fix(context): restore turn cap, serialize content parts and tool calls for llm compress, fix AftCompact debug log

Three context-compaction regression fixes after #8226:

1. Restore max_context_length -> enforce_max_turns propagation so
   normal turn-based truncation works again.
2. Serialize ContentPart and ToolCall objects into plain dicts in
   _message_to_dict so llm_compress no longer fails with JSON
   serialization errors.
3. Print _provider_messages (compacted) instead of run_context.messages
   (unchanged) in AftCompact debug log; truncate long role lists to
   first4,...,last4 to avoid log spam.

Assertions in tests are also hardened to avoid coupling to exact prompt
wording.

Author: Foolllll-J

astrbot/core/agent/context/compressor.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Protocol, runtime_checkable
 
-from ..message import Message
+from ..message import ContentPart, Message, ToolCall
 
 if TYPE_CHECKING:
     from astrbot import logger
@@ -100,9 +100,17 @@ def _message_to_dict(msg: Message) -> dict:
     """Convert a Message to a plain dict suitable for round splitting."""
     d = {"role": msg.role}
     if msg.content is not None:
-        d["content"] = msg.content
+        if isinstance(msg.content, list):
+            d["content"] = [
+                part.model_dump_for_context() if isinstance(part, ContentPart) else part
+                for part in msg.content
+            ]
+        else:
+            d["content"] = msg.content
     if getattr(msg, "tool_calls", None):
-        d["tool_calls"] = msg.tool_calls
+        d["tool_calls"] = [
+            tc.model_dump() if isinstance(tc, ToolCall) else tc for tc in msg.tool_calls
+        ]
     if getattr(msg, "tool_call_id", None):
         d["tool_call_id"] = msg.tool_call_id
     return d

astrbot/core/agent/runners/tool_loop_agent_runner.py

@@ -610,11 +610,14 @@ def _func_tool_for_provider(self) -> ToolSet | None:
             return None
         return self.req.func_tool
 
-    def _simple_print_message_role(self, tag: str = ""):
-        roles = []
-        for message in self.run_context.messages:
-            roles.append(message.role)
-        logger.debug(f"{tag} RunCtx.messages -> [{len(roles)}] {','.join(roles)}")
+    def _simple_print_message_role(self, tag: str, messages: list):
+        roles = [m.role for m in messages]
+        n = len(roles)
+        if n > 10:
+            summary = ",".join(roles[:4]) + ",...," + ",".join(roles[-4:])
+        else:
+            summary = ",".join(roles)
+        logger.debug(f"{tag} messages -> [{n}] {summary}")
 
     def follow_up(
         self,
@@ -713,11 +716,11 @@ async def step(self):
         # provider call. Persistent compaction is owned by the conversation /
         # memory layer.
         token_usage = self.req.conversation.token_usage if self.req.conversation else 0
-        self._simple_print_message_role("[BefCompact]")
+        self._simple_print_message_role("[BefCompact]", self.run_context.messages)
         self._provider_messages = await self.request_context_manager.process(
             self.run_context.messages, trusted_token_usage=token_usage
         )
-        self._simple_print_message_role("[AftCompact]")
+        self._simple_print_message_role("[AftCompact]", self._provider_messages)
 
         async for llm_response in self._iter_llm_responses_with_fallback():
             if llm_response.is_chunk:

astrbot/core/astr_main_agent.py

@@ -1534,6 +1534,7 @@ async def build_main_agent(
         llm_compress_keep_recent=config.llm_compress_keep_recent,
         llm_compress_provider=_get_compress_provider(config, plugin_context, event),
         truncate_turns=config.dequeue_context_length,
+        enforce_max_turns=config.max_context_length,
         tool_schema_mode=config.tool_schema_mode,
         fallback_providers=fallback_providers,
         tool_result_overflow_dir=(

tests/agent/test_context_manager.py

@@ -28,11 +28,9 @@ def __init__(self):
 
     async def text_chat(self, **kwargs):
         """模拟 LLM 调用，返回摘要"""
-        messages = kwargs.get("messages", [])
-        # 简单的摘要逻辑：返回消息数量统计
         return LLMResponse(
             role="assistant",
-            completion_text=f"历史对话包含 {len(messages) - 1} 条消息，主要讨论了技术话题。",
+            completion_text="Summary of conversation: Hello and discussed various topics.",
         )
 
     def get_model(self):
@@ -113,6 +111,28 @@ async def test_llm_compressor_keeps_history_when_summary_is_empty(self):
             "LLM context compression returned an empty summary."
         )
 
+    @pytest.mark.asyncio
+    async def test_llm_compressor_handles_textpart_content(self):
+        from astrbot.core.agent.context.compressor import LLMSummaryCompressor
+
+        provider = MockProvider()
+        compressor = LLMSummaryCompressor(provider=provider, keep_recent=1)  # type: ignore[arg-type]
+        messages = [
+            Message(role="user", content=[TextPart(text="Hello")]),
+            Message(role="assistant", content=[TextPart(text="Hi there")]),
+            Message(role="user", content=[TextPart(text="Summarize our work")]),
+            Message(role="assistant", content=[TextPart(text="Sure")]),
+        ]
+
+        result = await compressor(messages)
+
+        assert len(result) == 4
+        assert result[0].role == "user"
+        assert isinstance(result[0].content, str)
+        assert result[0].content.strip()
+        assert "Hello" in result[0].content
+        assert result[-1].content == [TextPart(text="Sure")]
+
     # ==================== Empty and Edge Cases ====================
 
     @pytest.mark.asyncio
@@ -759,5 +779,6 @@ def test_split_rounds_multi_tool(self):
     def test_split_rounds_empty(self):
         """Empty list returns no rounds."""
         from astrbot.core.agent.context.round_utils import split_into_rounds
+
         rounds = split_into_rounds([])
         assert len(rounds) == 0

tests/unit/test_astr_main_agent.py

@@ -985,6 +985,39 @@ async def test_build_main_agent_basic(
         assert result is not None
         assert isinstance(result, module.MainAgentBuildResult)
 
+    @pytest.mark.asyncio
+    async def test_build_main_agent_passes_max_context_length_to_runner(
+        self, mock_event, mock_context, mock_provider
+    ):
+        module = ama
+        mock_context.get_provider_by_id.return_value = None
+        mock_context.get_using_provider.return_value = mock_provider
+        mock_context.get_config.return_value = {}
+
+        conv_mgr = mock_context.conversation_manager
+        _setup_conversation_for_build(conv_mgr)
+
+        with (
+            patch("astrbot.core.astr_main_agent.AgentRunner") as mock_runner_cls,
+            patch("astrbot.core.astr_main_agent.AstrAgentContext"),
+        ):
+            mock_runner = MagicMock()
+            mock_runner.reset = AsyncMock()
+            mock_runner_cls.return_value = mock_runner
+
+            result = await module.build_main_agent(
+                event=mock_event,
+                plugin_context=mock_context,
+                config=module.MainAgentBuildConfig(
+                    tool_call_timeout=60,
+                    max_context_length=7,
+                ),
+            )
+
+        assert result is not None
+        mock_runner.reset.assert_awaited_once()
+        assert mock_runner.reset.await_args.kwargs["enforce_max_turns"] == 7
+
     @pytest.mark.asyncio
     async def test_build_main_agent_no_provider(self, mock_event, mock_context):
         """Test building main agent when no provider is available."""