Merge branch 'main' into pr-1900

README.md

@@ -64,7 +64,7 @@
 
 ## Key Features of nanobot:
 
-🪶 **Ultra-Lightweight**: Just ~4,000 lines of core agent code — 99% smaller than Clawdbot.
+🪶 **Ultra-Lightweight**: A super lightweight implementation of OpenClaw — 99% smaller, significantly faster.
 
 🔬 **Research-Ready**: Clean, readable code that's easy to understand, modify, and extend for research.
 
@@ -502,7 +502,8 @@ Uses **WebSocket** long connection — no public IP required.
       "appSecret": "xxx",
       "encryptKey": "",
       "verificationToken": "",
-      "allowFrom": ["ou_YOUR_OPEN_ID"]
+      "allowFrom": ["ou_YOUR_OPEN_ID"],
+      "groupPolicy": "mention"
     }
   }
 }
@@ -510,6 +511,7 @@ Uses **WebSocket** long connection — no public IP required.
 
 > `encryptKey` and `verificationToken` are optional for Long Connection mode.
 > `allowFrom`: Add your open_id (find it in nanobot logs when you message the bot). Use `["*"]` to allow all users.
+> `groupPolicy`: `"mention"` (default — respond only when @mentioned), `"open"` (respond to all group messages). Private chats always respond.
 
 **3. Run**
 

nanobot/agent/loop.py

@@ -4,7 +4,9 @@ from __future__ import annotations
 
 import asyncio
 import json
+import os
 import re
+import sys
 from contextlib import AsyncExitStack
 from pathlib import Path
 from typing import TYPE_CHECKING, Any, Awaitable, Callable
@@ -43,7 +45,7 @@ class AgentLoop:
     5. Sends responses back
     """
 
-    _TOOL_RESULT_MAX_CHARS = 500
+    _TOOL_RESULT_MAX_CHARS = 16_000
 
     def __init__(
         self,
@@ -256,8 +258,11 @@ class AgentLoop:
             except asyncio.TimeoutError:
                 continue
 
-            if msg.content.strip().lower() == "/stop":
+            cmd = msg.content.strip().lower()
+            if cmd == "/stop":
                 await self._handle_stop(msg)
+            elif cmd == "/restart":
+                await self._handle_restart(msg)
             else:
                 task = asyncio.create_task(self._dispatch(msg))
                 self._active_tasks.setdefault(msg.session_key, []).append(task)
@@ -274,11 +279,23 @@ class AgentLoop:
                 pass
         sub_cancelled = await self.subagents.cancel_by_session(msg.session_key)
         total = cancelled + sub_cancelled
-        content = f"⏹ Stopped {total} task(s)." if total else "No active task to stop."
+        content = f"Stopped {total} task(s)." if total else "No active task to stop."
         await self.bus.publish_outbound(OutboundMessage(
             channel=msg.channel, chat_id=msg.chat_id, content=content,
         ))
 
+    async def _handle_restart(self, msg: InboundMessage) -> None:
+        """Restart the process in-place via os.execv."""
+        await self.bus.publish_outbound(OutboundMessage(
+            channel=msg.channel, chat_id=msg.chat_id, content="Restarting...",
+        ))
+
+        async def _do_restart():
+            await asyncio.sleep(1)
+            os.execv(sys.executable, [sys.executable] + sys.argv)
+
+        asyncio.create_task(_do_restart())
+
     async def _dispatch(self, msg: InboundMessage) -> None:
         """Process a message under the global lock."""
         async with self._processing_lock:
@@ -373,9 +390,16 @@ class AgentLoop:
             return OutboundMessage(channel=msg.channel, chat_id=msg.chat_id,
                                   content="New session started.")
         if cmd == "/help":
-            return OutboundMessage(channel=msg.channel, chat_id=msg.chat_id,
+            lines = [
-                                  content="🐈 nanobot commands:\n/new — Start a new conversation\n/stop — Stop the current task\n/help — Show available commands")
+                "🐈 nanobot commands:",
-
+                "/new — Start a new conversation",
+                "/stop — Stop the current task",
+                "/restart — Restart the bot",
+                "/help — Show available commands",
+            ]
+            return OutboundMessage(
+                channel=msg.channel, chat_id=msg.chat_id, content="\n".join(lines),
+            )
         await self.memory_consolidator.maybe_consolidate_by_tokens(session)
 
         self._set_tool_context(msg.channel, msg.chat_id, msg.metadata.get("message_id"))

nanobot/agent/memory.py

@@ -120,6 +120,7 @@ class MemoryStore:
                 ],
                 tools=_SAVE_MEMORY_TOOL,
                 model=model,
+                tool_choice="required",
             )
 
             if not response.has_tool_calls:

nanobot/channels/feishu.py

@@ -352,6 +352,27 @@ class FeishuChannel(BaseChannel):
         self._running = False
         logger.info("Feishu bot stopped")
 
