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merge main into pr-554

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Re-bin
2026-02-15 06:12:15 +00:00
parent d30523f460 e2ef1f9d48
commit 54d5f637e7
30 changed files with 1209 additions and 433 deletions
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nanobot/agent/context.py
+8 -5
View File
@@ -73,7 +73,9 @@ Skills with available="false" need dependencies installed first - you can try in
def _get_identity(self) -> str:
"""Get the core identity section."""
from datetime import datetime
import time as _time
now = datetime.now().strftime("%Y-%m-%d %H:%M (%A)")
tz = _time.strftime("%Z") or "UTC"
workspace_path = str(self.workspace.expanduser().resolve())
system = platform.system()
runtime = f"{'macOS' if system == 'Darwin' else system} {platform.machine()}, Python {platform.python_version()}"
@@ -88,23 +90,24 @@ You are nanobot, a helpful AI assistant. You have access to tools that allow you
- Spawn subagents for complex background tasks
## Current Time
{now}
{now} ({tz})
## Runtime
{runtime}
## Workspace
Your workspace is at: {workspace_path}
- Memory files: {workspace_path}/memory/MEMORY.md
- Daily notes: {workspace_path}/memory/YYYY-MM-DD.md
- Long-term memory: {workspace_path}/memory/MEMORY.md
- History log: {workspace_path}/memory/HISTORY.md (grep-searchable)
- Custom skills: {workspace_path}/skills/{{skill-name}}/SKILL.md
IMPORTANT: When responding to direct questions or conversations, reply directly with your text response.
Only use the 'message' tool when you need to send a message to a specific chat channel (like WhatsApp).
For normal conversation, just respond with text - do not call the message tool.
Always be helpful, accurate, and concise. When using tools, explain what you're doing.
When remembering something, write to {workspace_path}/memory/MEMORY.md"""
Always be helpful, accurate, and concise. When using tools, think step by step: what you know, what you need, and why you chose this tool.
When remembering something important, write to {workspace_path}/memory/MEMORY.md
To recall past events, grep {workspace_path}/memory/HISTORY.md"""
def _load_bootstrap_files(self) -> str:
"""Load all bootstrap files from workspace."""
nanobot/agent/loop.py
+209 -144
View File
@@ -19,14 +19,15 @@ from nanobot.agent.tools.web import WebSearchTool, WebFetchTool
from nanobot.agent.tools.message import MessageTool
from nanobot.agent.tools.spawn import SpawnTool
from nanobot.agent.tools.cron import CronTool
from nanobot.agent.memory import MemoryStore
from nanobot.agent.subagent import SubagentManager
from nanobot.session.manager import SessionManager
from nanobot.session.manager import Session, SessionManager
class AgentLoop:
"""
The agent loop is the core processing engine.
It:
1. Receives messages from the bus
2. Builds context with history, memory, skills
@@ -34,7 +35,7 @@ class AgentLoop:
4. Executes tool calls
5. Sends responses back
"""
def __init__(
self,
bus: MessageBus,
@@ -42,6 +43,9 @@ class AgentLoop:
workspace: Path,
model: str | None = None,
max_iterations: int = 20,
temperature: float = 0.7,
max_tokens: int = 4096,
memory_window: int = 50,
brave_api_key: str | None = None,
exec_config: "ExecToolConfig | None" = None,
cron_service: "CronService | None" = None,
@@ -56,11 +60,14 @@ class AgentLoop:
self.workspace = workspace
self.model = model or provider.get_default_model()
self.max_iterations = max_iterations
self.temperature = temperature
self.max_tokens = max_tokens
self.memory_window = memory_window
self.brave_api_key = brave_api_key
self.exec_config = exec_config or ExecToolConfig()
self.cron_service = cron_service
self.restrict_to_workspace = restrict_to_workspace
self.context = ContextBuilder(workspace)
self.sessions = session_manager or SessionManager(workspace)
self.tools = ToolRegistry()
@@ -69,6 +76,8 @@ class AgentLoop:
workspace=workspace,
bus=bus,
model=self.model,
temperature=self.temperature,
max_tokens=self.max_tokens,
brave_api_key=brave_api_key,
exec_config=self.exec_config,
restrict_to_workspace=restrict_to_workspace,
@@ -122,28 +131,96 @@ class AgentLoop:
await self._mcp_stack.__aenter__()
await connect_mcp_servers(self._mcp_servers, self.tools, self._mcp_stack)
def _set_tool_context(self, channel: str, chat_id: str) -> None:
"""Update context for all tools that need routing info."""
