diff --git a/README.md b/README.md index 185f3e6..ecb46f5 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ # AI-CHAT-UI -一个基于 Vue 和 markstream-vue 构建的现代化 AI 对话界面，提供丰富的交互功能和精美的视觉体验。 +一个基于 Vue 和 markstream-vue 构建的现代化 AI 对话界面，提供丰富的交互功能和精美的视觉体验。支持多模型集成，包括智谱 GLM、阿里云百炼、OpenAI/Deepseek 等。 ## 页面展示 @@ -14,6 +14,8 @@ ## ✨ 核心功能 +### 前端功能 + | 功能 | 详细描述 | |-------|-------------------------------------| | 对话历史 | 支持多对话管理、置顶、重命名、删除 | @@ -36,34 +38,106 @@ | 数据管理 | 导入/导出设置、清除数据，保障数据安全 | | 预设提示词 | 快速选择常用角色设定，提升对话效率 | +### 后端功能 + +| 功能 | 详细描述 | +|-------|-------------------------------------| +| OpenAI 兼容 API | 提供标准 OpenAI 兼容接口，支持多模型路由 | +| 多模型支持 | 集成智谱 GLM、阿里云百炼、OpenAI/Deepseek 等平台 | +| 会话管理 | 支持对话历史的保存、加载、删除 | +| 文件上传 | 支持图片、文档等文件的上传和管理 | +| 健康检查 | 提供系统状态和可用模型检查 | +| 日志系统 | 详细的请求日志和响应时间记录 | + ## 🛠 技术栈 -- **核心框架**: Vue - +### 前端 +- **核心框架**: Vue 3 - **流式渲染**: markstream-vue - +- **类型系统**: TypeScript - **UI 设计**: 现代化响应式设计，支持暗色主题 - - **交互体验**: 丰富的快捷键系统和消息操作 +### 后端 +- **核心框架**: FastAPI +- **编程语言**: Python 3.12+ +- **数据库**: SQLite +- **API 设计**: RESTful API + OpenAI 兼容接口 +- **文件存储**: 本地文件系统 + +### 模型支持 +- **智谱 GLM**: glm-4-flash, glm-4, 等 +- **阿里云百炼**: qwen-turbo, qwen-plus, 等 +- **OpenAI/Deepseek**: gpt-3.5-turbo, gpt-4, deepseek-chat, 等 + ## 🚀 快速开始 -```Bash +### 1. 克隆仓库 -# 克隆仓库 +```bash git clone https://github.com/zll-it/ai-chat-ui.git - -# 进入项目目录 cd ai-chat-ui +``` -# 安装依赖 +### 2. 安装前端依赖 + +```bash npm install +``` -# 启动开发服务器 +### 3. 安装后端依赖 + +```bash +cd server +python3 -m venv .venv +source .venv/bin/activate # Linux/Mac +# .venv\Scripts\activate # Windows +pip install -r requirements.txt +``` + +### 4. 配置 API 密钥 + +在 `server` 目录下创建 `.env` 文件，添加以下配置： + +```env +# 智谱 GLM API 配置 +ZHIPUAI_API_KEY=your_zhipuai_api_key + +# 阿里云百炼 API 配置 +DASHSCOPE_API_KEY=your_dashscope_api_key + +# OpenAI API 配置（支持 Deepseek 等兼容接口） +OPENAI_API_KEY=your_openai_api_key +OPENAI_API_BASE=https://api.openai.com/v1 # 或其他兼容接口地址 + +# 服务器配置 +PORT=8000 +``` + +### 5. 启动服务 + +#### 启动后端服务器 + +```bash +# 在 server 目录下 +python main.py +``` + +#### 启动前端开发服务器 + +```bash +# 在项目根目录下 npm run dev +``` -# 构建生产版本 +### 6. 构建生产版本 + +```bash +# 构建前端 npm run build + +# 后端服务可以直接运行 +python server/main.py ``` ## 📋 使用说明 @@ -71,11 +145,8 @@ npm run build ### 基础操作 - **新建对话**: `Ctrl+N` 快捷键或点击页面右上角 "+" 按钮 - - **切换布局**: 点击页面右下角布局切换按钮 - - **主题切换**: 设置面板中选择浅色/深色/跟随系统 - - **搜索对话**: 使用页面顶部搜索框或快捷键 `Ctrl+K` ### 快捷键一览 @@ -87,7 +158,146 @@ npm run build | 复制当前消息 | Ctrl+C (消息 hover 时) | | 切换布局 | Ctrl+Shift+L | -## 📄 许可证 +### 模型选择 + +在对话设置中，可以选择不同的模型： + +- **智谱 GLM**: 国内高性能模型，响应速度快 +- **阿里云百炼**: 支持多语言和多模态 +- **OpenAI**: 全球领先的 GPT 系列模型 +- **Deepseek**: 专注于代码和技术领域的模型 + +## 📡 API 文档 + +### OpenAI 兼容接口 + +#### POST /v1/chat/completions + +标准的 OpenAI 兼容聊天接口，支持流式输出。 + +**请求示例**: + +```json +{ + "model": "glm-4-flash", + "messages": [ + {"role": "user", "content": "你好，请介绍一下你自己"} + ], + "stream": true, + "temperature": 0.7 +} +``` + +**响应示例**: + +```json +{ + "id": "chatcmpl-123", + "object": "chat.completion", + "created": 1677858242, + "model": "glm-4-flash", + "choices": [ + { + "index": 0, + "message": { + "role": "assistant", + "content": "你好！我是一个基于智谱 GLM 模型的AI助手..." + }, + "finish_reason": "stop" + } + ] +} +``` + +#### GET /v1/models + +获取所有可用模型列表。 + +**响应示例**: + +```json +{ + "object": "list", + "data": [ + { + "id": "glm-4-flash", + "object": "model", + "created": 1677825464, + "owned_by": "zhipuai" + }, + { + "id": "gpt-3.5-turbo", + "object": "model", + "created": 1677610602, + "owned_by": "openai" + } + ] +} +``` + +### 传统接口 + +#### POST /api/chat-ui/chat + +传统聊天接口，保持向后兼容。 + +#### GET /api/chat-ui/models + +获取模型列表（聚合所有可用平台）。 + +#### GET /api/chat-ui/conversations + +获取所有对话历史。 + +#### POST /api/chat-ui/upload + +上传文件（支持图片、文档等）。 + +## 🔧 配置说明 + +### 前端配置 + +前端配置文件位于 `src/config.ts`，主要配置项： + +- **API_BASE_URL**: 后端 API 地址 +- **DEFAULT_MODEL**: 默认模型 +- **THEME**: 默认主题 +- **FONT_SIZE**: 默认字体大小 + +### 后端配置 + +后端配置通过 `.env` 文件和 `server/config.py` 进行管理： + +- **PORT**: 服务器端口 +- **API 密钥**: 各平台的 API 密钥 +- **上传目录**: 文件上传的存储路径 +- **数据库配置**: SQLite 数据库设置 + +## � 项目结构 + +``` +ai-chat-ui/ +├── src/ # 前端源码 +│ ├── components/ # Vue 组件 +│ ├── services/ # API 服务 +│ ├── utils/ # 工具函数 +│ ├── App.vue # 主应用组件 +│ └── main.ts # 入口文件 +├── server/ # 后端源码 +│ ├── adapters/ # 模型适配器 +│ ├── api/ # API 路由 +│ ├── database/ # 数据库操作 +│ ├── utils/ # 工具函数 +│ ├── main.py # 主入口 +│ └── requirements.txt # 依赖文件 +├── public/ # 静态资源 +├── screenshots/ # 截图 +├── package.json # 前端依赖 +├── tsconfig.json # TypeScript 配置 +└── README.md # 项目说明 +``` + +## �📄 许可证 本项目采用 MIT 许可证 - 详见 [LICENSE](LICENSE) 文件 @@ -95,10 +305,35 @@ npm run build 欢迎提交 Issue 和 Pull Request 来帮助改进这个项目！ +### 开发流程 + +1. Fork 本仓库 +2. 创建特性分支 (`git checkout -b feature/amazing-feature`) +3. 提交更改 (`git commit -m 'Add amazing feature'`) +4. 推送到分支 (`git push origin feature/amazing-feature`) +5. 打开 Pull Request + +## 🌟 特性亮点 + +- **多模型集成**: 支持多个 AI 平台的模型，灵活切换 +- **现代化界面**: 美观的 UI 设计，支持深色主题 +- **流畅体验**: 流式输出和丰富的交互效果 +- **功能丰富**: 完整的对话管理和设置选项 +- **易于部署**: 简单的配置和启动流程 +- **OpenAI 兼容**: 标准的 OpenAI 兼容接口 + +## 📞 支持 + +如果您有任何问题或建议，欢迎： + +- 提交 Issue +- 发送邮件至：contact@example.com +- 参与项目讨论 + ---
-Made with ❤️ using Vue & markstream-vue +Made with ❤️ using Vue & FastAPI -
+ \ No newline at end of file diff --git a/server/adapters/dashscope_adapter.py b/server/adapters/dashscope_adapter.py index 7728b22..a6c94b7 100644 --- a/server/adapters/dashscope_adapter.py +++ b/server/adapters/dashscope_adapter.py @@ -10,7 +10,7 @@ from typing import Dict, List from fastapi.responses import JSONResponse, StreamingResponse from .base import BaseAdapter, ChatCompletionRequest, ModelInfo -from utils.logger import get_logger +from core import get_logger logger = get_logger() @@ -22,7 +22,7 @@ DASHSCOPE_MODELS = [ description="最强大的模型", max_tokens=8192, provider="Aliyun", - supports_thinking=True, + supports_thinking=False, supports_web_search=False, supports_vision=False, supports_files=False, @@ -33,7 +33,7 @@ DASHSCOPE_MODELS = [ description="能力均衡", max_tokens=8192, provider="Aliyun", - supports_thinking=False, + supports_thinking=True, supports_web_search=False, supports_vision=False, supports_files=False, @@ -44,7 +44,7 @@ DASHSCOPE_MODELS = [ description="速度更快、成本更低", max_tokens=8192, provider="Aliyun", - supports_thinking=False, + supports_thinking=True, supports_web_search=False, supports_vision=False, supports_files=False, diff --git a/server/adapters/glm_adapter.py b/server/adapters/glm_adapter.py index f7e6897..59cc659 100644 --- a/server/adapters/glm_adapter.py +++ b/server/adapters/glm_adapter.py @@ -11,7 +11,7 @@ from typing import Dict, List, Optional from fastapi.responses import JSONResponse, StreamingResponse from .base import BaseAdapter, ChatCompletionRequest, ModelInfo -from utils.logger import get_logger +from core import get_logger logger = get_logger() diff --git a/server/adapters/openai_adapter.py b/server/adapters/openai_adapter.py index 6ff980e..066131e 100644 --- a/server/adapters/openai_adapter.py +++ b/server/adapters/openai_adapter.py @@ -10,7 +10,7 @@ from typing import Dict, List, Optional from fastapi.responses import JSONResponse, StreamingResponse from .base import BaseAdapter, ChatCompletionRequest, ModelInfo -from utils.logger import get_logger +from core import get_logger logger = get_logger() diff --git a/server/api/conversation_routes.py b/server/api/conversation_routes.py index ee4971c..60ae8ef 100644 --- a/server/api/conversation_routes.py +++ b/server/api/conversation_routes.py @@ -18,7 +18,7 @@ sys.path.append(str(Path(__file__).parent.parent)) from database import get_db from utils.helpers import generate_unique_id -from utils.logger import log_error, log_exception, log_info +from core import log_error, log_exception, log_info # 配置上传目录 upload_dir = Path(__file__).parent.parent / "uploads" diff --git a/server/api/openai_gateway.py b/server/api/openai_gateway.py index 9afa60e..9d894c8 100644 --- a/server/api/openai_gateway.py +++ b/server/api/openai_gateway.py @@ -10,7 +10,7 @@ from fastapi.responses import JSONResponse from adapters import get_adapter, get_provider_from_model from adapters.base import ChatCompletionRequest -from utils.logger import get_logger +from core import get_logger logger = get_logger() diff --git a/server/config/__init__.py b/server/config/__init__.py new file mode 100644 index 0000000..3485eff --- /dev/null +++ b/server/config/__init__.py @@ -0,0 +1,23 @@ +""" +配置模块 + +提供统一的配置管理功能，包括平台配置、API密钥管理等。 +""" + +from .settings import ( + ProviderConfig, + PROVIDERS, + get_provider_config, + is_provider_available, + get_available_providers, + DEFAULT_PROVIDER, +) + +__all__ = [ + "ProviderConfig", + "PROVIDERS", + "get_provider_config", + "is_provider_available", + "get_available_providers", + "DEFAULT_PROVIDER", +] diff --git a/server/config.py b/server/config/settings.py similarity index 96% rename from server/config.py rename to server/config/settings.py index 1beb173..28d7086 100644 --- a/server/config.py +++ b/server/config/settings.py @@ -56,4 +56,4 @@ def get_available_providers() -> list: # 默认平台 -DEFAULT_PROVIDER = os.getenv("DEFAULT_PROVIDER", "glm") \ No newline at end of file +DEFAULT_PROVIDER = os.getenv("DEFAULT_PROVIDER", "glm") diff --git a/server/core/__init__.py b/server/core/__init__.py new file mode 100644 index 0000000..b10c9bf --- /dev/null +++ b/server/core/__init__.py @@ -0,0 +1,41 @@ +""" +日志模块 + +提供统一的日志管理功能，支持结构化日志、文件轮转、多级别日志等。 +""" + +from .logger import ( + LoggerSetup, + setup_global_logger, + get_logger, + log_debug, + log_info, + log_warning, + log_error, + log_critical, + log_exception, + log_structured, + log_request_info, + log_response_info, + log_error_detail, + log_chat_interaction, + log_system_status, +) + +__all__ = [ + "LoggerSetup", + "setup_global_logger", + "get_logger", + "log_debug", + "log_info", + "log_warning", + "log_error", + "log_critical", + "log_exception", + "log_structured", + "log_request_info", + "log_response_info", + "log_error_detail", + "log_chat_interaction", + "log_system_status", +] diff --git a/server/init_logging.py b/server/core/init.py similarity index 92% rename from server/init_logging.py rename to server/core/init.py index 6b71ff8..8149b5b 100644 --- a/server/init_logging.py +++ b/server/core/init.py @@ -1,40 +1,40 @@ -#!/usr/bin/env python -""" -初始化日志系统 -""" - -import os - -from utils.logger import setup_global_logger - - -def init_logging_system(): - """ - 初始化日志系统 - """ - # 从环境变量获取日志配置，如果没有则使用默认值 - log_level = os.getenv("LOG_LEVEL", "INFO") - log_dir = os.getenv("LOG_DIR", "logs") - - # 尝试从配置文件读取值 - try: - with open("logging.conf", "r", encoding="utf-8") as f: - for line in f: - if line.startswith("LOG_LEVEL="): - log_level = line.split("=", 1)[1].strip() - elif line.startswith("LOG_DIR="): - log_dir = line.split("=", 1)[1].strip() - except FileNotFoundError: - pass # 如果配置文件不存在，则使用环境变量或默认值 - - # 设置全局日志系统 - logger = setup_global_logger( - name="ai-chat-api", log_level=log_level, log_dir=log_dir - ) - - return logger - - -if __name__ == "__main__": - logger = init_logging_system() - logger.info("Logging system initialized successfully") +#!/usr/bin/env python +""" +初始化日志系统 +""" + +import os + +from .logger import setup_global_logger + + +def init_logging_system(): + """ + 初始化日志系统 + """ + # 从环境变量获取日志配置，如果没有则使用默认值 + log_level = os.getenv("LOG_LEVEL", "INFO") + log_dir = os.getenv("LOG_DIR", "logs") + + # 尝试从配置文件读取值 + try: + with open("logging.conf", "r", encoding="utf-8") as f: + for line in f: + if line.startswith("LOG_LEVEL="): + log_level = line.split("=", 1)[1].strip() + elif line.startswith("LOG_DIR="): + log_dir = line.split("=", 1)[1].strip() + except FileNotFoundError: + pass # 如果配置文件不存在，则使用环境变量或默认值 + + # 设置全局日志系统 + logger = setup_global_logger( + name="ai-chat-api", log_level=log_level, log_dir=log_dir + ) + + return logger + + +if __name__ == "__main__": + logger = init_logging_system() + logger.info("Logging system initialized successfully") diff --git a/server/utils/logger.py b/server/core/logger.py similarity index 96% rename from server/utils/logger.py rename to server/core/logger.py index 9e68d00..d639452 100644 --- a/server/utils/logger.py +++ b/server/core/logger.py @@ -1,277 +1,277 @@ -""" -统一日志管理系统 -提供结构化日志记录功能，支持不同日志级别、文件输出、轮转等 -""" - -import json -import logging -import os -import sys -from datetime import datetime -from logging.handlers import RotatingFileHandler -from pathlib import Path - - -class LoggerSetup: - """日志系统配置类""" - - def __init__( - self, - name: str = "ai-chat-server", - log_level: str = "INFO", - log_dir: str = "logs", - max_bytes: int = 10 * 1024 * 1024, - backup_count: int = 5, - ): - """ - 初始化日志系统 - - Args: - name: 日志记录器名称 - log_level: 日志级别 ('DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL') - log_dir: 