From 17abfc74ae94ce18e8ec53b969d47afed168170b Mon Sep 17 00:00:00 2001 From: Windpicker-owo <3431391539@qq.com> Date: Wed, 12 Nov 2025 21:19:19 +0800 Subject: [PATCH] =?UTF-8?q?refactor(prompt):=20=E4=BC=98=E5=8C=96=E4=BB=BB?= =?UTF-8?q?=E5=8A=A1=E5=B9=B6=E5=8F=91=E6=89=A7=E8=A1=8C=E9=80=BB=E8=BE=91?= =?UTF-8?q?=EF=BC=8C=E4=BD=BF=E7=94=A8=20as=5Fcompleted=20=E6=8F=90?= =?UTF-8?q?=E5=8D=87=E6=80=A7=E8=83=BD=E5=92=8C=E9=94=99=E8=AF=AF=E5=A4=84?= =?UTF-8?q?=E7=90=86?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- src/chat/utils/prompt.py | 302 ++++++++++++++++++++++++++++----------- 1 file changed, 217 insertions(+), 85 deletions(-) diff --git a/src/chat/utils/prompt.py b/src/chat/utils/prompt.py index e954d6b63..966f577db 100644 --- a/src/chat/utils/prompt.py +++ b/src/chat/utils/prompt.py @@ -24,7 +24,6 @@ install(extra_lines=3) logger = get_logger("unified_prompt") - class PromptContext: """提示词上下文管理器. @@ -41,7 +40,9 @@ class PromptContext: # _current_context_var: 使用contextvars来存储当前协程的上下文ID。 # 这确保了在并发执行的异步任务中，每个任务都能访问到正确的上下文ID。 - self._current_context_var = contextvars.ContextVar("current_context", default=None) + self._current_context_var = contextvars.ContextVar( + "current_context", default=None + ) # _context_lock: 一个异步锁，用于保护对共享资源_context_prompts的并发访问。 self._context_lock = asyncio.Lock() @@ -120,7 +121,9 @@ class PromptContext: return self._context_prompts[current_context][name] return None - async def register_async(self, prompt: "Prompt", context_id: str | None = None) -> None: + async def register_async( + self, prompt: "Prompt", context_id: str | None = None + ) -> None: """异步、安全地将提示模板注册到指定的作用域. 如果未指定context_id，则注册到当前协程的上下文中。 @@ -130,7 +133,9 @@ class PromptContext: if target_context := context_id or self._current_context: if prompt.name: # 使用setdefault确保目标上下文的字典存在，然后注册prompt - self._context_prompts.setdefault(target_context, {})[prompt.name] = prompt + self._context_prompts.setdefault(target_context, {})[ + prompt.name + ] = prompt class PromptManager: @@ -158,7 +163,9 @@ class PromptManager: async with self._context.async_scope(message_id): yield self - async def get_prompt_async(self, name: str, parameters: PromptParameters | None = None) -> "Prompt": + async def get_prompt_async( + self, name: str, parameters: PromptParameters | None = None + ) -> "Prompt": """异步获取提示模板，并动态地将插件内容注入其中. 获取提示词的优先级顺序为： @@ -309,12 +316,16 @@ class Prompt: elif not isinstance(template, str): template = str(template) - return template.replace("\\{", Prompt._TEMP_LEFT_BRACE).replace("\\}", Prompt._TEMP_RIGHT_BRACE) + return template.replace("\\{", Prompt._TEMP_LEFT_BRACE).replace( + "\\}", Prompt._TEMP_RIGHT_BRACE + ) @staticmethod def _restore_escaped_braces(template: str) -> str: """在格式化完成后，将临时标记还原为实际的花括号字符 `{` 和 `}`.""" - return template.replace(Prompt._TEMP_LEFT_BRACE, "{").replace(Prompt._TEMP_RIGHT_BRACE, "}") + return template.replace(Prompt._TEMP_LEFT_BRACE, "{").replace( + Prompt._TEMP_RIGHT_BRACE, "}" + ) def _parse_template_args(self, template: str) -> list[str]: """从模板字符串中解析出所有占位符（例如 "{user_name}" -> "user_name"）.""" @@ -365,7 +376,9 @@ class Prompt: result = main_formatted_prompt total_time = time.time() - start_time - logger.debug(f"Prompt构建完成，模式: {self.parameters.prompt_mode}, 耗时: {total_time:.2f}s") + logger.debug( + f"Prompt构建完成，模式: {self.parameters.prompt_mode}, 耗时: {total_time:.2f}s" + ) # 缓存结果 self._formatted_result = result @@ -410,9 +423,13 @@ class Prompt: # 如果参数对象中已经包含了某些block，说明它们是外部预构建的， # 我们将它们存起来，并跳过对应的实时构建任务。 