if message_tool := self.tools.get("message"):
if isinstance(message_tool, MessageTool):
message_tool.set_context(channel, chat_id)
if spawn_tool := self.tools.get("spawn"):
if isinstance(spawn_tool, SpawnTool):
spawn_tool.set_context(channel, chat_id)
if cron_tool := self.tools.get("cron"):
if isinstance(cron_tool, CronTool):
cron_tool.set_context(channel, chat_id)
async def _run_agent_loop(self, initial_messages: list[dict]) -> tuple[str | None, list[str]]:
"""
Run the agent iteration loop.
Args:
initial_messages: Starting messages for the LLM conversation.
Returns:
Tuple of (final_content, list_of_tools_used).
"""
messages = initial_messages
iteration = 0
final_content = None
tools_used: list[str] = []
while iteration < self.max_iterations:
iteration += 1
response = await self.provider.chat(
messages=messages,
tools=self.tools.get_definitions(),
model=self.model,
temperature=self.temperature,
max_tokens=self.max_tokens,
)
if response.has_tool_calls:
tool_call_dicts = [
{
"id": tc.id,
"type": "function",
"function": {
"name": tc.name,
"arguments": json.dumps(tc.arguments)
}
}
for tc in response.tool_calls
]
messages = self.context.add_assistant_message(
messages, response.content, tool_call_dicts,
reasoning_content=response.reasoning_content,
)
for tool_call in response.tool_calls:
tools_used.append(tool_call.name)
args_str = json.dumps(tool_call.arguments, ensure_ascii=False)
logger.info(f"Tool call: {tool_call.name}({args_str[:200]})")
result = await self.tools.execute(tool_call.name, tool_call.arguments)
messages = self.context.add_tool_result(
messages, tool_call.id, tool_call.name, result
)
messages.append({"role": "user", "content": "Reflect on the results and decide next steps."})
else:
final_content = response.content
break
return final_content, tools_used
async def run(self) -> None:
"""Run the agent loop, processing messages from the bus."""
self._running = True
await self._connect_mcp()
logger.info("Agent loop started")
while self._running:
try:
# Wait for next message
msg = await asyncio.wait_for(
self.bus.consume_inbound(),
timeout=1.0
)
# Process it
try:
response = await self._process_message(msg)
if response:
await self.bus.publish_outbound(response)
except Exception as e:
logger.error(f"Error processing message: {e}")
# Send error response
await self.bus.publish_outbound(OutboundMessage(
channel=msg.channel,
chat_id=msg.chat_id,
@@ -166,105 +243,70 @@ class AgentLoop:
self._running = False
logger.info("Agent loop stopping")
async def _process_message(self, msg: InboundMessage) -> OutboundMessage | None:
async def _process_message(self, msg: InboundMessage, session_key: str | None = None) -> OutboundMessage | None:
"""
Process a single inbound message.
Args:
msg: The inbound message to process.
session_key: Override session key (used by process_direct).
Returns:
The response message, or None if no response needed.
"""
# Handle system messages (subagent announces)
# The chat_id contains the original "channel:chat_id" to route back to
# System messages route back via chat_id ("channel:chat_id")
if msg.channel == "system":
return await self._process_system_message(msg)
preview = msg.content[:80] + "..." if len(msg.content) > 80 else msg.content
logger.info(f"Processing message from {msg.channel}:{msg.sender_id}: {preview}")
# Get or create session
session = self.sessions.get_or_create(msg.session_key)
key = session_key or msg.session_key
session = self.sessions.get_or_create(key)
# Update tool contexts
message_tool = self.tools.get("message")
if isinstance(message_tool, MessageTool):
message_tool.set_context(msg.channel, msg.chat_id)
# Handle slash commands
cmd = msg.content.strip().lower()
if cmd == "/new":
# Capture messages before clearing (avoid race condition with background task)
messages_to_archive = session.messages.copy()
session.clear()
self.sessions.save(session)
self.sessions.invalidate(session.key)
async def _consolidate_and_cleanup():
temp_session = Session(key=session.key)
temp_session.messages = messages_to_archive
await self._consolidate_memory(temp_session, archive_all=True)
asyncio.create_task(_consolidate_and_cleanup())
return OutboundMessage(channel=msg.channel, chat_id=msg.chat_id,
content="New session started. Memory consolidation in progress.")
