fix: ignore malformed tool call names

astrbot/core/agent/runners/tool_loop_agent_runner.py

@@ -473,9 +473,18 @@ async def _iter_llm_responses(
         if self.streaming:
             stream = self.provider.text_chat_stream(**payload)
             async for resp in stream:  # type: ignore
+                if not resp.is_chunk:
+                    self._sanitize_tool_call_entries(resp)
                 yield resp
         else:
-            yield await self.provider.text_chat(**payload)
+            yield await self._text_chat_with_sanitized_tool_calls(**payload)
+
+    async def _text_chat_with_sanitized_tool_calls(
+        self, **kwargs: T.Any
+    ) -> LLMResponse:
+        resp = await self.provider.text_chat(**kwargs)
+        self._sanitize_tool_call_entries(resp)
+        return resp
 
     async def _iter_llm_responses_with_fallback(
         self,
@@ -1269,6 +1278,102 @@ def _has_meaningful_assistant_reply(llm_resp: LLMResponse) -> bool:
         text = (llm_resp.completion_text or "").strip()
         return bool(text)
 
+    @staticmethod
+    def _sanitize_tool_call_entries(llm_resp: LLMResponse) -> None:
+        """Drop malformed tool calls and keep names/args/ids aligned."""
+        raw_tool_names = llm_resp.tools_call_name
+        if not raw_tool_names:
+            return
+
+        if not isinstance(raw_tool_names, list):
+            logger.warning(
+                "Dropped malformed tool calls because tool names are invalid."
+            )
+            llm_resp.tools_call_name = []
+            llm_resp.tools_call_args = []
+            llm_resp.tools_call_ids = []
+            llm_resp.tools_call_extra_content = {}
+            return
+
+        tool_names: list[str] = []
+        tool_args: list[dict[str, T.Any]] = []
+        tool_ids: list[str] = []
+        tool_extra_content: dict[str, dict[str, T.Any]] = {}
+        dropped_count = 0
+        changed = False
+        raw_tool_args = llm_resp.tools_call_args
+        raw_tool_ids = llm_resp.tools_call_ids
+        tool_args_source = raw_tool_args if isinstance(raw_tool_args, list) else []
+        tool_ids_source = raw_tool_ids if isinstance(raw_tool_ids, list) else []
+        if tool_args_source is not raw_tool_args:
+            changed = True
+        if tool_ids_source is not raw_tool_ids:
+            changed = True
+        raw_extra_content = llm_resp.tools_call_extra_content
+        extra_content_map = (
+            raw_extra_content if isinstance(raw_extra_content, dict) else {}
+        )
+        if extra_content_map is not raw_extra_content:
+            changed = True
+
+        for idx, tool_name in enumerate(raw_tool_names):
+            if not isinstance(tool_name, str) or not tool_name:
+                dropped_count += 1
+                changed = True
+                continue
+
+            tool_names.append(tool_name)
+
+            if idx < len(tool_args_source):
+                raw_args = tool_args_source[idx]
+                if isinstance(raw_args, dict):
+                    tool_args.append(raw_args)
+                else:
+                    tool_args.append({})
+                    changed = True
+            else:
+                tool_args.append({})
+                changed = True
+
+            if idx < len(tool_ids_source):
+                raw_tool_id = tool_ids_source[idx]
+                tool_id = (
+                    raw_tool_id
+                    if isinstance(raw_tool_id, str) and raw_tool_id
+                    else f"call_{uuid.uuid4().hex[:8]}"
+                )
+                if tool_id != raw_tool_id:
+                    changed = True
+            else:
+                tool_id = f"call_{uuid.uuid4().hex[:8]}"
+                changed = True
+            tool_ids.append(tool_id)
+
+            extra_content = extra_content_map.get(tool_id)
+            if isinstance(extra_content, dict) and extra_content:
+                tool_extra_content[tool_id] = extra_content
+
+        if len(tool_names) != len(raw_tool_names):
+            changed = True
+        if len(tool_args) != len(tool_args_source):
+            changed = True
+        if len(tool_ids) != len(tool_ids_source):
+            changed = True
+        if tool_extra_content != extra_content_map:
+            changed = True
+
+        if dropped_count:
+            logger.warning(
+                f"Dropped {dropped_count} malformed tool call(s) with "
+                "non-string or empty names."
+            )
+
+        if changed:
+            llm_resp.tools_call_name = tool_names
+            llm_resp.tools_call_args = tool_args
+            llm_resp.tools_call_ids = tool_ids
+            llm_resp.tools_call_extra_content = tool_extra_content
+
     def _build_tool_subset(self, tool_set: ToolSet, tool_names: list[str]) -> ToolSet:
         """Build a subset of tools from the given tool set based on tool names."""
         subset = ToolSet()
@@ -1300,7 +1405,7 @@ async def _resolve_tool_exec(
             )
             if param_subset.tools and tool_names:
                 contexts = self._build_tool_requery_context(tool_names)
-                requery_resp = await self.provider.text_chat(
+                requery_resp = await self._text_chat_with_sanitized_tool_calls(
                     contexts=self._sanitize_contexts_for_provider(contexts),
                     func_tool=param_subset,
                     model=self.req.model,
@@ -1327,7 +1432,7 @@ async def _resolve_tool_exec(
                         tool_names,
                         extra_instruction=self.SKILLS_LIKE_REQUERY_REPAIR_INSTRUCTION,
                     )
-                    repair_resp = await self.provider.text_chat(
+                    repair_resp = await self._text_chat_with_sanitized_tool_calls(
                         contexts=self._sanitize_contexts_for_provider(repair_contexts),
                         func_tool=param_subset,
                         model=self.req.model,