if self.parameters.expression_habits_block: - pre_built_params["expression_habits_block"] = self.parameters.expression_habits_block + pre_built_params["expression_habits_block"] = ( + self.parameters.expression_habits_block + ) if self.parameters.relation_info_block: - pre_built_params["relation_info_block"] = self.parameters.relation_info_block + pre_built_params["relation_info_block"] = ( + self.parameters.relation_info_block + ) if self.parameters.memory_block: pre_built_params["memory_block"] = self.parameters.memory_block logger.debug("使用预构建的memory_block，跳过实时构建") @@ -421,12 +438,16 @@ class Prompt: if self.parameters.knowledge_prompt: pre_built_params["knowledge_prompt"] = self.parameters.knowledge_prompt if self.parameters.cross_context_block: - pre_built_params["cross_context_block"] = self.parameters.cross_context_block + pre_built_params["cross_context_block"] = ( + self.parameters.cross_context_block + ) if self.parameters.notice_block: pre_built_params["notice_block"] = self.parameters.notice_block # --- 步骤 1.2: 根据参数和预构建情况，决定需要实时运行的任务 --- - if self.parameters.enable_expression and not pre_built_params.get("expression_habits_block"): + if self.parameters.enable_expression and not pre_built_params.get( + "expression_habits_block" + ): tasks.append(self._build_expression_habits()) task_names.append("expression_habits") @@ -434,19 +455,27 @@ class Prompt: # 使用新的记忆图系统，不再在 prompt.py 中构建记忆 # 如果需要记忆，必须通过 pre_built_params 传入 - if self.parameters.enable_relation and not pre_built_params.get("relation_info_block"): + if self.parameters.enable_relation and not pre_built_params.get( + "relation_info_block" + ): tasks.append(self._build_relation_info()) task_names.append("relation_info") - if self.parameters.enable_tool and not pre_built_params.get("tool_info_block"): + if self.parameters.enable_tool and not pre_built_params.get( + "tool_info_block" + ): tasks.append(self._build_tool_info()) task_names.append("tool_info") - if self.parameters.enable_knowledge and not pre_built_params.get("knowledge_prompt"): + if self.parameters.enable_knowledge and not pre_built_params.get( + "knowledge_prompt" + ): tasks.append(self._build_knowledge_info()) task_names.append("knowledge_info") - if self.parameters.enable_cross_context and not pre_built_params.get("cross_context_block"): + if self.parameters.enable_cross_context and not pre_built_params.get( + "cross_context_block" + ): tasks.append(self._build_cross_context()) task_names.append("cross_context") @@ -463,32 +492,61 @@ class Prompt: "expression_habits": 10.0, } - results = [] - # 循环等待每个任务，而不是使用`asyncio.gather`， - # 这样可以为每个任务应用独立的超时控制。 + # 使用 as_completed 并发执行任务，提供更好的性能和错误处理 + results = [None] * len(tasks) # 预分配结果列表，保持任务顺序 + task_with_meta = [] + + # 准备任务和元数据 for i, task in enumerate(tasks): task_name = task_names[i] if i < len(task_names) else f"task_{i}" - task_timeout = task_timeouts.get(task_name, 2.0) # 未指定超时的任务默认为2秒 + task_timeout = task_timeouts.get( + task_name, 2.0 + ) # 未指定超时的任务默认为2秒 + + # 检查任务是否为协程，非协程任务直接使用默认值 + if asyncio.iscoroutine(task): + task_with_meta.append( + ( + asyncio.wait_for(task, timeout=task_timeout), + task_name, + i, + task_timeout, + ) + ) + else: + logger.warning( + f"任务{task_name}不是协程对象，类型: {type(task)}，跳过处理" + ) + results[i] = self._get_default_result_for_task(task_name) # type: ignore + + # 并发执行任务，使用 as_completed 获得更好的性能 + for future in asyncio.as_completed( + [task_meta[0] for task_meta in task_with_meta] + ): + # 找到对应的任务元数据 + task_index = None + task_name = None + task_timeout = None + + for idx, (task, name, index, timeout) in enumerate(task_with_meta): + if task == future: + task_index = index + task_name = name + task_timeout = timeout + break try: - # 确保任务是可等待的协程 - if asyncio.iscoroutine(task): - # 使用 `asyncio.wait_for` 来执行带超时的任务 - result = await asyncio.wait_for(task, timeout=task_timeout) - results.append(result) - logger.debug(f"构建任务{task_name}完成 ({task_timeout}s)") - else: - # 如果任务不是协程，记录警告并使用默认值 - logger.warning(f"任务{task_name}不是协程对象，类型: {type(task)}，跳过处理") - results.append(self._get_default_result_for_task(task_name)) + result = await future + results[task_index] = result # type: ignore + logger.debug(f"构建任务{task_name}完成 ({task_timeout}s)") except asyncio.TimeoutError: - # 如果任务超时，记录警告并使用默认值 - logger.warning(f"构建任务{task_name}超时 ({task_timeout}s)，使用默认值") - results.append(self._get_default_result_for_task(task_name)) + logger.warning( + f"构建任务{task_name}超时 ({task_timeout}s)，使用默认值" + ) + results[task_index] = self._get_default_result_for_task(task_name) # type: ignore except Exception as e: - # 如果任务执行出错，记录错误并使用默认值 logger.error(f"构建任务{task_name}失败: {e!s}") - results.append(self._get_default_result_for_task(task_name)) + results[task_index] = self._get_default_result_for_task(task_name) # type: ignore # --- 步骤 3: 合并所有结果 --- context_data = {} @@ -501,7 +559,9 @@ class Prompt: context_data.update(result) # 合并预构建的参数，这会覆盖任何同名的实时构建结果 - context_data.update({key: value for key, value in pre_built_params.items() if value}) + context_data.update( + {key: value for key, value in pre_built_params.items() if value} + ) except asyncio.TimeoutError: # 这是一个不太可能发生的、总体的构建超时，作为最后的保障 @@ -522,7 +582,8 @@ class Prompt: { "keywords_reaction_prompt": self.parameters.keywords_reaction_prompt, "extra_info_block": self.parameters.extra_info_block, - "time_block": self.parameters.time_block or f"当前时间：{time.strftime('%Y-%m-%d %H:%M:%S')}", + "time_block": self.parameters.time_block + or f"当前时间：{time.strftime('%Y-%m-%d %H:%M:%S')}", "identity": self.parameters.identity_block, "schedule_block": self.parameters.schedule_block, "moderation_prompt": self.parameters.moderation_prompt_block, @@ -549,20 +610,25 @@ class Prompt: target_user_id = self.parameters.target_user_info.get("user_id") or "" # 调用核心构建逻辑 - read_history_prompt, unread_history_prompt = await self._build_s4u_chat_history_prompts( - self.parameters.message_list_before_now_long, - target_user_id, - self.parameters.sender, - self.parameters.chat_id, + read_history_prompt, unread_history_prompt = ( + await self._build_s4u_chat_history_prompts( + self.parameters.message_list_before_now_long, + target_user_id, + self.parameters.sender, + self.parameters.chat_id, + ) ) # 将构建好的prompt添加到上下文数据中 context_data["read_history_prompt"] = read_history_prompt context_data["unread_history_prompt"] = unread_history_prompt - async def _build_s4u_chat_history_prompts( - self, message_list_before_now: list[dict[str, Any]], target_user_id: str, sender: str, chat_id: str + self, + message_list_before_now: list[dict[str, Any]], + target_user_id: str, + sender: str, + chat_id: str, ) -> tuple[str, str]: """构建S4U风格的已读/未读历史消息prompt. @@ -574,7 +640,9 @@ class Prompt: from src.plugin_system.apis.generator_api import get_replyer # 获取一个临时的生成器实例来访问其方法 - temp_generator = await get_replyer(None, chat_id, request_type="prompt_building") + temp_generator = await get_replyer( + None, chat_id, request_type="prompt_building" + ) if temp_generator: # 调用实际的构建方法 return await temp_generator.build_s4u_chat_history_prompts( @@ -588,7 +656,9 @@ class Prompt: async def _build_expression_habits(self) -> dict[str, Any]: """构建表达习惯（如表情、口癖）的上下文块.""" # 检查当前聊天是否启用了表达习惯功能 - use_expression, _, _ = global_config.expression.get_expression_config_for_chat(self.parameters.chat_id) + use_expression, _, _ = global_config.expression.get_expression_config_for_chat( + self.parameters.chat_id + ) if not use_expression: return {"expression_habits_block": ""} @@ -601,15 +671,20 @@ class Prompt: if self.parameters.message_list_before_now_long: recent_messages = self.parameters.message_list_before_now_long[-10:] chat_history = await build_readable_messages( - recent_messages, replace_bot_name=True, timestamp_mode="normal", truncate=True + recent_messages, + replace_bot_name=True, + timestamp_mode="normal", + truncate=True, ) # 使用统一的表达方式选择入口（支持classic和exp_model模式） expression_selector = ExpressionSelector(self.parameters.chat_id) - selected_expressions = await