gardel/Mofox-Core
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

🤖 自动格式化代码 [skip ci]

Browse Source
This commit is contained in:
github-actions[bot]
2025-06-20 11:20:41 +00:00
parent 7dafbff036
commit 865645e02d
5 changed files with 132 additions and 137 deletions
Download Patch File Download Diff File Expand all files Collapse all files

77
src/chat/focus_chat/info_processors/relationship_processor.py
View File

@@ -536,14 +536,16 @@ class RelationshipProcessor(BaseProcessor):
# 对于每个(person_id, info_type)组合，只保留最新的记录
latest_records = {}
for info_fetching in self.info_fetching_cache:
key = (info_fetching['person_id'], info_fetching['info_type'])
if key not in latest_records or info_fetching['start_time'] > latest_records[key]['start_time']:
key = (info_fetching["person_id"], info_fetching["info_type"])
if key not in latest_records or info_fetching["start_time"] > latest_records[key]["start_time"]:
latest_records[key] = info_fetching
# 按时间排序并生成显示文本
sorted_records = sorted(latest_records.values(), key=lambda x: x['start_time'])
sorted_records = sorted(latest_records.values(), key=lambda x: x["start_time"])
for info_fetching in sorted_records:
info_cache_block += f"你已经调取了[{info_fetching['person_name']}]的[{info_fetching['info_type']}]信息\n"
info_cache_block += (
f"你已经调取了[{info_fetching['person_name']}]的[{info_fetching['info_type']}]信息\n"
)
prompt = (await global_prompt_manager.get_prompt_async("relationship_prompt")).format(
name_block=name_block,
@@ -569,13 +571,13 @@ class RelationshipProcessor(BaseProcessor):
if not person_id:
logger.warning(f"{self.log_prefix} 未找到用户 {person_name} 的ID，跳过调取信息。")
continue
# 检查是否是bot自己，如果是则跳过
user_id = person_info_manager.get_value_sync(person_id, "user_id")
if user_id == global_config.bot.qq_account:
logger.info(f"{self.log_prefix} 跳过调取bot自己({person_name})的信息。")
continue
self.info_fetching_cache.append(
{
"person_id": person_id,
@@ -625,7 +627,6 @@ class RelationshipProcessor(BaseProcessor):
if person_infos_str:
persons_infos_str += f"你对 {person_name} 的了解：{person_infos_str}\n"
return persons_infos_str
# ================================
@@ -733,32 +734,31 @@ class RelationshipProcessor(BaseProcessor):
使用小模型提取单个信息类型
"""
person_info_manager = get_person_info_manager()
# 首先检查 info_list 缓存
info_list = await person_info_manager.get_value(person_id, "info_list") or []
cached_info = None
print(f"info_list: {info_list}")
# 查找对应的 info_type
for info_item in info_list:
if info_item.get("info_type") == info_type:
cached_info = info_item.get("info_content")
logger.info(f"{self.log_prefix} [缓存命中] 从 info_list 中找到 {info_type} 信息: {cached_info}")
break
# 如果缓存中有信息，直接使用
if cached_info :
if cached_info:
person_name = await person_info_manager.get_value(person_id, "person_name")
if person_id not in self.info_fetched_cache:
self.info_fetched_cache[person_id] = {}
if cached_info == "none":
unknow = True
else:
unknow = False
self.info_fetched_cache[person_id][info_type] = {
"info": cached_info,
"ttl": 8,
@@ -768,26 +768,28 @@ class RelationshipProcessor(BaseProcessor):
}
logger.info(f"{self.log_prefix} [缓存使用] 直接使用缓存的 {person_name} 的 {info_type}: {cached_info}")
return
logger.info(f"{self.log_prefix} [缓存命中] 缓存中没有信息")
try:
nickname_str = ",".join(global_config.bot.alias_names)
name_block = f"你的名字是{global_config.bot.nickname},你的昵称有{nickname_str}，有人也会用这些昵称称呼你。"
person_name = await person_info_manager.get_value(person_id, "person_name")
