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Merge pull request #2 from MaiM-with-u/tc_merge

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修复了情绪管理器没有正确导入导致发布出消息
This commit is contained in:
Rikki
2025-03-11 16:59:22 +08:00
committed by GitHub
parent 67f6d7cd42 af962c2e84
commit 70c102068c
6 changed files with 48 additions and 31 deletions
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11
src/plugins/chat/bot.py
View File

@@ -163,12 +163,16 @@ class ChatBot:
response,raw_content = await self.gpt.generate_response(message)
# print(f"response: {response}")
if response:
# print(f"有response: {response}")
container = message_manager.get_container(chat.stream_id)
thinking_message = None
# 找到message,删除
# print(f"开始找思考消息")
for msg in container.messages:
if isinstance(msg, MessageThinking) and msg.message_info.message_id == think_id:
# print(f"找到思考消息: {msg}")
thinking_message = msg
container.messages.remove(msg)
break
@@ -186,14 +190,14 @@ class ChatBot:
mark_head = False
for msg in response:
print("test")
# print(f"\033[1;32m[回复内容]\033[0m {msg}")
# 通过时间改变时间戳
typing_time = calculate_typing_time(msg)
print(f"typing_time: {typing_time}")
accu_typing_time += typing_time
timepoint = tinking_time_point + accu_typing_time
message_segment = Seg(type='text', data=msg)
print(f"message_segment: {message_segment}")
bot_message = MessageSending(
message_id=think_id,
chat_stream=chat,
@@ -203,12 +207,15 @@ class ChatBot:
is_head=not mark_head,
is_emoji=False
)
print(f"bot_message: {bot_message}")
if not mark_head:
mark_head = True
print(f"添加消息到message_set: {bot_message}")
message_set.add_message(bot_message)
# message_set 可以直接加入 message_manager
# print(f"\033[1;32m[回复]\033[0m 将回复载入发送容器")
print(f"添加message_set到message_manager")
message_manager.add_message(message_set)
bot_response_time = tinking_time_point

5
src/plugins/chat/llm_generator.py
View File

@@ -63,6 +63,9 @@ class ResponseGenerator:
)
raw_content = model_response
# print(f"raw_content: {raw_content}")
# print(f"model_response: {model_response}")
if model_response:
logger.info(f'{global_config.BOT_NICKNAME}的回复是：{model_response}')
model_response = await self._process_response(model_response)
@@ -200,6 +203,8 @@ class ResponseGenerator:
return None, []
processed_response = process_llm_response(content)
# print(f"得到了处理后的llm返回{processed_response}")
return processed_response

9
src/plugins/chat/message_sender.py
View File

@@ -149,6 +149,7 @@ class MessageManager:
"""处理聊天流消息"""
container = self.get_container(chat_id)
if container.has_messages():
# print(f"处理有message的容器chat_id: {chat_id}")
message_earliest = container.get_earliest_message()
if isinstance(message_earliest, MessageThinking):
@@ -161,15 +162,15 @@ class MessageManager:
logger.warning(f"消息思考超时({thinking_time}秒)，移除该消息")
container.remove_message(message_earliest)
else:
print(f"\033[1;34m[调试]\033[0m 消息'{message_earliest.processed_plain_text}'正在发送中")
if message_earliest.is_head and message_earliest.update_thinking_time() > 30:
await message_sender.send_message(message_earliest.set_reply())
else:
await message_sender.send_message(message_earliest)
# if message_earliest.is_emoji:
# message_earliest.processed_plain_text = "[表情包]"
await message_earliest.process()
print(f"\033[1;34m[调试]\033[0m 消息'{message_earliest.processed_plain_text}'正在发送中")
await self.storage.store_message(message_earliest, message_earliest.chat_stream,None)
container.remove_message(message_earliest)

48
src/plugins/chat/utils.py
View File

@@ -15,6 +15,7 @@ from .config import global_config
from .message import MessageThinking, MessageRecv,MessageSending,MessageProcessBase,Message
from .message_base import MessageBase,BaseMessageInfo,UserInfo,GroupInfo
from .chat_stream import ChatStream
from ..moods.moods import MoodManager
driver = get_driver()
config = driver.config
@@ -72,43 +73,42 @@ 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
"""从数据库中获取最接近指定时间戳的聊天记录
Args:
db: 数据库实例
length: 要获取的消息数量
timestamp: 时间戳
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
list: 消息记录列表，每个记录包含时间和文本信息
"""
chat_records = []
closest_record = db.db.messages.find_one({"time": {"$lte": timestamp}}, sort=[('time', -1)])
if closest_record and closest_record.get('memorized', 0) < 4:
if closest_record:
closest_time = closest_record['time']
chat_id = closest_record['chat_id'] # 获取groupid
# 获取该时间戳之后的length条消息，且groupid相同
chat_id = closest_record['chat_id'] # 获取chat_id
# 获取该时间戳之后的length条消息，保持相同的chat_id
chat_records = list(db.db.messages.find(
{"time": {"$gt": closest_time}, "chat_id": chat_id}
{
"time": {"$gt": closest_time},
"chat_id": chat_id # 添加chat_id过滤
}
).sort('time', 1).limit(length))
# 更新每条消息的memorized属性
for record in records:
current_memorized = record.get('memorized', 0)
if current_memorized > 3:
print("消息已读取3次，跳过")
return ''
# 更新memorized值
db.db.messages.update_one(
{"_id": record["_id"]},
{"$set": {"memorized": current_memorized + 1}}
)
# 添加到记录列表中
chat_records.append({
'text': record["detailed_plain_text"],
# 转换记录格式
formatted_records = []
for record in chat_records:
formatted_records.append({
'time': record["time"],
'group_id': record["group_id"]
'chat_id': record["chat_id"],
'detailed_plain_text': record.get("detailed_plain_text", "") # 添加文本内容
})
return chat_records
return formatted_records
return []
async def get_recent_group_messages(db, chat_id:str, limit: int = 12) -> list:

4
src/plugins/chat/utils_image.py
View File

@@ -315,6 +315,10 @@ class ImageManager:
prompt = "请用中文描述这张图片的内容。如果有文字，请把文字都描述出来。并尝试猜测这个图片的含义。最多200个字。"
description, _ = await self._llm.generate_response_for_image(prompt, image_base64)
if description is None:
logger.warning("AI未能生成图片描述")
return "[图片]"
# 根据配置决定是否保存图片
if global_config.EMOJI_SAVE:
# 生成文件名和路径

2
src/plugins/memory_system/memory.py
View File

@@ -238,7 +238,7 @@ class Hippocampus:
time_info += f"是从 {earliest_str} 到 {latest_str} 的对话:\n"
for msg in messages:
input_text += f"{msg['text']}\n"
input_text += f"{msg['detailed_plain_text']}\n"
logger.debug(input_text)