Merge remote-tracking branch 'origin/main'

nanobot/agent/loop.py

@@ -309,7 +309,9 @@ class AgentLoop:
 
         async def _do_restart():
             await asyncio.sleep(1)
-            os.execv(sys.executable, [sys.executable] + sys.argv)
+            # Use -m nanobot instead of sys.argv[0] for Windows compatibility
+            # (sys.argv[0] may be just "nanobot" without full path on Windows)
+            os.execv(sys.executable, [sys.executable, "-m", "nanobot"] + sys.argv[1:])
 
         asyncio.create_task(_do_restart())
 

nanobot/agent/memory.py

@@ -57,6 +57,20 @@ def _normalize_save_memory_args(args: Any) -> dict[str, Any] | None:
         return args[0] if args and isinstance(args[0], dict) else None
     return args if isinstance(args, dict) else None
 
+_TOOL_CHOICE_ERROR_MARKERS = (
+    "tool_choice",
+    "toolchoice",
+    "does not support",
+    'should be ["none", "auto"]',
+)
+
+
+def _is_tool_choice_unsupported(content: str | None) -> bool:
+    """Detect provider errors caused by forced tool_choice being unsupported."""
+    text = (content or "").lower()
+    return any(m in text for m in _TOOL_CHOICE_ERROR_MARKERS)
+
+
 class MemoryStore:
     """Two-layer memory: MEMORY.md (long-term facts) + HISTORY.md (grep-searchable log)."""
 
@@ -118,15 +132,33 @@ class MemoryStore:
         ]
 
         try:
+            forced = {"type": "function", "function": {"name": "save_memory"}}
             response = await provider.chat_with_retry(
                 messages=chat_messages,
                 tools=_SAVE_MEMORY_TOOL,
                 model=model,
-                tool_choice={"type": "function", "function": {"name": "save_memory"}},
+                tool_choice=forced,
+            )
+
+            if response.finish_reason == "error" and _is_tool_choice_unsupported(
+                response.content
+            ):
+                logger.warning("Forced tool_choice unsupported, retrying with auto")
+                response = await provider.chat_with_retry(
+                    messages=chat_messages,
+                    tools=_SAVE_MEMORY_TOOL,
+                    model=model,
+                    tool_choice="auto",
                 )
 
             if not response.has_tool_calls:
-                logger.warning("Memory consolidation: LLM did not call save_memory, skipping")
+                logger.warning(
+                    "Memory consolidation: LLM did not call save_memory "
+                    "(finish_reason={}, content_len={}, content_preview={})",
+                    response.finish_reason,
+                    len(response.content or ""),
+                    (response.content or "")[:200],
+                )
                 return False
 
             args = _normalize_save_memory_args(response.tool_calls[0].arguments)

nanobot/channels/qq.py

@@ -114,16 +114,16 @@ class QQChannel(BaseChannel):
             if msg_type == "group":
                 await self._client.api.post_group_message(
                     group_openid=msg.chat_id,
-                    msg_type=2,
+                    msg_type=0,
-                    markdown={"content": msg.content},
+                    content=msg.content,
                     msg_id=msg_id,
                     msg_seq=self._msg_seq,
                 )
             else:
                 await self._client.api.post_c2c_message(
                     openid=msg.chat_id,
-                    msg_type=2,
+                    msg_type=0,
-                    markdown={"content": msg.content},
+                    content=msg.content,
                     msg_id=msg_id,
                     msg_seq=self._msg_seq,
                 )

pyproject.toml

@@ -75,13 +75,6 @@ build-backend = "hatchling.build"
 [tool.hatch.metadata]
 allow-direct-references = true
 
-[tool.hatch.build.targets.wheel]
-packages = ["nanobot"]
-
-[tool.hatch.build.targets.wheel.sources]
-"nanobot" = "nanobot"
-
-# Include non-Python files in skills and templates
 [tool.hatch.build]
 include = [
     "nanobot/**/*.py",
@@ -90,6 +83,15 @@ include = [
     "nanobot/skills/**/*.sh",
 ]
 
+[tool.hatch.build.targets.wheel]
+packages = ["nanobot"]
+
+[tool.hatch.build.targets.wheel.sources]
+"nanobot" = "nanobot"
+
+[tool.hatch.build.targets.wheel.force-include]
+"bridge" = "nanobot/bridge"
+
 [tool.hatch.build.targets.sdist]
 include = [
     "nanobot/",
@@ -98,9 +100,6 @@ include = [
     "LICENSE",
 ]
 