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")
spawn_tool = self.tools.get("spawn")
if isinstance(spawn_tool, SpawnTool):
spawn_tool.set_context(msg.channel, msg.chat_id)
cron_tool = self.tools.get("cron")
if isinstance(cron_tool, CronTool):
cron_tool.set_context(msg.channel, msg.chat_id)
# Build initial messages (use get_history for LLM-formatted messages)
messages = self.context.build_messages(
history=session.get_history(),
if len(session.messages) > self.memory_window:
asyncio.create_task(self._consolidate_memory(session))
self._set_tool_context(msg.channel, msg.chat_id)
initial_messages = self.context.build_messages(
history=session.get_history(max_messages=self.memory_window),
current_message=msg.content,
media=msg.media if msg.media else None,
channel=msg.channel,
chat_id=msg.chat_id,
)
# Agent loop
iteration = 0
final_content = None
while iteration < self.max_iterations:
iteration += 1
# Call LLM
response = await self.provider.chat(
messages=messages,
tools=self.tools.get_definitions(),
model=self.model
)
# Handle tool calls
if response.has_tool_calls:
# Add assistant message with tool calls
tool_call_dicts = [
{
"id": tc.id,
"type": "function",
"function": {
"name": tc.name,
"arguments": json.dumps(tc.arguments) # Must be JSON string
}
}
for tc in response.tool_calls
]
messages = self.context.add_assistant_message(
messages, response.content, tool_call_dicts,
reasoning_content=response.reasoning_content,
)
# Execute tools
for tool_call in response.tool_calls:
args_str = json.dumps(tool_call.arguments, ensure_ascii=False)
logger.info(f"Tool call: {tool_call.name}({args_str[:200]})")
result = await self.tools.execute(tool_call.name, tool_call.arguments)
messages = self.context.add_tool_result(
messages, tool_call.id, tool_call.name, result
)
else:
# No tool calls, we're done
final_content = response.content
break
final_content, tools_used = await self._run_agent_loop(initial_messages)
if final_content is None:
final_content = "I've completed processing but have no response to give."
# Log response preview
preview = final_content[:120] + "..." if len(final_content) > 120 else final_content
logger.info(f"Response to {msg.channel}:{msg.sender_id}: {preview}")
# Save to session
session.add_message("user", msg.content)
session.add_message("assistant", final_content)
session.add_message("assistant", final_content,
tools_used=tools_used if tools_used else None)
self.sessions.save(session)
return OutboundMessage(
@@ -293,76 +335,20 @@ class AgentLoop:
origin_channel = "cli"
origin_chat_id = msg.chat_id
# Use the origin session for context
session_key = f"{origin_channel}:{origin_chat_id}"
session = self.sessions.get_or_create(session_key)
# Update tool contexts
message_tool = self.tools.get("message")
if isinstance(message_tool, MessageTool):
message_tool.set_context(origin_channel, origin_chat_id)
spawn_tool = self.tools.get("spawn")
if isinstance(spawn_tool, SpawnTool):
spawn_tool.set_context(origin_channel, origin_chat_id)
cron_tool = self.tools.get("cron")
if isinstance(cron_tool, CronTool):
cron_tool.set_context(origin_channel, origin_chat_id)
# Build messages with the announce content
messages = self.context.build_messages(
history=session.get_history(),
self._set_tool_context(origin_channel, origin_chat_id)
initial_messages = self.context.build_messages(
history=session.get_history(max_messages=self.memory_window),
current_message=msg.content,
channel=origin_channel,
chat_id=origin_chat_id,
)
# Agent loop (limited for announce handling)
iteration = 0
final_content = None
while iteration < self.max_iterations:
iteration += 1
response = await self.provider.chat(
messages=messages,
tools=self.tools.get_definitions(),
model=self.model
)
if response.has_tool_calls:
tool_call_dicts = [
{
"id": tc.id,
"type": "function",
"function": {
"name": tc.name,
"arguments": json.dumps(tc.arguments)
}
}
for tc in response.tool_calls
]
messages = self.context.add_assistant_message(
messages, response.content, tool_call_dicts,
reasoning_content=response.reasoning_content,
)
for tool_call in response.tool_calls:
args_str = json.dumps(tool_call.arguments, ensure_ascii=False)
logger.info(f"Tool call: {tool_call.name}({args_str[:200]})")
result = await self.tools.execute(tool_call.name, tool_call.arguments)
messages = self.context.add_tool_result(
messages, tool_call.id, tool_call.name, result
)
else:
final_content = response.content
break
final_content, _ = await self._run_agent_loop(initial_messages)
if final_content is None:
final_content = "Background task completed."
