From 57c9dacb9954add27975bb4acdaf37d17d6f541d Mon Sep 17 00:00:00 2001 From: SengokuCola <1026294844@qq.com> Date: Tue, 27 May 2025 10:50:47 +0800 Subject: [PATCH] =?UTF-8?q?fix=EF=BC=9A=E7=AE=80=E5=8C=96=E4=BA=86?= =?UTF-8?q?=E8=BA=AB=E4=BB=BD=E9=85=8D=E7=BD=AE?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- changelogs/changelog.md | 6 + src/chat/memory_system/debug_memory.py | 63 --- .../memory_system/manually_alter_memory.py | 365 ------------------ src/chat/memory_system/offline_llm.py | 126 ------ src/chat/message_receive/message_buffer.py | 2 +- src/config/official_configs.py | 15 - src/individuality/identity.py | 79 +--- src/individuality/individuality.py | 35 +- template/bot_config_template.toml | 27 +- 9 files changed, 24 insertions(+), 694 deletions(-) delete mode 100644 src/chat/memory_system/debug_memory.py delete mode 100644 src/chat/memory_system/manually_alter_memory.py delete mode 100644 src/chat/memory_system/offline_llm.py diff --git a/changelogs/changelog.md b/changelogs/changelog.md index 00bdf2afc..1702392c6 100644 --- a/changelogs/changelog.md +++ b/changelogs/changelog.md @@ -32,6 +32,12 @@ - 示例插件：禁言插件 - 示例插件：豆包绘图插件 +**人格** +- 简化了人格身份的配置 + +**语音** +- 麦麦可以决定自行发送语音消息（需要搭配tts适配器） + **新增表达方式学习** - 自主学习群聊中的表达方式，更贴近群友 - 可自定义的学习频率和开关 diff --git a/src/chat/memory_system/debug_memory.py b/src/chat/memory_system/debug_memory.py deleted file mode 100644 index b09e703a1..000000000 --- a/src/chat/memory_system/debug_memory.py +++ /dev/null @@ -1,63 +0,0 @@ -# -*- coding: utf-8 -*- -import asyncio -import time -import sys -import os - -# 添加项目根目录到系统路径 -sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))) -from src.chat.memory_system.Hippocampus import HippocampusManager -from rich.traceback import install - -install(extra_lines=3) - - -async def test_memory_system(): - """测试记忆系统的主要功能""" - try: - # 初始化记忆系统 - print("开始初始化记忆系统...") - hippocampus_manager = HippocampusManager.get_instance() - hippocampus_manager.initialize() - print("记忆系统初始化完成") - - # 测试记忆构建 - # print("开始测试记忆构建...") - # await hippocampus_manager.build_memory() - # print("记忆构建完成") - - # 测试记忆检索 - test_text = "千石可乐在群里聊天" - - # test_text = '''千石可乐：分不清AI的陪伴和人类的陪伴,是这样吗？''' - print(f"开始测试记忆检索，测试文本: {test_text}\n") - memories = await hippocampus_manager.get_memory_from_text( - text=test_text, max_memory_num=3, max_memory_length=2, max_depth=3, fast_retrieval=False - ) - - await asyncio.sleep(1) - - print("检索到的记忆:") - for topic, memory_items in memories: - print(f"主题: {topic}") - print(f"- {memory_items}") - - except Exception as e: - print(f"测试过程中出现错误: {e}") - raise - - -async def main(): - """主函数""" - try: - start_time = time.time() - await test_memory_system() - end_time = time.time() - print(f"测试完成，总耗时: {end_time - start_time:.2f} 秒") - except Exception as e: - print(f"程序执行出错: {e}") - raise - - -if __name__ == "__main__": - asyncio.run(main()) diff --git a/src/chat/memory_system/manually_alter_memory.py b/src/chat/memory_system/manually_alter_memory.py deleted file mode 100644 index 9bbf59f5b..000000000 --- a/src/chat/memory_system/manually_alter_memory.py +++ /dev/null @@ -1,365 +0,0 @@ -# -*- coding: utf-8 -*- -import os -import sys -import time -from pathlib import Path -import datetime -from rich.console import Console -from Hippocampus import Hippocampus # 海马体和记忆图 - - -from dotenv import load_dotenv -from rich.traceback import install - -install(extra_lines=3) - - -""" -我想 总有那么一个瞬间 -你会想和某天才变态少女助手一样 -往Bot的海马体里插上几个电极 不是吗 - -Let's do some dirty job. -""" - -# 获取当前文件的目录 -current_dir = Path(__file__).resolve().parent -# 获取项目根目录（上三层目录） -project_root = current_dir.parent.parent.parent -# env.dev文件路径 -env_path = project_root / ".env.dev" - -# from chat.config import global_config -root_path = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../..")) -sys.path.append(root_path) - -from src.common.logger import get_module_logger # noqa E402 -from common.database.database import db # noqa E402 - -logger = get_module_logger("mem_alter") -console = Console() - -# 加载环境变量 -if env_path.exists(): - logger.info(f"从 {env_path} 加载环境变量") - load_dotenv(env_path) -else: - logger.warning(f"未找到环境变量文件: {env_path}") - logger.info("将使用默认配置") - - -# 查询节点信息 -def query_mem_info(hippocampus: Hippocampus): - while True: - query = input("\n请输入新的查询概念（输入'退出'以结束）：") - if query.lower() == "退出": - break - - items_list = hippocampus.memory_graph.get_related_item(query) - if items_list: - have_memory = False - first_layer, second_layer = items_list - if first_layer: - have_memory = True - print("\n直接相关的记忆：") - for item in first_layer: - print(f"- {item}") - if second_layer: - have_memory = True - print("\n间接相关的记忆：") - for item in second_layer: - print(f"- {item}") - if not have_memory: - print("\n未找到相关记忆。") - else: - print("未找到相关记忆。") - - -# 增加概念节点 -def add_mem_node(hippocampus: Hippocampus): - while True: - concept = input("请输入节点概念名:\n") - result = db.graph_data.nodes.count_documents({"concept": concept}) - - if result != 0: - console.print("[yellow]已存在名为“{concept}”的节点，行为已取消[/yellow]") - continue - - memory_items = list() - while True: - context = input("请输入节点描述信息（输入'终止'以结束）") - if context.lower() == "终止": - break - memory_items.append(context) - - current_time = datetime.datetime.now().timestamp() - hippocampus.memory_graph.G.add_node( - concept, memory_items=memory_items, created_time=current_time, last_modified=current_time - ) - - -# 删除概念节点（及连接到它的边） -def remove_mem_node(hippocampus: Hippocampus): - concept = input("请输入节点概念名:\n") - result = db.graph_data.nodes.count_documents({"concept": concept}) - - if result == 0: - console.print(f"[red]不存在名为“{concept}”的节点[/red]") - - edges = db.graph_data.edges.find({"$or": [{"source": concept}, {"target": concept}]}) - - for edge in edges: - console.print(f"[yellow]存在边“{edge['source']} -> {edge['target']}”, 请慎重考虑[/yellow]") - - console.print(f"[yellow]确定要移除名为“{concept}”的节点以及其相关边吗[/yellow]") - destory = console.input(f"[red]请输入“{concept}”以删除节点 其他输入将被视为取消操作[/red]\n") - if destory == concept: - hippocampus.memory_graph.G.remove_node(concept) - else: - logger.info("[green]删除操作已取消[/green]") - - -# 增加节点间边 -def add_mem_edge(hippocampus: Hippocampus): - while True: - source = input("请输入 **第一个节点** 名称（输入'退出'以结束）：\n") - if source.lower() == "退出": - break - if db.graph_data.nodes.count_documents({"concept": source}) == 0: - console.print(f"[yellow]“{source}”节点不存在，操作已取消。[/yellow]") - continue - - target = input("请输入 **第二个节点** 名称：\n") - if db.graph_data.nodes.count_documents({"concept": target}) == 0: - console.print(f"[yellow]“{target}”节点不存在，操作已取消。[/yellow]") - continue - - if source == target: - console.print(f"[yellow]试图创建“{source} <-> {target}”自环，操作已取消。