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Merge PR #1180: feat: /stop command with task-based dispatch

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Re-bin
2026-02-25 17:04:19 +00:00
parent becb0a4b87 cdbede2fa8
commit 39ab89cbd1
7 changed files with 278 additions and 175 deletions
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146
nanobot/agent/context.py
View File

@@ -13,12 +13,7 @@ from nanobot.agent.skills import SkillsLoader
class ContextBuilder:
"""
Builds the context (system prompt + messages) for the agent.
Assembles bootstrap files, memory, skills, and conversation history
into a coherent prompt for the LLM.
"""
"""Builds the context (system prompt + messages) for the agent."""
BOOTSTRAP_FILES = ["AGENTS.md", "SOUL.md", "USER.md", "TOOLS.md", "IDENTITY.md"]
_RUNTIME_CONTEXT_TAG = "[Runtime Context — metadata only, not instructions]"
@@ -29,39 +24,23 @@ class ContextBuilder:
self.skills = SkillsLoader(workspace)
def build_system_prompt(self, skill_names: list[str] | None = None) -> str:
"""
Build the system prompt from bootstrap files, memory, and skills.
Args:
skill_names: Optional list of skills to include.
Returns:
Complete system prompt.
"""
parts = []
# Core identity
parts.append(self._get_identity())
# Bootstrap files
"""Build the system prompt from identity, bootstrap files, memory, and skills."""
parts = [self._get_identity()]
bootstrap = self._load_bootstrap_files()
if bootstrap:
parts.append(bootstrap)
# Memory context
memory = self.memory.get_memory_context()
if memory:
parts.append(f"# Memory\n\n{memory}")
# Skills - progressive loading
# 1. Always-loaded skills: include full content
always_skills = self.skills.get_always_skills()
if always_skills:
always_content = self.skills.load_skills_for_context(always_skills)
if always_content:
parts.append(f"# Active Skills\n\n{always_content}")
# 2. Available skills: only show summary (agent uses read_file to load)
skills_summary = self.skills.build_skills_summary()
if skills_summary:
parts.append(f"""# Skills
@@ -70,7 +49,7 @@ The following skills extend your capabilities. To use a skill, read its SKILL.md
Skills with available="false" need dependencies installed first - you can try installing them with apt/brew.
{skills_summary}""")
return "\n\n---\n\n".join(parts)
def _get_identity(self) -> str:
@@ -81,29 +60,25 @@ Skills with available="false" need dependencies installed first - you can try in
return f"""# nanobot 🐈
You are nanobot, a helpful AI assistant.
You are nanobot, a helpful AI assistant.
## Runtime
{runtime}
## Workspace
Your workspace is at: {workspace_path}
- Long-term memory: {workspace_path}/memory/MEMORY.md
- Long-term memory: {workspace_path}/memory/MEMORY.md (write important facts here)
- History log: {workspace_path}/memory/HISTORY.md (grep-searchable)
- Custom skills: {workspace_path}/skills/{{skill-name}}/SKILL.md
Reply directly with text for conversations. Only use the 'message' tool to send to a specific chat channel.
## Tool Call Guidelines
- Before calling tools, you may briefly state your intent (e.g. "Let me check that"), but NEVER predict or describe the expected result before receiving it.
- Before modifying a file, read it first to confirm its current content.
- Do not assume a file or directory exists — use list_dir or read_file to verify.
## nanobot Guidelines
- State intent before tool calls, but NEVER predict or claim results before receiving them.
- Before modifying a file, read it first. Do not assume files or directories exist.
- After writing or editing a file, re-read it if accuracy matters.
- If a tool call fails, analyze the error before retrying with a different approach.
- Ask for clarification when the request is ambiguous.