# Save to session (mark as system message in history)
session.add_message("user", f"[System: {msg.sender_id}] {msg.content}")
session.add_message("assistant", final_content)
self.sessions.save(session)
@@ -373,6 +359,85 @@ class AgentLoop:
content=final_content
)
async def _consolidate_memory(self, session, archive_all: bool = False) -> None:
"""Consolidate old messages into MEMORY.md + HISTORY.md.
Args:
archive_all: If True, clear all messages and reset session (for /new command).
If False, only write to files without modifying session.
"""
memory = MemoryStore(self.workspace)
if archive_all:
old_messages = session.messages
keep_count = 0
logger.info(f"Memory consolidation (archive_all): {len(session.messages)} total messages archived")
else:
keep_count = self.memory_window // 2
if len(session.messages) <= keep_count:
logger.debug(f"Session {session.key}: No consolidation needed (messages={len(session.messages)}, keep={keep_count})")
return
messages_to_process = len(session.messages) - session.last_consolidated
if messages_to_process <= 0:
logger.debug(f"Session {session.key}: No new messages to consolidate (last_consolidated={session.last_consolidated}, total={len(session.messages)})")
return
old_messages = session.messages[session.last_consolidated:-keep_count]
if not old_messages:
return
logger.info(f"Memory consolidation started: {len(session.messages)} total, {len(old_messages)} new to consolidate, {keep_count} keep")
lines = []
for m in old_messages:
if not m.get("content"):
continue
tools = f" [tools: {', '.join(m['tools_used'])}]" if m.get("tools_used") else ""
lines.append(f"[{m.get('timestamp', '?')[:16]}] {m['role'].upper()}{tools}: {m['content']}")
conversation = "\n".join(lines)
current_memory = memory.read_long_term()
prompt = f"""You are a memory consolidation agent. Process this conversation and return a JSON object with exactly two keys:
1. "history_entry": A paragraph (2-5 sentences) summarizing the key events/decisions/topics. Start with a timestamp like [YYYY-MM-DD HH:MM]. Include enough detail to be useful when found by grep search later.
2. "memory_update": The updated long-term memory content. Add any new facts: user location, preferences, personal info, habits, project context, technical decisions, tools/services used. If nothing new, return the existing content unchanged.
## Current Long-term Memory
{current_memory or "(empty)"}
## Conversation to Process
{conversation}
Respond with ONLY valid JSON, no markdown fences."""
try:
response = await self.provider.chat(
messages=[
{"role": "system", "content": "You are a memory consolidation agent. Respond only with valid JSON."},
{"role": "user", "content": prompt},
],
model=self.model,
)
text = (response.content or "").strip()
if text.startswith("```"):
text = text.split("\n", 1)[-1].rsplit("```", 1)[0].strip()
result = json.loads(text)
if entry := result.get("history_entry"):
memory.append_history(entry)
if update := result.get("memory_update"):
if update != current_memory:
memory.write_long_term(update)
if archive_all:
session.last_consolidated = 0
else:
session.last_consolidated = len(session.messages) - keep_count
logger.info(f"Memory consolidation done: {len(session.messages)} messages, last_consolidated={session.last_consolidated}")
except Exception as e:
logger.error(f"Memory consolidation failed: {e}")
async def process_direct(
self,
content: str,
@@ -385,9 +450,9 @@ class AgentLoop:
Args:
content: The message content.
session_key: Session identifier.
channel: Source channel (for context).
chat_id: Source chat ID (for context).
session_key: Session identifier (overrides channel:chat_id for session lookup).
channel: Source channel (for tool context routing).
chat_id: Source chat ID (for tool context routing).
Returns:
The agent's response.
@@ -400,5 +465,5 @@ class AgentLoop:
content=content
)
response = await self._process_message(msg)
response = await self._process_message(msg, session_key=session_key)
return response.content if response else ""
nanobot/agent/memory.py
+12 -91
View File
@@ -1,109 +1,30 @@
"""Memory system for persistent agent memory."""
from pathlib import Path
from datetime import datetime
from nanobot.utils.helpers import ensure_dir, today_date
from nanobot.utils.helpers import ensure_dir
class MemoryStore:
"""
Memory system for the agent.
