From 5940c57845fd4e12a8680c282a167da888d7744c Mon Sep 17 00:00:00 2001 From: Null <1708213363@qq.com> Date: Wed, 4 Mar 2026 18:49:37 +0800 Subject: [PATCH 01/21] =?UTF-8?q?feat:=20=E6=94=AF=E6=8C=81=E5=BC=95?= =?UTF-8?q?=E7=94=A8=E5=9B=9E=E5=A4=8D=E6=B6=88=E6=81=AF=20(reply=5Fto)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 打通 message_id 全链路：存储 → 暴露 → 发送。 - history.py: add_group/private_message 增加 message_id 可选参数 - handlers.py: 用户消息入历史时传入 trigger_message_id - sender.py: 调整为先发送再写历史，提取 bot message_id； 增加 reply_to 参数，在消息段开头插入 reply 段 - prompts.py: 历史消息 XML 标签增加 message_id 属性 - get_recent_messages/get_messages_by_time: XML 输出增加 message_id - send_message/send_private_message: 新增 reply_to 工具参数 Co-Authored-By: Claude Opus 4.6 --- src/Undefined/ai/prompts.py | 9 +- src/Undefined/handlers.py | 2 + .../messages/get_messages_by_time/handler.py | 7 +- .../messages/get_recent_messages/handler.py | 7 +- .../messages/send_message/config.json | 4 + .../toolsets/messages/send_message/handler.py | 16 +- .../messages/send_private_message/config.json | 4 + .../messages/send_private_message/handler.py | 10 +- src/Undefined/utils/history.py | 54 ++++--- src/Undefined/utils/sender.py | 137 +++++++++++++----- 10 files changed, 183 insertions(+), 67 deletions(-) diff --git a/src/Undefined/ai/prompts.py b/src/Undefined/ai/prompts.py index f5c76f2d..43901f25 100644 --- a/src/Undefined/ai/prompts.py +++ b/src/Undefined/ai/prompts.py @@ -548,6 +548,7 @@ async def _inject_recent_messages( text = msg.get("message", "") role = msg.get("role", "member") title = msg.get("title", "") + message_id = msg.get("message_id") safe_sender = escape_xml_attr(sender_name) safe_sender_id = escape_xml_attr(sender_id) @@ -558,13 +559,17 @@ async def _inject_recent_messages( safe_time = escape_xml_attr(timestamp) safe_text = escape_xml_text(str(text)) + msg_id_attr = "" + if message_id is not None: + msg_id_attr = f' message_id="{escape_xml_attr(str(message_id))}"' + if msg_type_val == "group": location = ( chat_name if chat_name.endswith("群") else f"{chat_name}群" ) safe_location = escape_xml_attr(location) xml_msg = ( - f'\n{safe_text}\n' ) @@ -572,7 +577,7 @@ async def _inject_recent_messages( location = "私聊" safe_location = escape_xml_attr(location) xml_msg = ( - f'\n{safe_text}\n' ) context_lines.append(xml_msg) diff --git a/src/Undefined/handlers.py b/src/Undefined/handlers.py index a9cc1ac1..46beae88 100644 --- a/src/Undefined/handlers.py +++ b/src/Undefined/handlers.py @@ -272,6 +272,7 @@ async def handle_message(self, event: dict[str, Any]) -> None: text_content=parsed_content, display_name=private_sender_nickname, user_name=user_name, + message_id=trigger_message_id, ) # 如果是 bot 自己的消息，只保存不触发回复，避免无限循环 @@ -391,6 +392,7 @@ async def handle_message(self, event: dict[str, Any]) -> None: group_name=group_name, role=sender_role, title=sender_title, + message_id=trigger_message_id, ) # 如果是 bot 自己的消息，只保存不触发回复，避免无限循环 diff --git a/src/Undefined/skills/toolsets/messages/get_messages_by_time/handler.py b/src/Undefined/skills/toolsets/messages/get_messages_by_time/handler.py index 9d98116c..05f4ba6c 100644 --- a/src/Undefined/skills/toolsets/messages/get_messages_by_time/handler.py +++ b/src/Undefined/skills/toolsets/messages/get_messages_by_time/handler.py @@ -177,6 +177,7 @@ async def execute(args: Dict[str, Any], context: Dict[str, Any]) -> str: chat_name = msg.get("chat_name", "未知群聊") timestamp_str = msg.get("timestamp", "") text = msg.get("message", "") + message_id = msg.get("message_id") if msg_type_val == "group": # 确保群名以"群"结尾 @@ -184,8 +185,12 @@ async def execute(args: Dict[str, Any], context: Dict[str, Any]) -> str: else: location = "私聊" + msg_id_attr = "" + if message_id is not None: + msg_id_attr = f' message_id="{message_id}"' + # 格式：XML 标准化 - formatted.append(f""" + formatted.append(f""" {text} """) diff --git a/src/Undefined/skills/toolsets/messages/get_recent_messages/handler.py b/src/Undefined/skills/toolsets/messages/get_recent_messages/handler.py index 6077e883..fda39efe 100644 --- a/src/Undefined/skills/toolsets/messages/get_recent_messages/handler.py +++ b/src/Undefined/skills/toolsets/messages/get_recent_messages/handler.py @@ -104,10 +104,15 @@ def _format_message_xml(msg: dict[str, Any]) -> str: chat_name = msg.get("chat_name", "未知群聊") timestamp = msg.get("timestamp", "") text = msg.get("message", "") + message_id = msg.get("message_id") location = _format_message_location(msg_type_val, chat_name) - return f""" + msg_id_attr = "" + if message_id is not None: + msg_id_attr = f' message_id="{message_id}"' + + return f""" {text} """ diff --git a/src/Undefined/skills/toolsets/messages/send_message/config.json b/src/Undefined/skills/toolsets/messages/send_message/config.json index 7817db5f..72346de9 100644 --- a/src/Undefined/skills/toolsets/messages/send_message/config.json +++ b/src/Undefined/skills/toolsets/messages/send_message/config.json @@ -18,6 +18,10 @@ "target_id": { "type": "integer", "description": "可选。目标会话 ID：当 target_type=group 时为群号；target_type=private 时为用户 QQ 号。" + }, + "reply_to": { + "type": "integer", + "description": "可选。要引用回复的消息 ID (message_id)。设置后消息将以引用回复形式出现，可从历史消息的 message_id 属性获取。" } }, "required": ["message"] diff --git a/src/Undefined/skills/toolsets/messages/send_message/handler.py b/src/Undefined/skills/toolsets/messages/send_message/handler.py index ebd2dd0a..83635d91 100644 --- a/src/Undefined/skills/toolsets/messages/send_message/handler.py +++ b/src/Undefined/skills/toolsets/messages/send_message/handler.py @@ -173,6 +173,14 @@ async def execute(args: Dict[str, Any], context: Dict[str, Any]) -> str: logger.warning("[发送消息] 收到空消息请求") return "消息内容不能为空" + # 解析 reply_to 参数 + reply_to_raw = args.get("reply_to") + reply_to_id: int | None = None + if reply_to_raw is not None: + reply_to_id, reply_error = _parse_positive_int(reply_to_raw, "reply_to") + if reply_error: + return f"发送失败：{reply_error}" + runtime_config = context.get("runtime_config") send_message_callback = context.get("send_message_callback") @@ -206,10 +214,14 @@ async def execute(args: Dict[str, Any], context: Dict[str, Any]) -> str: try: if target_type == "group": logger.info("[发送消息] 准备发送到群 %s: %s", target_id, message[:100]) - await sender.send_group_message(target_id, message) + await sender.send_group_message( + target_id, message, reply_to=reply_to_id + ) else: logger.info("[发送消息] 准备发送私聊 %s: %s", target_id, message[:100]) - await sender.send_private_message(target_id, message) + await sender.send_private_message( + target_id, message, reply_to=reply_to_id + ) context["message_sent_this_turn"] = True return "消息已发送" except Exception as e: diff --git a/src/Undefined/skills/toolsets/messages/send_private_message/config.json b/src/Undefined/skills/toolsets/messages/send_private_message/config.json index 1ddba7d6..28026131 100644 --- a/src/Undefined/skills/toolsets/messages/send_private_message/config.json +++ b/src/Undefined/skills/toolsets/messages/send_private_message/config.json @@ -13,6 +13,10 @@ "message": { "type": "string", "description": "要发送的私聊消息内容" + }, + "reply_to": { + "type": "integer", + "description": "可选。要引用回复的消息 ID (message_id)。设置后消息将以引用回复形式出现，可从历史消息的 message_id 属性获取。" } }, "required": ["message"] diff --git a/src/Undefined/skills/toolsets/messages/send_private_message/handler.py b/src/Undefined/skills/toolsets/messages/send_private_message/handler.py index 84ed8589..5e6f2378 100644 --- a/src/Undefined/skills/toolsets/messages/send_private_message/handler.py +++ b/src/Undefined/skills/toolsets/messages/send_private_message/handler.py @@ -40,6 +40,14 @@ async def execute(args: Dict[str, Any], context: Dict[str, Any]) -> str: user_id, user_error = _parse_positive_int(user_id_raw, "user_id") message = str(args.get("message", "")) + # 解析 reply_to 参数 + reply_to_raw = args.get("reply_to") + reply_to_id: int | None = None + if reply_to_raw is not None: + reply_to_id, reply_error = _parse_positive_int(reply_to_raw, "reply_to") + if reply_error: + return f"发送失败：{reply_error}" + if user_error: return f"发送失败：{user_error}" if user_id is None: @@ -57,7 +65,7 @@ async def execute(args: Dict[str, Any], context: Dict[str, Any]) -> str: if sender: try: - await sender.send_private_message(user_id, message) + await sender.send_private_message(user_id, message, reply_to=reply_to_id) context["message_sent_this_turn"] = True return f"私聊消息已发送给用户 {user_id}" except Exception as e: diff --git a/src/Undefined/utils/history.py b/src/Undefined/utils/history.py index 15496392..4f79a107 100644 --- a/src/Undefined/utils/history.py +++ b/src/Undefined/utils/history.py @@ -267,6 +267,7 @@ async def add_group_message( group_name: str = "", role: str = "member", title: str = "", + message_id: int | None = None, ) -> None: """异步保存群消息到历史记录""" await self._ensure_initialized() @@ -285,19 +286,21 @@ async def add_group_message( f"[历史记录] 追加群消息: group={group_id}, current_count={current_count}" ) - self._message_history[group_id_str].append( - { - "type": "group", - "chat_id": group_id_str, - "chat_name": group_name or f"群{group_id_str}", - "user_id": sender_id_str, - "display_name": display_name, - "role": role, - "title": title, - "timestamp": datetime.now().strftime("%Y-%m-%d %H:%M:%S"), - "message": text_content, - } - ) + record: dict[str, Any] = { + "type": "group", + "chat_id": group_id_str, + "chat_name": group_name or f"群{group_id_str}", + "user_id": sender_id_str, + "display_name": display_name, + "role": role, + "title": title, + "timestamp": datetime.now().strftime("%Y-%m-%d %H:%M:%S"), + "message": text_content, + } + if message_id is not None: + record["message_id"] = message_id + + self._message_history[group_id_str].append(record) if len(self._message_history[group_id_str]) > self._max_records: self._message_history[group_id_str] = self._message_history[ @@ -315,6 +318,7 @@ async def add_private_message( text_content: str, display_name: str = "", user_name: str = "", + message_id: int | None = None, ) -> None: """异步保存私聊消息到历史记录""" await self._ensure_initialized() @@ -330,17 +334,19 @@ async def add_private_message( f"[历史记录] 追加私聊消息: user={user_id}, current_count={current_count}" ) - self._private_message_history[user_id_str].append( - { - "type": "private", - "chat_id": user_id_str, - "chat_name": user_name or f"QQ用户{user_id_str}", - "user_id": user_id_str, - "display_name": display_name or user_name or user_id_str, - "timestamp": datetime.now().strftime("%Y-%m-%d %H:%M:%S"), - "message": text_content, - } - ) + record: dict[str, Any] = { + "type": "private", + "chat_id": user_id_str, + "chat_name": user_name or f"QQ用户{user_id_str}", + "user_id": user_id_str, + "display_name": display_name or user_name or user_id_str, + "timestamp": datetime.now().strftime("%Y-%m-%d %H:%M:%S"), + "message": text_content, + } + if message_id is not None: + record["message_id"] = message_id + + self._private_message_history[user_id_str].append(record) if len(self._private_message_history[user_id_str]) > self._max_records: self._private_message_history[user_id_str] = ( diff --git a/src/Undefined/utils/sender.py b/src/Undefined/utils/sender.py index 7a8921b2..cd92bb56 100644 --- a/src/Undefined/utils/sender.py +++ b/src/Undefined/utils/sender.py @@ -65,6 +65,7 @@ async def send_group_message( history_prefix: str = "", *, mark_sent: bool = True, + reply_to: int | None = None, ) -> None: """发送群消息""" if not self.config.is_group_allowed(group_id): @@ -87,37 +88,57 @@ async def send_group_message( # 将 [@{qq_id}] 格式转换为 [CQ:at,qq={qq_id}] message = process_at_mentions(message) - # 保存到历史记录 + # 准备历史记录文本（不含 reply 段） + history_content: str | None = None if auto_history: - # 解析消息以便正确处理 CQ 码（如图片） - segments = message_to_segments(message) - history_content = extract_text(segments, self.bot_qq) + hist_segments = message_to_segments(message) + history_content = extract_text(hist_segments, self.bot_qq) if history_prefix: history_content = f"{history_prefix}{history_content}" - logger.debug(f"[历史记录] 正在保存 Bot 群聊回复: group={group_id}") + # 发送消息 + bot_message_id: int | None = None + if len(message) <= MAX_MESSAGE_LENGTH: + segments = message_to_segments(message) + if reply_to is not None: + segments.insert(0, {"type": "reply", "data": {"id": str(reply_to)}}) + result = await self.onebot.send_group_message( + group_id, segments, mark_sent=mark_sent + ) + if isinstance(result, dict): + bot_message_id = result.get("message_id") + else: + bot_message_id = await self._send_chunked_group( + group_id, message, mark_sent=mark_sent, reply_to=reply_to + ) + + # 发送成功后写入历史记录 + if auto_history and history_content is not None: + logger.debug(f"[历史记录] 正在保存 Bot 群聊回复: group={group_id}") await self.history_manager.add_group_message( group_id=group_id, sender_id=self.bot_qq, text_content=history_content, sender_nickname="Bot", - group_name="", # 群名暂时未知，通常不需要Bot去获取 - ) - - # 自动分段发送 - if len(message) <= MAX_MESSAGE_LENGTH: - segments = message_to_segments(message) - await self.onebot.send_group_message( - group_id, segments, mark_sent=mark_sent + group_name="", + message_id=bot_message_id, ) - return - # 按行分割 + async def _send_chunked_group( + self, + group_id: int, + message: str, + *, + mark_sent: bool = True, + reply_to: int | None = None, + ) -> int | None: + """分段发送群消息，返回第一段的 message_id。""" logger.info(f"[消息分段] 消息过长 ({len(message)} 字符)，正在自动分段发送...") lines = message.split("\n") current_chunk: list[str] = [] current_length = 0 chunk_count = 0 + first_message_id: int | None = None for line in lines: line_length = len(line) + 1 @@ -126,9 +147,14 @@ async def send_group_message( chunk_count += 1 chunk_text = "\n".join(current_chunk) logger.debug(f"[消息分段] 发送第 {chunk_count} 段") - await self.onebot.send_group_message( - group_id, message_to_segments(chunk_text), mark_sent=mark_sent + segments = message_to_segments(chunk_text) + if chunk_count == 1 and reply_to is not None: + segments.insert(0, {"type": "reply", "data": {"id": str(reply_to)}}) + result = await self.onebot.send_group_message( + group_id, segments, mark_sent=mark_sent ) + if chunk_count == 1 and isinstance(result, dict): + first_message_id = result.get("message_id") current_chunk = [] current_length = 0 @@ -139,11 +165,17 @@ async def send_group_message( chunk_count += 1 chunk_text = "\n".join(current_chunk) logger.debug(f"[消息分段] 发送第 {chunk_count} 段 (最后一段)") - await self.onebot.send_group_message( - group_id, message_to_segments(chunk_text), mark_sent=mark_sent + segments = message_to_segments(chunk_text) + if chunk_count == 1 and reply_to is not None: + segments.insert(0, {"type": "reply", "data": {"id": str(reply_to)}}) + result = await self.onebot.send_group_message( + group_id, segments, mark_sent=mark_sent ) + if chunk_count == 1 and isinstance(result, dict): + first_message_id = result.get("message_id") logger.info(f"[消息分段] 已完成 {chunk_count} 段消息的发送") + return first_message_id async def send_private_message( self, @@ -152,6 +184,7 @@ async def send_private_message( auto_history: bool = True, *, mark_sent: bool = True, + reply_to: int | None = None, ) -> None: """发送私聊消息""" if not self.config.is_private_allowed(user_id): @@ -170,34 +203,55 @@ async def send_private_message( safe_message = redact_string(message) logger.info(f"[发送消息] 目标用户:{user_id} | 内容摘要:{safe_message[:100]}...") - # 保存到历史记录 + + # 准备历史记录文本 + history_content: str | None = None if auto_history: - # 解析消息以便正确处理 CQ 码 + hist_segments = message_to_segments(message) + history_content = extract_text(hist_segments, self.bot_qq) + + # 发送消息 + bot_message_id: int | None = None + if len(message) <= MAX_MESSAGE_LENGTH: segments = message_to_segments(message) - history_content = extract_text(segments, self.bot_qq) - logger.debug(f"[历史记录] 正在保存 Bot 私聊回复: user={user_id}") + if reply_to is not None: + segments.insert(0, {"type": "reply", "data": {"id": str(reply_to)}}) + result = await self.onebot.send_private_message( + user_id, segments, mark_sent=mark_sent + ) + if isinstance(result, dict): + bot_message_id = result.get("message_id") + else: + bot_message_id = await self._send_chunked_private( + user_id, message, mark_sent=mark_sent, reply_to=reply_to + ) + # 发送成功后写入历史记录 + if auto_history and history_content is not None: + logger.debug(f"[历史记录] 正在保存 Bot 私聊回复: user={user_id}") await self.history_manager.add_private_message( user_id=user_id, text_content=history_content, display_name="Bot", user_name="Bot", + message_id=bot_message_id, ) - # 自动分段发送 - if len(message) <= MAX_MESSAGE_LENGTH: - segments = message_to_segments(message) - await self.onebot.send_private_message( - user_id, segments, mark_sent=mark_sent - ) - return - - # 按行分割 + async def _send_chunked_private( + self, + user_id: int, + message: str, + *, + mark_sent: bool = True, + reply_to: int | None = None, + ) -> int | None: + """分段发送私聊消息，返回第一段的 message_id。""" logger.info(f"[消息分段] 消息过长 ({len(message)} 字符)，正在自动分段发送...") lines = message.split("\n") current_chunk: list[str] = [] current_length = 0 chunk_count = 0 + first_message_id: int | None = None for line in lines: line_length = len(line) + 1 @@ -206,9 +260,14 @@ async def send_private_message( chunk_count += 1 chunk_text = "\n".join(current_chunk) logger.debug(f"[消息分段] 发送第 {chunk_count} 段") - await self.onebot.send_private_message( - user_id, message_to_segments(chunk_text), mark_sent=mark_sent + segments = message_to_segments(chunk_text) + if chunk_count == 1 and reply_to is not None: + segments.insert(0, {"type": "reply", "data": {"id": str(reply_to)}}) + result = await self.onebot.send_private_message( + user_id, segments, mark_sent=mark_sent ) + if chunk_count == 1 and isinstance(result, dict): + first_message_id = result.get("message_id") current_chunk = [] current_length = 0 @@ -219,11 +278,17 @@ async def send_private_message( chunk_count += 1 chunk_text = "\n".join(current_chunk) logger.debug(f"[消息分段] 发送第 {chunk_count} 段 (最后一段)") - await self.onebot.send_private_message( - user_id, message_to_segments(chunk_text), mark_sent=mark_sent + segments = message_to_segments(chunk_text) + if chunk_count == 1 and reply_to is not None: + segments.insert(0, {"type": "reply", "data": {"id": str(reply_to)}}) + result = await self.onebot.send_private_message( + user_id, segments, mark_sent=mark_sent ) + if chunk_count == 1 and isinstance(result, dict): + first_message_id = result.get("message_id") logger.info(f"[消息分段] 已完成 {chunk_count} 段消息的发送") + return first_message_id async def send_group_poke( self, From 59a978a57f4f62017b9e8dae77a2e76882b88dc7 Mon Sep 17 00:00:00 2001 From: Null <1708213363@qq.com> Date: Wed, 4 Mar 2026 19:50:51 +0800 Subject: [PATCH 02/21] =?UTF-8?q?feat(python=5Finterpreter):=20=E6=94=AF?= =?UTF-8?q?=E6=8C=81=E5=AE=89=E8=A3=85=E7=AC=AC=E4=B8=89=E6=96=B9=E5=BA=93?= =?UTF-8?q?=E5=92=8C=E5=8F=91=E9=80=81=E8=BE=93=E5=87=BA=E6=96=87=E4=BB=B6?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - 新增 libraries 参数：可选指定 pip 安装的第三方库列表，启用网络下载 - 新增 send_files 参数：代码执行成功后自动发送生成的文件给用户 - 图片文件通过 CQ 码内联发送，其他文件通过上传接口发送为附件 - 代码写入脚本文件执行，避免 shell 引号转义问题 - 库名正则校验防止 requirements.txt 注入（-r/-e/--index-url） - 有库时内存上限 512m、超时 10 分钟；无库时保持原有安全限制 Co-Authored-By: Claude Opus 4.6 --- .../tools/python_interpreter/config.json | 20 +- .../tools/python_interpreter/handler.py | 236 ++++++++++++++---- 2 files changed, 204 insertions(+), 52 deletions(-) diff --git a/src/Undefined/skills/tools/python_interpreter/config.json b/src/Undefined/skills/tools/python_interpreter/config.json index 1685b0e2..4431491b 100644 --- a/src/Undefined/skills/tools/python_interpreter/config.json +++ b/src/Undefined/skills/tools/python_interpreter/config.json @@ -2,13 +2,27 @@ "type": "function", "function": { "name": "python_interpreter", - "description": "在隔离的 Docker 容器中执行 Python 代码。适用于数学计算、数据处理和逻辑验证。无法访问网络或宿主机文件系统。", + "description": "在隔离的 Docker 容器中执行 Python 代码。适用于数学计算、数据处理、图表绘制等任务。可选安装第三方库，并可在执行后自动发送生成的文件（如图片、文档等）。输出文件请写入 /tmp/ 目录。", "parameters": { "type": "object", "properties": { "code": { "type": "string", - "description": "要执行的 Python 代码。" + "description": "要执行的 Python 代码。如需生成文件，请写入 /tmp/ 目录（如 /tmp/output.png）。" + }, + "libraries": { + "type": "array", + "items": { + "type": "string" + }, + "description": "可选。需要通过 pip 安装的第三方库列表，如 [\"matplotlib\", \"pillow\"]。指定后容器将启用网络以下载安装。" + }, + "send_files": { + "type": "array", + "items": { + "type": "string" + }, + "description": "可选。代码执行后要发送给用户的文件路径列表（容器内 /tmp/ 下的路径），如 [\"/tmp/chart.png\", \"/tmp/result.csv\"]。图片文件将内联发送，其他文件作为附件上传。仅在代码执行成功时发送。" } }, "required": [ @@ -16,4 +30,4 @@ ] } } -} \ No newline at end of file +} diff --git a/src/Undefined/skills/tools/python_interpreter/handler.py b/src/Undefined/skills/tools/python_interpreter/handler.py index 223f9e56..43bc212f 100644 --- a/src/Undefined/skills/tools/python_interpreter/handler.py +++ b/src/Undefined/skills/tools/python_interpreter/handler.py @@ -1,5 +1,10 @@ import asyncio import logging +import os +import re +import shutil +import tempfile +from pathlib import Path from typing import Any, Dict logger = logging.getLogger(__name__) @@ -7,51 +12,94 @@ # Docker 执行配置 DOCKER_IMAGE = "python:3.11-slim" MEMORY_LIMIT = "128m" +MEMORY_LIMIT_WITH_LIBS = "512m" CPU_LIMIT = "0.5" TIMEOUT = 480 # 8 分钟 +TIMEOUT_WITH_LIBS = 600 # 10 分钟（pip 安装需要更多时间） + +# 图片扩展名（内联发送而非文件附件） +_IMAGE_EXTENSIONS = frozenset({".png", ".jpg", ".jpeg", ".gif", ".bmp", ".webp"}) + +# 安全：库名仅允许 PyPI 合法字符，必须以字母/数字开头（防止 -r/-e/--index-url 注入） +_SAFE_LIB_PATTERN = re.compile(r"^[A-Za-z0-9][A-Za-z0-9._\-\[\],<>=!~]*$") async def execute(args: Dict[str, Any], context: Dict[str, Any]) -> str: - """ - 在 Docker 容器中执行 Python 代码。 - """ + """在 Docker 容器中执行 Python 代码，可选安装库和发送输出文件。""" code = args.get("code", "") if not code: return "错误: 未提供代码。" - # 构建 docker run 命令 - # --rm: 执行后自动删除容器 - # --network none: 禁用网络 - # --memory/--cpus: 资源限制 - # --read-only: 只读文件系统 - # --tmpfs /tmp: 允许在 /tmp 写入 - # -u 1000:1000: 以非 root 用户运行 (在 slim 镜像中通常存在 'python' 用户，或者用 UID) - - cmd = [ - "docker", - "run", - "--rm", - "--network", - "none", - "--memory", - MEMORY_LIMIT, - "--cpus", - CPU_LIMIT, - "--read-only", - "--tmpfs", - "/tmp", - "-i", # 交互模式，用于传入代码 - DOCKER_IMAGE, - "python", - "-c", - code, - ] - - logger.info(f"[Python解释器] 开始执行代码，超时限制: {TIMEOUT}s") - logger.debug(f"[Python解释器] 代码内容:\n{code}") + libraries: list[str] = args.get("libraries") or [] + send_files: list[str] = args.get("send_files") or [] + + # 验证库名 + for lib in libraries: + if not _SAFE_LIB_PATTERN.match(lib): + return f"错误: 无效的库名 '{lib}'。" + + # 验证文件路径必须在 /tmp/ 下 + for fpath in send_files: + if not fpath.startswith("/tmp/"): + return f"错误: 输出文件路径必须在 /tmp/ 目录下: '{fpath}'" + + has_libs = bool(libraries) + memory = MEMORY_LIMIT_WITH_LIBS if has_libs else MEMORY_LIMIT + timeout = TIMEOUT_WITH_LIBS if has_libs else TIMEOUT + + # 创建宿主机临时目录，绑定挂载到容器 /tmp + host_tmpdir = tempfile.mkdtemp(prefix="pyinterp_") try: - # 使用 asyncio 执行子进程 + # 将代码写入脚本文件（避免 shell 引号转义问题） + script_path = os.path.join(host_tmpdir, "_script.py") + with open(script_path, "w", encoding="utf-8") as f: + f.write(code) + + # 构建 docker 命令 + cmd: list[str] = [ + "docker", + "run", + "--rm", + "--memory", + memory, + "--cpus", + CPU_LIMIT, + "-v", + f"{host_tmpdir}:/tmp", + ] + + if has_libs: + # 需要网络下载包、需要写权限安装包 + req_path = os.path.join(host_tmpdir, "_requirements.txt") + with open(req_path, "w", encoding="utf-8") as f: + for lib in libraries: + f.write(lib + "\n") + cmd.append(DOCKER_IMAGE) + # pip install → 运行代码 → 修正文件权限以便宿主机清理 + cmd.extend( + [ + "sh", + "-c", + "pip install --quiet -r /tmp/_requirements.txt " + "&& python /tmp/_script.py; " + "_e=$?; chmod -R a+rw /tmp 2>/dev/null; exit $_e", + ] + ) + else: + # 无需网络、只读文件系统 + cmd.extend(["--network", "none", "--read-only"]) + cmd.append(DOCKER_IMAGE) + cmd.extend(["python", "/tmp/_script.py"]) + + logger.info( + "[Python解释器] 开始执行, 超时: %ss, 库: %s, 输出文件: %s", + timeout, + libraries, + send_files, + ) + logger.debug("[Python解释器] 代码内容:\n%s", code) + process = await asyncio.create_subprocess_exec( *cmd, stdout=asyncio.subprocess.PIPE, @@ -59,35 +107,125 @@ async def execute(args: Dict[str, Any], context: Dict[str, Any]) -> str: ) try: - # 等待完成，带超时 - stdout, stderr = await asyncio.wait_for( - process.communicate(), timeout=TIMEOUT + stdout_bytes, stderr_bytes = await asyncio.wait_for( + process.communicate(), timeout=timeout ) exit_code = process.returncode - response = stdout.decode("utf-8", errors="replace") - error_output = stderr.decode("utf-8", errors="replace") + response = stdout_bytes.decode("utf-8", errors="replace") + error_output = stderr_bytes.decode("utf-8", errors="replace") + # 构建结果 + parts: list[str] = [] if exit_code == 0: - return response if response.strip() else "代码执行成功 (无输出)。" + parts.append( + response if response.strip() else "代码执行成功 (无输出)。" + ) else: - return ( + parts.append( f"代码执行失败 (退出代码: {exit_code}):\n{error_output}\n{response}" ) + # 执行成功时发送文件 + if send_files and exit_code == 0: + file_result = await _send_output_files(send_files, host_tmpdir, context) + if file_result: + parts.append(file_result) + + return "\n".join(parts) + except asyncio.TimeoutError: - # 超时处理 try: - # 尝试杀掉容器 (由于用了 --rm，杀掉容器会清理资源) - # 注意：子进程是 docker 客户端，单纯 kill 客户端可能不会立刻停止远程容器 - # 但在这里 docker run -i 配合 communicate()，终止子进程通常足够 process.terminate() await process.wait() except Exception as e: - logger.error(f"[Python解释器] 终止超时进程失败: {e}") - - return f"错误: 代码执行超时 ({TIMEOUT}s)。" + logger.error("[Python解释器] 终止超时进程失败: %s", e) + return f"错误: 代码执行超时 ({timeout}s)。" except Exception as e: - logger.exception(f"[Python解释器] 执行出错: {e}") + logger.exception("[Python解释器] 执行出错: %s", e) return "执行出错，请检查代码或重试" + finally: + shutil.rmtree(host_tmpdir, ignore_errors=True) + + +async def _send_output_files( + send_files: list[str], + host_tmpdir: str, + context: Dict[str, Any], +) -> str: + """发送输出文件给用户，返回状态摘要。""" + sender = context.get("sender") + if sender is None: + return "文件发送失败：发送通道不可用" + + request_type = context.get("request_type") + group_id = context.get("group_id") + user_id = context.get("user_id") + + results: list[str] = [] + for container_path in send_files: + # /tmp/output.png → {host_tmpdir}/output.png + relative = container_path.removeprefix("/tmp/") + host_path = os.path.join(host_tmpdir, relative) + + if not os.path.isfile(host_path): + results.append(f"文件未找到: {container_path}") + continue + + file_name = os.path.basename(host_path) + ext = Path(host_path).suffix.lower() + + try: + if ext in _IMAGE_EXTENSIONS: + # 图片：通过 CQ 码内联发送 + await _send_image_inline( + sender, request_type, group_id, user_id, host_path + ) + else: + # 其他文件：通过文件上传接口发送 + await _send_file_upload( + sender, request_type, group_id, user_id, host_path, file_name + ) + results.append(f"已发送: {file_name}") + except Exception as e: + logger.exception("[Python解释器] 文件发送失败: %s", container_path) + results.append(f"发送失败: {file_name} ({e})") + + return "\n".join(results) if results else "" + + +async def _send_image_inline( + sender: Any, + request_type: str | None, + group_id: Any, + user_id: Any, + host_path: str, +) -> None: + """通过 CQ:image 内联发送图片。""" + abs_path = Path(host_path).resolve() + image_cq = f"[CQ:image,file=file://{abs_path}]" + + if request_type == "group" and group_id: + await sender.send_group_message(int(group_id), image_cq, auto_history=False) + elif user_id: + await sender.send_private_message(int(user_id), image_cq, auto_history=False) + else: + raise RuntimeError("无法确定发送目标") + + +async def _send_file_upload( + sender: Any, + request_type: str | None, + group_id: Any, + user_id: Any, + host_path: str, + file_name: str, +) -> None: + """通过文件上传接口发送文件。""" + if request_type == "group" and group_id: + await sender.send_group_file(int(group_id), host_path, file_name) + elif user_id: + await sender.send_private_file(int(user_id), host_path, file_name) + else: + raise RuntimeError("无法确定发送目标") From 32b871da01b6807466015dc9f461066435b645a2 Mon Sep 17 00:00:00 2001 From: Null <1708213363@qq.com> Date: Wed, 4 Mar 2026 20:29:03 +0800 Subject: [PATCH 03/21] =?UTF-8?q?fix:=20reply=5Fto=20=E5=8F=82=E6=95=B0?= =?UTF-8?q?=E8=A7=A3=E6=9E=90=E5=A4=B1=E8=B4=A5=E6=97=B6=E9=9D=99=E9=BB=98?= =?UTF-8?q?=E5=BF=BD=E7=95=A5=E8=80=8C=E9=9D=9E=E6=8A=A5=E9=94=99?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-Authored-By: Claude Opus 4.6 --- .../skills/toolsets/messages/send_message/handler.py | 9 ++------- .../toolsets/messages/send_private_message/handler.py | 9 ++------- 2 files changed, 4 insertions(+), 14 deletions(-) diff --git a/src/Undefined/skills/toolsets/messages/send_message/handler.py b/src/Undefined/skills/toolsets/messages/send_message/handler.py index 83635d91..1efb5fcc 100644 --- a/src/Undefined/skills/toolsets/messages/send_message/handler.py +++ b/src/Undefined/skills/toolsets/messages/send_message/handler.py @@ -173,13 +173,8 @@ async def execute(args: Dict[str, Any], context: Dict[str, Any]) -> str: logger.warning("[发送消息] 收到空消息请求") return "消息内容不能为空" - # 解析 reply_to 参数 - reply_to_raw = args.get("reply_to") - reply_to_id: int | None = None - if reply_to_raw is not None: - reply_to_id, reply_error = _parse_positive_int(reply_to_raw, "reply_to") - if reply_error: - return f"发送失败：{reply_error}" + # 解析 reply_to 参数（无效值静默忽略，视为未传） + reply_to_id, _ = _parse_positive_int(args.get("reply_to"), "reply_to") runtime_config = context.get("runtime_config") diff --git a/src/Undefined/skills/toolsets/messages/send_private_message/handler.py b/src/Undefined/skills/toolsets/messages/send_private_message/handler.py index 5e6f2378..6ac26cf0 100644 --- a/src/Undefined/skills/toolsets/messages/send_private_message/handler.py +++ b/src/Undefined/skills/toolsets/messages/send_private_message/handler.py @@ -40,13 +40,8 @@ async def execute(args: Dict[str, Any], context: Dict[str, Any]) -> str: user_id, user_error = _parse_positive_int(user_id_raw, "user_id") message = str(args.get("message", "")) - # 解析 reply_to 参数 - reply_to_raw = args.get("reply_to") - reply_to_id: int | None = None - if reply_to_raw is not None: - reply_to_id, reply_error = _parse_positive_int(reply_to_raw, "reply_to") - if reply_error: - return f"发送失败：{reply_error}" + # 解析 reply_to 参数（无效值静默忽略，视为未传） + reply_to_id, _ = _parse_positive_int(args.get("reply_to"), "reply_to") if user_error: return f"发送失败：{user_error}" From 497633b4add9a1a14576a05deb23aa02a719db85 Mon Sep 17 00:00:00 2001 From: Null <1708213363@qq.com> Date: Wed, 4 Mar 2026 21:25:23 +0800 Subject: [PATCH 04/21] =?UTF-8?q?fix:=20=E4=BC=98=E5=8C=96=E4=BE=A7?= =?UTF-8?q?=E5=86=99=E6=8F=90=E7=A4=BA=E8=AF=8D?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- res/prompts/historian_profile_merge.md | 36 ++++++++++++++++++----- src/Undefined/skills/tools/end/handler.py | 2 +- 2 files changed, 30 insertions(+), 8 deletions(-) diff --git a/res/prompts/historian_profile_merge.md b/res/prompts/historian_profile_merge.md index 71300314..11216200 100644 --- a/res/prompts/historian_profile_merge.md +++ b/res/prompts/historian_profile_merge.md @@ -1,4 +1,4 @@ -你是一个侧写维护员。根据新事件更新指定目标实体的侧写。 +你是一个人物侧写师。你的工作是维护每个实体的**立体画像**——读完侧写，就能在脑海中浮现这个人/群的轮廓。 必须遵守的硬约束： 1. 本次只允许更新目标实体：`{target_entity_type}:{target_entity_id}`。 @@ -48,8 +48,8 @@ 2. 保留现有稳定特征，整合新信息；参考历史事件判断现有特征是否仍然成立，避免因本轮未提及而误删长期稳定特征 3. 矛盾时以新信息为准 4. tags 只写"这个实体**是什么**"（身份/角色/核心领域），不写"聊过什么话题"；最多 10 个，话题级细节已在 summary 中覆盖。若现有 tags 不符合此规范（数量过多或含话题标签），直接按规范重写，不必保留旧 tags -5. 保持简洁，只记录长期稳定的特征 -6. 侧写是"稳定画像"，不是"事件流水账" +5. 侧写是"人物素描"，不是"属性清单"或"事件流水账"——要有主线、有层次，能合并的特征就融成一句话 +6. 只保留长期稳定的特征，表达紧凑但不丢失关键信息 7. 若 `current_profile` 本身不符合以上规范，可直接整体重写为合规版本（不必保留其原有写法） 严禁写入以下内容（这些属于事件记忆，不应进入侧写）： @@ -60,10 +60,32 @@ 若本轮只有事件细节、无法抽象为长期稳定特征，必须 `skip=true`。 -`summary` 输出格式约束： -- 使用 Markdown 项目符号（`- `）输出 4-8 条 -- 每条只写"长期稳定特征/偏好/角色关系/沟通风格" -- 句子短而概括，避免冗长复述 +`summary` 输出格式约束（核心原则：画一个人/群，不是列属性卡）： + +**用户侧写**结构： +1. **核心画像**（第一句）：一句话抓住这个人最本质的特质（身份 + 核心驱动力/风格），读完就能大致"看到"这个人 +2. **展开描述**（后续 1-3 句群）：围绕 2-3 个维度用连贯的短句展开，维度间要有逻辑关联而非孤立罗列 + - 维度参考：技术/专业方向与能力、做事风格与决策偏好、沟通方式与性格特征 +3. 总字数 100-300 字；关键信息不可丢失，但表达要紧凑——能合并的特征融成一句，不要拆成多条孤立要点 + +**群聊侧写**结构： +1. **核心定位**（第一句）：一句话概括群的本质定位与氛围基调 +2. **展开描述**（后续）：成员构成、讨论风格、群文化等，可用项目符号辅助，但每条要有信息密度 +3. 总字数 80-250 字 + +**反面示例**（不要这样写——碎片化，读完记不住是谁）： +``` +- 在校学生兼独立开发者 +- AI/Agent 工程实践者，偏工程化落地 +- 沟通中喜欢追问到具体机制 +- 对表述与参数准确性敏感 +- 关注稳定性与成本 +``` + +**正面示例**（应该这样写——精炼连贯，读完脑中浮现一个人）： +``` +务实的工程型开发者，在校学生身份下独立运营开源项目。核心驱动力是"让东西真正能用"——偏好可配置、可维护的方案，习惯小实验快速验证，不可行就止损。沟通直奔具体机制与数据结构，对表述准确性敏感，发现偏差会刨根问底。 +``` 输出规则（调用 `update_profile` 工具）： - 若应跳过更新：`skip=true`，并给出 `skip_reason`；`summary` 置空字符串，`tags` 可为空数组。**调用后流程立即终止，无法再执行任何操作，请确保在此之前已完成所有必要的读取与更新。** diff --git a/src/Undefined/skills/tools/end/handler.py b/src/Undefined/skills/tools/end/handler.py index d48e5a02..d122ae25 100644 --- a/src/Undefined/skills/tools/end/handler.py +++ b/src/Undefined/skills/tools/end/handler.py @@ -280,7 +280,7 @@ async def execute(args: Dict[str, Any], context: Dict[str, Any]) -> str: "拒绝结束对话：你填写了 memo（本轮行动备忘）但本轮未发送任何消息或媒体内容。" "请先发送消息给用户，或使用 force=true 强制结束。" "若本轮确实未做任何事，建议留空 memo 以避免记忆噪声。当然，你要存也没关系。这只是个提示，防止你忘了。" - "若你获取到了新信息，考虑填写 observations 字段以保存这些信息，而不是放在 memo 里。" + "若你获取到了新信息，应填写 observations 字段以保存这些信息，而不是放在 memo 里。" ) if summary: From e4176182791bab4de09ae78f7901505173582bf6 Mon Sep 17 00:00:00 2001 From: Null <1708213363@qq.com> Date: Fri, 6 Mar 2026 19:33:24 +0800 Subject: [PATCH 05/21] =?UTF-8?q?fix:=20=E8=B0=83=E6=95=B4=E5=8F=B2?= =?UTF-8?q?=E5=AE=98=E6=8F=90=E7=A4=BA=E8=AF=8D?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- res/prompts/historian_profile_merge.md | 68 +++++++++++++++++--------- 1 file changed, 46 insertions(+), 22 deletions(-) diff --git a/res/prompts/historian_profile_merge.md b/res/prompts/historian_profile_merge.md index 11216200..c0716f3f 100644 --- a/res/prompts/historian_profile_merge.md +++ b/res/prompts/historian_profile_merge.md @@ -45,12 +45,17 @@ 要求： 1. **先调用 `read_profile` 读取目标实体的当前侧写**，再决定如何更新 -2. 保留现有稳定特征，整合新信息；参考历史事件判断现有特征是否仍然成立，避免因本轮未提及而误删长期稳定特征 -3. 矛盾时以新信息为准 +2. **增量更新原则**（核心）： + - 现有侧写是长期积累的全貌，本轮新事件只是一个增量片段 + - 默认保留所有现有稳定特征，新信息用于"补充细节"或"修正矛盾"，而非"重新定义" + - 参考历史事件列表判断旧特征是否仍然成立——只要历史中反复出现，就应保留 + - 只有当新信息与旧特征**明确矛盾**时才覆盖，否则应融合表达（如"既...也..."） +3. 若新旧信息矛盾且新信息更可靠，以新信息为准并说明变化 4. tags 只写"这个实体**是什么**"（身份/角色/核心领域），不写"聊过什么话题"；最多 10 个，话题级细节已在 summary 中覆盖。若现有 tags 不符合此规范（数量过多或含话题标签），直接按规范重写，不必保留旧 tags -5. 侧写是"人物素描"，不是"属性清单"或"事件流水账"——要有主线、有层次，能合并的特征就融成一句话 -6. 只保留长期稳定的特征，表达紧凑但不丢失关键信息 -7. 若 `current_profile` 本身不符合以上规范，可直接整体重写为合规版本（不必保留其原有写法） +5. 侧写要有"主线"——第一条定调，后续条目围绕它展开，而非孤立罗列无关特征 +6. **信息密度优先于表达精炼**：每条要有具体细节（技术栈/工具/行为模式），不要为了简洁而泛化成抽象描述 +7. **核心画像要抓独特性**：第一句要写出"这个人区别于其他人的本质"，而非通用描述（如"开发者"太泛，"把系统当产线打理的工程型开发者"才有辨识度） +8. 若 `current_profile` 本身不符合以上规范，可直接整体重写为合规版本（不必保留其原有写法） 严禁写入以下内容（这些属于事件记忆，不应进入侧写）： - 某次/近期/今天/昨天的具体经过 @@ -60,31 +65,50 @@ 若本轮只有事件细节、无法抽象为长期稳定特征，必须 `skip=true`。 -`summary` 输出格式约束（核心原则：画一个人/群，不是列属性卡）： +`summary` 输出格式约束： -**用户侧写**结构： -1. **核心画像**（第一句）：一句话抓住这个人最本质的特质（身份 + 核心驱动力/风格），读完就能大致"看到"这个人 -2. **展开描述**（后续 1-3 句群）：围绕 2-3 个维度用连贯的短句展开，维度间要有逻辑关联而非孤立罗列 - - 维度参考：技术/专业方向与能力、做事风格与决策偏好、沟通方式与性格特征 -3. 总字数 100-300 字；关键信息不可丢失，但表达要紧凑——能合并的特征融成一句，不要拆成多条孤立要点 +**用户侧写**结构（使用 Markdown 项目符号 `- `）： +1. **第一条：核心画像** + - 一句话定位这个人的身份与核心特质，为后续条目定调 + - 要具体，不要泛泛而谈（如"在校学生/业余开发者，做技术取舍会权衡时间、算力与预算"比"务实的开发者"信息量大） + +2. **后续 4-8 条：多维度展开** + - 每条聚焦一个维度：技术栈/工作方式/决策偏好/沟通风格/排障思路等 + - **关键：每条要有具体细节**，不要抽象概括（如"模型名需包含完整前缀与斜杠"比"注重细节"有用） + - 条目间要有逻辑关联，共同支撑第一条的核心画像 + +3. **信息密度优先**：宁可多写一条具体特征，也不要为了精炼而泛化 +4. 总字数 150-400 字 **群聊侧写**结构： -1. **核心定位**（第一句）：一句话概括群的本质定位与氛围基调 -2. **展开描述**（后续）：成员构成、讨论风格、群文化等，可用项目符号辅助，但每条要有信息密度 -3. 总字数 80-250 字 +- 同样使用项目符号，第一条定位群的核心属性，后续展开成员构成、讨论风格、群文化等 +- 总字数 120-350 字 -**反面示例**（不要这样写——碎片化，读完记不住是谁）： +**反面示例**（不要这样写）： ``` -- 在校学生兼独立开发者 -- AI/Agent 工程实践者，偏工程化落地 -- 沟通中喜欢追问到具体机制 -- 对表述与参数准确性敏感 -- 关注稳定性与成本 +❌ 过度抽象，丢失具体信息： +"Null 是那种把 AI 系统当工程产线来打理的人，核心驱动力不是炫技，而是让模型、链路和配置始终保持可用、可控、可回退。" +→ 问题：比喻虽好，但"权衡算力与预算"、"OpenAI 兼容接口"、"容器化"等关键细节全丢了 + +❌ 孤立罗列，缺乏主线： +- 会 Python +- 用过 Docker +- 喜欢开源 +→ 问题：每条独立，看不出这个人的核心特质和做事逻辑 ``` -**正面示例**（应该这样写——精炼连贯，读完脑中浮现一个人）： +**正面示例**（应该这样写）： ``` -务实的工程型开发者，在校学生身份下独立运营开源项目。核心驱动力是"让东西真正能用"——偏好可配置、可维护的方案，习惯小实验快速验证，不可行就止损。沟通直奔具体机制与数据结构，对表述准确性敏感，发现偏差会刨根问底。 +✓ 第一条定调 + 后续高密度展开： +- 在校学生/业余开发者，做技术取舍会权衡时间、算力与预算，偏好高性价比方案。 +- 独立开发并维护开源项目，关注 AI 应用与 Agent 的工程化落地。 +- 熟悉本地/自建模型服务与 OpenAI 兼容接口的接入联调，强调配置项必须与实际资源严格一致。 +- 对"标识符/名称"细节较敏感（如模型名需包含完整前缀与斜杠、tag 等），倾向要求原样填写以避免隐性错误。 +- 有容器化与自建基础设施经验，偏好自动化运维与稳定可控的部署方式。 +- 排障思路偏"先核对关键信息—再做最小改动验证"，会主动索要配置/截图与报错信息。 +- 沟通风格简短直接，在社群中常承担技术支持与规则把关角色。 + +（注：每条都有具体细节，共同支撑"务实的工程型开发者"这个核心画像） ``` 输出规则（调用 `update_profile` 工具）： From d2bd479dd86e4a3aaa4fbf2c7fdd5c5b21262670 Mon Sep 17 00:00:00 2001 From: Null <1708213363@qq.com> Date: Sat, 7 Mar 2026 13:40:30 +0800 Subject: [PATCH 06/21] feat(config): support model request params --- config.toml.example | 28 + docs/configuration.md | 18 +- src/Undefined/ai/llm.py | 68 +- src/Undefined/ai/model_selector.py | 2 + src/Undefined/ai/retrieval.py | 56 ++ src/Undefined/config/loader.py | 29 + src/Undefined/config/models.py | 8 + src/Undefined/utils/request_params.py | 45 ++ src/Undefined/webui/static/js/config-form.js | 694 ++++++++++++++----- src/Undefined/webui/utils/toml_render.py | 47 +- tests/test_config_request_params.py | 98 +++ tests/test_llm_request_params.py | 85 +++ tests/test_retrieval.py | 74 ++ tests/test_webui_render_toml.py | 53 ++ 14 files changed, 1132 insertions(+), 173 deletions(-) create mode 100644 src/Undefined/utils/request_params.py create mode 100644 tests/test_config_request_params.py create mode 100644 tests/test_llm_request_params.py diff --git a/config.toml.example b/config.toml.example index 01a5d639..70fca10f 100644 --- a/config.toml.example +++ b/config.toml.example @@ -102,6 +102,10 @@ thinking_include_budget = true # en: Thinking tool-call compatibility: pass back reasoning_content in multi-turn tool calls to avoid 400 errors from some models. thinking_tool_call_compat = false +# zh: 额外请求体参数（可选），可用于 temperature、reasoning_effort 或供应商私有参数。 +# en: Extra request-body params (optional), e.g. temperature, reasoning_effort, or vendor-specific fields. +[models.chat.request_params] + # zh: 模型池配置（可选，支持多模型轮询/随机/用户指定）。 # en: Model pool configuration (optional, supports round-robin/random/user-specified). [models.chat.pool] @@ -143,6 +147,10 @@ thinking_include_budget = true # en: Thinking tool-call compatibility: pass back reasoning_content in multi-turn tool calls to avoid 400 errors from some models. thinking_tool_call_compat = false +# zh: 额外请求体参数（可选），可用于 temperature、reasoning_effort 或供应商私有参数。 +# en: Extra request-body params (optional), e.g. temperature, reasoning_effort, or vendor-specific fields. +[models.vision.request_params] + # zh: 安全模型配置（用于防注入检测和注入后回复生成）。 # en: Security model config (injection detection and post-injection responses). [models.security] @@ -177,6 +185,10 @@ thinking_include_budget = true # en: Thinking tool-call compatibility: pass back reasoning_content in multi-turn tool calls to avoid 400 errors from some models. thinking_tool_call_compat = false +# zh: 额外请求体参数（可选），可用于 temperature、reasoning_effort 或供应商私有参数。 +# en: Extra request-body params (optional), e.g. temperature, reasoning_effort, or vendor-specific fields. +[models.security.request_params] + # zh: Agent 模型配置（用于执行 agents）。 # en: Agent model config (used to run agents). [models.agent] @@ -208,6 +220,10 @@ thinking_include_budget = true # en: Thinking tool-call compatibility: pass back reasoning_content in multi-turn tool calls to avoid 400 errors from some models. thinking_tool_call_compat = false +# zh: 额外请求体参数（可选），可用于 temperature、reasoning_effort 或供应商私有参数。 +# en: Extra request-body params (optional), e.g. temperature, reasoning_effort, or vendor-specific fields. +[models.agent.request_params] + # zh: Agent 模型池配置（可选，支持多模型轮询/随机/用户指定）。 # en: Agent model pool configuration (optional, supports round-robin/random/user-specified). [models.agent.pool] @@ -252,6 +268,10 @@ thinking_include_budget = true # en: Thinking tool-call compatibility: pass back reasoning_content in multi-turn tool calls to avoid 400 errors from some models. thinking_tool_call_compat = false +# zh: 额外请求体参数（可选），可用于 temperature、reasoning_effort 或供应商私有参数。 +# en: Extra request-body params (optional), e.g. temperature, reasoning_effort, or vendor-specific fields. +[models.historian.request_params] + # zh: 嵌入模型配置（知识库语义检索使用）。 # en: Embedding model config (used by knowledge semantic retrieval). [models.embedding] @@ -277,6 +297,10 @@ query_instruction = "" # en: Document instruction prefix (optional, common for E5-style models, e.g. "passage: "). document_instruction = "" +# zh: 额外请求体参数（可选），用于 embedding 供应商的扩展字段。 +# en: Extra request-body params (optional) for embedding-provider-specific fields. +[models.embedding.request_params] + # zh: 重排模型配置（知识库二阶段检索使用）。 # en: Rerank model config (used in second-stage knowledge retrieval). [models.rerank] @@ -296,6 +320,10 @@ queue_interval_seconds = 1.0 # en: Query instruction prefix (optional, required by some rerank models, e.g. "Instruct: ...\\nQuery: "). query_instruction = "" +# zh: 额外请求体参数（可选），用于 rerank 供应商的扩展字段。 +# en: Extra request-body params (optional) for rerank-provider-specific fields. +[models.rerank.request_params] + # zh: 本地知识库配置。 # en: Local knowledge base settings. [knowledge] diff --git a/docs/configuration.md b/docs/configuration.md index 0481f77f..7659fb1e 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -146,6 +146,7 @@ model_name = "gpt-4o-mini" | `thinking_budget_tokens` | thinking 预算 | | `thinking_include_budget` | 是否发送 budget_tokens | | `thinking_tool_call_compat` | Tool Calls 兼容模式（回传 reasoning_content） | +| `request_params` | 额外请求体参数（透传给模型 API，保留字段会忽略） | 兼容字段（旧配置）： - `models..deepseek_new_cot_support` @@ -159,6 +160,9 @@ model_name = "gpt-4o-mini" - `queue_interval_seconds=1.0`（`<=0` 回退 `1.0`） - `thinking_budget_tokens=20000` +补充： +- 可通过 `[models.chat.request_params]` 传入 `temperature`、`response_format`、`reasoning_effort` 或兼容网关私有字段。 + ### 4.4.3 `[models.vision]` 视觉模型 默认： @@ -205,7 +209,11 @@ model_name = "gpt-4o-mini" `models` 条目支持字段： - `model_name`（必填） -- `api_url`/`api_key`/`max_tokens`/`queue_interval_seconds`/`thinking_*`（可选，缺省继承主模型） +- `api_url`/`api_key`/`max_tokens`/`queue_interval_seconds`/`thinking_*`/`request_params`（可选，缺省继承主模型） + +`request_params` 继承规则： +- `[[models.chat.pool.models]]` 与 `[[models.agent.pool.models]]` 的 `request_params` 会与主模型按顶层键浅合并。 +- 同名键由池条目覆盖；嵌套对象按整键替换，不做深合并。 生效条件（全部满足才启用池）： 1. `features.pool_enabled=true` @@ -223,6 +231,7 @@ model_name = "gpt-4o-mini" | `dimensions` | `0` | 向量维度；`0`/空视为 `None`（模型默认） | | `query_instruction` | `""` | 查询前缀 | | `document_instruction` | `""` | 文档前缀 | +| `request_params` | `{}` | 额外请求体参数；保留字段如 `model`/`input`/`dimensions` 会忽略 | ### 4.4.9 `[models.rerank]` 重排模型 @@ -233,6 +242,13 @@ model_name = "gpt-4o-mini" | `model_name` | `""` | 模型名 | | `queue_interval_seconds` | `1.0` | `<=0` 回退 `1.0` | | `query_instruction` | `""` | 查询前缀 | +| `request_params` | `{}` | 额外请求体参数；保留字段如 `model`/`query`/`documents`/`top_n` 会忽略 | + +`request_params` 说明： +- 仅用于**请求体**字段，不包含 `api_key`、`base_url`、`timeout`、`extra_headers` 等 client 选项。 +- 聊天类保留字段：`model`、`messages`、`max_tokens`、`tools`、`tool_choice`、`stream`、`stream_options`。 +- embedding 保留字段：`model`、`input`、`dimensions`。 +- rerank 保留字段：`model`、`query`、`documents`、`top_n`、`return_documents`。 --- diff --git a/src/Undefined/ai/llm.py b/src/Undefined/ai/llm.py index db00aaca..bd7fd86f 100644 --- a/src/Undefined/ai/llm.py +++ b/src/Undefined/ai/llm.py @@ -35,6 +35,10 @@ ) from Undefined.token_usage_storage import TokenUsageStorage, TokenUsage from Undefined.utils.logging import log_debug_json, redact_string +from Undefined.utils.request_params import ( + merge_request_params, + split_reserved_request_params, +) from Undefined.utils.tool_calls import normalize_tool_arguments_json logger = logging.getLogger(__name__) @@ -72,6 +76,25 @@ "top_logprobs", } +_SDK_REQUEST_OPTION_FIELDS: frozenset[str] = frozenset( + {"extra_headers", "extra_query", "extra_body", "timeout"} +) + +_CHAT_COMPLETIONS_RESERVED_FIELDS: frozenset[str] = ( + frozenset( + { + "model", + "messages", + "max_tokens", + "tools", + "tool_choice", + "stream", + "stream_options", + } + ) + | _SDK_REQUEST_OPTION_FIELDS +) + _THINKING_KEYS: tuple[str, ...] = ( "thinking", "reasoning", @@ -729,6 +752,44 @@ def _normalize_openai_base_url( return normalized, default_query, True +def _warn_ignored_request_params( + *, + call_type: str, + model_name: str, + ignored: dict[str, Any], +) -> None: + if not ignored: + return + logger.warning( + "[request_params] ignored_keys=%s type=%s model=%s", + ",".join(sorted(ignored)), + call_type, + model_name, + ) + + +def _build_effective_request_kwargs( + model_config: ModelConfig, + *, + call_type: str, + overrides: dict[str, Any], +) -> dict[str, Any]: + merged = merge_request_params( + getattr(model_config, "request_params", {}), + overrides, + ) + allowed, ignored = split_reserved_request_params( + merged, + _CHAT_COMPLETIONS_RESERVED_FIELDS, + ) + _warn_ignored_request_params( + call_type=call_type, + model_name=model_config.model_name, + ignored=ignored, + ) + return allowed + + class ModelRequester: """统一的模型请求封装。""" @@ -774,13 +835,18 @@ async def request( tool_args_fixed, len(messages_for_api), ) + effective_kwargs = _build_effective_request_kwargs( + model_config, + call_type=call_type, + overrides=dict(kwargs), + ) request_body = build_request_body( model_config=model_config, messages=messages_for_api, max_tokens=max_tokens, tools=tools, tool_choice=tool_choice, - **kwargs, + **effective_kwargs, ) api_to_internal: dict[str, str] = {} diff --git a/src/Undefined/ai/model_selector.py b/src/Undefined/ai/model_selector.py index 62515908..d255ca6d 100644 --- a/src/Undefined/ai/model_selector.py +++ b/src/Undefined/ai/model_selector.py @@ -245,6 +245,7 @@ def _entry_to_chat_config( thinking_budget_tokens=entry.thinking_budget_tokens, thinking_include_budget=entry.thinking_include_budget, thinking_tool_call_compat=entry.thinking_tool_call_compat, + request_params=entry.request_params, pool=primary.pool, ) @@ -263,5 +264,6 @@ def _entry_to_agent_config( thinking_budget_tokens=entry.thinking_budget_tokens, thinking_include_budget=entry.thinking_include_budget, thinking_tool_call_compat=entry.thinking_tool_call_compat, + request_params=entry.request_params, pool=primary.pool, ) diff --git a/src/Undefined/ai/retrieval.py b/src/Undefined/ai/retrieval.py index f0e5971a..82c42d42 100644 --- a/src/Undefined/ai/retrieval.py +++ b/src/Undefined/ai/retrieval.py @@ -11,6 +11,7 @@ from Undefined.ai.tokens import TokenCounter from Undefined.config import EmbeddingModelConfig, RerankModelConfig +from Undefined.utils.request_params import split_reserved_request_params logger = logging.getLogger(__name__) @@ -20,6 +21,18 @@ _TokenCounterGetter: TypeAlias = Callable[[str], TokenCounter] _RecordUsageCallback: TypeAlias = Callable[..., None] +_SDK_REQUEST_OPTION_FIELDS: frozenset[str] = frozenset( + {"extra_headers", "extra_query", "extra_body", "timeout"} +) +_EMBEDDING_KNOWN_FIELDS: frozenset[str] = frozenset({"encoding_format", "user"}) +_EMBEDDING_RESERVED_FIELDS: frozenset[str] = ( + frozenset({"model", "input", "dimensions"}) | _SDK_REQUEST_OPTION_FIELDS +) +_RERANK_RESERVED_FIELDS: frozenset[str] = ( + frozenset({"model", "query", "documents", "top_n", "return_documents"}) + | _SDK_REQUEST_OPTION_FIELDS +) + class RetrievalRequester: """统一处理嵌入与重排请求，便于复用统计与 SDK 调用逻辑。""" @@ -37,6 +50,26 @@ def __init__( self._get_token_counter = get_token_counter self._record_usage = record_usage + def _split_request_params( + self, + model_config: _ModelConfig, + *, + reserved_fields: frozenset[str], + call_type: str, + ) -> tuple[dict[str, Any], dict[str, Any]]: + allowed, ignored = split_reserved_request_params( + getattr(model_config, "request_params", {}), + reserved_fields, + ) + if ignored: + logger.warning( + "[request_params] ignored_keys=%s type=%s model=%s", + ",".join(sorted(ignored)), + call_type, + model_config.model_name, + ) + return allowed, ignored + async def embed( self, model_config: EmbeddingModelConfig, texts: list[str] ) -> list[list[float]]: @@ -46,10 +79,27 @@ async def embed( start_time = time.perf_counter() client = self._get_openai_client(model_config) + request_params, _ = self._split_request_params( + model_config, + reserved_fields=_EMBEDDING_RESERVED_FIELDS, + call_type="embedding", + ) + method_kwargs = { + key: value + for key, value in request_params.items() + if key in _EMBEDDING_KNOWN_FIELDS + } + extra_body = { + key: value + for key, value in request_params.items() + if key not in _EMBEDDING_KNOWN_FIELDS + } response = await client.embeddings.create( model=model_config.model_name, input=texts, dimensions=model_config.dimensions or NOT_GIVEN, # type: ignore[arg-type] + extra_body=extra_body or None, + **method_kwargs, ) response_dict = self._response_to_dict(response) embeddings = [item.embedding for item in response.data] @@ -96,7 +146,13 @@ async def rerank( start_time = time.perf_counter() client = self._get_openai_client(model_config) + request_params, _ = self._split_request_params( + model_config, + reserved_fields=_RERANK_RESERVED_FIELDS, + call_type="rerank", + ) request_body: dict[str, Any] = { + **request_params, "model": model_config.model_name, "query": query, "documents": documents, diff --git a/src/Undefined/config/loader.py b/src/Undefined/config/loader.py index 053f0ef4..c9081497 100644 --- a/src/Undefined/config/loader.py +++ b/src/Undefined/config/loader.py @@ -39,6 +39,10 @@ def load_dotenv( SecurityModelConfig, VisionModelConfig, ) +from Undefined.utils.request_params import ( + merge_request_params, + normalize_request_params, +) logger = logging.getLogger(__name__) @@ -225,6 +229,16 @@ def _coerce_str_list(value: Any) -> list[str]: return [] +def _coerce_request_params(value: Any) -> dict[str, Any]: + return normalize_request_params(value) + + +def _get_model_request_params(data: dict[str, Any], model_name: str) -> dict[str, Any]: + return _coerce_request_params( + _get_nested(data, ("models", model_name, "request_params")) + ) + + def _get_value( data: dict[str, Any], path: tuple[str, ...], @@ -1511,6 +1525,10 @@ def _parse_model_pool( item.get("thinking_tool_call_compat"), primary_config.thinking_tool_call_compat, ), + request_params=merge_request_params( + primary_config.request_params, + item.get("request_params"), + ), ) ) @@ -1554,6 +1572,7 @@ def _parse_embedding_model_config(data: dict[str, Any]) -> EmbeddingModelConfig: _get_value(data, ("models", "embedding", "document_instruction"), None), "", ), + request_params=_get_model_request_params(data, "embedding"), ) @staticmethod @@ -1587,6 +1606,7 @@ def _parse_rerank_model_config(data: dict[str, Any]) -> RerankModelConfig: query_instruction=_coerce_str( _get_value(data, ("models", "rerank", "query_instruction"), None), "" ), + request_params=_get_model_request_params(data, "rerank"), ) @staticmethod @@ -1648,6 +1668,7 @@ def _parse_chat_model_config(data: dict[str, Any]) -> ChatModelConfig: ), thinking_include_budget=thinking_include_budget, thinking_tool_call_compat=thinking_tool_call_compat, + request_params=_get_model_request_params(data, "chat"), ) config.pool = Config._parse_model_pool(data, "chat", config) return config @@ -1711,6 +1732,7 @@ def _parse_vision_model_config(data: dict[str, Any]) -> VisionModelConfig: ), thinking_include_budget=thinking_include_budget, thinking_tool_call_compat=thinking_tool_call_compat, + request_params=_get_model_request_params(data, "vision"), ) @staticmethod @@ -1788,6 +1810,7 @@ def _parse_security_model_config( ), thinking_include_budget=thinking_include_budget, thinking_tool_call_compat=thinking_tool_call_compat, + request_params=_get_model_request_params(data, "security"), ) logger.warning("未配置安全模型，将使用对话模型作为后备") @@ -1801,6 +1824,7 @@ def _parse_security_model_config( thinking_budget_tokens=0, thinking_include_budget=True, thinking_tool_call_compat=False, + request_params=merge_request_params(chat_model.request_params), ) @staticmethod @@ -1862,6 +1886,7 @@ def _parse_agent_model_config(data: dict[str, Any]) -> AgentModelConfig: ), thinking_include_budget=thinking_include_budget, thinking_tool_call_compat=thinking_tool_call_compat, + request_params=_get_model_request_params(data, "agent"), ) config.pool = Config._parse_model_pool(data, "agent", config) return config @@ -2009,6 +2034,10 @@ def _parse_historian_model_config( ), thinking_include_budget=thinking_include_budget, thinking_tool_call_compat=thinking_tool_call_compat, + request_params=merge_request_params( + fallback.request_params, + h.get("request_params"), + ), ) @staticmethod diff --git a/src/Undefined/config/models.py b/src/Undefined/config/models.py index 2a256ab8..0f0992e0 100644 --- a/src/Undefined/config/models.py +++ b/src/Undefined/config/models.py @@ -3,6 +3,7 @@ from __future__ import annotations from dataclasses import dataclass, field +from typing import Any @dataclass @@ -18,6 +19,7 @@ class ModelPoolEntry: thinking_budget_tokens: int = 0 thinking_include_budget: bool = True thinking_tool_call_compat: bool = False + request_params: dict[str, Any] = field(default_factory=dict) @dataclass @@ -44,6 +46,7 @@ class ChatModelConfig: thinking_tool_call_compat: bool = ( False # 思维链 + 工具调用兼容（回传 reasoning_content） ) + request_params: dict[str, Any] = field(default_factory=dict) pool: ModelPool | None = None # 模型池配置 @@ -61,6 +64,7 @@ class VisionModelConfig: thinking_tool_call_compat: bool = ( False # 思维链 + 工具调用兼容（回传 reasoning_content） ) + request_params: dict[str, Any] = field(default_factory=dict) @dataclass @@ -78,6 +82,7 @@ class SecurityModelConfig: thinking_tool_call_compat: bool = ( False # 思维链 + 工具调用兼容（回传 reasoning_content） ) + request_params: dict[str, Any] = field(default_factory=dict) @dataclass @@ -91,6 +96,7 @@ class EmbeddingModelConfig: dimensions: int | None = None query_instruction: str = "" # 查询端指令前缀（如 Qwen3-Embedding 需要） document_instruction: str = "" # 文档端指令前缀（如 E5 系列需要 "passage: "） + request_params: dict[str, Any] = field(default_factory=dict) @dataclass @@ -102,6 +108,7 @@ class RerankModelConfig: model_name: str queue_interval_seconds: float = 1.0 query_instruction: str = "" # 查询端指令前缀（如部分 rerank 模型需要） + request_params: dict[str, Any] = field(default_factory=dict) @dataclass @@ -119,6 +126,7 @@ class AgentModelConfig: thinking_tool_call_compat: bool = ( False # 思维链 + 工具调用兼容（回传 reasoning_content） ) + request_params: dict[str, Any] = field(default_factory=dict) pool: ModelPool | None = None # 模型池配置 diff --git a/src/Undefined/utils/request_params.py b/src/Undefined/utils/request_params.py new file mode 100644 index 00000000..58139a77 --- /dev/null +++ b/src/Undefined/utils/request_params.py @@ -0,0 +1,45 @@ +from __future__ import annotations + +from typing import Any, Mapping + + +def _clone_json_like(value: Any) -> Any: + if value is None or isinstance(value, (str, int, float, bool)): + return value + if isinstance(value, dict): + return {str(key): _clone_json_like(item) for key, item in value.items()} + if isinstance(value, list): + return [_clone_json_like(item) for item in value] + if isinstance(value, tuple): + return [_clone_json_like(item) for item in value] + return str(value) + + +def normalize_request_params(value: Any) -> dict[str, Any]: + if not isinstance(value, Mapping): + return {} + return {str(key): _clone_json_like(item) for key, item in value.items()} + + +def merge_request_params(*values: Any) -> dict[str, Any]: + merged: dict[str, Any] = {} + for value in values: + if not isinstance(value, Mapping): + continue + merged.update(normalize_request_params(value)) + return merged + + +def split_reserved_request_params( + params: Mapping[str, Any] | None, + reserved_keys: set[str] | frozenset[str], +) -> tuple[dict[str, Any], dict[str, Any]]: + normalized = normalize_request_params(params) + allowed: dict[str, Any] = {} + reserved: dict[str, Any] = {} + for key, value in normalized.items(): + if key in reserved_keys: + reserved[key] = value + else: + allowed[key] = value + return allowed, reserved diff --git a/src/Undefined/webui/static/js/config-form.js b/src/Undefined/webui/static/js/config-form.js index 13eecfca..3260f9eb 100644 --- a/src/Undefined/webui/static/js/config-form.js +++ b/src/Undefined/webui/static/js/config-form.js @@ -42,6 +42,40 @@ function updateConfigSearchIndex() { }); } +function isPlainObject(value) { + return value !== null && typeof value === "object" && !Array.isArray(value) +} + +function isAotCollection(path, value) { + return Array.isArray(value) && (AOT_PATHS.has(path) || value.some(item => item !== null && typeof item === "object")) +} + +function isRequestParamsPath(path) { + return path === "request_params" || path.endsWith(".request_params") +} + +function scheduleAutoSave() { + if (state.saveTimer) clearTimeout(state.saveTimer) + showSaveStatus("saving", t("config.typing")) + state.saveTimer = setTimeout(() => { + state.saveTimer = null + autoSave() + }, 1000) +} + +function createEditorNode(path, value) { + if (isRequestParamsPath(path)) { + return createRequestParamsWidget(path, isPlainObject(value) ? value : {}) + } + if (isPlainObject(value)) { + return createSubSubSection(path, value) + } + if (isAotCollection(path, value)) { + return createAotWidget(path, value) + } + return createField(path, value) +} + function buildConfigForm() { const container = get("formSections"); if (!container) return; @@ -93,42 +127,7 @@ function buildConfigForm() { card.appendChild(fieldGrid); for (const [key, val] of Object.entries(values)) { - if (typeof val === "object" && !Array.isArray(val)) { - const subSection = document.createElement("div"); - subSection.className = "form-subsection"; - - const subTitle = document.createElement("div"); - subTitle.className = "form-subtitle"; - subTitle.innerText = `[${section}.${key}]`; - subSection.appendChild(subTitle); - - const subCommentKey = `${section}.${key}`; - const subComment = getComment(subCommentKey); - if (subComment) { - const subHint = document.createElement("div"); - subHint.className = "form-subtitle-hint"; - subHint.innerText = subComment; - subHint.dataset.commentPath = subCommentKey; - subSection.appendChild(subHint); - } - - const subGrid = document.createElement("div"); - subGrid.className = "form-fields"; - for (const [sk, sv] of Object.entries(val)) { - const subPath = `${section}.${key}.${sk}`; - if (sv !== null && typeof sv === "object" && !Array.isArray(sv)) { - subGrid.appendChild(createSubSubSection(subPath, sv)); - } else if (Array.isArray(sv) && (AOT_PATHS.has(subPath) || sv.some(i => typeof i === "object" && i !== null))) { - subGrid.appendChild(createAotWidget(subPath, sv)); - } else { - subGrid.appendChild(createField(subPath, sv)); - } - } - subSection.appendChild(subGrid); - fieldGrid.appendChild(subSection); - continue; - } - fieldGrid.appendChild(createField(`${section}.${key}`, val)); + fieldGrid.appendChild(createEditorNode(`${section}.${key}`, val)); } container.appendChild(card); } @@ -294,11 +293,7 @@ function createField(path, val) { input.dataset.path = path; group.appendChild(input); - input.oninput = () => { - if (state.saveTimer) clearTimeout(state.saveTimer); - showSaveStatus("saving", t("config.typing")); - state.saveTimer = setTimeout(() => { state.saveTimer = null; autoSave(); }, 1000); - }; + input.oninput = () => scheduleAutoSave(); } return group; } @@ -324,145 +319,534 @@ function createSubSubSection(path, obj) { grid.className = "form-fields"; for (const [k, v] of Object.entries(obj)) { const subPath = `${path}.${k}`; - if (AOT_PATHS.has(subPath) || (Array.isArray(v) && v.length > 0 && v.every(i => typeof i === "object" && i !== null))) { - grid.appendChild(createAotWidget(subPath, v)); - } else { - grid.appendChild(createField(subPath, v)); - } + grid.appendChild(createEditorNode(subPath, v)); } div.appendChild(grid); return div; } +function buildEmptyStructuredValue(value) { + if (Array.isArray(value)) { + return value.length > 0 ? [buildEmptyStructuredValue(value[0])] : [] + } + if (isPlainObject(value)) { + return Object.fromEntries(Object.keys(value).map(key => [key, buildEmptyStructuredValue(value[key])])) + } + if (typeof value === "boolean") return false + if (value === null) return null + return "" +} + +function inferStructuredType(value) { + if (Array.isArray(value)) return "array" + if (isPlainObject(value)) return "object" + return "scalar" +} + +function inferScalarType(value) { + if (value === null) return "null" + if (typeof value === "number") return "number" + if (typeof value === "boolean") return "boolean" + return "string" +} + +function createRequestParamsWidget(path, value) { + const group = document.createElement("div") + group.className = "form-group" + group.dataset.path = path + + const label = document.createElement("label") + label.className = "form-label" + label.innerText = path.split(".").pop() + group.appendChild(label) + + const comment = getComment(path) + if (comment) { + const hint = document.createElement("div") + hint.className = "form-hint" + hint.innerText = comment + hint.dataset.commentPath = path + group.appendChild(hint) + } + + group.dataset.searchText = `${path} ${comment || ""}`.toLowerCase() + const editor = createStructuredValueEditor(value, { rootType: "object" }) + editor.dataset.requestParamsRoot = "true" + group.appendChild(editor) + return group +} + +function createStructuredActionButton(text, onClick) { + const button = document.createElement("button") + button.type = "button" + button.className = "btn ghost btn-sm" + button.innerText = text + button.onclick = onClick + return button +} + +function createStructuredValueEditor(value, options = {}) { + const rootType = options.rootType || inferStructuredType(value) + if (rootType === "object") { + return createStructuredObjectEditor(isPlainObject(value) ? value : {}) + } + if (rootType === "array") { + return createStructuredArrayEditor(Array.isArray(value) ? value : []) + } + return createStructuredScalarEditor(value) +} + +function createStructuredObjectEditor(value) { + const wrapper = document.createElement("div") + wrapper.dataset.structuredType = "object" + + const body = document.createElement("div") + body.className = "request-params-object-body" + wrapper.appendChild(body) + + Object.entries(value).forEach(([key, itemValue]) => { + body.appendChild(createStructuredObjectEntry(key, itemValue)) + }) + + const actions = document.createElement("div") + actions.style.marginTop = "8px" + actions.style.display = "flex" + actions.style.gap = "8px" + actions.style.flexWrap = "wrap" + actions.appendChild(createStructuredActionButton(`${t("config.aot_add")} Field`, () => { + body.appendChild(createStructuredObjectEntry("", "")) + autoSave() + })) + actions.appendChild(createStructuredActionButton(`${t("config.aot_add")} Object`, () => { + body.appendChild(createStructuredObjectEntry("", {})) + autoSave() + })) + actions.appendChild(createStructuredActionButton(`${t("config.aot_add")} Array`, () => { + body.appendChild(createStructuredObjectEntry("", [])) + autoSave() + })) + wrapper.appendChild(actions) + + return wrapper +} + +function createStructuredObjectEntry(key, value) { + const entry = document.createElement("div") + entry.className = "request-params-object-entry" + entry.style.cssText = "border:1px solid var(--border);border-radius:6px;padding:10px;margin-bottom:8px;" + + const keyGroup = document.createElement("div") + keyGroup.className = "form-group" + const keyLabel = document.createElement("label") + keyLabel.className = "form-label" + keyLabel.innerText = "key" + keyGroup.appendChild(keyLabel) + const keyInput = document.createElement("input") + keyInput.type = "text" + keyInput.className = "form-control request-params-key-input" + keyInput.value = key || "" + keyInput.oninput = () => scheduleAutoSave() + keyGroup.appendChild(keyInput) + entry.appendChild(keyGroup) + + const valueContainer = document.createElement("div") + valueContainer.className = "request-params-entry-value" + valueContainer.appendChild(createStructuredValueEditor(value)) + entry.appendChild(valueContainer) + + const removeBtn = createStructuredActionButton(t("config.aot_remove"), () => { + entry.remove() + autoSave() + }) + entry.appendChild(removeBtn) + + return entry +} + +function createStructuredArrayEditor(value) { + const wrapper = document.createElement("div") + wrapper.dataset.structuredType = "array" + + const body = document.createElement("div") + body.className = "request-params-array-body" + wrapper.appendChild(body) + + value.forEach(itemValue => { + body.appendChild(createStructuredArrayEntry(itemValue)) + }) + + const actions = document.createElement("div") + actions.style.marginTop = "8px" + actions.style.display = "flex" + actions.style.gap = "8px" + actions.style.flexWrap = "wrap" + actions.appendChild(createStructuredActionButton(`${t("config.aot_add")} Value`, () => { + body.appendChild(createStructuredArrayEntry("")) + autoSave() + })) + actions.appendChild(createStructuredActionButton(`${t("config.aot_add")} Object`, () => { + body.appendChild(createStructuredArrayEntry({})) + autoSave() + })) + actions.appendChild(createStructuredActionButton(`${t("config.aot_add")} Array`, () => { + body.appendChild(createStructuredArrayEntry([])) + autoSave() + })) + wrapper.appendChild(actions) + + return wrapper +} + +function createStructuredArrayEntry(value) { + const entry = document.createElement("div") + entry.className = "request-params-array-entry" + entry.style.cssText = "border:1px solid var(--border);border-radius:6px;padding:10px;margin-bottom:8px;" + + const valueContainer = document.createElement("div") + valueContainer.className = "request-params-entry-value" + valueContainer.appendChild(createStructuredValueEditor(value)) + entry.appendChild(valueContainer) + + const removeBtn = createStructuredActionButton(t("config.aot_remove"), () => { + entry.remove() + autoSave() + }) + entry.appendChild(removeBtn) + + return entry +} + +function createStructuredScalarEditor(value) { + const wrapper = document.createElement("div") + wrapper.dataset.structuredType = "scalar" + + const typeGroup = document.createElement("div") + typeGroup.className = "form-group" + const typeLabel = document.createElement("label") + typeLabel.className = "form-label" + typeLabel.innerText = "type" + typeGroup.appendChild(typeLabel) + + const typeSelect = document.createElement("select") + typeSelect.className = "form-control request-params-scalar-type" + ;["string", "number", "boolean", "null"].forEach(type => { + const option = document.createElement("option") + option.value = type + option.innerText = type + typeSelect.appendChild(option) + }) + typeSelect.value = inferScalarType(value) + typeGroup.appendChild(typeSelect) + wrapper.appendChild(typeGroup) + + const valueContainer = document.createElement("div") + valueContainer.className = "request-params-scalar-value" + wrapper.appendChild(valueContainer) + + const renderValueInput = () => { + const scalarType = typeSelect.value + valueContainer.textContent = "" + + if (scalarType === "null") { + const emptyHint = document.createElement("div") + emptyHint.className = "form-hint" + emptyHint.innerText = "null" + valueContainer.appendChild(emptyHint) + return + } + + if (scalarType === "boolean") { + const booleanWrap = document.createElement("label") + booleanWrap.className = "toggle-wrapper" + const booleanInput = document.createElement("input") + booleanInput.type = "checkbox" + booleanInput.className = "toggle-input request-params-scalar-input" + booleanInput.checked = typeof value === "boolean" ? value : false + booleanInput.onchange = () => autoSave() + const track = document.createElement("span") + track.className = "toggle-track" + const handle = document.createElement("span") + handle.className = "toggle-handle" + track.appendChild(handle) + booleanWrap.appendChild(booleanInput) + booleanWrap.appendChild(track) + valueContainer.appendChild(booleanWrap) + return + } + + const input = document.createElement("input") + input.className = "form-control request-params-scalar-input" + input.type = scalarType === "number" ? "number" : "text" + if (scalarType === "number") { + input.step = "any" + input.value = typeof value === "number" ? String(value) : "" + } else { + input.value = value == null ? "" : String(value) + } + input.oninput = () => scheduleAutoSave() + valueContainer.appendChild(input) + } + + typeSelect.onchange = () => { + value = typeSelect.value === "boolean" ? false : typeSelect.value === "null" ? null : "" + renderValueInput() + autoSave() + } + + renderValueInput() + return wrapper +} + +function getStructuredValueChild(container) { + return Array.from(container.children).find(child => child.dataset && child.dataset.structuredType) +} + +function readStructuredValueEditor(node) { + const type = node.dataset.structuredType + if (type === "object") { + const result = {} + const body = node.querySelector(".request-params-object-body") + Array.from(body ? body.children : []).forEach(entry => { + const keyInput = entry.querySelector(".request-params-key-input") + const key = keyInput ? keyInput.value.trim() : "" + if (!key) return + const valueContainer = entry.querySelector(".request-params-entry-value") + const valueNode = valueContainer ? getStructuredValueChild(valueContainer) : null + if (!valueNode) return + result[key] = readStructuredValueEditor(valueNode) + }) + return result + } + if (type === "array") { + const body = node.querySelector(".request-params-array-body") + return Array.from(body ? body.children : []).map(entry => { + const valueContainer = entry.querySelector(".request-params-entry-value") + const valueNode = valueContainer ? getStructuredValueChild(valueContainer) : null + return valueNode ? readStructuredValueEditor(valueNode) : null + }) + } + + const scalarType = node.querySelector(".request-params-scalar-type")?.value || "string" + if (scalarType === "null") return null + const scalarInput = node.querySelector(".request-params-scalar-input") + if (scalarType === "boolean") { + return Boolean(scalarInput?.checked) + } + const raw = scalarInput ? scalarInput.value : "" + if (scalarType === "number") { + const parsed = Number(raw) + return Number.isNaN(parsed) ? 0 : parsed + } + return raw +} + +function createAotScalarInput(key, value) { + const isLong = isLongText(value) + const isNumber = typeof value === "number" + const isBoolean = typeof value === "boolean" + const isArray = Array.isArray(value) + const isSecret = isSensitiveKey(key) + + if (isBoolean) { + const wrapper = document.createElement("label") + wrapper.className = "toggle-wrapper" + const toggle = document.createElement("input") + toggle.type = "checkbox" + toggle.className = "toggle-input aot-field-input" + toggle.dataset.valueType = "boolean" + toggle.checked = Boolean(value) + toggle.onchange = () => autoSave() + const track = document.createElement("span") + track.className = "toggle-track" + const handle = document.createElement("span") + handle.className = "toggle-handle" + track.appendChild(handle) + wrapper.appendChild(toggle) + wrapper.appendChild(track) + return wrapper + } + + let input + if (isLong) { + input = document.createElement("textarea") + input.className = "form-control form-textarea aot-field-input" + } else { + input = document.createElement("input") + input.className = "form-control aot-field-input" + input.type = isNumber ? "number" : isSecret ? "password" : "text" + if (isNumber) input.step = "any" + if (isSecret) input.setAttribute("autocomplete", "new-password") + } + + input.dataset.valueType = isNumber ? "number" : isArray ? "array" : "string" + if (isArray) { + input.dataset.arrayType = value.every(item => typeof item === "number") ? "number" : "string" + input.value = value.join(", ") + } else { + input.value = value == null ? "" : String(value) + } + input.oninput = () => scheduleAutoSave() + return input +} + function createAotEntry(path, entry) { - const div = document.createElement("div"); - div.className = "aot-entry"; - div.style.cssText = "border:1px solid var(--border);border-radius:6px;padding:10px;margin-bottom:8px;"; - const fields = document.createElement("div"); - fields.className = "form-fields"; - for (const [k, v] of Object.entries(entry)) { - const fg = document.createElement("div"); - fg.className = "form-group"; - fg.dataset.path = `${path}[].${k}`; - const lbl = document.createElement("label"); - lbl.className = "form-label"; - lbl.innerText = k; - fg.appendChild(lbl); - const isSecret = isSensitiveKey(k); - const inp = document.createElement("input"); - inp.className = "form-control aot-field-input"; - inp.type = isSecret ? "password" : "text"; - inp.value = v == null ? "" : String(v); - inp.dataset.fieldKey = k; - if (isSecret) inp.setAttribute("autocomplete", "new-password"); - inp.oninput = () => { - if (state.saveTimer) clearTimeout(state.saveTimer); - showSaveStatus("saving", t("config.typing")); - state.saveTimer = setTimeout(() => { state.saveTimer = null; autoSave(); }, 1000); - }; - fg.appendChild(inp); - fields.appendChild(fg); - } - div.appendChild(fields); - const removeBtn = document.createElement("button"); - removeBtn.type = "button"; - removeBtn.className = "btn ghost btn-sm"; - removeBtn.innerText = t("config.aot_remove"); - removeBtn.onclick = () => { div.remove(); autoSave(); }; - div.appendChild(removeBtn); - return div; + const div = document.createElement("div") + div.className = "aot-entry" + div.style.cssText = "border:1px solid var(--border);border-radius:6px;padding:10px;margin-bottom:8px;" + const fields = document.createElement("div") + fields.className = "form-fields" + + for (const [key, value] of Object.entries(entry)) { + const field = document.createElement("div") + field.className = "form-group aot-entry-field" + field.dataset.fieldKey = key + field.dataset.path = `${path}[].${key}` + + const label = document.createElement("label") + label.className = "form-label" + label.innerText = key + field.appendChild(label) + + const fieldPath = `${path}.${key}` + if (isPlainObject(value) || Array.isArray(value)) { + field.dataset.fieldEditor = "structured" + const editor = createStructuredValueEditor(value, { rootType: isRequestParamsPath(fieldPath) ? "object" : inferStructuredType(value) }) + field.appendChild(editor) + } else { + field.dataset.fieldEditor = "scalar" + field.appendChild(createAotScalarInput(key, value)) + } + fields.appendChild(field) + } + + div.appendChild(fields) + const removeBtn = document.createElement("button") + removeBtn.type = "button" + removeBtn.className = "btn ghost btn-sm" + removeBtn.innerText = t("config.aot_remove") + removeBtn.onclick = () => { div.remove(); autoSave() } + div.appendChild(removeBtn) + return div +} + +function buildAotTemplate(path, arr) { + if (arr && arr.length > 0) { + const template = buildEmptyStructuredValue(arr[0]) + if (AOT_PATHS.has(path) && !Object.prototype.hasOwnProperty.call(template, "request_params")) { + template.request_params = {} + } + return template + } + return { model_name: "", api_url: "", api_key: "", request_params: {} } } function createAotWidget(path, arr) { - const DEFAULT_ENTRY = { model_name: "", api_url: "", api_key: "" }; - const container = document.createElement("div"); - container.className = "form-group"; - container.dataset.path = path; - const lbl = document.createElement("div"); - lbl.className = "form-label"; - lbl.innerText = path.split(".").pop(); - container.appendChild(lbl); - const comment = getComment(path); + const container = document.createElement("div") + container.className = "form-group" + container.dataset.path = path + const lbl = document.createElement("div") + lbl.className = "form-label" + lbl.innerText = path.split(".").pop() + container.appendChild(lbl) + const comment = getComment(path) if (comment) { - const hint = document.createElement("div"); - hint.className = "form-hint"; - hint.innerText = comment; - hint.dataset.commentPath = path; - container.appendChild(hint); - } - const entriesDiv = document.createElement("div"); - entriesDiv.dataset.aotPath = path; - container.appendChild(entriesDiv); - (arr || []).forEach(entry => entriesDiv.appendChild(createAotEntry(path, entry))); - const addBtn = document.createElement("button"); - addBtn.type = "button"; - addBtn.className = "btn ghost btn-sm"; - addBtn.style.marginTop = "4px"; - addBtn.innerText = t("config.aot_add"); + const hint = document.createElement("div") + hint.className = "form-hint" + hint.innerText = comment + hint.dataset.commentPath = path + container.appendChild(hint) + } + container.dataset.searchText = `${path} ${comment || ""}`.toLowerCase() + const entriesDiv = document.createElement("div") + entriesDiv.dataset.aotPath = path + container.appendChild(entriesDiv) + ;(arr || []).forEach(entry => entriesDiv.appendChild(createAotEntry(path, entry))) + const addBtn = document.createElement("button") + addBtn.type = "button" + addBtn.className = "btn ghost btn-sm" + addBtn.style.marginTop = "4px" + addBtn.innerText = t("config.aot_add") addBtn.onclick = () => { - const template = arr && arr.length > 0 ? Object.fromEntries(Object.keys(arr[0]).map(k => [k, ""])) : DEFAULT_ENTRY; - entriesDiv.appendChild(createAotEntry(path, template)); - autoSave(); - }; - container.appendChild(addBtn); - return container; + entriesDiv.appendChild(createAotEntry(path, buildAotTemplate(path, arr))) + autoSave() + } + container.appendChild(addBtn) + return container +} + +function parseInputValue(input) { + const valueType = input.dataset.valueType || "string" + if (valueType === "boolean") { + return input.checked + } + const raw = input.value + if (valueType === "number") { + const trimmed = raw.trim() + if (!trimmed) return "" + const parsed = trimmed.includes(".") ? parseFloat(trimmed) : parseInt(trimmed, 10) + return Number.isNaN(parsed) ? raw : parsed + } + if (valueType === "array") { + const items = raw.split(",").map(item => item.trim()).filter(Boolean) + return input.dataset.arrayType === "number" + ? items.map(item => { + const number = Number(item) + return Number.isNaN(number) ? item : number + }) + : items + } + return raw } async function autoSave() { - showSaveStatus("saving"); + showSaveStatus("saving") - const patch = {}; + const patch = {} document.querySelectorAll(".config-input").forEach(input => { - const path = input.dataset.path; - let val; - if (input.type === "checkbox") { - val = input.checked; - } else { - const raw = input.value; - const valueType = input.dataset.valueType || "string"; - if (valueType === "number") { - const trimmed = raw.trim(); - if (!trimmed) { val = ""; } - else { - val = trimmed.includes(".") ? parseFloat(trimmed) : parseInt(trimmed, 10); - if (Number.isNaN(val)) val = raw; - } - } else if (valueType === "array") { - const items = raw.split(",").map(s => s.trim()).filter(Boolean); - val = input.dataset.arrayType === "number" - ? items.map(item => { const num = Number(item); return Number.isNaN(num) ? item : num; }) - : items; - } else { - val = raw; - } - } - patch[path] = val; - }); + patch[input.dataset.path] = parseInputValue(input) + }) + + document.querySelectorAll("[data-request-params-root]").forEach(editor => { + const group = editor.closest(".form-group") + if (!group?.dataset.path) return + patch[group.dataset.path] = readStructuredValueEditor(editor) + }) document.querySelectorAll("[data-aot-path]").forEach(container => { - const aotPath = container.dataset.aotPath; - const entries = []; + const aotPath = container.dataset.aotPath + const entries = [] container.querySelectorAll(".aot-entry").forEach(entry => { - const obj = {}; - entry.querySelectorAll(".aot-field-input").forEach(inp => { obj[inp.dataset.fieldKey] = inp.value; }); - entries.push(obj); - }); - patch[aotPath] = entries; - }); + const obj = {} + entry.querySelectorAll(".aot-entry-field").forEach(field => { + const key = field.dataset.fieldKey + if (!key) return + if (field.dataset.fieldEditor === "structured") { + const valueNode = getStructuredValueChild(field) + obj[key] = valueNode ? readStructuredValueEditor(valueNode) : {} + return + } + const input = field.querySelector(".aot-field-input") + if (!input) return + obj[key] = parseInputValue(input) + }) + entries.push(obj) + }) + patch[aotPath] = entries + }) try { - const res = await api("/api/patch", { method: "POST", body: JSON.stringify({ patch }) }); - const data = await res.json(); + const res = await api("/api/patch", { method: "POST", body: JSON.stringify({ patch }) }) + const data = await res.json() if (data.success) { - showSaveStatus("saved"); - if (data.warning) showToast(`${t("common.warning")}: ${data.warning}`, "warning", 5000); + showSaveStatus("saved") + if (data.warning) showToast(`${t("common.warning")}: ${data.warning}`, "warning", 5000) } else { - showSaveStatus("error", t("config.save_error")); - showToast(`${t("common.error")}: ${data.error}`, "error", 5000); + showSaveStatus("error", t("config.save_error")) + showToast(`${t("common.error")}: ${data.error}`, "error", 5000) } } catch (e) { - showSaveStatus("error", t("config.save_network_error")); - showToast(`${t("common.error")}: ${e.message}`, "error", 5000); + showSaveStatus("error", t("config.save_network_error")) + showToast(`${t("common.error")}: ${e.message}`, "error", 5000) } } diff --git a/src/Undefined/webui/utils/toml_render.py b/src/Undefined/webui/utils/toml_render.py index 467e7dbd..532b0db6 100644 --- a/src/Undefined/webui/utils/toml_render.py +++ b/src/Undefined/webui/utils/toml_render.py @@ -61,13 +61,40 @@ def _is_array_of_tables(value: Any) -> bool: ) -def render_table(path: list[str], table: TomlData) -> list[str]: - lines: list[str] = [] - items = [ +def _render_scalar_items(path: list[str], table: TomlData) -> list[str]: + return [ f"{key} = {format_value(table[key])}" for key in sorted_keys(table, path) if not isinstance(table[key], dict) and not _is_array_of_tables(table[key]) ] + + +def _render_nested_items(path: list[str], table: TomlData) -> list[str]: + lines: list[str] = [] + for key in sorted_keys(table, path): + value = table[key] + if isinstance(value, dict): + lines.extend(render_table(path + [key], value)) + elif _is_array_of_tables(value): + aot_path = path + [key] + for item in value: + lines.extend( + _render_array_of_tables_item(aot_path, cast(TomlData, item)) + ) + return lines + + +def _render_array_of_tables_item(path: list[str], table: TomlData) -> list[str]: + lines = [f"[[{'.'.join(path)}]]"] + lines.extend(_render_scalar_items(path, table)) + lines.append("") + lines.extend(_render_nested_items(path, table)) + return lines + + +def render_table(path: list[str], table: TomlData) -> list[str]: + lines: list[str] = [] + items = _render_scalar_items(path, table) if items and path: lines.append(f"[{'.'