[/yellow]") - continue - - hippocampus.memory_graph.connect_dot(source, target) - edge = hippocampus.memory_graph.G.get_edge_data(source, target) - if edge["strength"] == 1: - console.print(f"[green]成功创建边“{source} <-> {target}”，默认权重1[/green]") - else: - console.print( - f"[yellow]边“{source} <-> {target}”已存在，" - f"更新权重: {edge['strength'] - 1} <-> {edge['strength']}[/yellow]" - ) - - -# 删除节点间边 -def remove_mem_edge(hippocampus: Hippocampus): - while True: - source = input("请输入 **第一个节点** 名称（输入'退出'以结束）：\n") - if source.lower() == "退出": - break - if db.graph_data.nodes.count_documents({"concept": source}) == 0: - console.print("[yellow]“{source}”节点不存在，操作已取消。[/yellow]") - continue - - target = input("请输入 **第二个节点** 名称：\n") - if db.graph_data.nodes.count_documents({"concept": target}) == 0: - console.print("[yellow]“{target}”节点不存在，操作已取消。[/yellow]") - continue - - if source == target: - console.print("[yellow]试图创建“{source} <-> {target}”自环，操作已取消。[/yellow]") - continue - - edge = hippocampus.memory_graph.G.get_edge_data(source, target) - if edge is None: - console.print("[yellow]边“{source} <-> {target}”不存在，操作已取消。[/yellow]") - continue - else: - accept = console.input("[orange]请输入“确认”以确认删除操作（其他输入视为取消）[/orange]\n") - if accept.lower() == "确认": - hippocampus.memory_graph.G.remove_edge(source, target) - console.print(f"[green]边“{source} <-> {target}”已删除。[green]") - - -# 修改节点信息 -def alter_mem_node(hippocampus: Hippocampus): - batch_environment = dict() - while True: - concept = input("请输入节点概念名（输入'终止'以结束）:\n") - if concept.lower() == "终止": - break - _, node = hippocampus.memory_graph.get_dot(concept) - if node is None: - console.print(f"[yellow]“{concept}”节点不存在，操作已取消。[/yellow]") - continue - - console.print("[yellow]注意，请确保你知道自己在做什么[/yellow]") - console.print("[yellow]你将获得一个执行任意代码的环境[/yellow]") - console.print("[red]你已经被警告过了。[/red]\n") - - node_environment = {"concept": "<节点名>", "memory_items": "<记忆文本数组>"} - console.print( - "[green]环境变量中会有env与batchEnv两个dict, env在切换节点时会清空, batchEnv在操作终止时才会清空[/green]" - ) - console.print( - f"[green] env 会被初始化为[/green]\n{node_environment}\n[green]且会在用户代码执行完毕后被提交 [/green]" - ) - console.print( - "[yellow]为便于书写临时脚本，请手动在输入代码通过Ctrl+C等方式触发KeyboardInterrupt来结束代码执行[/yellow]" - ) - - # 拷贝数据以防操作炸了 - node_environment = dict(node) - node_environment["concept"] = concept - - while True: - - def user_exec(script, env, batch_env): - return eval(script, env, batch_env) - - try: - command = console.input() - except KeyboardInterrupt: - # 稍微防一下小天才 - try: - if isinstance(node_environment["memory_items"], list): - node["memory_items"] = node_environment["memory_items"] - else: - raise Exception - - except Exception as e: - console.print( - f"[red]我不知道你做了什么，但显然nodeEnviroment['memory_items']已经不是个数组了，" - f"操作已取消: {str(e)}[/red]" - ) - break - - try: - user_exec(command, node_environment, batch_environment) - except Exception as e: - console.print(e) - console.print( - "[red]自定义代码执行时发生异常，已捕获，请重试（可通过 console.print(locals()) 检查环境状态）[/red]" - ) - - -# 修改边信息 -def alter_mem_edge(hippocampus: Hippocampus): - batch_enviroment = dict() - while True: - source = input("请输入 **第一个节点** 名称（输入'终止'以结束）：\n") - if source.lower() == "终止": - break - if hippocampus.memory_graph.get_dot(source) is None: - console.print(f"[yellow]“{source}”节点不存在，操作已取消。