feat: 可选启动系统时间提示

astrbot/core/config/default.py

@@ -26,6 +26,7 @@ DEFAULT_CONFIG = {
     "wake_prefix": "",
     "web_search": False,
     "identifier": False,
+    "datetime_system_prompt": True,
     "default_personality": "如果用户寻求帮助或者打招呼，请告诉他可以用 /help 查看 AstrBot 帮助。",
     "prompt_prefix": ""
   },
@@ -237,6 +238,9 @@ CONFIG_METADATA_2 = {
             "wake_prefix": {"description": "LLM 聊天额外唤醒前缀", "type": "string", "hint": "使用 LLM 聊天额外的触发条件。如填写 `chat`，则需要消息前缀加上 `/chat` 才能触发 LLM 聊天，是一个防止滥用的手段。"},
             "web_search": {"description": "启用网页搜索", "type": "bool", "hint": "能访问 Google 时效果最佳。如果 Google 访问失败，程序会依次访问 Bing, Sogo 搜索引擎。"},
             "identifier": {"description": "启动识别群员", "type": "bool", "hint": "在 Prompt 前加上群成员的名字以让模型更好地了解群聊状态。启用将略微增加 token 开销，"},
+            "datetime_system_prompt": {"description": "启用日期时间系统提示", "type": "bool", "hint": "启用后，会在系统提示词中加上当前机器的日期时间。"},
+            "default_personality": {"description": "默认人格", "type": "string", "hint": "默认人格（情境设置/System Prompt）文本。"},
+            "prompt_prefix": {"description": "Prompt 前缀文本", "type": "string", "hint": "添加之后，会在每次对话的 Prompt 前加上此文本。"},
         }
     },
     "content_safety": {

astrbot/core/pipeline/process_stage/method/llm_request.py

@@ -13,7 +13,6 @@ from astrbot.core.star.star import star_map
 class LLMRequestSubStage(Stage):
     
     async def initialize(self, ctx: PipelineContext) -> None:
-        self.curr_provider = ctx.plugin_manager.context.get_using_provider()
         self.prompt_prefix = ctx.astrbot_config['provider_settings']['prompt_prefix']
         self.identifier = ctx.astrbot_config['provider_settings']['identifier']
         self.ctx = ctx
@@ -35,14 +34,15 @@ class LLMRequestSubStage(Stage):
         
         tools = self.ctx.plugin_manager.context.get_llm_tool_manager()
         
+        provider = self.ctx.plugin_manager.context.get_using_provider()
         try:
-            llm_response = await self.curr_provider.text_chat(
+            llm_response = await provider.text_chat(
                 prompt=event.message_str, 
                 session_id=event.session_id, 
                 image_urls=image_urls,
                 func_tool=tools
             )
-            await Metric.upload(llm_tick=1, model_name=self.curr_provider.get_model(), provider_type=self.curr_provider.meta().type)
+            await Metric.upload(llm_tick=1, model_name=provider.get_model(), provider_type=provider.meta().type)
             
             if llm_response.role == 'assistant':
                 # text completion

astrbot/core/provider/sources/openai_source.py

@@ -1,6 +1,7 @@
 import traceback
 import base64
 import json
+import datetime
 
 from openai import AsyncOpenAI, NOT_GIVEN
 from openai.types.chat.chat_completion import ChatCompletion
@@ -28,6 +29,7 @@ class ProviderOpenAIOfficial(Provider):
         self.chosen_api_key = None
         self.api_keys: List = provider_config.get("key", [])
         self.chosen_api_key = self.api_keys[0] if len(self.api_keys) > 0 else None
+        self.enable_datetime = provider_config.get("datetime_system_prompt", True)
 
         self.client = AsyncOpenAI(
             api_key=self.chosen_api_key,
@@ -136,15 +138,19 @@ class ProviderOpenAIOfficial(Provider):
         new_record = await self.assemble_context(prompt, image_urls)
         
         context_query = []
-        
         if not contexts:
             context_query = [*self.session_memory[session_id], new_record]
+            system_prompt = ""
             if self.curr_personality["prompt"]:
-                context_query.insert(0, {"role": "system", "content": self.curr_personality["prompt"]})
+                system_prompt = self.curr_personality["prompt"]
+            if self.enable_datetime:
+                system_prompt += f"Current datetime: {datetime.datetime.now().strftime('%Y-%m-%d %H:%M')}"
+            if system_prompt:
+                context_query.insert(0, {"role": "system", "content": system_prompt})
         else:
             context_query = contexts
             
-        logger.debug(f"请求上下文：{context_query}")
+        logger.debug(f"请求上下文：{context_query}, {self.get_model()}")
         
         payloads = {
             "messages": context_query,