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v0.5.7

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记忆系统接入关键词，重新启动自主发言功能
This commit is contained in:
SengokuCola
2025-03-06 14:27:22 +08:00
parent 8bca235ecf
commit eaa711ada7
10 changed files with 520 additions and 112 deletions
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115
src/plugins/chat/prompt_builder.py
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@@ -2,13 +2,15 @@ import time
import random
from ..schedule.schedule_generator import bot_schedule
import os
from .utils import get_embedding, combine_messages, get_recent_group_detailed_plain_text
from .utils import get_embedding, combine_messages, get_recent_group_detailed_plain_text,find_similar_topics
from ...common.database import Database
from .config import global_config
from .topic_identifier import topic_identifier
from ..memory_system.memory import memory_graph
from ..memory_system.memory import memory_graph,hippocampus
from random import choice
import numpy as np
import jieba
from collections import Counter
class PromptBuilder:
def __init__(self):
@@ -16,7 +18,9 @@ class PromptBuilder:
self.activate_messages = ''
self.db = Database.get_instance()
def _build_prompt(self,
async def _build_prompt(self,
message_txt: str,
sender_name: str = "某人",
relationship_value: float = 0.0,
@@ -31,60 +35,7 @@ class PromptBuilder:
Returns:
str: 构建好的prompt
"""
memory_prompt = ''
start_time = time.time() # 记录开始时间
# topic = await topic_identifier.identify_topic_llm(message_txt)
topic = topic_identifier.identify_topic_snownlp(message_txt)
# print(f"\033[1;32m[pb主题识别]\033[0m 主题: {topic}")
all_first_layer_items = [] # 存储所有第一层记忆
all_second_layer_items = {} # 用字典存储每个topic的第二层记忆
overlapping_second_layer = set() # 存储重叠的第二层记忆
if topic:
# 遍历所有topic
for current_topic in topic:
first_layer_items, second_layer_items = memory_graph.get_related_item(current_topic, depth=2)
# if first_layer_items:
# print(f"\033[1;32m[前额叶]\033[0m 主题 '{current_topic}' 的第一层记忆: {first_layer_items}")
# 记录第一层数据
all_first_layer_items.extend(first_layer_items)
# 记录第二层数据
all_second_layer_items[current_topic] = second_layer_items
# 检查是否有重叠的第二层数据
for other_topic, other_second_layer in all_second_layer_items.items():
if other_topic != current_topic:
# 找到重叠的记忆
overlap = set(second_layer_items) & set(other_second_layer)
if overlap:
# print(f"\033[1;32m[前额叶]\033[0m 发现主题 '{current_topic}' 和 '{other_topic}' 有共同的第二层记忆: {overlap}")
overlapping_second_layer.update(overlap)
selected_first_layer = random.sample(all_first_layer_items, min(2, len(all_first_layer_items))) if all_first_layer_items else []
selected_second_layer = random.sample(list(overlapping_second_layer), min(2, len(overlapping_second_layer))) if overlapping_second_layer else []
# 合并并去重
all_memories = list(set(selected_first_layer + selected_second_layer))
if all_memories:
print(f"\033[1;32m[前额叶]\033[0m 合并所有需要的记忆: {all_memories}")