tests/test_tool_loop_agent_runner.py

@@ -1364,6 +1364,177 @@ async def text_chat(self, **kwargs) -> LLMResponse:
     assert parts[0].text == "<image_caption>一张猫的照片</image_caption>"
 
 
+@pytest.mark.asyncio
+async def test_skills_like_requery_drops_malformed_tool_names():
+    captured_contexts = []
+
+    class MalformedToolNameProvider(MockProvider):
+        async def text_chat(self, **kwargs) -> LLMResponse:
+            self.call_count += 1
+            if self.call_count == 1:
+                return LLMResponse(
+                    role="assistant",
+                    completion_text="选择工具",
+                    tools_call_name=["test_tool", None],
+                    tools_call_args=[{"query": "test"}, {"query": "bad"}],
+                    tools_call_ids=["call_1", "call_bad"],
+                    usage=TokenUsage(input_other=10, output=5),
+                )
+            if self.call_count == 2:
+                captured_contexts.extend(kwargs.get("contexts") or [])
+                return LLMResponse(
+                    role="assistant",
+                    completion_text="调用工具",
+                    tools_call_name=["test_tool"],
+                    tools_call_args=[{"query": "actual"}],
+                    tools_call_ids=["call_2"],
+                    usage=TokenUsage(input_other=10, output=5),
+                )
+            return LLMResponse(
+                role="assistant",
+                completion_text="最终回复",
+                usage=TokenUsage(input_other=10, output=5),
+            )
+
+    provider = MalformedToolNameProvider()
+    tool = FunctionTool(
+        name="test_tool",
+        description="测试",
+        parameters={"type": "object", "properties": {"query": {"type": "string"}}},
+        handler=AsyncMock(),
+    )
+    req = ProviderRequest(
+        prompt="调用工具",
+        func_tool=ToolSet(tools=[tool]),
+        contexts=[],
+    )
+    runner = ToolLoopAgentRunner()
+
+    await runner.reset(
+        provider=provider,
+        request=req,
+        run_context=ContextWrapper(context=None),
+        tool_executor=cast(Any, MockToolExecutor()),
+        agent_hooks=MockHooks(),
+        tool_schema_mode="skills_like",
+    )
+
+    async for _ in runner.step():
+        pass
+
+    assert provider.call_count == 2
+    assert captured_contexts[0]["content"].startswith(
+        "You have decided to call tool(s): test_tool."
+    )
+    tool_messages = [msg for msg in runner.run_context.messages if msg.role == "tool"]
+    assert len(tool_messages) == 1
+    assert tool_messages[0].tool_call_id == "call_2"
+
+
+@pytest.mark.asyncio
+async def test_tool_loop_drops_malformed_tool_names_before_execution():
+    class MalformedToolNameProvider(MockProvider):
+        async def text_chat(self, **kwargs) -> LLMResponse:
+            self.call_count += 1
+            return LLMResponse(
+                role="assistant",
+                completion_text="调用工具",
+                tools_call_name=["test_tool", None],
+                tools_call_args=[{"query": "actual"}, {"query": "bad"}],
+                tools_call_ids=["call_1", "call_bad"],
+                usage=TokenUsage(input_other=10, output=5),
