diff --git a/README.md b/README.md
index 575dc8232..0c02d1cba 100644
--- a/README.md
+++ b/README.md
@@ -40,6 +40,10 @@
**交流群**: 571780722 另一个群(开发和建议相关讨论)不一定有空回复,会优先写文档和代码
**交流群**: 1035228475 另一个群(开发和建议相关讨论)不一定有空回复,会优先写文档和代码
+**其他平台版本**
+
+- (由 [CabLate](https://github.com/cablate) 贡献) [Telegram 与其他平台(未来可能会有)的版本](https://github.com/cablate/MaiMBot/tree/telegram) - [集中讨论串](https://github.com/SengokuCola/MaiMBot/discussions/149)
+
##
📚 文档 ⬇️ 快速开始使用麦麦 ⬇️
diff --git a/run.py b/run.py
index 5546d1faa..baea4d13c 100644
--- a/run.py
+++ b/run.py
@@ -98,7 +98,7 @@ def install_mongodb_compass():
run_cmd(r"powershell mongodb\bin\Install-Compass.ps1")
input("按任意键启动麦麦")
input("如不需要启动此窗口可直接关闭,无需等待 Compass 安装完成")
- install_mongodb_compass()
+ run_maimbot()
def install_napcat():
diff --git a/run_memory_vis.bat b/run_memory_vis.bat
index 14b9c766f..b1feb0cb2 100644
--- a/run_memory_vis.bat
+++ b/run_memory_vis.bat
@@ -8,7 +8,18 @@ if errorlevel 1 (
exit /b 1
)
echo Conda 环境 "%CONDA_ENV%" 激活成功
-python src/plugins/memory_system/memory_manual_build.py
+
+set /p OPTION="请选择运行选项 (1: 运行全部绘制, 2: 运行简单绘制): "
+if "%OPTION%"=="1" (
+ python src/plugins/memory_system/memory_manual_build.py
+) else if "%OPTION%"=="2" (
+ python src/plugins/memory_system/draw_memory.py
+) else (
+ echo 无效的选项
+ pause
+ exit /b 1
+)
+
if errorlevel 1 (
echo 命令执行失败,错误代码 %errorlevel%
pause
diff --git a/src/plugins/chat/emoji_manager.py b/src/plugins/chat/emoji_manager.py
index eb1ff281a..414eaf74d 100644
--- a/src/plugins/chat/emoji_manager.py
+++ b/src/plugins/chat/emoji_manager.py
@@ -36,6 +36,7 @@ class EmojiManager:
self.llm_emotion_judge = LLM_request(model=global_config.llm_normal_minor, max_tokens=60,
temperature=0.8) # 更高的温度,更少的token(后续可以根据情绪来调整温度)
+
def _ensure_emoji_dir(self):
"""确保表情存储目录存在"""
os.makedirs(self.EMOJI_DIR, exist_ok=True)
@@ -331,3 +332,4 @@ class EmojiManager:
# 创建全局单例
emoji_manager = EmojiManager()
+
diff --git a/src/plugins/chat/utils.py b/src/plugins/chat/utils.py
index e5ebad59d..054526e94 100644
--- a/src/plugins/chat/utils.py
+++ b/src/plugins/chat/utils.py
@@ -99,37 +99,43 @@ def calculate_information_content(text):
def get_cloest_chat_from_db(db, length: int, timestamp: str):
- """从数据库中获取最接近指定时间戳的聊天记录,并记录读取次数"""
- chat_text = ''
+ """从数据库中获取最接近指定时间戳的聊天记录,并记录读取次数
+
+ Returns:
+ list: 消息记录字典列表,每个字典包含消息内容和时间信息
+ """
+ chat_records = []
closest_record = db.db.messages.find_one({"time": {"$lte": timestamp}}, sort=[('time', -1)])
-
- if closest_record and closest_record.get('memorized', 0) < 4:
+
+ if closest_record and closest_record.get('memorized', 0) < 4:
closest_time = closest_record['time']
- group_id = closest_record['group_id'] # 获取groupid
+ group_id = closest_record['group_id']