expression_selector.select_suitable_expressions( - chat_id=self.parameters.chat_id, - chat_history=chat_history, - target_message=self.parameters.target, + selected_expressions = ( + await expression_selector.select_suitable_expressions( + chat_id=self.parameters.chat_id, + chat_history=chat_history, + target_message=self.parameters.target, + ) ) # 将选择的表达习惯格式化为提示词的一部分 @@ -641,7 +716,9 @@ class Prompt: """构建与对话目标相关的关系信息.""" try: # 调用静态方法来执行实际的构建逻辑 - relation_info = await Prompt.build_relation_info(self.parameters.chat_id, self.parameters.reply_to) + relation_info = await Prompt.build_relation_info( + self.parameters.chat_id, self.parameters.reply_to + ) return {"relation_info_block": relation_info} except Exception as e: logger.error(f"构建关系信息失败: {e}") @@ -660,7 +737,10 @@ class Prompt: if self.parameters.message_list_before_now_long: recent_messages = self.parameters.message_list_before_now_long[-15:] chat_history = await build_readable_messages( - recent_messages, replace_bot_name=True, timestamp_mode="normal", truncate=True + recent_messages, + replace_bot_name=True, + timestamp_mode="normal", + truncate=True, ) # 决定是否调用工具并执行 @@ -682,7 +762,9 @@ class Prompt: tool_info_parts.append(f"- 【{tool_name}】{result_type}: {content}") - tool_info_parts.append("以上是你获取到的实时信息，请在回复时参考这些信息。") + tool_info_parts.append( + "以上是你获取到的实时信息，请在回复时参考这些信息。" + ) tool_info_block = "\n".join(tool_info_parts) else: tool_info_block = "" @@ -710,7 +792,10 @@ class Prompt: # 将检索结果格式化为提示词 if knowledge_results and knowledge_results.get("knowledge_items"): - knowledge_parts = ["## 知识库信息", "以下是与你当前对话相关的知识信息："] + knowledge_parts = [ + "## 知识库信息", + "以下是与你当前对话相关的知识信息：", + ] for item in knowledge_results["knowledge_items"]: content = item.get("content", "") @@ -720,20 +805,27 @@ class Prompt: # 过滤掉相关性低于阈值的知识 try: relevance_float = float(relevance) - if relevance_float < global_config.lpmm_knowledge.qa_paragraph_threshold: + if ( + relevance_float + < global_config.lpmm_knowledge.qa_paragraph_threshold + ): continue relevance_str = f"{relevance_float:.2f}" except (ValueError, TypeError): relevance_str = str(relevance) if source: - knowledge_parts.append(f"- [{relevance_str}] {content} (来源: {source})") + knowledge_parts.append( + f"- [{relevance_str}] {content} (来源: {source})" + ) else: knowledge_parts.append(f"- [{relevance_str}] {content}") # 如果有总结，也一并加入 if knowledge_results.get("summary"): - knowledge_parts.append(f"\n知识总结: {knowledge_results['summary']}") + knowledge_parts.append( + f"\n知识总结: {knowledge_results['summary']}" + ) knowledge_prompt = "\n".join(knowledge_parts) else: @@ -750,7 +842,9 @@ class Prompt: try: # 调用静态方法来执行实际的构建逻辑 cross_context = await Prompt.build_cross_context( - self.parameters.chat_id, self.parameters.prompt_mode, self.parameters.target_user_info + self.parameters.chat_id, + self.parameters.prompt_mode, + self.parameters.target_user_info, ) return {"cross_context_block": cross_context} except Exception as e: @@ -769,7 +863,11 @@ class Prompt: params = self._prepare_default_params(context_data) # 如果prompt有名称，则通过全局管理器格式化（这样可以应用注入逻辑），否则直接格式化 - return await global_prompt_manager.format_prompt(self.name, **params) if self.name else self.format(**params) + return ( + await global_prompt_manager.format_prompt(self.name, **params) + if self.name + else self.format(**params) + ) def _prepare_s4u_params(self, context_data: dict[str, Any]) -> dict[str, Any]: """为S4U（Scene for You）模式准备最终用于格式化的参数字典.""" @@ -780,14 +878,20 @@ class Prompt: "knowledge_prompt": context_data.get("knowledge_prompt", ""), "memory_block": context_data.get("memory_block", ""), "relation_info_block": context_data.get("relation_info_block", ""), - "extra_info_block": self.parameters.extra_info_block or context_data.get("extra_info_block", ""), + "extra_info_block": self.parameters.extra_info_block + or context_data.get("extra_info_block", ""), "cross_context_block": context_data.get("cross_context_block", ""), - "notice_block": self.parameters.notice_block or context_data.get("notice_block", ""), - "identity": self.parameters.identity_block or context_data.get("identity", ""), - "action_descriptions": self.parameters.action_descriptions or context_data.get("action_descriptions", ""), - "schedule_block": self.parameters.schedule_block or context_data.get("schedule_block", ""), + "notice_block": self.parameters.notice_block + or context_data.get("notice_block", ""), + "identity": self.parameters.identity_block + or context_data.get("identity", ""), + "action_descriptions": self.parameters.action_descriptions + or context_data.get("action_descriptions", ""), + "schedule_block": self.parameters.schedule_block + or context_data.get("schedule_block", ""), "sender_name": self.parameters.sender or "未知用户", - "mood_state": self.parameters.mood_prompt or context_data.get("mood_state", ""), + "mood_state": self.parameters.mood_prompt + or context_data.get("mood_state", ""), "read_history_prompt": context_data.get("read_history_prompt", ""), "unread_history_prompt": context_data.get("unread_history_prompt", ""), "time_block": context_data.get("time_block", ""), @@ -795,7 +899,8 @@ class Prompt: "reply_style": global_config.personality.reply_style, "keywords_reaction_prompt": self.parameters.keywords_reaction_prompt or context_data.get("keywords_reaction_prompt", ""), - "moderation_prompt": self.parameters.moderation_prompt_block or context_data.get("moderation_prompt", ""), + "moderation_prompt": self.parameters.moderation_prompt_block + or context_data.get("moderation_prompt", ""), "safety_guidelines_block": self.parameters.safety_guidelines_block or context_data.get("safety_guidelines_block", ""), "auth_role_prompt_block": self.parameters.auth_role_prompt_block @@ -813,22 +918,29 @@ class Prompt: "knowledge_prompt": context_data.get("knowledge_prompt", ""), "memory_block": context_data.get("memory_block", ""), "relation_info_block": context_data.get("relation_info_block", ""), - "extra_info_block": self.parameters.extra_info_block or context_data.get("extra_info_block", ""), + "extra_info_block": self.parameters.extra_info_block + or context_data.get("extra_info_block", ""), "cross_context_block": context_data.get("cross_context_block", ""), - "notice_block": self.parameters.notice_block or context_data.get("notice_block", ""), - "identity": self.parameters.identity_block or context_data.get("identity", ""), - "action_descriptions": self.parameters.action_descriptions or context_data.get("action_descriptions", ""), - "schedule_block": self.parameters.schedule_block or context_data.get("schedule_block", ""), + "notice_block": self.parameters.notice_block + or context_data.get("notice_block", ""), + "identity": self.parameters.identity_block + or context_data.get("identity", ""), + "action_descriptions": self.parameters.action_descriptions + or context_data.get("action_descriptions", ""), + "schedule_block": self.parameters.schedule_block + or context_data.get("schedule_block", ""), "time_block": context_data.get("time_block", ""), "chat_info": context_data.get("chat_info", ""), "reply_target_block": context_data.get("reply_target_block", ""), "reply_style": global_config.personality.reply_style, - "mood_state": self.parameters.mood_prompt or context_data.get("mood_state", ""), + "mood_state": self.parameters.mood_prompt + or context_data.get("mood_state", ""), "read_history_prompt": context_data.get("read_history_prompt", ""), "unread_history_prompt": context_data.get("unread_history_prompt", ""), "keywords_reaction_prompt": self.parameters.keywords_reaction_prompt or context_data.get("keywords_reaction_prompt", ""), - "moderation_prompt": self.parameters.moderation_prompt_block