person_impression = await person_info_manager.get_value(person_id, "impression")
if person_impression:
person_impression_block = f"<对{person_name}的总体了解>\n{person_impression}\n</对{person_name}的总体了解>"
person_impression_block = (
f"<对{person_name}的总体了解>\n{person_impression}\n</对{person_name}的总体了解>"
)
else:
person_impression_block = ""
points = await person_info_manager.get_value(person_id, "points")
if points:
points_text = "\n".join([f"{point[2]}:{point[0]}" for point in points])
points_text_block = f"<对{person_name}的近期了解>\n{points_text}\n</对{person_name}的近期了解>"
else:
points_text_block = ""
if not points_text_block and not person_impression_block:
if person_id not in self.info_fetched_cache:
self.info_fetched_cache[person_id] = {}
@@ -799,7 +801,7 @@ class RelationshipProcessor(BaseProcessor):
"unknow": True,
}
return
prompt = (await global_prompt_manager.get_prompt_async("fetch_person_info_prompt")).format(
name_block=name_block,
info_type=info_type,
@@ -810,7 +812,7 @@ class RelationshipProcessor(BaseProcessor):
)
except Exception:
logger.error(traceback.format_exc())
print(prompt)
try:
@@ -824,7 +826,7 @@ class RelationshipProcessor(BaseProcessor):
if info_type in content_json:
info_content = content_json[info_type]
is_unknown = info_content == "none" or not info_content
# 保存到运行时缓存
if person_id not in self.info_fetched_cache:
self.info_fetched_cache[person_id] = {}
@@ -835,16 +837,20 @@ class RelationshipProcessor(BaseProcessor):
"person_name": person_name,
"unknow": is_unknown,
}
# 保存到持久化缓存 (info_list)
await self._save_info_to_cache(person_id, info_type, info_content if not is_unknown else "none")
if not is_unknown:
logger.info(f"{self.log_prefix} [LLM提取] 成功获取并缓存 {person_name} 的 {info_type}: {info_content}")
logger.info(
f"{self.log_prefix} [LLM提取] 成功获取并缓存 {person_name} 的 {info_type}: {info_content}"
)
else:
logger.info(f"{self.log_prefix} [LLM提取] {person_name} 的 {info_type} 信息不明确")
else:
logger.warning(f"{self.log_prefix} [LLM提取] 小模型返回空结果，获取 {person_name} 的 {info_type} 信息失败。")
logger.warning(
f"{self.log_prefix} [LLM提取] 小模型返回空结果，获取 {person_name} 的 {info_type} 信息失败。"
)
except Exception as e:
logger.error(f"{self.log_prefix} [LLM提取] 执行小模型请求获取用户信息时出错: {e}")
logger.error(traceback.format_exc())
@@ -852,7 +858,7 @@ class RelationshipProcessor(BaseProcessor):
async def _save_info_to_cache(self, person_id: str, info_type: str, info_content: str):
"""
将提取到的信息保存到 person_info 的 info_list 字段中
Args:
person_id: 用户ID
info_type: 信息类型
@@ -860,23 +866,23 @@ class RelationshipProcessor(BaseProcessor):
"""
try:
person_info_manager = get_person_info_manager()
# 获取现有的 info_list
info_list = await person_info_manager.get_value(person_id, "info_list") or []
# 查找是否已存在相同 info_type 的记录
found_index = -1
for i, info_item in enumerate(info_list):
if isinstance(info_item, dict) and info_item.get("info_type") == info_type:
found_index = i
break
# 创建新的信息记录
new_info_item = {
"info_type": info_type,
"info_content": info_content,
}
if found_index >= 0:
# 更新现有记录
info_list[found_index] = new_info_item
@@ -885,14 +891,13 @@ class RelationshipProcessor(BaseProcessor):
# 添加新记录
info_list.append(new_info_item)
logger.info(f"{self.log_prefix} [缓存保存] 新增 {person_id} 的 {info_type} 信息缓存")
# 保存更新后的 info_list
await person_info_manager.update_one_field(person_id, "info_list", info_list)
except Exception as e:
logger.error(f"{self.log_prefix} [缓存保存] 保存信息到缓存失败: {e}")
logger.error(traceback.format_exc())
init_prompt()

