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meng_xi_pan
2025-03-14 16:47:31 +08:00
parent 6a5316bcf8
commit 414340588d
3 changed files with 95 additions and 35 deletions
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35
src/plugins/chat/llm_generator.py
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@@ -76,30 +76,31 @@ class ResponseGenerator:
self, message: MessageThinking, model: LLM_request
) -> Optional[str]:
"""使用指定的模型生成回复"""
sender_name = (
message.chat_stream.user_info.user_nickname
or f"用户{message.chat_stream.user_info.user_id}"
)
if message.chat_stream.user_info.user_cardname:
sender_name = ""
if message.chat_stream.user_info.user_cardname and message.chat_stream.user_info.user_nickname:
sender_name = f"[({message.chat_stream.user_info.user_id}){message.chat_stream.user_info.user_nickname}]{message.chat_stream.user_info.user_cardname}"
elif message.chat_stream.user_info.user_nickname:
sender_name = f"({message.chat_stream.user_info.user_id}){message.chat_stream.user_info.user_nickname}"
else:
f"用户({message.chat_stream.user_info.user_id})"
# 获取关系值
relationship_value = (
relationship_manager.get_relationship(
message.chat_stream
).relationship_value
if relationship_manager.get_relationship(message.chat_stream)
else 0.0
)
if relationship_value != 0.0:
# print(f"\033[1;32m[关系管理]\033[0m 回复中_当前关系值: {relationship_value}")
pass
# # 获取关系值
# relationship_value = (
# relationship_manager.get_relationship(
# message.chat_stream
# ).relationship_value
# if relationship_manager.get_relationship(message.chat_stream)
# else 0.0
# )
# if relationship_value != 0.0:
# # print(f"\033[1;32m[关系管理]\033[0m 回复中_当前关系值: {relationship_value}")
# pass
# 构建prompt
prompt, prompt_check = await prompt_builder._build_prompt(
message.chat_stream,
message_txt=message.processed_plain_text,
sender_name=sender_name,
relationship_value=relationship_value,
stream_id=message.chat_stream.stream_id,
)