+            )
+
+    provider = MalformedToolNameProvider()
+    tool = FunctionTool(
+        name="test_tool",
+        description="测试",
+        parameters={"type": "object", "properties": {"query": {"type": "string"}}},
+        handler=AsyncMock(),
+    )
+    req = ProviderRequest(
+        prompt="调用工具",
+        func_tool=ToolSet(tools=[tool]),
+        contexts=[],
+    )
+    runner = ToolLoopAgentRunner()
+
+    await runner.reset(
+        provider=provider,
+        request=req,
+        run_context=ContextWrapper(context=None),
+        tool_executor=cast(Any, MockToolExecutor()),
+        agent_hooks=MockHooks(),
+    )
+
+    async for _ in runner.step():
+        pass
+
+    tool_messages = [msg for msg in runner.run_context.messages if msg.role == "tool"]
+    assert len(tool_messages) == 1
+    assert tool_messages[0].tool_call_id == "call_1"
+
+
+@pytest.mark.asyncio
+async def test_tool_loop_sanitizes_malformed_tool_ids_args_and_extra_content():
+    class MalformedToolFieldsProvider(MockProvider):
+        async def text_chat(self, **kwargs) -> LLMResponse:
+            self.call_count += 1
+            response = LLMResponse(
+                role="assistant",
+                completion_text="调用工具",
+                tools_call_name=["test_tool", "test_tool"],
+                tools_call_args=[{"query": "actual"}, "bad-args"],
+                tools_call_ids=["call_1", None],
+                usage=TokenUsage(input_other=10, output=5),
+            )
+            response.tools_call_extra_content = None
+            return response
+
+    class CapturingHooks(MockHooks):
+        def __init__(self):
+            super().__init__()
+            self.tool_args_list = []
+
+        async def on_tool_start(self, run_context, tool, tool_args):
+            await super().on_tool_start(run_context, tool, tool_args)
+            self.tool_args_list.append(tool_args)
+
+    provider = MalformedToolFieldsProvider()
+    hooks = CapturingHooks()
+    tool = FunctionTool(
+        name="test_tool",
+        description="测试",
+        parameters={"type": "object", "properties": {"query": {"type": "string"}}},
+        handler=AsyncMock(),
+    )
+    req = ProviderRequest(
+        prompt="调用工具",
+        func_tool=ToolSet(tools=[tool]),
+        contexts=[],
+    )
+    runner = ToolLoopAgentRunner()
+
+    await runner.reset(
+        provider=provider,
+        request=req,
+        run_context=ContextWrapper(context=None),
+        tool_executor=cast(Any, MockToolExecutor()),
+        agent_hooks=hooks,
+    )
+
+    async for _ in runner.step():
+        pass
+
+    tool_messages = [msg for msg in runner.run_context.messages if msg.role == "tool"]
+    assert len(tool_messages) == 2
+    tool_call_ids = [msg.tool_call_id for msg in tool_messages]
+    assert tool_call_ids[0] == "call_1"
+    assert tool_call_ids[1] is not None
+    assert tool_call_ids[1].startswith("call_")
+    assert hooks.tool_args_list == [{"query": "actual"}, {}]
+
+
 @pytest.mark.asyncio
 async def test_follow_up_accepted_when_active_and_not_stopping(
     runner, mock_provider, provider_request, mock_tool_executor, mock_hooks