# 获取该时间戳之后的length条消息,且groupid相同
- chat_records = list(db.db.messages.find(
+ records = list(db.db.messages.find(
{"time": {"$gt": closest_time}, "group_id": group_id}
).sort('time', 1).limit(length))
-
+
# 更新每条消息的memorized属性
- for record in chat_records:
- # 检查当前记录的memorized值
+ for record in records:
current_memorized = record.get('memorized', 0)
if current_memorized > 3:
- # print(f"消息已读取3次,跳过")
+ print("消息已读取3次,跳过")
return ''
-
+
# 更新memorized值
db.db.messages.update_one(
{"_id": record["_id"]},
{"$set": {"memorized": current_memorized + 1}}
)
-
- chat_text += record["detailed_plain_text"]
-
- return chat_text
- # print(f"消息已读取3次,跳过")
- return ''
+
+ # 添加到记录列表中
+ chat_records.append({
+ 'text': record["detailed_plain_text"],
+ 'time': record["time"],
+ 'group_id': record["group_id"]
+ })
+
+ return chat_records
async def get_recent_group_messages(db, group_id: int, limit: int = 12) -> list:
diff --git a/src/plugins/memory_system/draw_memory.py b/src/plugins/memory_system/draw_memory.py
index 006991bcb..c2d04064d 100644
--- a/src/plugins/memory_system/draw_memory.py
+++ b/src/plugins/memory_system/draw_memory.py
@@ -201,67 +201,6 @@ def topic_what(text, topic):
prompt = f'这是一段文字:{text}。我想知道这记忆里有什么关于{topic}的话题,帮我总结成一句自然的话,可以包含时间和人物。只输出这句话就好'
return prompt
-def visualize_graph(memory_graph: Memory_graph, color_by_memory: bool = False):
- # 设置中文字体
- plt.rcParams['font.sans-serif'] = ['SimHei'] # 用来正常显示中文标签
- plt.rcParams['axes.unicode_minus'] = False # 用来正常显示负号
-
- G = memory_graph.G
-
- # 保存图到本地
- nx.write_gml(G, "memory_graph.gml") # 保存为 GML 格式
-
- # 根据连接条数或记忆数量设置节点颜色
- node_colors = []
- nodes = list(G.nodes()) # 获取图中实际的节点列表
-
- if color_by_memory:
- # 计算每个节点的记忆数量
- memory_counts = []
- for node in nodes:
- memory_items = G.nodes[node].get('memory_items', [])
- if isinstance(memory_items, list):
- count = len(memory_items)
- else:
- count = 1 if memory_items else 0
- memory_counts.append(count)
- max_memories = max(memory_counts) if memory_counts else 1
-
- for count in memory_counts:
- # 使用不同的颜色方案:红色表示记忆多,蓝色表示记忆少
- if max_memories > 0:
- intensity = min(1.0, count / max_memories)
- color = (intensity, 0, 1.0 - intensity) # 从蓝色渐变到红色
- else:
- color = (0, 0, 1) # 如果没有记忆,则为蓝色
- node_colors.append(color)
- else:
- # 使用原来的连接数量着色方案
- max_degree = max(G.degree(), key=lambda x: x[1])[1] if G.degree() else 1
- for node in nodes:
- degree = G.degree(node)
- if max_degree > 0:
- red = min(1.0, degree / max_degree)
- blue = 1.0 - red
- color = (red, 0, blue)
- else:
- color = (0, 0, 1)
- node_colors.append(color)
-
- # 绘制图形
- plt.figure(figsize=(12, 8))
- pos = nx.spring_layout(G, k=1, iterations=50)
- nx.draw(G, pos,
- with_labels=True,
- node_color=node_colors,
- node_size=200,
- font_size=10,
- font_family='SimHei',
- font_weight='bold')
