fix(openai): apply empty-assistant filter to streaming path

astrbot/core/provider/sources/openai_source.py

@@ -519,6 +519,42 @@ async def get_models(self):
         except NotFoundError as e:
             raise Exception(f"获取模型列表失败：{e}")
 
+    @staticmethod
+    def _sanitize_assistant_messages(payloads: dict) -> None:
+        """在请求发送前过滤/规范化空的 assistant 消息。
+
+        严格 API（Moonshot、DeepSeek Reasoner 等）会在 assistant 消息同时缺少
+        ``content`` 和 ``tool_calls`` 时返回 400。把 ``""`` / ``None`` / ``[]``
+        都视作空内容：无 tool_calls 时整条过滤掉；有 tool_calls 时将 content
+        设为 ``None`` 以符合 OpenAI 规范。就地修改 ``payloads["messages"]``。
+        """
+        messages = payloads.get("messages")
+        if not isinstance(messages, list):
+            return
+
+        def _is_empty(content: Any) -> bool:
+            return content is None or content == "" or content == []
+
+        cleaned: list[Any] = []
+        for idx, msg in enumerate(messages):
+            if not isinstance(msg, dict) or msg.get("role") != "assistant":
+                cleaned.append(msg)
+                continue
+
+            content = msg.get("content")
+            tool_calls = msg.get("tool_calls")
+
+            if _is_empty(content) and not tool_calls:
+                logger.warning(f"过滤第 {idx} 条空 assistant 消息 (无工具调用)")
+                continue
+
+            if _is_empty(content) and tool_calls:
+                msg["content"] = None
+
+            cleaned.append(msg)
+
+        payloads["messages"] = cleaned
+
     async def _query(self, payloads: dict, tools: ToolSet | None) -> LLMResponse:
         if tools:
             model = payloads.get("model", "").lower()
@@ -548,26 +584,7 @@ async def _query(self, payloads: dict, tools: ToolSet | None) -> LLMResponse:
 
         model = payloads.get("model", "").lower()
 
-        if "messages" in payloads and isinstance(payloads["messages"], list):
-            cleaned_messages = []
-            for idx, msg in enumerate(payloads["messages"]):
-                # 过滤空的 assistant 消息，防止严格 API（如 Moonshot）返回 400 错误
-                if msg.get("role") == "assistant":
-                    content = msg.get("content")
-                    tool_calls = msg.get("tool_calls")
-
-                    # 情况1: 空/null content 且无 tool_calls -> 过滤掉
-                    if not tool_calls and (content == "" or content is None):
-                        logger.warning(f"过滤第 {idx} 条空 assistant 消息 (无工具调用)")
-                        continue
-
-                    # 情况2: 空 content 但有 tool_calls -> 设为 None (符合 OpenAI 规范)
-                    if content == "" and tool_calls:
-                        msg["content"] = None
-
-                cleaned_messages.append(msg)
-
-            payloads["messages"] = cleaned_messages
+        self._sanitize_assistant_messages(payloads)
 
         completion = await self.client.chat.completions.create(
             **payloads,
@@ -619,6 +636,8 @@ async def _query_stream(
             del payloads[key]
         self._apply_provider_specific_extra_body_overrides(extra_body)
 
+        self._sanitize_assistant_messages(payloads)
+
         stream = await self.client.chat.completions.create(
             **payloads,
             stream=True,

tests/test_openai_source.py

@@ -1618,3 +1618,109 @@ async def fake_create(**kwargs):
         assert messages[2] == {"role": "user", "content": "hello"}
     finally:
         await provider.terminate()
+
+
+@pytest.mark.asyncio
+async def test_query_stream_filters_empty_assistant_message(monkeypatch):
+    """Regression for #7721: streaming path must also filter empty assistant messages.
+
+    Previously only ``_query`` sanitized the payload; ``_query_stream`` forwarded
+    the raw history and strict providers (e.g. DeepSeek Reasoner) returned 400 on
+    the next turn after a tool call whose assistant entry had reasoning only.
+    """
+    provider = _make_provider()
+    try:
+        captured_kwargs = {}
+
+        async def fake_stream():
+            yield ChatCompletionChunk.model_validate(
+                {
+                    "id": "chatcmpl-stream",
+                    "object": "chat.completion.chunk",
+                    "created": 0,
+                    "model": "deepseek-reasoner",
+                    "choices": [
+                        {
+                            "index": 0,
+                            "delta": {"role": "assistant", "content": "ok"},
+                            "finish_reason": "stop",
+                        }
+                    ],
+                }
+            )
+
+        async def fake_create(**kwargs):
+            captured_kwargs.update(kwargs)
+            return fake_stream()
+
+        monkeypatch.setattr(provider.client.chat.completions, "create", fake_create)
+
+        payloads = {
+            "model": "deepseek-reasoner",
+            "messages": [
+                {"role": "user", "content": "hello"},
+                {"role": "assistant", "content": ""},  # should be filtered
+                {"role": "user", "content": "world"},
+            ],
+        }
+
+        async for _ in provider._query_stream(payloads=payloads, tools=None):
+            pass
+
+        messages = captured_kwargs["messages"]
+        assert len(messages) == 2
+        assert messages[0] == {"role": "user", "content": "hello"}
+        assert messages[1] == {"role": "user", "content": "world"}
+    finally:
+        await provider.terminate()
+
+
+@pytest.mark.asyncio
+async def test_query_filters_empty_list_content_assistant_message(monkeypatch):
+    """Empty-list content (``content == []``) must also be filtered, not just ``""`` / ``None``."""
+    provider = _make_provider()
+    try:
+        captured_kwargs = {}
+
+        async def fake_create(**kwargs):
+            captured_kwargs.update(kwargs)
+            return ChatCompletion.model_validate(
+                {
+                    "id": "chatcmpl-test",
+                    "object": "chat.completion",
+                    "created": 0,
+                    "model": "gpt-4o-mini",
+                    "choices": [
+                        {
+                            "index": 0,
+                            "message": {"role": "assistant", "content": "ok"},
+                            "finish_reason": "stop",
+                        }
+                    ],
+                    "usage": {
+                        "prompt_tokens": 1,
+                        "completion_tokens": 1,
+                        "total_tokens": 2,
+                    },
+                }
+            )
+
+        monkeypatch.setattr(provider.client.chat.completions, "create", fake_create)
+
+        payloads = {
+            "model": "gpt-4o-mini",
+            "messages": [
+                {"role": "user", "content": "hi"},
+                {"role": "assistant", "content": []},  # should be filtered
+                {"role": "user", "content": "again"},
+            ],
+        }
+
+        await provider._query(payloads=payloads, tools=None)
+
+        messages = captured_kwargs["messages"]
+        assert len(messages) == 2
+        assert messages[0] == {"role": "user", "content": "hi"}
+        assert messages[1] == {"role": "user", "content": "again"}
+    finally:
+        await provider.terminate()