日志文件存储目录 - max_bytes: 单个日志文件最大大小（字节） - backup_count: 保留的备份文件数量 - """ - self.name = name - self.log_level = getattr(logging, log_level.upper(), logging.INFO) - self.log_dir = Path(log_dir) - self.max_bytes = max_bytes - self.backup_count = backup_count - - # 创建日志目录 - self.log_dir.mkdir(exist_ok=True) - - # 设置日志格式（去掉 funcName:lineno，保持人类可读性） - self.formatter = logging.Formatter( - "%(asctime)s - %(name)s - %(levelname)s - %(message)s" - ) - - # 创建logger实例 - self.logger = self._setup_logger() - - def _setup_logger(self): - """设置logger实例""" - logger = logging.getLogger(self.name) - logger.setLevel(self.log_level) - - # 避免重复添加处理器 - if logger.handlers: - logger.handlers.clear() - - # 控制台处理器 - console_handler = logging.StreamHandler(sys.stdout) - console_handler.setLevel(self.log_level) - console_handler.setFormatter(self.formatter) - logger.addHandler(console_handler) - - # 文件处理器 - 按日期分割 - date_str = datetime.now().strftime("%Y-%m-%d") - log_file = self.log_dir / f"{self.name}_{date_str}.log" - - file_handler = RotatingFileHandler( - str(log_file), - maxBytes=self.max_bytes, - backupCount=self.backup_count, - encoding="utf-8", - ) - file_handler.setLevel(self.log_level) - file_handler.setFormatter(self.formatter) - logger.addHandler(file_handler) - - return logger - - def get_logger(self): - """获取配置好的logger实例""" - return self.logger - - -# 全局日志实例 -_logger_instance = None - - -def setup_global_logger( - name: str = "ai-chat-server", - log_level: str = "INFO", - log_dir: str = "logs", - max_bytes: int = 10 * 1024 * 1024, - backup_count: int = 5, -): - """ - 设置全局日志系统 - - Args: - name: 日志记录器名称 - log_level: 日志级别 - log_dir: 日志文件目录 - max_bytes: 最大文件大小 - backup_count: 备份文件数 - """ - global _logger_instance - logger_setup = LoggerSetup(name, log_level, log_dir, max_bytes, backup_count) - _logger_instance = logger_setup.get_logger() - return _logger_instance - - -def get_logger(name: str = None): - """ - 获取日志记录器实例 - - Args: - name: 如果提供，返回子记录器；否则返回全局记录器 - """ - global _logger_instance - if _logger_instance is None: - # 如果没有初始化，默认创建一个 - _logger_instance = setup_global_logger() - - if name and name != _logger_instance.name: - return _logger_instance.getChild(name) - return _logger_instance - - -# 便捷的日志记录函数 -def log_debug(message: str, *args, **kwargs): - """记录DEBUG级别日志""" - logger = get_logger() - logger.debug(message, *args, **kwargs) - - -def log_info(message: str, *args, **kwargs): - """记录INFO级别日志""" - logger = get_logger() - logger.info(message, *args, **kwargs) - - -def log_warning(message: str, *args, **kwargs): - """记录WARNING级别日志""" - logger = get_logger() - logger.warning(message, *args, **kwargs) - - -def log_error(message: str, *args, **kwargs): - """记录ERROR级别日志""" - logger = get_logger() - logger.error(message, *args, **kwargs) - - -def log_critical(message: str, *args, **kwargs): - """记录CRITICAL级别日志""" - logger = get_logger() - logger.critical(message, *args, **kwargs) - - -def log_exception(message: str = ""): - """记录异常信息""" - logger = get_logger() - logger.exception(message) - - -def log_structured(level: str, message: str, **details): - """ - 记录结构化日志 - - Args: - level: 日志级别 - message: 日志消息 - **details: 额外的结构化数据 - """ - logger = get_logger() - # 为了开发时的可读性，不再使用单行 JSON 打印全结构 - # 转换为更易读的格式 - detail_str = ", ".join(f"{k}={v}" for k, v in details.items() if v) - formatted_msg = f"[{message}] {detail_str}" - - getattr(logger, level.lower())(formatted_msg) - - -def log_request_info( - method: str, - path: str, - client_ip: str = "unknown", - user_agent: str = "", - referer: str = "", -): - """记录请求信息日志""" - log_structured( - "info", - "API Request", - method=method, - path=path, - client_ip=client_ip, - user_agent=user_agent, - referer=referer, - ) - - -def log_response_info( - status_code: int, - process_time: float, - path: str = "", - method: str = "", - client_ip: str = "", -): - """记录响应信息日志""" - log_structured( - "info", - "API Response", - status_code=status_code, - process_time_ms=process_time, - path=path, - method=method, - client_ip=client_ip, - ) - - -def log_error_detail( - error_type: str, error_message: str, traceback_info: str = "", context: dict = None -): - """记录详细的错误信息""" - log_structured( - "error", - f"{error_type}: {error_message}", - traceback=traceback_info, - context=context or {}, - ) - - -def log_chat_interaction( - user_input: str, - ai_response: str, - model: str = "", - conversation_id: str = "", - tokens_used: dict = None, -): - """记录聊天交互日志""" - log_structured( - "info", - "Chat Interaction", - user_input=( - user_input[:100] + "..." if len(user_input) > 100 else user_input - ), # 截断长输入 - ai_response=( - ai_response[:100] + "..." if len(ai_response) > 100 else ai_response - ), - model=model, - conversation_id=conversation_id, - tokens_used=tokens_used, - ) - - -def log_system_status( - status: str, - uptime: float = 0, - cpu_usage: float = 0, - memory_usage: float = 0, - disk_usage: float = 0, -): - """记录系统状态日志""" - log_structured( - "info", - "System Status", - status=status, - uptime_seconds=uptime, - cpu_percent=cpu_usage, - memory_percent=memory_usage, - disk_percent=disk_usage, - ) +""" +统一日志管理系统 +提供结构化日志记录功能，支持不同日志级别、文件输出、轮转等 +""" + +import json +import logging +import os +import sys +from datetime import datetime +from logging.handlers import RotatingFileHandler +from pathlib import Path + + +class LoggerSetup: + """日志系统配置类""" + + def __init__( + self, + name: str = "ai-chat-server", + log_level: str = "INFO", + log_dir: str = "logs", + max_bytes: int = 10 * 1024 * 1024, + backup_count: int = 5, + ): + """ + 初始化日志系统 + + Args: + name: 日志记录器名称 + log_level: 日志级别 ('DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL') + log_dir: 日志文件存储目录 + max_bytes: 单个日志文件最大大小（字节） + backup_count: 保留的备份文件数量 + """ + self.name = name + self.log_level = getattr(logging, log_level.upper(), logging.INFO) + self.log_dir = Path(log_dir) + self.max_bytes = max_bytes + self.backup_count = backup_count + + # 创建日志目录 + self.log_dir.mkdir(exist_ok=True) + + # 设置日志格式（去掉 funcName:lineno，保持人类可读性） + self.formatter = logging.Formatter( + "%(asctime)s - %(name)s - %(levelname)s - %(message)s" + ) + + # 创建logger实例 + self.logger = self._setup_logger() + + def _setup_logger(self): + """设置logger实例""" + logger = logging.getLogger(self.name) + logger.setLevel(self.log_level) + + # 避免重复添加处理器 + if logger.handlers: + logger.handlers.clear() + + # 控制台处理器 + console_handler = logging.StreamHandler(sys.stdout) + console_handler.setLevel(self.log_level) + console_handler.setFormatter(self.formatter) + logger.addHandler(console_handler) + + # 文件处理器 - 按日期分割 + date_str = datetime.now().strftime("%Y-%m-%d") + log_file = self.log_dir / f"{self.name}_{date_str}.log" + + file_handler = RotatingFileHandler( + str(log_file), + maxBytes=self.max_bytes, + backupCount=self.backup_count, + encoding="utf-8", + ) + file_handler.setLevel(self.log_level) + file_handler.setFormatter(self.formatter) + logger.addHandler(file_handler) + + return logger + + def get_logger(self): + """获取配置好的logger实例""" + return self.logger + + +# 全局日志实例 +_logger_instance = None + + +def setup_global_logger( + name: str = "ai-chat-server", + log_level: str = "INFO", + log_dir: str = "logs", + max_bytes: int = 10 * 1024 * 1024, + backup_count: int = 5, +): + """ + 设置全局日志系统 + + Args: + name: 日志记录器名称 + log_level: 日志级别 + log_dir: 日志文件目录 + max_bytes: 最大文件大小 + backup_count: 备份文件数 + """ + global _logger_instance + logger_setup = LoggerSetup(name, log_level, log_dir, max_bytes, backup_count) + _logger_instance = logger_setup.get_logger() + return _logger_instance + + +def get_logger(name: str = None): + """ + 获取日志记录器实例 + + Args: + name: 如果提供，返回子记录器；否则返回全局记录器 + """ + global _logger_instance + if _logger_instance is None: + # 如果没有初始化，默认创建一个 + _logger_instance = setup_global_logger() + + if name and name != _logger_instance.name: + return _logger_instance.getChild(name) + return _logger_instance + + +# 便捷的日志记录函数 +def log_debug(message: str, *args, **kwargs): + """记录DEBUG级别日志""" + logger = get_logger() + logger.debug(message, *args, **kwargs) + + +def log_info(message: str, *args, **kwargs): + """记录INFO级别日志""" + logger = get_logger() + logger.info(message, *args, **kwargs) + + +def log_warning(message: str, *args, **kwargs): + """记录WARNING级别日志""" + logger = get_logger() + logger.warning(message, *args, **kwargs) + + +def log_error(message: str, *args, **kwargs): + """记录ERROR级别日志""" + logger = get_logger() + logger.error(message, *args, **kwargs) + + +def log_critical(message: str, *args, **kwargs): + """记录CRITICAL级别日志""" + logger = get_logger() + logger.critical(message, *args, **kwargs) + + +def log_exception(message: str = ""): + """记录异常信息""" + logger = get_logger() + logger.exception(message) + + +def log_structured(level: str, message: str, **details): + """ + 记录结构化日志 + + Args: + level: 日志级别 + message: 日志消息 + **details: 额外的结构化数据 + """ + logger = get_logger() + # 为了开发时的可读性，不再使用单行 JSON 打印全结构 + # 转换为更易读的格式 + detail_str = ", ".join(f"{k}={v}" for k, v in details.items() if v) + formatted_msg = f"[{message}] {detail_str}" + + getattr(logger, level.lower())(formatted_msg) + + +def log_request_info( + method: str, + path: str, + client_ip: str = "unknown", + user_agent: str = "", + referer: str = "", +): + """记录请求信息日志""" + log_structured( + "info", + "API Request", + method=method, + path=path, + client_ip=client_ip, + user_agent=user_agent, + referer=referer, + ) + + +def log_response_info( + status_code: int, + process_time: float, + path: str = "", + method: str = "", + client_ip: str = "", +): + """记录响应信息日志""" + log_structured( + "info", + "API Response", + status_code=status_code, + process_time_ms=process_time, + path=path, + method=method, + client_ip=client_ip, + ) + + +def log_error_detail( + error_type: str, error_message: str, traceback_info: str = "", context: dict = None +): + """记录详细的错误信息""" + log_structured( + "error", + f"{error_type}: {error_message}", + traceback=traceback_info, + context=context or {}, + ) + + +def log_chat_interaction( + user_input: str, + ai_response: str, + model: str = "", + conversation_id: str = "", + tokens_used: dict = None, +): + """记录聊天交互日志""" + log_structured( + "info", + "Chat Interaction", + user_input=( + user_input[:100] + "..." if len(user_input) > 100 else user_input + ), # 截断长输入 + ai_response=( + ai_response[:100] + "..." if len(ai_response) > 100 else ai_response + ), + model=model, + conversation_id=conversation_id, + tokens_used=tokens_used, + ) + + +def log_system_status( + status: str, + uptime: float = 0, + cpu_usage: float = 0, + memory_usage: float = 0, + disk_usage: float = 0, +): + """记录系统状态日志""" + log_structured( + "info", + "System Status", + status=status, + uptime_seconds=uptime, + cpu_percent=cpu_usage, + memory_percent=memory_usage, + disk_percent=disk_usage, + ) diff --git a/server/database/__init__.py b/server/database/__init__.py new file mode 100644 index 0000000..db014e9 --- /dev/null +++ b/server/database/__init__.py @@ -0,0 +1,91 @@ +""" +数据库模块 + +提供 SQLite 数据库连接和会话管理功能。 +""" + +import os +import sqlite3 +from pathlib import Path +from contextlib import contextmanager +from typing import Optional + +# 默认数据库路径 +DEFAULT_DB_PATH = Path(__file__).parent.parent / "data" / "chat.db" + + +def init_db(db_path: Optional[str] = None): + """ + 初始化数据库 + 创建必要的表结构 + """ + if db_path is None: + db_path = os.getenv("DB_PATH", str(DEFAULT_DB_PATH)) + + # 确保数据目录存在 + Path(db_path).parent.mkdir(parents=True, exist_ok=True) + + conn = sqlite3.connect(db_path) + cursor = conn.cursor() + + # 创建会话表 + cursor.execute(""" + CREATE TABLE IF NOT EXISTS conversations ( + id TEXT PRIMARY KEY, + title TEXT, + model TEXT, + created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, + updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP + ) + """) + + # 创建消息表 + cursor.execute(""" + CREATE TABLE IF NOT EXISTS messages ( + id TEXT PRIMARY KEY, + conversation_id TEXT, + role TEXT, + content TEXT, + created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, + FOREIGN KEY (conversation_id) REFERENCES conversations(id) ON DELETE CASCADE + ) + """) + + # 创建文件表 + cursor.execute(""" + CREATE TABLE IF NOT EXISTS files ( + id TEXT PRIMARY KEY, + conversation_id TEXT, + filename TEXT, + file_path TEXT, + file_type TEXT, + created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, + FOREIGN KEY (conversation_id) REFERENCES conversations(id) ON DELETE CASCADE + ) + """) + + conn.commit() + conn.close() + + print(f"[数据库] 初始化完成: {db_path}") + + +@contextmanager +def get_db(db_path: Optional[str] = None): + """ + 获取数据库连接的上下文管理器 + + 用法: + with get_db() as db: + cursor = db.execute("SELECT * FROM conversations") + rows = cursor.fetchall() + """ + if db_path is None: + db_path = os.getenv("DB_PATH", str(DEFAULT_DB_PATH)) + + conn = sqlite3.connect(db_path) + conn.row_factory = sqlite3.Row + try: + yield conn + finally: + conn.close() diff --git a/server/logging.conf b/server/logging.conf deleted file mode 100644 index ac0a9cd..0000000 --- a/server/logging.conf +++ /dev/null @@ -1,14 +0,0 @@ -# 日志配置文件 -# 可以在 .env 文件中设置以下环境变量来控制日志行为 - -# 日志级别: DEBUG, INFO, WARNING, ERROR, CRITICAL -LOG_LEVEL=INFO - -# 日志文件目录 -LOG_DIR=logs - -# 日志文件最大大小 (字节) -LOG_MAX_BYTES=10485760 # 10MB - -# 保留的备份日志文件数量 -LOG_BACKUP_COUNT=5 \ No newline at end of file diff --git a/server/main.py b/server/main.py index a5ff1b3..f2513ee 100644 --- a/server/main.py +++ b/server/main.py @@ -41,7 +41,7 @@ sys.path.append("/home/mt/project/ai-chat-ui/server") # ── 工具/日志（与平台无关）─────────────────────────────────────────── from utils.helpers import log_response -from utils.logger import get_logger +from core import get_logger logger = get_logger() @@ -99,7 +99,7 @@ async def logging_middleware(request: Request, call_next): @app.get("/health") async def health_check(): - from config import get_available_providers + from config.settings import get_available_providers return { "status": "healthy", @@ -216,7 +216,7 @@ if __name__ == "__main__": port = int(os.getenv("PORT", 8000)) # 获取可用平台 - from config import get_available_providers + from config.settings import get_available_providers available = get_available_providers() diff --git a/server/utils/file_cache.py b/server/utils/file_cache.py deleted file mode 100644 index 390a163..0000000 --- a/server/utils/file_cache.py +++ /dev/null @@ -1,67 +0,0 @@ -""" -GLM 文件 ID 缓存（基于磁盘的简单 KV，sha256 → file_id，3天有效期） -""" - -import hashlib -import json -import threading -import time -from pathlib import Path - -_CACHE_FILE = Path(__file__).parent.parent / "uploads" / ".glm_file_cache.json" -_lock = threading.Lock() -_TTL = 3 * 24 * 3600 # 3天 - - -def _load() -> dict: - try: - if _CACHE_FILE.exists(): - return json.loads(_CACHE_FILE.read_text(encoding="utf-8")) - except Exception: - pass - return {} - - -def _save(data: dict) -> None: - try: - _CACHE_FILE.parent.mkdir(parents=True, exist_ok=True) - _CACHE_FILE.write_text( - json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8" - ) - except Exception as e: - print(f"[file_cache] 写入失败：{e}") - - -def sha256_of_file(file_path: Path) -> str: - h = hashlib.sha256() - with open(file_path, "rb") as f: - for chunk in iter(lambda: f.read(65536), b""): - h.update(chunk) - return h.hexdigest() - - -def get(file_hash: str) -> dict | None: - with _lock: - data = _load() - entry = data.get(file_hash) - if not entry: - return None - if entry.get("expires_at", 0) <= time.time(): - data.pop(file_hash, None) - _save(data) - return None - return entry - - -def set(file_hash: str, file_id: str) -> None: - with _lock: - data = _load() - data[file_hash] = {"file_id": file_id, "expires_at": time.time() + _TTL} - _save(data) - - -def delete(file_hash: str) -> None: - with _lock: - data = _load() - data.pop(file_hash, None) - _save(data) diff --git a/server/utils/glm_adapter.py b/server/utils/glm_adapter.py deleted file mode 100644 index ac7c56d..0000000 --- a/server/utils/glm_adapter.py +++ /dev/null @@ -1,523 +0,0 @@ -""" -GLM-4.6V 适配层（基于 zai-sdk） -SDK：pip install zai-sdk -模型：glm-4.6v（支持文本/图像/文档/深度思考） -""" - -import base64 -import json -import os -import sys -import threading -from pathlib import Path -from typing import AsyncGenerator - - -# ── 自动注入 venv site-packages ─────────────────────────────────────── -def _ensure_venv(): - server_dir = Path(__file__).parent.parent - for sp in sorted( - (server_dir / ".venv" / "lib").glob("python*/site-packages"), reverse=True - ): - if sp.exists() and str(sp) not in sys.path: - sys.path.insert(0, str(sp)) - print(f"[GLM] venv 注入：{sp}") - break - - -# ── 客户端单例 ──────────────────────────────────────────────────────── -_client = None - - -def get_client(): - global _client - if _client is None: - _ensure_venv() - try: - from zai import ZhipuAiClient - except ImportError: - raise ImportError("GLM 模式需要安装 zai-sdk：.venv/bin/pip install zai-sdk") - api_key = os.getenv("ZHIPU_API_KEY").strip() or os.getenv("GLM_API_KEY").strip() - if not api_key: - raise ValueError("GLM 模式需要设置环境变量 ZHIPU_API_KEY") - _client = ZhipuAiClient(api_key=api_key) - print("[GLM] ZhipuAiClient 初始化完成（zai-sdk）") - return _client - - -# ── 模型映射 ────────────────────────────────────────────────────────── -DEFAULT_TEXT_MODEL = "glm-4-flash" # 默认文本模型 -DEFAULT_VISION_MODEL = "glm-4.6v" # 图片/附件识别用 glm-4.6v - - -def resolve_model(model: str, has_vision: bool = False) -> str: - # 当消息包含图片或附件时，使用视觉模型 - if has_vision: - print(f"[GLM] 检测到图片/附件，使用视觉模型：{model} → {DEFAULT_VISION_MODEL}") - return DEFAULT_VISION_MODEL - # 普通文本对话，保持原模型不变 - print(f"[GLM] 使用模型：{model}") - return model - - -# ── 文件上传（含 file_id 缓存）─────────────────────────────────────── -def upload_file_for_extract(local_path: Path) -> str: - from utils.file_cache import get as cache_get - from utils.file_cache import set as cache_set - from utils.file_cache import sha256_of_file - - file_hash = sha256_of_file(local_path) - cached = cache_get(file_hash) - if cached: - print(f"[GLM] file_id 缓存命中：{local_path.name} → {cached['file_id']}") - return cached["file_id"] - - client = get_client() - mime_map = { - ".pdf": "application/pdf", - ".docx": "application/vnd.openxmlformats-officedocument.wordprocessingml.document", - ".doc": "application/msword", - ".xlsx": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", - ".xls": "application/vnd.ms-excel", - ".pptx": "application/vnd.openxmlformats-officedocument.presentationml.presentation", - ".ppt": "application/vnd.ms-powerpoint", - } - mime = mime_map.get(local_path.suffix.lower(), "application/octet-stream") - print(f"[GLM] 上传文件：{local_path.name}（{mime}）") - with open(local_path, "rb") as f: - file_obj = client.files.create( - file=(local_path.name, f, mime), purpose="file-extract" - ) - file_id = file_obj.id - cache_set(file_hash, file_id) - print(f"[GLM] 上传成功：file_id={file_id}") - return file_id - - -# ── 图像编码 ───────────────────────────────────────────────────────── -def encode_image(image_source: str) -> dict: - """将图像来源统一转为 OpenAI image_url 格式""" - if image_source.startswith("data:image") or image_source.startswith( - ("http://", "https://") - ): - return {"type": "image_url", "image_url": {"url": image_source}} - # 本地路径 → base64 - local = Path(image_source.replace("file://", "").lstrip("/")) - if not local.exists(): - local = Path.cwd() / local - ext = local.suffix.lstrip(".") - with open(local, "rb") as f: - b64 = base64.b64encode(f.read()).decode() - return {"type": "image_url", "image_url": {"url": f"data:image/{ext};base64,{b64}"}} - - -# ── 消息格式转换 ────────────────────────────────────────────────────── -def build_glm_messages(messages: list, files: list | None = None) -> tuple[list, bool]: - """ - 将 OpenAI 格式的 messages + files 转换为 zai-sdk 所需格式。 - 返回 (glm_messages, has_vision)。 - """ - from urllib.parse import urlparse - - glm_messages = [] - has_vision = False - - for msg in messages: - if not isinstance(msg, dict): - glm_messages.append({"role": "user", "content": str(msg)}) - continue - role = msg.get("role", "user") - content = msg.get("content", "") - - if isinstance(content, str): - glm_messages.append({"role": role, "content": content}) - elif isinstance(content, list): - new_content = [] - for item in content: - if not isinstance(item, dict): - new_content.append({"type": "text", "text": str(item)}) - continue - t = item.get("type") - if t == "text": - new_content.append({"type": "text", "text": item.get("text", "")}) - elif t == "image_url": - has_vision = True - img_val = item.get("image_url", "") - img_src = ( - img_val.get("url", "") if isinstance(img_val, dict) else img_val - ) - new_content.append(encode_image(img_src)) - elif t == "file_url": - # file_url 类型（PDF/DOCX/TXT 等文档链接）原样透传 - has_vision = True - new_content.append(item) - else: - new_content.append({"type": "text", "text": str(item)}) - glm_messages.append({"role": role, "content": new_content}) - else: - glm_messages.append({"role": role, "content": str(content)}) - - # 处理独立附件列表 - if files: - doc_exts = { - ".pdf", - ".doc", - ".docx", - ".xlsx", - ".xls", - ".pptx", - ".ppt", - ".txt", - ".md", - ".csv", - ".json", - ".log", - } - img_exts = {".jpg", ".jpeg", ".png", ".gif", ".bmp", ".webp"} - inserts = [] - - for file_url in files: - parsed = urlparse(file_url) - filename = parsed.path.split("/")[-1] - suffix = Path(filename).suffix.lower() - - # ── 远程 URL（OSS 等）→ 直接透传 ───────────────── - if file_url.startswith(("http://", "https://")): - has_vision = True - if suffix in img_exts: - inserts.append( - {"type": "image_url", "image_url": {"url": file_url}} - ) - else: - # 文档/文本类统一走 file_url - inserts.append({"type": "file_url", "file_url": {"url": file_url}}) - continue - - # ── 本地文件回退逻辑 ────────────────────────────── - rel = parsed.path.lstrip("/") - local = Path(rel) - - if suffix in img_exts: - has_vision = True - try: - inserts.append(encode_image(f"file://{rel}")) - except Exception as e: - print(f"[GLM] 图像编码失败：{e}") - elif suffix in doc_exts: - has_vision = True - if local.exists(): - try: - fid = upload_file_for_extract(local) - inserts.append({"type": "file", "file": {"file_id": fid}}) - except Exception as e: - inserts.append( - {"type": "text", "text": f"[文件上传失败：{filename}，{e}]"} - ) - else: - inserts.append( - {"type": "text", "text": f"[附件：{filename}，类型：{suffix}]"} - ) - - if inserts: - for i in range(len(glm_messages) - 1, -1, -1): - if glm_messages[i].get("role") == "user": - old = glm_messages[i]["content"] - if isinstance(old, str): - new_content = inserts + [{"type": "text", "text": old}] - elif isinstance(old, list): - new_content = inserts + old - else: - new_content = inserts - glm_messages[i] = {"role": "user", "content": new_content} - break - - return glm_messages, has_vision - - -# ── 网络搜索 tool 构建 ────────────────────────────────────────────── -def _build_web_search_tool(mode: str | bool) -> dict: - """ - 根据搜索模式构建 web_search tool 配置。 - - mode: - - True / "simple" : 简单搜索（search_std + medium, 10条） - - "deep" : 深度搜索（search_pro + high, 20条） - """ - if mode == "deep": - # 深度搜索：高阶搜索引擎 + 详细内容 + 更多结果 - return { - "type": "web_search", - "web_search": { - "enable": True, - "search_result": True, - "search_engine": "search_pro", - "content_size": "high", - "count": 20, - }, - } - # 简单搜索（默认）：基础搜索引擎 + 摘要内容 - return { - "type": "web_search", - "web_search": { - "enable": True, - "search_result": True, - "search_engine": "search_std", - "content_size": "medium", - "count": 10, - }, - } - - -# ── 哨兵对象 ───────────────────────────────────────────────────────── -_SENTINEL = object() - - -# ── 流式调用 ──────────────────────────────────────────────────────── -async def glm_stream_generator( - messages: list, - model: str, - temperature: float, - max_tokens: int, - files: list | None = None, - web_search: str | bool = False, - deep_thinking: bool = False, -) -> AsyncGenerator[str, None]: - """ - GLM 流式 SSE 生成器。 - 使用 queue.Queue + 专用线程（生产者）+ asyncio 消费者模式， - 让 zai-sdk 同步迭代器在单一线程内安全运行。 - - web_search: - - False / "" : 不启用联网搜索 - - True / "simple" : 简单搜索（search_std + medium） - - "deep" : 深度搜索（search_pro + high + 更多结果） - """ - import asyncio - import queue - - from utils.helpers import generate_unique_id, get_current_timestamp - - glm_msgs, has_vision = build_glm_messages(messages, files) - actual_model = resolve_model(model, has_vision) - - extra_kwargs: dict = {} - if web_search: - extra_kwargs["tools"] = [_build_web_search_tool(web_search)] - if not deep_thinking: - # 智普默认开启思考模式，所以要用非门（不知道“非门”描述是否准确。前端选择开启思考模式，这里不做变动。前端选择关闭思考模式，这里关闭。） - extra_kwargs["thinking"] = {"type": "disabled"} - print( - f"[GLM] 流式请求：model={actual_model} vision={has_vision} " - f"web_search={web_search} thinking={deep_thinking}" - ) - # ── 调试：打印发送给 GLM 的完整消息结构 ── - for i, msg in enumerate(glm_msgs): - role = msg.get("role", "?") - content = msg.get("content", "") - if isinstance(content, list): - for j, part in enumerate(content): - if not isinstance(part, dict): - print(f"[GLM-DEBUG] msg[{i}].content[{j}]: {type(part).