+    def _is_bot_mentioned(self, message: Any) -> bool:
+        """Check if the bot is @mentioned in the message."""
+        raw_content = message.content or ""
+        if "@_all" in raw_content:
+            return True
+
+        for mention in getattr(message, "mentions", None) or []:
+            mid = getattr(mention, "id", None)
+            if not mid:
+                continue
+            # Bot mentions have no user_id (None or "") but a valid open_id
+            if not getattr(mid, "user_id", None) and (getattr(mid, "open_id", None) or "").startswith("ou_"):
+                return True
+        return False
+
+    def _is_group_message_for_bot(self, message: Any) -> bool:
+        """Allow group messages when policy is open or bot is @mentioned."""
+        if self.config.group_policy == "open":
+            return True
+        return self._is_bot_mentioned(message)
+
     def _add_reaction_sync(self, message_id: str, emoji_type: str) -> None:
         """Sync helper for adding reaction (runs in thread pool)."""
         from lark_oapi.api.im.v1 import CreateMessageReactionRequest, CreateMessageReactionRequestBody, Emoji
@@ -893,6 +914,10 @@ class FeishuChannel(BaseChannel):
             chat_type = message.chat_type
             msg_type = message.message_type
 
+            if chat_type == "group" and not self._is_group_message_for_bot(message):
+                logger.debug("Feishu: skipping group message (not mentioned)")
+                return
+
             # Add reaction
             await self._add_reaction(message_id, self.config.react_emoji)
 

nanobot/channels/telegram.py

@@ -164,6 +164,7 @@ class TelegramChannel(BaseChannel):
         BotCommand("new", "Start a new conversation"),
         BotCommand("stop", "Stop the current task"),
         BotCommand("help", "Show available commands"),
+        BotCommand("restart", "Restart the bot"),
     ]
 
     def __init__(self, config: TelegramConfig, bus: MessageBus):
@@ -221,6 +222,7 @@ class TelegramChannel(BaseChannel):
         self._app.add_handler(CommandHandler("start", self._on_start))
         self._app.add_handler(CommandHandler("new", self._forward_command))
         self._app.add_handler(CommandHandler("stop", self._forward_command))
+        self._app.add_handler(CommandHandler("restart", self._forward_command))
         self._app.add_handler(CommandHandler("help", self._on_help))
 
         # Add message handler for text, photos, voice, documents

nanobot/config/schema.py

@@ -48,6 +48,7 @@ class FeishuConfig(Base):
     react_emoji: str = (
         "THUMBSUP"  # Emoji type for message reactions (e.g. THUMBSUP, OK, DONE, SMILE)
     )
+    group_policy: Literal["open", "mention"] = "mention"  # "mention" responds when @mentioned, "open" responds to all
 
 
 class DingTalkConfig(Base):

nanobot/providers/azure_openai_provider.py

@@ -88,6 +88,7 @@ class AzureOpenAIProvider(LLMProvider):
         max_tokens: int = 4096,
         temperature: float = 0.7,
         reasoning_effort: str | None = None,
+        tool_choice: str | dict[str, Any] | None = None,
     ) -> dict[str, Any]:
         """Prepare the request payload with Azure OpenAI 2024-10-21 compliance."""
         payload: dict[str, Any] = {
@@ -106,7 +107,7 @@ class AzureOpenAIProvider(LLMProvider):
 
         if tools:
             payload["tools"] = tools
-            payload["tool_choice"] = "auto"
+            payload["tool_choice"] = tool_choice or "auto"
 