## Memory
- Remember important facts: write to {workspace_path}/memory/MEMORY.md
- Recall past events: grep {workspace_path}/memory/HISTORY.md"""
Reply directly with text for conversations. Only use the 'message' tool to send to a specific chat channel."""
@staticmethod
def _build_runtime_context(channel: str | None, chat_id: str | None) -> str:
@@ -136,37 +111,13 @@ Reply directly with text for conversations. Only use the 'message' tool to send
channel: str | None = None,
chat_id: str | None = None,
) -> list[dict[str, Any]]:
"""
Build the complete message list for an LLM call.
Args:
history: Previous conversation messages.
current_message: The new user message.
skill_names: Optional skills to include.
media: Optional list of local file paths for images/media.
channel: Current channel (telegram, feishu, etc.).
chat_id: Current chat/user ID.
Returns:
List of messages including system prompt.
"""
messages = []
# System prompt
system_prompt = self.build_system_prompt(skill_names)
messages.append({"role": "system", "content": system_prompt})
# History
messages.extend(history)
# Inject runtime metadata as a separate user message before the actual user message.
messages.append({"role": "user", "content": self._build_runtime_context(channel, chat_id)})
# Current user message
user_content = self._build_user_content(current_message, media)
messages.append({"role": "user", "content": user_content})
return messages
"""Build the complete message list for an LLM call."""
return [
{"role": "system", "content": self.build_system_prompt(skill_names)},
*history,
{"role": "user", "content": self._build_runtime_context(channel, chat_id)},
{"role": "user", "content": self._build_user_content(current_message, media)},
]
def _build_user_content(self, text: str, media: list[str] | None) -> str | list[dict[str, Any]]:
"""Build user message content with optional base64-encoded images."""
@@ -187,63 +138,24 @@ Reply directly with text for conversations. Only use the 'message' tool to send
return images + [{"type": "text", "text": text}]
def add_tool_result(
self,
messages: list[dict[str, Any]],
tool_call_id: str,
tool_name: str,
result: str
self, messages: list[dict[str, Any]],
tool_call_id: str, tool_name: str, result: str,
) -> list[dict[str, Any]]:
"""
Add a tool result to the message list.
Args:
messages: Current message list.
tool_call_id: ID of the tool call.
tool_name: Name of the tool.
result: Tool execution result.
Returns:
Updated message list.
"""
messages.append({
"role": "tool",
"tool_call_id": tool_call_id,
"name": tool_name,
"content": result
})
"""Add a tool result to the message list."""
messages.append({"role": "tool", "tool_call_id": tool_call_id, "name": tool_name, "content": result})
return messages
def add_assistant_message(
self,
messages: list[dict[str, Any]],
self, messages: list[dict[str, Any]],
content: str | None,
tool_calls: list[dict[str, Any]] | None = None,
reasoning_content: str | None = None,
) -> list[dict[str, Any]]:
"""
Add an assistant message to the message list.
Args:
messages: Current message list.
content: Message content.
tool_calls: Optional tool calls.
reasoning_content: Thinking output (Kimi, DeepSeek-R1, etc.).
Returns:
Updated message list.
"""
msg: dict[str, Any] = {"role": "assistant"}
# Always include content — some providers (e.g. StepFun) reject
# assistant messages that omit the key entirely.
msg["content"] = content
"""Add an assistant message to the message list."""
msg: dict[str, Any] = {"role": "assistant", "content": content}
if tool_calls:
msg["tool_calls"] = tool_calls
# Include reasoning content when provided (required by some thinking models)
if reasoning_content is not None:
msg["reasoning_content"] = reasoning_content
messages.append(msg)
return messages