[/yellow]") - continue - - target = input("请输入 **第二个节点** 名称：\n") - if hippocampus.memory_graph.get_dot(target) is None: - console.print(f"[yellow]“{target}”节点不存在，操作已取消。[/yellow]") - continue - - edge = hippocampus.memory_graph.G.get_edge_data(source, target) - if edge is None: - console.print(f"[yellow]边“{source} <-> {target}”不存在，操作已取消。[/yellow]") - continue - - console.print("[yellow]注意，请确保你知道自己在做什么[/yellow]") - console.print("[yellow]你将获得一个执行任意代码的环境[/yellow]") - console.print("[red]你已经被警告过了。[/red]\n") - - edge_environment = {"source": "<节点名>", "target": "<节点名>", "strength": "<强度值,装在一个list里>"} - console.print( - "[green]环境变量中会有env与batchEnv两个dict, env在切换节点时会清空, batchEnv在操作终止时才会清空[/green]" - ) - console.print( - f"[green] env 会被初始化为[/green]\n{edge_environment}\n[green]且会在用户代码执行完毕后被提交 [/green]" - ) - console.print( - "[yellow]为便于书写临时脚本，请手动在输入代码通过Ctrl+C等方式触发KeyboardInterrupt来结束代码执行[/yellow]" - ) - - # 拷贝数据以防操作炸了 - edge_environment["strength"] = [edge["strength"]] - edge_environment["source"] = source - edge_environment["target"] = target - - while True: - - def user_exec(script, env, batch_env): - return eval(script, env, batch_env) - - try: - command = console.input() - except KeyboardInterrupt: - # 稍微防一下小天才 - try: - if isinstance(edge_environment["strength"][0], int): - edge["strength"] = edge_environment["strength"][0] - else: - raise Exception - - except Exception as e: - console.print( - f"[red]我不知道你做了什么，但显然edgeEnviroment['strength']已经不是个int了，" - f"操作已取消: {str(e)}[/red]" - ) - break - - try: - user_exec(command, edge_environment, batch_enviroment) - except Exception as e: - console.print(e) - console.print( - "[red]自定义代码执行时发生异常，已捕获，请重试（可通过 console.print(locals()) 检查环境状态）[/red]" - ) - - -async def main(): - start_time = time.time() - - # 创建海马体 - hippocampus = Hippocampus() - - # 从数据库同步数据 - hippocampus.entorhinal_cortex.sync_memory_from_db() - - end_time = time.time() - logger.info(f"\033[32m[加载海马体耗时: {end_time - start_time:.2f} 秒]\033[0m") - - while True: - try: - query = int( - input( - """请输入操作类型 -0 -> 查询节点; 1 -> 增加节点; 2 -> 移除节点; 3 -> 增加边; 4 -> 移除边; -5 -> 修改节点; 6 -> 修改边; 其他任意输入 -> 退出 -""" - ) - ) - except ValueError: - query = -1 - - if query == 0: - query_mem_info(hippocampus.memory_graph) - elif query == 1: - add_mem_node(hippocampus) - elif query == 2: - remove_mem_node(hippocampus) - elif query == 3: - add_mem_edge(hippocampus) - elif query == 4: - remove_mem_edge(hippocampus) - elif query == 5: - alter_mem_node(hippocampus) - elif query == 6: - alter_mem_edge(hippocampus) - else: - print("已结束操作") - break - - hippocampus.entorhinal_cortex.sync_memory_to_db() - - -if __name__ == "__main__": - import asyncio - - asyncio.run(main()) diff --git a/src/chat/memory_system/offline_llm.py b/src/chat/memory_system/offline_llm.py deleted file mode 100644 index d4862ad36..000000000 --- a/src/chat/memory_system/offline_llm.py +++ /dev/null @@ -1,126 +0,0 @@ -import asyncio -import os -import time -from typing import Tuple, Union - -import aiohttp -import requests -from src.common.logger import get_module_logger -from rich.traceback import install - -install(extra_lines=3) - -logger = get_module_logger("offline_llm") - - -class LLMRequestOff: - def __init__(self, model_name="deepseek-ai/DeepSeek-V3", **kwargs): - self.model_name = model_name - self.params = kwargs - self.api_key = os.getenv("SILICONFLOW_KEY") - self.base_url = os.getenv("SILICONFLOW_BASE_URL") - - if