__name__}") - continue - part_type = part.get("type", "?") - if part_type == "image_url": - img_val = part.get("image_url", "") - img_url = ( - img_val.get("url", "") - if isinstance(img_val, dict) - else str(img_val) - ) - display = img_url[:120] + "..." if len(img_url) > 120 else img_url - print( - f"[GLM-DEBUG] msg[{i}].content[{j}]: type=image_url, url={display}" - ) - elif part_type == "text": - preview = (part.get("text", "") or "")[:100] - print( - f"[GLM-DEBUG] msg[{i}].content[{j}]: type=text, text={preview}" - ) - else: - print(f"[GLM-DEBUG] msg[{i}].content[{j}]: {part}") - else: - print(f"[GLM-DEBUG] msg[{i}]: role={role}, content={str(content)[:150]}") - if extra_kwargs: - print(f"[GLM-DEBUG] extra_kwargs={extra_kwargs}") - # 原始 JSON 转储（用于排查结构问题） - import json as _json - - print( - f"[GLM-RAW] messages={_json.dumps(glm_msgs, ensure_ascii=False, default=str)[:2000]}" - ) - - chunk_queue: queue.Queue = queue.Queue(maxsize=128) - - def _producer(): - try: - client = get_client() - resp = client.chat.completions.create( - model=actual_model, - messages=glm_msgs, - stream=True, - temperature=temperature, - max_tokens=max_tokens, - **extra_kwargs, - ) - for chunk in resp: - chunk_queue.put(chunk) - except Exception as exc: - chunk_queue.put(exc) - finally: - chunk_queue.put(_SENTINEL) - - t = threading.Thread(target=_producer, daemon=True) - t.start() - - loop = asyncio.get_running_loop() - - full_reasoning = "" # 累计思考内容（用于判断是否首次） - full_content = "" # 累计正式回答（用于判断是否首次） - - while True: - item = await loop.run_in_executor(None, chunk_queue.get) - - if item is _SENTINEL: - break - - if isinstance(item, Exception): - print(f"[GLM] 生产者异常：{item}") - yield f"data: {json.dumps({'error': {'message': str(item), 'type': 'glm_error'}}, ensure_ascii=False)}\n\n" - break - - try: - delta = item.choices[0].delta - reasoning = getattr(delta, "reasoning_content", "") or "" - text = getattr(delta, "content", "") or "" - - delta_str = "" - - # ── 思考过程（reasoning_content）──────────────────────── - if reasoning: - if not full_reasoning: - # 首个思考片段：添加 开始标签 - delta_str += "" - full_reasoning += reasoning - delta_str += reasoning - - # ── 正式回答（content）────────────────────────────────── - if text: - if not full_content and full_reasoning: - # 思考结束后首次出现正式回答：关闭 标签 - delta_str += "\n\n" - full_content += text - delta_str += text - - if not delta_str: - continue - - data = { - "id": f"chatcmpl-{generate_unique_id()}", - "object": "chat.completion.chunk", - "created": get_current_timestamp(), - "model": actual_model, - "choices": [ - {"index": 0, "delta": {"content": delta_str}, "finish_reason": None} - ], - } - yield f"data: {json.dumps(data, ensure_ascii=False)}\n\n" - - except Exception as e: - print(f"[GLM] chunk 解析异常：{e}") - - finish = { - "id": f"chatcmpl-{generate_unique_id()}", - "object": "chat.completion.chunk", - "created": get_current_timestamp(), - "model": actual_model, - "choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}], - } - yield f"data: {json.dumps(finish, ensure_ascii=False)}\n\n" - yield "data: [DONE]\n\n" - - -# ── 非流式调用 ──────────────────────────────────────────────────────── -def glm_chat_sync( - messages: list, - model: str, - temperature: float, - max_tokens: int, - files: list | None = None, - web_search: str | bool = False, - deep_thinking: bool = False, -) -> dict: - """ - web_search: - - False / "" : 不启用联网搜索 - - True / "simple" : 简单搜索（search_std + medium） - - "deep" : 深度搜索（search_pro + high + 更多结果） - """ - glm_msgs, has_vision = build_glm_messages(messages, files) - actual_model = resolve_model(model, has_vision) - - extra_kwargs: dict = {} - if web_search: - extra_kwargs["tools"] = [_build_web_search_tool(web_search)] - if deep_thinking: - extra_kwargs["thinking"] = {"type": "enabled"} - - client = get_client() - print(f"[GLM] 非流式请求：model={actual_model}") - # ── 调试：打印发送给 GLM 的完整消息结构 ── - for i, msg in enumerate(glm_msgs): - role = msg.get("role", "?") - content = msg.get("content", "") - if isinstance(content, list): - for j, part in enumerate(content): - if not isinstance(part, dict): - print(f"[GLM-DEBUG] msg[{i}].content[{j}]: {type(part).__name__}") - continue - part_type = part.get("type", "?") - if part_type == "image_url": - img_val = part.get("image_url", "") - img_url = ( - img_val.get("url", "") - if isinstance(img_val, dict) - else str(img_val) - ) - display = img_url[:120] + "..." if len(img_url) > 120 else img_url - print( - f"[GLM-DEBUG] msg[{i}].content[{j}]: type=image_url, url={display}" - ) - elif part_type == "text": - preview = (part.get("text", "") or "")[:100] - print( - f"[GLM-DEBUG] msg[{i}].content[{j}]: type=text, text={preview}" - ) - else: - print(f"[GLM-DEBUG] msg[{i}].content[{j}]: {part}") - else: - print(f"[GLM-DEBUG] msg[{i}]: role={role}, content={str(content)[:150]}") - if extra_kwargs: - print(f"[GLM-DEBUG] extra_kwargs={extra_kwargs}") - # 原始 JSON 转储（用于排查结构问题） - import json as _json - - print( - f"[GLM-RAW] messages={_json.dumps(glm_msgs, ensure_ascii=False, default=str)[:2000]}" - ) - resp = client.chat.completions.create( - model=actual_model, - messages=glm_msgs, - stream=False, - temperature=temperature, - max_tokens=max_tokens, - **extra_kwargs, - ) - content = resp.choices[0].message.content or "" - usage = None - if hasattr(resp, "usage") and resp.usage: - usage = { - "promptTokens": resp.usage.prompt_tokens, - "completionTokens": resp.usage.completion_tokens, - "totalTokens": resp.usage.total_tokens, - } - return {"content": content, "model": actual_model, "usage": usage} diff --git a/server/utils/helpers.py b/server/utils/helpers.py index b136eb1..0459112 100644 --- a/server/utils/helpers.py +++ b/server/utils/helpers.py @@ -8,7 +8,7 @@ import uuid from datetime import datetime from typing import Dict -from .logger import (log_chat_interaction, log_error_detail, log_request_info, +from core import (log_chat_interaction, log_error_detail, log_request_info, log_response_info) diff --git a/server/utils/test_glm_search.py b/server/utils/test_glm_search.py deleted file mode 100644 index 7acb47b..0000000 --- a/server/utils/test_glm_search.py +++ /dev/null @@ -1,37 +0,0 @@ -import asyncio -import os -import sys -from pathlib import Path - -# Add project root to sys.path -root_dir = Path(__file__).parent -sys.path.insert(0, str(root_dir)) - -# Set API key from .env if needed -from dotenv import load_dotenv - -from utils.glm_adapter import _ensure_venv, glm_chat_sync, glm_stream_generator - -load_dotenv() - - -async def test_stream(): - msgs = [{"role": "user", "content": "今天北京天气怎样？"}] - print("Testing stream...") - async for chunk in glm_stream_generator( - msgs, "glm-4.5-air", 0.7, 1024, web_search=True - ): - print(chunk, end="") - - -def test_sync(): - msgs = [{"role": "user", "content": "今天几号？武汉天气怎样？"