chore: ruff format

* fix: assistant message validation error when tool_call exists but content not exists

* fix: enhance content validation in Message model to allow None for assistant role with tool_calls

astrbot/core/agent/message.py

@@ -3,7 +3,7 @@
 
 from typing import Any, ClassVar, Literal, cast
 
-from pydantic import BaseModel, GetCoreSchemaHandler
+from pydantic import BaseModel, GetCoreSchemaHandler, model_validator
 from pydantic_core import core_schema
 
 
@@ -145,23 +145,39 @@ class Message(BaseModel):
         "tool",
     ]
 
-    content: str | list[ContentPart]
+    content: str | list[ContentPart] | None = None
     """The content of the message."""
 
+    tool_calls: list[ToolCall] | list[dict] | None = None
+    """The tool calls of the message."""
+
+    tool_call_id: str | None = None
+    """The ID of the tool call."""
+
+    @model_validator(mode="after")
+    def check_content_required(self):
+        # assistant + tool_calls is not None: allow content to be None
+        if self.role == "assistant" and self.tool_calls is not None:
+            return self
+
+        # other all cases: content is required
+        if self.content is None:
+            raise ValueError(
+                "content is required unless role='assistant' and tool_calls is not None"
+            )
+        return self
+
 
 class AssistantMessageSegment(Message):
     """A message segment from the assistant."""
 
     role: Literal["assistant"] = "assistant"
-    content: str | list[ContentPart] | None = None
-    tool_calls: list[ToolCall] | list[dict] | None = None
 
 
 class ToolCallMessageSegment(Message):
     """A message segment representing a tool call."""
 
     role: Literal["tool"] = "tool"
-    tool_call_id: str
 
 
 class UserMessageSegment(Message):

packages/astrbot/long_term_memory.py

@@ -8,7 +8,7 @@ from astrbot.api import star
 from astrbot.api.event import AstrMessageEvent
 from astrbot.api.message_components import At, Image, Plain
 from astrbot.api.platform import MessageType
-from astrbot.api.provider import Provider, ProviderRequest
+from astrbot.api.provider import LLMResponse, Provider, ProviderRequest
 from astrbot.core.astrbot_config_mgr import AstrBotConfigManager
 
 """
@@ -158,8 +158,12 @@ class LongTermMemory:
         cfg = self.cfg(event)
         if cfg["enable_active_reply"]:
             prompt = req.prompt
-            req.prompt = f"You are now in a chatroom. The chat history is as follows:\n{chats_str}"
-            req.prompt += f"\nNow, a new message is coming: `{prompt}`. Please react to it. Only output your response and do not output any other information."
+            req.prompt = (
+                f"You are now in a chatroom. The chat history is as follows:\n{chats_str}"
+                f"\nNow, a new message is coming: `{prompt}`. "
+                "Please react to it. Only output your response and do not output any other information. "
+                "You MUST use the SAME language as the chatroom is using."
+            )
             req.contexts = []  # 清空上下文，当使用了主动回复，所有聊天记录都在一个prompt中。
         else:
             req.system_prompt += (
@@ -167,13 +171,15 @@ class LongTermMemory:
             )
             req.system_prompt += chats_str
 
-    async def after_req_llm(self, event: AstrMessageEvent):
+    async def after_req_llm(self, event: AstrMessageEvent, llm_resp: LLMResponse):
         if event.unified_msg_origin not in self.session_chats:
             return
 
-        if event.get_result() and event.get_result().is_llm_result():
-            final_message = f"[You/{datetime.datetime.now().strftime('%H:%M:%S')}]: {event.get_result().get_plain_text()}"
-            logger.debug(f"ltm | {event.unified_msg_origin} | {final_message}")
+        if llm_resp.completion_text:
+            final_message = f"[You/{datetime.datetime.now().strftime('%H:%M:%S')}]: {llm_resp.completion_text}"
+            logger.debug(
+                f"Recorded AI response: {event.unified_msg_origin} | {final_message}"
+            )
             self.session_chats[event.unified_msg_origin].append(final_message)
             cfg = self.cfg(event)
             if len(self.session_chats[event.unified_msg_origin]) > cfg["max_cnt"]:

packages/astrbot/main.py

@@ -322,7 +322,7 @@ class Main(star.Star):
 
     @filter.on_llm_response()
     async def inject_reasoning(self, event: AstrMessageEvent, resp: LLMResponse):
-        """在 LLM 响应后基于配置注入思考过程文本"""
+        """在 LLM 响应后基于配置注入思考过程文本 / 在 LLM 响应后记录对话"""
         umo = event.unified_msg_origin
         cfg = self.context.get_config(umo).get("provider_settings", {})
         show_reasoning = cfg.get("display_reasoning_text", False)
@@ -331,12 +331,9 @@ class Main(star.Star):
                 f"🤔 思考: {resp.reasoning_content}\n\n{resp.completion_text}"
             )
 
-    @filter.after_message_sent()
-    async def after_llm_req(self, event: AstrMessageEvent):
-        """在 LLM 请求后记录对话"""
         if self.ltm and self.ltm_enabled(event):
             try:
-                await self.ltm.after_req_llm(event)
+                await self.ltm.after_req_llm(event, resp)
             except Exception as e:
                 logger.error(f"ltm: {e}")