.join(path)}]") lines.extend(items) @@ -75,19 +102,7 @@ def render_table(path: list[str], table: TomlData) -> list[str]: elif items: lines.extend(items) lines.append("") - for key in sorted_keys(table, path): - value = table[key] - if isinstance(value, dict): - lines.extend(render_table(path + [key], value)) - elif _is_array_of_tables(value): - aot_path = ".".join(path + [key]) - for item in value: - lines.append(f"[[{aot_path}]]") - for k in sorted_keys(item, path + [key]): - v = item[k] - if not isinstance(v, dict): - lines.append(f"{k} = {format_value(v)}") - lines.append("") + lines.extend(_render_nested_items(path, table)) return lines diff --git a/tests/test_config_request_params.py b/tests/test_config_request_params.py new file mode 100644 index 00000000..f52384ac --- /dev/null +++ b/tests/test_config_request_params.py @@ -0,0 +1,98 @@ +from __future__ import annotations + +from pathlib import Path + +from Undefined.config.loader import Config + + +def _load_config(path: Path, text: str) -> Config: + path.write_text(text, "utf-8") + return Config.load(path, strict=False) + + +def test_model_request_params_load_and_inherit(tmp_path: Path) -> None: + cfg = _load_config( + tmp_path / "config.toml", + """ +[onebot] +ws_url = "ws://127.0.0.1:3001" + +[models.chat] +api_url = "https://api.openai.com/v1" +api_key = "sk-chat" +model_name = "gpt-chat" + +[models.chat.request_params] +temperature = 0.2 +metadata = { source = "chat" } + +[models.chat.pool] +enabled = true +strategy = "round_robin" + +[[models.chat.pool.models]] +model_name = "gpt-chat-b" +api_url = "https://pool.example/v1" +api_key = "sk-pool" + +[models.chat.pool.models.request_params] +temperature = 0.6 +provider = { name = "pool" } + +[models.agent] +api_url = "https://api.openai.com/v1" +api_key = "sk-agent" +model_name = "gpt-agent" + +[models.agent.request_params] +temperature = 0.3 +metadata = { source = "agent" } +response_format = { type = "json_object" } + +[models.historian] +model_name = "gpt-historian" + +[models.historian.request_params] +temperature = 0.1 +metadata = { source = "historian" } + +[models.embedding] +api_url = "https://api.openai.com/v1" +api_key = "sk-embed" +model_name = "text-embedding-3-small" + +[models.embedding.request_params] +encoding_format = "base64" +metadata = { source = "embed" } + +[models.rerank] +api_url = "https://api.openai.com/v1" +api_key = "sk-rerank" +model_name = "text-rerank-001" + +[models.rerank.request_params] +priority = "high" +""", + ) + + assert cfg.chat_model.request_params == { + "temperature": 0.2, + "metadata": {"source": "chat"}, + } + assert cfg.chat_model.pool is not None + assert cfg.chat_model.pool.models[0].request_params == { + "temperature": 0.6, + "metadata": {"source": "chat"}, + "provider": {"name": "pool"}, + } + assert cfg.security_model.request_params == cfg.chat_model.request_params + assert cfg.historian_model.request_params == { + "temperature": 0.1, + "metadata": {"source": "historian"}, + "response_format": {"type": "json_object"}, + } + assert cfg.embedding_model.request_params == { + "encoding_format": "base64", + "metadata": {"source": "embed"}, + } + assert cfg.rerank_model.request_params == {"priority": "high"} diff --git a/tests/test_llm_request_params.py b/tests/test_llm_request_params.py new file mode 100644 index 00000000..7cabc398 --- /dev/null +++ b/tests/test_llm_request_params.py @@ -0,0 +1,85 @@ +from __future__ import annotations + +from typing import Any, cast + +import httpx +import pytest +from openai import AsyncOpenAI + +from Undefined.ai.llm import ModelRequester +from Undefined.config.models import ChatModelConfig +from Undefined.token_usage_storage import TokenUsageStorage + + +class _FakeUsageStorage: + async def record(self, _usage: Any) -> None: + return None + + +class _FakeChatCompletionsAPI: + def __init__(self) -> None: + self.last_kwargs: dict[str, Any] | None = None + + async def create(self, **kwargs: Any) -> dict[str, Any]: + self.last_kwargs = dict(kwargs) + return { + "choices": [{"message": {"content": "ok"}}], + "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2}, + } + + +class _FakeChatClient: + def __init__(self) -> None: + self.chat = type("_Chat", (), {"completions": _FakeChatCompletionsAPI()})() + + +@pytest.mark.asyncio +async def test_request_uses_model_request_params_and_call_overrides( + caplog: pytest.LogCaptureFixture, +) -> None: + requester = ModelRequester( + http_client=httpx.AsyncClient(), + token_usage_storage=cast(TokenUsageStorage, _FakeUsageStorage()), + ) + fake_client = _FakeChatClient() + setattr( + requester, + "_get_openai_client_for_model", + lambda _cfg: cast(AsyncOpenAI, fake_client), + ) + cfg = ChatModelConfig( + api_url="https://api.openai.com/v1", + api_key="sk-test", + model_name="gpt-test", + max_tokens=512, + request_params={ + "temperature": 0.2, + "metadata": {"source": "config"}, + "stream": True, + "model": "should-be-ignored", + }, + ) + + await requester.request( + model_config=cfg, + messages=[{"role": "user", "content": "hello"}], + max_tokens=128, + call_type="chat", + temperature=0.7, + reasoning_effort="high", + ) + + assert fake_client.chat.completions.last_kwargs is not None + assert fake_client.chat.completions.last_kwargs["model"] == "gpt-test" + assert fake_client.chat.completions.last_kwargs["max_tokens"] == 128 + assert fake_client.chat.completions.last_kwargs["temperature"] == 0.7 + assert fake_client.chat.completions.last_kwargs["extra_body"] == { + "metadata": {"source": "config"}, + "reasoning_effort": "high", + } + assert ( + "ignored_keys=model,stream" in caplog.text + or "ignored_keys=stream,model" in caplog.text + ) + + await requester._http_client.aclose() diff --git a/tests/test_retrieval.py b/tests/test_retrieval.py index 5b7d558c..39bc65cc 100644 --- a/tests/test_retrieval.py +++ b/tests/test_retrieval.py @@ -106,6 +106,45 @@ async def test_embed_passes_dimensions_to_openai_sdk() -> None: assert fake_client.embeddings.last_kwargs["dimensions"] == 768 +@pytest.mark.asyncio +async def test_embed_passes_request_params_and_ignores_reserved_fields( + caplog: pytest.LogCaptureFixture, +) -> None: + fake_client = _FakeClient() + requester = RetrievalRequester( + get_openai_client=lambda _cfg: cast(AsyncOpenAI, fake_client), + response_to_dict=lambda response: { + "usage": getattr(response, "usage", {}), + }, + get_token_counter=lambda _model: cast(TokenCounter, _DummyCounter()), + record_usage=lambda **_kwargs: None, + ) + cfg = EmbeddingModelConfig( + api_url="https://api.openai.com/v1", + api_key="sk-test", + model_name="text-embedding-3-small", + queue_interval_seconds=1.0, + dimensions=768, + request_params={ + "encoding_format": "base64", + "user": "tester", + "metadata": {"source": "embed"}, + "dimensions": 1024, + }, + ) + + await requester.embed(cfg, ["hello"]) + + assert fake_client.embeddings.last_kwargs is not None + assert fake_client.embeddings.last_kwargs["dimensions"] == 768 + assert fake_client.embeddings.last_kwargs["encoding_format"] == "base64" + assert fake_client.embeddings.last_kwargs["user"] == "tester" + assert fake_client.embeddings.last_kwargs["extra_body"] == { + "metadata": {"source": "embed"} + } + assert "ignored_keys=dimensions" in caplog.text + + class _FakeRerankClient: def __init__(self) -> None: self.last_post_path: str | None = None @@ -142,6 +181,41 @@ async def test_rerank_disables_return_documents_in_request() -> None: assert result == [{"index": 1, "relevance_score": 0.88, "document": "doc B"}] +@pytest.mark.asyncio +async def test_rerank_passes_request_params_and_ignores_reserved_fields( + caplog: pytest.LogCaptureFixture, +) -> None: + fake_client = _FakeRerankClient() + requester = RetrievalRequester( + get_openai_client=lambda _cfg: cast(AsyncOpenAI, fake_client), + response_to_dict=lambda response: cast(dict[str, Any], response), + get_token_counter=lambda _model: cast(TokenCounter, _DummyCounter()), + record_usage=lambda **_kwargs: None, + ) + cfg = RerankModelConfig( + api_url="https://api.openai.com/v1", + api_key="sk-test", + model_name="text-rerank-001", + queue_interval_seconds=1.0, + request_params={ + "priority": "high", + "return_documents": True, + "query": "ignored", + }, + ) + + await requester.rerank(cfg, query="hello", documents=["doc A", "doc B"], top_n=1) + + assert fake_client.last_post_body is not None + assert fake_client.last_post_body["priority"] == "high" + assert fake_client.last_post_body["query"] == "hello" + assert fake_client.last_post_body["return_documents"] is False + assert ( + "ignored_keys=query,return_documents" in caplog.text + or "ignored_keys=return_documents,query" in caplog.text + ) + + @pytest.mark.asyncio async def test_rerank_falls_back_to_local_estimation_when_usage_is_zero() -> None: fake_client = _FakeRerankClient() diff --git a/tests/test_webui_render_toml.py b/tests/test_webui_render_toml.py index 83773f9c..6d8665a7 100644 --- a/tests/test_webui_render_toml.py +++ b/tests/test_webui_render_toml.py @@ -58,3 +58,56 @@ def test_aot_not_rendered_as_string(self) -> None: rendered = render_toml(tomllib.loads(src)) assert '"{' not in rendered assert "[[items]]" in rendered + + def test_pool_model_request_params_roundtrip(self) -> None: + """模型池条目下的 request_params 嵌套结构应完整往返""" + src = """ +[models.chat.pool] +enabled = true + +[[models.chat.pool.models]] +model_name = "gpt-5" +api_url = "https://api.openai.com/v1" +api_key = "sk-a" + +[models.chat.pool.models.request_params] +temperature = 0.7 + +[models.chat.pool.models.request_params.metadata] +source = "webui" + +[[models.chat.pool.models.request_params.tags]] +name = "alpha" + +[[models.chat.pool.models.request_params.tags]] +name = "beta" +""" + data = _roundtrip(src) + model = data["models"]["chat"]["pool"]["models"][0] + params = model["request_params"] + assert params["temperature"] == 0.7 + assert params["metadata"]["source"] == "webui" + assert [item["name"] for item in params["tags"]] == ["alpha", "beta"] + + def test_nested_aot_child_tables_roundtrip(self) -> None: + """数组表项下的嵌套表与子数组表不能在渲染时丢失""" + src = """ +[[items]] +name = "root" + +[items.meta] +enabled = true + +[[items.meta.children]] +name = "child-a" + +[[items.meta.children]] +name = "child-b" +""" + data = _roundtrip(src) + item = data["items"][0] + assert item["meta"]["enabled"] is True + assert [child["name"] for child in item["meta"]["children"]] == [ + "child-a", + "child-b", + ] From 5cf9ed8ed9eb9dc9317788131bf7feb162ae4df2 Mon Sep 17 00:00:00 2001 From: Null <1708213363@qq.com> Date: Sat, 7 Mar 2026 15:42:34 +0800 Subject: [PATCH 07/21] feat(ai): support responses transport and reasoning config --- AGENTS.md | 43 +- config.toml.example | 75 +++- docs/configuration.md | 51 ++- docs/openapi.md | 14 +- src/Undefined/ai/client.py | 26 +- src/Undefined/ai/llm.py | 201 +++++++-- src/Undefined/ai/model_selector.py | 6 + src/Undefined/ai/parsing.py | 11 + src/Undefined/ai/transports/__init__.py | 23 + .../ai/transports/openai_transport.py | 412 ++++++++++++++++++ src/Undefined/api/app.py | 6 + src/Undefined/cognitive/historian.py | 9 + src/Undefined/config/loader.py | 157 ++++++- src/Undefined/config/models.py | 25 +- src/Undefined/injection_response_agent.py | 6 +- src/Undefined/services/ai_coordinator.py | 1 + src/Undefined/services/security.py | 6 +- src/Undefined/skills/agents/README.md | 15 +- src/Undefined/skills/agents/runner.py | 9 + src/Undefined/webui/static/js/config-form.js | 50 ++- tests/test_config_request_params.py | 40 +- tests/test_llm_request_params.py | 252 ++++++++++- tests/test_runtime_api_probes.py | 65 +++ tests/test_webui_render_toml.py | 8 + 24 files changed, 1406 insertions(+), 105 deletions(-) create mode 100644 src/Undefined/ai/transports/__init__.py create mode 100644 src/Undefined/ai/transports/openai_transport.py create mode 100644 tests/test_runtime_api_probes.py diff --git a/AGENTS.md b/AGENTS.md index 9d2bd030..cba03cf5 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -1,37 +1,28 @@ # Repository Guidelines ## Project Structure & Module Organization -Core Python code lives in `src/Undefined/`, organized by domain: `ai/`, `services/`, `cognitive/`, `skills/`, `webui/`, and `utils/`. -Tests are in `tests/` (pytest auto-discovers from this directory). -Runtime/config assets live in `res/`, `img/`, and `config/`. -Operational scripts are in `scripts/` (for example, `scripts/reembed_cognitive.py`). -Documentation is in `docs/`, and CI/release workflows are under `.github/workflows/`. +Primary code lives in `src/Undefined/`. Keep changes in the matching domain package: `ai/` for model orchestration, `cognitive/` for memory pipelines, `services/` for runtime services, `skills/` for tools/agents/commands, `webui/` for the management UI, and `utils/` for shared helpers. Tests live in `tests/`. Packaged assets and defaults live in `res/`, `img/`, and `config/`. Scripts are in `scripts/`; docs are in `docs/`. ## Build, Test, and Development Commands -- `uv sync --group dev -p 3.12`: install project + development dependencies. -- `uv run playwright install`: install browser runtime used by rendering/web features. -- `uv run Undefined` or `uv run Undefined-webui`: run bot or WebUI (choose one, do not run both). -- `uv run ruff format .`: auto-format code. -- `uv run ruff check .`: lint checks. -- `uv run mypy .`: strict type checking (project is configured with `mypy` strict mode). -- `uv run pytest tests/`: run full test suite. -- `uv build --wheel`: build distributable wheel (CI also validates packaged resources). +- `uv sync --group dev -p 3.12`: install the project with contributor tooling. +- `uv run playwright install`: install the browser runtime used by rendering and web-driven features. +- `cp config.toml.example config.toml`: create a local config before running the app. +- `uv run Undefined`: start the bot process directly. +- `uv run Undefined-webui`: start the WebUI manager. Do not run this alongside `Undefined`. +- `uv run ruff format .`: apply formatting. +- `uv run ruff check .`: run lint checks. +- `uv run mypy .`: run strict type checking. +- `uv run pytest tests/`: run the full test suite. +- `uv build --wheel`: build the distribution and verify packaged resources. ## Coding Style & Naming Conventions -Use 4-space indentation, type annotations, and `async`/`await` for I/O paths when applicable. -Follow Ruff formatting output; do not hand-tune style against formatter/linter. -Use `snake_case` for modules/functions/variables, `PascalCase` for classes, and `UPPER_SNAKE_CASE` for constants. -Keep modules focused by capability (for example, add chat command logic under `skills/commands/`). +Use 4-space indentation, Python type hints, and `async`/`await` for I/O paths. Let Ruff drive formatting instead of hand-formatting around it. Use `snake_case` for modules, functions, and variables; `PascalCase` for classes; `UPPER_SNAKE_CASE` for constants. Keep modules narrow in scope, and place new Skills content under the correct subtree such as `skills/tools/`, `skills/toolsets/`, or `skills/agents/`. ## Testing Guidelines -Frameworks: `pytest`, `pytest-asyncio` (`asyncio_mode = auto`). -Name tests as `test_*.py` and test functions as `test_*`. -Prefer targeted runs during development, e.g. `uv run pytest tests/test_parse_command.py -q`. -Before opening a PR, run format, lint, type check, and full tests locally. -No fixed coverage gate is enforced, but add tests for behavior changes and regressions. +The project uses `pytest` with `pytest-asyncio` (`asyncio_mode = auto`). Name files `tests/test_*.py` and test functions `test_*`. Prefer focused runs while iterating, for example `uv run pytest tests/test_parse_command.py -q`, then finish with the full suite. Add regression coverage for behavior changes in handlers, config loading, Skills discovery, and WebUI routes. ## Commit & Pull Request Guidelines -Use Conventional Commit style seen in history: `feat: ...`, `fix(scope): ...`, `chore(version): ...`, `refactor: ...`. -Release tooling groups commits by `feat`/`fix`, so use these prefixes accurately. -PRs should include: concise summary, linked issue (if any), test evidence (commands/results), and screenshots for WebUI changes. -Ensure CI passes (`ruff`, `mypy`, `pytest`, build checks) before requesting review. +Follow the commit style already used in history: `feat: ...`, `fix(scope): ...`, `chore(version): ...`. Keep subjects short and imperative. PRs should include a clear summary, linked issue when applicable, the commands you ran (`ruff`, `mypy`, `pytest`), and screenshots for WebUI changes. If you modify `res/`, `img/`, or `config.toml.example`, note that wheel packaging was checked with `uv build --wheel`. + +## Security & Configuration Tips +Treat `config.toml` as runtime state and avoid committing secrets. Prefer `config.toml.example` for documented defaults. Outputs under `data/` and `logs/` should stay out of feature commits unless the change explicitly targets fixtures or diagnostics. diff --git a/config.toml.example b/config.toml.example index 70fca10f..4bd8c629 100644 --- a/config.toml.example +++ b/config.toml.example @@ -89,6 +89,15 @@ max_tokens = 8192 # zh: 队列发车间隔（秒）。 # en: Queue interval (seconds). queue_interval_seconds = 1.0 +# zh: API 模式：传统 chat.completions 或新版 responses。 +# en: API mode: classic chat.completions or the newer responses API. +api_mode = "chat_completions" +# zh: 是否启用 reasoning.effort。 +# en: Enable reasoning.effort. +reasoning_enabled = false +# zh: reasoning.effort 档位：none / minimal / low / medium / high / xhigh。 +# en: reasoning.effort level: none / minimal / low / medium / high / xhigh. +reasoning_effort = "medium" # zh: 是否启用 thinking（思维链）。 # en: Enable thinking (reasoning). thinking_enabled = false @@ -100,10 +109,10 @@ thinking_budget_tokens = 20000 thinking_include_budget = true # zh: 思维链工具调用兼容：启用后在多轮工具调用中回传 reasoning_content，避免部分模型返回 400。 # en: Thinking tool-call compatibility: pass back reasoning_content in multi-turn tool calls to avoid 400 errors from some models. -thinking_tool_call_compat = false +thinking_tool_call_compat = true -# zh: 额外请求体参数（可选），可用于 temperature、reasoning_effort 或供应商私有参数。 -# en: Extra request-body params (optional), e.g. temperature, reasoning_effort, or vendor-specific fields. +# zh: 额外请求体参数（可选），可用于 temperature 或供应商私有参数。 +# en: Extra request-body params (optional), e.g. temperature or vendor-specific fields. [models.chat.request_params] # zh: 模型池配置（可选，支持多模型轮询/随机/用户指定）。 @@ -134,6 +143,15 @@ model_name = "" # zh: 队列发车间隔（秒）。 # en: Queue interval (seconds). queue_interval_seconds = 1.0 +# zh: API 模式：传统 chat.completions 或新版 responses。 +# en: API mode: classic chat.completions or the newer responses API. +api_mode = "chat_completions" +# zh: 是否启用 reasoning.effort。 +# en: Enable reasoning.effort. +reasoning_enabled = false +# zh: reasoning.effort 档位：none / minimal / low / medium / high / xhigh。 +# en: reasoning.effort level: none / minimal / low / medium / high / xhigh. +reasoning_effort = "medium" # zh: 是否启用 thinking（思维链）。 # en: Enable thinking (reasoning). thinking_enabled = false @@ -145,10 +163,10 @@ thinking_budget_tokens = 20000 thinking_include_budget = true # zh: 思维链工具调用兼容：启用后在多轮工具调用中回传 reasoning_content，避免部分模型返回 400。 # en: Thinking tool-call compatibility: pass back reasoning_content in multi-turn tool calls to avoid 400 errors from some models. -thinking_tool_call_compat = false +thinking_tool_call_compat = true -# zh: 额外请求体参数（可选），可用于 temperature、reasoning_effort 或供应商私有参数。 -# en: Extra request-body params (optional), e.g. temperature, reasoning_effort, or vendor-specific fields. +# zh: 额外请求体参数（可选），可用于 temperature 或供应商私有参数。 +# en: Extra request-body params (optional), e.g. temperature or vendor-specific fields. [models.vision.request_params] # zh: 安全模型配置（用于防注入检测和注入后回复生成）。 @@ -172,6 +190,15 @@ max_tokens = 100 # zh: 队列发车间隔（秒）。 # en: Queue interval (seconds). queue_interval_seconds = 1.0 +# zh: API 模式：传统 chat.completions 或新版 responses。 +# en: API mode: classic chat.completions or the newer responses API. +api_mode = "chat_completions" +# zh: 是否启用 reasoning.effort。 +# en: Enable reasoning.effort. +reasoning_enabled = false +# zh: reasoning.effort 档位：none / minimal / low / medium / high / xhigh。 +# en: reasoning.effort level: none / minimal / low / medium / high / xhigh. +reasoning_effort = "medium" # zh: 是否启用 thinking（思维链）。 # en: Enable thinking (reasoning). thinking_enabled = false @@ -183,10 +210,10 @@ thinking_budget_tokens = 0 thinking_include_budget = true # zh: 思维链工具调用兼容：启用后在多轮工具调用中回传 reasoning_content，避免部分模型返回 400。 # en: Thinking tool-call compatibility: pass back reasoning_content in multi-turn tool calls to avoid 400 errors from some models. -thinking_tool_call_compat = false +thinking_tool_call_compat = true -# zh: 额外请求体参数（可选），可用于 temperature、reasoning_effort 或供应商私有参数。 -# en: Extra request-body params (optional), e.g. temperature, reasoning_effort, or vendor-specific fields. +# zh: 额外请求体参数（可选），可用于 temperature 或供应商私有参数。 +# en: Extra request-body params (optional), e.g. temperature or vendor-specific fields. [models.security.request_params] # zh: Agent 模型配置（用于执行 agents）。 @@ -207,6 +234,15 @@ max_tokens = 4096 # zh: 队列发车间隔（秒）。 # en: Queue interval (seconds). queue_interval_seconds = 1.0 +# zh: API 模式：传统 chat.completions 或新版 responses。 +# en: API mode: classic chat.completions or the newer responses API. +api_mode = "chat_completions" +# zh: 是否启用 reasoning.effort。 +# en: Enable reasoning.effort. +reasoning_enabled = false +# zh: reasoning.effort 档位：none / minimal / low / medium / high / xhigh。 +# en: reasoning.effort level: none / minimal / low / medium / high / xhigh. +reasoning_effort = "medium" # zh: 是否启用 thinking（思维链）。 # en: Enable thinking (reasoning). thinking_enabled = false @@ -218,10 +254,10 @@ thinking_budget_tokens = 0 thinking_include_budget = true # zh: 思维链工具调用兼容：启用后在多轮工具调用中回传 reasoning_content，避免部分模型返回 400。 # en: Thinking tool-call compatibility: pass back reasoning_content in multi-turn tool calls to avoid 400 errors from some models. -thinking_tool_call_compat = false +thinking_tool_call_compat = true -# zh: 额外请求体参数（可选），可用于 temperature、reasoning_effort 或供应商私有参数。 -# en: Extra request-body params (optional), e.g. temperature, reasoning_effort, or vendor-specific fields. +# zh: 额外请求体参数（可选），可用于 temperature 或供应商私有参数。 +# en: Extra request-body params (optional), e.g. temperature or vendor-specific fields. [models.agent.request_params] # zh: Agent 模型池配置（可选，支持多模型轮询/随机/用户指定）。 @@ -255,6 +291,15 @@ max_tokens = 4096 # zh: 队列发车间隔（秒）。 # en: Queue interval (seconds). queue_interval_seconds = 1.0 +# zh: API 模式：传统 chat.completions 或新版 responses。 +# en: API mode: classic chat.completions or the newer responses API. +api_mode = "chat_completions" +# zh: 是否启用 reasoning.effort。 +# en: Enable reasoning.effort. +reasoning_enabled = false +# zh: reasoning.effort 档位：none / minimal / low / medium / high / xhigh。 +# en: reasoning.effort level: none / minimal / low / medium / high / xhigh. +reasoning_effort = "medium" # zh: 是否启用 thinking（思维链）。 # en: Enable thinking (reasoning). thinking_enabled = false @@ -266,10 +311,10 @@ thinking_budget_tokens = 0 thinking_include_budget = true # zh: 思维链工具调用兼容：启用后在多轮工具调用中回传 reasoning_content，避免部分模型返回 400。 # en: Thinking tool-call compatibility: pass back reasoning_content in multi-turn tool calls to avoid 400 errors from some models. -thinking_tool_call_compat = false +thinking_tool_call_compat = true -# zh: 额外请求体参数（可选），可用于 temperature、reasoning_effort 或供应商私有参数。 -# en: Extra request-body params (optional), e.g. temperature, reasoning_effort, or vendor-specific fields. +# zh: 额外请求体参数（可选），可用于 temperature 或供应商私有参数。 +# en: Extra request-body params (optional), e.g. temperature or vendor-specific fields. [models.historian.request_params] # zh: 嵌入模型配置（知识库语义检索使用）。 diff --git a/docs/configuration.md b/docs/configuration.md index 7659fb1e..4ed6a221 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -142,12 +142,27 @@ model_name = "gpt-4o-mini" | `model_name` | 模型名 | | `max_tokens` | 最大输出 token（vision 无此字段） | | `queue_interval_seconds` | 该模型请求队列发车间隔（秒） | -| `thinking_enabled` | 是否启用思维链参数 | +| `api_mode` | 请求模式：`chat_completions` 或 `responses` | +| `reasoning_enabled` | 是否启用 `reasoning.effort` | +| `reasoning_effort` | `reasoning.effort` 档位：`none` / `minimal` / `low` / `medium` / `high` / `xhigh` | +| `thinking_enabled` | 是否启用旧式 `thinking` 参数 | | `thinking_budget_tokens` | thinking 预算 | -| `thinking_include_budget` | 是否发送 budget_tokens | -| `thinking_tool_call_compat` | Tool Calls 兼容模式（回传 reasoning_content） | +| `thinking_include_budget` | 是否发送 `budget_tokens` | +| `thinking_tool_call_compat` | Tool Calls 兼容模式：在多轮工具调用中回填 `reasoning_content`；默认 `true` | | `request_params` | 额外请求体参数（透传给模型 API，保留字段会忽略） | +请求模式说明： +- `api_mode="chat_completions"`：走 `client.chat.completions.create(...)` + - `thinking_enabled=true` 时发送旧式 `thinking` + - `reasoning_enabled=true` 时额外发送 `reasoning={ effort = ... }` +- `api_mode="responses"`：走 `client.responses.create(...)` + - 仅在 `reasoning_enabled=true` 时发送 `reasoning={ effort = ... }` + - 旧式 `thinking_*` 不会下发到 `responses` + +`request_params` 说明： +- 适合放 provider 私有请求体字段，例如 `metadata`、`temperature`、兼容网关扩展参数等。 +- 不要再通过 `request_params` 传 `reasoning` / `reasoning_effort` / `thinking`；这些现在有正式配置字段控制。 + 兼容字段（旧配置）： - `models..deepseek_new_cot_support` - 若开启：等效默认 `thinking_include_budget=false` + `thinking_tool_call_compat=true` @@ -158,37 +173,51 @@ model_name = "gpt-4o-mini" 默认： - `max_tokens=8192` - `queue_interval_seconds=1.0`（`<=0` 回退 `1.0`） +- `api_mode="chat_completions"` +- `reasoning_enabled=false` +- `reasoning_effort="medium"` - `thinking_budget_tokens=20000` +- `thinking_tool_call_compat=true` 补充： -- 可通过 `[models.chat.request_params]` 传入 `temperature`、`response_format`、`reasoning_effort` 或兼容网关私有字段。 +- 若上游只对 `/v1/responses` 识别自定义参数，可将 `api_mode` 切到 `responses`。 +- `[models.chat.request_params]` 仍可放 `temperature`、`response_format` 或兼容网关私有字段，但不再用于 `reasoning` 配置。 ### 4.4.3 `[models.vision]` 视觉模型 默认： - `queue_interval_seconds=1.0`（`<=0` 回退 `1.0`） +- `api_mode="chat_completions"` +- `reasoning_enabled=false` +- `reasoning_effort="medium"` - `thinking_budget_tokens=20000` +- `thinking_tool_call_compat=true` ### 4.4.4 `[models.security]` 安全模型 字段： - 额外开关：`enabled=true` -- 默认：`max_tokens=100`，`thinking_budget_tokens=0` +- 默认：`max_tokens=100`、`api_mode="chat_completions"`、`reasoning_enabled=false`、`reasoning_effort="medium"`、`thinking_budget_tokens=0`、`thinking_tool_call_compat=true` 关键回退逻辑： - 若 `api_url/api_key/model_name` 任一缺失，会自动回退为 chat 模型（并告警）。 +- 回退时会继承 chat 的 `api_mode`、`reasoning_*` 与 `request_params`；旧 `thinking_*` 仍保持安全模型自身默认值。 ### 4.4.5 `[models.agent]` Agent 执行模型 默认： - `max_tokens=4096` - `queue_interval_seconds=1.0`（`<=0` 回退 `1.0`） +- `api_mode="chat_completions"` +- `reasoning_enabled=false` +- `reasoning_effort="medium"` +- `thinking_tool_call_compat=true` ### 4.4.6 `[models.historian]` 史官模型 - 用于认知记忆后台改写。 - 若整个节缺失或为空：完整回退到 `models.agent`。 -- 若部分字段缺失：逐项继承 agent 配置。 +- 若部分字段缺失：逐项继承 agent 配置，包括 `api_mode`、`reasoning_*`、`thinking_*` 与 `request_params`。 - `queue_interval_seconds<=0` 时回退到 agent 的间隔。 ### 4.4.7 模型池 @@ -209,7 +238,10 @@ model_name = "gpt-4o-mini" `models` 条目支持字段： - `model_name`（必填） -- `api_url`/`api_key`/`max_tokens`/`queue_interval_seconds`/`thinking_*`/`request_params`（可选，缺省继承主模型） +- `api_url` / `api_key` / `max_tokens` / `queue_interval_seconds` +- `api_mode` / `reasoning_enabled` / `reasoning_effort` +- `thinking_*` / `request_params` +- 以上可选字段缺省继承主模型 `request_params` 继承规则： - `[[models.chat.pool.models]]` 与 `[[models.agent.pool.models]]` 的 `request_params` 会与主模型按顶层键浅合并。 @@ -246,7 +278,8 @@ model_name = "gpt-4o-mini" `request_params` 说明： - 仅用于**请求体**字段，不包含 `api_key`、`base_url`、`timeout`、`extra_headers` 等 client 选项。 -- 聊天类保留字段：`model`、`messages`、`max_tokens`、`tools`、`tool_choice`、`stream`、`stream_options`。 +- 聊天类（`chat_completions`）保留字段：`model`、`messages`、`max_tokens`、`tools`、`tool_choice`、`stream`、`stream_options`、`reasoning`、`reasoning_effort`。 +- 聊天类（`responses`）保留字段：`model`、`input`、`instructions`、`max_output_tokens`、`tools`、`tool_choice`、`previous_response_id`、`stream`、`stream_options`、`thinking`、`reasoning`、`reasoning_effort`。 - embedding 保留字段：`model`、`input`、`dimensions`。 - rerank 保留字段：`model`、`query`、`documents`、`top_n`、`return_documents`。 @@ -638,7 +671,9 @@ model_name = "gpt-4o-mini" - `BOT_QQ` / `SUPERADMIN_QQ` - `ONEBOT_WS_URL` / `ONEBOT_TOKEN` - `CHAT_MODEL_API_URL` / `CHAT_MODEL_API_KEY` / `CHAT_MODEL_NAME` +- `CHAT_MODEL_API_MODE` / `CHAT_MODEL_REASONING_ENABLED` / `CHAT_MODEL_REASONING_EFFORT` - `VISION_MODEL_*` / `AGENT_MODEL_*` / `SECURITY_MODEL_*` +- 上述模型环境变量同样覆盖 `*_THINKING_ENABLED`、`*_THINKING_BUDGET_TOKENS`、`*_THINKING_TOOL_CALL_COMPAT` - `EMBEDDING_MODEL_*` / `RERANK_MODEL_*` - `SEARXNG_URL` - `HTTP_PROXY` / `HTTPS_PROXY` diff --git a/docs/openapi.md b/docs/openapi.md index f683f6a1..eca5d6df 100644 --- a/docs/openapi.md +++ b/docs/openapi.md @@ -79,7 +79,7 @@ curl http://127.0.0.1:8788/openapi.json | `cognitive` | `object` | 认知服务（`enabled`、`queue`） | | `api` | `object` | Runtime API 配置（`enabled`、`host`、`port`、`openapi_enabled`） | | `skills` | `object` | 技能统计，包含 `tools`、`agents`、`anthropic_skills` 三个子对象 | -| `models` | `object` | 模型配置，包含各模型的 `model_name`、脱敏 `api_url`、`thinking_enabled` | +| `models` | `object` | 模型配置；聊天类模型包含 `model_name`、脱敏 `api_url`、`api_mode`、`thinking_enabled`、`thinking_tool_call_compat`、`reasoning_enabled`、`reasoning_effort` | `skills` 子对象结构： @@ -93,11 +93,19 @@ curl http://127.0.0.1:8788/openapi.json } ``` -`models` 子对象结构（URL 经脱敏处理，仅保留 scheme + host）： +`models` 子对象结构（URL 经脱敏处理，仅保留 scheme + host；embedding/rerank 仅返回 `model_name` 与 `api_url`）： ```json { - "chat_model": { "model_name": "claude-sonnet-4-20250514", "api_url": "https://api.example.com/...", "thinking_enabled": false }, + "chat_model": { + "model_name": "claude-sonnet-4-20250514", + "api_url": "https://api.example.com/...", + "api_mode": "responses", + "thinking_enabled": false, + "thinking_tool_call_compat": true, + "reasoning_enabled": true, + "reasoning_effort": "high" + }, "embedding_model": { "model_name": "text-embedding-3-small", "api_url": "https://api.example.com/..." } } ``` diff --git a/src/Undefined/ai/client.py b/src/Undefined/ai/client.py index 113bd86b..86153ddc 100644 --- a/src/Undefined/ai/client.py +++ b/src/Undefined/ai/client.py @@ -320,6 +320,7 @@ async def submit_background_llm_call( tool_choice: Any = "auto", call_type: str = "background", max_tokens: int | None = None, + transport_state: dict[str, Any] | None = None, ) -> dict[str, Any]: """将 LLM 调用投递到后台队列，走统一发车间隔和 Token 统计。 无 queue_manager 时降级为直接调用。""" @@ -336,6 +337,7 @@ async def submit_background_llm_call( tool_choice=tool_choice, call_type=call_type, max_tokens=effective_max_tokens, + transport_state=transport_state, ) request_id = uuid4().hex event: asyncio.Event = asyncio.Event() @@ -351,6 +353,7 @@ async def submit_background_llm_call( "tool_choice": tool_choice, "call_type": call_type, "max_tokens": effective_max_tokens, + "transport_state": transport_state, }, model_name=model_name, ) @@ -642,10 +645,18 @@ async def request_model( call_type: str = "chat", tools: list[dict[str, Any]] | None = None, tool_choice: str = "auto", + transport_state: dict[str, Any] | None = None, **kwargs: Any, ) -> dict[str, Any]: + message_count_for_transport = len(messages) tools = self.tool_manager.maybe_merge_agent_tools(call_type, tools) - messages, tools = await self._maybe_prefetch_tools(messages, tools, call_type) + if not ( + isinstance(transport_state, dict) + and transport_state.get("previous_response_id") + ): + messages, tools = await self._maybe_prefetch_tools( + messages, tools, call_type + ) return await self._requester.request( model_config=model_config, messages=messages, @@ -653,6 +664,8 @@ async def request_model( call_type=call_type, tools=tools, tool_choice=tool_choice, + transport_state=transport_state, + message_count_for_transport=message_count_for_transport, **kwargs, ) @@ -859,6 +872,7 @@ async def ask( cot_compat = getattr(effective_chat_config, "thinking_tool_call_compat", False) cot_compat_logged = False cot_missing_logged = False + transport_state: dict[str, Any] | None = None while iteration < max_iterations: iteration += 1 @@ -872,6 +886,7 @@ async def ask( call_type="chat", tools=tools, tool_choice="auto", + transport_state=transport_state, ) tool_name_map = ( @@ -885,6 +900,15 @@ async def ask( str(k): str(v) for k, v in raw_api_to_internal.items() } + next_transport_state = ( + result.get("_transport_state") if isinstance(result, dict) else None + ) + transport_state = ( + next_transport_state + if isinstance(next_transport_state, dict) + else None + ) + choice = result.get("choices", [{}])[0] message = choice.get("message", {}) content: str = message.get("content") or "" diff --git a/src/Undefined/ai/llm.py b/src/Undefined/ai/llm.py index bd7fd86f..0b584846 100644 --- a/src/Undefined/ai/llm.py +++ b/src/Undefined/ai/llm.py @@ -21,6 +21,13 @@ ) from Undefined.ai.parsing import extract_choices_content +from Undefined.ai.transports import ( + API_MODE_RESPONSES, + build_responses_request_body, + get_api_mode, + get_reasoning_payload, + normalize_responses_result, +) from Undefined.ai.retrieval import RetrievalRequester from Undefined.ai.tokens import TokenCounter from Undefined.config import ( @@ -80,6 +87,26 @@ {"extra_headers", "extra_query", "extra_body", "timeout"} ) +_RESPONSES_KNOWN_FIELDS: set[str] = { + "model", + "input", + "instructions", + "max_output_tokens", + "metadata", + "previous_response_id", + "reasoning", + "temperature", + "top_p", + "tools", + "tool_choice", + "parallel_tool_calls", + "stream", + "stream_options", + "text", + "truncation", + "user", +} + _CHAT_COMPLETIONS_RESERVED_FIELDS: frozenset[str] = ( frozenset( { @@ -90,6 +117,28 @@ "tool_choice", "stream", "stream_options", + "reasoning", + "reasoning_effort", + } + ) + | _SDK_REQUEST_OPTION_FIELDS +) + +_RESPONSES_RESERVED_FIELDS: frozenset[str] = ( + frozenset( + { + "model", + "input", + "instructions", + "max_output_tokens", + "tools", + "tool_choice", + "previous_response_id", + "stream", + "stream_options", + "thinking", + "reasoning", + "reasoning_effort", } ) | _SDK_REQUEST_OPTION_FIELDS @@ -332,6 +381,19 @@ def _split_chat_completion_params( return known, extra +def _split_responses_params( + body: dict[str, Any], +) -> tuple[dict[str, Any], dict[str, Any]]: + known: dict[str, Any] = {} + extra: dict[str, Any] = {} + for key, value in body.items(): + if key in _RESPONSES_KNOWN_FIELDS: + known[key] = value + else: + extra[key] = value + return known, extra + + def _is_deepseek_provider(model_config: ModelConfig) -> bool: model_name = str(getattr(model_config, "model_name", "") or "").lower() if model_name.startswith("deepseek"): @@ -778,9 +840,14 @@ def _build_effective_request_kwargs( getattr(model_config, "request_params", {}), overrides, ) + reserved_fields = ( + _RESPONSES_RESERVED_FIELDS + if get_api_mode(model_config) == API_MODE_RESPONSES + else _CHAT_COMPLETIONS_RESERVED_FIELDS + ) allowed, ignored = split_reserved_request_params( merged, - _CHAT_COMPLETIONS_RESERVED_FIELDS, + reserved_fields, ) _warn_ignored_request_params( call_type=call_type, @@ -821,11 +888,19 @@ async def request( call_type: str = "chat", tools: list[dict[str, Any]] | None = None, tool_choice: str = "auto", + transport_state: dict[str, Any] | None = None, + message_count_for_transport: int | None = None, **kwargs: Any, ) -> dict[str, Any]: """发送请求到模型 API。""" start_time = time.perf_counter() cot_compat = getattr(model_config, "thinking_tool_call_compat", False) + api_mode = get_api_mode(model_config) + transport_message_count = ( + message_count_for_transport + if message_count_for_transport is not None + else len(messages) + ) messages_for_api, tool_args_fixed = _sanitize_openai_messages_tool_arguments( messages ) @@ -835,32 +910,30 @@ async def request( tool_args_fixed, len(messages_for_api), ) - effective_kwargs = _build_effective_request_kwargs( - model_config, - call_type=call_type, - overrides=dict(kwargs), - ) - request_body = build_request_body( - model_config=model_config, - messages=messages_for_api, - max_tokens=max_tokens, - tools=tools, - tool_choice=tool_choice, - **effective_kwargs, - ) + tools_for_api = tools api_to_internal: dict[str, str] = {} internal_to_api: dict[str, str] = {} - if isinstance(request_body.get("tools"), list): + if isinstance(tools_for_api, list): + request_for_sanitize = { + "messages": messages_for_api, + "tools": list(tools_for_api), + } api_to_internal, internal_to_api = _sanitize_openai_tool_names_in_request( - request_body + request_for_sanitize ) - - if "tools" in request_body and isinstance(request_body.get("tools"), list): + raw_messages = request_for_sanitize.get("messages") + if isinstance(raw_messages, list): + messages_for_api = raw_messages + raw_tools = request_for_sanitize.get("tools") + if isinstance(raw_tools, list): + tools_for_api = raw_tools + + if isinstance(tools_for_api, list): sanitized_tools, changed_count, changes = _sanitize_openai_tools( - request_body["tools"] + tools_for_api ) - request_body["tools"] = sanitized_tools + tools_for_api = sanitized_tools if changed_count and logger.isEnabledFor(logging.INFO): logger.info( "[tools.sanitize] changed=%s total=%s truncate_enabled=%s max_desc_len=%s", @@ -882,13 +955,30 @@ async def request( change.get("new_preview"), ) + effective_kwargs = _build_effective_request_kwargs( + model_config, + call_type=call_type, + overrides=dict(kwargs), + ) + request_body = build_request_body( + model_config=model_config, + messages=messages_for_api, + max_tokens=max_tokens, + tools=tools_for_api, + tool_choice=tool_choice, + internal_to_api=internal_to_api, + transport_state=transport_state, + **effective_kwargs, + ) + try: if cot_compat and logger.isEnabledFor(logging.DEBUG): logger.debug( - "[思维链兼容] enabled=%s type=%s model=%s thinking_enabled=%s tools=%s messages=%s", + "[思维链兼容] enabled=%s type=%s model=%s api_mode=%s thinking_enabled=%s tools=%s messages=%s", cot_compat, call_type, model_config.model_name, + api_mode, getattr(model_config, "thinking_enabled", False), bool(tools), len(messages), @@ -896,19 +986,45 @@ async def request( if logger.isEnabledFor(logging.DEBUG): logger.debug( - "[API请求] type=%s model=%s url=%s max_tokens=%s tools=%s tool_choice=%s messages=%s", + "[API请求] type=%s model=%s api_mode=%s url=%s max_tokens=%s tools=%s tool_choice=%s messages=%s", call_type, model_config.model_name, + api_mode, model_config.api_url, max_tokens, - bool(tools), + bool(tools_for_api), tool_choice, len(messages), ) log_debug_json(logger, "[API请求体]", request_body) - result = await self._request_with_openai(model_config, request_body) - result = self._normalize_result(result) + raw_result = await self._request_with_openai(model_config, request_body) + if api_mode == API_MODE_RESPONSES: + result = normalize_responses_result( + raw_result, + api_to_internal if api_to_internal else None, + ) + response_id = str( + raw_result.get("id") or result.get("id") or "" + ).strip() + if response_id: + choice = result.get("choices", [{}])[0] + message = ( + choice.get("message", {}) if isinstance(choice, dict) else {} + ) + tool_calls = ( + message.get("tool_calls", []) + if isinstance(message, dict) + else [] + ) + result["_transport_state"] = { + "api_mode": api_mode, + "previous_response_id": response_id, + "tool_result_start_index": transport_message_count + + (1 if tool_calls else 0), + } + else: + result = self._normalize_result(raw_result) if api_to_internal: result["_tool_name_map"] = { "api_to_internal": api_to_internal, @@ -1038,6 +1154,12 @@ async def _request_with_openai( self, model_config: ModelConfig, request_body: dict[str, Any] ) -> dict[str, Any]: client = self._get_openai_client_for_model(model_config) + if get_api_mode(model_config) == API_MODE_RESPONSES: + params, extra_body = _split_responses_params(request_body) + if extra_body: + params["extra_body"] = extra_body + response = await client.responses.create(**params) + return self._response_to_dict(response) params, extra_body = _split_chat_completion_params(request_body) if extra_body: params["extra_body"] = extra_body @@ -1236,16 +1358,36 @@ def build_request_body( max_tokens: int, tools: list[dict[str, Any]] | None = None, tool_choice: str = "auto", + internal_to_api: dict[str, str] | None = None, + transport_state: dict[str, Any] | None = None, **kwargs: Any, ) -> dict[str, Any]: """构建 API 请求体。""" + api_mode = get_api_mode(model_config) + extra_kwargs: dict[str, Any] = dict(kwargs) + reasoning_payload = get_reasoning_payload(model_config) + + if api_mode == API_MODE_RESPONSES: + extra_kwargs.pop("thinking", None) + extra_kwargs.pop("reasoning", None) + extra_kwargs.pop("reasoning_effort", None) + return build_responses_request_body( + model_config, + messages, + max_tokens, + tools=tools, + tool_choice=tool_choice, + extra_kwargs=extra_kwargs, + internal_to_api=internal_to_api or {}, + transport_state=transport_state, + ) + body: dict[str, Any] = { "model": model_config.model_name, "messages": messages, "max_tokens": max_tokens, } - extra_kwargs: dict[str, Any] = dict(kwargs) if "thinking" in extra_kwargs: normalized = _normalize_thinking_override( extra_kwargs.get("thinking"), model_config @@ -1255,6 +1397,9 @@ def build_request_body( else: extra_kwargs["thinking"] = normalized + extra_kwargs.pop("reasoning", None) + extra_kwargs.pop("reasoning_effort", None) + if getattr(model_config, "thinking_enabled", False): thinking_param: dict[str, Any] = {"type": "enabled"} if getattr(model_config, "thinking_include_budget", True): @@ -1263,9 +1408,11 @@ def build_request_body( ) body["thinking"] = thinking_param + if reasoning_payload is not None: + body["reasoning"] = reasoning_payload + if tools: body["tools"] = tools - # thinking 模式不支持强制指定 tool_choice（specified），降级为 auto thinking_active = "thinking" in body if thinking_active and isinstance(tool_choice, dict): body["tool_choice"] = "auto" diff --git a/src/Undefined/ai/model_selector.py b/src/Undefined/ai/model_selector.py index d255ca6d..989da9bb 100644 --- a/src/Undefined/ai/model_selector.py +++ b/src/Undefined/ai/model_selector.py @@ -241,10 +241,13 @@ def _entry_to_chat_config( model_name=entry.model_name, max_tokens=entry.max_tokens, queue_interval_seconds=entry.queue_interval_seconds, + api_mode=entry.api_mode, thinking_enabled=entry.thinking_enabled, thinking_budget_tokens=entry.thinking_budget_tokens, thinking_include_budget=entry.thinking_include_budget, thinking_tool_call_compat=entry.thinking_tool_call_compat, + reasoning_enabled=entry.reasoning_enabled, + reasoning_effort=entry.reasoning_effort, request_params=entry.request_params, pool=primary.pool, ) @@ -260,10 +263,13 @@ def _entry_to_agent_config( model_name=entry.model_name, max_tokens=entry.max_tokens, queue_interval_seconds=entry.queue_interval_seconds, + api_mode=entry.api_mode, thinking_enabled=entry.thinking_enabled, thinking_budget_tokens=entry.thinking_budget_tokens, thinking_include_budget=entry.thinking_include_budget, thinking_tool_call_compat=entry.thinking_tool_call_compat, + reasoning_enabled=entry.reasoning_enabled, + reasoning_effort=entry.reasoning_effort, request_params=entry.request_params, pool=primary.pool, ) diff --git a/src/Undefined/ai/parsing.py b/src/Undefined/ai/parsing.py index d76a8edc..b25f26e0 100644 --- a/src/Undefined/ai/parsing.py +++ b/src/Undefined/ai/parsing.py @@ -47,6 +47,13 @@ def _extract_from_choice(choice: Any) -> str: return content or "" +def _extract_output_text(result: dict[str, Any]) -> str: + value = result.get("output_text") + if isinstance(value, str): + return value + return "" + + def _find_first_choice(result: dict[str, Any]) -> dict[str, Any] | None: """在响应中查找第一个选项。 @@ -114,6 +121,10 @@ def extract_choices_content(result: dict[str, Any]) -> str: """ logger.debug(f"提取 choices 内容，响应结构: {list(result.keys())}") + output_text = _extract_output_text(result) + if output_text: + return output_text + # 查找第一个选项 choice = _find_first_choice(result) diff --git a/src/Undefined/ai/transports/__init__.py b/src/Undefined/ai/transports/__init__.py new file mode 100644 index 00000000..9f33ccf8 --- /dev/null +++ b/src/Undefined/ai/transports/__init__.py @@ -0,0 +1,23 @@ +"""LLM transport helpers.""" + +from .openai_transport import ( + API_MODE_CHAT_COMPLETIONS, + API_MODE_RESPONSES, + build_responses_request_body, + get_api_mode, + get_reasoning_payload, + normalize_api_mode, + normalize_reasoning_effort, + normalize_responses_result, +) + +__all__ = [ + "API_MODE_CHAT_COMPLETIONS", + "API_MODE_RESPONSES", + "build_responses_request_body", + "get_api_mode", + "get_reasoning_payload", + "normalize_api_mode", + "normalize_reasoning_effort", + "normalize_responses_result", +] diff --git a/src/Undefined/ai/transports/openai_transport.py b/src/Undefined/ai/transports/openai_transport.py new file mode 100644 index 00000000..70f2b809 --- /dev/null +++ b/src/Undefined/ai/transports/openai_transport.py @@ -0,0 +1,412 @@ +from __future__ import annotations + +import json +from typing import Any + +API_MODE_CHAT_COMPLETIONS = "chat_completions" +API_MODE_RESPONSES = "responses" +_VALID_API_MODES = {API_MODE_CHAT_COMPLETIONS, API_MODE_RESPONSES} +_VALID_REASONING_EFFORTS = {"none", "minimal", "low", "medium", "high", "xhigh"} + + +def normalize_api_mode(value: Any, default: str = API_MODE_CHAT_COMPLETIONS) -> str: + text = str(value or default).strip().lower() + if text not in _VALID_API_MODES: + return default + return text + + +def get_api_mode(model_config: Any) -> str: + return normalize_api_mode( + getattr(model_config, "api_mode", API_MODE_CHAT_COMPLETIONS) + ) + + +def normalize_reasoning_effort(value: Any, default: str = "medium") -> str: + text = str(value or default).strip().lower() + if text not in _VALID_REASONING_EFFORTS: + return default + return text + + +def get_reasoning_payload(model_config: Any) -> dict[str, Any] | None: + if not bool(getattr(model_config, "reasoning_enabled", False)): + return None + return { + "effort": normalize_reasoning_effort( + getattr(model_config, "reasoning_effort", "medium") + ) + } + + +def _stringify_content(value: Any) -> str: + if value is None: + return "" + if isinstance(value, str): + return value + if isinstance(value, list): + chunks: list[str] = [] + for item in value: + if isinstance(item, str): + chunks.append(item) + continue + if not isinstance(item, dict): + continue + item_type = str(item.get("type", "")).strip().lower() + if item_type in { + "text", + "input_text", + "output_text", + "reasoning_text", + "summary_text", + }: + text = item.get("text") + if text is not None: + chunks.append(str(text)) + continue + if item_type == "refusal": + refusal = item.get("refusal") + if refusal is not None: + chunks.append(str(refusal)) + continue + if item_type == "image_url": + image_url = item.get("image_url") or {} + if isinstance(image_url, dict) and image_url.get("url"): + chunks.append(str(image_url.get("url"))) + continue + if item_type.endswith("_url"): + payload = item.get(item_type) or {} + if isinstance(payload, dict) and payload.get("url"): + chunks.append(str(payload.get("url"))) + continue + data = item.get("data") + if isinstance(data, dict) and data.get("text") is not None: + chunks.append(str(data.get("text"))) + return "\n".join(chunk for chunk in chunks if chunk) + if isinstance(value, dict): + if value.get("text") is not None: + return str(value.get("text")) + if value.get("content") is not None: + return _stringify_content(value.get("content")) + return json.dumps(value, ensure_ascii=False, default=str) + return str(value) + + +def _content_to_response_parts(content: Any) -> list[dict[str, Any]]: + if isinstance(content, str): + return [{"type": "input_text", "text": content}] + if not isinstance(content, list): + text = _stringify_content(content) + return [{"type": "input_text", "text": text}] if text else [] + + parts: list[dict[str, Any]] = [] + for item in content: + if isinstance(item, str): + if item: + parts.append({"type": "input_text", "text": item}) + continue + if not isinstance(item, dict): + continue + item_type = str(item.get("type", "")).strip().lower() + if item_type in {"text", "input_text"}: + text_value: Any | None = item.get("text") + if text_value is None: + data = item.get("data") + if isinstance(data, dict): + text_value = data.get("text") + if text_value is not None: + parts.append({"type": "input_text", "text": str(text_value)}) + continue + if item_type == "image_url": + image = item.get("image_url") or {} + if isinstance(image, dict) and image.get("url"): + parts.append( + { + "type": "input_image", + "image_url": str(image.get("url")), + "detail": str(image.get("detail") or "auto"), + } + ) + continue + if item_type.endswith("_url"): + image = item.get(item_type) or {} + if isinstance(image, dict) and image.get("url"): + parts.append( + { + "type": "input_image", + "image_url": str(image.get("url")), + "detail": str(image.get("detail") or "auto"), + } + ) + continue + if item_type == "input_image": + image_url = item.get("image_url") + if image_url: + parts.append( + { + "type": "input_image", + "image_url": str(image_url), + "detail": str(item.get("detail") or "auto"), + } + ) + continue + text = _stringify_content(item) + if text: + parts.append({"type": "input_text", "text": text}) + return parts + + +def _message_to_responses_input( + message: dict[str, Any], + internal_to_api: dict[str, str], +) -> list[dict[str, Any]]: + role = str(message.get("role", "")).strip().lower() + if not role: + return [] + + if role == "tool": + tool_call_id = str(message.get("tool_call_id", "")).strip() + if not tool_call_id: + return [] + return [ + { + "type": "function_call_output", + "call_id": tool_call_id, + "output": _stringify_content(message.get("content")), + } + ] + + items: list[dict[str, Any]] = [] + content_parts = _content_to_response_parts(message.get("content")) + if role in {"user", "assistant", "system", "developer"} and content_parts: + items.append( + { + "type": "message", + "role": role, + "content": content_parts, + } + ) + + if role == "assistant": + tool_calls = message.get("tool_calls") + if isinstance(tool_calls, list): + for tool_call in tool_calls: + if not isinstance(tool_call, dict): + continue + function = tool_call.get("function") or {} + if not isinstance(function, dict): + continue + name = str(function.get("name", "")).strip() + if not name: + continue + api_name = internal_to_api.get(name, name) + call_id = str( + tool_call.get("id") or tool_call.get("call_id") or "" + ).strip() + if not call_id: + continue + items.append( + { + "type": "function_call", + "call_id": call_id, + "name": api_name, + "arguments": str(function.get("arguments", "{}")), + } + ) + return items + + +def _messages_to_instruction_text(messages: list[dict[str, Any]]) -> str: + lines: list[str] = [] + for message in messages: + role = str(message.get("role", "")).strip().lower() + if role not in {"system", "developer"}: + continue + text = _stringify_content(message.get("content")) + if text: + lines.append(text) + return "\n\n".join(line for line in lines if line).strip() + + +def _messages_to_responses_input( + messages: list[dict[str, Any]], + internal_to_api: dict[str, str], + *, + include_system: bool, +) -> list[dict[str, Any]]: + items: list[dict[str, Any]] = [] + for message in messages: + role = str(message.get("role", "")).strip().lower() + if not include_system and role in {"system", "developer"}: + continue + if ( + not include_system + and role == "assistant" + and not message.get("content") + and not message.get("tool_calls") + ): + continue + items.extend(_message_to_responses_input(message, internal_to_api)) + return items + + +def _normalize_responses_tool_choice(tool_choice: Any) -> Any: + if not isinstance(tool_choice, dict): + return tool_choice + choice_type = str(tool_choice.get("type", "")).strip().lower() + if choice_type == "function": + function = tool_choice.get("function") + if isinstance(function, dict): + name = str(function.get("name", "")).strip() + if name: + return {"type": "function", "name": name} + return tool_choice + + +def build_responses_request_body( + model_config: Any, + messages: list[dict[str, Any]], + max_tokens: int, + *, + tools: list[dict[str, Any]] | None, + tool_choice: Any, + extra_kwargs: dict[str, Any], + internal_to_api: dict[str, str], + transport_state: dict[str, Any] | None, +) -> dict[str, Any]: + body: dict[str, Any] = { + "model": getattr(model_config, "model_name"), + "max_output_tokens": max_tokens, + } + reasoning = get_reasoning_payload(model_config) + if reasoning is not None: + body["reasoning"] = reasoning + if tools: + body["tools"] = tools + body["tool_choice"] = _normalize_responses_tool_choice(tool_choice) + + previous_response_id = "" + start_index = 0 + if isinstance(transport_state, dict): + previous_response_id = str( + transport_state.get("previous_response_id") or "" + ).strip() + try: + start_index = int(transport_state.get("tool_result_start_index") or 0) + except Exception: + start_index = 0 + if start_index < 0: + start_index = 0 + + if previous_response_id: + body["previous_response_id"] = previous_response_id + body["input"] = _messages_to_responses_input( + messages[start_index:], internal_to_api, include_system=True + ) + else: + instructions = _messages_to_instruction_text(messages) + if instructions: + body["instructions"] = instructions + body["input"] = _messages_to_responses_input( + messages, internal_to_api, include_system=False + ) + + body.update(extra_kwargs) + return body + + +def _collect_reasoning_text(output: list[dict[str, Any]]) -> str: + chunks: list[str] = [] + for item in output: + if not isinstance(item, dict) or item.get("type") != "reasoning": + continue + content = item.get("content") + if isinstance(content, list): + for part in content: + if not isinstance(part, dict): + continue + if part.get("type") == "reasoning_text" and part.get("text"): + chunks.append(str(part.get("text"))) + summary = item.get("summary") + if isinstance(summary, list): + for part in summary: + if not isinstance(part, dict): + continue + if part.get("type") == "summary_text" and part.get("text"): + chunks.append(str(part.get("text"))) + return "\n".join(chunk for chunk in chunks if chunk).strip() + + +def normalize_responses_result( + result: dict[str, Any], + api_to_internal: dict[str, str] | None = None, +) -> dict[str, Any]: + normalized = dict(result) + output_raw = result.get("output") + output = output_raw if isinstance(output_raw, list) else [] + + assistant_texts: list[str] = [] + tool_calls: list[dict[str, Any]] = [] + for item in output: + if not isinstance(item, dict): + continue + item_type = str(item.get("type", "")).strip().lower() + if ( + item_type == "message" + and str(item.get("role", "")).strip().lower() == "assistant" + ): + content = item.get("content") + if isinstance(content, list): + for part in content: + if not isinstance(part, dict): + continue + part_type = str(part.get("type", "")).strip().lower() + if part_type == "output_text" and part.get("text") is not None: + assistant_texts.append(str(part.get("text"))) + elif part_type == "refusal" and part.get("refusal") is not None: + assistant_texts.append(str(part.get("refusal"))) + elif item_type == "function_call": + function_name = str(item.get("name", "")).strip() + if api_to_internal: + function_name = api_to_internal.get(function_name, function_name) + call_id = str(item.get("call_id") or item.get("id") or "").strip() + if not function_name or not call_id: + continue + tool_calls.append( + { + "id": call_id, + "type": "function", + "function": { + "name": function_name, + "arguments": str(item.get("arguments", "{}")), + }, + } + ) + + message: dict[str, Any] = { + "role": "assistant", + "content": "\n".join(text for text in assistant_texts if text).strip(), + } + reasoning_content = _collect_reasoning_text(output) + if reasoning_content: + message["reasoning_content"] = reasoning_content + if tool_calls: + message["tool_calls"] = tool_calls + + normalized["choices"] = [ + { + "index": 0, + "message": message, + "finish_reason": "tool_calls" if tool_calls else "stop", + } + ] + + usage = result.get("usage") + if isinstance(usage, dict): + normalized["usage"] = { + "prompt_tokens": int(usage.get("input_tokens", 0) or 0), + "completion_tokens": int(usage.get("output_tokens", 0) or 0), + "total_tokens": int(usage.get("total_tokens", 0) or 0), + } + + return normalized diff --git a/src/Undefined/api/app.py b/src/Undefined/api/app.py index 30192a81..3cf11c45 100644 --- a/src/Undefined/api/app.py +++ b/src/Undefined/api/app.py @@ -523,7 +523,13 @@ async def _internal_probe_handler(self, request: web.Request) -> Response: models_info[label] = { "model_name": getattr(mcfg, "model_name", ""), "api_url": _mask_url(getattr(mcfg, "api_url", "")), + "api_mode": getattr(mcfg, "api_mode", "chat_completions"), "thinking_enabled": getattr(mcfg, "thinking_enabled", False), + "thinking_tool_call_compat": getattr( + mcfg, "thinking_tool_call_compat", True + ), + "reasoning_enabled": getattr(mcfg, "reasoning_enabled", False), + "reasoning_effort": getattr(mcfg, "reasoning_effort", "medium"), } for label in ("embedding_model", "rerank_model"): mcfg = getattr(cfg, label, None) diff --git a/src/Undefined/cognitive/historian.py b/src/Undefined/cognitive/historian.py index 105873ec..eb32ca77 100644 --- a/src/Undefined/cognitive/historian.py +++ b/src/Undefined/cognitive/historian.py @@ -858,6 +858,7 @@ async def _merge_profile_target( tools = [_READ_PROFILE_TOOL, _PROFILE_TOOL] result = False max_turns = 100 + transport_state: dict[str, Any] | None = None for turn in range(max_turns): response = await self._ai_client.submit_background_llm_call( @@ -866,6 +867,14 @@ async def _merge_profile_target( tools=tools, tool_choice="auto", call_type="historian_profile_merge", + transport_state=transport_state, + ) + + next_transport_state = ( + response.get("_transport_state") if isinstance(response, dict) else None + ) + transport_state = ( + next_transport_state if isinstance(next_transport_state, dict) else None ) choices = response.get("choices") or [] diff --git a/src/Undefined/config/loader.py b/src/Undefined/config/loader.py index c9081497..85431446 100644 --- a/src/Undefined/config/loader.py +++ b/src/Undefined/config/loader.py @@ -255,6 +255,10 @@ def _get_value( return None +_VALID_API_MODES = {"chat_completions", "responses"} +_VALID_REASONING_EFFORTS = {"none", "minimal", "low", "medium", "high", "xhigh"} + + def _resolve_thinking_compat_flags( data: dict[str, Any], model_name: str, @@ -280,7 +284,7 @@ def _resolve_thinking_compat_flags( ) include_budget_default = True - tool_call_compat_default = False + tool_call_compat_default = True if legacy_value is not None: legacy_enabled = _coerce_bool(legacy_value, False) include_budget_default = not legacy_enabled @@ -292,6 +296,26 @@ def _resolve_thinking_compat_flags( ) +def _resolve_api_mode( + data: dict[str, Any], + model_name: str, + env_key: str, + default: str = "chat_completions", +) -> str: + raw_value = _get_value(data, ("models", model_name, "api_mode"), env_key) + value = _coerce_str(raw_value, default).strip().lower() + if value not in _VALID_API_MODES: + return default + return value + + +def _resolve_reasoning_effort(value: Any, default: str = "medium") -> str: + effort = _coerce_str(value, default).strip().lower() + if effort not in _VALID_REASONING_EFFORTS: + return default + return effort + + def load_local_admins() -> list[int]: """从本地配置文件加载动态管理员列表""" if not LOCAL_CONFIG_PATH.exists(): @@ -1510,6 +1534,16 @@ def _parse_model_pool( item.get("queue_interval_seconds"), primary_config.queue_interval_seconds, ), + api_mode=( + _coerce_str(item.get("api_mode"), primary_config.api_mode) + .strip() + .lower() + ) + if _coerce_str(item.get("api_mode"), primary_config.api_mode) + .strip() + .lower() + in _VALID_API_MODES + else primary_config.api_mode, thinking_enabled=_coerce_bool( item.get("thinking_enabled"), primary_config.thinking_enabled ), @@ -1525,6 +1559,14 @@ def _parse_model_pool( item.get("thinking_tool_call_compat"), primary_config.thinking_tool_call_compat, ), + reasoning_enabled=_coerce_bool( + item.get("reasoning_enabled"), + primary_config.reasoning_enabled, + ), + reasoning_effort=_resolve_reasoning_effort( + item.get("reasoning_effort"), + primary_config.reasoning_effort, + ), request_params=merge_request_params( primary_config.request_params, item.get("request_params"), @@ -1630,6 +1672,23 @@ def _parse_chat_model_config(data: dict[str, Any]) -> ChatModelConfig: legacy_env_key="CHAT_MODEL_DEEPSEEK_NEW_COT_SUPPORT", ) ) + api_mode = _resolve_api_mode(data, "chat", "CHAT_MODEL_API_MODE") + reasoning_enabled = _coerce_bool( + _get_value( + data, + ("models", "chat", "reasoning_enabled"), + "CHAT_MODEL_REASONING_ENABLED", + ), + False, + ) + reasoning_effort = _resolve_reasoning_effort( + _get_value( + data, + ("models", "chat", "reasoning_effort"), + "CHAT_MODEL_REASONING_EFFORT", + ), + "medium", + ) config = ChatModelConfig( api_url=_coerce_str( _get_value(data, ("models", "chat", "api_url"), "CHAT_MODEL_API_URL"), @@ -1650,6 +1709,7 @@ def _parse_chat_model_config(data: dict[str, Any]) -> ChatModelConfig: 8192, ), queue_interval_seconds=queue_interval_seconds, + api_mode=api_mode, thinking_enabled=_coerce_bool( _get_value( data, @@ -1668,6 +1728,8 @@ def _parse_chat_model_config(data: dict[str, Any]) -> ChatModelConfig: ), thinking_include_budget=thinking_include_budget, thinking_tool_call_compat=thinking_tool_call_compat, + reasoning_enabled=reasoning_enabled, + reasoning_effort=reasoning_effort, request_params=_get_model_request_params(data, "chat"), ) config.pool = Config._parse_model_pool(data, "chat", config) @@ -1694,6 +1756,23 @@ def _parse_vision_model_config(data: dict[str, Any]) -> VisionModelConfig: legacy_env_key="VISION_MODEL_DEEPSEEK_NEW_COT_SUPPORT", ) ) + api_mode = _resolve_api_mode(data, "vision", "VISION_MODEL_API_MODE") + reasoning_enabled = _coerce_bool( + _get_value( + data, + ("models", "vision", "reasoning_enabled"), + "VISION_MODEL_REASONING_ENABLED", + ), + False, + ) + reasoning_effort = _resolve_reasoning_effort( + _get_value( + data, + ("models", "vision", "reasoning_effort"), + "VISION_MODEL_REASONING_EFFORT", + ), + "medium", + ) return VisionModelConfig( api_url=_coerce_str( _get_value( @@ -1714,6 +1793,7 @@ def _parse_vision_model_config(data: dict[str, Any]) -> VisionModelConfig: "", ), queue_interval_seconds=queue_interval_seconds, + api_mode=api_mode, thinking_enabled=_coerce_bool( _get_value( data, @@ -1732,6 +1812,8 @@ def _parse_vision_model_config(data: dict[str, Any]) -> VisionModelConfig: ), thinking_include_budget=thinking_include_budget, thinking_tool_call_compat=thinking_tool_call_compat, + reasoning_enabled=reasoning_enabled, + reasoning_effort=reasoning_effort, request_params=_get_model_request_params(data, "vision"), ) @@ -1777,6 +1859,23 @@ def _parse_security_model_config( legacy_env_key="SECURITY_MODEL_DEEPSEEK_NEW_COT_SUPPORT", ) ) + api_mode = _resolve_api_mode(data, "security", "SECURITY_MODEL_API_MODE") + reasoning_enabled = _coerce_bool( + _get_value( + data, + ("models", "security", "reasoning_enabled"), + "SECURITY_MODEL_REASONING_ENABLED", + ), + False, + ) + reasoning_effort = _resolve_reasoning_effort( + _get_value( + data, + ("models", "security", "reasoning_effort"), + "SECURITY_MODEL_REASONING_EFFORT", + ), + "medium", + ) if api_url and api_key and model_name: return SecurityModelConfig( @@ -1792,6 +1891,7 @@ def _parse_security_model_config( 100, ), queue_interval_seconds=queue_interval_seconds, + api_mode=api_mode, thinking_enabled=_coerce_bool( _get_value( data, @@ -1810,6 +1910,8 @@ def _parse_security_model_config( ), thinking_include_budget=thinking_include_budget, thinking_tool_call_compat=thinking_tool_call_compat, + reasoning_enabled=reasoning_enabled, + reasoning_effort=reasoning_effort, request_params=_get_model_request_params(data, "security"), ) @@ -1820,10 +1922,13 @@ def _parse_security_model_config( model_name=chat_model.model_name, max_tokens=chat_model.max_tokens, queue_interval_seconds=chat_model.queue_interval_seconds, + api_mode=chat_model.api_mode, thinking_enabled=False, thinking_budget_tokens=0, thinking_include_budget=True, - thinking_tool_call_compat=False, + thinking_tool_call_compat=chat_model.thinking_tool_call_compat, + reasoning_enabled=chat_model.reasoning_enabled, + reasoning_effort=chat_model.reasoning_effort, request_params=merge_request_params(chat_model.request_params), ) @@ -1848,6 +1953,23 @@ def _parse_agent_model_config(data: dict[str, Any]) -> AgentModelConfig: legacy_env_key="AGENT_MODEL_DEEPSEEK_NEW_COT_SUPPORT", ) ) + api_mode = _resolve_api_mode(data, "agent", "AGENT_MODEL_API_MODE") + reasoning_enabled = _coerce_bool( + _get_value( + data, + ("models", "agent", "reasoning_enabled"), + "AGENT_MODEL_REASONING_ENABLED", + ), + False, + ) + reasoning_effort = _resolve_reasoning_effort( + _get_value( + data, + ("models", "agent", "reasoning_effort"), + "AGENT_MODEL_REASONING_EFFORT", + ), + "medium", + ) config = AgentModelConfig( api_url=_coerce_str( _get_value(data, ("models", "agent", "api_url"), "AGENT_MODEL_API_URL"), @@ -1868,6 +1990,7 @@ def _parse_agent_model_config(data: dict[str, Any]) -> AgentModelConfig: 4096, ), queue_interval_seconds=queue_interval_seconds, + api_mode=api_mode, thinking_enabled=_coerce_bool( _get_value( data, @@ -1886,6 +2009,8 @@ def _parse_agent_model_config(data: dict[str, Any]) -> AgentModelConfig: ), thinking_include_budget=thinking_include_budget, thinking_tool_call_compat=thinking_tool_call_compat, + reasoning_enabled=reasoning_enabled, + reasoning_effort=reasoning_effort, request_params=_get_model_request_params(data, "agent"), ) config.pool = Config._parse_model_pool(data, "agent", config) @@ -1968,12 +2093,15 @@ def _log_debug_info( ] for name, cfg in configs: logger.debug( - "[配置] %s_model=%s api_url=%s api_key_set=%s thinking=%s cot_compat=%s", + "[配置] %s_model=%s api_url=%s api_key_set=%s api_mode=%s thinking=%s reasoning=%s/%s cot_compat=%s", name, cfg.model_name, cfg.api_url, bool(cfg.api_key), + getattr(cfg, "api_mode", "chat_completions"), cfg.thinking_enabled, + getattr(cfg, "reasoning_enabled", False), + getattr(cfg, "reasoning_effort", "medium"), getattr(cfg, "thinking_tool_call_compat", False), ) @@ -2020,12 +2148,19 @@ def _parse_historian_model_config( legacy_env_key="HISTORIAN_MODEL_DEEPSEEK_NEW_COT_SUPPORT", ) ) + api_mode = _resolve_api_mode( + {"models": {"historian": h}}, + "historian", + "HISTORIAN_MODEL_API_MODE", + fallback.api_mode, + ) return AgentModelConfig( api_url=_coerce_str(h.get("api_url"), fallback.api_url), api_key=_coerce_str(h.get("api_key"), fallback.api_key), model_name=_coerce_str(h.get("model_name"), fallback.model_name), max_tokens=_coerce_int(h.get("max_tokens"), fallback.max_tokens), queue_interval_seconds=queue_interval_seconds, + api_mode=api_mode, thinking_enabled=_coerce_bool( h.get("thinking_enabled"), fallback.thinking_enabled ), @@ -2034,6 +2169,22 @@ def _parse_historian_model_config( ), thinking_include_budget=thinking_include_budget, thinking_tool_call_compat=thinking_tool_call_compat, + reasoning_enabled=_coerce_bool( + _get_value( + {"models": {"historian": h}}, + ("models", "historian", "reasoning_enabled"), + "HISTORIAN_MODEL_REASONING_ENABLED", + ), + fallback.reasoning_enabled, + ), + reasoning_effort=_resolve_reasoning_effort( + _get_value( + {"models": {"historian": h}}, + ("models", "historian", "reasoning_effort"), + "HISTORIAN_MODEL_REASONING_EFFORT", + ), + fallback.reasoning_effort, + ), request_params=merge_request_params( fallback.request_params, h.get("request_params"), diff --git a/src/Undefined/config/models.py b/src/Undefined/config/models.py index 0f0992e0..7269c70b 100644 --- a/src/Undefined/config/models.py +++ b/src/Undefined/config/models.py @@ -15,10 +15,13 @@ class ModelPoolEntry: model_name: str max_tokens: int queue_interval_seconds: float = 1.0 + api_mode: str = "chat_completions" thinking_enabled: bool = False thinking_budget_tokens: int = 0 thinking_include_budget: bool = True - thinking_tool_call_compat: bool = False + thinking_tool_call_compat: bool = True + reasoning_enabled: bool = False + reasoning_effort: str = "medium" request_params: dict[str, Any] = field(default_factory=dict) @@ -40,12 +43,15 @@ class ChatModelConfig: model_name: str max_tokens: int queue_interval_seconds: float = 1.0 + api_mode: str = "chat_completions" # 请求 API 模式 thinking_enabled: bool = False # 是否启用 thinking thinking_budget_tokens: int = 20000 # 思维预算 token 数量 thinking_include_budget: bool = True # 是否在请求中发送 budget_tokens thinking_tool_call_compat: bool = ( - False # 思维链 + 工具调用兼容（回传 reasoning_content） + True # 思维链 + 工具调用兼容（回传 reasoning_content） ) + reasoning_enabled: bool = False # 是否启用 reasoning.effort + reasoning_effort: str = "medium" # reasoning effort 档位 request_params: dict[str, Any] = field(default_factory=dict) pool: ModelPool | None = None # 模型池配置 @@ -58,12 +64,15 @@ class VisionModelConfig: api_key: str model_name: str queue_interval_seconds: float = 1.0 + api_mode: str = "chat_completions" # 请求 API 模式 thinking_enabled: bool = False # 是否启用 thinking thinking_budget_tokens: int = 20000 # 思维预算 token 数量 thinking_include_budget: bool = True # 是否在请求中发送 budget_tokens thinking_tool_call_compat: bool = ( - False # 思维链 + 工具调用兼容（回传 reasoning_content） + True # 思维链 + 工具调用兼容（回传 reasoning_content） ) + reasoning_enabled: bool = False # 是否启用 reasoning.effort + reasoning_effort: str = "medium" # reasoning effort 档位 request_params: dict[str, Any] = field(default_factory=dict) @@ -76,12 +85,15 @@ class SecurityModelConfig: model_name: str max_tokens: int queue_interval_seconds: float = 1.0 + api_mode: str = "chat_completions" # 请求 API 模式 thinking_enabled: bool = False # 是否启用 thinking thinking_budget_tokens: int = 0 # 思维预算 token 数量 thinking_include_budget: bool = True # 是否在请求中发送 budget_tokens thinking_tool_call_compat: bool = ( - False # 思维链 + 工具调用兼容（回传 reasoning_content） + True # 思维链 + 工具调用兼容（回传 reasoning_content） ) + reasoning_enabled: bool = False # 是否启用 reasoning.effort + reasoning_effort: str = "medium" # reasoning effort 档位 request_params: dict[str, Any] = field(default_factory=dict) @@ -120,12 +132,15 @@ class AgentModelConfig: model_name: str max_tokens: int = 4096 queue_interval_seconds: float = 1.0 + api_mode: str = "chat_completions" # 请求 API 模式 thinking_enabled: bool = False # 是否启用 thinking thinking_budget_tokens: int = 0 # 思维预算 token 数量 thinking_include_budget: bool = True # 是否在请求中发送 budget_tokens thinking_tool_call_compat: bool = ( - False # 思维链 + 工具调用兼容（回传 reasoning_content） + True # 思维链 + 工具调用兼容（回传 reasoning_content） ) + reasoning_enabled: bool = False # 是否启用 reasoning.effort + reasoning_effort: str = "medium" # reasoning effort 档位 request_params: dict[str, Any] = field(default_factory=dict) pool: ModelPool | None = None # 模型池配置 diff --git a/src/Undefined/injection_response_agent.py b/src/Undefined/injection_response_agent.py index 25df1420..f0f4e796 100644 --- a/src/Undefined/injection_response_agent.py +++ b/src/Undefined/injection_response_agent.py @@ -8,6 +8,7 @@ from typing import Any from Undefined.ai.llm import ModelRequester +from Undefined.ai.transports import API_MODE_CHAT_COMPLETIONS, get_api_mode from Undefined.ai.parsing import extract_choices_content from Undefined.config import SecurityModelConfig from Undefined.utils.resources import read_text_resource @@ -58,7 +59,10 @@ async def generate_response(self, user_message: str) -> str: start_time = time.perf_counter() try: request_kwargs: dict[str, Any] = {"temperature": 0.7} - if not self.security_config.thinking_enabled: + if ( + get_api_mode(self.security_config) == API_MODE_CHAT_COMPLETIONS + and not self.security_config.thinking_enabled + ): request_kwargs["thinking"] = {"enabled": False, "budget_tokens": 0} result = await self._requester.request( diff --git a/src/Undefined/services/ai_coordinator.py b/src/Undefined/services/ai_coordinator.py index 1493f163..3ddd78a6 100644 --- a/src/Undefined/services/ai_coordinator.py +++ b/src/Undefined/services/ai_coordinator.py @@ -516,6 +516,7 @@ async def _execute_background_llm_call(self, request: dict[str, Any]) -> None: call_type=request.get("call_type", "background"), max_tokens=request.get("max_tokens") or getattr(request["model_config"], "max_tokens", 4096), + transport_state=request.get("transport_state"), ) self.ai.set_llm_call_result(request_id, result) except Exception as exc: diff --git a/src/Undefined/services/security.py b/src/Undefined/services/security.py index 2d993f0e..50857fd3 100644 --- a/src/Undefined/services/security.py +++ b/src/Undefined/services/security.py @@ -8,6 +8,7 @@ from Undefined.injection_response_agent import InjectionResponseAgent from Undefined.token_usage_storage import TokenUsageStorage from Undefined.ai.llm import ModelRequester +from Undefined.ai.transports import API_MODE_CHAT_COMPLETIONS, get_api_mode from Undefined.ai.parsing import extract_choices_content from Undefined.utils.resources import read_text_resource from Undefined.utils.xml import escape_xml_text, escape_xml_attr @@ -103,7 +104,10 @@ async def detect_injection( # 使用安全模型配置进行注入检测 security_config = self.config.security_model request_kwargs: dict[str, Any] = {} - if not security_config.thinking_enabled: + if ( + get_api_mode(security_config) == API_MODE_CHAT_COMPLETIONS + and not security_config.thinking_enabled + ): request_kwargs["thinking"] = {"enabled": False, "budget_tokens": 0} result = await self._requester.request( diff --git a/src/Undefined/skills/agents/README.md b/src/Undefined/skills/agents/README.md index 96793af3..f04880d0 100644 --- a/src/Undefined/skills/agents/README.md +++ b/src/Undefined/skills/agents/README.md @@ -31,12 +31,21 @@ agent_name/ [models.agent] api_url = "https://api.openai.com/v1" api_key = "..." -model = "gpt-4o-mini" +model_name = "gpt-4o-mini" max_tokens = 4096 +api_mode = "chat_completions" +reasoning_enabled = false +reasoning_effort = "medium" thinking_enabled = false thinking_budget_tokens = 0 +thinking_tool_call_compat = true ``` +说明： +- `api_mode = "chat_completions"` 时，旧 `thinking_*` 仍按原逻辑生效；若开启 `reasoning_enabled`，也会额外发送 `reasoning.effort`。 +- `api_mode = "responses"` 时，Agent 的多轮工具调用会自动使用 `previous_response_id + function_call_output` 续轮；旧 `thinking_*` 不会发到 `responses`。 +- `thinking_tool_call_compat` 默认 `true`，会把 `reasoning_content` 回填到本地消息历史，便于日志、回放和兼容读取。 + 兼容的环境变量（会覆盖 `config.toml`）： ```env @@ -44,8 +53,12 @@ AGENT_MODEL_API_URL= AGENT_MODEL_API_KEY= AGENT_MODEL_NAME= AGENT_MODEL_MAX_TOKENS=4096 +AGENT_MODEL_API_MODE=chat_completions +AGENT_MODEL_REASONING_ENABLED=false +AGENT_MODEL_REASONING_EFFORT=medium AGENT_MODEL_THINKING_ENABLED=false AGENT_MODEL_THINKING_BUDGET_TOKENS=0 +AGENT_MODEL_THINKING_TOOL_CALL_COMPAT=true ``` ## 介绍自动生成（推荐） diff --git a/src/Undefined/skills/agents/runner.py b/src/Undefined/skills/agents/runner.py index e9743bc9..7f5fcf82 100644 --- a/src/Undefined/skills/agents/runner.py +++ b/src/Undefined/skills/agents/runner.py @@ -102,6 +102,7 @@ async def run_agent_with_tools( if agent_history: messages.extend(agent_history) messages.append({"role": "user", "content": user_content}) + transport_state: dict[str, Any] | None = None for iteration in range(1, max_iterations + 1): logger.debug("[Agent:%s] iteration=%s", agent_name, iteration) @@ -113,6 +114,7 @@ async def run_agent_with_tools( call_type=f"agent:{agent_name}", tools=tools if tools else None, tool_choice="auto", + transport_state=transport_state, ) tool_name_map = ( @@ -127,6 +129,13 @@ async def run_agent_with_tools( for key, value in raw_api_to_internal.items() } + next_transport_state = ( + result.get("_transport_state") if isinstance(result, dict) else None + ) + transport_state = ( + next_transport_state if isinstance(next_transport_state, dict) else None + ) + choice: dict[str, Any] = result.get("choices", [{}])[0] message: dict[str, Any] = choice.get("message", {}) content: str = message.get("content") or "" diff --git a/src/Undefined/webui/static/js/config-form.js b/src/Undefined/webui/static/js/config-form.js index 3260f9eb..6fef53b8 100644 --- a/src/Undefined/webui/static/js/config-form.js +++ b/src/Undefined/webui/static/js/config-form.js @@ -219,6 +219,16 @@ function isLongText(value) { return typeof value === "string" && (value.length > 80 || value.includes("\n")); } +const FIELD_SELECT_OPTIONS = { + api_mode: ["chat_completions", "responses"], + reasoning_effort: ["none", "minimal", "low", "medium", "high", "xhigh"], +} + +function getFieldSelectOptions(path) { + const key = path.split(".").pop() + return FIELD_SELECT_OPTIONS[key] || null +} + function createField(path, val) { const group = document.createElement("div"); group.className = "form-group"; @@ -264,8 +274,20 @@ function createField(path, val) { const isArray = Array.isArray(val); const isNumber = typeof val === "number"; const isSecret = isSensitiveKey(path); + const selectOptions = getFieldSelectOptions(path); - if (isLongText(val)) { + if (selectOptions) { + input = document.createElement("select"); + input.className = "form-control config-input"; + input.dataset.valueType = "string"; + selectOptions.forEach(optionValue => { + const option = document.createElement("option"); + option.value = optionValue; + option.innerText = optionValue; + option.selected = String(val ?? "") === optionValue; + input.appendChild(option); + }); + } else if (isLongText(val)) { input = document.createElement("textarea"); input.className = "form-control form-textarea config-input"; input.value = val || ""; @@ -293,7 +315,11 @@ function createField(path, val) { input.dataset.path = path; group.appendChild(input); - input.oninput = () => scheduleAutoSave(); + if (selectOptions) { + input.onchange = () => autoSave(); + } else { + input.oninput = () => scheduleAutoSave(); + } } return group; } @@ -732,12 +758,26 @@ function createAotEntry(path, entry) { function buildAotTemplate(path, arr) { if (arr && arr.length > 0) { const template = buildEmptyStructuredValue(arr[0]) - if (AOT_PATHS.has(path) && !Object.prototype.hasOwnProperty.call(template, "request_params")) { - template.request_params = {} + if (AOT_PATHS.has(path)) { + if (!Object.prototype.hasOwnProperty.call(template, "request_params")) { + template.request_params = {} + } + if (!Object.prototype.hasOwnProperty.call(template, "api_mode")) { + template.api_mode = "chat_completions" + } + if (!Object.prototype.hasOwnProperty.call(template, "thinking_tool_call_compat")) { + template.thinking_tool_call_compat = true + } + if (!Object.prototype.hasOwnProperty.call(template, "reasoning_enabled")) { + template.reasoning_enabled = false + } + if (!Object.prototype.hasOwnProperty.call(template, "reasoning_effort")) { + template.reasoning_effort = "medium" + } } return template } - return { model_name: "", api_url: "", api_key: "", request_params: {} } + return { model_name: "", api_url: "", api_key: "", api_mode: "chat_completions", thinking_tool_call_compat: true, reasoning_enabled: false, reasoning_effort: "medium", request_params: {} } } function createAotWidget(path, arr) { diff --git a/tests/test_config_request_params.py b/tests/test_config_request_params.py index f52384ac..c36afde8 100644 --- a/tests/test_config_request_params.py +++ b/tests/test_config_request_params.py @@ -10,7 +10,9 @@ def _load_config(path: Path, text: str) -> Config: return Config.load(path, strict=False) -def test_model_request_params_load_and_inherit(tmp_path: Path) -> None: +def test_model_request_params_load_inherit_and_new_transport_fields( + tmp_path: Path, +) -> None: cfg = _load_config( tmp_path / "config.toml", """ @@ -21,6 +23,9 @@ def test_model_request_params_load_and_inherit(tmp_path: Path) -> None: api_url = "https://api.openai.com/v1" api_key = "sk-chat" model_name = "gpt-chat" +api_mode = "responses" +reasoning_enabled = true +reasoning_effort = "high" [models.chat.request_params] temperature = 0.2 @@ -34,6 +39,9 @@ def test_model_request_params_load_and_inherit(tmp_path: Path) -> None: model_name = "gpt-chat-b" api_url = "https://pool.example/v1" api_key = "sk-pool" +api_mode = "chat_completions" +reasoning_enabled = false +reasoning_effort = "low" [models.chat.pool.models.request_params] temperature = 0.6 @@ -43,6 +51,9 @@ def test_model_request_params_load_and_inherit(tmp_path: Path) -> None: api_url = "https://api.openai.com/v1" api_key = "sk-agent" model_name = "gpt-agent" +api_mode = "responses" +reasoning_enabled = true +reasoning_effort = "minimal" [models.agent.request_params] temperature = 0.3 @@ -51,6 +62,8 @@ def test_model_request_params_load_and_inherit(tmp_path: Path) -> None: [models.historian] model_name = "gpt-historian" +api_mode = "chat_completions" +reasoning_effort = "xhigh" [models.historian.request_params] temperature = 0.1 @@ -75,22 +88,47 @@ def test_model_request_params_load_and_inherit(tmp_path: Path) -> None: """, ) + assert cfg.chat_model.api_mode == "responses" + assert cfg.chat_model.reasoning_enabled is True + assert cfg.chat_model.reasoning_effort == "high" + assert cfg.chat_model.thinking_tool_call_compat is True assert cfg.chat_model.request_params == { "temperature": 0.2, "metadata": {"source": "chat"}, } + assert cfg.chat_model.pool is not None + assert cfg.chat_model.pool.models[0].api_mode == "chat_completions" + assert cfg.chat_model.pool.models[0].reasoning_enabled is False + assert cfg.chat_model.pool.models[0].reasoning_effort == "low" + assert cfg.chat_model.pool.models[0].thinking_tool_call_compat is True assert cfg.chat_model.pool.models[0].request_params == { "temperature": 0.6, "metadata": {"source": "chat"}, "provider": {"name": "pool"}, } + + assert cfg.security_model.api_mode == cfg.chat_model.api_mode + assert cfg.security_model.reasoning_enabled == cfg.chat_model.reasoning_enabled + assert cfg.security_model.reasoning_effort == cfg.chat_model.reasoning_effort + assert cfg.security_model.thinking_tool_call_compat is True assert cfg.security_model.request_params == cfg.chat_model.request_params + + assert cfg.agent_model.api_mode == "responses" + assert cfg.agent_model.reasoning_enabled is True + assert cfg.agent_model.reasoning_effort == "minimal" + assert cfg.agent_model.thinking_tool_call_compat is True + + assert cfg.historian_model.api_mode == "chat_completions" + assert cfg.historian_model.reasoning_enabled is True + assert cfg.historian_model.reasoning_effort == "xhigh" + assert cfg.historian_model.thinking_tool_call_compat is True assert cfg.historian_model.request_params == { "temperature": 0.1, "metadata": {"source": "historian"}, "response_format": {"type": "json_object"}, } + assert cfg.embedding_model.request_params == { "encoding_format": "base64", "metadata": {"source": "embed"}, diff --git a/tests/test_llm_request_params.py b/tests/test_llm_request_params.py index 7cabc398..ea2aed3c 100644 --- a/tests/test_llm_request_params.py +++ b/tests/test_llm_request_params.py @@ -7,6 +7,7 @@ from openai import AsyncOpenAI from Undefined.ai.llm import ModelRequester +from Undefined.ai.parsing import extract_choices_content from Undefined.config.models import ChatModelConfig from Undefined.token_usage_storage import TokenUsageStorage @@ -17,31 +18,58 @@ async def record(self, _usage: Any) -> None: class _FakeChatCompletionsAPI: - def __init__(self) -> None: + def __init__(self, responses: list[dict[str, Any]] | None = None) -> None: self.last_kwargs: dict[str, Any] | None = None + self.calls: list[dict[str, Any]] = [] + self._responses = list(responses or []) async def create(self, **kwargs: Any) -> dict[str, Any]: self.last_kwargs = dict(kwargs) + self.calls.append(dict(kwargs)) + if self._responses: + return self._responses.pop(0) return { "choices": [{"message": {"content": "ok"}}], "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2}, } -class _FakeChatClient: - def __init__(self) -> None: - self.chat = type("_Chat", (), {"completions": _FakeChatCompletionsAPI()})() +class _FakeResponsesAPI: + def __init__(self, responses: list[dict[str, Any]] | None = None) -> None: + self.last_kwargs: dict[str, Any] | None = None + self.calls: list[dict[str, Any]] = [] + self._responses = list(responses or []) + + async def create(self, **kwargs: Any) -> dict[str, Any]: + self.last_kwargs = dict(kwargs) + self.calls.append(dict(kwargs)) + if not self._responses: + raise AssertionError("fake responses exhausted") + return self._responses.pop(0) + + +class _FakeClient: + def __init__( + self, + *, + chat_responses: list[dict[str, Any]] | None = None, + responses: list[dict[str, Any]] | None = None, + ) -> None: + self.chat = type( + "_Chat", (), {"completions": _FakeChatCompletionsAPI(chat_responses)} + )() + self.responses = _FakeResponsesAPI(responses) @pytest.mark.asyncio -async def test_request_uses_model_request_params_and_call_overrides( +async def test_chat_request_uses_model_reasoning_and_request_params( caplog: pytest.LogCaptureFixture, ) -> None: requester = ModelRequester( http_client=httpx.AsyncClient(), token_usage_storage=cast(TokenUsageStorage, _FakeUsageStorage()), ) - fake_client = _FakeChatClient() + fake_client = _FakeClient() setattr( requester, "_get_openai_client_for_model", @@ -52,6 +80,8 @@ async def test_request_uses_model_request_params_and_call_overrides( api_key="sk-test", model_name="gpt-test", max_tokens=512, + reasoning_enabled=True, + reasoning_effort="high", request_params={ "temperature": 0.2, "metadata": {"source": "config"}, @@ -66,7 +96,6 @@ async def test_request_uses_model_request_params_and_call_overrides( max_tokens=128, call_type="chat", temperature=0.7, - reasoning_effort="high", ) assert fake_client.chat.completions.last_kwargs is not None @@ -75,7 +104,7 @@ async def test_request_uses_model_request_params_and_call_overrides( assert fake_client.chat.completions.last_kwargs["temperature"] == 0.7 assert fake_client.chat.completions.last_kwargs["extra_body"] == { "metadata": {"source": "config"}, - "reasoning_effort": "high", + "reasoning": {"effort": "high"}, } assert ( "ignored_keys=model,stream" in caplog.text @@ -83,3 +112,210 @@ async def test_request_uses_model_request_params_and_call_overrides( ) await requester._http_client.aclose() + + +@pytest.mark.asyncio +async def test_responses_request_normalizes_tool_calls_and_usage() -> None: + requester = ModelRequester( + http_client=httpx.AsyncClient(), + token_usage_storage=cast(TokenUsageStorage, _FakeUsageStorage()), + ) + fake_client = _FakeClient( + responses=[ + { + "id": "resp_1", + "output": [ + { + "type": "reasoning", + "id": "rs_1", + "summary": [{"type": "summary_text", "text": "先想一下"}], + }, + { + "type": "function_call", + "call_id": "call_1", + "name": "lookup", + "arguments": '{"query": "weather"}', + }, + ], + "usage": {"input_tokens": 11, "output_tokens": 7, "total_tokens": 18}, + } + ] + ) + setattr( + requester, + "_get_openai_client_for_model", + lambda _cfg: cast(AsyncOpenAI, fake_client), + ) + cfg = ChatModelConfig( + api_url="https://api.openai.com/v1", + api_key="sk-test", + model_name="gpt-test", + max_tokens=512, + api_mode="responses", + reasoning_enabled=True, + reasoning_effort="low", + request_params={ + "metadata": {"source": "config"}, + "custom_flag": "on", + }, + ) + + result = await requester.request( + model_config=cfg, + messages=[{"role": "user", "content": "hello"}], + max_tokens=128, + call_type="chat", + tools=[ + { + "type": "function", + "function": { + "name": "lookup", + "description": "lookup weather", + "parameters": { + "type": "object", + "properties": {"query": {"type": "string"}}, + "required": ["query"], + }, + }, + } + ], + tool_choice=cast(Any, {"type": "function", "function": {"name": "lookup"}}), + thinking={"enabled": False, "budget_tokens": 0}, + ) + + assert fake_client.responses.last_kwargs is not None + assert fake_client.responses.last_kwargs["model"] == "gpt-test" + assert