-[tool.hatch.build.targets.wheel.force-include]
-"bridge" = "nanobot/bridge"
-
 [tool.ruff]
 line-length = 100
 target-version = "py311"

tests/test_memory_consolidation_types.py

@@ -288,3 +288,60 @@ class TestMemoryConsolidationTypeHandling:
         assert "temperature" not in kwargs
         assert "max_tokens" not in kwargs
         assert "reasoning_effort" not in kwargs
+
+    @pytest.mark.asyncio
+    async def test_tool_choice_fallback_on_unsupported_error(self, tmp_path: Path) -> None:
+        """Forced tool_choice rejected by provider -> retry with auto and succeed."""
+        store = MemoryStore(tmp_path)
+        error_resp = LLMResponse(
+            content="Error calling LLM: litellm.BadRequestError: "
+            "The tool_choice parameter does not support being set to required or object",
+            finish_reason="error",
+            tool_calls=[],
+        )
+        ok_resp = _make_tool_response(
+            history_entry="[2026-01-01] Fallback worked.",
+            memory_update="# Memory\nFallback OK.",
+        )
+
+        call_log: list[dict] = []
+
+        async def _tracking_chat(**kwargs):
+            call_log.append(kwargs)
+            return error_resp if len(call_log) == 1 else ok_resp
+
+        provider = AsyncMock()
+        provider.chat_with_retry = AsyncMock(side_effect=_tracking_chat)
+        messages = _make_messages(message_count=60)
+
+        result = await store.consolidate(messages, provider, "test-model")
+
+        assert result is True
+        assert len(call_log) == 2
+        assert isinstance(call_log[0]["tool_choice"], dict)
+        assert call_log[1]["tool_choice"] == "auto"
+        assert "Fallback worked." in store.history_file.read_text()
+
+    @pytest.mark.asyncio
+    async def test_tool_choice_fallback_auto_no_tool_call(self, tmp_path: Path) -> None:
+        """Forced rejected, auto retry also produces no tool call -> return False."""
+        store = MemoryStore(tmp_path)
+        error_resp = LLMResponse(
+            content="Error: tool_choice must be none or auto",
+            finish_reason="error",
+            tool_calls=[],
+        )
+        no_tool_resp = LLMResponse(
+            content="Here is a summary.",
+            finish_reason="stop",
+            tool_calls=[],
+        )
+
+        provider = AsyncMock()
+        provider.chat_with_retry = AsyncMock(side_effect=[error_resp, no_tool_resp])
+        messages = _make_messages(message_count=60)
+
+        result = await store.consolidate(messages, provider, "test-model")
+
+        assert result is False
+        assert not store.history_file.exists()

tests/test_qq_channel.py

@@ -44,7 +44,7 @@ async def test_on_group_message_routes_to_group_chat_id() -> None:
 
 
 @pytest.mark.asyncio
-async def test_send_group_message_uses_group_api_with_msg_seq() -> None:
+async def test_send_group_message_uses_plain_text_group_api_with_msg_seq() -> None:
     channel = QQChannel(QQConfig(app_id="app", secret="secret", allow_from=["*"]), MessageBus())
     channel._client = _FakeClient()
     channel._chat_type_cache["group123"] = "group"
@@ -60,7 +60,37 @@ async def test_send_group_message_uses_group_api_with_msg_seq() -> None:
 
     assert len(channel._client.api.group_calls) == 1
     call = channel._client.api.group_calls[0]
-    assert call["group_openid"] == "group123"
+    assert call == {
-    assert call["msg_id"] == "msg1"
+        "group_openid": "group123",
-    assert call["msg_seq"] == 2
+        "msg_type": 0,
+        "content": "hello",
+        "msg_id": "msg1",
+        "msg_seq": 2,
+    }
     assert not channel._client.api.c2c_calls
+
+
+@pytest.mark.asyncio
+async def test_send_c2c_message_uses_plain_text_c2c_api_with_msg_seq() -> None:
+    channel = QQChannel(QQConfig(app_id="app", secret="secret", allow_from=["*"]), MessageBus())
+    channel._client = _FakeClient()
+
+    await channel.send(
+        OutboundMessage(
+            channel="qq",
+            chat_id="user123",
+            content="hello",
+            metadata={"message_id": "msg1"},
+        )
+    )
+
+    assert len(channel._client.api.c2c_calls) == 1
+    call = channel._client.api.c2c_calls[0]
+    assert call == {
+        "openid": "user123",
+        "msg_type": 0,
+        "content": "hello",
+        "msg_id": "msg1",
+        "msg_seq": 2,
+    }
+    assert not channel._client.api.group_calls