feat:添加来自困惑内容的主动提问发言

This commit is contained in:
SengokuCola
2025-10-04 17:18:43 +08:00
parent eaf218ff15
commit 35c3fe5b10
16 changed files with 666 additions and 334 deletions

View File

@@ -3,15 +3,79 @@
记忆系统工具函数
包含模糊查找、相似度计算等工具函数
"""
import json
import re
from difflib import SequenceMatcher
from typing import List, Tuple, Optional
from src.common.database.database_model import MemoryChest as MemoryChestModel
from src.common.logger import get_logger
from json_repair import repair_json
logger = get_logger("memory_utils")
def get_all_titles(exclude_locked: bool = False) -> list[str]:
"""
获取记忆仓库中的所有标题
Args:
exclude_locked: 是否排除锁定的记忆,默认为 False
Returns:
list: 包含所有标题的列表
"""
try:
# 查询所有记忆记录的标题
titles = []
for memory in MemoryChestModel.select():
if memory.title:
# 如果 exclude_locked 为 True 且记忆已锁定,则跳过
if exclude_locked and memory.locked:
continue
titles.append(memory.title)
return titles
except Exception as e:
print(f"获取记忆标题时出错: {e}")
return []
def parse_md_json(json_text: str) -> list[str]:
"""从Markdown格式的内容中提取JSON对象和推理内容"""
json_objects = []
reasoning_content = ""
# 使用正则表达式查找```json包裹的JSON内容
json_pattern = r"```json\s*(.*?)\s*```"
matches = re.findall(json_pattern, json_text, re.DOTALL)
# 提取JSON之前的内容作为推理文本
if matches:
# 找到第一个```json的位置
first_json_pos = json_text.find("```json")
if first_json_pos > 0:
reasoning_content = json_text[:first_json_pos].strip()
# 清理推理内容中的注释标记
reasoning_content = re.sub(r"^//\s*", "", reasoning_content, flags=re.MULTILINE)
reasoning_content = reasoning_content.strip()
for match in matches:
try:
# 清理可能的注释和格式问题
json_str = re.sub(r"//.*?\n", "\n", match) # 移除单行注释
json_str = re.sub(r"/\*.*?\*/", "", json_str, flags=re.DOTALL) # 移除多行注释
if json_str := json_str.strip():
json_obj = json.loads(json_str)
if isinstance(json_obj, dict):
json_objects.append(json_obj)
elif isinstance(json_obj, list):
for item in json_obj:
if isinstance(item, dict):
json_objects.append(item)
except Exception as e:
logger.warning(f"解析JSON块失败: {e}, 块内容: {match[:100]}...")
continue
return json_objects, reasoning_content
def calculate_similarity(text1: str, text2: str) -> float:
"""