fake_client.responses.last_kwargs["max_output_tokens"] == 128 + assert fake_client.responses.last_kwargs["reasoning"] == {"effort": "low"} + assert fake_client.responses.last_kwargs["tool_choice"] == { + "type": "function", + "name": "lookup", + } + assert fake_client.responses.last_kwargs["metadata"] == {"source": "config"} + assert fake_client.responses.last_kwargs["extra_body"] == {"custom_flag": "on"} + assert "thinking" not in fake_client.responses.last_kwargs + + message = result["choices"][0]["message"] + assert message["tool_calls"][0]["id"] == "call_1" + assert message["tool_calls"][0]["function"]["name"] == "lookup" + assert message["reasoning_content"] == "先想一下" + assert result["usage"] == { + "prompt_tokens": 11, + "completion_tokens": 7, + "total_tokens": 18, + } + assert result["_transport_state"] == { + "api_mode": "responses", + "previous_response_id": "resp_1", + "tool_result_start_index": 2, + } + + await requester._http_client.aclose() + + +@pytest.mark.asyncio +async def test_responses_transport_state_uses_previous_response_id_and_tool_outputs() -> ( + None +): + requester = ModelRequester( + http_client=httpx.AsyncClient(), + token_usage_storage=cast(TokenUsageStorage, _FakeUsageStorage()), + ) + fake_client = _FakeClient( + responses=[ + { + "id": "resp_1", + "output": [ + { + "type": "function_call", + "call_id": "call_1", + "name": "lookup", + "arguments": '{"query": "weather"}', + } + ], + "usage": {"input_tokens": 3, "output_tokens": 2, "total_tokens": 5}, + }, + { + "id": "resp_2", + "output": [ + { + "type": "message", + "id": "msg_1", + "role": "assistant", + "status": "completed", + "content": [{"type": "output_text", "text": "all done"}], + } + ], + "usage": {"input_tokens": 4, "output_tokens": 3, "total_tokens": 7}, + }, + ] + ) + setattr( + requester, + "_get_openai_client_for_model", + lambda _cfg: cast(AsyncOpenAI, fake_client), + ) + cfg = ChatModelConfig( + api_url="https://api.openai.com/v1", + api_key="sk-test", + model_name="gpt-test", + max_tokens=512, + api_mode="responses", + reasoning_enabled=True, + reasoning_effort="medium", + ) + tools = [ + { + "type": "function", + "function": { + "name": "lookup", + "description": "lookup weather", + "parameters": { + "type": "object", + "properties": {"query": {"type": "string"}}, + "required": ["query"], + }, + }, + } + ] + + first = await requester.request( + model_config=cfg, + messages=[{"role": "user", "content": "hello"}], + max_tokens=128, + call_type="chat", + tools=tools, + ) + first_tool_calls = first["choices"][0]["message"]["tool_calls"] + messages = [ + {"role": "user", "content": "hello"}, + {"role": "assistant", "content": "", "tool_calls": first_tool_calls}, + {"role": "tool", "tool_call_id": "call_1", "content": "done"}, + ] + + second = await requester.request( + model_config=cfg, + messages=messages, + max_tokens=128, + call_type="chat", + tools=tools, + transport_state=first["_transport_state"], + message_count_for_transport=len(messages), + ) + + assert fake_client.responses.calls[1]["previous_response_id"] == "resp_1" + assert fake_client.responses.calls[1]["input"] == [ + { + "type": "function_call_output", + "call_id": "call_1", + "output": "done", + } + ] + assert extract_choices_content(second) == "all done" + assert second["usage"] == { + "prompt_tokens": 4, + "completion_tokens": 3, + "total_tokens": 7, + } + + await requester._http_client.aclose() diff --git a/tests/test_runtime_api_probes.py b/tests/test_runtime_api_probes.py new file mode 100644 index 00000000..da1f6783 --- /dev/null +++ b/tests/test_runtime_api_probes.py @@ -0,0 +1,65 @@ +from __future__ import annotations + +import json +from types import SimpleNamespace +from typing import Any, cast + +import pytest +from aiohttp import web + +from Undefined.api import RuntimeAPIContext, RuntimeAPIServer + + +@pytest.mark.asyncio +async def test_runtime_internal_probe_includes_chat_model_transport_fields() -> None: + context = RuntimeAPIContext( + config_getter=lambda: SimpleNamespace( + api=SimpleNamespace( + enabled=True, + host="127.0.0.1", + port=8788, + auth_key="changeme", + openapi_enabled=True, + ), + chat_model=SimpleNamespace( + model_name="gpt-5.4", + api_url="https://api.example.com/v1", + api_mode="responses", + thinking_enabled=False, + thinking_tool_call_compat=True, + reasoning_enabled=True, + reasoning_effort="high", + ), + embedding_model=SimpleNamespace( + model_name="text-embedding-3-small", + api_url="https://api.example.com/v1", + ), + ), + onebot=SimpleNamespace(connection_status=lambda: {}), + ai=SimpleNamespace(memory_storage=None), + command_dispatcher=SimpleNamespace(), + queue_manager=SimpleNamespace(snapshot=lambda: {}), + history_manager=SimpleNamespace(), + ) + server = RuntimeAPIServer(context, host="127.0.0.1", port=8788) + + request = cast(web.Request, cast(Any, SimpleNamespace())) + response = await server._internal_probe_handler(request) + response_text = response.text + assert response_text is not None + payload = json.loads(response_text) + + chat_model = payload["models"]["chat_model"] + assert chat_model == { + "model_name": "gpt-5.4", + "api_url": "https://api.example.com/...", + "api_mode": "responses", + "thinking_enabled": False, + "thinking_tool_call_compat": True, + "reasoning_enabled": True, + "reasoning_effort": "high", + } + assert payload["models"]["embedding_model"] == { + "model_name": "text-embedding-3-small", + "api_url": "https://api.example.com/...", + } diff --git a/tests/test_webui_render_toml.py b/tests/test_webui_render_toml.py index 6d8665a7..8d853c75 100644 --- a/tests/test_webui_render_toml.py +++ b/tests/test_webui_render_toml.py @@ -69,6 +69,10 @@ def test_pool_model_request_params_roundtrip(self) -> None: model_name = "gpt-5" api_url = "https://api.openai.com/v1" api_key = "sk-a" +api_mode = "responses" +thinking_tool_call_compat = true +reasoning_enabled = true +reasoning_effort = "high" [models.chat.pool.models.request_params] temperature = 0.7 @@ -84,6 +88,10 @@ def test_pool_model_request_params_roundtrip(self) -> None: """ data = _roundtrip(src) model = data["models"]["chat"]["pool"]["models"][0] + assert model["api_mode"] == "responses" + assert model["thinking_tool_call_compat"] is True + assert model["reasoning_enabled"] is True + assert model["reasoning_effort"] == "high" params = model["request_params"] assert params["temperature"] == 0.7 assert params["metadata"]["source"] == "webui" From 60d7b2ac05dce64d508975f54ac0b4136679db07 Mon Sep 17 00:00:00 2001 From: Null <1708213363@qq.com> Date: Sat, 7 Mar 2026 16:29:00 +0800 Subject: [PATCH 08/21] feat(webui): sync config template comments --- docs/configuration.md | 1 + scripts/README.md | 20 ++++ scripts/sync_config_template.py | 67 ++++++++++++ src/Undefined/webui/routes/_auth.py | 6 +- src/Undefined/webui/routes/_config.py | 30 +++++- src/Undefined/webui/static/js/config-form.js | 27 +++++ src/Undefined/webui/static/js/i18n.js | 10 ++ src/Undefined/webui/static/js/main.js | 3 + src/Undefined/webui/templates/index.html | 2 + src/Undefined/webui/utils/__init__.py | 12 ++- src/Undefined/webui/utils/comment.py | 21 ++-- src/Undefined/webui/utils/config_sync.py | 88 ++++++++++++++++ src/Undefined/webui/utils/toml_render.py | 104 +++++++++++++++---- tests/test_config_template_sync.py | 45 ++++++++ tests/test_webui_render_toml.py | 29 +++++- 15 files changed, 430 insertions(+), 35 deletions(-) create mode 100644 scripts/sync_config_template.py create mode 100644 src/Undefined/webui/utils/config_sync.py create mode 100644 tests/test_config_template_sync.py diff --git a/docs/configuration.md b/docs/configuration.md index 4ed6a221..68c5d81e 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -17,6 +17,7 @@ - 主文件：`config.toml` - 示例模板：`config.toml.example` - 启动 WebUI 时，如 `config.toml` 不存在，会自动用示例模板生成。 +- 已有 `config.toml` 想补齐新增配置项/注释时，可用 WebUI 的“同步模板”按钮，或运行 `uv run python scripts/sync_config_template.py`。 ### 1.2 运行时本地文件 - `config.local.json`：运行时维护的本地管理员列表（如 `/addadmin`）。 diff --git a/scripts/README.md b/scripts/README.md index 12a9d319..f9410c3e 100644 --- a/scripts/README.md +++ b/scripts/README.md @@ -4,6 +4,26 @@ ## 脚本列表 +### [`sync_config_template.py`](sync_config_template.py) — 同步配置模板与注释 + +保留当前 `config.toml` 已有配置值，同时把 `config.toml.example` 中新增的配置项、默认空表和双语注释同步回来。 + +```bash +# 直接写回 config.toml +uv run python scripts/sync_config_template.py + +# 仅预览，不落盘 +uv run python scripts/sync_config_template.py --dry-run + +# 输出同步后的完整内容 +uv run python scripts/sync_config_template.py --stdout +``` + +**适用场景**： +- 项目升级后想把新增配置项补齐到现有 `config.toml` +- 想恢复 `config.toml.example` 中的最新双语注释 +- 不想手工比对新旧配置文件 + ### [`reembed_cognitive.py`](reembed_cognitive.py) — 认知记忆向量库重嵌入 当更换嵌入模型（维度变化或模型升级）时，对 ChromaDB 中的 `cognitive_events` 和 `cognitive_profiles` 进行全量重嵌入。 diff --git a/scripts/sync_config_template.py b/scripts/sync_config_template.py new file mode 100644 index 00000000..cbf2a3ce --- /dev/null +++ b/scripts/sync_config_template.py @@ -0,0 +1,67 @@ +from __future__ import annotations + +import argparse +import sys +from pathlib import Path + +from Undefined.webui.utils import sync_config_file + + +def build_parser() -> argparse.ArgumentParser: + parser = argparse.ArgumentParser( + description="同步 config.toml.example 中的新配置项与注释到现有 config.toml，同时保留已有配置值。" + ) + parser.add_argument( + "--config", + type=Path, + default=Path("config.toml"), + help="目标配置文件路径，默认: config.toml", + ) + parser.add_argument( + "--example", + type=Path, + default=Path("config.toml.example"), + help="示例配置文件路径，默认: config.toml.example", + ) + parser.add_argument( + "--dry-run", + action="store_true", + help="仅预览同步结果，不写回文件。", + ) + parser.add_argument( + "--stdout", + action="store_true", + help="将同步后的完整 TOML 输出到标准输出。", + ) + return parser + + +def main() -> int: + args = build_parser().parse_args() + try: + result = sync_config_file( + config_path=args.config, + example_path=args.example, + write=not args.dry_run, + ) + except FileNotFoundError as exc: + print(f"[sync-config] 未找到示例配置：{exc}", file=sys.stderr) + return 1 + except ValueError as exc: + print(f"[sync-config] 配置解析失败：{exc}", file=sys.stderr) + return 1 + + action = "预览完成" if args.dry_run else "同步完成" + print(f"[sync-config] {action}: {args.config}") + print(f"[sync-config] 新增路径数量: {len(result.added_paths)}") + for path in result.added_paths: + print(f" + {path}") + + if args.stdout: + print("\n--- merged config.toml ---\n") + print(result.content, end="") + return 0 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/src/Undefined/webui/routes/_auth.py b/src/Undefined/webui/routes/_auth.py index cbe363e2..52689781 100644 --- a/src/Undefined/webui/routes/_auth.py +++ b/src/Undefined/webui/routes/_auth.py @@ -19,7 +19,7 @@ _record_login_failure, _clear_login_failures, ) -from ..utils import read_config_source, apply_patch, render_toml +from ..utils import read_config_source, apply_patch, load_comment_map, render_toml @routes.post("/api/login") @@ -171,7 +171,9 @@ async def password_handler(request: web.Request) -> Response: data_dict = {} patched = apply_patch(data_dict, {"webui.password": new_password}) - CONFIG_PATH.write_text(render_toml(patched), encoding="utf-8") + CONFIG_PATH.write_text( + render_toml(patched, comments=load_comment_map()), encoding="utf-8" + ) get_config_manager().reload() request.app["settings"] = load_webui_settings() get_session_store(request).clear() diff --git a/src/Undefined/webui/routes/_config.py b/src/Undefined/webui/routes/_config.py index 26770f05..e5128569 100644 --- a/src/Undefined/webui/routes/_config.py +++ b/src/Undefined/webui/routes/_config.py @@ -16,6 +16,7 @@ apply_patch, render_toml, sort_config, + sync_config_file, ) @@ -85,7 +86,9 @@ async def config_patch_handler(request: web.Request) -> Response: data = {} patched = apply_patch(data, patch) - CONFIG_PATH.write_text(render_toml(patched), encoding="utf-8") + CONFIG_PATH.write_text( + render_toml(patched, comments=load_comment_map()), encoding="utf-8" + ) get_config_manager().reload() validation_ok, validation_msg = validate_required_config() return web.json_response( @@ -95,3 +98,28 @@ async def config_patch_handler(request: web.Request) -> Response: "warning": None if validation_ok else validation_msg, } ) + + +@routes.post("/api/config/sync-template") +async def sync_config_template_handler(request: web.Request) -> Response: + if not check_auth(request): + return web.json_response({"error": "Unauthorized"}, status=401) + try: + result = sync_config_file() + get_config_manager().reload() + validation_ok, validation_msg = validate_required_config() + return web.json_response( + { + "success": True, + "message": "Synced", + "added_paths": result.added_paths, + "added_count": len(result.added_paths), + "warning": None if validation_ok else validation_msg, + } + ) + except FileNotFoundError as exc: + return web.json_response({"success": False, "error": str(exc)}, status=404) + except ValueError as exc: + return web.json_response({"success": False, "error": str(exc)}, status=400) + except Exception as exc: + return web.json_response({"success": False, "error": str(exc)}, status=500) diff --git a/src/Undefined/webui/static/js/config-form.js b/src/Undefined/webui/static/js/config-form.js index 6fef53b8..59c64350 100644 --- a/src/Undefined/webui/static/js/config-form.js +++ b/src/Undefined/webui/static/js/config-form.js @@ -890,6 +890,33 @@ async function autoSave() { } } +async function syncConfigTemplate(button) { + if (!confirm(t("config.sync_confirm"))) return; + setButtonLoading(button, true); + showSaveStatus("saving", t("config.syncing")); + try { + const res = await api("/api/config/sync-template", { method: "POST" }); + const data = await res.json(); + if (!data.success) { + showSaveStatus("error", t("config.save_error")); + showToast(`${t("common.error")}: ${data.error || t("config.sync_error")}`, "error", 5000); + return; + } + await loadConfig(); + showSaveStatus("saved", t("config.saved")); + if (data.warning) { + showToast(`${t("common.warning")}: ${data.warning}`, "warning", 5000); + } + const suffix = Number.isFinite(data.added_count) ? ` (+${data.added_count})` : ""; + showToast(`${t("config.sync_success")}${suffix}`, "info", 4000); + } catch (e) { + showSaveStatus("error", t("config.sync_error")); + showToast(`${t("common.error")}: ${e.message}`, "error", 5000); + } finally { + setButtonLoading(button, false); + } +} + async function resetConfig() { if (!confirm(t("config.reset_confirm"))) return; try { diff --git a/src/Undefined/webui/static/js/i18n.js b/src/Undefined/webui/static/js/i18n.js index 32092056..59c913e3 100644 --- a/src/Undefined/webui/static/js/i18n.js +++ b/src/Undefined/webui/static/js/i18n.js @@ -71,6 +71,11 @@ const I18N = { "config.save": "保存更改", "config.reset": "重置更改", "config.reset_confirm": "确定要撤销所有本地更改吗？这将从服务器重新加载配置。", + "config.sync_template": "同步模板", + "config.sync_confirm": "确定要把 config.toml.example 中的新配置项和注释同步到当前 config.toml 吗？现有配置值会保留。", + "config.syncing": "同步模板中...", + "config.sync_success": "模板同步完成", + "config.sync_error": "模板同步失败", "config.search_placeholder": "搜索配置...", "config.clear_search": "清除搜索", "config.expand_all": "全部展开", @@ -272,6 +277,11 @@ const I18N = { "config.save": "Save Changes", "config.reset": "Revert Changes", "config.reset_confirm": "Are you sure you want to revert all local changes? This will reload the configuration from the server.", + "config.sync_template": "Sync Template", + "config.sync_confirm": "Sync new settings and comments from config.toml.example into the current config.toml? Existing configured values will be kept.", + "config.syncing": "Syncing template...", + "config.sync_success": "Template sync completed", + "config.sync_error": "Template sync failed", "config.search_placeholder": "Search config...", "config.clear_search": "Clear search", "config.expand_all": "Expand all", diff --git a/src/Undefined/webui/static/js/main.js b/src/Undefined/webui/static/js/main.js index dedbc0b0..a9d036bd 100644 --- a/src/Undefined/webui/static/js/main.js +++ b/src/Undefined/webui/static/js/main.js @@ -140,6 +140,9 @@ async function init() { const resetBtn = get("btnResetConfig"); if (resetBtn) resetBtn.onclick = resetConfig; + const syncConfigBtn = get("btnSyncConfigTemplate"); + if (syncConfigBtn) syncConfigBtn.onclick = () => syncConfigTemplate(syncConfigBtn); + const refreshLogsBtn = get("btnRefreshLogs"); if (refreshLogsBtn) { refreshLogsBtn.onclick = async () => { diff --git a/src/Undefined/webui/templates/index.html b/src/Undefined/webui/templates/index.html index 0501c425..98ad198b 100644 --- a/src/Undefined/webui/templates/index.html +++ b/src/Undefined/webui/templates/index.html @@ -301,6 +301,8 @@

配置修改

data-i18n="config.expand_all">全部展开 + diff --git a/src/Undefined/webui/utils/__init__.py b/src/Undefined/webui/utils/__init__.py index 9d3c496b..9e4e2f1c 100644 --- a/src/Undefined/webui/utils/__init__.py +++ b/src/Undefined/webui/utils/__init__.py @@ -8,7 +8,13 @@ CONFIG_EXAMPLE_PATH, TomlData, ) -from .comment import CommentMap, parse_comment_map, load_comment_map +from .comment import ( + CommentMap, + parse_comment_map, + parse_comment_map_text, + load_comment_map, +) +from .config_sync import ConfigTemplateSyncResult, sync_config_file, sync_config_text from .toml_render import ( format_value, render_table, @@ -31,7 +37,11 @@ "TomlData", "CommentMap", "parse_comment_map", + "parse_comment_map_text", "load_comment_map", + "ConfigTemplateSyncResult", + "sync_config_file", + "sync_config_text", "format_value", "render_table", "render_toml", diff --git a/src/Undefined/webui/utils/comment.py b/src/Undefined/webui/utils/comment.py index df7fba71..53bc2353 100644 --- a/src/Undefined/webui/utils/comment.py +++ b/src/Undefined/webui/utils/comment.py @@ -34,17 +34,11 @@ def _normalize_comment_buffer(buffer: list[str]) -> dict[str, str]: return result -def parse_comment_map(path: Path) -> CommentMap: - if not path.exists(): - return {} +def parse_comment_map_text(text: str) -> CommentMap: comments: CommentMap = {} buffer: list[str] = [] current_section = "" - try: - lines = path.read_text(encoding="utf-8").splitlines() - except Exception: - return {} - for raw_line in lines: + for raw_line in text.splitlines(): line = raw_line.strip() if not line: buffer.clear() @@ -53,7 +47,7 @@ def parse_comment_map(path: Path) -> CommentMap: buffer.append(line.lstrip("#").strip()) continue if line.startswith("[") and line.endswith("]"): - section_name = line[1:-1].strip() + section_name = line.strip("[]").strip() if buffer: comment = _normalize_comment_buffer(buffer) if comment: @@ -74,6 +68,15 @@ def parse_comment_map(path: Path) -> CommentMap: return comments +def parse_comment_map(path: Path) -> CommentMap: + if not path.exists(): + return {} + try: + return parse_comment_map_text(path.read_text(encoding="utf-8")) + except Exception: + return {} + + def load_comment_map() -> CommentMap: example_path = _resolve_config_example_path() comments = parse_comment_map(example_path) if example_path else {} diff --git a/src/Undefined/webui/utils/config_sync.py b/src/Undefined/webui/utils/config_sync.py new file mode 100644 index 00000000..d79edc06 --- /dev/null +++ b/src/Undefined/webui/utils/config_sync.py @@ -0,0 +1,88 @@ +from __future__ import annotations + +import tomllib +from dataclasses import dataclass +from pathlib import Path +from Undefined.config.loader import CONFIG_PATH + +from .comment import CommentMap, parse_comment_map_text +from .config_io import CONFIG_EXAMPLE_PATH, _resolve_config_example_path +from .toml_render import TomlData, merge_defaults, render_toml + + +@dataclass(frozen=True) +class ConfigTemplateSyncResult: + content: str + added_paths: list[str] + comments: CommentMap + + +def _parse_toml_text(content: str, *, label: str) -> TomlData: + if not content.strip(): + return {} + try: + data = tomllib.loads(content) + except tomllib.TOMLDecodeError as exc: + raise ValueError(f"{label} TOML parse error: {exc}") from exc + if not isinstance(data, dict): + raise ValueError(f"{label} TOML root must be a table") + return data + + +def _collect_added_paths( + defaults: TomlData, current: TomlData, prefix: str = "" +) -> list[str]: + added: list[str] = [] + for key, default_value in defaults.items(): + path = f"{prefix}.{key}" if prefix else key + if key not in current: + added.append(path) + continue + current_value = current[key] + if isinstance(default_value, dict) and isinstance(current_value, dict): + added.extend(_collect_added_paths(default_value, current_value, path)) + return added + + +def _merge_comment_maps(current: CommentMap, example: CommentMap) -> CommentMap: + merged: CommentMap = dict(current) + for key, value in example.items(): + merged[key] = dict(value) + return merged + + +def sync_config_text(current_text: str, example_text: str) -> ConfigTemplateSyncResult: + current_data = _parse_toml_text(current_text, label="current config") + example_data = _parse_toml_text(example_text, label="config example") + added_paths = _collect_added_paths(example_data, current_data) + merged = merge_defaults(example_data, current_data) + comments = _merge_comment_maps( + parse_comment_map_text(current_text), + parse_comment_map_text(example_text), + ) + content = render_toml(merged, comments=comments) + return ConfigTemplateSyncResult( + content=content, + added_paths=added_paths, + comments=comments, + ) + + +def sync_config_file( + config_path: Path = CONFIG_PATH, + example_path: Path = CONFIG_EXAMPLE_PATH, + *, + write: bool = True, +) -> ConfigTemplateSyncResult: + resolved_example = _resolve_config_example_path(example_path) + if resolved_example is None or not resolved_example.exists(): + raise FileNotFoundError(f"config example not found: {example_path}") + + current_text = ( + config_path.read_text(encoding="utf-8") if config_path.exists() else "" + ) + example_text = resolved_example.read_text(encoding="utf-8") + result = sync_config_text(current_text, example_text) + if write: + config_path.write_text(result.content, encoding="utf-8") + return result diff --git a/src/Undefined/webui/utils/toml_render.py b/src/Undefined/webui/utils/toml_render.py index 532b0db6..ef396e91 100644 --- a/src/Undefined/webui/utils/toml_render.py +++ b/src/Undefined/webui/utils/toml_render.py @@ -3,6 +3,7 @@ from functools import lru_cache from typing import Any, cast +from .comment import CommentMap from .config_io import load_default_data TomlData = dict[str, Any] @@ -61,55 +62,116 @@ def _is_array_of_tables(value: Any) -> bool: ) -def _render_scalar_items(path: list[str], table: TomlData) -> list[str]: - return [ - f"{key} = {format_value(table[key])}" - for key in sorted_keys(table, path) - if not isinstance(table[key], dict) and not _is_array_of_tables(table[key]) - ] +def _comment_lines(comments: CommentMap | None, path_key: str) -> list[str]: + if not comments: + return [] + entry = comments.get(path_key) + if not entry: + return [] + lines: list[str] = [] + zh = str(entry.get("zh", "")).strip() + en = str(entry.get("en", "")).strip() + if zh: + lines.append(f"# zh: {zh}") + if en: + lines.append(f"# en: {en}") + if not lines: + for value in entry.values(): + text = str(value).strip() + if text: + lines.append(f"# {text}") + return lines + + +def _append_comment( + lines: list[str], comments: CommentMap | None, path_key: str +) -> None: + comment_lines = _comment_lines(comments, path_key) + if comment_lines: + lines.extend(comment_lines) + + +def _render_scalar_items( + path: list[str], table: TomlData, comments: CommentMap | None = None +) -> list[str]: + lines: list[str] = [] + path_prefix = ".".join(path) if path else "" + for key in sorted_keys(table, path): + value = table[key] + if isinstance(value, dict) or _is_array_of_tables(value): + continue + path_key = f"{path_prefix}.{key}" if path_prefix else key + _append_comment(lines, comments, path_key) + lines.append(f"{key} = {format_value(value)}") + return lines -def _render_nested_items(path: list[str], table: TomlData) -> list[str]: +def _render_nested_items( + path: list[str], table: TomlData, comments: CommentMap | None = None +) -> list[str]: lines: list[str] = [] for key in sorted_keys(table, path): value = table[key] if isinstance(value, dict): - lines.extend(render_table(path + [key], value)) + lines.extend(render_table(path + [key], value, comments=comments)) elif _is_array_of_tables(value): aot_path = path + [key] - for item in value: + for index, item in enumerate(value): lines.extend( - _render_array_of_tables_item(aot_path, cast(TomlData, item)) + _render_array_of_tables_item( + aot_path, + cast(TomlData, item), + comments=comments, + include_collection_comment=index == 0, + ) ) return lines -def _render_array_of_tables_item(path: list[str], table: TomlData) -> list[str]: - lines = [f"[[{'.'.join(path)}]]"] - lines.extend(_render_scalar_items(path, table)) +def _render_array_of_tables_item( + path: list[str], + table: TomlData, + *, + comments: CommentMap | None = None, + include_collection_comment: bool = False, +) -> list[str]: + lines: list[str] = [] + path_key = ".".join(path) + if include_collection_comment: + _append_comment(lines, comments, path_key) + lines.append(f"[[{path_key}]]") + lines.extend(_render_scalar_items(path, table, comments=comments)) lines.append("") - lines.extend(_render_nested_items(path, table)) + lines.extend(_render_nested_items(path, table, comments=comments)) return lines -def render_table(path: list[str], table: TomlData) -> list[str]: +def render_table( + path: list[str], table: TomlData, comments: CommentMap | None = None +) -> list[str]: lines: list[str] = [] - items = _render_scalar_items(path, table) - if items and path: + items = _render_scalar_items(path, table, comments=comments) + nested = _render_nested_items(path, table, comments=comments) + + if path: + _append_comment(lines, comments, ".".join(path)) lines.append(f"[{'.'.join(path)}]") lines.extend(items) lines.append("") - elif items: + lines.extend(nested) + return lines + + if items: lines.extend(items) lines.append("") - lines.extend(_render_nested_items(path, table)) + lines.extend(nested) return lines -def render_toml(data: TomlData) -> str: +def render_toml(data: TomlData, comments: CommentMap | None = None) -> str: if not data: return "" - return "\n".join(render_table([], data)).rstrip() + "\n" + return "\n".join(render_table([], data, comments=comments)).rstrip() + "\n" def apply_patch(data: TomlData, patch: dict[str, Any]) -> TomlData: diff --git a/tests/test_config_template_sync.py b/tests/test_config_template_sync.py new file mode 100644 index 00000000..c37f3b51 --- /dev/null +++ b/tests/test_config_template_sync.py @@ -0,0 +1,45 @@ +from __future__ import annotations + +import tomllib + +from Undefined.webui.utils import sync_config_text + + +def test_sync_config_text_preserves_values_and_adds_new_fields_with_comments() -> None: + current = """ +# custom comment should stay for unknown path +[core] +bot_qq = 123456 + +[custom] +flag = true +""" + example = """ +# zh: 机器人小号配置。 +# en: Bot account settings. +[core] +# zh: 机器人QQ号。 +# en: Bot QQ number. +bot_qq = 0 +# zh: 是否处理私聊消息。 +# en: Process private messages. +process_private_message = true + +# zh: 模板新增小节。 +# en: Newly added section from template. +[features] +# zh: 是否启用模型池。 +# en: Enable model pool. +pool_enabled = false +""" + + result = sync_config_text(current, example) + data = tomllib.loads(result.content) + + assert data["core"]["bot_qq"] == 123456 + assert data["core"]["process_private_message"] is True + assert data["features"]["pool_enabled"] is False + assert data["custom"]["flag"] is True + assert "# zh: 是否处理私聊消息。" in result.content + assert "# en: Enable model pool." in result.content + assert result.added_paths == ["core.process_private_message", "features"] diff --git a/tests/test_webui_render_toml.py b/tests/test_webui_render_toml.py index 8d853c75..11c217ce 100644 --- a/tests/test_webui_render_toml.py +++ b/tests/test_webui_render_toml.py @@ -2,7 +2,7 @@ import tomllib -from Undefined.webui.utils import render_toml +from Undefined.webui.utils import parse_comment_map_text, render_toml def _roundtrip(toml_str: str) -> dict: # type: ignore[type-arg] @@ -119,3 +119,30 @@ def test_nested_aot_child_tables_roundtrip(self) -> None: "child-a", "child-b", ] + + def test_render_comments_and_empty_table(self) -> None: + """带注释的空表应被完整渲染出来""" + src = """ +# zh: 主配置 +# en: Main section +[models.chat.request_params] +""" + comments = parse_comment_map_text(src) + rendered = render_toml( + {"models": {"chat": {"request_params": {}}}}, comments=comments + ) + assert "# zh: 主配置" in rendered + assert "[models.chat.request_params]" in rendered + + def test_render_comments_before_scalar_keys(self) -> None: + """标量字段前应写出示例注释""" + comments = { + "core.bot_qq": { + "zh": "机器人QQ号。", + "en": "Bot QQ number.", + } + } + rendered = render_toml({"core": {"bot_qq": 1}}, comments=comments) + assert "# zh: 机器人QQ号。" in rendered + assert "# en: Bot QQ number." in rendered + assert "bot_qq = 1" in rendered From ab58e7e14d66023606b90e525b500e92d0b82a15 Mon Sep 17 00:00:00 2001 From: Null <1708213363@qq.com> Date: Sat, 7 Mar 2026 16:42:51 +0800 Subject: [PATCH 09/21] docs(scripts): document direct config sync entry --- docs/configuration.md | 2 +- scripts/README.md | 9 ++++++--- scripts/reembed_cognitive.py | 0 scripts/sync_config_template.py | 8 +++++++- 4 files changed, 14 insertions(+), 5 deletions(-) mode change 100644 => 100755 scripts/reembed_cognitive.py mode change 100644 => 100755 scripts/sync_config_template.py diff --git a/docs/configuration.md b/docs/configuration.md index 68c5d81e..0d2dd1b0 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -17,7 +17,7 @@ - 主文件：`config.toml` - 示例模板：`config.toml.example` - 启动 WebUI 时，如 `config.toml` 不存在，会自动用示例模板生成。 -- 已有 `config.toml` 想补齐新增配置项/注释时，可用 WebUI 的“同步模板”按钮，或运行 `uv run python scripts/sync_config_template.py`。 +- 已有 `config.toml` 想补齐新增配置项/注释时，可用 WebUI 的“同步模板”按钮，或运行 `python scripts/sync_config_template.py`（也支持 `uv run python scripts/sync_config_template.py`）。 ### 1.2 运行时本地文件 - `config.local.json`：运行时维护的本地管理员列表（如 `/addadmin`）。 diff --git a/scripts/README.md b/scripts/README.md index f9410c3e..cae7f2dc 100644 --- a/scripts/README.md +++ b/scripts/README.md @@ -9,14 +9,17 @@ 保留当前 `config.toml` 已有配置值，同时把 `config.toml.example` 中新增的配置项、默认空表和双语注释同步回来。 ```bash -# 直接写回 config.toml +# 直接用 Python 运行 +python scripts/sync_config_template.py + +# 若希望复用项目虚拟环境，也可这样运行 uv run python scripts/sync_config_template.py # 仅预览，不落盘 -uv run python scripts/sync_config_template.py --dry-run +python scripts/sync_config_template.py --dry-run # 输出同步后的完整内容 -uv run python scripts/sync_config_template.py --stdout +python scripts/sync_config_template.py --stdout ``` **适用场景**： diff --git a/scripts/reembed_cognitive.py b/scripts/reembed_cognitive.py old mode 100644 new mode 100755 diff --git a/scripts/sync_config_template.py b/scripts/sync_config_template.py old mode 100644 new mode 100755 index cbf2a3ce..93cff1bb --- a/scripts/sync_config_template.py +++ b/scripts/sync_config_template.py @@ -1,10 +1,16 @@ +#!/usr/bin/env python3 from __future__ import annotations import argparse import sys from pathlib import Path -from Undefined.webui.utils import sync_config_file +_PROJECT_ROOT = Path(__file__).resolve().parent.parent +_SRC_DIR = _PROJECT_ROOT / "src" +if str(_SRC_DIR) not in sys.path: + sys.path.insert(0, str(_SRC_DIR)) + +from Undefined.webui.utils import sync_config_file # noqa: E402 def build_parser() -> argparse.ArgumentParser: From ed1f6de124be0556010a51d1972c2d94b95fab52 Mon Sep 17 00:00:00 2001 From: Null <1708213363@qq.com> Date: Sat, 7 Mar 2026 17:07:20 +0800 Subject: [PATCH 10/21] fix(webui): escape multiline toml strings --- src/Undefined/webui/utils/toml_render.py | 3 ++- tests/test_config_template_sync.py | 22 ++++++++++++++++++++++ tests/test_webui_render_toml.py | 19 +++++++++++++++++++ 3 files changed, 43 insertions(+), 1 deletion(-) diff --git a/src/Undefined/webui/utils/toml_render.py b/src/Undefined/webui/utils/toml_render.py index ef396e91..7bf9e90f 100644 --- a/src/Undefined/webui/utils/toml_render.py +++ b/src/Undefined/webui/utils/toml_render.py @@ -1,5 +1,6 @@ from __future__ import annotations +import json from functools import lru_cache from typing import Any, cast @@ -48,7 +49,7 @@ def format_value(value: Any) -> str: if isinstance(value, (int, float)): return str(value) if isinstance(value, str): - return f'"{value.replace(chr(92), chr(92) * 2).replace(chr(34), chr(92) + chr(34))}"' + return json.dumps(value, ensure_ascii=False) if isinstance(value, list): return f"[{', '.join(format_value(item) for item in value)}]" return f'"{str(value)}"' diff --git a/tests/test_config_template_sync.py b/tests/test_config_template_sync.py index c37f3b51..9eed5cc6 100644 --- a/tests/test_config_template_sync.py +++ b/tests/test_config_template_sync.py @@ -43,3 +43,25 @@ def test_sync_config_text_preserves_values_and_adds_new_fields_with_comments() - assert "# zh: 是否处理私聊消息。" in result.content assert "# en: Enable model pool." in result.content assert result.added_paths == ["core.process_private_message", "features"] + + +def test_sync_config_text_preserves_multiline_string_values() -> None: + current = ''' +[models.embedding] +query_instruction = """第一行 +第二行 +第三行""" +''' + example = ''' +[models.embedding] +query_instruction = """默认第一行 +默认第二行""" +document_instruction = """文档前缀 +第二行""" +''' + result = sync_config_text(current, example) + parsed = tomllib.loads(result.content) + assert ( + parsed["models"]["embedding"]["query_instruction"] == "第一行\n第二行\n第三行" + ) + assert parsed["models"]["embedding"]["document_instruction"] == "文档前缀\n第二行" diff --git a/tests/test_webui_render_toml.py b/tests/test_webui_render_toml.py index 11c217ce..60e4882c 100644 --- a/tests/test_webui_render_toml.py +++ b/tests/test_webui_render_toml.py @@ -146,3 +146,22 @@ def test_render_comments_before_scalar_keys(self) -> None: assert "# zh: 机器人QQ号。" in rendered assert "# en: Bot QQ number." in rendered assert "bot_qq = 1" in rendered + + def test_multiline_string_roundtrip(self) -> None: + """多行字符串应被渲染成合法 TOML，并可完整往返""" + original = "第一行\n第二行\n第三行" + rendered = render_toml( + {"models": {"embedding": {"query_instruction": original}}} + ) + parsed = tomllib.loads(rendered) + assert parsed["models"]["embedding"]["query_instruction"] == original + assert "\n" in rendered + + def test_multiline_string_with_quotes_and_backslashes_roundtrip(self) -> None: + """带引号与反斜杠的多行字符串也必须是合法 TOML""" + original = 'prefix "quoted"\npath\\to\\file\nline3' + rendered = render_toml( + {"models": {"embedding": {"document_instruction": original}}} + ) + parsed = tomllib.loads(rendered) + assert parsed["models"]["embedding"]["document_instruction"] == original From f6ca7cc8437899cb6b36a4472b5bc3b51ee337b6 Mon Sep 17 00:00:00 2001 From: Null <1708213363@qq.com> Date: Sat, 7 Mar 2026 17:38:01 +0800 Subject: [PATCH 11/21] fix(ai): normalize responses function tools --- .../ai/transports/openai_transport.py | 57 +++++++++- tests/test_llm_request_params.py | 100 +++++++++++++++++- 2 files changed, 152 insertions(+), 5 deletions(-) diff --git a/src/Undefined/ai/transports/openai_transport.py b/src/Undefined/ai/transports/openai_transport.py index 70f2b809..da1b8c31 100644 --- a/src/Undefined/ai/transports/openai_transport.py +++ b/src/Undefined/ai/transports/openai_transport.py @@ -250,7 +250,51 @@ def _messages_to_responses_input( return items -def _normalize_responses_tool_choice(tool_choice: Any) -> Any: +def _normalize_responses_tools( + tools: list[dict[str, Any]], + internal_to_api: dict[str, str], +) -> list[dict[str, Any]]: + normalized_tools: list[dict[str, Any]] = [] + for tool in tools: + if not isinstance(tool, dict): + continue + tool_type = str(tool.get("type", "")).strip().lower() + if tool_type != "function": + normalized_tools.append(dict(tool)) + continue + + function = tool.get("function") + if not isinstance(function, dict): + normalized_tools.append(dict(tool)) + continue + + name = str(function.get("name", "")).strip() + if not name: + normalized_tools.append(dict(tool)) + continue + + api_name = internal_to_api.get(name, name) + normalized_tool: dict[str, Any] = { + "type": "function", + "name": api_name, + } + description = function.get("description") + if description is not None: + normalized_tool["description"] = description + parameters = function.get("parameters") + if parameters is not None: + normalized_tool["parameters"] = parameters + strict = function.get("strict") + if strict is not None: + normalized_tool["strict"] = strict + normalized_tools.append(normalized_tool) + return normalized_tools + + +def _normalize_responses_tool_choice( + tool_choice: Any, + internal_to_api: dict[str, str], +) -> Any: if not isinstance(tool_choice, dict): return tool_choice choice_type = str(tool_choice.get("type", "")).strip().lower() @@ -259,7 +303,10 @@ def _normalize_responses_tool_choice(tool_choice: Any) -> Any: if isinstance(function, dict): name = str(function.get("name", "")).strip() if name: - return {"type": "function", "name": name} + return { + "type": "function", + "name": internal_to_api.get(name, name), + } return tool_choice @@ -282,8 +329,10 @@ def build_responses_request_body( if reasoning is not None: body["reasoning"] = reasoning if tools: - body["tools"] = tools - body["tool_choice"] = _normalize_responses_tool_choice(tool_choice) + body["tools"] = _normalize_responses_tools(tools, internal_to_api) + body["tool_choice"] = _normalize_responses_tool_choice( + tool_choice, internal_to_api + ) previous_response_id = "" start_index = 0 diff --git a/tests/test_llm_request_params.py b/tests/test_llm_request_params.py index ea2aed3c..7bc31186 100644 --- a/tests/test_llm_request_params.py +++ b/tests/test_llm_request_params.py @@ -6,7 +6,7 @@ import pytest from openai import AsyncOpenAI -from Undefined.ai.llm import ModelRequester +from Undefined.ai.llm import ModelRequester, _encode_tool_name_for_api from Undefined.ai.parsing import extract_choices_content from Undefined.config.models import ChatModelConfig from Undefined.token_usage_storage import TokenUsageStorage @@ -187,6 +187,18 @@ async def test_responses_request_normalizes_tool_calls_and_usage() -> None: assert fake_client.responses.last_kwargs["model"] == "gpt-test" assert fake_client.responses.last_kwargs["max_output_tokens"] == 128 assert fake_client.responses.last_kwargs["reasoning"] == {"effort": "low"} + assert fake_client.responses.last_kwargs["tools"] == [ + { + "type": "function", + "name": "lookup", + "description": "lookup weather", + "parameters": { + "type": "object", + "properties": {"query": {"type": "string"}}, + "required": ["query"], + }, + } + ] assert fake_client.responses.last_kwargs["tool_choice"] == { "type": "function", "name": "lookup", @@ -319,3 +331,89 @@ async def test_responses_transport_state_uses_previous_response_id_and_tool_outp } await requester._http_client.aclose() + + +@pytest.mark.asyncio +async def test_responses_tools_and_tool_choice_use_sanitized_api_names() -> None: + requester = ModelRequester( + http_client=httpx.AsyncClient(), + token_usage_storage=cast(TokenUsageStorage, _FakeUsageStorage()), + ) + expected_api_name = _encode_tool_name_for_api("lookup.weather@bj") + fake_client = _FakeClient( + responses=[ + { + "id": "resp_1", + "output": [ + { + "type": "function_call", + "call_id": "call_1", + "name": expected_api_name, + "arguments": '{"query": "weather"}', + } + ], + "usage": {"input_tokens": 2, "output_tokens": 3, "total_tokens": 5}, + } + ] + ) + setattr( + requester, + "_get_openai_client_for_model", + lambda _cfg: cast(AsyncOpenAI, fake_client), + ) + cfg = ChatModelConfig( + api_url="https://api.openai.com/v1", + api_key="sk-test", + model_name="gpt-test", + max_tokens=512, + api_mode="responses", + ) + + result = await requester.request( + model_config=cfg, + messages=[{"role": "user", "content": "hello"}], + max_tokens=128, + call_type="chat", + tools=[ + { + "type": "function", + "function": { + "name": "lookup.weather@bj", + "description": "lookup weather", + "parameters": { + "type": "object", + "properties": {"query": {"type": "string"}}, + "required": ["query"], + }, + }, + } + ], + tool_choice=cast( + Any, + {"type": "function", "function": {"name": "lookup.weather@bj"}}, + ), + ) + + assert fake_client.responses.last_kwargs is not None + tool_payload = fake_client.responses.last_kwargs["tools"][0] + api_tool_name = tool_payload["name"] + assert tool_payload == { + "type": "function", + "name": api_tool_name, + "description": "lookup weather", + "parameters": { + "type": "object", + "properties": {"query": {"type": "string"}}, + "required": ["query"], + }, + } + assert api_tool_name != "lookup.weather@bj" + assert fake_client.responses.last_kwargs["tool_choice"] == { + "type": "function", + "name": api_tool_name, + } + assert result["choices"][0]["message"]["tool_calls"][0]["function"]["name"] == ( + "lookup.weather@bj" + ) + + await requester._http_client.aclose() From 4abef5b474faafe6fb2039a4ad0acf429aad0813 Mon Sep 17 00:00:00 2001 From: Null <1708213363@qq.com> Date: Sat, 7 Mar 2026 17:49:47 +0800 Subject: [PATCH 12/21] fix(ai): compat responses tool choice string --- .../ai/transports/openai_transport.py | 44 +++++++++++++------ tests/test_llm_request_params.py | 10 +---- 2 files changed, 32 insertions(+), 22 deletions(-) diff --git a/src/Undefined/ai/transports/openai_transport.py b/src/Undefined/ai/transports/openai_transport.py index da1b8c31..3593774d 100644 --- a/src/Undefined/ai/transports/openai_transport.py +++ b/src/Undefined/ai/transports/openai_transport.py @@ -294,20 +294,25 @@ def _normalize_responses_tools( def _normalize_responses_tool_choice( tool_choice: Any, internal_to_api: dict[str, str], -) -> Any: +) -> tuple[Any, str | None]: if not isinstance(tool_choice, dict): - return tool_choice + return tool_choice, None choice_type = str(tool_choice.get("type", "")).strip().lower() - if choice_type == "function": - function = tool_choice.get("function") - if isinstance(function, dict): - name = str(function.get("name", "")).strip() - if name: - return { - "type": "function", - "name": internal_to_api.get(name, name), - } - return tool_choice + if choice_type != "function": + return tool_choice, None + + name = "" + function = tool_choice.get("function") + if isinstance(function, dict): + name = str(function.get("name", "")).strip() + elif tool_choice.get("name") is not None: + name = str(tool_choice.get("name", "")).strip() + + if not name: + return "auto", None + + api_name = internal_to_api.get(name, name) + return "required", api_name def build_responses_request_body( @@ -329,10 +334,21 @@ def build_responses_request_body( if reasoning is not None: body["reasoning"] = reasoning if tools: - body["tools"] = _normalize_responses_tools(tools, internal_to_api) - body["tool_choice"] = _normalize_responses_tool_choice( + normalized_tools = _normalize_responses_tools(tools, internal_to_api) + normalized_tool_choice, selected_tool_name = _normalize_responses_tool_choice( tool_choice, internal_to_api ) + if selected_tool_name: + filtered_tools = [ + tool + for tool in normalized_tools + if str(tool.get("type", "")).strip().lower() == "function" + and str(tool.get("name", "")).strip() == selected_tool_name + ] + if filtered_tools: + normalized_tools = filtered_tools + body["tools"] = normalized_tools + body["tool_choice"] = normalized_tool_choice previous_response_id = "" start_index = 0 diff --git a/tests/test_llm_request_params.py b/tests/test_llm_request_params.py index 7bc31186..e7ec29db 100644 --- a/tests/test_llm_request_params.py +++ b/tests/test_llm_request_params.py @@ -199,10 +199,7 @@ async def test_responses_request_normalizes_tool_calls_and_usage() -> None: }, } ] - assert fake_client.responses.last_kwargs["tool_choice"] == { - "type": "function", - "name": "lookup", - } + assert fake_client.responses.last_kwargs["tool_choice"] == "required" assert fake_client.responses.last_kwargs["metadata"] == {"source": "config"} assert fake_client.responses.last_kwargs["extra_body"] == {"custom_flag": "on"} assert "thinking" not in fake_client.responses.last_kwargs @@ -408,10 +405,7 @@ async def test_responses_tools_and_tool_choice_use_sanitized_api_names() -> None }, } assert api_tool_name != "lookup.weather@bj" - assert fake_client.responses.last_kwargs["tool_choice"] == { - "type": "function", - "name": api_tool_name, - } + assert fake_client.responses.last_kwargs["tool_choice"] == "required" assert result["choices"][0]["message"]["tool_calls"][0]["function"]["name"] == ( "lookup.weather@bj" ) From 456288b9de1e01a98b6123cb299f079c66276e58 Mon Sep 17 00:00:00 2001 From: Null <1708213363@qq.com> Date: Sat, 7 Mar 2026 18:25:14 +0800 Subject: [PATCH 13/21] feat(ai): add responses tool choice compat switch --- config.toml.example | 15 +++ docs/configuration.md | 20 ++-- docs/openapi.md | 3 +- .../ai/transports/openai_transport.py | 12 ++- src/Undefined/api/app.py | 3 + src/Undefined/config/loader.py | 47 +++++++++- src/Undefined/config/models.py | 13 +++ src/Undefined/webui/static/js/config-form.js | 5 +- tests/test_config_request_params.py | 8 ++ tests/test_llm_request_params.py | 94 ++++++++++++++++++- tests/test_runtime_api_probes.py | 2 + tests/test_webui_render_toml.py | 2 + 12 files changed, 211 insertions(+), 13 deletions(-) diff --git a/config.toml.example b/config.toml.example index 4bd8c629..2a661f6d 100644 --- a/config.toml.example +++ b/config.toml.example @@ -110,6 +110,9 @@ thinking_include_budget = true # zh: 思维链工具调用兼容：启用后在多轮工具调用中回传 reasoning_content，避免部分模型返回 400。 # en: Thinking tool-call compatibility: pass back reasoning_content in multi-turn tool calls to avoid 400 errors from some models. thinking_tool_call_compat = true +# zh: Responses API 的 tool_choice 兼容模式：仅为兼容部分只接受字符串 tool_choice 的代理，上报为 "required" 并只保留目标工具。默认关闭。 +# en: Responses API tool_choice compatibility mode: for proxies that only accept string tool_choice, send "required" and keep only the selected tool. Disabled by default. +responses_tool_choice_compat = false # zh: 额外请求体参数（可选），可用于 temperature 或供应商私有参数。 # en: Extra request-body params (optional), e.g. temperature or vendor-specific fields. @@ -164,6 +167,9 @@ thinking_include_budget = true # zh: 思维链工具调用兼容：启用后在多轮工具调用中回传 reasoning_content，避免部分模型返回 400。 # en: Thinking tool-call compatibility: pass back reasoning_content in multi-turn tool calls to avoid 400 errors from some models. thinking_tool_call_compat = true +# zh: Responses API 的 tool_choice 兼容模式：仅为兼容部分只接受字符串 tool_choice 的代理，上报为 "required" 并只保留目标工具。默认关闭。 +# en: Responses API tool_choice compatibility mode: for proxies that only accept string tool_choice, send "required" and keep only the selected tool. Disabled by default. +responses_tool_choice_compat = false # zh: 额外请求体参数（可选），可用于 temperature 或供应商私有参数。 # en: Extra request-body params (optional), e.g. temperature or vendor-specific fields. @@ -211,6 +217,9 @@ thinking_include_budget = true # zh: 思维链工具调用兼容：启用后在多轮工具调用中回传 reasoning_content，避免部分模型返回 400。 # en: Thinking tool-call compatibility: pass back reasoning_content in multi-turn tool calls to avoid 400 errors from some models. thinking_tool_call_compat = true +# zh: Responses API 的 tool_choice 兼容模式：仅为兼容部分只接受字符串 tool_choice 的代理，上报为 "required" 并只保留目标工具。默认关闭。 +# en: Responses API tool_choice compatibility mode: for proxies that only accept string tool_choice, send "required" and keep only the selected tool. Disabled by default. +responses_tool_choice_compat = false # zh: 额外请求体参数（可选），可用于 temperature 或供应商私有参数。 # en: Extra request-body params (optional), e.g. temperature or vendor-specific fields. @@ -255,6 +264,9 @@ thinking_include_budget = true # zh: 思维链工具调用兼容：启用后在多轮工具调用中回传 reasoning_content，避免部分模型返回 400。 # en: Thinking tool-call compatibility: pass back reasoning_content in multi-turn tool calls to avoid 400 errors from some models. thinking_tool_call_compat = true +# zh: Responses API 的 tool_choice 兼容模式：仅为兼容部分只接受字符串 tool_choice 的代理，上报为 "required" 并只保留目标工具。默认关闭。 +# en: Responses API tool_choice compatibility mode: for proxies that only accept string tool_choice, send "required" and keep only the selected tool. Disabled by default. +responses_tool_choice_compat = false # zh: 额外请求体参数（可选），可用于 temperature 或供应商私有参数。 # en: Extra request-body params (optional), e.g. temperature or vendor-specific fields. @@ -312,6 +324,9 @@ thinking_include_budget = true # zh: 思维链工具调用兼容：启用后在多轮工具调用中回传 reasoning_content，避免部分模型返回 400。 # en: Thinking tool-call compatibility: pass back reasoning_content in multi-turn tool calls to avoid 400 errors from some models. thinking_tool_call_compat = true +# zh: Responses API 的 tool_choice 兼容模式：仅为兼容部分只接受字符串 tool_choice 的代理，上报为 "required" 并只保留目标工具。默认关闭。 +# en: Responses API tool_choice compatibility mode: for proxies that only accept string tool_choice, send "required" and keep only the selected tool. Disabled by default. +responses_tool_choice_compat = false # zh: 额外请求体参数（可选），可用于 temperature 或供应商私有参数。 # en: Extra request-body params (optional), e.g. temperature or vendor-specific fields. diff --git a/docs/configuration.md b/docs/configuration.md index 0d2dd1b0..16836232 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -150,6 +150,7 @@ model_name = "gpt-4o-mini" | `thinking_budget_tokens` | thinking 预算 | | `thinking_include_budget` | 是否发送 `budget_tokens` | | `thinking_tool_call_compat` | Tool Calls 兼容模式：在多轮工具调用中回填 `reasoning_content`；默认 `true` | +| `responses_tool_choice_compat` | `responses` 下的 `tool_choice` 兼容开关：对不支持对象型 `tool_choice` 的代理降级为字符串 `"required"`；默认 `false` | | `request_params` | 额外请求体参数（透传给模型 API，保留字段会忽略） | 请求模式说明： @@ -158,6 +159,8 @@ model_name = "gpt-4o-mini" - `reasoning_enabled=true` 时额外发送 `reasoning={ effort = ... }` - `api_mode="responses"`：走 `client.responses.create(...)` - 仅在 `reasoning_enabled=true` 时发送 `reasoning={ effort = ... }` + - `responses_tool_choice_compat=true` 时，会把指定函数的 `tool_choice` 降级为字符串 `"required"`，并只保留目标工具，用于兼容部分不完整代理 + - 关闭时使用官方对象格式：`{"type":"function","name":"..."}` - 旧式 `thinking_*` 不会下发到 `responses` `request_params` 说明： @@ -179,6 +182,7 @@ model_name = "gpt-4o-mini" - `reasoning_effort="medium"` - `thinking_budget_tokens=20000` - `thinking_tool_call_compat=true` +- `responses_tool_choice_compat=false` 补充： - 若上游只对 `/v1/responses` 识别自定义参数，可将 `api_mode` 切到 `responses`。 @@ -193,16 +197,17 @@ model_name = "gpt-4o-mini" - `reasoning_effort="medium"` - `thinking_budget_tokens=20000` - `thinking_tool_call_compat=true` +- `responses_tool_choice_compat=false` ### 4.4.4 `[models.security]` 安全模型 字段： - 额外开关：`enabled=true` -- 默认：`max_tokens=100`、`api_mode="chat_completions"`、`reasoning_enabled=false`、`reasoning_effort="medium"`、`thinking_budget_tokens=0`、`thinking_tool_call_compat=true` +- 默认：`max_tokens=100`、`api_mode="chat_completions"`、`reasoning_enabled=false`、`reasoning_effort="medium"`、`thinking_budget_tokens=0`、`thinking_tool_call_compat=true`、`responses_tool_choice_compat=false` 关键回退逻辑： - 若 `api_url/api_key/model_name` 任一缺失，会自动回退为 chat 模型（并告警）。 -- 回退时会继承 chat 的 `api_mode`、`reasoning_*` 与 `request_params`；旧 `thinking_*` 仍保持安全模型自身默认值。 +- 回退时会继承 chat 的 `api_mode`、`reasoning_*`、`responses_tool_choice_compat` 与 `request_params`；旧 `thinking_*` 仍保持安全模型自身默认值。 ### 4.4.5 `[models.agent]` Agent 执行模型 @@ -213,12 +218,13 @@ model_name = "gpt-4o-mini" - `reasoning_enabled=false` - `reasoning_effort="medium"` - `thinking_tool_call_compat=true` +- `responses_tool_choice_compat=false` ### 4.4.6 `[models.historian]` 史官模型 - 用于认知记忆后台改写。 - 若整个节缺失或为空：完整回退到 `models.agent`。 -- 若部分字段缺失：逐项继承 agent 配置，包括 `api_mode`、`reasoning_*`、`thinking_*` 与 `request_params`。 +- 若部分字段缺失：逐项继承 agent 配置，包括 `api_mode`、`reasoning_*`、`thinking_*`、`responses_tool_choice_compat` 与 `request_params`。 - `queue_interval_seconds<=0` 时回退到 agent 的间隔。 ### 4.4.7 模型池 @@ -240,7 +246,7 @@ model_name = "gpt-4o-mini" `models` 条目支持字段： - `model_name`（必填） - `api_url` / `api_key` / `max_tokens` / `queue_interval_seconds` -- `api_mode` / `reasoning_enabled` / `reasoning_effort` +- `api_mode` / `reasoning_enabled` / `reasoning_effort` / `responses_tool_choice_compat` - `thinking_*` / `request_params` - 以上可选字段缺省继承主模型 @@ -672,9 +678,9 @@ model_name = "gpt-4o-mini" - `BOT_QQ` / `SUPERADMIN_QQ` - `ONEBOT_WS_URL` / `ONEBOT_TOKEN` - `CHAT_MODEL_API_URL` / `CHAT_MODEL_API_KEY` / `CHAT_MODEL_NAME` -- `CHAT_MODEL_API_MODE` / `CHAT_MODEL_REASONING_ENABLED` / `CHAT_MODEL_REASONING_EFFORT` -- `VISION_MODEL_*` / `AGENT_MODEL_*` / `SECURITY_MODEL_*` -- 上述模型环境变量同样覆盖 `*_THINKING_ENABLED`、`*_THINKING_BUDGET_TOKENS`、`*_THINKING_TOOL_CALL_COMPAT` +- `CHAT_MODEL_API_MODE` / `CHAT_MODEL_REASONING_ENABLED` / `CHAT_MODEL_REASONING_EFFORT` / `CHAT_MODEL_RESPONSES_TOOL_CHOICE_COMPAT` +- `VISION_MODEL_*` / `AGENT_MODEL_*` / `SECURITY_MODEL_*` / `HISTORIAN_MODEL_*` +- 上述模型环境变量同样覆盖 `*_THINKING_ENABLED`、`*_THINKING_BUDGET_TOKENS`、`*_THINKING_TOOL_CALL_COMPAT`、`*_RESPONSES_TOOL_CHOICE_COMPAT` - `EMBEDDING_MODEL_*` / `RERANK_MODEL_*` - `SEARXNG_URL` - `HTTP_PROXY` / `HTTPS_PROXY` diff --git a/docs/openapi.md b/docs/openapi.md index eca5d6df..5ea73def 100644 --- a/docs/openapi.md +++ b/docs/openapi.md @@ -79,7 +79,7 @@ curl http://127.0.0.1:8788/openapi.json | `cognitive` | `object` | 认知服务（`enabled`、`queue`） | | `api` | `object` | Runtime API 配置（`enabled`、`host`、`port`、`openapi_enabled`） | | `skills` | `object` | 技能统计，包含 `tools`、`agents`、`anthropic_skills` 三个子对象 | -| `models` | `object` | 模型配置；聊天类模型包含 `model_name`、脱敏 `api_url`、`api_mode`、`thinking_enabled`、`thinking_tool_call_compat`、`reasoning_enabled`、`reasoning_effort` | +| `models` | `object` | 模型配置；聊天类模型包含 `model_name`、脱敏 `api_url`、`api_mode`、`thinking_enabled`、`thinking_tool_call_compat`、`responses_tool_choice_compat`、`reasoning_enabled`、`reasoning_effort` | `skills` 子对象结构： @@ -103,6 +103,7 @@ curl http://127.0.0.1:8788/openapi.json "api_mode": "responses", "thinking_enabled": false, "thinking_tool_call_compat": true, + "responses_tool_choice_compat": false, "reasoning_enabled": true, "reasoning_effort": "high" }, diff --git a/src/Undefined/ai/transports/openai_transport.py b/src/Undefined/ai/transports/openai_transport.py index 3593774d..10cdc7e1 100644 --- a/src/Undefined/ai/transports/openai_transport.py +++ b/src/Undefined/ai/transports/openai_transport.py @@ -294,6 +294,8 @@ def _normalize_responses_tools( def _normalize_responses_tool_choice( tool_choice: Any, internal_to_api: dict[str, str], + *, + compat_mode: bool = False, ) -> tuple[Any, str | None]: if not isinstance(tool_choice, dict): return tool_choice, None @@ -312,7 +314,9 @@ def _normalize_responses_tool_choice( return "auto", None api_name = internal_to_api.get(name, name) - return "required", api_name + if compat_mode: + return "required", api_name + return {"type": "function", "name": api_name}, None def build_responses_request_body( @@ -336,7 +340,11 @@ def build_responses_request_body( if tools: normalized_tools = _normalize_responses_tools(tools, internal_to_api) normalized_tool_choice, selected_tool_name = _normalize_responses_tool_choice( - tool_choice, internal_to_api + tool_choice, + internal_to_api, + compat_mode=bool( + getattr(model_config, "responses_tool_choice_compat", False) + ), ) if selected_tool_name: filtered_tools = [ diff --git a/src/Undefined/api/app.py b/src/Undefined/api/app.py index 3cf11c45..09618ae8 100644 --- a/src/Undefined/api/app.py +++ b/src/Undefined/api/app.py @@ -528,6 +528,9 @@ async def _internal_probe_handler(self, request: web.Request) -> Response: "thinking_tool_call_compat": getattr( mcfg, "thinking_tool_call_compat", True ), + "responses_tool_choice_compat": getattr( + mcfg, "responses_tool_choice_compat", False + ), "reasoning_enabled": getattr(mcfg, "reasoning_enabled", False), "reasoning_effort": getattr(mcfg, "reasoning_effort", "medium"), } diff --git a/src/Undefined/config/loader.py b/src/Undefined/config/loader.py index 85431446..0548c1f8 100644 --- a/src/Undefined/config/loader.py +++ b/src/Undefined/config/loader.py @@ -316,6 +316,22 @@ def _resolve_reasoning_effort(value: Any, default: str = "medium") -> str: return effort +def _resolve_responses_tool_choice_compat( + data: dict[str, Any], + model_name: str, + env_key: str, + default: bool = False, +) -> bool: + return _coerce_bool( + _get_value( + data, + ("models", model_name, "responses_tool_choice_compat"), + env_key, + ), + default, + ) + + def load_local_admins() -> list[int]: """从本地配置文件加载动态管理员列表""" if not LOCAL_CONFIG_PATH.exists(): @@ -1559,6 +1575,10 @@ def _parse_model_pool( item.get("thinking_tool_call_compat"), primary_config.thinking_tool_call_compat, ), + responses_tool_choice_compat=_coerce_bool( + item.get("responses_tool_choice_compat"), + primary_config.responses_tool_choice_compat, + ), reasoning_enabled=_coerce_bool( item.get("reasoning_enabled"), primary_config.reasoning_enabled, @@ -1673,6 +1693,9 @@ def _parse_chat_model_config(data: dict[str, Any]) -> ChatModelConfig: ) ) api_mode = _resolve_api_mode(data, "chat", "CHAT_MODEL_API_MODE") + responses_tool_choice_compat = _resolve_responses_tool_choice_compat( + data, "chat", "CHAT_MODEL_RESPONSES_TOOL_CHOICE_COMPAT" + ) reasoning_enabled = _coerce_bool( _get_value( data, @@ -1728,6 +1751,7 @@ def _parse_chat_model_config(data: dict[str, Any]) -> ChatModelConfig: ), thinking_include_budget=thinking_include_budget, thinking_tool_call_compat=thinking_tool_call_compat, + responses_tool_choice_compat=responses_tool_choice_compat, reasoning_enabled=reasoning_enabled, reasoning_effort=reasoning_effort, request_params=_get_model_request_params(data, "chat"), @@ -1757,6 +1781,9 @@ def _parse_vision_model_config(data: dict[str, Any]) -> VisionModelConfig: ) ) api_mode = _resolve_api_mode(data, "vision", "VISION_MODEL_API_MODE") + responses_tool_choice_compat = _resolve_responses_tool_choice_compat( + data, "vision", "VISION_MODEL_RESPONSES_TOOL_CHOICE_COMPAT" + ) reasoning_enabled = _coerce_bool( _get_value( data, @@ -1812,6 +1839,7 @@ def _parse_vision_model_config(data: dict[str, Any]) -> VisionModelConfig: ), thinking_include_budget=thinking_include_budget, thinking_tool_call_compat=thinking_tool_call_compat, + responses_tool_choice_compat=responses_tool_choice_compat, reasoning_enabled=reasoning_enabled, reasoning_effort=reasoning_effort, request_params=_get_model_request_params(data, "vision"), @@ -1860,6 +1888,9 @@ def _parse_security_model_config( ) ) api_mode = _resolve_api_mode(data, "security", "SECURITY_MODEL_API_MODE") + responses_tool_choice_compat = _resolve_responses_tool_choice_compat( + data, "security", "SECURITY_MODEL_RESPONSES_TOOL_CHOICE_COMPAT" + ) reasoning_enabled = _coerce_bool( _get_value( data, @@ -1910,6 +1941,7 @@ def _parse_security_model_config( ), thinking_include_budget=thinking_include_budget, thinking_tool_call_compat=thinking_tool_call_compat, + responses_tool_choice_compat=responses_tool_choice_compat, reasoning_enabled=reasoning_enabled, reasoning_effort=reasoning_effort, request_params=_get_model_request_params(data, "security"), @@ -1927,6 +1959,7 @@ def _parse_security_model_config( thinking_budget_tokens=0, thinking_include_budget=True, thinking_tool_call_compat=chat_model.thinking_tool_call_compat, + responses_tool_choice_compat=chat_model.responses_tool_choice_compat, reasoning_enabled=chat_model.reasoning_enabled, reasoning_effort=chat_model.reasoning_effort, request_params=merge_request_params(chat_model.request_params), @@ -1954,6 +1987,9 @@ def _parse_agent_model_config(data: dict[str, Any]) -> AgentModelConfig: ) ) api_mode = _resolve_api_mode(data, "agent", "AGENT_MODEL_API_MODE") + responses_tool_choice_compat = _resolve_responses_tool_choice_compat( + data, "agent", "AGENT_MODEL_RESPONSES_TOOL_CHOICE_COMPAT" + ) reasoning_enabled = _coerce_bool( _get_value( data, @@ -2009,6 +2045,7 @@ def _parse_agent_model_config(data: dict[str, Any]) -> AgentModelConfig: ), thinking_include_budget=thinking_include_budget, thinking_tool_call_compat=thinking_tool_call_compat, + responses_tool_choice_compat=responses_tool_choice_compat, reasoning_enabled=reasoning_enabled, reasoning_effort=reasoning_effort, request_params=_get_model_request_params(data, "agent"), @@ -2093,7 +2130,7 @@ def _log_debug_info( ] for name, cfg in configs: logger.debug( - "[配置] %s_model=%s api_url=%s api_key_set=%s api_mode=%s thinking=%s reasoning=%s/%s cot_compat=%s", + "[配置] %s_model=%s api_url=%s api_key_set=%s api_mode=%s thinking=%s reasoning=%s/%s cot_compat=%s responses_tool_choice_compat=%s", name, cfg.model_name, cfg.api_url, @@ -2103,6 +2140,7 @@ def _log_debug_info( getattr(cfg, "reasoning_enabled", False), getattr(cfg, "reasoning_effort", "medium"), getattr(cfg, "thinking_tool_call_compat", False), + getattr(cfg, "responses_tool_choice_compat", False), ) def update_from(self, new_config: "Config") -> dict[str, tuple[Any, Any]]: @@ -2154,6 +2192,12 @@ def _parse_historian_model_config( "HISTORIAN_MODEL_API_MODE", fallback.api_mode, ) + responses_tool_choice_compat = _resolve_responses_tool_choice_compat( + {"models": {"historian": h}}, + "historian", + "HISTORIAN_MODEL_RESPONSES_TOOL_CHOICE_COMPAT", + fallback.responses_tool_choice_compat, + ) return AgentModelConfig( api_url=_coerce_str(h.get("api_url"), fallback.api_url), api_key=_coerce_str(h.get("api_key"), fallback.api_key), @@ -2169,6 +2213,7 @@ def _parse_historian_model_config( ), thinking_include_budget=thinking_include_budget, thinking_tool_call_compat=thinking_tool_call_compat, + responses_tool_choice_compat=responses_tool_choice_compat, reasoning_enabled=_coerce_bool( _get_value( {"models": {"historian": h}}, diff --git a/src/Undefined/config/models.py b/src/Undefined/config/models.py index 7269c70b..6b403c5f 100644 --- a/src/Undefined/config/models.py +++ b/src/Undefined/config/models.py @@ -20,6 +20,7 @@ class ModelPoolEntry: thinking_budget_tokens: int = 0 thinking_include_budget: bool = True thinking_tool_call_compat: bool = True + responses_tool_choice_compat: bool = False reasoning_enabled: bool = False reasoning_effort: str = "medium" request_params: dict[str, Any] = field(default_factory=dict) @@ -50,6 +51,9 @@ class ChatModelConfig: thinking_tool_call_compat: bool = ( True # 思维链 + 工具调用兼容（回传 reasoning_content） ) + responses_tool_choice_compat: bool = ( + False # Responses API 的 tool_choice 兼容模式（降级为字符串 required） + ) reasoning_enabled: bool = False # 是否启用 reasoning.effort reasoning_effort: str = "medium" # reasoning effort 档位 request_params: dict[str, Any] = field(default_factory=dict) @@ -71,6 +75,9 @@ class VisionModelConfig: thinking_tool_call_compat: bool = ( True # 思维链 + 工具调用兼容（回传 reasoning_content） ) + responses_tool_choice_compat: bool = ( + False # Responses API 的 tool_choice 兼容模式（降级为字符串 required） + ) reasoning_enabled: bool = False # 是否启用 reasoning.effort reasoning_effort: str = "medium" # reasoning effort 档位 request_params: dict[str, Any] = field(default_factory=dict) @@ -92,6 +99,9 @@ class SecurityModelConfig: thinking_tool_call_compat: bool = ( True # 思维链 + 工具调用兼容（回传 reasoning_content） ) + responses_tool_choice_compat: bool = ( + False # Responses API 的 tool_choice 兼容模式（降级为字符串 required） + ) reasoning_enabled: bool = False # 是否启用 reasoning.effort reasoning_effort: str = "medium" # reasoning effort 档位 request_params: dict[str, Any] = field(default_factory=dict) @@ -139,6 +149,9 @@ class AgentModelConfig: thinking_tool_call_compat: bool = ( True # 思维链 + 工具调用兼容（回传 reasoning_content） ) + responses_tool_choice_compat: bool = ( + False # Responses API 的 tool_choice 兼容模式（降级为字符串 required） + ) reasoning_enabled: bool = False # 是否启用 reasoning.effort reasoning_effort: str = "medium" # reasoning effort 档位 request_params: dict[str, Any] = field(default_factory=dict) diff --git a/src/Undefined/webui/static/js/config-form.js b/src/Undefined/webui/static/js/config-form.js index 59c64350..dfd64421 100644 --- a/src/Undefined/webui/static/js/config-form.js +++ b/src/Undefined/webui/static/js/config-form.js @@ -768,6 +768,9 @@ function buildAotTemplate(path, arr) { if (!Object.prototype.hasOwnProperty.call(template, "thinking_tool_call_compat")) { template.thinking_tool_call_compat = true } + if (!Object.prototype.hasOwnProperty.call(template, "responses_tool_choice_compat")) { + template.responses_tool_choice_compat = false + } if (!Object.prototype.hasOwnProperty.call(template, "reasoning_enabled")) { template.reasoning_enabled = false } @@ -777,7 +780,7 @@ function buildAotTemplate(path, arr) { } return template } - return { model_name: "", api_url: "", api_key: "", api_mode: "chat_completions", thinking_tool_call_compat: true, reasoning_enabled: false, reasoning_effort: "medium", request_params: {} } + return { model_name: "", api_url: "", api_key: "", api_mode: "chat_completions", thinking_tool_call_compat: true, responses_tool_choice_compat: false, reasoning_enabled: false, reasoning_effort: "medium", request_params: {} } } function createAotWidget(path, arr) { diff --git a/tests/test_config_request_params.py b/tests/test_config_request_params.py index c36afde8..8a5d077d 100644 --- a/tests/test_config_request_params.py +++ b/tests/test_config_request_params.py @@ -26,6 +26,7 @@ def test_model_request_params_load_inherit_and_new_transport_fields( api_mode = "responses" reasoning_enabled = true reasoning_effort = "high" +responses_tool_choice_compat = true [models.chat.request_params] temperature = 0.2 @@ -54,6 +55,7 @@ def test_model_request_params_load_inherit_and_new_transport_fields( api_mode = "responses" reasoning_enabled = true reasoning_effort = "minimal" +responses_tool_choice_compat = true [models.agent.request_params] temperature = 0.3 @@ -92,6 +94,7 @@ def test_model_request_params_load_inherit_and_new_transport_fields( assert cfg.chat_model.reasoning_enabled is True assert cfg.chat_model.reasoning_effort == "high" assert cfg.chat_model.thinking_tool_call_compat is True + assert cfg.chat_model.responses_tool_choice_compat is True assert cfg.chat_model.request_params == { "temperature": 0.2, "metadata": {"source": "chat"}, @@ -102,6 +105,7 @@ def test_model_request_params_load_inherit_and_new_transport_fields( assert cfg.chat_model.pool.models[0].reasoning_enabled is False assert cfg.chat_model.pool.models[0].reasoning_effort == "low" assert cfg.chat_model.pool.models[0].thinking_tool_call_compat is True + assert cfg.chat_model.pool.models[0].responses_tool_choice_compat is True assert cfg.chat_model.pool.models[0].request_params == { "temperature": 0.6, "metadata": {"source": "chat"}, @@ -112,17 +116,20 @@ def test_model_request_params_load_inherit_and_new_transport_fields( assert cfg.security_model.reasoning_enabled == cfg.chat_model.reasoning_enabled assert cfg.security_model.reasoning_effort == cfg.chat_model.reasoning_effort assert cfg.security_model.thinking_tool_call_compat is True + assert cfg.security_model.responses_tool_choice_compat is True assert cfg.security_model.request_params == cfg.chat_model.request_params assert cfg.agent_model.api_mode == "responses" assert cfg.agent_model.reasoning_enabled is True assert cfg.agent_model.reasoning_effort == "minimal" assert cfg.agent_model.thinking_tool_call_compat is True + assert cfg.agent_model.responses_tool_choice_compat is True assert cfg.historian_model.api_mode == "chat_completions" assert cfg.historian_model.reasoning_enabled is True assert cfg.historian_model.reasoning_effort == "xhigh" assert cfg.historian_model.thinking_tool_call_compat is True + assert cfg.historian_model.responses_tool_choice_compat is True assert cfg.historian_model.request_params == { "temperature": 0.1, "metadata": {"source": "historian"}, @@ -134,3 +141,4 @@ def test_model_request_params_load_inherit_and_new_transport_fields( "metadata": {"source": "embed"}, } assert cfg.rerank_model.request_params == {"priority": "high"} + assert cfg.vision_model.responses_tool_choice_compat is False diff --git a/tests/test_llm_request_params.py b/tests/test_llm_request_params.py index e7ec29db..971f5acc 100644 --- a/tests/test_llm_request_params.py +++ b/tests/test_llm_request_params.py @@ -199,7 +199,10 @@ async def test_responses_request_normalizes_tool_calls_and_usage() -> None: }, } ] - assert fake_client.responses.last_kwargs["tool_choice"] == "required" + assert fake_client.responses.last_kwargs["tool_choice"] == { + "type": "function", + "name": "lookup", + } assert fake_client.responses.last_kwargs["metadata"] == {"source": "config"} assert fake_client.responses.last_kwargs["extra_body"] == {"custom_flag": "on"} assert "thinking" not in fake_client.responses.last_kwargs @@ -222,6 +225,94 @@ async def test_responses_request_normalizes_tool_calls_and_usage() -> None: await requester._http_client.aclose() +@pytest.mark.asyncio +async def test_responses_tool_choice_compat_mode_uses_required_string() -> None: + requester = ModelRequester( + http_client=httpx.AsyncClient(), + token_usage_storage=cast(TokenUsageStorage, _FakeUsageStorage()), + ) + fake_client = _FakeClient( + responses=[ + { + "id": "resp_compat", + "output": [ + { + "type": "function_call", + "call_id": "call_compat", + "name": "lookup", + "arguments": '{"query": "weather"}', + } + ], + "usage": {"input_tokens": 5, "output_tokens": 4, "total_tokens": 9}, + } + ] + ) + setattr( + requester, + "_get_openai_client_for_model", + lambda _cfg: cast(AsyncOpenAI, fake_client), + ) + cfg = ChatModelConfig( + api_url="https://api.openai.com/v1", + api_key="sk-test", + model_name="gpt-test", + max_tokens=512, + api_mode="responses", + responses_tool_choice_compat=True, + ) + + await requester.request( + model_config=cfg, + messages=[{"role": "user", "content": "hello"}], + max_tokens=128, + call_type="chat", + tools=[ + { + "type": "function", + "function": { + "name": "lookup", + "description": "lookup weather", + "parameters": { + "type": "object", + "properties": {"query": {"type": "string"}}, + "required": ["query"], + }, + }, + }, + { + "type": "function", + "function": { + "name": "search", + "description": "search docs", + "parameters": { + "type": "object", + "properties": {"query": {"type": "string"}}, + "required": ["query"], + }, + }, + }, + ], + tool_choice=cast(Any, {"type": "function", "function": {"name": "lookup"}}), + ) + + assert fake_client.responses.last_kwargs is not None + assert fake_client.responses.last_kwargs["tool_choice"] == "required" + assert fake_client.responses.last_kwargs["tools"] == [ + { + "type": "function", + "name": "lookup", + "description": "lookup weather", + "parameters": { + "type": "object", + "properties": {"query": {"type": "string"}}, + "required": ["query"], + }, + } + ] + + await requester._http_client.aclose() + + @pytest.mark.asyncio async def test_responses_transport_state_uses_previous_response_id_and_tool_outputs() -> ( None @@ -364,6 +455,7 @@ async def test_responses_tools_and_tool_choice_use_sanitized_api_names() -> None model_name="gpt-test", max_tokens=512, api_mode="responses", + responses_tool_choice_compat=True, ) result = await requester.request( diff --git a/tests/test_runtime_api_probes.py b/tests/test_runtime_api_probes.py index da1f6783..c39817d6 100644 --- a/tests/test_runtime_api_probes.py +++ b/tests/test_runtime_api_probes.py @@ -27,6 +27,7 @@ async def test_runtime_internal_probe_includes_chat_model_transport_fields() -> api_mode="responses", thinking_enabled=False, thinking_tool_call_compat=True, + responses_tool_choice_compat=False, reasoning_enabled=True, reasoning_effort="high", ), @@ -56,6 +57,7 @@ async def test_runtime_internal_probe_includes_chat_model_transport_fields() -> "api_mode": "responses", "thinking_enabled": False, "thinking_tool_call_compat": True, + "responses_tool_choice_compat": False, "reasoning_enabled": True, "reasoning_effort": "high", } diff --git a/tests/test_webui_render_toml.py b/tests/test_webui_render_toml.py index 60e4882c..00c329bd 100644 --- a/tests/test_webui_render_toml.py +++ b/tests/test_webui_render_toml.py @@ -71,6 +71,7 @@ def test_pool_model_request_params_roundtrip(self) -> None: api_key = "sk-a" api_mode = "responses" thinking_tool_call_compat = true +responses_tool_choice_compat = true reasoning_enabled = true reasoning_effort = "high" @@ -90,6 +91,7 @@ def test_pool_model_request_params_roundtrip(self) -> None: model = data["models"]["chat"]["pool"]["models"][0] assert model["api_mode"] == "responses" assert model["thinking_tool_call_compat"] is True + assert model["responses_tool_choice_compat"] is True assert model["reasoning_enabled"] is True assert model["reasoning_effort"] == "high" params = model["request_params"] From 66eede2da97852482f28c370ace2da2367fe97f7 Mon Sep 17 00:00:00 2001 From: Null <1708213363@qq.com> Date: Sat, 7 Mar 2026 18:37:30 +0800 Subject: [PATCH 14/21] docs(config): clarify responses compat usage --- config.toml.example | 20 ++++++++++---------- docs/configuration.md | 6 ++++-- docs/openapi.md | 2 ++ 3 files changed, 16 insertions(+), 12 deletions(-) diff --git a/config.toml.example b/config.toml.example index 2a661f6d..ea749aaf 100644 --- a/config.toml.example +++ b/config.toml.example @@ -110,8 +110,8 @@ thinking_include_budget = true # zh: 思维链工具调用兼容：启用后在多轮工具调用中回传 reasoning_content，避免部分模型返回 400。 # en: Thinking tool-call compatibility: pass back reasoning_content in multi-turn tool calls to avoid 400 errors from some models. thinking_tool_call_compat = true -# zh: Responses API 的 tool_choice 兼容模式：仅为兼容部分只接受字符串 tool_choice 的代理，上报为 "required" 并只保留目标工具。默认关闭。 -# en: Responses API tool_choice compatibility mode: for proxies that only accept string tool_choice, send "required" and keep only the selected tool. Disabled by default. +# zh: Responses API 的 tool_choice 兼容模式：仅在关闭时请求仍返回 500、怀疑上游不兼容对象型 tool_choice 时再尝试开启；开启后上报为 "required" 并只保留目标工具。当前已在 new-api v0.11.4-alpha.3 发现该问题。默认关闭。 +# en: Responses API tool_choice compatibility mode: only try enabling this when requests still return 500 with the default setting and you suspect the upstream does not support object-style tool_choice; it sends "required" and keeps only the selected tool. This issue is currently observed on new-api v0.11.4-alpha.3. Disabled by default. responses_tool_choice_compat = false # zh: 额外请求体参数（可选），可用于 temperature 或供应商私有参数。 @@ -167,8 +167,8 @@ thinking_include_budget = true # zh: 思维链工具调用兼容：启用后在多轮工具调用中回传 reasoning_content，避免部分模型返回 400。 # en: Thinking tool-call compatibility: pass back reasoning_content in multi-turn tool calls to avoid 400 errors from some models. thinking_tool_call_compat = true -# zh: Responses API 的 tool_choice 兼容模式：仅为兼容部分只接受字符串 tool_choice 的代理，上报为 "required" 并只保留目标工具。默认关闭。 -# en: Responses API tool_choice compatibility mode: for proxies that only accept string tool_choice, send "required" and keep only the selected tool. Disabled by default. +# zh: Responses API 的 tool_choice 兼容模式：仅在关闭时请求仍返回 500、怀疑上游不兼容对象型 tool_choice 时再尝试开启；开启后上报为 "required" 并只保留目标工具。当前已在 new-api v0.11.4-alpha.3 发现该问题。默认关闭。 +# en: Responses API tool_choice compatibility mode: only try enabling this when requests still return 500 with the default setting and you suspect the upstream does not support object-style tool_choice; it sends "required" and keeps only the selected tool. This issue is currently observed on new-api v0.11.4-alpha.3. Disabled by default. responses_tool_choice_compat = false # zh: 额外请求体参数（可选），可用于 temperature 或供应商私有参数。 @@ -217,8 +217,8 @@ thinking_include_budget = true # zh: 思维链工具调用兼容：启用后在多轮工具调用中回传 reasoning_content，避免部分模型返回 400。 # en: Thinking tool-call compatibility: pass back reasoning_content in multi-turn tool calls to avoid 400 errors from some models. thinking_tool_call_compat = true -# zh: Responses API 的 tool_choice 兼容模式：仅为兼容部分只接受字符串 tool_choice 的代理，上报为 "required" 并只保留目标工具。默认关闭。 -# en: Responses API tool_choice compatibility mode: for proxies that only accept string tool_choice, send "required" and keep only the selected tool. Disabled by default. +# zh: Responses API 的 tool_choice 兼容模式：仅在关闭时请求仍返回 500、怀疑上游不兼容对象型 tool_choice 时再尝试开启；开启后上报为 "required" 并只保留目标工具。当前已在 new-api v0.11.4-alpha.3 发现该问题。默认关闭。 +# en: Responses API tool_choice compatibility mode: only try enabling this when requests still return 500 with the default setting and you suspect the upstream does not support object-style tool_choice; it sends "required" and keeps only the selected tool. This issue is currently observed on new-api v0.11.4-alpha.3. Disabled by default. responses_tool_choice_compat = false # zh: 额外请求体参数（可选），可用于 temperature 或供应商私有参数。 @@ -264,8 +264,8 @@ thinking_include_budget = true # zh: 思维链工具调用兼容：启用后在多轮工具调用中回传 reasoning_content，避免部分模型返回 400。 # en: Thinking tool-call compatibility: pass back reasoning_content in multi-turn tool calls to avoid 400 errors from some models. thinking_tool_call_compat = true -# zh: Responses API 的 tool_choice 兼容模式：仅为兼容部分只接受字符串 tool_choice 的代理，上报为 "required" 并只保留目标工具。默认关闭。 -# en: Responses API tool_choice compatibility mode: for proxies that only accept string tool_choice, send "required" and keep only the selected tool. Disabled by default. +# zh: Responses API 的 tool_choice 兼容模式：仅在关闭时请求仍返回 500、怀疑上游不兼容对象型 tool_choice 时再尝试开启；开启后上报为 "required" 并只保留目标工具。当前已在 new-api v0.11.4-alpha.3 发现该问题。默认关闭。 +# en: Responses API tool_choice compatibility mode: only try enabling this when requests still return 500 with the default setting and you suspect the upstream does not support object-style tool_choice; it sends "required" and keeps only the selected tool. This issue is currently observed on new-api v0.11.4-alpha.3. Disabled by default. responses_tool_choice_compat = false # zh: 额外请求体参数（可选），可用于 temperature 或供应商私有参数。 @@ -324,8 +324,8 @@ thinking_include_budget = true # zh: 思维链工具调用兼容：启用后在多轮工具调用中回传 reasoning_content，避免部分模型返回 400。 # en: Thinking tool-call compatibility: pass back reasoning_content in multi-turn tool calls to avoid 400 errors from some models. thinking_tool_call_compat = true -# zh: Responses API 的 tool_choice 兼容模式：仅为兼容部分只接受字符串 tool_choice 的代理，上报为 "required" 并只保留目标工具。默认关闭。 -# en: Responses API tool_choice compatibility mode: for proxies that only accept string tool_choice, send "required" and keep only the selected tool. Disabled by default. +# zh: Responses API 的 tool_choice 兼容模式：仅在关闭时请求仍返回 500、怀疑上游不兼容对象型 tool_choice 时再尝试开启；开启后上报为 "required" 并只保留目标工具。当前已在 new-api v0.11.4-alpha.3 发现该问题。默认关闭。 +# en: Responses API tool_choice compatibility mode: only try enabling this when requests still return 500 with the default setting and you suspect the upstream does not support object-style tool_choice; it sends "required" and keeps only the selected tool. This issue is currently observed on new-api v0.11.4-alpha.3. Disabled by default. responses_tool_choice_compat = false # zh: 额外请求体参数（可选），可用于 temperature 或供应商私有参数。 diff --git a/docs/configuration.md b/docs/configuration.md index 16836232..ddf937c3 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -150,7 +150,7 @@ model_name = "gpt-4o-mini" | `thinking_budget_tokens` | thinking 预算 | | `thinking_include_budget` | 是否发送 `budget_tokens` | | `thinking_tool_call_compat` | Tool Calls 兼容模式：在多轮工具调用中回填 `reasoning_content`；默认 `true` | -| `responses_tool_choice_compat` | `responses` 下的 `tool_choice` 兼容开关：对不支持对象型 `tool_choice` 的代理降级为字符串 `"required"`；默认 `false` | +| `responses_tool_choice_compat` | `responses` 下的 `tool_choice` 兼容开关：仅建议在默认关闭时请求仍返回 500、怀疑上游不兼容对象型 `tool_choice` 时再尝试开启；开启后降级为字符串 `"required"`；默认 `false` | | `request_params` | 额外请求体参数（透传给模型 API，保留字段会忽略） | 请求模式说明： @@ -159,8 +159,10 @@ model_name = "gpt-4o-mini" - `reasoning_enabled=true` 时额外发送 `reasoning={ effort = ... }` - `api_mode="responses"`：走 `client.responses.create(...)` - 仅在 `reasoning_enabled=true` 时发送 `reasoning={ effort = ... }` + - 默认使用官方对象格式：`{"type":"function","name":"..."}` - `responses_tool_choice_compat=true` 时，会把指定函数的 `tool_choice` 降级为字符串 `"required"`，并只保留目标工具，用于兼容部分不完整代理 - - 关闭时使用官方对象格式：`{"type":"function","name":"..."}` + - 仅建议在默认关闭时请求仍返回 500，再尝试开启该兼容开关 + - 当前已知 `new-api v0.11.4-alpha.3` 存在这类兼容问题 - 旧式 `thinking_*` 不会下发到 `responses` `request_params` 说明： diff --git a/docs/openapi.md b/docs/openapi.md index 5ea73def..1360406c 100644 --- a/docs/openapi.md +++ b/docs/openapi.md @@ -111,6 +111,8 @@ curl http://127.0.0.1:8788/openapi.json } ``` +说明：`responses_tool_choice_compat` 通常保持 `false`；仅建议在 `responses` 请求默认配置下仍返回 `500` 时再尝试开启。当前已知 `new-api v0.11.4-alpha.3` 存在该兼容问题。 + #### 外部探针响应字段 | 字段 | 类型 | 说明 | From f137cbd32f57c44e033a11a21af51c5270f1e889 Mon Sep 17 00:00:00 2001 From: Null <1708213363@qq.com> Date: Sat, 7 Mar 2026 19:32:47 +0800 Subject: [PATCH 15/21] fix(ai): fallback responses tool followups to replay --- src/Undefined/ai/llm.py | 79 ++++++++- .../ai/transports/openai_transport.py | 6 +- tests/test_llm_request_params.py | 152 +++++++++++++++++- 3 files changed, 229 insertions(+), 8 deletions(-) diff --git a/src/Undefined/ai/llm.py b/src/Undefined/ai/llm.py index 0b584846..9cec9a34 100644 --- a/src/Undefined/ai/llm.py +++ b/src/Undefined/ai/llm.py @@ -155,6 +155,10 @@ _DEFAULT_TOOLS_DESCRIPTION_MAX_LEN = 1024 _TOOLS_PARAM_INDEX_RE = re.compile(r"Tools\[(\d+)\]", re.IGNORECASE) +_RESPONSES_MISSING_TOOL_CALL_OUTPUT_RE = re.compile( + r"no tool call found for function call output with call_id", + re.IGNORECASE, +) _DEFAULT_TOOLS_DESCRIPTION_PREVIEW_LEN = 160 _DEFAULT_TOOL_NAME_DOT_DELIMITER = "-_-" @@ -227,6 +231,32 @@ def _encode_tool_name_for_api(tool_name: str) -> str: return encoded +def _responses_should_fallback_to_stateless_replay( + exc: APIStatusError, + request_body: dict[str, Any], + *, + stateless_replay: bool, +) -> bool: + if stateless_replay or not request_body.get("previous_response_id"): + return False + input_items = request_body.get("input") + if not isinstance(input_items, list) or not any( + isinstance(item, dict) and item.get("type") == "function_call_output" + for item in input_items + ): + return False + if exc.status_code != 400 or not isinstance(exc.body, dict): + return False + error = exc.body.get("error") + if not isinstance(error, dict): + return False + message = str(error.get("message", "")).strip() + param = str(error.get("param", "")).strip().lower() + return param == "input" and bool( + _RESPONSES_MISSING_TOOL_CALL_OUTPUT_RE.search(message) + ) + + def _sanitize_openai_tool_names_in_request( request_body: dict[str, Any], ) -> tuple[dict[str, str], dict[str, str]]: @@ -960,6 +990,11 @@ async def request( call_type=call_type, overrides=dict(kwargs), ) + responses_stateless_replay = bool( + isinstance(transport_state, dict) + and transport_state.get("stateless_replay") + ) + effective_transport_state = transport_state request_body = build_request_body( model_config=model_config, messages=messages_for_api, @@ -967,7 +1002,7 @@ async def request( tools=tools_for_api, tool_choice=tool_choice, internal_to_api=internal_to_api, - transport_state=transport_state, + transport_state=effective_transport_state, **effective_kwargs, ) @@ -998,7 +1033,45 @@ async def request( ) log_debug_json(logger, "[API请求体]", request_body) - raw_result = await self._request_with_openai(model_config, request_body) + try: + raw_result = await self._request_with_openai(model_config, request_body) + except APIStatusError as exc: + if ( + api_mode == API_MODE_RESPONSES + and _responses_should_fallback_to_stateless_replay( + exc, + request_body, + stateless_replay=responses_stateless_replay, + ) + ): + logger.warning( + "[responses.compat] previous_response_id 续轮失败，自动降级为 stateless replay: model=%s call_type=%s previous_response_id=%s", + model_config.model_name, + call_type, + request_body.get("previous_response_id", ""), + ) + effective_transport_state = dict(effective_transport_state or {}) + effective_transport_state["stateless_replay"] = True + responses_stateless_replay = True + request_body = build_request_body( + model_config=model_config, + messages=messages_for_api, + max_tokens=max_tokens, + tools=tools_for_api, + tool_choice=tool_choice, + internal_to_api=internal_to_api, + transport_state=effective_transport_state, + **effective_kwargs, + ) + if logger.isEnabledFor(logging.DEBUG): + log_debug_json( + logger, "[API请求体][stateless replay]", request_body + ) + raw_result = await self._request_with_openai( + model_config, request_body + ) + else: + raise if api_mode == API_MODE_RESPONSES: result = normalize_responses_result( raw_result, @@ -1023,6 +1096,8 @@ async def request( "tool_result_start_index": transport_message_count + (1 if tool_calls else 0), } + if responses_stateless_replay: + result["_transport_state"]["stateless_replay"] = True else: result = self._normalize_result(raw_result) if api_to_internal: diff --git a/src/Undefined/ai/transports/openai_transport.py b/src/Undefined/ai/transports/openai_transport.py index 10cdc7e1..67e07101 100644 --- a/src/Undefined/ai/transports/openai_transport.py +++ b/src/Undefined/ai/transports/openai_transport.py @@ -94,7 +94,7 @@ def _stringify_content(value: Any) -> str: def _content_to_response_parts(content: Any) -> list[dict[str, Any]]: if isinstance(content, str): - return [{"type": "input_text", "text": content}] + return [{"type": "input_text", "text": content}] if content else [] if not isinstance(content, list): text = _stringify_content(content) return [{"type": "input_text", "text": text}] if text else [] @@ -360,10 +360,12 @@ def build_responses_request_body( previous_response_id = "" start_index = 0 + stateless_replay = False if isinstance(transport_state, dict): previous_response_id = str( transport_state.get("previous_response_id") or "" ).strip() + stateless_replay = bool(transport_state.get("stateless_replay")) try: start_index = int(transport_state.get("tool_result_start_index") or 0) except Exception: @@ -371,7 +373,7 @@ def build_responses_request_body( if start_index < 0: start_index = 0 - if previous_response_id: + if previous_response_id and not stateless_replay: body["previous_response_id"] = previous_response_id body["input"] = _messages_to_responses_input( messages[start_index:], internal_to_api, include_system=True diff --git a/tests/test_llm_request_params.py b/tests/test_llm_request_params.py index 971f5acc..97a0193d 100644 --- a/tests/test_llm_request_params.py +++ b/tests/test_llm_request_params.py @@ -4,7 +4,7 @@ import httpx import pytest -from openai import AsyncOpenAI +from openai import AsyncOpenAI, BadRequestError from Undefined.ai.llm import ModelRequester, _encode_tool_name_for_api from Undefined.ai.parsing import extract_choices_content @@ -35,7 +35,7 @@ async def create(self, **kwargs: Any) -> dict[str, Any]: class _FakeResponsesAPI: - def __init__(self, responses: list[dict[str, Any]] | None = None) -> None: + def __init__(self, responses: list[Any] | None = None) -> None: self.last_kwargs: dict[str, Any] | None = None self.calls: list[dict[str, Any]] = [] self._responses = list(responses or []) @@ -45,7 +45,16 @@ async def create(self, **kwargs: Any) -> dict[str, Any]: self.calls.append(dict(kwargs)) if not self._responses: raise AssertionError("fake responses exhausted") - return self._responses.pop(0) + item = self._responses.pop(0) + if isinstance(item, Exception): + raise item + return cast(dict[str, Any], item) + + +def _make_bad_request_error(message: str, body: dict[str, Any]) -> BadRequestError: + request = httpx.Request("POST", "https://api.example.com/v1/responses") + response = httpx.Response(400, request=request) + return BadRequestError(message, response=response, body=body) class _FakeClient: @@ -387,7 +396,7 @@ async def test_responses_transport_state_uses_previous_response_id_and_tool_outp tools=tools, ) first_tool_calls = first["choices"][0]["message"]["tool_calls"] - messages = [ + messages: list[dict[str, Any]] = [ {"role": "user", "content": "hello"}, {"role": "assistant", "content": "", "tool_calls": first_tool_calls}, {"role": "tool", "tool_call_id": "call_1", "content": "done"}, @@ -421,6 +430,141 @@ async def test_responses_transport_state_uses_previous_response_id_and_tool_outp await requester._http_client.aclose() +@pytest.mark.asyncio +async def test_responses_followup_falls_back_to_stateless_replay_on_missing_call_id() -> ( + None +): + requester = ModelRequester( + http_client=httpx.AsyncClient(), + token_usage_storage=cast(TokenUsageStorage, _FakeUsageStorage()), + ) + fake_client = _FakeClient( + responses=cast( + list[dict[str, Any]], + [ + _make_bad_request_error( + "No tool call found for function call output with call_id call_1.", + { + "error": { + "message": "No tool call found for function call output with call_id call_1.", + "type": "invalid_request_error", + "param": "input", + "code": None, + } + }, + ), + { + "id": "resp_2", + "output": [ + { + "type": "message", + "id": "msg_1", + "role": "assistant", + "status": "completed", + "content": [{"type": "output_text", "text": "all done"}], + } + ], + "usage": {"input_tokens": 6, "output_tokens": 3, "total_tokens": 9}, + }, + ], + ), + ) + setattr( + requester, + "_get_openai_client_for_model", + lambda _cfg: cast(AsyncOpenAI, fake_client), + ) + cfg = ChatModelConfig( + api_url="https://api.openai.com/v1", + api_key="sk-test", + model_name="gpt-test", + max_tokens=512, + api_mode="responses", + ) + messages: list[dict[str, Any]] = [ + {"role": "user", "content": "hello"}, + { + "role": "assistant", + "content": "", + "tool_calls": [ + { + "id": "call_1", + "type": "function", + "function": { + "name": "lookup", + "arguments": '{"query": "weather"}', + }, + } + ], + }, + {"role": "tool", "tool_call_id": "call_1", "content": "done"}, + ] + + result = await requester.request( + model_config=cfg, + messages=messages, + max_tokens=128, + call_type="chat", + tools=[ + { + "type": "function", + "function": { + "name": "lookup", + "description": "lookup weather", + "parameters": { + "type": "object", + "properties": {"query": {"type": "string"}}, + "required": ["query"], + }, + }, + } + ], + transport_state={ + "api_mode": "responses", + "previous_response_id": "resp_1", + "tool_result_start_index": 2, + }, + message_count_for_transport=len(messages), + ) + + assert fake_client.responses.calls[0]["previous_response_id"] == "resp_1" + assert fake_client.responses.calls[0]["input"] == [ + { + "type": "function_call_output", + "call_id": "call_1", + "output": "done", + } + ] + assert "previous_response_id" not in fake_client.responses.calls[1] + replay_input = fake_client.responses.calls[1]["input"] + assert replay_input[0] == { + "type": "message", + "role": "user", + "content": [{"type": "input_text", "text": "hello"}], + } + assert replay_input[1]["type"] == "function_call" + assert replay_input[1]["call_id"] == "call_1" + assert replay_input[1]["name"] == "lookup" + assert replay_input[1]["arguments"] in { + '{"query": "weather"}', + '{"query":"weather"}', + } + assert replay_input[2] == { + "type": "function_call_output", + "call_id": "call_1", + "output": "done", + } + assert extract_choices_content(result) == "all done" + assert result["_transport_state"] == { + "api_mode": "responses", + "previous_response_id": "resp_2", + "tool_result_start_index": 3, + "stateless_replay": True, + } + + await requester._http_client.aclose() + + @pytest.mark.asyncio async def test_responses_tools_and_tool_choice_use_sanitized_api_names() -> None: requester = ModelRequester( From df130c18b79ce1ea0e24c3b3d0b3b62c3cc5272c Mon Sep 17 00:00:00 2001 From: Null <1708213363@qq.com> Date: Sat, 7 Mar 2026 19:55:38 +0800 Subject: [PATCH 16/21] feat(config): add responses stateless replay switch --- config.toml.example | 15 +++ docs/configuration.md | 21 ++-- docs/openapi.md | 5 +- src/Undefined/ai/llm.py | 9 +- src/Undefined/api/app.py | 3 + src/Undefined/config/loader.py | 47 +++++++- src/Undefined/config/models.py | 5 + src/Undefined/skills/agents/README.md | 4 +- src/Undefined/webui/static/js/config-form.js | 5 +- tests/test_config_request_params.py | 32 +++++- tests/test_llm_request_params.py | 107 +++++++++++++++++++ tests/test_runtime_api_probes.py | 2 + tests/test_webui_render_toml.py | 2 + 13 files changed, 242 insertions(+), 15 deletions(-) diff --git a/config.toml.example b/config.toml.example index ea749aaf..0f9c6083 100644 --- a/config.toml.example +++ b/config.toml.example @@ -113,6 +113,9 @@ thinking_tool_call_compat = true # zh: Responses API 的 tool_choice 兼容模式：仅在关闭时请求仍返回 500、怀疑上游不兼容对象型 tool_choice 时再尝试开启；开启后上报为 "required" 并只保留目标工具。当前已在 new-api v0.11.4-alpha.3 发现该问题。默认关闭。 # en: Responses API tool_choice compatibility mode: only try enabling this when requests still return 500 with the default setting and you suspect the upstream does not support object-style tool_choice; it sends "required" and keeps only the selected tool. This issue is currently observed on new-api v0.11.4-alpha.3. Disabled by default. responses_tool_choice_compat = false +# zh: Responses API 续轮强制降级：启用后，多轮工具调用将始终跳过 previous_response_id，直接使用完整消息重放（stateless replay）。仅在上游不兼容 responses 状态续轮时使用。默认关闭。 +# en: Responses API force stateless replay: when enabled, multi-turn tool follow-ups always skip previous_response_id and replay the full message history instead. Use only when the upstream does not handle stateful responses follow-ups correctly. Disabled by default. +responses_force_stateless_replay = false # zh: 额外请求体参数（可选），可用于 temperature 或供应商私有参数。 # en: Extra request-body params (optional), e.g. temperature or vendor-specific fields. @@ -170,6 +173,9 @@ thinking_tool_call_compat = true # zh: Responses API 的 tool_choice 兼容模式：仅在关闭时请求仍返回 500、怀疑上游不兼容对象型 tool_choice 时再尝试开启；开启后上报为 "required" 并只保留目标工具。当前已在 new-api v0.11.4-alpha.3 发现该问题。默认关闭。 # en: Responses API tool_choice compatibility mode: only try enabling this when requests still return 500 with the default setting and you suspect the upstream does not support object-style tool_choice; it sends "required" and keeps only the selected tool. This issue is currently observed on new-api v0.11.4-alpha.3. Disabled by default. responses_tool_choice_compat = false +# zh: Responses API 续轮强制降级：启用后，多轮工具调用将始终跳过 previous_response_id，直接使用完整消息重放（stateless replay）。仅在上游不兼容 responses 状态续轮时使用。默认关闭。 +# en: Responses API force stateless replay: when enabled, multi-turn tool follow-ups always skip previous_response_id and replay the full message history instead. Use only when the upstream does not handle stateful responses follow-ups correctly. Disabled by default. +responses_force_stateless_replay = false # zh: 额外请求体参数（可选），可用于 temperature 或供应商私有参数。 # en: Extra request-body params (optional), e.g. temperature or vendor-specific fields. @@ -220,6 +226,9 @@ thinking_tool_call_compat = true # zh: Responses API 的 tool_choice 兼容模式：仅在关闭时请求仍返回 500、怀疑上游不兼容对象型 tool_choice 时再尝试开启；开启后上报为 "required" 并只保留目标工具。当前已在 new-api v0.11.4-alpha.3 发现该问题。默认关闭。 # en: Responses API tool_choice compatibility mode: only try enabling this when requests still return 500 with the default setting and you suspect the upstream does not support object-style tool_choice; it sends "required" and keeps only the selected tool. This issue is currently observed on new-api v0.11.4-alpha.3. Disabled by default. responses_tool_choice_compat = false +# zh: Responses API 续轮强制降级：启用后，多轮工具调用将始终跳过 previous_response_id，直接使用完整消息重放（stateless replay）。仅在上游不兼容 responses 状态续轮时使用。默认关闭。 +# en: Responses API force stateless replay: when enabled, multi-turn tool follow-ups always skip previous_response_id and replay the full message history instead. Use only when the upstream does not handle stateful responses follow-ups correctly. Disabled by default. +responses_force_stateless_replay = false # zh: 额外请求体参数（可选），可用于 temperature 或供应商私有参数。 # en: Extra request-body params (optional), e.g. temperature or vendor-specific fields. @@ -267,6 +276,9 @@ thinking_tool_call_compat = true # zh: Responses API 的 tool_choice 兼容模式：仅在关闭时请求仍返回 500、怀疑上游不兼容对象型 tool_choice 时再尝试开启；开启后上报为 "required" 并只保留目标工具。当前已在 new-api v0.11.4-alpha.3 发现该问题。默认关闭。 # en: Responses API tool_choice compatibility mode: only try enabling this when requests still return 500 with the default setting and you suspect the upstream does not support object-style tool_choice; it sends "required" and keeps only the selected tool. This issue is currently observed on new-api v0.11.4-alpha.3. Disabled by default. responses_tool_choice_compat = false +# zh: Responses API 续轮强制降级：启用后，多轮工具调用将始终跳过 previous_response_id，直接使用完整消息重放（stateless replay）。仅在上游不兼容 responses 状态续轮时使用。默认关闭。 +# en: Responses API force stateless replay: when enabled, multi-turn tool follow-ups always skip previous_response_id and replay the full message history instead. Use only when the upstream does not handle stateful responses follow-ups correctly. Disabled by default. +responses_force_stateless_replay = false # zh: 额外请求体参数（可选），可用于 temperature 或供应商私有参数。 # en: Extra request-body params (optional), e.g. temperature or vendor-specific fields. @@ -327,6 +339,9 @@ thinking_tool_call_compat = true # zh: Responses API 的 tool_choice 兼容模式：仅在关闭时请求仍返回 500、怀疑上游不兼容对象型 tool_choice 时再尝试开启；开启后上报为 "required" 并只保留目标工具。当前已在 new-api v0.11.4-alpha.3 发现该问题。默认关闭。 # en: Responses API tool_choice compatibility mode: only try enabling this when requests still return 500 with the default setting and you suspect the upstream does not support object-style tool_choice; it sends "required" and keeps only the selected tool. This issue is currently observed on new-api v0.11.4-alpha.3. Disabled by default. responses_tool_choice_compat = false +# zh: Responses API 续轮强制降级：启用后，多轮工具调用将始终跳过 previous_response_id，直接使用完整消息重放（stateless replay）。仅在上游不兼容 responses 状态续轮时使用。默认关闭。 +# en: Responses API force stateless replay: when enabled, multi-turn tool follow-ups always skip previous_response_id and replay the full message history instead. Use only when the upstream does not handle stateful responses follow-ups correctly. Disabled by default. +responses_force_stateless_replay = false # zh: 额外请求体参数（可选），可用于 temperature 或供应商私有参数。 # en: Extra request-body params (optional), e.g. temperature or vendor-specific fields. diff --git a/docs/configuration.md b/docs/configuration.md index ddf937c3..e4244050 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -151,6 +151,7 @@ model_name = "gpt-4o-mini" | `thinking_include_budget` | 是否发送 `budget_tokens` | | `thinking_tool_call_compat` | Tool Calls 兼容模式：在多轮工具调用中回填 `reasoning_content`；默认 `true` | | `responses_tool_choice_compat` | `responses` 下的 `tool_choice` 兼容开关：仅建议在默认关闭时请求仍返回 500、怀疑上游不兼容对象型 `tool_choice` 时再尝试开启；开启后降级为字符串 `"required"`；默认 `false` | +| `responses_force_stateless_replay` | `responses` 下的续轮强制降级开关：启用后多轮工具调用始终跳过 `previous_response_id`，改为完整消息重放；默认 `false` | | `request_params` | 额外请求体参数（透传给模型 API，保留字段会忽略） | 请求模式说明： @@ -161,7 +162,8 @@ model_name = "gpt-4o-mini" - 仅在 `reasoning_enabled=true` 时发送 `reasoning={ effort = ... }` - 默认使用官方对象格式：`{"type":"function","name":"..."}` - `responses_tool_choice_compat=true` 时，会把指定函数的 `tool_choice` 降级为字符串 `"required"`，并只保留目标工具，用于兼容部分不完整代理 - - 仅建议在默认关闭时请求仍返回 500，再尝试开启该兼容开关 + - `responses_force_stateless_replay=true` 时，多轮工具调用会始终跳过 `previous_response_id`，直接走完整消息重放 + - 仅建议在默认关闭时请求仍返回 500，再尝试开启这些兼容开关 - 当前已知 `new-api v0.11.4-alpha.3` 存在这类兼容问题 - 旧式 `thinking_*` 不会下发到 `responses` @@ -185,6 +187,7 @@ model_name = "gpt-4o-mini" - `thinking_budget_tokens=20000` - `thinking_tool_call_compat=true` - `responses_tool_choice_compat=false` +- `responses_force_stateless_replay=false` 补充： - 若上游只对 `/v1/responses` 识别自定义参数，可将 `api_mode` 切到 `responses`。 @@ -200,16 +203,17 @@ model_name = "gpt-4o-mini" - `thinking_budget_tokens=20000` - `thinking_tool_call_compat=true` - `responses_tool_choice_compat=false` +- `responses_force_stateless_replay=false` ### 4.4.4 `[models.security]` 安全模型 字段： - 额外开关：`enabled=true` -- 默认：`max_tokens=100`、`api_mode="chat_completions"`、`reasoning_enabled=false`、`reasoning_effort="medium"`、`thinking_budget_tokens=0`、`thinking_tool_call_compat=true`、`responses_tool_choice_compat=false` +- 默认：`max_tokens=100`、`api_mode="chat_completions"`、`reasoning_enabled=false`、`reasoning_effort="medium"`、`thinking_budget_tokens=0`、`thinking_tool_call_compat=true`、`responses_tool_choice_compat=false`、`responses_force_stateless_replay=false` 关键回退逻辑： - 若 `api_url/api_key/model_name` 任一缺失，会自动回退为 chat 模型（并告警）。 -- 回退时会继承 chat 的 `api_mode`、`reasoning_*`、`responses_tool_choice_compat` 与 `request_params`；旧 `thinking_*` 仍保持安全模型自身默认值。 +- 回退时会继承 chat 的 `api_mode`、`reasoning_*`、`responses_tool_choice_compat`、`responses_force_stateless_replay` 与 `request_params`；旧 `thinking_*` 仍保持安全模型自身默认值。 ### 4.4.5 `[models.agent]` Agent 执行模型 @@ -221,12 +225,13 @@ model_name = "gpt-4o-mini" - `reasoning_effort="medium"` - `thinking_tool_call_compat=true` - `responses_tool_choice_compat=false` +- `responses_force_stateless_replay=false` ### 4.4.6 `[models.historian]` 史官模型 - 用于认知记忆后台改写。 - 若整个节缺失或为空：完整回退到 `models.agent`。 -- 若部分字段缺失：逐项继承 agent 配置，包括 `api_mode`、`reasoning_*`、`thinking_*`、`responses_tool_choice_compat` 与 `request_params`。 +- 若部分字段缺失：逐项继承 agent 配置，包括 `api_mode`、`reasoning_*`、`thinking_*`、`responses_tool_choice_compat`、`responses_force_stateless_replay` 与 `request_params`。 - `queue_interval_seconds<=0` 时回退到 agent 的间隔。 ### 4.4.7 模型池 @@ -248,7 +253,7 @@ model_name = "gpt-4o-mini" `models` 条目支持字段： - `model_name`（必填） - `api_url` / `api_key` / `max_tokens` / `queue_interval_seconds` -- `api_mode` / `reasoning_enabled` / `reasoning_effort` / `responses_tool_choice_compat` +- `api_mode` / `reasoning_enabled` / `reasoning_effort` / `responses_tool_choice_compat` / `responses_force_stateless_replay` - `thinking_*` / `request_params` - 以上可选字段缺省继承主模型 @@ -288,7 +293,7 @@ model_name = "gpt-4o-mini" `request_params` 说明： - 仅用于**请求体**字段，不包含 `api_key`、`base_url`、`timeout`、`extra_headers` 等 client 选项。 - 聊天类（`chat_completions`）保留字段：`model`、`messages`、`max_tokens`、`tools`、`tool_choice`、`stream`、`stream_options`、`reasoning`、`reasoning_effort`。 -- 聊天类（`responses`）保留字段：`model`、`input`、`instructions`、`max_output_tokens`、`tools`、`tool_choice`、`previous_response_id`、`stream`、`stream_options`、`thinking`、`reasoning`、`reasoning_effort`。 +- 聊天类（`responses`）保留字段：`model`、`input`、`instructions`、`max_output_tokens`、`tools`、`tool_choice`、`previous_response_id`、`stream`、`stream_options`、`thinking`、`reasoning`、`reasoning_effort`。启用 `responses_force_stateless_replay` 时会主动跳过 `previous_response_id`。 - embedding 保留字段：`model`、`input`、`dimensions`。 - rerank 保留字段：`model`、`query`、`documents`、`top_n`、`return_documents`。 @@ -680,9 +685,9 @@ model_name = "gpt-4o-mini" - `BOT_QQ` / `SUPERADMIN_QQ` - `ONEBOT_WS_URL` / `ONEBOT_TOKEN` - `CHAT_MODEL_API_URL` / `CHAT_MODEL_API_KEY` / `CHAT_MODEL_NAME` -- `CHAT_MODEL_API_MODE` / `CHAT_MODEL_REASONING_ENABLED` / `CHAT_MODEL_REASONING_EFFORT` / `CHAT_MODEL_RESPONSES_TOOL_CHOICE_COMPAT` +- `CHAT_MODEL_API_MODE` / `CHAT_MODEL_REASONING_ENABLED` / `CHAT_MODEL_REASONING_EFFORT` / `CHAT_MODEL_RESPONSES_TOOL_CHOICE_COMPAT` / `CHAT_MODEL_RESPONSES_FORCE_STATELESS_REPLAY` - `VISION_MODEL_*` / `AGENT_MODEL_*` / `SECURITY_MODEL_*` / `HISTORIAN_MODEL_*` -- 上述模型环境变量同样覆盖 `*_THINKING_ENABLED`、`*_THINKING_BUDGET_TOKENS`、`*_THINKING_TOOL_CALL_COMPAT`、`*_RESPONSES_TOOL_CHOICE_COMPAT` +- 上述模型环境变量同样覆盖 `*_THINKING_ENABLED`、`*_THINKING_BUDGET_TOKENS`、`*_THINKING_TOOL_CALL_COMPAT`、`*_RESPONSES_TOOL_CHOICE_COMPAT`、`*_RESPONSES_FORCE_STATELESS_REPLAY` - `EMBEDDING_MODEL_*` / `RERANK_MODEL_*` - `SEARXNG_URL` - `HTTP_PROXY` / `HTTPS_PROXY` diff --git a/docs/openapi.md b/docs/openapi.md index 1360406c..db5a6f26 100644 --- a/docs/openapi.md +++ b/docs/openapi.md @@ -79,7 +79,7 @@ curl http://127.0.0.1:8788/openapi.json | `cognitive` | `object` | 认知服务（`enabled`、`queue`） | | `api` | `object` | Runtime API 配置（`enabled`、`host`、`port`、`openapi_enabled`） | | `skills` | `object` | 技能统计，包含 `tools`、`agents`、`anthropic_skills` 三个子对象 | -| `models` | `object` | 模型配置；聊天类模型包含 `model_name`、脱敏 `api_url`、`api_mode`、`thinking_enabled`、`thinking_tool_call_compat`、`responses_tool_choice_compat`、`reasoning_enabled`、`reasoning_effort` | +| `models` | `object` | 模型配置；聊天类模型包含 `model_name`、脱敏 `api_url`、`api_mode`、`thinking_enabled`、`thinking_tool_call_compat`、`responses_tool_choice_compat`、`responses_force_stateless_replay`、`reasoning_enabled`、`reasoning_effort` | `skills` 子对象结构： @@ -104,6 +104,7 @@ curl http://127.0.0.1:8788/openapi.json "thinking_enabled": false, "thinking_tool_call_compat": true, "responses_tool_choice_compat": false, + "responses_force_stateless_replay": false, "reasoning_enabled": true, "reasoning_effort": "high" }, @@ -111,7 +112,7 @@ curl http://127.0.0.1:8788/openapi.json } ``` -说明：`responses_tool_choice_compat` 通常保持 `false`；仅建议在 `responses` 请求默认配置下仍返回 `500` 时再尝试开启。当前已知 `new-api v0.11.4-alpha.3` 存在该兼容问题。 +说明：`responses_tool_choice_compat` 与 `responses_force_stateless_replay` 通常都保持 `false`；仅建议在 `responses` 请求默认配置下仍返回 `500`，且怀疑上游不兼容状态续轮时再尝试开启。当前已知 `new-api v0.11.4-alpha.3` 存在该兼容问题。 #### 外部探针响应字段 diff --git a/src/Undefined/ai/llm.py b/src/Undefined/ai/llm.py index 9cec9a34..41d93b61 100644 --- a/src/Undefined/ai/llm.py +++ b/src/Undefined/ai/llm.py @@ -991,10 +991,17 @@ async def request( overrides=dict(kwargs), ) responses_stateless_replay = bool( + getattr(model_config, "responses_force_stateless_replay", False) + ) or bool( isinstance(transport_state, dict) and transport_state.get("stateless_replay") ) - effective_transport_state = transport_state + effective_transport_state: dict[str, Any] | None + if responses_stateless_replay: + effective_transport_state = dict(transport_state or {}) + effective_transport_state["stateless_replay"] = True + else: + effective_transport_state = transport_state request_body = build_request_body( model_config=model_config, messages=messages_for_api, diff --git a/src/Undefined/api/app.py b/src/Undefined/api/app.py index 09618ae8..0cf5528e 100644 --- a/src/Undefined/api/app.py +++ b/src/Undefined/api/app.py @@ -531,6 +531,9 @@ async def _internal_probe_handler(self, request: web.Request) -> Response: "responses_tool_choice_compat": getattr( mcfg, "responses_tool_choice_compat", False ), + "responses_force_stateless_replay": getattr( + mcfg, "responses_force_stateless_replay", False + ), "reasoning_enabled": getattr(mcfg, "reasoning_enabled", False), "reasoning_effort": getattr(mcfg, "reasoning_effort", "medium"), } diff --git a/src/Undefined/config/loader.py b/src/Undefined/config/loader.py index 0548c1f8..31bc2e56 100644 --- a/src/Undefined/config/loader.py +++ b/src/Undefined/config/loader.py @@ -332,6 +332,22 @@ def _resolve_responses_tool_choice_compat( ) +def _resolve_responses_force_stateless_replay( + data: dict[str, Any], + model_name: str, + env_key: str, + default: bool = False, +) -> bool: + return _coerce_bool( + _get_value( + data, + ("models", model_name, "responses_force_stateless_replay"), + env_key, + ), + default, + ) + + def load_local_admins() -> list[int]: """从本地配置文件加载动态管理员列表""" if not LOCAL_CONFIG_PATH.exists(): @@ -1579,6 +1595,10 @@ def _parse_model_pool( item.get("responses_tool_choice_compat"), primary_config.responses_tool_choice_compat, ), + responses_force_stateless_replay=_coerce_bool( + item.get("responses_force_stateless_replay"), + primary_config.responses_force_stateless_replay, + ), reasoning_enabled=_coerce_bool( item.get("reasoning_enabled"), primary_config.reasoning_enabled, @@ -1696,6 +1716,9 @@ def _parse_chat_model_config(data: dict[str, Any]) -> ChatModelConfig: responses_tool_choice_compat = _resolve_responses_tool_choice_compat( data, "chat", "CHAT_MODEL_RESPONSES_TOOL_CHOICE_COMPAT" ) + responses_force_stateless_replay = _resolve_responses_force_stateless_replay( + data, "chat", "CHAT_MODEL_RESPONSES_FORCE_STATELESS_REPLAY" + ) reasoning_enabled = _coerce_bool( _get_value( data, @@ -1752,6 +1775,7 @@ def _parse_chat_model_config(data: dict[str, Any]) -> ChatModelConfig: thinking_include_budget=thinking_include_budget, thinking_tool_call_compat=thinking_tool_call_compat, responses_tool_choice_compat=responses_tool_choice_compat, + responses_force_stateless_replay=responses_force_stateless_replay, reasoning_enabled=reasoning_enabled, reasoning_effort=reasoning_effort, request_params=_get_model_request_params(data, "chat"), @@ -1784,6 +1808,9 @@ def _parse_vision_model_config(data: dict[str, Any]) -> VisionModelConfig: responses_tool_choice_compat = _resolve_responses_tool_choice_compat( data, "vision", "VISION_MODEL_RESPONSES_TOOL_CHOICE_COMPAT" ) + responses_force_stateless_replay = _resolve_responses_force_stateless_replay( + data, "vision", "VISION_MODEL_RESPONSES_FORCE_STATELESS_REPLAY" + ) reasoning_enabled = _coerce_bool( _get_value( data, @@ -1840,6 +1867,7 @@ def _parse_vision_model_config(data: dict[str, Any]) -> VisionModelConfig: thinking_include_budget=thinking_include_budget, thinking_tool_call_compat=thinking_tool_call_compat, responses_tool_choice_compat=responses_tool_choice_compat, + responses_force_stateless_replay=responses_force_stateless_replay, reasoning_enabled=reasoning_enabled, reasoning_effort=reasoning_effort, request_params=_get_model_request_params(data, "vision"), @@ -1891,6 +1919,9 @@ def _parse_security_model_config( responses_tool_choice_compat = _resolve_responses_tool_choice_compat( data, "security", "SECURITY_MODEL_RESPONSES_TOOL_CHOICE_COMPAT" ) + responses_force_stateless_replay = _resolve_responses_force_stateless_replay( + data, "security", "SECURITY_MODEL_RESPONSES_FORCE_STATELESS_REPLAY" + ) reasoning_enabled = _coerce_bool( _get_value( data, @@ -1942,6 +1973,7 @@ def _parse_security_model_config( thinking_include_budget=thinking_include_budget, thinking_tool_call_compat=thinking_tool_call_compat, responses_tool_choice_compat=responses_tool_choice_compat, + responses_force_stateless_replay=responses_force_stateless_replay, reasoning_enabled=reasoning_enabled, reasoning_effort=reasoning_effort, request_params=_get_model_request_params(data, "security"), @@ -1960,6 +1992,7 @@ def _parse_security_model_config( thinking_include_budget=True, thinking_tool_call_compat=chat_model.thinking_tool_call_compat, responses_tool_choice_compat=chat_model.responses_tool_choice_compat, + responses_force_stateless_replay=chat_model.responses_force_stateless_replay, reasoning_enabled=chat_model.reasoning_enabled, reasoning_effort=chat_model.reasoning_effort, request_params=merge_request_params(chat_model.request_params), @@ -1990,6 +2023,9 @@ def _parse_agent_model_config(data: dict[str, Any]) -> AgentModelConfig: responses_tool_choice_compat = _resolve_responses_tool_choice_compat( data, "agent", "AGENT_MODEL_RESPONSES_TOOL_CHOICE_COMPAT" ) + responses_force_stateless_replay = _resolve_responses_force_stateless_replay( + data, "agent", "AGENT_MODEL_RESPONSES_FORCE_STATELESS_REPLAY" + ) reasoning_enabled = _coerce_bool( _get_value( data, @@ -2046,6 +2082,7 @@ def _parse_agent_model_config(data: dict[str, Any]) -> AgentModelConfig: thinking_include_budget=thinking_include_budget, thinking_tool_call_compat=thinking_tool_call_compat, responses_tool_choice_compat=responses_tool_choice_compat, + responses_force_stateless_replay=responses_force_stateless_replay, reasoning_enabled=reasoning_enabled, reasoning_effort=reasoning_effort, request_params=_get_model_request_params(data, "agent"), @@ -2130,7 +2167,7 @@ def _log_debug_info( ] for name, cfg in configs: logger.debug( - "[配置] %s_model=%s api_url=%s api_key_set=%s api_mode=%s thinking=%s reasoning=%s/%s cot_compat=%s responses_tool_choice_compat=%s", + "[配置] %s_model=%s api_url=%s api_key_set=%s api_mode=%s thinking=%s reasoning=%s/%s cot_compat=%s responses_tool_choice_compat=%s responses_force_stateless_replay=%s", name, cfg.model_name, cfg.api_url, @@ -2141,6 +2178,7 @@ def _log_debug_info( getattr(cfg, "reasoning_effort", "medium"), getattr(cfg, "thinking_tool_call_compat", False), getattr(cfg, "responses_tool_choice_compat", False), + getattr(cfg, "responses_force_stateless_replay", False), ) def update_from(self, new_config: "Config") -> dict[str, tuple[Any, Any]]: @@ -2198,6 +2236,12 @@ def _parse_historian_model_config( "HISTORIAN_MODEL_RESPONSES_TOOL_CHOICE_COMPAT", fallback.responses_tool_choice_compat, ) + responses_force_stateless_replay = _resolve_responses_force_stateless_replay( + {"models": {"historian": h}}, + "historian", + "HISTORIAN_MODEL_RESPONSES_FORCE_STATELESS_REPLAY", + fallback.responses_force_stateless_replay, + ) return AgentModelConfig( api_url=_coerce_str(h.get("api_url"), fallback.api_url), api_key=_coerce_str(h.get("api_key"), fallback.api_key), @@ -2214,6 +2258,7 @@ def _parse_historian_model_config( thinking_include_budget=thinking_include_budget, thinking_tool_call_compat=thinking_tool_call_compat, responses_tool_choice_compat=responses_tool_choice_compat, + responses_force_stateless_replay=responses_force_stateless_replay, reasoning_enabled=_coerce_bool( _get_value( {"models": {"historian": h}}, diff --git a/src/Undefined/config/models.py b/src/Undefined/config/models.py index 6b403c5f..720cfa61 100644 --- a/src/Undefined/config/models.py +++ b/src/Undefined/config/models.py @@ -21,6 +21,7 @@ class ModelPoolEntry: thinking_include_budget: bool = True thinking_tool_call_compat: bool = True responses_tool_choice_compat: bool = False + responses_force_stateless_replay: bool = False reasoning_enabled: bool = False reasoning_effort: str = "medium" request_params: dict[str, Any] = field(default_factory=dict) @@ -54,6 +55,7 @@ class ChatModelConfig: responses_tool_choice_compat: bool = ( False # Responses API 的 tool_choice 兼容模式（降级为字符串 required） ) + responses_force_stateless_replay: bool = False # Responses API 续轮强制降级为 stateless replay（不使用 previous_response_id） reasoning_enabled: bool = False # 是否启用 reasoning.effort reasoning_effort: str = "medium" # reasoning effort 档位 request_params: dict[str, Any] = field(default_factory=dict) @@ -78,6 +80,7 @@ class VisionModelConfig: responses_tool_choice_compat: bool = ( False # Responses API 的 tool_choice 兼容模式（降级为字符串 required） ) + responses_force_stateless_replay: bool = False # Responses API 续轮强制降级为 stateless replay（不使用 previous_response_id） reasoning_enabled: bool = False # 是否启用 reasoning.effort reasoning_effort: str = "medium" # reasoning effort 档位 request_params: dict[str, Any] = field(default_factory=dict) @@ -102,6 +105,7 @@ class SecurityModelConfig: responses_tool_choice_compat: bool = ( False # Responses API 的 tool_choice 兼容模式（降级为字符串 required） ) + responses_force_stateless_replay: bool = False # Responses API 续轮强制降级为 stateless replay（不使用 previous_response_id） reasoning_enabled: bool = False # 是否启用 reasoning.effort reasoning_effort: str = "medium" # reasoning effort 档位 request_params: dict[str, Any] = field(default_factory=dict) @@ -152,6 +156,7 @@ class AgentModelConfig: responses_tool_choice_compat: bool = ( False # Responses API 的 tool_choice 兼容模式（降级为字符串 required） ) + responses_force_stateless_replay: bool = False # Responses API 续轮强制降级为 stateless replay（不使用 previous_response_id） reasoning_enabled: bool = False # 是否启用 reasoning.effort reasoning_effort: str = "medium" # reasoning effort 档位 request_params: dict[str, Any] = field(default_factory=dict) diff --git a/src/Undefined/skills/agents/README.md b/src/Undefined/skills/agents/README.md index f04880d0..8f46a53a 100644 --- a/src/Undefined/skills/agents/README.md +++ b/src/Undefined/skills/agents/README.md @@ -39,11 +39,13 @@ reasoning_effort = "medium" thinking_enabled = false thinking_budget_tokens = 0 thinking_tool_call_compat = true +responses_tool_choice_compat = false +responses_force_stateless_replay = false ``` 说明： - `api_mode = "chat_completions"` 时，旧 `thinking_*` 仍按原逻辑生效；若开启 `reasoning_enabled`，也会额外发送 `reasoning.effort`。 -- `api_mode = "responses"` 时，Agent 的多轮工具调用会自动使用 `previous_response_id + function_call_output` 续轮；旧 `thinking_*` 不会发到 `responses`。 +- `api_mode = "responses"` 时，Agent 的多轮工具调用默认使用 `previous_response_id + function_call_output` 续轮；若开启 `responses_force_stateless_replay`，则会始终改为完整消息重放；旧 `thinking_*` 不会发到 `responses`。 - `thinking_tool_call_compat` 默认 `true`，会把 `reasoning_content` 回填到本地消息历史，便于日志、回放和兼容读取。 兼容的环境变量（会覆盖 `config.toml`）： diff --git a/src/Undefined/webui/static/js/config-form.js b/src/Undefined/webui/static/js/config-form.js index dfd64421..2a89538b 100644 --- a/src/Undefined/webui/static/js/config-form.js +++ b/src/Undefined/webui/static/js/config-form.js @@ -771,6 +771,9 @@ function buildAotTemplate(path, arr) { if (!Object.prototype.hasOwnProperty.call(template, "responses_tool_choice_compat")) { template.responses_tool_choice_compat = false } + if (!Object.prototype.hasOwnProperty.call(template, "responses_force_stateless_replay")) { + template.responses_force_stateless_replay = false + } if (!Object.prototype.hasOwnProperty.call(template, "reasoning_enabled")) { template.reasoning_enabled = false } @@ -780,7 +783,7 @@ function buildAotTemplate(path, arr) { } return template } - return { model_name: "", api_url: "", api_key: "", api_mode: "chat_completions", thinking_tool_call_compat: true, responses_tool_choice_compat: false, reasoning_enabled: false, reasoning_effort: "medium", request_params: {} } + return { model_name: "", api_url: "", api_key: "", api_mode: "chat_completions", thinking_tool_call_compat: true, responses_tool_choice_compat: false, responses_force_stateless_replay: false, reasoning_enabled: false, reasoning_effort: "medium", request_params: {} } } function createAotWidget(path, arr) { diff --git a/tests/test_config_request_params.py b/tests/test_config_request_params.py index 8a5d077d..4e059065 100644 --- a/tests/test_config_request_params.py +++ b/tests/test_config_request_params.py @@ -27,6 +27,7 @@ def test_model_request_params_load_inherit_and_new_transport_fields( reasoning_enabled = true reasoning_effort = "high" responses_tool_choice_compat = true +responses_force_stateless_replay = true [models.chat.request_params] temperature = 0.2 @@ -48,6 +49,20 @@ def test_model_request_params_load_inherit_and_new_transport_fields( temperature = 0.6 provider = { name = "pool" } +[models.vision] +api_url = "https://api.openai.com/v1" +api_key = "sk-vision" +model_name = "gpt-vision" +api_mode = "responses" +reasoning_enabled = true +reasoning_effort = "low" +responses_tool_choice_compat = true +responses_force_stateless_replay = true + +[models.vision.request_params] +temperature = 0.4 +metadata = { source = "vision" } + [models.agent] api_url = "https://api.openai.com/v1" api_key = "sk-agent" @@ -56,6 +71,7 @@ def test_model_request_params_load_inherit_and_new_transport_fields( reasoning_enabled = true reasoning_effort = "minimal" responses_tool_choice_compat = true +responses_force_stateless_replay = true [models.agent.request_params] temperature = 0.3 @@ -95,6 +111,7 @@ def test_model_request_params_load_inherit_and_new_transport_fields( assert cfg.chat_model.reasoning_effort == "high" assert cfg.chat_model.thinking_tool_call_compat is True assert cfg.chat_model.responses_tool_choice_compat is True + assert cfg.chat_model.responses_force_stateless_replay is True assert cfg.chat_model.request_params == { "temperature": 0.2, "metadata": {"source": "chat"}, @@ -106,17 +123,29 @@ def test_model_request_params_load_inherit_and_new_transport_fields( assert cfg.chat_model.pool.models[0].reasoning_effort == "low" assert cfg.chat_model.pool.models[0].thinking_tool_call_compat is True assert cfg.chat_model.pool.models[0].responses_tool_choice_compat is True + assert cfg.chat_model.pool.models[0].responses_force_stateless_replay is True assert cfg.chat_model.pool.models[0].request_params == { "temperature": 0.6, "metadata": {"source": "chat"}, "provider": {"name": "pool"}, } + assert cfg.vision_model.api_mode == "responses" + assert cfg.vision_model.reasoning_enabled is True + assert cfg.vision_model.reasoning_effort == "low" + assert cfg.vision_model.responses_tool_choice_compat is True + assert cfg.vision_model.responses_force_stateless_replay is True + assert cfg.vision_model.request_params == { + "temperature": 0.4, + "metadata": {"source": "vision"}, + } + assert cfg.security_model.api_mode == cfg.chat_model.api_mode assert cfg.security_model.reasoning_enabled == cfg.chat_model.reasoning_enabled assert cfg.security_model.reasoning_effort == cfg.chat_model.reasoning_effort assert cfg.security_model.thinking_tool_call_compat is True assert cfg.security_model.responses_tool_choice_compat is True + assert cfg.security_model.responses_force_stateless_replay is True assert cfg.security_model.request_params == cfg.chat_model.request_params assert cfg.agent_model.api_mode == "responses" @@ -124,12 +153,14 @@ def test_model_request_params_load_inherit_and_new_transport_fields( assert cfg.agent_model.reasoning_effort == "minimal" assert cfg.agent_model.thinking_tool_call_compat is True assert cfg.agent_model.responses_tool_choice_compat is True + assert cfg.agent_model.responses_force_stateless_replay is True assert cfg.historian_model.api_mode == "chat_completions" assert cfg.historian_model.reasoning_enabled is True assert cfg.historian_model.reasoning_effort == "xhigh" assert cfg.historian_model.thinking_tool_call_compat is True assert cfg.historian_model.responses_tool_choice_compat is True + assert cfg.historian_model.responses_force_stateless_replay is True assert cfg.historian_model.request_params == { "temperature": 0.1, "metadata": {"source": "historian"}, @@ -141,4 +172,3 @@ def test_model_request_params_load_inherit_and_new_transport_fields( "metadata": {"source": "embed"}, } assert cfg.rerank_model.request_params == {"priority": "high"} - assert cfg.vision_model.responses_tool_choice_compat is False diff --git a/tests/test_llm_request_params.py b/tests/test_llm_request_params.py index 97a0193d..5d0c6cdb 100644 --- a/tests/test_llm_request_params.py +++ b/tests/test_llm_request_params.py @@ -430,6 +430,113 @@ async def test_responses_transport_state_uses_previous_response_id_and_tool_outp await requester._http_client.aclose() +@pytest.mark.asyncio +async def test_responses_force_stateless_replay_skips_previous_response_id() -> None: + requester = ModelRequester( + http_client=httpx.AsyncClient(), + token_usage_storage=cast(TokenUsageStorage, _FakeUsageStorage()), + ) + fake_client = _FakeClient( + responses=[ + { + "id": "resp_2", + "output": [ + { + "type": "message", + "id": "msg_1", + "role": "assistant", + "status": "completed", + "content": [{"type": "output_text", "text": "all done"}], + } + ], + "usage": {"input_tokens": 6, "output_tokens": 3, "total_tokens": 9}, + } + ] + ) + setattr( + requester, + "_get_openai_client_for_model", + lambda _cfg: cast(AsyncOpenAI, fake_client), + ) + cfg = ChatModelConfig( + api_url="https://api.openai.com/v1", + api_key="sk-test", + model_name="gpt-test", + max_tokens=512, + api_mode="responses", + responses_force_stateless_replay=True, + ) + messages: list[dict[str, Any]] = [ + {"role": "user", "content": "hello"}, + { + "role": "assistant", + "content": "", + "tool_calls": [ + { + "id": "call_1", + "type": "function", + "function": { + "name": "lookup", + "arguments": '{"query": "weather"}', + }, + } + ], + }, + {"role": "tool", "tool_call_id": "call_1", "content": "done"}, + ] + + result = await requester.request( + model_config=cfg, + messages=messages, + max_tokens=128, + call_type="chat", + tools=[ + { + "type": "function", + "function": { + "name": "lookup", + "description": "lookup weather", + "parameters": { + "type": "object", + "properties": {"query": {"type": "string"}}, + "required": ["query"], + }, + }, + } + ], + transport_state={ + "api_mode": "responses", + "previous_response_id": "resp_1", + "tool_result_start_index": 2, + }, + message_count_for_transport=len(messages), + ) + + assert "previous_response_id" not in fake_client.responses.calls[0] + replay_input = fake_client.responses.calls[0]["input"] + assert replay_input[0] == { + "type": "message", + "role": "user", + "content": [{"type": "input_text", "text": "hello"}], + } + assert replay_input[1]["type"] == "function_call" + assert replay_input[1]["call_id"] == "call_1" + assert replay_input[2] == { + "type": "function_call_output", + "call_id": "call_1", + "output": "done", + } + assert extract_choices_content(result) == "all done" + assert result["_transport_state"] == { + "api_mode": "responses", + "previous_response_id": "resp_2", + "tool_result_start_index": 3, + "stateless_replay": True, + } + + await requester._http_client.aclose() + + @pytest.mark.asyncio async def test_responses_followup_falls_back_to_stateless_replay_on_missing_call_id() -> ( None diff --git a/tests/test_runtime_api_probes.py b/tests/test_runtime_api_probes.py index c39817d6..6e48a663 100644 --- a/tests/test_runtime_api_probes.py +++ b/tests/test_runtime_api_probes.py @@ -28,6 +28,7 @@ async def test_runtime_internal_probe_includes_chat_model_transport_fields() -> thinking_enabled=False, thinking_tool_call_compat=True, responses_tool_choice_compat=False, + responses_force_stateless_replay=False, reasoning_enabled=True, reasoning_effort="high", ), @@ -58,6 +59,7 @@ async def test_runtime_internal_probe_includes_chat_model_transport_fields() -> "thinking_enabled": False, "thinking_tool_call_compat": True, "responses_tool_choice_compat": False, + "responses_force_stateless_replay": False, "reasoning_enabled": True, "reasoning_effort": "high", } diff --git a/tests/test_webui_render_toml.py b/tests/test_webui_render_toml.py index 00c329bd..5298b435 100644 --- a/tests/test_webui_render_toml.py +++ b/tests/test_webui_render_toml.py @@ -72,6 +72,7 @@ def test_pool_model_request_params_roundtrip(self) -> None: api_mode = "responses" thinking_tool_call_compat = true responses_tool_choice_compat = true +responses_force_stateless_replay = true reasoning_enabled = true reasoning_effort = "high" @@ -92,6 +93,7 @@ def test_pool_model_request_params_roundtrip(self) -> None: assert model["api_mode"] == "responses" assert model["thinking_tool_call_compat"] is True assert model["responses_tool_choice_compat"] is True + assert model["responses_force_stateless_replay"] is True assert model["reasoning_enabled"] is True assert model["reasoning_effort"] == "high" params = model["request_params"] From bf949ee2c3de20d6e91e384dfce9ab4bfb7d3af5 Mon Sep 17 00:00:00 2001 From: Null <1708213363@qq.com> Date: Sat, 7 Mar 2026 22:34:22 +0800 Subject: [PATCH 17/21] feat: harden python interpreter, fix sender message_id, sync pool model configs - python_interpreter: separate pip install (with network) from code execution (network=none, read-only), add path traversal protection for send_files via _resolve_output_host_path - sender: extract _extract_message_id to handle nested data.message_id envelope from OneBot responses - model_selector: pass responses_tool_choice_compat and responses_force_stateless_replay through pool model selection - config_sync/toml_render: support array-of-tables (pool models) in template merge and comment augmentation - Add tests for python interpreter handler, sender, model pool flags, and config sync pool model merging Co-Authored-By: Claude Opus 4.6 --- src/Undefined/ai/model_selector.py | 4 + .../tools/python_interpreter/handler.py | 189 +++++++++++++----- src/Undefined/utils/sender.py | 38 ++-- src/Undefined/webui/utils/config_sync.py | 120 ++++++++++- src/Undefined/webui/utils/toml_render.py | 15 ++ tests/test_config_template_sync.py | 50 +++++ tests/test_model_pool.py | 73 ++++++- tests/test_python_interpreter_handler.py | 105 ++++++++++ tests/test_sender.py | 61 ++++++ 9 files changed, 586 insertions(+), 69 deletions(-) create mode 100644 tests/test_python_interpreter_handler.py create mode 100644 tests/test_sender.py diff --git a/src/Undefined/ai/model_selector.py b/src/Undefined/ai/model_selector.py index 989da9bb..026dda89 100644 --- a/src/Undefined/ai/model_selector.py +++ b/src/Undefined/ai/model_selector.py @@ -246,6 +246,8 @@ def _entry_to_chat_config( thinking_budget_tokens=entry.thinking_budget_tokens, thinking_include_budget=entry.thinking_include_budget, thinking_tool_call_compat=entry.thinking_tool_call_compat, + responses_tool_choice_compat=entry.responses_tool_choice_compat, + responses_force_stateless_replay=entry.responses_force_stateless_replay, reasoning_enabled=entry.reasoning_enabled, reasoning_effort=entry.reasoning_effort, request_params=entry.request_params, @@ -268,6 +270,8 @@ def _entry_to_agent_config( thinking_budget_tokens=entry.thinking_budget_tokens, thinking_include_budget=entry.thinking_include_budget, thinking_tool_call_compat=entry.thinking_tool_call_compat, + responses_tool_choice_compat=entry.responses_tool_choice_compat, + responses_force_stateless_replay=entry.responses_force_stateless_replay, reasoning_enabled=entry.reasoning_enabled, reasoning_effort=entry.reasoning_effort, request_params=entry.request_params, diff --git a/src/Undefined/skills/tools/python_interpreter/handler.py b/src/Undefined/skills/tools/python_interpreter/handler.py index 43bc212f..e935c7ec 100644 --- a/src/Undefined/skills/tools/python_interpreter/handler.py +++ b/src/Undefined/skills/tools/python_interpreter/handler.py @@ -4,7 +4,8 @@ import re import shutil import tempfile -from pathlib import Path +import time +from pathlib import Path, PurePosixPath from typing import Any, Dict logger = logging.getLogger(__name__) @@ -24,6 +25,105 @@ _SAFE_LIB_PATTERN = re.compile(r"^[A-Za-z0-9][A-Za-z0-9._\-\[\],<>=!