random_item = " ".join(all_memories)
memory_prompt = f"看到这些聊天，你想起来{random_item}\n"
else:
memory_prompt = "" # 如果没有记忆，则返回空字符串
end_time = time.time() # 记录结束时间
print(f"\033[1;32m[回忆耗时]\033[0m 耗时: {(end_time - start_time):.3f}秒") # 输出耗时
"""
#先禁用关系
if 0 > 30:
relation_prompt = "关系特别特别好，你很喜欢喜欢他"
@@ -112,22 +63,48 @@ class PromptBuilder:
prompt_info = self.get_prompt_info(message_txt,threshold=0.5)
if prompt_info:
prompt_info = f'''\n----------------------------------------------------\n你有以下这些[知识]：\n{prompt_info}\n请你记住上面的[知识]，之后可能会用到\n----------------------------------------------------\n'''
# promt_info_prompt = '你有一些[知识]，在上面可以参考。'
end_time = time.time()
print(f"\033[1;32m[知识检索]\033[0m 耗时: {(end_time - start_time):.3f}秒")
# print(f"\033[1;34m[调试]\033[0m 获取知识库内容结果: {prompt_info}")
# print(f"\033[1;34m[调试信息]\033[0m 正在构建聊天上下文")
# 获取聊天上下文
chat_talking_prompt = ''
if group_id:
chat_talking_prompt = get_recent_group_detailed_plain_text(self.db, group_id, limit=global_config.MAX_CONTEXT_SIZE,combine = True)
chat_talking_prompt = f"以下是群里正在聊天的内容：\n{chat_talking_prompt}"
# print(f"\033[1;34m[调试]\033[0m 已从数据库获取群 {group_id} 的消息记录:{chat_talking_prompt}")
# 使用新的记忆获取方法
memory_prompt = ''
start_time = time.time()
# 调用 hippocampus 的 get_relevant_memories 方法
relevant_memories = await hippocampus.get_relevant_memories(
text=message_txt,
max_topics=5,
similarity_threshold=0.4
)
if relevant_memories:
# 格式化记忆内容
memory_items = []
for memory in relevant_memories:
memory_items.append(f"关于「{memory['topic']}」的记忆：{memory['content']}")
memory_prompt = f"看到这些聊天，你想起来：\n" + "\n".join(memory_items) + "\n"
# 打印调试信息
print("\n\033[1;32m[记忆检索]\033[0m 找到以下相关记忆：")
for memory in relevant_memories:
print(f"- 主题「{memory['topic']}」[相似度: {memory['similarity']:.2f}]: {memory['content']}")
end_time = time.time()
print(f"\033[1;32m[回忆耗时]\033[0m 耗时: {(end_time - start_time):.3f}秒")
#激活prompt构建
activate_prompt = ''
activate_prompt = f"以上是群里正在进行的聊天，{memory_prompt} 现在昵称为 '{sender_name}' 的用户说的:{message_txt}。引起了你的注意,你和他{relation_prompt}，你想要{relation_prompt_2}。"
@@ -162,29 +139,19 @@ class PromptBuilder:
if random.random() < 0.01:
prompt_ger += '你喜欢用文言文'
#额外信息要求
extra_info = '''但是记得回复平淡一些，简短一些，尤其注意在没明确提到时不要过多提及自身的背景, 记住不要输出多余内容(包括前后缀，冒号和引号，括号，表情等)，只需要输出回复内容就好，不要输出其他任何内容'''
#合并prompt
prompt = ""
prompt += f"{prompt_info}\n"
prompt += f"{prompt_date}\n"
prompt += f"{chat_talking_prompt}\n"
# prompt += f"{memory_prompt}\n"
# prompt += f"{activate_prompt}\n"
prompt += f"{prompt_personality}\n"
prompt += f"{prompt_ger}\n"
prompt += f"{extra_info}\n"
'''读空气prompt处理'''
activate_prompt_check=f"以上是群里正在进行的聊天，昵称为 '{sender_name}' 的用户说的:{message_txt}。引起了你的注意,你和他{relation_prompt}，你想要{relation_prompt_2}，但是这不一定是合适的时机，请你决定是否要回应这条消息。"
prompt_personality_check = ''
extra_check_info=f"请注意把握群里的聊天内容的基础上，综合群内的氛围，例如，和{global_config.BOT_NICKNAME}相关的话题要积极回复,如果是at自己的消息一定要回复，如果自己正在和别人聊天一定要回复，其他话题如果合适搭话也可以回复，如果认为应该回复请输出yes，否则输出no，请注意是决定是否需要回复，而不是编写回复内容，除了yes和no不要输出任何回复内容。"