or context_data.get("moderation_prompt", ""), + "moderation_prompt": self.parameters.moderation_prompt_block + or context_data.get("moderation_prompt", ""), "safety_guidelines_block": self.parameters.safety_guidelines_block or context_data.get("safety_guidelines_block", ""), "auth_role_prompt_block": self.parameters.auth_role_prompt_block @@ -847,17 +959,21 @@ class Prompt: "chat_target": "", "time_block": context_data.get("time_block", ""), "chat_info": context_data.get("chat_info", ""), - "identity": self.parameters.identity_block or context_data.get("identity", ""), - "schedule_block": self.parameters.schedule_block or context_data.get("schedule_block", ""), + "identity": self.parameters.identity_block + or context_data.get("identity", ""), + "schedule_block": self.parameters.schedule_block + or context_data.get("schedule_block", ""), "chat_target_2": "", "reply_target_block": context_data.get("reply_target_block", ""), "raw_reply": self.parameters.target, "reason": "", - "mood_state": self.parameters.mood_prompt or context_data.get("mood_state", ""), + "mood_state": self.parameters.mood_prompt + or context_data.get("mood_state", ""), "reply_style": global_config.personality.reply_style, "keywords_reaction_prompt": self.parameters.keywords_reaction_prompt or context_data.get("keywords_reaction_prompt", ""), - "moderation_prompt": self.parameters.moderation_prompt_block or context_data.get("moderation_prompt", ""), + "moderation_prompt": self.parameters.moderation_prompt_block + or context_data.get("moderation_prompt", ""), "safety_guidelines_block": self.parameters.safety_guidelines_block or context_data.get("safety_guidelines_block", ""), "auth_role_prompt_block": self.parameters.auth_role_prompt_block @@ -902,7 +1018,9 @@ class Prompt: return result except (IndexError, KeyError) as e: # 捕获格式化错误并抛出更具信息量的异常 - raise ValueError(f"格式化模板失败: {self.template}, args={args}, kwargs={kwargs} {e!s}") from e + raise ValueError( + f"格式化模板失败: {self.template}, args={args}, kwargs={kwargs} {e!s}" + ) from e def __str__(self) -> str: """返回格式化后的结果，如果还未格式化，则返回原始模板.""" @@ -976,8 +1094,12 @@ class Prompt: return f"你完全不认识{sender}，不理解ta的相关信息。" # 使用关系提取器构建用户关系信息和聊天流印象 - user_relation_info = await relationship_fetcher.build_relation_info(person_id, points_num=5) - stream_impression = await relationship_fetcher.build_chat_stream_impression(chat_id) + user_relation_info = await relationship_fetcher.build_relation_info( + person_id, points_num=5 + ) + stream_impression = await relationship_fetcher.build_chat_stream_impression( + chat_id + ) # 组合两部分信息 info_parts = [] @@ -1016,7 +1138,9 @@ class Prompt: return {} @staticmethod - async def build_cross_context(chat_id: str, prompt_mode: str, target_user_info: dict[str, Any] | None) -> str: + async def build_cross_context( + chat_id: str, prompt_mode: str, target_user_info: dict[str, Any] | None + ) -> str: """构建跨群聊的上下文信息. Args: @@ -1039,7 +1163,9 @@ class Prompt: # 目前只为s4u模式构建跨群上下文 if prompt_mode == "s4u": - return await cross_context_api.build_cross_context_s4u(chat_stream, target_user_info) + return await cross_context_api.build_cross_context_s4u( + chat_stream, target_user_info + ) return "" @@ -1073,7 +1199,10 @@ class Prompt: # 工厂函数 def create_prompt( - template: str, name: str | None = None, parameters: PromptParameters | None = None, **kwargs + template: str, + name: str | None = None, + parameters: PromptParameters | None = None, + **kwargs, ) -> Prompt: """一个用于快速创建`Prompt`实例的工厂函数. @@ -1094,7 +1223,10 @@ def create_prompt( async def create_prompt_async( - template: str, name: str | None = None, parameters: PromptParameters | None = None, **kwargs + template: str, + name: str | None = None, + parameters: PromptParameters | None = None, + **kwargs, ) -> Prompt: """异步创建`Prompt`实例，并自动处理插件内容的动态注入.