-
- title = '记忆图谱可视化 - ' + ('按记忆数量着色' if color_by_memory else '按连接数量着色')
- plt.title(title, fontsize=16, fontfamily='SimHei')
- plt.show()
def visualize_graph_lite(memory_graph: Memory_graph, color_by_memory: bool = False):
@@ -280,7 +219,7 @@ def visualize_graph_lite(memory_graph: Memory_graph, color_by_memory: bool = Fal
memory_items = H.nodes[node].get('memory_items', [])
memory_count = len(memory_items) if isinstance(memory_items, list) else (1 if memory_items else 0)
degree = H.degree(node)
- if memory_count < 5 or degree < 2: # 改为小于2而不是小于等于2
+ if memory_count < 3 or degree < 2: # 改为小于2而不是小于等于2
nodes_to_remove.append(node)
H.remove_nodes_from(nodes_to_remove)
@@ -291,7 +230,7 @@ def visualize_graph_lite(memory_graph: Memory_graph, color_by_memory: bool = Fal
return
# 保存图到本地
- nx.write_gml(H, "memory_graph.gml") # 保存为 GML 格式
+ # nx.write_gml(H, "memory_graph.gml") # 保存为 GML 格式
# 计算节点大小和颜色
node_colors = []
@@ -315,21 +254,23 @@ def visualize_graph_lite(memory_graph: Memory_graph, color_by_memory: bool = Fal
memory_count = len(memory_items) if isinstance(memory_items, list) else (1 if memory_items else 0)
# 使用指数函数使变化更明显
ratio = memory_count / max_memories
- size = 500 + 5000 * (ratio ** 2) # 使用平方函数使差异更明显
+ size = 500 + 5000 * (ratio ) # 使用1.5次方函数使差异不那么明显
node_sizes.append(size)
# 计算节点颜色(基于连接数)
degree = H.degree(node)
# 红色分量随着度数增加而增加
- red = min(1.0, degree / max_degree)
+ r = (degree / max_degree) ** 0.3
+ red = min(1.0, r)
# 蓝色分量随着度数减少而增加
- blue = 1.0 - red
- color = (red, 0, blue)
+ blue = max(0.0, 1 - red)
+ # blue = 1
+ color = (red, 0.1, blue)
node_colors.append(color)
# 绘制图形
plt.figure(figsize=(12, 8))
- pos = nx.spring_layout(H, k=1.5, iterations=50) # 增加k值使节点分布更开
+ pos = nx.spring_layout(H, k=1, iterations=50) # 增加k值使节点分布更开
nx.draw(H, pos,
with_labels=True,
node_color=node_colors,
@@ -339,7 +280,7 @@ def visualize_graph_lite(memory_graph: Memory_graph, color_by_memory: bool = Fal
font_weight='bold',
edge_color='gray',
width=0.5,
- alpha=0.7)
+ alpha=0.9)
title = '记忆图谱可视化 - 节点大小表示记忆数量,颜色表示连接数'
plt.title(title, fontsize=16, fontfamily='SimHei')
diff --git a/src/plugins/memory_system/memory_manual_build.py b/src/plugins/memory_system/memory_manual_build.py
index 012e5ecbb..3c120f21b 100644
--- a/src/plugins/memory_system/memory_manual_build.py
+++ b/src/plugins/memory_system/memory_manual_build.py
@@ -944,7 +944,7 @@ async def main():
db = Database.get_instance()
start_time = time.time()
- test_pare = {'do_build_memory':True,'do_forget_topic':False,'do_visualize_graph':True,'do_query':False,'do_merge_memory':False}
+ test_pare = {'do_build_memory':False,'do_forget_topic':False,'do_visualize_graph':True,'do_query':False,'do_merge_memory':False}
# 创建记忆图
memory_graph = Memory_graph()