         return payload
 
@@ -118,6 +119,7 @@ class AzureOpenAIProvider(LLMProvider):
         max_tokens: int = 4096,
         temperature: float = 0.7,
         reasoning_effort: str | None = None,
+        tool_choice: str | dict[str, Any] | None = None,
     ) -> LLMResponse:
         """
         Send a chat completion request to Azure OpenAI.
@@ -137,7 +139,8 @@ class AzureOpenAIProvider(LLMProvider):
         url = self._build_chat_url(deployment_name)
         headers = self._build_headers()
         payload = self._prepare_request_payload(
-            deployment_name, messages, tools, max_tokens, temperature, reasoning_effort
+            deployment_name, messages, tools, max_tokens, temperature, reasoning_effort,
+            tool_choice=tool_choice,
         )
 
         try:

nanobot/providers/base.py

@@ -166,6 +166,7 @@ class LLMProvider(ABC):
         max_tokens: int = 4096,
         temperature: float = 0.7,
         reasoning_effort: str | None = None,
+        tool_choice: str | dict[str, Any] | None = None,
     ) -> LLMResponse:
         """
         Send a chat completion request.
@@ -176,6 +177,7 @@ class LLMProvider(ABC):
             model: Model identifier (provider-specific).
             max_tokens: Maximum tokens in response.
             temperature: Sampling temperature.
+            tool_choice: Tool selection strategy ("auto", "required", or specific tool dict).
         
         Returns:
             LLMResponse with content and/or tool calls.
@@ -195,6 +197,7 @@ class LLMProvider(ABC):
         max_tokens: object = _SENTINEL,
         temperature: object = _SENTINEL,
         reasoning_effort: object = _SENTINEL,
+        tool_choice: str | dict[str, Any] | None = None,
     ) -> LLMResponse:
         """Call chat() with retry on transient provider failures.
 
@@ -218,6 +221,7 @@ class LLMProvider(ABC):
                     max_tokens=max_tokens,
                     temperature=temperature,
                     reasoning_effort=reasoning_effort,
+                    tool_choice=tool_choice,
                 )
             except asyncio.CancelledError:
                 raise
@@ -250,6 +254,7 @@ class LLMProvider(ABC):
                 max_tokens=max_tokens,
                 temperature=temperature,
                 reasoning_effort=reasoning_effort,
+                tool_choice=tool_choice,
             )
         except asyncio.CancelledError:
             raise

nanobot/providers/custom_provider.py

@@ -25,7 +25,8 @@ class CustomProvider(LLMProvider):
 
     async def chat(self, messages: list[dict[str, Any]], tools: list[dict[str, Any]] | None = None,
                    model: str | None = None, max_tokens: int = 4096, temperature: float = 0.7,
-                   reasoning_effort: str | None = None) -> LLMResponse:
+                   reasoning_effort: str | None = None,
+                   tool_choice: str | dict[str, Any] | None = None) -> LLMResponse:
         kwargs: dict[str, Any] = {
             "model": model or self.default_model,
             "messages": self._sanitize_empty_content(messages),
@@ -35,7 +36,7 @@ class CustomProvider(LLMProvider):
         if reasoning_effort:
             kwargs["reasoning_effort"] = reasoning_effort
         if tools:
-            kwargs.update(tools=tools, tool_choice="auto")
+            kwargs.update(tools=tools, tool_choice=tool_choice or "auto")
         try:
             return self._parse(await self._client.chat.completions.create(**kwargs))
         except Exception as e:

nanobot/providers/litellm_provider.py

@@ -214,6 +214,7 @@ class LiteLLMProvider(LLMProvider):
         max_tokens: int = 4096,
         temperature: float = 0.7,
         reasoning_effort: str | None = None,
+        tool_choice: str | dict[str, Any] | None = None,
     ) -> LLMResponse:
         """
         Send a chat completion request via LiteLLM.
@@ -267,7 +268,7 @@ class LiteLLMProvider(LLMProvider):
         
         if tools:
             kwargs["tools"] = tools
-            kwargs["tool_choice"] = "auto"
+            kwargs["tool_choice"] = tool_choice or "auto"
 
         try:
             response = await acompletion(**kwargs)

nanobot/providers/openai_codex_provider.py

@@ -32,6 +32,7 @@ class OpenAICodexProvider(LLMProvider):
         max_tokens: int = 4096,
         temperature: float = 0.7,
         reasoning_effort: str | None = None,
+        tool_choice: str | dict[str, Any] | None = None,
     ) -> LLMResponse:
         model = model or self.default_model
         system_prompt, input_items = _convert_messages(messages)
@@ -48,7 +49,7 @@ class OpenAICodexProvider(LLMProvider):
             "text": {"verbosity": "medium"},
             "include": ["reasoning.encrypted_content"],
             "prompt_cache_key": _prompt_cache_key(messages),
-            "tool_choice": "auto",
+            "tool_choice": tool_choice or "auto",
             "parallel_tool_calls": True,
         }
 

