "📆", + "📇", + "📈", + "📉", + "📊", + "📋", + "📌", + "📍", + "📎", + "📏", + "📐", + "📑", + "📒", + "📓", + "📔", + "📕", + "📖", + "📗", + "📘", + "📙", + "📚", + "📛", + "📜", + "📝", + "📞", + "📟", + "📠", + "📡", + "📢", + "📣", + "📤", + "📥", + "📦", + "📧", + "📨", + "📩", + "📪", + "📫", + "📮", + "📰", + "📱", + "📲", + "📳", + "📴", + "📶", + "📷", + "📹", + "📺", + "📻", + "📼", + "🔃", + "🔊", + "🔋", + "🔌", + "🔍", + "🔎", + "🔏", + "🔐", + "🔑", + "🔒", + "🔓", + "🔔", + "🔖", + "🔗", + "🔘", + "🔙", + "🔚", + "🔛", + "🔜", + "🔝", + "🔞", + "🔟", + "🔠", + "🔡", + "🔢", + "🔣", + "🔤", + "🔥", + "🔦", + "🔧", + "🔨", + "🔩", + "🔪", + "🔫", + "🔮", + "🔯", + "🔰", + "🔱", + "🔲", + "🔳", + "🔴", + "🔵", + "🔶", + "🔷", + "🔸", + "🔹", + "🔺", + "🔻", + "🔼", + "🔽", + "🕐", + "🕑", + "🕒", + "🕓", + "🕔", + "🕕", + "🕖", + "🕗", + "🕘", + "🕙", + "🕚", + "🕛", + "🗻", + "🗼", + "🗽", + "🗾", + "🗿", + "😀", + "😇", + "😈", + "😎", + "😐", + "😑", + "😕", + "😗", + "😙", + "😛", + "😟", + "😦", + "😧", + "😬", + "😮", + "😯", + "😴", + "😶", + "🚁", + "🚂", + "🚆", + "🚈", + "🚊", + "🚍", + "🚎", + "🚐", + "🚔", + "🚖", + "🚘", + "🚛", + "🚜", + "🚝", + "🚞", + "🚟", + "🚠", + "🚡", + "🚣", + "🚦", + "🚮", + "🚯", + "🚰", + "🚱", + "🚳", + "🚴", + "🚵", + "🚷", + "🚸", + "🚿", + "🛁", + "🛂", + "🛃", + "🛄", + "🛅", + "🌍", + "🌎", + "🌐", + "🌒", + "🌖", + "🌗", + "🌘", + "🌚", + "🌜", + "🌝", + "🌞", + "🌲", + "🌳", + "🍋", + "🍐", + "🍼", + "🏇", + "🏉", + "🏤", + "🐀", + "🐁", + "🐂", + "🐃", + "🐄", + "🐅", + "🐆", + "🐇", + "🐈", + "🐉", + "🐊", + "🐋", + "🐏", + "🐐", + "🐓", + "🐕", + "🐖", + "🐪", + "👥", + "👬", + "👭", + "💭", + "💶", + "💷", + "📬", + "📭", + "📯", + "📵", + "🔀", + "🔁", + "🔂", + "🔄", + "🔅", + "🔆", + "🔇", + "🔉", + "🔕", + "🔬", + "🔭", + "🕜", + "🕝", + "🕞", + "🕟", + "🕠", + "🕡", + "🕢", + "🕣", + "🕤", + "🕥", + "🕦", + "🕧" + ] + } +} \ No newline at end of file diff --git a/vendor/paddleocr/official_models/PP-OCRv5_server_rec/inference.json b/vendor/paddleocr/official_models/PP-OCRv5_server_rec/inference.json new file mode 100644 index 0000000..6701133 --- /dev/null +++ b/vendor/paddleocr/official_models/PP-OCRv5_server_rec/inference.json @@ -0,0 +1 @@ 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\ No newline at end of file diff --git a/vendor/paddleocr/official_models/PP-OCRv5_server_rec/inference.yml b/vendor/paddleocr/official_models/PP-OCRv5_server_rec/inference.yml new file mode 100644 index 0000000..f5156e7 --- /dev/null +++ b/vendor/paddleocr/official_models/PP-OCRv5_server_rec/inference.yml @@ -0,0 +1,18426 @@ +Global: + model_name: PP-OCRv5_server_rec +Hpi: + backend_configs: + paddle_infer: + trt_dynamic_shapes: &id001 + x: + - - 1 + - 3 + - 48 + - 160 + - - 1 + - 3 + - 48 + - 320 + - - 8 + - 3 + - 48 + - 3200 + tensorrt: + dynamic_shapes: *id001 +PreProcess: + transform_ops: + - DecodeImage: + channel_first: false + img_mode: BGR + - MultiLabelEncode: + gtc_encode: NRTRLabelEncode + - RecResizeImg: + image_shape: + - 3 + - 48 + - 320 + - KeepKeys: + keep_keys: + - image + - label_ctc + - label_gtc + - length + - valid_ratio +PostProcess: + name: CTCLabelDecode + character_dict: + - 　 + - 一 + - 乙 + - 二 + - 十 + - 丁 + - 厂 + - 七 + - 卜 + - 八 + - 人 + - 入 + - 儿 + - 匕 + - 几 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