From 5a7aa0668140ef8d2368b84ab24824a6054de532 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E6=9C=B1=E6=BD=AE?= Date: Mon, 16 Mar 2026 13:39:58 +0800 Subject: [PATCH] =?UTF-8?q?v2=20=E5=AE=9E=E7=8E=B0shell=5Fenv=E6=94=AF?= =?UTF-8?q?=E6=8C=81?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- agent/agent_config.py | 79 +++++++++++++++++++++++++++++++++++- routes/chat.py | 93 ++++++++++++++++++++++++++++++++++++++++++- utils/api_models.py | 18 ++++++++- 3 files changed, 185 insertions(+), 5 deletions(-) diff --git a/agent/agent_config.py b/agent/agent_config.py index d8693af..e5c955b 100644 --- a/agent/agent_config.py +++ b/agent/agent_config.py @@ -203,7 +203,7 @@ class AgentConfig: enable_memori=enable_memori, memori_semantic_search_top_k=bot_config.get("memori_semantic_search_top_k", MEM0_SEMANTIC_SEARCH_TOP_K), trace_id=trace_id, - shell_env=getattr(request, 'shell_env', None) or bot_config.get("shell_env") or {}, + shell_env=bot_config.get("shell_env") or {}, ) # 在创建 config 时尽早准备 checkpoint 消息 @@ -218,7 +218,82 @@ class AgentConfig: config.safe_print() return config - + + @classmethod + async def from_v3_request(cls, request, bot_config: Dict, project_dir: Optional[str] = None, messages: Optional[List] = None, language: Optional[str] = None): + """从v3请求创建配置 - 从数据库读取所有配置""" + # 延迟导入避免循环依赖 + from .logging_handler import LoggingCallbackHandler + from utils.fastapi_utils import get_preamble_text + from utils.settings import ( + MEM0_ENABLED, + MEM0_SEMANTIC_SEARCH_TOP_K, + ) + from .checkpoint_utils import prepare_checkpoint_message + from .checkpoint_manager import get_checkpointer_manager + from utils.log_util.context import g + + if messages is None: + messages = [] + + # 从全局上下文获取 trace_id + trace_id = None + try: + trace_id = getattr(g, 'trace_id', None) + except LookupError: + pass + + # 从数据库配置获取语言（如果没有传递） + if language is None: + language = bot_config.get("language", "zh") + + # 处理 system_prompt 和 preamble + system_prompt_from_db = bot_config.get("system_prompt", "") + preamble_text, system_prompt = get_preamble_text(language, system_prompt_from_db) + + + # 从数据库配置获取其他参数 + enable_thinking = bot_config.get("enable_thinking", False) + enable_memori = bot_config.get("enable_memori", False) + + config = cls( + bot_id=request.bot_id, + api_key=bot_config.get("api_key", ""), + model_name=bot_config.get("model", "qwen/qwen3-next-80b-a3b-instruct"), + model_server=bot_config.get("model_server", ""), + language=language, + system_prompt=system_prompt, + mcp_settings=bot_config.get("mcp_settings", []), + user_identifier=bot_config.get("user_identifier", ""), + session_id=request.session_id, + enable_thinking=enable_thinking, + project_dir=project_dir, + stream=request.stream, + tool_response=bot_config.get("tool_response", True), + generate_cfg={}, # v3接口不传递额外的generate_cfg + logging_handler=LoggingCallbackHandler(), + messages=messages, + _origin_messages=messages, + preamble_text=preamble_text, + dataset_ids=bot_config.get("dataset_ids", []), + enable_memori=enable_memori, + memori_semantic_search_top_k=bot_config.get("memori_semantic_search_top_k", MEM0_SEMANTIC_SEARCH_TOP_K), + trace_id=trace_id, + ) + + # 在创建 config 时尽早准备 checkpoint 消息 + if config.session_id: + try: + manager = get_checkpointer_manager() + checkpointer = manager.checkpointer + if checkpointer: + await prepare_checkpoint_message(config, checkpointer) + except Exception as e: + logger.warning(f"Failed to load checkpointer: {e}") + + config.safe_print() + return config + def invoke_config(self): """返回Langchain需要的配置字典""" config = {} diff --git a/routes/chat.py b/routes/chat.py index f59e33a..fa848e2 100644 --- a/routes/chat.py +++ b/routes/chat.py @@ -12,10 +12,10 @@ logger = logging.getLogger('app') from utils import ( Message, ChatRequest, ChatResponse, BatchSaveChatRequest, BatchSaveChatResponse ) -from utils.api_models import ChatRequestV2 +from utils.api_models import ChatRequestV2, ChatRequestV3 from utils.fastapi_utils