30
src/chat/focus_chat/info_processors/self_processor.py
View File

@@ -18,7 +18,6 @@ logger = get_logger("processor")
def init_prompt():
indentify_prompt = """
{time_now}，以下是正在进行的聊天内容：
<聊天记录>
@@ -46,7 +45,7 @@ class SelfProcessor(BaseProcessor):
super().__init__()
self.subheartflow_id = subheartflow_id
self.info_fetched_cache: Dict[str, Dict[str, any]] = {}
self.llm_model = LLMRequest(
@@ -57,8 +56,6 @@ class SelfProcessor(BaseProcessor):
name = get_chat_manager().get_stream_name(self.subheartflow_id)
self.log_prefix = f"[{name}] "
async def process_info(self, observations: List[Observation] = None, *infos) -> List[InfoBase]:
"""处理信息对象
@@ -123,22 +120,22 @@ class SelfProcessor(BaseProcessor):
individuality = get_individuality()
available_keywords = individuality.get_all_keywords()
available_keywords_str = "、".join(available_keywords) if available_keywords else "暂无关键词"
prompt = (await global_prompt_manager.get_prompt_async("indentify_prompt")).format(
name_block=name_block,
time_now=time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()),
chat_observe_info=chat_observe_info[-200:],
available_keywords=available_keywords_str,
bot_name = global_config.bot.nickname
bot_name=global_config.bot.nickname,
)
keyword = ""
try:
keyword, _ = await self.llm_model.generate_response_async(prompt=prompt)
print(f"prompt: {prompt}\nkeyword: {keyword}")
if not keyword:
logger.warning(f"{self.log_prefix} LLM返回空结果，自我识别失败。")
except Exception as e:
@@ -146,7 +143,6 @@ class SelfProcessor(BaseProcessor):
logger.error(f"{self.log_prefix} 执行LLM请求或处理响应时出错: {e}")
logger.error(traceback.format_exc())
keyword = "我是谁，我从哪来，要到哪去"
# 解析关键词
keyword = keyword.strip()
@@ -155,20 +151,20 @@ class SelfProcessor(BaseProcessor):
else:
# 只保留非空关键词，去除多余空格
keyword_set = [k.strip() for k in keyword.split(",") if k.strip()]
# 从individuality缓存中查询关键词信息
for keyword in keyword_set:
if keyword not in self.info_fetched_cache:
# 直接从individuality的json缓存中获取关键词信息
fetched_info = individuality.get_keyword_info(keyword)
if fetched_info:
self.info_fetched_cache[keyword] = {
"info": fetched_info,
"ttl": 5,
}
logger.info(f"{self.log_prefix} 从个体特征缓存中获取关键词 '{keyword}' 的信息")
# 管理TTL（生存时间）
expired_keywords = []
for fetched_keyword, info in self.info_fetched_cache.items():
@@ -176,18 +172,16 @@ class SelfProcessor(BaseProcessor):
info["ttl"] -= 1
else:
expired_keywords.append(fetched_keyword)
# 删除过期的关键词
for expired_keyword in expired_keywords:
del self.info_fetched_cache[expired_keyword]
fetched_info_str = ""
for keyword, info in self.info_fetched_cache.items():
fetched_info_str += f"你的：{keyword}信息是: {info['info']}\n"
return fetched_info_str
init_prompt()

5
src/chat/focus_chat/planners/planner_simple.py
View File

@@ -342,11 +342,8 @@ class ActionPlanner(BasePlanner):
else:
chat_content_block = "你还未开始聊天"
action_options_block = ""
for using_actions_name, using_actions_info in current_available_actions.items():
using_action_prompt = await global_prompt_manager.get_prompt_async("action_prompt")
if using_actions_info["parameters"]:
@@ -383,7 +380,7 @@ class ActionPlanner(BasePlanner):
# 获取当前时间
time_block = f"当前时间：{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}"
bot_name = global_config.bot.nickname
if global_config.bot.alias_names:
bot_nickname = f",也有人叫你{','.join(global_config.bot.alias_names)}"