pyproject.toml

@@ -49,7 +49,7 @@ dependencies = [
 
 [project.optional-dependencies]
 wecom = [
-    "wecom-aibot-sdk-python @ git+https://github.com/chengyongru/wecom_aibot_sdk.git@v0.1.2",
+    "wecom-aibot-sdk-python>=0.1.2",
 ]
 matrix = [
     "matrix-nio[e2e]>=0.25.2",

tests/test_loop_save_turn.py

@@ -5,7 +5,7 @@ from nanobot.session.manager import Session
 
 def _mk_loop() -> AgentLoop:
     loop = AgentLoop.__new__(AgentLoop)
-    loop._TOOL_RESULT_MAX_CHARS = 500
+    loop._TOOL_RESULT_MAX_CHARS = AgentLoop._TOOL_RESULT_MAX_CHARS
     return loop
 
 
@@ -39,3 +39,17 @@ def test_save_turn_keeps_image_placeholder_after_runtime_strip() -> None:
         skip=0,
     )
     assert session.messages[0]["content"] == [{"type": "text", "text": "[image]"}]
+
+
+def test_save_turn_keeps_tool_results_under_16k() -> None:
+    loop = _mk_loop()
+    session = Session(key="test:tool-result")
+    content = "x" * 12_000
+
+    loop._save_turn(
+        session,
+        [{"role": "tool", "tool_call_id": "call_1", "name": "read_file", "content": content}],
+        skip=0,
+    )
+
+    assert session.messages[0]["content"] == content

tests/test_restart_command.py

@@ -0,0 +1,76 @@
+"""Tests for /restart slash command."""
+
+from __future__ import annotations
+
+import asyncio
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+from nanobot.bus.events import InboundMessage
+
+
+def _make_loop():
+    """Create a minimal AgentLoop with mocked dependencies."""
+    from nanobot.agent.loop import AgentLoop
+    from nanobot.bus.queue import MessageBus
+
+    bus = MessageBus()
+    provider = MagicMock()
+    provider.get_default_model.return_value = "test-model"
+    workspace = MagicMock()
+    workspace.__truediv__ = MagicMock(return_value=MagicMock())
+
+    with patch("nanobot.agent.loop.ContextBuilder"), \
+         patch("nanobot.agent.loop.SessionManager"), \
+         patch("nanobot.agent.loop.SubagentManager"):
+        loop = AgentLoop(bus=bus, provider=provider, workspace=workspace)
+    return loop, bus
+
+
+class TestRestartCommand:
+
+    @pytest.mark.asyncio
+    async def test_restart_sends_message_and_calls_execv(self):
+        loop, bus = _make_loop()
+        msg = InboundMessage(channel="cli", sender_id="user", chat_id="direct", content="/restart")
+
+        with patch("nanobot.agent.loop.os.execv") as mock_execv:
+            await loop._handle_restart(msg)
+            out = await asyncio.wait_for(bus.consume_outbound(), timeout=1.0)
+            assert "Restarting" in out.content
+
+            await asyncio.sleep(1.5)
+            mock_execv.assert_called_once()
+
+    @pytest.mark.asyncio
+    async def test_restart_intercepted_in_run_loop(self):
+        """Verify /restart is handled at the run-loop level, not inside _dispatch."""
+        loop, bus = _make_loop()
+        msg = InboundMessage(channel="telegram", sender_id="u1", chat_id="c1", content="/restart")
+
+        with patch.object(loop, "_handle_restart") as mock_handle:
+            mock_handle.return_value = None
+            await bus.publish_inbound(msg)
+
+            loop._running = True
+            run_task = asyncio.create_task(loop.run())
+            await asyncio.sleep(0.1)
+            loop._running = False
+            run_task.cancel()
+            try:
+                await run_task
+            except asyncio.CancelledError:
+                pass
+
+            mock_handle.assert_called_once()
+
+    @pytest.mark.asyncio
+    async def test_help_includes_restart(self):
+        loop, bus = _make_loop()
+        msg = InboundMessage(channel="telegram", sender_id="u1", chat_id="c1", content="/help")
+
+        response = await loop._process_message(msg)
+
+        assert response is not None
+        assert "/restart" in response.content