Supports daily notes (memory/YYYY-MM-DD.md) and long-term memory (MEMORY.md).
"""
"""Two-layer memory: MEMORY.md (long-term facts) + HISTORY.md (grep-searchable log)."""
def __init__(self, workspace: Path):
self.workspace = workspace
self.memory_dir = ensure_dir(workspace / "memory")
self.memory_file = self.memory_dir / "MEMORY.md"
def get_today_file(self) -> Path:
"""Get path to today's memory file."""
return self.memory_dir / f"{today_date()}.md"
def read_today(self) -> str:
"""Read today's memory notes."""
today_file = self.get_today_file()
if today_file.exists():
return today_file.read_text(encoding="utf-8")
return ""
def append_today(self, content: str) -> None:
"""Append content to today's memory notes."""
today_file = self.get_today_file()
if today_file.exists():
existing = today_file.read_text(encoding="utf-8")
content = existing + "\n" + content
else:
# Add header for new day
header = f"# {today_date()}\n\n"
content = header + content
today_file.write_text(content, encoding="utf-8")
self.history_file = self.memory_dir / "HISTORY.md"
def read_long_term(self) -> str:
"""Read long-term memory (MEMORY.md)."""
if self.memory_file.exists():
return self.memory_file.read_text(encoding="utf-8")
return ""
def write_long_term(self, content: str) -> None:
"""Write to long-term memory (MEMORY.md)."""
self.memory_file.write_text(content, encoding="utf-8")
def get_recent_memories(self, days: int = 7) -> str:
"""
Get memories from the last N days.
Args:
days: Number of days to look back.
Returns:
Combined memory content.
"""
from datetime import timedelta
memories = []
today = datetime.now().date()
for i in range(days):
date = today - timedelta(days=i)
date_str = date.strftime("%Y-%m-%d")
file_path = self.memory_dir / f"{date_str}.md"
if file_path.exists():
content = file_path.read_text(encoding="utf-8")
memories.append(content)
return "\n\n---\n\n".join(memories)
def list_memory_files(self) -> list[Path]:
"""List all memory files sorted by date (newest first)."""
if not self.memory_dir.exists():
return []
files = list(self.memory_dir.glob("????-??-??.md"))
return sorted(files, reverse=True)
def append_history(self, entry: str) -> None:
with open(self.history_file, "a", encoding="utf-8") as f:
f.write(entry.rstrip() + "\n\n")
def get_memory_context(self) -> str:
"""
Get memory context for the agent.
Returns:
Formatted memory context including long-term and recent memories.
"""
parts = []
# Long-term memory
long_term = self.read_long_term()
if long_term:
parts.append("## Long-term Memory\n" + long_term)
# Today's notes
today = self.read_today()
if today:
parts.append("## Today's Notes\n" + today)
return "\n\n".join(parts) if parts else ""
return f"## Long-term Memory\n{long_term}" if long_term else ""
nanobot/agent/subagent.py
+17 -4
View File
@@ -12,7 +12,7 @@ from nanobot.bus.events import InboundMessage
from nanobot.bus.queue import MessageBus
from nanobot.providers.base import LLMProvider
from nanobot.agent.tools.registry import ToolRegistry
from nanobot.agent.tools.filesystem import ReadFileTool, WriteFileTool, ListDirTool
from nanobot.agent.tools.filesystem import ReadFileTool, WriteFileTool, EditFileTool, ListDirTool
from nanobot.agent.tools.shell import ExecTool
from nanobot.agent.tools.web import WebSearchTool, WebFetchTool
@@ -32,6 +32,8 @@ class SubagentManager:
workspace: Path,
bus: MessageBus,
model: str | None = None,
temperature: float = 0.7,
max_tokens: int = 4096,
brave_api_key: str | None = None,
exec_config: "ExecToolConfig | None" = None,
restrict_to_workspace: bool = False,
@@ -41,6 +43,8 @@ class SubagentManager:
self.workspace = workspace
self.bus = bus
self.model = model or provider.get_default_model()
self.temperature = temperature
self.max_tokens = max_tokens
self.brave_api_key = brave_api_key
self.exec_config = exec_config or ExecToolConfig()
self.restrict_to_workspace = restrict_to_workspace
@@ -101,6 +105,7 @@ class SubagentManager:
allowed_dir = self.workspace if self.restrict_to_workspace else None
tools.register(ReadFileTool(allowed_dir=allowed_dir))
tools.register(WriteFileTool(allowed_dir=allowed_dir))
tools.register(EditFileTool(allowed_dir=allowed_dir))
tools.register(ListDirTool(allowed_dir=allowed_dir))
tools.register(ExecTool(
working_dir=str(self.workspace),
@@ -129,6 +134,8 @@ class SubagentManager:
messages=messages,
tools=tools.get_definitions(),
model=self.model,
temperature=self.temperature,
max_tokens=self.max_tokens,
)
if response.has_tool_calls:
@@ -210,12 +217,17 @@ Summarize this naturally for the user. Keep it brief (1-2 sentences). Do not men
def _build_subagent_prompt(self, task: str) -> str:
"""Build a focused system prompt for the subagent."""