147
src/individuality/individuality.py
View File

@@ -7,7 +7,6 @@ import json
import os
import hashlib
import traceback
import time
from rich.traceback import install
from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
from src.manager.async_task_manager import AsyncTask
@@ -19,11 +18,10 @@ install(extra_lines=3)
logger = get_logger("individuality")
def init_prompt():
"""初始化用于关键词提取的prompts"""
extract_keywords_prompt = """
请分析以下对某人的描述，提取出其中的独立关键词。每个关键词应该是可以用来从某一角度概括的方面：性格，身高，喜好，外貌，身份，兴趣，爱好，习惯，等等。
@@ -38,7 +36,7 @@ def init_prompt():
请输出关键词：
"""
Prompt(extract_keywords_prompt, "extract_keywords_prompt")
fetch_info_prompt = """
{name_block}，你的性格的特征是：
{prompt_personality}
@@ -49,7 +47,6 @@ def init_prompt():
Prompt(fetch_info_prompt, "fetch_info_prompt")
class Individuality:
"""个体特征管理类"""
@@ -60,7 +57,7 @@ class Individuality:
self.express_style: PersonalityExpression = PersonalityExpression()
self.name = ""
# 关键词缓存相关
self.keyword_info_cache: dict = {} # {keyword: [info_list]}
self.fetch_info_file_path = "data/personality/fetch_info.json"
@@ -92,7 +89,7 @@ class Individuality:
await self.express_style.extract_and_store_personality_expressions()
self.name = bot_nickname
# 预处理关键词和生成信息缓存
await self._preprocess_personality_keywords(personality_sides, identity_detail)
@@ -265,18 +262,17 @@ class Individuality:
def _get_config_hash(self, personality_sides: list, identity_detail: list) -> str:
"""获取当前personality和identity配置的哈希值"""
# 将配置转换为字符串并排序，确保一致性
config_str = json.dumps({
"personality_sides": sorted(personality_sides),
"identity_detail": sorted(identity_detail)
}, sort_keys=True)
return hashlib.md5(config_str.encode('utf-8')).hexdigest()
config_str = json.dumps(
{"personality_sides": sorted(personality_sides), "identity_detail": sorted(identity_detail)}, sort_keys=True
)
return hashlib.md5(config_str.encode("utf-8")).hexdigest()
def _load_meta_info(self) -> dict:
"""从JSON文件中加载元信息"""
if os.path.exists(self.meta_info_file_path):
try:
with open(self.meta_info_file_path, 'r', encoding='utf-8') as f:
with open(self.meta_info_file_path, "r", encoding="utf-8") as f:
return json.load(f)
except Exception as e:
print(f"读取meta_info文件失败: {e}")
@@ -288,7 +284,7 @@ class Individuality:
try:
# 确保目录存在
os.makedirs(os.path.dirname(self.meta_info_file_path), exist_ok=True)
with open(self.meta_info_file_path, 'w', encoding='utf-8') as f:
with open(self.meta_info_file_path, "w", encoding="utf-8") as f:
json.dump(meta_info, f, ensure_ascii=False, indent=2)
except Exception as e:
print(f"保存meta_info文件失败: {e}")
@@ -297,30 +293,30 @@ class Individuality:
"""检查配置是否发生变化，如果变化则清空fetch_info.json"""
current_config_hash = self._get_config_hash(personality_sides, identity_detail)
meta_info = self._load_meta_info()
stored_config_hash = meta_info.get("config_hash", "")
if current_config_hash != stored_config_hash:
logger.info(f"检测到personality或identity配置发生变化，清空fetch_info数据")
logger.info("检测到personality或identity配置发生变化，清空fetch_info数据")
# 清空fetch_info文件
if os.path.exists(self.fetch_info_file_path):
try:
os.remove(self.fetch_info_file_path)
logger.info(f"已清空fetch_info文件")
logger.info("已清空fetch_info文件")
except Exception as e:
logger.error(f"清空fetch_info文件失败: {e}")
# 更新元信息
meta_info["config_hash"] = current_config_hash
self._save_meta_info(meta_info)
logger.info(f"已更新配置哈希值")
logger.info("已更新配置哈希值")
def _load_fetch_info_from_file(self) -> dict:
"""从JSON文件中加载已保存的fetch_info数据"""
if os.path.exists(self.fetch_info_file_path):
try:
with open(self.fetch_info_file_path, 'r', encoding='utf-8') as f:
with open(self.fetch_info_file_path, "r", encoding="utf-8") as f:
data = json.load(f)
# 兼容旧格式：如果是字符串则转换为列表
for keyword, value in data.items():
@@ -337,7 +333,7 @@ class Individuality:
try:
# 确保目录存在
os.makedirs(os.path.dirname(self.fetch_info_file_path), exist_ok=True)
with open(self.fetch_info_file_path, 'w', encoding='utf-8') as f:
with open(self.fetch_info_file_path, "w", encoding="utf-8") as f:
json.dump(fetch_info_data, f, ensure_ascii=False, indent=2)
except Exception as e:
logger.error(f"保存fetch_info文件失败: {e}")
@@ -345,22 +341,21 @@ class Individuality:
async def _preprocess_personality_keywords(self, personality_sides: list, identity_detail: list):
"""预处理personality关键词，提取关键词并生成缓存"""
try:
logger.info("开始预处理personality关键词...")
# 检查配置变化
self._check_config_change_and_clear(personality_sides, identity_detail)
# 加载已有的预处理数据（如果存在）
fetch_info_data = self._load_fetch_info_from_file()
logger.info(f"加载已有数据，现有关键词数量: {len(fetch_info_data)}")
# 检查并清理错误分割的关键词（包含逗号的键）
keys_to_fix = []
for key in fetch_info_data.keys():
if "," in key:
keys_to_fix.append(key)
if keys_to_fix:
logger.info(f"发现 {len(keys_to_fix)} 个需要重新分割的关键词")
for bad_key in keys_to_fix:
@@ -369,7 +364,7 @@ class Individuality:
info_list = fetch_info_data[bad_key]
# 删除旧的错误键
del fetch_info_data[bad_key]
# 按逗号分割并重新添加
split_keywords = [k.strip() for k in bad_key.split(",") if k.strip()]
for split_keyword in split_keywords:
@@ -380,64 +375,64 @@ class Individuality:
if info not in fetch_info_data[split_keyword]:
fetch_info_data[split_keyword].append(info)
logger.info(f"已将信息分配给关键词: '{split_keyword}'")
# 保存清理后的数据
self._save_fetch_info_to_file(fetch_info_data)
logger.info(f"清理完成，现在共有 {len(fetch_info_data)} 个关键词")
# 构建完整描述（personality + identity）
personality_sides_str = ""
for personality_side in personality_sides:
personality_sides_str += f"{personality_side}，"
# 添加identity内容
for detail in identity_detail:
personality_sides_str += f"{detail}，"
if not personality_sides_str:
logger.info("没有personality和identity配置，跳过预处理")
return
# 提取关键词
extract_prompt = (await global_prompt_manager.get_prompt_async("extract_keywords_prompt")).format(
personality_sides=personality_sides_str
)
llm_model = LLMRequest(
model=global_config.model.utils_small,
request_type="individuality.keyword_extract",
)
keywords_result, _ = await llm_model.generate_response_async(prompt=extract_prompt)
logger.info(f"LLM返回的原始关键词结果: '{keywords_result}'")
if not keywords_result or keywords_result.strip() == "none":
logger.info("未提取到有效关键词")
return
# 解析关键词
keyword_set = [k.strip() for k in keywords_result.split(",") if k.strip()]
logger.info(f"分割后的关键词列表: {keyword_set}")
logger.info(f"共提取到 {len(keyword_set)} 个关键词")
# 构建名称块和身份信息
nickname_str = ""
for nickname in global_config.bot.alias_names:
nickname_str += f"{nickname},"
name_block = f"你的名字是{self.name},你的昵称有{nickname_str}，有人也会用这些昵称称呼你。"
identity_detail_str = "你"
for detail in identity_detail:
identity_detail_str += f"{detail},"
# 为每个关键词生成fetched_info，添加到现有数据中
updated_count = 0
new_count = 0
for keyword in keyword_set:
try:
logger.info(f"正在处理关键词: '{keyword}' (长度: {len(keyword)})")
# 检查是否已存在该关键词
if keyword in fetch_info_data:
logger.info(f"关键词 '{keyword}' 已存在，将添加新信息...")
@@ -446,17 +441,17 @@ class Individuality:
logger.info(f"正在为新关键词 '{keyword}' 生成信息...")
action_type = "新增"
fetch_info_data[keyword] = [] # 初始化为空列表
fetch_prompt = (await global_prompt_manager.get_prompt_async("fetch_info_prompt")).format(
name_block=name_block,
prompt_personality=personality_sides_str,
indentify_block=identity_detail_str,
keyword=keyword,
bot_name=self.name
bot_name=self.name,
)
fetched_info, _ = await llm_model.generate_response_async(prompt=fetch_prompt)
if fetched_info and fetched_info.strip() != "none":
# 添加到列表中，避免重复
if fetched_info not in fetch_info_data[keyword]:
@@ -470,26 +465,29 @@ class Individuality:
logger.info(f"关键词 '{keyword}' 的信息已存在，跳过重复添加")
else:
logger.info(f"关键词 '{keyword}' 没有相关信息")
except Exception as e:
logger.error(f"为关键词 '{keyword}' 生成信息时出错: {e}")