}] - print("Testing sync...") - res = glm_chat_sync(msgs, "glm-4.5-air", 0.7, 1024, web_search=True) - print(res) - - -if __name__ == "__main__": - _ensure_venv() - # test_sync() - asyncio.run(test_stream()) diff --git a/server/utils/test_oss_doc_glm.py b/server/utils/test_oss_doc_glm.py deleted file mode 100644 index 6a1d35a..0000000 --- a/server/utils/test_oss_doc_glm.py +++ /dev/null @@ -1,171 +0,0 @@ -""" -测试脚本：上传 PDF / DOCX / TXT 文件到阿里云 OSS → 获取 URL → 发送给 GLM-4.6V 识别 - -支持的文件类型: - - .pdf → 上传 OSS 后以 file_url 类型发送 URL 给 GLM - - .docx → 上传 OSS 后以 file_url 类型发送 URL 给 GLM - - .txt → 上传 OSS 后以 file_url 类型发送 URL 给 GLM - -用法: - cd server - source ~/.bashrc && source .venv/bin/activate - python -m utils.test_oss_doc_glm --file <本地文件路径> [--prompt "请总结这份文件"] -""" - -import argparse -import sys -from pathlib import Path - -# 确保 server 目录在 sys.path -sys.path.insert(0, str(Path(__file__).resolve().parent.parent)) - -from utils.oss_uploader import upload_file -from utils.glm_adapter import glm_chat_sync - - -# 文件类型分组 -DOC_EXTS = {".pdf", ".doc", ".docx", ".xlsx", ".xls", ".pptx", ".ppt"} -TXT_EXTS = {".txt", ".md", ".csv", ".json", ".log"} -IMG_EXTS = {".jpg", ".jpeg", ".png", ".gif", ".bmp", ".webp"} -# 所有可通过 file_url 发送的类型 -FILE_URL_EXTS = DOC_EXTS | TXT_EXTS - - -def detect_file_type(suffix: str) -> str: - """根据后缀判断文件类别: 'file_url' / 'image' / 'unknown'""" - suffix = suffix.lower() - if suffix in FILE_URL_EXTS: - return "file_url" - elif suffix in IMG_EXTS: - return "image" - return "unknown" - - -def build_messages_for_file_url(file_url: str, prompt: str) -> list: - """ - 为文档/文本文件构建消息。 - 使用 file_url 类型，直接传递 OSS 的 URL 给 GLM。 - """ - return [ - { - "role": "user", - "content": [ - { - "type": "file_url", - "file_url": {"url": file_url}, - }, - { - "type": "text", - "text": prompt, - }, - ], - } - ] - - -def build_messages_for_image(file_url: str, prompt: str) -> list: - """为图片文件构建消息，使用 image_url 类型。""" - return [ - { - "role": "user", - "content": [ - {"type": "image_url", "image_url": {"url": file_url}}, - {"type": "text", "text": prompt}, - ], - } - ] - - -def main(): - parser = argparse.ArgumentParser( - description="上传 PDF/DOCX/TXT 文件到 OSS 并让 GLM-4.6V 识别" - ) - parser.add_argument("--file", required=True, help="要上传的本地文件路径") - parser.add_argument( - "--prompt", default="请总结这份文件的主要内容", help="发给 GLM 的提示词" - ) - parser.add_argument( - "--model", default="glm-4.6v", help="GLM 模型名称（默认: glm-4.6v）" - ) - args = parser.parse_args() - - file_path = Path(args.file).resolve() - if not file_path.exists(): - print(f"❌ 文件不存在: {file_path}") - sys.exit(1) - - suffix = file_path.suffix.lower() - file_type = detect_file_type(suffix) - print(f"📂 文件信息:") - print(f" 路径: {file_path}") - print(f" 后缀: {suffix}") - print(f" 类型: {file_type}") - print(f" 大小: {file_path.stat().st_size / 1024:.1f} KB") - print() - - # ── 第一步：上传文件到 OSS ──────────────────────────────── - print(f"📤 正在上传文件到阿里云 OSS...") - oss_result = upload_file(str(file_path)) - file_url = oss_result["url"] - print(f"✅ OSS 上传成功!") - print(f" URL: {file_url}") - print(f" ETag: {oss_result['etag']}") - print() - - # ── 第二步：根据文件类型构建消息 ────────────────────────── - print(f"🔧 正在构建 GLM 消息...") - - if file_type == "file_url": - # PDF / DOCX / TXT 等：使用 file_url 类型发送 OSS URL - print(f" 策略: 使用 file_url 发送 OSS 链接") - messages = build_messages_for_file_url(file_url, args.prompt) - elif file_type == "image": - # 图片：使用 image_url - print(f" 策略: 使用 image_url 发送 OSS 链接") - messages = build_messages_for_image(file_url, args.prompt) - else: - print(f"❌ 不支持的文件类型: {suffix}") - print(f" 支持: {', '.join(sorted(FILE_URL_EXTS | IMG_EXTS))}") - sys.exit(1) - - print() - - # ── 第三步：发送给 GLM 识别 ────────────────────────────── - print(f"🤖 正在请求 GLM ({args.model}) 识别文件...") - print(f" 提示词: {args.prompt}") - print() - - try: - result = glm_chat_sync( - messages=messages, - model=args.model, - temperature=0.7, - max_tokens=4096, - ) - - print("─" * 60) - print("📝 GLM 回复:") - print("─" * 60) - print(result["content"]) - print("─" * 60) - - if result.get("usage"): - usage = result["usage"] - print( - f"\n📊 Token 用量: 输入 {usage['promptTokens']} | " - f"输出 {usage['completionTokens']} | " - f"总计 {usage['totalTokens']}" - ) - - print(f"\n✅ 测试完成! 使用模型: {result.get('model', args.model)}") - - except Exception as e: - print(f"\n❌ GLM 请求失败: {e}") - import traceback - - traceback.print_exc() - sys.exit(1) - - -if __name__ == "__main__": - main() diff --git a/server/utils/test_oss_glm.py b/server/utils/test_oss_glm.py deleted file mode 100644 index cd0e56a..0000000 --- a/server/utils/test_oss_glm.py +++ /dev/null @@ -1,89 +0,0 @@ -""" -测试脚本：上传文件到 OSS → 获取 URL → 发送给 GLM 进行识别 - -用法: - cd server - source ~/.bashrc && source .venv/bin/activate - python -m utils.test_oss_glm --file <本地文件路径> [--prompt "描述一下这张图片"] -""" - -import argparse -import sys -from pathlib import Path - -# 确保 server 目录在 sys.path -sys.path.insert(0, str(Path(__file__).resolve().parent.parent)) - -from utils.oss_uploader import upload_file -from utils.glm_adapter import glm_chat_sync - - -def main(): - parser = argparse.ArgumentParser(description="上传文件到 OSS 并让 GLM 读取") - parser.add_argument("--file", required=True, help="要上传的本地文件路径") - parser.add_argument( - "--prompt", default="请描述一下这张图片的内容", help="发给 GLM 的提示词" - ) - parser.add_argument( - "--model", default="glm-4.6v", help="GLM 模型名称（默认: glm-4.6v）" - ) - args = parser.parse_args() - - # ── 第一步：上传文件到 OSS ──────────────────────────────── - file_path = args.file - if not Path(file_path).exists(): - print(f"❌ 文件不存在: {file_path}") - sys.exit(1) - - print(f"📤 正在上传文件: {file_path}") - oss_result = upload_file(file_path) - file_url = oss_result["url"] - print(f"✅ 上传成功!") - print(f" URL: {file_url}") - print() - - # ── 第二步：构建消息，把 URL 发给 GLM ────────────────────── - messages = [ - { - "role": "user", - "content": [ - { - "type": "image_url", - "image_url": {"url": file_url}, - }, - { - "type": "text", - "text": args.prompt, - }, - ], - } - ] - - print(f"🤖 正在请求 GLM ({args.model}) 识别图片...") - print(f" 提示词: {args.prompt}") - print() - - result = glm_chat_sync( - messages=messages, - model=args.model, - temperature=0.7, - max_tokens=2048, - ) - - print("─" * 60) - print("📝 GLM 回复:") - print("─" * 60) - print(result["content"]) - print("─" * 60) - - if result.get("usage"): - usage = result["usage"] - print( - f"\n📊 Token 用量: 输入 {usage['promptTokens']} | " - f"输出 {usage['completionTokens']} | " - f"总计 {usage['totalTokens']}" - ) - - -if __name__ == "__main__": - main()