from datetime import datetime
import time as _time
now = datetime.now().strftime("%Y-%m-%d %H:%M (%A)")
tz = _time.strftime("%Z") or "UTC"
return f"""# Subagent
You are a subagent spawned by the main agent to complete a specific task.
## Current Time
{now} ({tz})
## Your Task
{task}
You are a subagent spawned by the main agent to complete a specific task.
## Rules
1. Stay focused - complete only the assigned task, nothing else
@@ -236,6 +248,7 @@ You are a subagent spawned by the main agent to complete a specific task.
## Workspace
Your workspace is at: {self.workspace}
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."""
nanobot/agent/tools/cron.py
+16 -3
View File
@@ -50,6 +50,10 @@ class CronTool(Tool):
"type": "string",
"description": "Cron expression like '0 9 * * *' (for scheduled tasks)"
},
"at": {
"type": "string",
"description": "ISO datetime for one-time execution (e.g. '2026-02-12T10:30:00')"
},
"job_id": {
"type": "string",
"description": "Job ID (for remove)"
@@ -64,30 +68,38 @@ class CronTool(Tool):
message: str = "",
every_seconds: int | None = None,
cron_expr: str | None = None,
at: str | None = None,
job_id: str | None = None,
**kwargs: Any
) -> str:
if action == "add":
return self._add_job(message, every_seconds, cron_expr)
return self._add_job(message, every_seconds, cron_expr, at)
elif action == "list":
return self._list_jobs()
elif action == "remove":
return self._remove_job(job_id)
return f"Unknown action: {action}"
def _add_job(self, message: str, every_seconds: int | None, cron_expr: str | None) -> str:
def _add_job(self, message: str, every_seconds: int | None, cron_expr: str | None, at: str | None) -> str:
if not message:
return "Error: message is required for add"
if not self._channel or not self._chat_id:
return "Error: no session context (channel/chat_id)"
# Build schedule
delete_after = False
if every_seconds:
schedule = CronSchedule(kind="every", every_ms=every_seconds * 1000)
elif cron_expr:
schedule = CronSchedule(kind="cron", expr=cron_expr)
elif at:
from datetime import datetime
dt = datetime.fromisoformat(at)
at_ms = int(dt.timestamp() * 1000)
schedule = CronSchedule(kind="at", at_ms=at_ms)
delete_after = True
else:
return "Error: either every_seconds or cron_expr is required"
return "Error: either every_seconds, cron_expr, or at is required"
job = self._cron.add_job(
name=message[:30],
@@ -96,6 +108,7 @@ class CronTool(Tool):
deliver=True,
channel=self._channel,
to=self._chat_id,
delete_after_run=delete_after,
)
return f"Created job '{job.name}' (id: {job.id})"
nanobot/channels/dingtalk.py
+9 -2
View File
@@ -137,8 +137,15 @@ class DingTalkChannel(BaseChannel):
logger.info("DingTalk bot started with Stream Mode")
# client.start() is an async infinite loop handling the websocket connection
await self._client.start()
# Reconnect loop: restart stream if SDK exits or crashes
while self._running:
try:
await self._client.start()
except Exception as e:
logger.warning(f"DingTalk stream error: {e}")
if self._running:
logger.info("Reconnecting DingTalk stream in 5 seconds...")
await asyncio.sleep(5)
except Exception as e:
logger.exception(f"Failed to start DingTalk channel: {e}")
nanobot/channels/feishu.py
+105 -10
View File
@@ -39,6 +39,53 @@ MSG_TYPE_MAP = {
}
def _extract_post_text(content_json: dict) -> str:
"""Extract plain text from Feishu post (rich text) message content.