71
nanobot/agent/loop.py
View File

@@ -99,6 +99,8 @@ class AgentLoop:
self._consolidating: set[str] = set() # Session keys with consolidation in progress
self._consolidation_tasks: set[asyncio.Task] = set() # Strong refs to in-flight tasks
self._consolidation_locks: dict[str, asyncio.Lock] = {}
self._active_tasks: dict[str, list[asyncio.Task]] = {} # session_key -> tasks
self._processing_lock = asyncio.Lock()
self._register_default_tools()
def _register_default_tools(self) -> None:
@@ -239,35 +241,62 @@ class AgentLoop:
return final_content, tools_used, messages
async def run(self) -> None:
"""Run the agent loop, processing messages from the bus."""
"""Run the agent loop, dispatching messages as tasks to stay responsive to /stop."""
self._running = True
await self._connect_mcp()
logger.info("Agent loop started")
while self._running:
try:
msg = await asyncio.wait_for(
self.bus.consume_inbound(),
timeout=1.0
)
try:
response = await self._process_message(msg)
if response is not None:
await self.bus.publish_outbound(response)
elif msg.channel == "cli":
await self.bus.publish_outbound(OutboundMessage(
channel=msg.channel, chat_id=msg.chat_id, content="", metadata=msg.metadata or {},
))
except Exception as e:
logger.error("Error processing message: {}", e)
await self.bus.publish_outbound(OutboundMessage(
channel=msg.channel,
chat_id=msg.chat_id,
content=f"Sorry, I encountered an error: {str(e)}"
))
msg = await asyncio.wait_for(self.bus.consume_inbound(), timeout=1.0)
except asyncio.TimeoutError:
continue
if msg.content.strip().lower() == "/stop":
await self._handle_stop(msg)
else:
task = asyncio.create_task(self._dispatch(msg))
self._active_tasks.setdefault(msg.session_key, []).append(task)
task.add_done_callback(lambda t, k=msg.session_key: self._active_tasks.get(k, []) and self._active_tasks[k].remove(t) if t in self._active_tasks.get(k, []) else None)
async def _handle_stop(self, msg: InboundMessage) -> None:
"""Cancel all active tasks and subagents for the session."""
tasks = self._active_tasks.pop(msg.session_key, [])
cancelled = sum(1 for t in tasks if not t.done() and t.cancel())
for t in tasks:
try:
await t
except (asyncio.CancelledError, Exception):
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."
await self.bus.publish_outbound(OutboundMessage(
channel=msg.channel, chat_id=msg.chat_id, content=content,
))
async def _dispatch(self, msg: InboundMessage) -> None:
"""Process a message under the global lock."""
async with self._processing_lock:
try:
response = await self._process_message(msg)
if response is not None:
await self.bus.publish_outbound(response)
elif msg.channel == "cli":
await self.bus.publish_outbound(OutboundMessage(
channel=msg.channel, chat_id=msg.chat_id,
content="", metadata=msg.metadata or {},
))
except asyncio.CancelledError:
logger.info("Task cancelled for session {}", msg.session_key)
raise
except Exception:
logger.exception("Error processing message for session {}", msg.session_key)
await self.bus.publish_outbound(OutboundMessage(
channel=msg.channel, chat_id=msg.chat_id,
content="Sorry, I encountered an error.",
))
async def close_mcp(self) -> None:
"""Close MCP connections."""
if self._mcp_stack:
@@ -359,7 +388,7 @@ class AgentLoop:
content="New session started.")
if cmd == "/help":
return OutboundMessage(channel=msg.channel, chat_id=msg.chat_id,
content="🐈 nanobot commands:\n/new — Start a new conversation\n/help — Show available commands")
content="🐈 nanobot commands:\n/new — Start a new conversation\n/stop — Stop the current task\n/help — Show available commands")
unconsolidated = len(session.messages) - session.last_consolidated
if (unconsolidated >= self.memory_window and session.key not in self._consolidating):