not self.api_key or not self.base_url: - raise ValueError("环境变量未正确加载：SILICONFLOW_KEY 或 SILICONFLOW_BASE_URL 未设置") - - logger.info(f"API URL: {self.base_url}") # 使用 logger 记录 base_url - - def generate_response(self, prompt: str) -> Union[str, Tuple[str, str]]: - """根据输入的提示生成模型的响应""" - headers = {"Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json"} - - # 构建请求体 - data = { - "model": self.model_name, - "messages": [{"role": "user", "content": prompt}], - "temperature": 0.5, - **self.params, - } - - # 发送请求到完整的 chat/completions 端点 - api_url = f"{self.base_url.rstrip('/')}/chat/completions" - logger.info(f"Request URL: {api_url}") # 记录请求的 URL - - max_retries = 3 - base_wait_time = 15 # 基础等待时间（秒） - - for retry in range(max_retries): - try: - response = requests.post(api_url, headers=headers, json=data) - - if response.status_code == 429: - wait_time = base_wait_time * (2**retry) # 指数退避 - logger.warning(f"遇到请求限制(429)，等待{wait_time}秒后重试...") - time.sleep(wait_time) - continue - - response.raise_for_status() # 检查其他响应状态 - - result = response.json() - if "choices" in result and len(result["choices"]) > 0: - content = result["choices"][0]["message"]["content"] - reasoning_content = result["choices"][0]["message"].get("reasoning_content", "") - return content, reasoning_content - return "没有返回结果", "" - - except Exception as e: - if retry < max_retries - 1: # 如果还有重试机会 - wait_time = base_wait_time * (2**retry) - logger.error(f"[回复]请求失败，等待{wait_time}秒后重试... 错误: {str(e)}") - time.sleep(wait_time) - else: - logger.error(f"请求失败: {str(e)}") - return f"请求失败: {str(e)}", "" - - logger.error("达到最大重试次数，请求仍然失败") - return "达到最大重试次数，请求仍然失败", "" - - async def generate_response_async(self, prompt: str) -> Union[str, Tuple[str, str]]: - """异步方式根据输入的提示生成模型的响应""" - headers = {"Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json"} - - # 构建请求体 - data = { - "model": self.model_name, - "messages": [{"role": "user", "content": prompt}], - "temperature": 0.5, - **self.params, - } - - # 发送请求到完整的 chat/completions 端点 - api_url = f"{self.base_url.rstrip('/')}/chat/completions" - logger.info(f"Request URL: {api_url}") # 记录请求的 URL - - max_retries = 3 - base_wait_time = 15 - - async with aiohttp.ClientSession() as session: - for retry in range(max_retries): - try: - async with session.post(api_url, headers=headers, json=data) as response: - if response.status == 429: - wait_time = base_wait_time * (2**retry) # 指数退避 - logger.warning(f"遇到请求限制(429)，等待{wait_time}秒后重试...") - await asyncio.sleep(wait_time) - continue - - response.raise_for_status() # 检查其他响应状态 - - result = await response.json() - if "choices" in result and len(result["choices"]) > 0: - content = result["choices"][0]["message"]["content"] - reasoning_content = result["choices"][0]["message"].get("reasoning_content", "") - return content, reasoning_content - return "没有返回结果", "" - - except Exception as e: - if retry < max_retries - 1: # 如果还有重试机会 - wait_time = base_wait_time * (2**retry) - logger.error(f"[回复]请求失败，等待{wait_time}秒后重试... 