import ( process_messages, - create_project_directory, extract_api_key_from_auth, generate_v2_auth_token, fetch_bot_config, + create_project_directory, extract_api_key_from_auth, generate_v2_auth_token, fetch_bot_config, fetch_bot_config_from_db, call_preamble_llm, create_stream_chunk ) @@ -768,6 +768,95 @@ async def chat_completions_v2(request: ChatRequestV2, authorization: Optional[st raise HTTPException(status_code=500, detail=f"Internal server error: {str(e)}") +@router.post("/api/v3/chat/completions") +async def chat_completions_v3(request: ChatRequestV3, authorization: Optional[str] = Header(None)): + """ + Chat completions API v3 - 从数据库读取配置 + + 与 v2 相比，v3 从本地数据库读取所有配置参数，而不是从后端 API。 + 前端只需要传递 bot_id 和 messages，其他配置从数据库自动读取。 + + Args: + request: ChatRequestV3 包含 bot_id, messages, stream, session_id + authorization: 可选的认证头 + + Returns: + Union[ChatResponse, StreamingResponse]: Chat completion response or stream + + Required Parameters: + - bot_id: str - 目标机器人ID（用户创建时填写的ID） + - messages: List[Message] - 对话消息列表 + + Optional Parameters: + - stream: bool - 是否流式输出，默认false + - session_id: str - 会话ID，用于保存聊天历史 + + Configuration (from database): + - model: 模型名称 + - api_key: API密钥 + - model_server: 模型服务器地址 + - language: 回复语言 + - tool_response: 是否包含工具响应 + - system_prompt: 系统提示词 + - dataset_ids: 数据集ID列表 + - mcp_settings: MCP服务器配置 + - user_identifier: 用户标识符 + + Authentication: + - 可选的 Authorization header（如果需要验证） + """ + try: + # 获取bot_id（必需参数） + bot_id = request.bot_id + if not bot_id: + raise HTTPException(status_code=400, detail="bot_id is required") + + # 可选的鉴权验证（如果传递了 authorization header） + if authorization: + expected_token = generate_v2_auth_token(bot_id) + provided_token = extract_api_key_from_auth(authorization) + if provided_token and provided_token != expected_token: + logger.warning(f"Invalid auth token provided for v3 API, but continuing anyway") + + # 从数据库获取机器人配置 + bot_config = await fetch_bot_config_from_db(bot_id, request.user_identifier) + + # 构造类 v2 的请求格式 + # 从数据库配置中提取参数 + language = bot_config.get("language", "zh") + # 创建项目目录（从数据库配置获取） + project_dir = create_project_directory( + bot_config.get("dataset_ids", []), + bot_id, + bot_config.get("skills", []) + ) + + # 处理消息 + messages = process_messages(request.messages, language) + + # 创建 AgentConfig 对象 + # 需要构造一个兼容 v2 的配置对象 + config = await AgentConfig.from_v3_request( + request, + bot_config, + project_dir, + messages, + language + ) + + # 调用公共的agent创建和响应生成逻辑 + return await create_agent_and_generate_response(config) + + except HTTPException: + raise + except Exception as e: + import traceback + error_details = traceback.format_exc() + logger.error(f"Error in chat_completions_v3: {str(e)}") + logger.error(f"Full traceback: {error_details}") + raise HTTPException(status_code=500, detail=f"Internal server error: {str(e)}") + + # ============================================================================ # 聊天历史查询接口 # ============================================================================ diff --git a/utils/api_models.py b/utils/api_models.py index 386c6f9..baf488d 100644 --- a/utils/api_models.py +++ b/utils/api_models.py @@ -68,11 +68,27 @@ class ChatRequestV2(BaseModel): language: Optional[str] = "zh" user_identifier: Optional[str] = "" session_id: Optional[str] = None - shell_env: Optional[Dict[str, str]] = None model_config = ConfigDict(extra='allow') +class ChatRequestV3(BaseModel): + """ + v3 API 请求模型 - 从数据库读取配置 + + 所有配置参数从数据库读取，前端只需传递： + - bot_id: Bot 的用户ID（用于从数据库查找配置） + - messages: 对话消息列表 + - session_id: 可选的会话ID + - user_identifier: 当前登录用户的用户名，用于标识用户身份 + """ + messages: List[Message] + bot_id: str + stream: Optional[bool] = False + session_id: Optional[str] = None + user_identifier: Optional[str] = None + + class FileProcessRequest(BaseModel): unique_id: str files: Optional[Dict[str, List[str]]] = Field(default=None, description="Files organized by key groups. Each key maps to a list of file paths (supports zip files)")