diff --git a/astrbot/core/config/default.py b/astrbot/core/config/default.py index fc304d587..4a75a11bc 100644 --- a/astrbot/core/config/default.py +++ b/astrbot/core/config/default.py @@ -54,6 +54,7 @@ DEFAULT_CONFIG = { "wake_prefix": "", "web_search": False, "web_search_link": False, + "display_reasoning_text": False, "identifier": False, "datetime_system_prompt": True, "default_personality": "default", @@ -1652,6 +1653,11 @@ CONFIG_METADATA_2 = { "obvious_hint": True, "hint": "开启后,将会传入网页搜索结果的链接给模型,并引导模型输出引用链接。", }, + "display_reasoning_text": { + "description": "显示思考内容", + "type": "bool", + "hint": "开启后,将在回复中显示模型的思考过程。", + }, "identifier": { "description": "启动识别群员", "type": "bool", diff --git a/packages/thinking_filter/main.py b/packages/thinking_filter/main.py new file mode 100644 index 000000000..eb36a107f --- /dev/null +++ b/packages/thinking_filter/main.py @@ -0,0 +1,70 @@ +import re +from astrbot.api.event import filter, AstrMessageEvent +from astrbot.api.star import Context, Star, register +from astrbot.api.provider import LLMResponse +from openai.types.chat.chat_completion import ChatCompletion + + +@register( + "thinking_filter", + "Soulter", + "可选择是否过滤推理模型的思考内容", + "1.0.0", + "https://astrbot.app", +) +class R1Filter(Star): + def __init__(self, context: Context): + super().__init__(context) + self.display_reasoning_text = ( + self.context.get_config() + .get("provider_settings", {}) + .get("display_reasoning_text", False) + ) + + @filter.on_llm_response() + async def resp(self, event: AstrMessageEvent, response: LLMResponse): + if self.display_reasoning_text: + if ( + response + and response.raw_completion + and isinstance(response.raw_completion, ChatCompletion) + ): + if ( + len(response.raw_completion.choices) + and response.raw_completion.choices[0].message + ): + message = response.raw_completion.choices[0].message + reasoning_content = "" # 初始化 reasoning_content + + # 检查 Groq deepseek-r1-distill-llama-70b模型的 'reasoning' 属性 + if hasattr(message, "reasoning") and message.reasoning: + reasoning_content = message.reasoning + # 检查 DeepSeek deepseek-reasoner模型的 'reasoning_content' + elif ( + hasattr(message, "reasoning_content") + and message.reasoning_content + ): + reasoning_content = message.reasoning_content + + if reasoning_content: + response.completion_text = ( + f"🤔思考:{reasoning_content}\n\n{message.content}" + ) + else: + response.completion_text = message.content + + else: + # DeepSeek 官方的模型的思考存在了 reason_content 字段因此不需要过滤 + completion_text = response.completion_text + # 适配 ollama deepseek-r1 模型 + if r"" in completion_text or r"" in completion_text: + completion_text = re.sub( + r".*?", "", completion_text, flags=re.DOTALL + ).strip() + # 可能有单标签情况 + completion_text = ( + completion_text.replace(r"", "") + .replace(r"", "") + .strip() + ) + response.completion_text = completion_text