~]*$") +def _resolve_output_host_path(container_path: str, host_tmpdir: str) -> Path | None: + """将容器内 /tmp 路径映射到宿主机临时目录，并拒绝目录穿越/符号链接逃逸。""" + try: + pure_path = PurePosixPath(container_path) + relative = pure_path.relative_to("/tmp") + except (TypeError, ValueError): + return None + + host_tmp_root = Path(host_tmpdir).resolve() + candidate = (host_tmp_root / relative.as_posix()).resolve(strict=False) + + try: + candidate.relative_to(host_tmp_root) + except ValueError: + return None + + return candidate + + +def _build_docker_base_cmd(host_tmpdir: str, memory: str) -> list[str]: + return [ + "docker", + "run", + "--rm", + "--memory", + memory, + "--cpus", + CPU_LIMIT, + "-v", + f"{host_tmpdir}:/tmp", + ] + + +def _build_install_cmd(host_tmpdir: str, memory: str) -> list[str]: + cmd = _build_docker_base_cmd(host_tmpdir, memory) + cmd.append(DOCKER_IMAGE) + cmd.extend( + [ + "sh", + "-c", + "python -m pip install --quiet --disable-pip-version-check " + "--no-cache-dir -r /tmp/_requirements.txt --target /tmp/_site_packages; " + "_e=$?; chmod -R a+rw /tmp 2>/dev/null; exit $_e", + ] + ) + return cmd + + +def _build_exec_cmd( + host_tmpdir: str, + memory: str, + *, + pythonpath: str | None = None, +) -> list[str]: + cmd = _build_docker_base_cmd(host_tmpdir, memory) + cmd.extend(["--network", "none", "--read-only"]) + if pythonpath: + cmd.extend(["-e", f"PYTHONPATH={pythonpath}"]) + cmd.append(DOCKER_IMAGE) + cmd.extend( + [ + "sh", + "-c", + "python /tmp/_script.py; _e=$?; chmod -R a+rw /tmp 2>/dev/null; exit $_e", + ] + ) + return cmd + + +async def _run_docker_command( + cmd: list[str], + *, + timeout: float, +) -> tuple[int, str, str]: + process = await asyncio.create_subprocess_exec( + *cmd, + stdout=asyncio.subprocess.PIPE, + stderr=asyncio.subprocess.PIPE, + ) + + try: + stdout_bytes, stderr_bytes = await asyncio.wait_for( + process.communicate(), timeout=timeout + ) + except asyncio.TimeoutError: + try: + process.terminate() + await process.wait() + except Exception as e: + logger.error("[Python解释器] 终止超时进程失败: %s", e) + raise + + return ( + process.returncode if process.returncode is not None else 1, + stdout_bytes.decode("utf-8", errors="replace"), + stderr_bytes.decode("utf-8", errors="replace"), + ) + + async def execute(args: Dict[str, Any], context: Dict[str, Any]) -> str: """在 Docker 容器中执行 Python 代码，可选安装库和发送输出文件。""" code = args.get("code", "") @@ -38,11 +138,6 @@ async def execute(args: Dict[str, Any], context: Dict[str, Any]) -> str: if not _SAFE_LIB_PATTERN.match(lib): return f"错误: 无效的库名 '{lib}'。" - # 验证文件路径必须在 /tmp/ 下 - for fpath in send_files: - if not fpath.startswith("/tmp/"): - return f"错误: 输出文件路径必须在 /tmp/ 目录下: '{fpath}'" - has_libs = bool(libraries) memory = MEMORY_LIMIT_WITH_LIBS if has_libs else MEMORY_LIMIT timeout = TIMEOUT_WITH_LIBS if has_libs else TIMEOUT @@ -51,46 +146,45 @@ async def execute(args: Dict[str, Any], context: Dict[str, Any]) -> str: host_tmpdir = tempfile.mkdtemp(prefix="pyinterp_") try: + # 验证文件路径必须绑定到容器 /tmp，并且不能逃逸宿主机临时目录 + for fpath in send_files: + if _resolve_output_host_path(fpath, host_tmpdir) is None: + return f"错误: 输出文件路径必须位于容器 /tmp 目录内: '{fpath}'" + # 将代码写入脚本文件（避免 shell 引号转义问题） script_path = os.path.join(host_tmpdir, "_script.py") with open(script_path, "w", encoding="utf-8") as f: f.write(code) - # 构建 docker 命令 - cmd: list[str] = [ - "docker", - "run", - "--rm", - "--memory", - memory, - "--cpus", - CPU_LIMIT, - "-v", - f"{host_tmpdir}:/tmp", - ] + deadline = time.monotonic() + timeout if has_libs: - # 需要网络下载包、需要写权限安装包 + # 单独安装依赖，再以无网络/只读根文件系统执行用户代码。 req_path = os.path.join(host_tmpdir, "_requirements.txt") with open(req_path, "w", encoding="utf-8") as f: for lib in libraries: f.write(lib + "\n") - cmd.append(DOCKER_IMAGE) - # pip install → 运行代码 → 修正文件权限以便宿主机清理 - cmd.extend( - [ - "sh", - "-c", - "pip install --quiet -r /tmp/_requirements.txt " - "&& python /tmp/_script.py; " - "_e=$?; chmod -R a+rw /tmp 2>/dev/null; exit $_e", - ] + install_timeout = max(deadline - time.monotonic(), 1.0) + install_cmd = _build_install_cmd(host_tmpdir, memory) + install_code, install_stdout, install_stderr = await _run_docker_command( + install_cmd, + timeout=install_timeout, + ) + if install_code != 0: + return ( + f"依赖安装失败 (退出代码: {install_code}):\n" + f"{install_stderr}\n{install_stdout}" + ) + + exec_timeout = max(deadline - time.monotonic(), 1.0) + cmd = _build_exec_cmd( + host_tmpdir, + memory, + pythonpath="/tmp/_site_packages", ) else: - # 无需网络、只读文件系统 - cmd.extend(["--network", "none", "--read-only"]) - cmd.append(DOCKER_IMAGE) - cmd.extend(["python", "/tmp/_script.py"]) + cmd = _build_exec_cmd(host_tmpdir, memory) + exec_timeout = timeout logger.info( "[Python解释器] 开始执行, 超时: %ss, 库: %s, 输出文件: %s", @@ -100,21 +194,12 @@ async def execute(args: Dict[str, Any], context: Dict[str, Any]) -> str: ) logger.debug("[Python解释器] 代码内容:\n%s", code) - process = await asyncio.create_subprocess_exec( - *cmd, - stdout=asyncio.subprocess.PIPE, - stderr=asyncio.subprocess.PIPE, - ) - try: - stdout_bytes, stderr_bytes = await asyncio.wait_for( - process.communicate(), timeout=timeout + exit_code, response, error_output = await _run_docker_command( + cmd, + timeout=exec_timeout, ) - exit_code = process.returncode - response = stdout_bytes.decode("utf-8", errors="replace") - error_output = stderr_bytes.decode("utf-8", errors="replace") - # 构建结果 parts: list[str] = [] if exit_code == 0: @@ -135,11 +220,6 @@ async def execute(args: Dict[str, Any], context: Dict[str, Any]) -> str: return "\n".join(parts) except asyncio.TimeoutError: - try: - process.terminate() - await process.wait() - except Exception as e: - logger.error("[Python解释器] 终止超时进程失败: %s", e) return f"错误: 代码执行超时 ({timeout}s)。" except Exception as e: @@ -165,9 +245,12 @@ async def _send_output_files( results: list[str] = [] for container_path in send_files: - # /tmp/output.png → {host_tmpdir}/output.png - relative = container_path.removeprefix("/tmp/") - host_path = os.path.join(host_tmpdir, relative) + resolved_host_path = _resolve_output_host_path(container_path, host_tmpdir) + if resolved_host_path is None: + results.append(f"文件路径非法: {container_path}") + continue + + host_path = str(resolved_host_path) if not os.path.isfile(host_path): results.append(f"文件未找到: {container_path}") diff --git a/src/Undefined/utils/sender.py b/src/Undefined/utils/sender.py index cd92bb56..1eeaaa6c 100644 --- a/src/Undefined/utils/sender.py +++ b/src/Undefined/utils/sender.py @@ -19,6 +19,22 @@ MAX_MESSAGE_LENGTH = 4000 +def _extract_message_id(result: object) -> int | None: + if not isinstance(result, dict): + return None + + message_id = result.get("message_id") + if message_id is None: + data = result.get("data") + if isinstance(data, dict): + message_id = data.get("message_id") + + try: + return int(message_id) if message_id is not None else None + except (TypeError, ValueError): + return None + + def _format_size(size_bytes: int | None) -> str: if size_bytes is None or size_bytes < 0: return "未知大小" @@ -105,8 +121,7 @@ async def send_group_message( result = await self.onebot.send_group_message( group_id, segments, mark_sent=mark_sent ) - if isinstance(result, dict): - bot_message_id = result.get("message_id") + bot_message_id = _extract_message_id(result) else: bot_message_id = await self._send_chunked_group( group_id, message, mark_sent=mark_sent, reply_to=reply_to @@ -153,8 +168,8 @@ async def _send_chunked_group( result = await self.onebot.send_group_message( group_id, segments, mark_sent=mark_sent ) - if chunk_count == 1 and isinstance(result, dict): - first_message_id = result.get("message_id") + if chunk_count == 1: + first_message_id = _extract_message_id(result) current_chunk = [] current_length = 0 @@ -171,8 +186,8 @@ async def _send_chunked_group( result = await self.onebot.send_group_message( group_id, segments, mark_sent=mark_sent ) - if chunk_count == 1 and isinstance(result, dict): - first_message_id = result.get("message_id") + if chunk_count == 1: + first_message_id = _extract_message_id(result) logger.info(f"[消息分段] 已完成 {chunk_count} 段消息的发送") return first_message_id @@ -219,8 +234,7 @@ async def send_private_message( result = await self.onebot.send_private_message( user_id, segments, mark_sent=mark_sent ) - if isinstance(result, dict): - bot_message_id = result.get("message_id") + bot_message_id = _extract_message_id(result) else: bot_message_id = await self._send_chunked_private( user_id, message, mark_sent=mark_sent, reply_to=reply_to @@ -266,8 +280,8 @@ async def _send_chunked_private( result = await self.onebot.send_private_message( user_id, segments, mark_sent=mark_sent ) - if chunk_count == 1 and isinstance(result, dict): - first_message_id = result.get("message_id") + if chunk_count == 1: + first_message_id = _extract_message_id(result) current_chunk = [] current_length = 0 @@ -284,8 +298,8 @@ async def _send_chunked_private( result = await self.onebot.send_private_message( user_id, segments, mark_sent=mark_sent ) - if chunk_count == 1 and isinstance(result, dict): - first_message_id = result.get("message_id") + if chunk_count == 1: + first_message_id = _extract_message_id(result) logger.info(f"[消息分段] 已完成 {chunk_count} 段消息的发送") return first_message_id diff --git a/src/Undefined/webui/utils/config_sync.py b/src/Undefined/webui/utils/config_sync.py index d79edc06..61a88626 100644 --- a/src/Undefined/webui/utils/config_sync.py +++ b/src/Undefined/webui/utils/config_sync.py @@ -1,8 +1,11 @@ from __future__ import annotations +import copy import tomllib from dataclasses import dataclass from pathlib import Path +from typing import Any + from Undefined.config.loader import CONFIG_PATH from .comment import CommentMap, parse_comment_map_text @@ -41,9 +44,118 @@ def _collect_added_paths( current_value = current[key] if isinstance(default_value, dict) and isinstance(current_value, dict): added.extend(_collect_added_paths(default_value, current_value, path)) + elif _is_array_of_tables(default_value) and _is_array_of_tables(current_value): + if not default_value or not current_value: + continue + template_item = default_value[0] + for index, current_item in enumerate(current_value): + default_item = ( + default_value[index] + if index < len(default_value) + else template_item + ) + added.extend( + _collect_added_paths( + default_item, + current_item, + f"{path}[{index}]", + ) + ) return added +def _is_array_of_tables(value: Any) -> bool: + return ( + isinstance(value, list) + and bool(value) + and all(isinstance(item, dict) for item in value) + ) + + +def _get_nested_value(data: TomlData, path: tuple[str, ...]) -> Any: + node: Any = data + for key in path: + if not isinstance(node, dict): + return None + node = node.get(key) + if node is None: + return None + return node + + +def _prepare_pool_model_templates( + example_data: TomlData, + current_data: TomlData, +) -> TomlData: + prepared = copy.deepcopy(example_data) + + for model_kind in ("chat", "agent"): + current_models = _get_nested_value( + current_data, + ("models", model_kind, "pool", "models"), + ) + example_models = _get_nested_value( + prepared, + ("models", model_kind, "pool", "models"), + ) + model_table = _get_nested_value(prepared, ("models", model_kind)) + + if not (_is_array_of_tables(current_models) and current_models): + continue + if example_models != []: + continue + if not isinstance(model_table, dict): + continue + + template = { + key: copy.deepcopy(value) + for key, value in model_table.items() + if key != "pool" + } + pool_table = model_table.get("pool") + if not isinstance(pool_table, dict): + continue + pool_table["models"] = [template] + + return prepared + + +def _augment_pool_model_comments( + example_comments: CommentMap, + example_data: TomlData, + current_data: TomlData, +) -> CommentMap: + merged: CommentMap = dict(example_comments) + for model_kind in ("chat", "agent"): + current_models = _get_nested_value( + current_data, + ("models", model_kind, "pool", "models"), + ) + example_models = _get_nested_value( + example_data, + ("models", model_kind, "pool", "models"), + ) + if not (_is_array_of_tables(current_models) and current_models): + continue + if example_models != []: + continue + + source_prefix = f"models.{model_kind}" + target_prefix = f"models.{model_kind}.pool.models" + for path, value in example_comments.items(): + if path == source_prefix: + merged[target_prefix] = dict(value) + continue + if not path.startswith(f"{source_prefix}."): + continue + suffix = path.removeprefix(source_prefix) + if suffix.startswith(".pool"): + continue + merged[f"{target_prefix}{suffix}"] = dict(value) + + return merged + + def _merge_comment_maps(current: CommentMap, example: CommentMap) -> CommentMap: merged: CommentMap = dict(current) for key, value in example.items(): @@ -54,11 +166,13 @@ def _merge_comment_maps(current: CommentMap, example: CommentMap) -> CommentMap: def sync_config_text(current_text: str, example_text: str) -> ConfigTemplateSyncResult: current_data = _parse_toml_text(current_text, label="current config") example_data = _parse_toml_text(example_text, label="config example") - added_paths = _collect_added_paths(example_data, current_data) - merged = merge_defaults(example_data, current_data) + prepared_example_data = _prepare_pool_model_templates(example_data, current_data) + added_paths = _collect_added_paths(prepared_example_data, current_data) + merged = merge_defaults(prepared_example_data, current_data) + example_comments = parse_comment_map_text(example_text) comments = _merge_comment_maps( parse_comment_map_text(current_text), - parse_comment_map_text(example_text), + _augment_pool_model_comments(example_comments, example_data, current_data), ) content = render_toml(merged, comments=comments) return ConfigTemplateSyncResult( diff --git a/src/Undefined/webui/utils/toml_render.py b/src/Undefined/webui/utils/toml_render.py index 7bf9e90f..ed2538a3 100644 --- a/src/Undefined/webui/utils/toml_render.py +++ b/src/Undefined/webui/utils/toml_render.py @@ -194,6 +194,21 @@ def merge_defaults(defaults: TomlData, data: TomlData) -> TomlData: for key, value in data.items(): if isinstance(value, dict) and isinstance(merged.get(key), dict): merged[key] = merge_defaults(merged[key], value) + elif _is_array_of_tables(value) and _is_array_of_tables(merged.get(key)): + default_items = cast(list[TomlData], merged[key]) + current_items = cast(list[TomlData], value) + if not default_items: + merged[key] = list(current_items) + continue + + template_item = default_items[0] + merged[key] = [ + merge_defaults( + default_items[idx] if idx < len(default_items) else template_item, + item, + ) + for idx, item in enumerate(current_items) + ] else: merged[key] = value return merged diff --git a/tests/test_config_template_sync.py b/tests/test_config_template_sync.py index 9eed5cc6..e57c2189 100644 --- a/tests/test_config_template_sync.py +++ b/tests/test_config_template_sync.py @@ -65,3 +65,53 @@ def test_sync_config_text_preserves_multiline_string_values() -> None: parsed["models"]["embedding"]["query_instruction"] == "第一行\n第二行\n第三行" ) assert parsed["models"]["embedding"]["document_instruction"] == "文档前缀\n第二行" + + +def test_sync_config_text_merges_new_fields_into_existing_pool_model_entries() -> None: + current = """ +[models.chat] +api_url = "https://primary.example/v1" +api_key = "primary-key" +model_name = "primary-model" +max_tokens = 4096 + +[models.chat.pool] +enabled = true +strategy = "round_robin" + +[[models.chat.pool.models]] +model_name = "pool-a" +api_url = "https://pool.example/v1" +api_key = "pool-key" +max_tokens = 2048 +""" + example = """ +[models.chat] +api_url = "" +api_key = "" +model_name = "" +max_tokens = 4096 +api_mode = "responses" +responses_tool_choice_compat = true +responses_force_stateless_replay = true + +[models.chat.request_params] +temperature = 0.2 + +[models.chat.pool] +enabled = false +strategy = "default" +models = [] +""" + + result = sync_config_text(current, example) + parsed = tomllib.loads(result.content) + model = parsed["models"]["chat"]["pool"]["models"][0] + + assert model["model_name"] == "pool-a" + assert model["api_mode"] == "responses" + assert model["responses_tool_choice_compat"] is True + assert model["responses_force_stateless_replay"] is True + assert model["request_params"]["temperature"] == 0.2 + assert "models.chat.pool.models[0].api_mode" in result.added_paths + assert "models.chat.pool.models[0].request_params" in result.added_paths diff --git a/tests/test_model_pool.py b/tests/test_model_pool.py index ff6deec8..92c9e4f8 100644 --- a/tests/test_model_pool.py +++ b/tests/test_model_pool.py @@ -8,7 +8,12 @@ import pytest from Undefined.ai.model_selector import ModelSelector -from Undefined.config.models import ChatModelConfig, ModelPool, ModelPoolEntry +from Undefined.config.models import ( + AgentModelConfig, + ChatModelConfig, + ModelPool, + ModelPoolEntry, +) from Undefined.services.model_pool import ModelPoolService @@ -295,6 +300,72 @@ def test_get_all_chat_models( assert models[1][0] == "model-a" assert models[2][0] == "model-b" + def test_select_chat_config_preserves_responses_flags( + self, + model_selector: ModelSelector, + ) -> None: + primary = ChatModelConfig( + api_url="https://api.example.com/v1", + api_key="primary-key", + model_name="primary-model", + max_tokens=4096, + pool=ModelPool( + enabled=True, + strategy="round_robin", + models=[ + ModelPoolEntry( + api_url="https://pool.example.com/v1", + api_key="pool-key", + model_name="pool-model", + max_tokens=2048, + api_mode="responses", + responses_tool_choice_compat=True, + responses_force_stateless_replay=True, + ) + ], + ), + ) + + result = model_selector.select_chat_config(primary, global_enabled=True) + + assert result.model_name == "pool-model" + assert result.api_mode == "responses" + assert result.responses_tool_choice_compat is True + assert result.responses_force_stateless_replay is True + + def test_select_agent_config_preserves_responses_flags( + self, + model_selector: ModelSelector, + ) -> None: + primary = AgentModelConfig( + api_url="https://api.example.com/v1", + api_key="primary-key", + model_name="primary-agent", + max_tokens=4096, + pool=ModelPool( + enabled=True, + strategy="round_robin", + models=[ + ModelPoolEntry( + api_url="https://pool.example.com/v1", + api_key="pool-key", + model_name="pool-agent", + max_tokens=2048, + api_mode="responses", + responses_tool_choice_compat=True, + responses_force_stateless_replay=True, + ) + ], + ), + ) + + result = model_selector.select_agent_config(primary, global_enabled=True) + + assert result.model_name == "pool-agent" + assert result.api_mode == "responses" + assert result.responses_tool_choice_compat is True + assert result.responses_force_stateless_replay is True + class TestModelPoolServiceHandleMessage: """测试 ModelPoolService 的消息处理""" diff --git a/tests/test_python_interpreter_handler.py b/tests/test_python_interpreter_handler.py new file mode 100644 index 00000000..5a2aeee0 --- /dev/null +++ b/tests/test_python_interpreter_handler.py @@ -0,0 +1,105 @@ +from __future__ import annotations + +import asyncio +from pathlib import Path + +import pytest + +from Undefined.skills.tools.python_interpreter import handler as python_handler + + +class _FakeProcess: + def __init__(self, *, returncode: int = 0) -> None: + self.returncode = returncode + + async def communicate(self) -> tuple[bytes, bytes]: + return b"", b"" + + def terminate(self) -> None: + return None + + async def wait(self) -> int: + return self.returncode + + +def test_resolve_output_host_path_rejects_symlink_escape(tmp_path: Path) -> None: + host_tmpdir = tmp_path / "mounted" + host_tmpdir.mkdir() + outside_file = tmp_path / "secret.txt" + outside_file.write_text("secret", encoding="utf-8") + (host_tmpdir / "leak.txt").symlink_to(outside_file) + + assert ( + python_handler._resolve_output_host_path( + "/tmp/leak.txt", + str(host_tmpdir), + ) + is None + ) + + +@pytest.mark.asyncio +async def test_execute_rejects_send_files_that_escape_tmp_mount( + monkeypatch: pytest.MonkeyPatch, +) -> None: + async def _unexpected_subprocess(*args: object, **kwargs: object) -> None: + raise AssertionError("subprocess should not be called") + + monkeypatch.setattr( + asyncio, + "create_subprocess_exec", + _unexpected_subprocess, + ) + + result = await python_handler.execute( + { + "code": "print('hello')", + "send_files": ["/tmp/../../data0/Undefined/config.toml"], + }, + {}, + ) + + assert "错误: 输出文件路径必须位于容器 /tmp 目录内" in result + + +@pytest.mark.asyncio +async def test_execute_with_libraries_runs_user_code_in_network_isolated_container( + monkeypatch: pytest.MonkeyPatch, +) -> None: + calls: list[tuple[str, ...]] = [] + + async def _fake_create_subprocess_exec( + *args: str, **kwargs: object + ) -> _FakeProcess: + calls.append(tuple(args)) + return _FakeProcess() + + monkeypatch.setattr( + asyncio, + "create_subprocess_exec", + _fake_create_subprocess_exec, + ) + + result = await python_handler.execute( + { + "code": "print('hello')", + "libraries": ["requests"], + }, + {}, + ) + + assert result == "代码执行成功 (无输出)。" + assert len(calls) == 2 + + install_cmd = calls[0] + exec_cmd = calls[1] + + assert "--network" not in install_cmd + assert "python /tmp/_script.py" not in " ".join(install_cmd) + assert "pip install" in " ".join(install_cmd) + + assert "--network" in exec_cmd + assert "none" in exec_cmd + assert "--read-only" in exec_cmd + assert "PYTHONPATH=/tmp/_site_packages" in exec_cmd + assert "python /tmp/_script.py" in " ".join(exec_cmd) diff --git a/tests/test_sender.py b/tests/test_sender.py new file mode 100644 index 00000000..221d458f --- /dev/null +++ b/tests/test_sender.py @@ -0,0 +1,61 @@ +from __future__ import annotations + +from typing import cast +from unittest.mock import AsyncMock, MagicMock + +import pytest + +from Undefined.utils.sender import MAX_MESSAGE_LENGTH, MessageSender + + +@pytest.fixture +def sender() -> MessageSender: + onebot = MagicMock() + history_manager = MagicMock() + history_manager.add_group_message = AsyncMock() + history_manager.add_private_message = AsyncMock() + + config = MagicMock() + config.is_group_allowed.return_value = True + config.is_private_allowed.return_value = True + config.access_control_enabled.return_value = False + config.group_access_denied_reason.return_value = None + config.private_access_denied_reason.return_value = None + + return MessageSender(onebot, history_manager, bot_qq=10000, config=config) + + +@pytest.mark.asyncio +async def test_send_group_message_reads_message_id_from_onebot_envelope( + sender: MessageSender, +) -> None: + sender.onebot.send_group_message = AsyncMock( # type: ignore[method-assign] + return_value={"data": {"message_id": 123456}} + ) + + await sender.send_group_message(12345, "hello group") + + mock = cast(AsyncMock, sender.history_manager.add_group_message) + assert mock.await_count == 1 + assert mock.await_args is not None + assert mock.await_args.kwargs["message_id"] == 123456 + + +@pytest.mark.asyncio +async def test_send_private_message_reads_message_id_from_chunked_envelope( + sender: MessageSender, +) -> None: + sender.onebot.send_private_message = AsyncMock( # type: ignore[method-assign] + side_effect=[ + {"data": {"message_id": "223344"}}, + {"data": {"message_id": "223345"}}, + ] + ) + long_message = f"{'a' * (MAX_MESSAGE_LENGTH - 500)}\n{'b' * 700}" + + await sender.send_private_message(54321, long_message) + + mock = cast(AsyncMock, sender.history_manager.add_private_message) + assert mock.await_count == 1 + assert mock.await_args is not None + assert mock.await_args.kwargs["message_id"] == 223344 From a61161734cf0d9c3b203bb6abfd57d8d3fde6858 Mon Sep 17 00:00:00 2001 From: Null <1708213363@qq.com> Date: Sun, 8 Mar 2026 00:10:39 +0800 Subject: [PATCH 18/21] fix: address review issues in responses and python interpreter Handle Responses replies from gateways that return top-level output_text, preserve tool replay offsets after prefetch injection, and avoid racing temp cleanup with OneBot file reads while lowering container privileges. Co-Authored-By: Claude Opus 4.6 --- src/Undefined/ai/client.py | 2 +- .../ai/transports/openai_transport.py | 10 +- .../tools/python_interpreter/handler.py | 43 +++++++- tests/test_llm_request_params.py | 99 ++++++++++++++++++- tests/test_python_interpreter_handler.py | 51 ++++++++++ 5 files changed, 194 insertions(+), 11 deletions(-) diff --git a/src/Undefined/ai/client.py b/src/Undefined/ai/client.py index 86153ddc..7df04e19 100644 --- a/src/Undefined/ai/client.py +++ b/src/Undefined/ai/client.py @@ -648,7 +648,6 @@ async def request_model( transport_state: dict[str, Any] | None = None, **kwargs: Any, ) -> dict[str, Any]: - message_count_for_transport = len(messages) tools = self.tool_manager.maybe_merge_agent_tools(call_type, tools) if not ( isinstance(transport_state, dict) @@ -657,6 +656,7 @@ async def request_model( messages, tools = await self._maybe_prefetch_tools( messages, tools, call_type ) + message_count_for_transport = len(messages) return await self._requester.request( model_config=model_config, messages=messages, diff --git a/src/Undefined/ai/transports/openai_transport.py b/src/Undefined/ai/transports/openai_transport.py index 67e07101..5c6d7e7e 100644 --- a/src/Undefined/ai/transports/openai_transport.py +++ b/src/Undefined/ai/transports/openai_transport.py @@ -440,6 +440,10 @@ def normalize_responses_result( assistant_texts.append(str(part.get("text"))) elif part_type == "refusal" and part.get("refusal") is not None: assistant_texts.append(str(part.get("refusal"))) + else: + text = _stringify_content(content) + if text: + assistant_texts.append(text) elif item_type == "function_call": function_name = str(item.get("name", "")).strip() if api_to_internal: @@ -458,9 +462,13 @@ def normalize_responses_result( } ) + content = "\n".join(text for text in assistant_texts if text).strip() + if not content and "output_text" in result: + content = str(result["output_text"]).strip() + message: dict[str, Any] = { "role": "assistant", - "content": "\n".join(text for text in assistant_texts if text).strip(), + "content": content, } reasoning_content = _collect_reasoning_text(output) if reasoning_content: diff --git a/src/Undefined/skills/tools/python_interpreter/handler.py b/src/Undefined/skills/tools/python_interpreter/handler.py index e935c7ec..2262dc74 100644 --- a/src/Undefined/skills/tools/python_interpreter/handler.py +++ b/src/Undefined/skills/tools/python_interpreter/handler.py @@ -12,26 +12,35 @@ # Docker 执行配置 DOCKER_IMAGE = "python:3.11-slim" +DOCKER_USER = "65534:65534" MEMORY_LIMIT = "128m" MEMORY_LIMIT_WITH_LIBS = "512m" CPU_LIMIT = "0.5" TIMEOUT = 480 # 8 分钟 TIMEOUT_WITH_LIBS = 600 # 10 分钟（pip 安装需要更多时间） +OUTPUT_FILE_RETENTION_SECONDS = 30.0 # 图片扩展名（内联发送而非文件附件） _IMAGE_EXTENSIONS = frozenset({".png", ".jpg", ".jpeg", ".gif", ".bmp", ".webp"}) # 安全：库名仅允许 PyPI 合法字符，必须以字母/数字开头（防止 -r/-e/--index-url 注入） _SAFE_LIB_PATTERN = re.compile(r"^[A-Za-z0-9][A-Za-z0-9._\-\[\],<>=!~]*$") +_PENDING_CLEANUP_TASKS: set[asyncio.Task[None]] = set() -def _resolve_output_host_path(container_path: str, host_tmpdir: str) -> Path | None: - """将容器内 /tmp 路径映射到宿主机临时目录，并拒绝目录穿越/符号链接逃逸。""" +def _get_output_relative_path(container_path: str) -> PurePosixPath | None: try: - pure_path = PurePosixPath(container_path) - relative = pure_path.relative_to("/tmp") + relative = PurePosixPath(container_path).relative_to("/tmp") except (TypeError, ValueError): return None + return relative if relative.parts else None + + +def _resolve_output_host_path(container_path: str, host_tmpdir: str) -> Path | None: + """将容器内 /tmp 路径映射到宿主机临时目录，并拒绝目录穿越/符号链接逃逸。""" + relative = _get_output_relative_path(container_path) + if relative is None: + return None host_tmp_root = Path(host_tmpdir).resolve() candidate = (host_tmp_root / relative.as_posix()).resolve(strict=False) @@ -44,6 +53,23 @@ def _resolve_output_host_path(container_path: str, host_tmpdir: str) -> Path | N return candidate +async def _cleanup_output_dir_later(host_tmpdir: str, delay_seconds: float) -> None: + try: + await asyncio.sleep(delay_seconds) + await asyncio.to_thread(shutil.rmtree, host_tmpdir, True) + finally: + task = asyncio.current_task() + if task is not None: + _PENDING_CLEANUP_TASKS.discard(task) + + +def _schedule_output_dir_cleanup(host_tmpdir: str) -> None: + task = asyncio.create_task( + _cleanup_output_dir_later(host_tmpdir, OUTPUT_FILE_RETENTION_SECONDS) + ) + _PENDING_CLEANUP_TASKS.add(task) + + def _build_docker_base_cmd(host_tmpdir: str, memory: str) -> list[str]: return [ "docker", @@ -53,6 +79,8 @@ def _build_docker_base_cmd(host_tmpdir: str, memory: str) -> list[str]: memory, "--cpus", CPU_LIMIT, + "--user", + DOCKER_USER, "-v", f"{host_tmpdir}:/tmp", ] @@ -144,6 +172,7 @@ async def execute(args: Dict[str, Any], context: Dict[str, Any]) -> str: # 创建宿主机临时目录，绑定挂载到容器 /tmp host_tmpdir = tempfile.mkdtemp(prefix="pyinterp_") + defer_cleanup = False try: # 验证文件路径必须绑定到容器 /tmp，并且不能逃逸宿主机临时目录 @@ -216,6 +245,7 @@ async def execute(args: Dict[str, Any], context: Dict[str, Any]) -> str: file_result = await _send_output_files(send_files, host_tmpdir, context) if file_result: parts.append(file_result) + defer_cleanup = True return "\n".join(parts) @@ -226,7 +256,10 @@ async def execute(args: Dict[str, Any], context: Dict[str, Any]) -> str: logger.exception("[Python解释器] 执行出错: %s", e) return "执行出错，请检查代码或重试" finally: - shutil.rmtree(host_tmpdir, ignore_errors=True) + if defer_cleanup: + _schedule_output_dir_cleanup(host_tmpdir) + else: + shutil.rmtree(host_tmpdir, ignore_errors=True) async def _send_output_files( diff --git a/tests/test_llm_request_params.py b/tests/test_llm_request_params.py index 5d0c6cdb..f68c46ed 100644 --- a/tests/test_llm_request_params.py +++ b/tests/test_llm_request_params.py @@ -7,6 +7,7 @@ from openai import AsyncOpenAI, BadRequestError from Undefined.ai.llm import ModelRequester, _encode_tool_name_for_api +from Undefined.ai.transports.openai_transport import normalize_responses_result from Undefined.ai.parsing import extract_choices_content from Undefined.config.models import ChatModelConfig from Undefined.token_usage_storage import TokenUsageStorage @@ -231,7 +232,34 @@ async def test_responses_request_normalizes_tool_calls_and_usage() -> None: "tool_result_start_index": 2, } - await requester._http_client.aclose() + +def test_normalize_responses_result_falls_back_to_output_text_and_scalar_content() -> ( + None +): + top_level = normalize_responses_result( + { + "id": "resp_top_level", + "output": [], + "output_text": "hello from gateway", + } + ) + assert top_level["choices"][0]["message"]["content"] == "hello from gateway" + + scalar_content = normalize_responses_result( + { + "id": "resp_scalar", + "output": [ + { + "type": "message", + "role": "assistant", + "content": {"text": "hello from content object"}, + } + ], + } + ) + assert scalar_content["choices"][0]["message"]["content"] == ( + "hello from content object" + ) @pytest.mark.asyncio @@ -427,11 +455,74 @@ async def test_responses_transport_state_uses_previous_response_id_and_tool_outp "total_tokens": 7, } - await requester._http_client.aclose() - @pytest.mark.asyncio -async def test_responses_force_stateless_replay_skips_previous_response_id() -> None: +async def test_responses_transport_state_uses_prefetched_message_count() -> None: + requester = ModelRequester( + http_client=httpx.AsyncClient(), + token_usage_storage=cast(TokenUsageStorage, _FakeUsageStorage()), + ) + fake_client = _FakeClient( + responses=[ + { + "id": "resp_prefetch", + "output": [ + { + "type": "function_call", + "call_id": "call_prefetch", + "name": "lookup", + "arguments": '{"query": "weather"}', + } + ], + "usage": {"input_tokens": 3, "output_tokens": 2, "total_tokens": 5}, + } + ] + ) + setattr( + requester, + "_get_openai_client_for_model", + lambda _cfg: cast(AsyncOpenAI, fake_client), + ) + cfg = ChatModelConfig( + api_url="https://api.openai.com/v1", + api_key="sk-test", + model_name="gpt-test", + max_tokens=512, + api_mode="responses", + ) + + result = await requester.request( + model_config=cfg, + messages=[ + {"role": "system", "content": "prefetch result"}, + {"role": "user", "content": "hello"}, + ], + max_tokens=128, + call_type="chat", + tools=[ + { + "type": "function", + "function": { + "name": "lookup", + "description": "lookup weather", + "parameters": { + "type": "object", + "properties": {"query": {"type": "string"}}, + "required": ["query"], + }, + }, + } + ], + message_count_for_transport=2, + ) + + assert result["_transport_state"] == { + "api_mode": "responses", + "previous_response_id": "resp_prefetch", + "tool_result_start_index": 3, + } + + await requester._http_client.aclose() requester = ModelRequester( http_client=httpx.AsyncClient(), token_usage_storage=cast(TokenUsageStorage, _FakeUsageStorage()), diff --git a/tests/test_python_interpreter_handler.py b/tests/test_python_interpreter_handler.py index 5a2aeee0..8072c326 100644 --- a/tests/test_python_interpreter_handler.py +++ b/tests/test_python_interpreter_handler.py @@ -1,7 +1,9 @@ from __future__ import annotations import asyncio +import tempfile from pathlib import Path +from unittest.mock import AsyncMock, MagicMock import pytest @@ -97,9 +99,58 @@ async def _fake_create_subprocess_exec( assert "--network" not in install_cmd assert "python /tmp/_script.py" not in " ".join(install_cmd) assert "pip install" in " ".join(install_cmd) + assert "--user" in install_cmd + assert python_handler.DOCKER_USER in install_cmd assert "--network" in exec_cmd assert "none" in exec_cmd assert "--read-only" in exec_cmd assert "PYTHONPATH=/tmp/_site_packages" in exec_cmd assert "python /tmp/_script.py" in " ".join(exec_cmd) + assert "--user" in exec_cmd + assert python_handler.DOCKER_USER in exec_cmd + + +@pytest.mark.asyncio +async def test_execute_defers_cleanup_after_sending_files( + monkeypatch: pytest.MonkeyPatch, + tmp_path: Path, +) -> None: + host_tmpdir = tmp_path / "mounted" + host_tmpdir.mkdir() + output_file = host_tmpdir / "result.txt" + output_file.write_text("hello", encoding="utf-8") + + monkeypatch.setattr(tempfile, "mkdtemp", lambda prefix: str(host_tmpdir)) + monkeypatch.setattr( + python_handler, + "_run_docker_command", + AsyncMock(return_value=(0, "", "")), + ) + send_files_mock = AsyncMock(return_value="已发送: result.txt") + monkeypatch.setattr(python_handler, "_send_output_files", send_files_mock) + cleanup_mock = MagicMock() + monkeypatch.setattr(python_handler, "_schedule_output_dir_cleanup", cleanup_mock) + + result = await python_handler.execute( + { + "code": "print('hello')", + "send_files": ["/tmp/result.txt"], + }, + {}, + ) + + assert result == "代码执行成功 (无输出)。\n已发送: result.txt" + cleanup_mock.assert_called_once_with(str(host_tmpdir)) + assert output_file.exists() + + +@pytest.mark.asyncio +async def test_cleanup_output_dir_later_removes_directory(tmp_path: Path) -> None: + host_tmpdir = tmp_path / "mounted" + host_tmpdir.mkdir() + (host_tmpdir / "result.txt").write_text("hello", encoding="utf-8") + + await python_handler._cleanup_output_dir_later(str(host_tmpdir), 0) + + assert not host_tmpdir.exists() From 9ec403d46fc7423d369f1fc26e852c7429a3abf7 Mon Sep 17 00:00:00 2001 From: Null <1708213363@qq.com> Date: Sun, 8 Mar 2026 10:18:13 +0800 Subject: [PATCH 19/21] fix: delay writing python script until offline execution --- .../skills/tools/python_interpreter/handler.py | 11 +++++++---- tests/test_python_interpreter_handler.py | 17 ++++++++++++----- 2 files changed, 19 insertions(+), 9 deletions(-) diff --git a/src/Undefined/skills/tools/python_interpreter/handler.py b/src/Undefined/skills/tools/python_interpreter/handler.py index 2262dc74..6ad09231 100644 --- a/src/Undefined/skills/tools/python_interpreter/handler.py +++ b/src/Undefined/skills/tools/python_interpreter/handler.py @@ -180,11 +180,7 @@ async def execute(args: Dict[str, Any], context: Dict[str, Any]) -> str: if _resolve_output_host_path(fpath, host_tmpdir) is None: return f"错误: 输出文件路径必须位于容器 /tmp 目录内: '{fpath}'" - # 将代码写入脚本文件（避免 shell 引号转义问题） script_path = os.path.join(host_tmpdir, "_script.py") - with open(script_path, "w", encoding="utf-8") as f: - f.write(code) - deadline = time.monotonic() + timeout if has_libs: @@ -205,6 +201,10 @@ async def execute(args: Dict[str, Any], context: Dict[str, Any]) -> str: f"{install_stderr}\n{install_stdout}" ) + # 避免在有网络的安装阶段暴露用户脚本给依赖安装代码。 + with open(script_path, "w", encoding="utf-8") as f: + f.write(code) + exec_timeout = max(deadline - time.monotonic(), 1.0) cmd = _build_exec_cmd( host_tmpdir, @@ -212,6 +212,9 @@ async def execute(args: Dict[str, Any], context: Dict[str, Any]) -> str: pythonpath="/tmp/_site_packages", ) else: + # 将代码写入脚本文件（避免 shell 引号转义问题） + with open(script_path, "w", encoding="utf-8") as f: + f.write(code) cmd = _build_exec_cmd(host_tmpdir, memory) exec_timeout = timeout diff --git a/tests/test_python_interpreter_handler.py b/tests/test_python_interpreter_handler.py index 8072c326..a50ba072 100644 --- a/tests/test_python_interpreter_handler.py +++ b/tests/test_python_interpreter_handler.py @@ -69,6 +69,7 @@ async def test_execute_with_libraries_runs_user_code_in_network_isolated_contain monkeypatch: pytest.MonkeyPatch, ) -> None: calls: list[tuple[str, ...]] = [] + script_paths: list[str] = [] async def _fake_create_subprocess_exec( *args: str, **kwargs: object @@ -76,11 +77,15 @@ async def _fake_create_subprocess_exec( calls.append(tuple(args)) return _FakeProcess() - monkeypatch.setattr( - asyncio, - "create_subprocess_exec", - _fake_create_subprocess_exec, - ) + real_mkdtemp = tempfile.mkdtemp + + def _tracked_mkdtemp(prefix: str) -> str: + path = real_mkdtemp(prefix=prefix) + script_paths.append(str(Path(path) / "_script.py")) + return path + + monkeypatch.setattr(asyncio, "create_subprocess_exec", _fake_create_subprocess_exec) + monkeypatch.setattr(tempfile, "mkdtemp", _tracked_mkdtemp) result = await python_handler.execute( { @@ -101,6 +106,8 @@ async def _fake_create_subprocess_exec( assert "pip install" in " ".join(install_cmd) assert "--user" in install_cmd assert python_handler.DOCKER_USER in install_cmd + assert len(script_paths) == 1 + assert not Path(script_paths[0]).exists() assert "--network" in exec_cmd assert "none" in exec_cmd From f9170052692450a87fd99914260e6641a783ebe8 Mon Sep 17 00:00:00 2001 From: Null <1708213363@qq.com> Date: Sun, 8 Mar 2026 10:40:14 +0800 Subject: [PATCH 20/21] fix: run python interpreter container as host user Use the current host uid/gid for Docker bind mounts so the mounted temp directory remains accessible without opening it to world-writable permissions. Co-Authored-By: Claude Opus 4.6 --- src/Undefined/skills/tools/python_interpreter/handler.py | 7 +++++-- tests/test_python_interpreter_handler.py | 5 +++-- 2 files changed, 8 insertions(+), 4 deletions(-) diff --git a/src/Undefined/skills/tools/python_interpreter/handler.py b/src/Undefined/skills/tools/python_interpreter/handler.py index 6ad09231..002bf560 100644 --- a/src/Undefined/skills/tools/python_interpreter/handler.py +++ b/src/Undefined/skills/tools/python_interpreter/handler.py @@ -12,7 +12,6 @@ # Docker 执行配置 DOCKER_IMAGE = "python:3.11-slim" -DOCKER_USER = "65534:65534" MEMORY_LIMIT = "128m" MEMORY_LIMIT_WITH_LIBS = "512m" CPU_LIMIT = "0.5" @@ -70,6 +69,10 @@ def _schedule_output_dir_cleanup(host_tmpdir: str) -> None: _PENDING_CLEANUP_TASKS.add(task) +def _get_docker_user() -> str: + return f"{os.getuid()}:{os.getgid()}" + + def _build_docker_base_cmd(host_tmpdir: str, memory: str) -> list[str]: return [ "docker", @@ -80,7 +83,7 @@ def _build_docker_base_cmd(host_tmpdir: str, memory: str) -> list[str]: "--cpus", CPU_LIMIT, "--user", - DOCKER_USER, + _get_docker_user(), "-v", f"{host_tmpdir}:/tmp", ] diff --git a/tests/test_python_interpreter_handler.py b/tests/test_python_interpreter_handler.py index a50ba072..6683eb8d 100644 --- a/tests/test_python_interpreter_handler.py +++ b/tests/test_python_interpreter_handler.py @@ -1,6 +1,7 @@ from __future__ import annotations import asyncio +import os import tempfile from pathlib import Path from unittest.mock import AsyncMock, MagicMock @@ -105,7 +106,7 @@ def _tracked_mkdtemp(prefix: str) -> str: assert "python /tmp/_script.py" not in " ".join(install_cmd) assert "pip install" in " ".join(install_cmd) assert "--user" in install_cmd - assert python_handler.DOCKER_USER in install_cmd + assert f"{os.getuid()}:{os.getgid()}" in install_cmd assert len(script_paths) == 1 assert not Path(script_paths[0]).exists() @@ -115,7 +116,7 @@ def _tracked_mkdtemp(prefix: str) -> str: assert "PYTHONPATH=/tmp/_site_packages" in exec_cmd assert "python /tmp/_script.py" in " ".join(exec_cmd) assert "--user" in exec_cmd - assert python_handler.DOCKER_USER in exec_cmd + assert f"{os.getuid()}:{os.getgid()}" in exec_cmd @pytest.mark.asyncio From cc772cb8182eec317a468d56530ab96001b86ac1 Mon Sep 17 00:00:00 2001 From: Null <1708213363@qq.com> Date: Sun, 8 Mar 2026 10:44:14 +0800 Subject: [PATCH 21/21] chore(version): bump version to 3.1.2 --- pyproject.toml | 2 +- src/Undefined/__init__.py | 2 +- uv.lock | 1012 +++++++++++++++++++------------------ 3 files changed, 521 insertions(+), 495 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 2ca0c342..e9d13689 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [project] name = "Undefined-bot" -version = "3.1.1" +version = "3.1.2" description = "QQ bot platform with cognitive memory architecture and multi-agent Skills, via OneBot V11." readme = "README.md" authors = [ diff --git a/src/Undefined/__init__.py b/src/Undefined/__init__.py index 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