错误: {str(e)}") - await asyncio.sleep(wait_time) - else: - logger.error(f"请求失败: {str(e)}") - return f"请求失败: {str(e)}", "" - - logger.error("达到最大重试次数，请求仍然失败") - return "达到最大重试次数，请求仍然失败", "" diff --git a/src/chat/message_receive/message_buffer.py b/src/chat/message_receive/message_buffer.py index 2df256ce5..f513b22a5 100644 --- a/src/chat/message_receive/message_buffer.py +++ b/src/chat/message_receive/message_buffer.py @@ -1,4 +1,4 @@ -from ..person_info.person_info import person_info_manager +from src.person_info.person_info import person_info_manager from src.common.logger_manager import get_logger import asyncio from dataclasses import dataclass, field diff --git a/src/config/official_configs.py b/src/config/official_configs.py index a5b7805ad..519e4430c 100644 --- a/src/config/official_configs.py +++ b/src/config/official_configs.py @@ -41,21 +41,6 @@ class PersonalityConfig(ConfigBase): class IdentityConfig(ConfigBase): """个体特征配置类""" - height: int = 170 - """身高（单位：厘米）""" - - weight: float = 50 - """体重（单位：千克）""" - - age: int = 18 - """年龄（单位：岁）""" - - gender: str = "女" - """性别（男/女）""" - - appearance: str = "可爱" - """外貌描述""" - identity_detail: list[str] = field(default_factory=lambda: []) """身份特征""" diff --git a/src/individuality/identity.py b/src/individuality/identity.py index f79da547a..bb3125985 100644 --- a/src/individuality/identity.py +++ b/src/individuality/identity.py @@ -7,99 +7,24 @@ class Identity: """身份特征类""" identity_detail: List[str] # 身份细节描述 - height: int # 身高（厘米） - weight: float # 体重（千克） - age: int # 年龄 - gender: str # 性别 - appearance: str # 外貌特征 - _instance = None - - def __new__(cls, *args, **kwargs): - if cls._instance is None: - cls._instance = super().__new__(cls) - return cls._instance - - def __init__( - self, - identity_detail: List[str] = None, - height: int = 0, - weight: float = 0, - age: int = 0, - gender: str = "", - appearance: str = "", - ): + def __init__(self, identity_detail: List[str] = None): """初始化身份特征 Args: identity_detail: 身份细节描述列表 - height: 身高（厘米） - weight: 体重（千克） - age: 年龄 - gender: 性别 - appearance: 外貌特征 """ if identity_detail is None: identity_detail = [] self.identity_detail = identity_detail - self.height = height - self.weight = weight - self.age = age - self.gender = gender - self.appearance = appearance - - @classmethod - def get_instance(cls) -> "Identity": - """获取Identity单例实例 - - Returns: - Identity: 单例实例 - """ - if cls._instance is None: - cls._instance = cls() - return cls._instance - - @classmethod - def initialize( - cls, identity_detail: List[str], height: int, weight: float, age: int, gender: str, appearance: str - ) -> "Identity": - """初始化身份特征 - - Args: - identity_detail: 身份细节描述列表 - height: 身高（厘米） - weight: 体重（千克） - age: 年龄 - gender: 性别 - appearance: 外貌特征 - - Returns: - Identity: 初始化后的身份特征实例 - """ - instance = cls.get_instance() - instance.identity_detail = identity_detail - instance.height = height - instance.weight = weight - instance.age = age - instance.gender = gender - instance.appearance = appearance - return instance def to_dict(self) -> dict: """将身份特征转换为字典格式""" return { "identity_detail": self.identity_detail, - "height": self.height, - "weight": self.weight, - "age": self.age, - "gender": self.gender, - "appearance": self.appearance, } @classmethod def from_dict(cls, data: dict) -> "Identity": """从字典创建身份特征实例""" - instance = cls.get_instance() - for key, value in data.items(): - setattr(instance, key, value) - return instance + return cls(identity_detail=data.get("identity_detail", [])) diff --git a/src/individuality/individuality.py b/src/individuality/individuality.py index ba462c5e3..d6682fd0d 100644 --- a/src/individuality/individuality.py +++ b/src/individuality/individuality.py @@ -1,6 +1,4 @@ from typing import Optional - -from numpy import double from .personality import Personality from .identity import Identity from .expression_style import PersonalityExpression @@ -27,11 +25,6 @@ class Individuality: personality_core: str, personality_sides: list, identity_detail: list, - height: int, - weight: double, - age: int, - gender: str, - appearance: str, ) -> None: """初始化个体特征 @@ -40,11 +33,6 @@ class Individuality: personality_core: 人格核心特点 personality_sides: 人格侧面描述 identity_detail: 身份细节描述 - height: 身高（厘米） - weight: 体重（千克） - age: 年龄 - gender: 性别 - appearance: 外貌特征 """ # 初始化人格 self.personality = Personality.initialize( @@ -52,9 +40,7 @@ class Individuality: ) # 初始化身份 - self.identity = Identity.initialize( - identity_detail=identity_detail, height=height, weight=weight, age=age, gender=gender, appearance=appearance - ) + self.identity = Identity(identity_detail=identity_detail) await self.express_style.extract_and_store_personality_expressions() @@ -120,7 +106,7 @@ class Individuality: 获取身份特征的prompt Args: - level (int): 详细程度 (1: 随机细节, 2: 所有细节+外貌年龄性别, 3: 同2) + level (int): 详细程度 (1: 随机细节, 2: 所有细节, 3: 同2) x_person (int, optional): 人称代词 (0: 无人称, 1: 我, 2: 你). 默认为 2. Returns: @@ -145,23 +131,10 @@ class Individuality: identity_detail = list(self.identity.identity_detail) random.shuffle(identity_detail) if level == 1: - identity_parts.append(f"身份是{identity_detail[0]}") + identity_parts.append(f"{identity_detail[0]}") elif level >= 2: details_str = "、".join(identity_detail) - identity_parts.append(f"身份是{details_str}") - - # 根据level添加其他身份信息 - if level >= 3: - if self.identity.appearance: - identity_parts.append(f"{self.identity.appearance}") - if self.identity.age > 0: - identity_parts.append(f"年龄大约{self.identity.age}岁") - if self.identity.gender: - identity_parts.append(f"性别是{self.identity.gender}") - if self.identity.height: - identity_parts.append(f"身高大约{self.identity.height}厘米") - if self.identity.weight: - identity_parts.append(f"体重大约{self.identity.weight}千克") + identity_parts.append(f"{details_str}") if identity_parts: details_str = "，".join(identity_parts) diff --git a/template/bot_config_template.toml b/template/bot_config_template.toml index ef6bbfa5c..a9f53a74b 100644 --- a/template/bot_config_template.toml +++ b/template/bot_config_template.toml @@ -1,5 +1,5 @@ [inner] -version = "2.4.0" +version = "2.5.0" #----以下是给开发人员阅读的，如果你只是部署了麦麦，不需要阅读---- #如果你想要修改配置文件，请在修改后将version的值进行变更 @@ -25,21 +25,18 @@ personality_sides = [ "用一句话或几句话描述人格的一些细节", "用一句话或几句话描述人格的一些细节", "用一句话或几句话描述人格的一些细节", -]# 条数任意，不能为0, 该选项还在调试中，可能未完全生效 - -# 身份特点 部分选项仅在 专注聊天 有效 -[identity] #アイデンティティがない 生まれないらららら -identity_detail = [ - "身份特点", - "身份特点", ]# 条数任意，不能为0 -#外貌特征 -age = 18 # 年龄 单位岁 -gender = "女" # 性别 -height = "170" # 身高（单位cm） -weight = "50" # 体重（单位kg） -appearance = "用一句或几句话描述外貌特征" # 外貌特征 +# 身份特点 +[identity] #アイデンティティがない 生まれないらららら +identity_detail = [ + "年龄为19岁", + "是女孩子", + "身高为160cm", + "有橙色的短发", +] +# 可以描述外贸，性别，身高，职业，属性等等描述 +# 条数任意，不能为0 [chat] #麦麦的聊天通用设置 chat_mode = "normal" # 聊天模式 —— 普通模式：normal，专注模式：focus，在普通模式和专注模式之间自动切换 @@ -96,8 +93,6 @@ self_identify_processor = true # 是否启用自我识别处理器 tool_use_processor = true # 是否启用工具使用处理器 working_memory_processor = true # 是否启用工作记忆处理器 - - [expression] # 表达方式 expression_style = "描述麦麦说话的表达风格，表达习惯"