Supports two formats:
1. Direct format: {"title": "...", "content": [...]}
2. Localized format: {"zh_cn": {"title": "...", "content": [...]}}
"""
def extract_from_lang(lang_content: dict) -> str | None:
if not isinstance(lang_content, dict):
return None
title = lang_content.get("title", "")
content_blocks = lang_content.get("content", [])
if not isinstance(content_blocks, list):
return None
text_parts = []
if title:
text_parts.append(title)
for block in content_blocks:
if not isinstance(block, list):
continue
for element in block:
if isinstance(element, dict):
tag = element.get("tag")
if tag == "text":
text_parts.append(element.get("text", ""))
elif tag == "a":
text_parts.append(element.get("text", ""))
elif tag == "at":
text_parts.append(f"@{element.get('user_name', 'user')}")
return " ".join(text_parts).strip() if text_parts else None
# Try direct format first
if "content" in content_json:
result = extract_from_lang(content_json)
if result:
return result
# Try localized format
for lang_key in ("zh_cn", "en_us", "ja_jp"):
lang_content = content_json.get(lang_key)
result = extract_from_lang(lang_content)
if result:
return result
return ""
class FeishuChannel(BaseChannel):
"""
Feishu/Lark channel using WebSocket long connection.
@@ -98,12 +145,15 @@ class FeishuChannel(BaseChannel):
log_level=lark.LogLevel.INFO
)
# Start WebSocket client in a separate thread
# Start WebSocket client in a separate thread with reconnect loop
def run_ws():
try:
self._ws_client.start()
except Exception as e:
logger.error(f"Feishu WebSocket error: {e}")
while self._running:
try:
self._ws_client.start()
except Exception as e:
logger.warning(f"Feishu WebSocket error: {e}")
if self._running:
import time; time.sleep(5)
self._ws_thread = threading.Thread(target=run_ws, daemon=True)
self._ws_thread.start()
@@ -163,6 +213,10 @@ class FeishuChannel(BaseChannel):
re.MULTILINE,
)
_HEADING_RE = re.compile(r"^(#{1,6})\s+(.+)$", re.MULTILINE)
_CODE_BLOCK_RE = re.compile(r"(```[\s\S]*?```)", re.MULTILINE)
@staticmethod
def _parse_md_table(table_text: str) -> dict | None:
"""Parse a markdown table into a Feishu table element."""
@@ -182,17 +236,52 @@ class FeishuChannel(BaseChannel):
}
def _build_card_elements(self, content: str) -> list[dict]:
"""Split content into markdown + table elements for Feishu card."""
"""Split content into div/markdown + table elements for Feishu card."""
elements, last_end = [], 0
for m in self._TABLE_RE.finditer(content):
before = content[last_end:m.start()].strip()
if before:
elements.append({"tag": "markdown", "content": before})
before = content[last_end:m.start()]
if before.strip():
elements.extend(self._split_headings(before))
elements.append(self._parse_md_table(m.group(1)) or {"tag": "markdown", "content": m.group(1)})
last_end = m.end()
remaining = content[last_end:].strip()
remaining = content[last_end:]
if remaining.strip():
elements.extend(self._split_headings(remaining))
return elements or [{"tag": "markdown", "content": content}]
def _split_headings(self, content: str) -> list[dict]:
"""Split content by headings, converting headings to div elements."""