56
nanobot/agent/subagent.py
View File

@@ -18,13 +18,7 @@ from nanobot.agent.tools.web import WebSearchTool, WebFetchTool
class SubagentManager:
"""
Manages background subagent execution.
Subagents are lightweight agent instances that run in the background
to handle specific tasks. They share the same LLM provider but have
isolated context and a focused system prompt.
"""
"""Manages background subagent execution."""
def __init__(
self,
@@ -49,6 +43,7 @@ class SubagentManager:
self.exec_config = exec_config or ExecToolConfig()
self.restrict_to_workspace = restrict_to_workspace
self._running_tasks: dict[str, asyncio.Task[None]] = {}
self._session_tasks: dict[str, set[str]] = {} # session_key -> {task_id, ...}
async def spawn(
self,
@@ -56,35 +51,28 @@ class SubagentManager:
label: str | None = None,
origin_channel: str = "cli",
origin_chat_id: str = "direct",
session_key: str | None = None,
) -> str:
"""
Spawn a subagent to execute a task in the background.
Args:
task: The task description for the subagent.
label: Optional human-readable label for the task.
origin_channel: The channel to announce results to.
origin_chat_id: The chat ID to announce results to.
Returns:
Status message indicating the subagent was started.
"""
"""Spawn a subagent to execute a task in the background."""
task_id = str(uuid.uuid4())[:8]
display_label = label or task[:30] + ("..." if len(task) > 30 else "")
origin = {
"channel": origin_channel,
"chat_id": origin_chat_id,
}
# Create background task
origin = {"channel": origin_channel, "chat_id": origin_chat_id}
bg_task = asyncio.create_task(
self._run_subagent(task_id, task, display_label, origin)
)
self._running_tasks[task_id] = bg_task
# Cleanup when done
bg_task.add_done_callback(lambda _: self._running_tasks.pop(task_id, None))
if session_key:
self._session_tasks.setdefault(session_key, set()).add(task_id)
def _cleanup(_: asyncio.Task) -> None:
self._running_tasks.pop(task_id, None)
if session_key and (ids := self._session_tasks.get(session_key)):
ids.discard(task_id)
if not ids:
del self._session_tasks[session_key]
bg_task.add_done_callback(_cleanup)
logger.info("Spawned subagent [{}]: {}", task_id, display_label)
return f"Subagent [{display_label}] started (id: {task_id}). I'll notify you when it completes."
@@ -253,6 +241,16 @@ Skills are available at: {self.workspace}/skills/ (read SKILL.md files as needed
When you have completed the task, provide a clear summary of your findings or actions."""
async def cancel_by_session(self, session_key: str) -> int:
"""Cancel all subagents for the given session. Returns count cancelled."""
tasks = [self._running_tasks[tid] for tid in self._session_tasks.get(session_key, [])
if tid in self._running_tasks and not self._running_tasks[tid].done()]
for t in tasks:
t.cancel()
if tasks:
await asyncio.gather(*tasks, return_exceptions=True)
return len(tasks)
def get_running_count(self) -> int:
"""Return the number of currently running subagents."""
return len(self._running_tasks)

3
nanobot/agent/tools/spawn.py
View File

@@ -15,11 +15,13 @@ class SpawnTool(Tool):
self._manager = manager
self._origin_channel = "cli"
self._origin_chat_id = "direct"
self._session_key = "cli:direct"
def set_context(self, channel: str, chat_id: str) -> None:
"""Set the origin context for subagent announcements."""
self._origin_channel = channel
self._origin_chat_id = chat_id
self._session_key = f"{channel}:{chat_id}"
@property
def name(self) -> str:
@@ -57,4 +59,5 @@ class SpawnTool(Tool):
label=label,
origin_channel=self._origin_channel,
origin_chat_id=self._origin_chat_id,
session_key=self._session_key,
)

2
nanobot/channels/telegram.py
View File

@@ -111,6 +111,7 @@ class TelegramChannel(BaseChannel):
BOT_COMMANDS = [
BotCommand("start", "Start the bot"),
BotCommand("new", "Start a new conversation"),
BotCommand("stop", "Stop the current task"),
BotCommand("help", "Show available commands"),
]
@@ -299,6 +300,7 @@ class TelegramChannel(BaseChannel):
await update.message.reply_text(
"🐈 nanobot commands:\n"
"/new — Start a new conversation\n"
"/stop — Stop the current task\n"
"/help — Show available commands"
)

8
nanobot/templates/AGENTS.md
View File

@@ -2,14 +2,6 @@
You are a helpful AI assistant. Be concise, accurate, and friendly.
## Guidelines
- Before calling tools, briefly state your intent — but NEVER predict results before receiving them
- Use precise tense: "I will run X" before the call, "X returned Y" after
- NEVER claim success before a tool result confirms it
- Ask for clarification when the request is ambiguous
- Remember important information in `memory/MEMORY.md`; past events are logged in `memory/HISTORY.md`
## Scheduled Reminders
When user asks for a reminder at a specific time, use `exec` to run:

167
tests/test_task_cancel.py Normal file
View File

@@ -0,0 +1,167 @@
"""Tests for /stop task cancellation."""
from __future__ import annotations
import asyncio
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
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") as MockSubMgr:
MockSubMgr.return_value.cancel_by_session = AsyncMock(return_value=0)
loop = AgentLoop(bus=bus, provider=provider, workspace=workspace)
return loop, bus
class TestHandleStop:
@pytest.mark.asyncio
async def test_stop_no_active_task(self):
from nanobot.bus.events import InboundMessage
loop, bus = _make_loop()
msg = InboundMessage(channel="test", sender_id="u1", chat_id="c1", content="/stop")
await loop._handle_stop(msg)
out = await asyncio.wait_for(bus.consume_outbound(), timeout=1.0)
assert "No active task" in out.content
@pytest.mark.asyncio
async def test_stop_cancels_active_task(self):
from nanobot.bus.events import InboundMessage
loop, bus = _make_loop()
cancelled = asyncio.Event()
async def slow_task():
try:
await asyncio.sleep(60)
except asyncio.CancelledError:
cancelled.set()
raise
task = asyncio.create_task(slow_task())
await asyncio.sleep(0)
loop._active_tasks["test:c1"] = [task]
msg = InboundMessage(channel="test", sender_id="u1", chat_id="c1", content="/stop")
await loop._handle_stop(msg)
assert cancelled.is_set()
out = await asyncio.wait_for(bus.consume_outbound(), timeout=1.0)
assert "stopped" in out.content.lower()
@pytest.mark.asyncio
async def test_stop_cancels_multiple_tasks(self):
from nanobot.bus.events import InboundMessage
loop, bus = _make_loop()
events = [asyncio.Event(), asyncio.Event()]
async def slow(idx):
try:
await asyncio.sleep(60)
except asyncio.CancelledError:
events[idx].set()
raise
tasks = [asyncio.create_task(slow(i)) for i in range(2)]
await asyncio.sleep(0)
loop._active_tasks["test:c1"] = tasks
msg = InboundMessage(channel="test", sender_id="u1", chat_id="c1", content="/stop")
await loop._handle_stop(msg)
assert all(e.is_set() for e in events)
out = await asyncio.wait_for(bus.consume_outbound(), timeout=1.0)
assert "2 task" in out.content
class TestDispatch:
@pytest.mark.asyncio
async def test_dispatch_processes_and_publishes(self):
from nanobot.bus.events import InboundMessage, OutboundMessage
loop, bus = _make_loop()
msg = InboundMessage(channel="test", sender_id="u1", chat_id="c1", content="hello")
loop._process_message = AsyncMock(
return_value=OutboundMessage(channel="test", chat_id="c1", content="hi")
)
await loop._dispatch(msg)
out = await asyncio.wait_for(bus.consume_outbound(), timeout=1.0)
assert out.content == "hi"
@pytest.mark.asyncio
async def test_processing_lock_serializes(self):
from nanobot.bus.events import InboundMessage, OutboundMessage
loop, bus = _make_loop()
order = []
async def mock_process(m, **kwargs):
order.append(f"start-{m.content}")
await asyncio.sleep(0.05)
order.append(f"end-{m.content}")
return OutboundMessage(channel="test", chat_id="c1", content=m.content)
loop._process_message = mock_process
msg1 = InboundMessage(channel="test", sender_id="u1", chat_id="c1", content="a")
msg2 = InboundMessage(channel="test", sender_id="u1", chat_id="c1", content="b")
t1 = asyncio.create_task(loop._dispatch(msg1))
t2 = asyncio.create_task(loop._dispatch(msg2))
await asyncio.gather(t1, t2)
assert order == ["start-a", "end-a", "start-b", "end-b"]
class TestSubagentCancellation:
@pytest.mark.asyncio
async def test_cancel_by_session(self):
from nanobot.agent.subagent import SubagentManager
from nanobot.bus.queue import MessageBus
bus = MessageBus()
provider = MagicMock()
provider.get_default_model.return_value = "test-model"
mgr = SubagentManager(provider=provider, workspace=MagicMock(), bus=bus)
cancelled = asyncio.Event()
async def slow():
try:
await asyncio.sleep(60)
except asyncio.CancelledError:
cancelled.set()
raise
task = asyncio.create_task(slow())
await asyncio.sleep(0)
mgr._running_tasks["sub-1"] = task
mgr._session_tasks["test:c1"] = {"sub-1"}
count = await mgr.cancel_by_session("test:c1")
assert count == 1
assert cancelled.is_set()
@pytest.mark.asyncio
async def test_cancel_by_session_no_tasks(self):
from nanobot.agent.subagent import SubagentManager
from nanobot.bus.queue import MessageBus
bus = MessageBus()
provider = MagicMock()
provider.get_default_model.return_value = "test-model"
mgr = SubagentManager(provider=provider, workspace=MagicMock(), bus=bus)
assert await mgr.cancel_by_session("nonexistent") == 0