continue
# 保存合并后的数据到文件和内存缓存
if updated_count > 0 or new_count > 0:
self._save_fetch_info_to_file(fetch_info_data)
logger.info(f"预处理完成，新增 {new_count} 个关键词，追加 {updated_count} 个关键词信息，总计 {len(fetch_info_data)} 个关键词")
logger.info(
f"预处理完成，新增 {new_count} 个关键词，追加 {updated_count} 个关键词信息，总计 {len(fetch_info_data)} 个关键词"
)
else:
logger.info("预处理完成，但没有生成任何新的有效信息")
# 将数据加载到内存缓存
self.keyword_info_cache = fetch_info_data
logger.info(f"关键词缓存已加载，共 {len(self.keyword_info_cache)} 个关键词")
# 注册定时任务（延迟执行，避免阻塞初始化）
import asyncio
asyncio.create_task(self._register_keyword_update_task_delayed())
except Exception as e:
logger.error(f"预处理personality关键词时出错: {e}")
traceback.print_exc()
@@ -499,32 +497,34 @@ class Individuality:
try:
# 等待一小段时间确保系统完全初始化
import asyncio
await asyncio.sleep(5)
from src.manager.async_task_manager import async_task_manager
logger = get_logger("individuality")
# 创建定时任务
task = KeywordUpdateTask(
personality_sides=list(global_config.personality.personality_sides),
identity_detail=list(global_config.identity.identity_detail),
individuality_instance=self
individuality_instance=self,
)
# 注册任务
await async_task_manager.add_task(task)
logger.info("关键词更新定时任务已注册")
except Exception as e:
logger.error(f"注册关键词更新定时任务失败: {e}")
traceback.print_exc()
def get_keyword_info(self, keyword: str) -> str:
"""获取指定关键词的信息
Args:
keyword: 关键词
Returns:
str: 随机选择的一条信息，如果没有则返回空字符串
"""
@@ -549,37 +549,38 @@ def get_individuality():
class KeywordUpdateTask(AsyncTask):
"""关键词更新定时任务"""
def __init__(self, personality_sides: list, identity_detail: list, individuality_instance):
# 调用父类构造函数
super().__init__(
task_name="keyword_update_task",
wait_before_start=3600, # 1小时后开始
run_interval=3600 # 每小时运行一次
run_interval=3600, # 每小时运行一次
)
self.personality_sides = personality_sides
self.identity_detail = identity_detail
self.identity_detail = identity_detail
self.individuality_instance = individuality_instance
# 任务控制参数
self.max_runs = 20
self.current_runs = 0
self.original_config_hash = individuality_instance._get_config_hash(personality_sides, identity_detail)
async def run(self):
"""执行任务"""
try:
from src.common.logger import get_logger
logger = get_logger("individuality.task")
# 检查是否超过最大运行次数
if self.current_runs >= self.max_runs:
logger.info(f"关键词更新任务已达到最大运行次数({self.max_runs})，停止执行")
# 设置为0间隔来停止循环任务
self.run_interval = 0
return
# 检查配置是否发生变化
current_config_hash = self.individuality_instance._get_config_hash(
self.personality_sides, self.identity_detail
@@ -589,17 +590,17 @@ class KeywordUpdateTask(AsyncTask):
# 设置为0间隔来停止循环任务
self.run_interval = 0
return
self.current_runs += 1
logger.info(f"开始执行关键词更新任务 (第{self.current_runs}/{self.max_runs}次)")
# 执行关键词预处理
await self.individuality_instance._preprocess_personality_keywords(
self.personality_sides, self.identity_detail
)
logger.info(f"关键词更新任务完成 (第{self.current_runs}/{self.max_runs}次)")
except Exception as e:
logger.error(f"关键词更新任务执行失败: {e}")
traceback.print_exc()

10
src/person_info/relationship_manager.py
View File

@@ -283,13 +283,12 @@ class RelationshipManager:
points_data = [points_data]
# 添加可读时间到每个point
points_list = [(item["point"], float(item["weight"]), current_time) for item in points_data]
logger_str=f"了解了有关{person_name}的新印象：\n"
logger_str = f"了解了有关{person_name}的新印象：\n"
for point in points_list:
logger_str+=f"{point[0]},重要性：{point[1]}\n\n"
logger_str += f"{point[0]},重要性：{point[1]}\n\n"
logger.info("logger_str")
except json.JSONDecodeError:
logger.error(f"解析points JSON失败: {points}")
return
@@ -476,7 +475,6 @@ class RelationshipManager:
person_id, "forgotten_points", json.dumps(forgotten_points, ensure_ascii=False, indent=None)
)
# 更新数据库
await person_info_manager.update_one_field(
person_id, "points", json.dumps(current_points, ensure_ascii=False, indent=None)