protected = content
code_blocks = []
for m in self._CODE_BLOCK_RE.finditer(content):
code_blocks.append(m.group(1))
protected = protected.replace(m.group(1), f"\x00CODE{len(code_blocks)-1}\x00", 1)
elements = []
last_end = 0
for m in self._HEADING_RE.finditer(protected):
before = protected[last_end:m.start()].strip()
if before:
elements.append({"tag": "markdown", "content": before})
level = len(m.group(1))
text = m.group(2).strip()
elements.append({
"tag": "div",
"text": {
"tag": "lark_md",
"content": f"**{text}**",
},
})
last_end = m.end()
remaining = protected[last_end:].strip()
if remaining:
elements.append({"tag": "markdown", "content": remaining})
for i, cb in enumerate(code_blocks):
for el in elements:
if el.get("tag") == "markdown":
el["content"] = el["content"].replace(f"\x00CODE{i}\x00", cb)
return elements or [{"tag": "markdown", "content": content}]
async def send(self, msg: OutboundMessage) -> None:
@@ -284,6 +373,12 @@ class FeishuChannel(BaseChannel):
content = json.loads(message.content).get("text", "")
except json.JSONDecodeError:
content = message.content or ""
elif msg_type == "post":
try:
content_json = json.loads(message.content)
content = _extract_post_text(content_json)
except (json.JSONDecodeError, TypeError):
content = message.content or ""
else:
content = MSG_TYPE_MAP.get(msg_type, f"[{msg_type}]")
nanobot/channels/manager.py
+2 -7
View File
@@ -3,7 +3,7 @@
from __future__ import annotations
import asyncio
from typing import Any, TYPE_CHECKING
from typing import Any
from loguru import logger
@@ -12,9 +12,6 @@ from nanobot.bus.queue import MessageBus
from nanobot.channels.base import BaseChannel
from nanobot.config.schema import Config
if TYPE_CHECKING:
from nanobot.session.manager import SessionManager
class ChannelManager:
"""
@@ -26,10 +23,9 @@ class ChannelManager:
- Route outbound messages
"""
def __init__(self, config: Config, bus: MessageBus, session_manager: "SessionManager | None" = None):
def __init__(self, config: Config, bus: MessageBus):
self.config = config
self.bus = bus
self.session_manager = session_manager
self.channels: dict[str, BaseChannel] = {}
self._dispatch_task: asyncio.Task | None = None
@@ -46,7 +42,6 @@ class ChannelManager:
self.config.channels.telegram,
self.bus,
groq_api_key=self.config.providers.groq.api_key,
session_manager=self.session_manager,
)
logger.info("Telegram channel enabled")
except ImportError as e:
nanobot/channels/qq.py
+9 -6
View File
@@ -75,12 +75,15 @@ class QQChannel(BaseChannel):
logger.info("QQ bot started (C2C private message)")
async def _run_bot(self) -> None:
"""Run the bot connection."""
try:
await self._client.start(appid=self.config.app_id, secret=self.config.secret)
except Exception as e:
logger.error(f"QQ auth failed, check AppID/Secret at q.qq.com: {e}")
self._running = False
"""Run the bot connection with auto-reconnect."""
while self._running:
try:
await self._client.start(appid=self.config.app_id, secret=self.config.secret)
except Exception as e:
logger.warning(f"QQ bot error: {e}")
if self._running:
logger.info("Reconnecting QQ bot in 5 seconds...")
await asyncio.sleep(5)
async def stop(self) -> None:
"""Stop the QQ bot."""
nanobot/channels/telegram.py
+18 -43
View File
@@ -4,20 +4,16 @@ from __future__ import annotations
import asyncio
import re
from typing import TYPE_CHECKING
from loguru import logger
from telegram import BotCommand, Update
from telegram.ext import Application, CommandHandler, MessageHandler, filters, ContextTypes
from telegram.request import HTTPXRequest
from nanobot.bus.events import OutboundMessage
from nanobot.bus.queue import MessageBus
from nanobot.channels.base import BaseChannel
from nanobot.config.schema import TelegramConfig
if TYPE_CHECKING:
from nanobot.session.manager import SessionManager
def _markdown_to_telegram_html(text: str) -> str:
"""
@@ -94,7 +90,7 @@ class TelegramChannel(BaseChannel):
# Commands registered with Telegram's command menu
BOT_COMMANDS = [
BotCommand("start", "Start the bot"),
BotCommand("reset", "Reset conversation history"),
BotCommand("new", "Start a new conversation"),
BotCommand("help", "Show available commands"),
]
@@ -103,12 +99,10 @@ class TelegramChannel(BaseChannel):
config: TelegramConfig,
bus: MessageBus,
groq_api_key: str = "",
session_manager: SessionManager | None = None,
):
super().__init__(config, bus)
self.config: TelegramConfig = config
self.groq_api_key = groq_api_key
self.session_manager = session_manager
self._app: Application | None = None
self._chat_ids: dict[str, int] = {} # Map sender_id to chat_id for replies
self._typing_tasks: dict[str, asyncio.Task] = {} # chat_id -> typing loop task
@@ -121,16 +115,18 @@ class TelegramChannel(BaseChannel):
self._running = True
# Build the application
builder = Application.builder().token(self.config.token)
# Build the application with larger connection pool to avoid pool-timeout on long runs
req = HTTPXRequest(connection_pool_size=16, pool_timeout=5.0, connect_timeout=30.0, read_timeout=30.0)
builder = Application.builder().token(self.config.token).request(req).get_updates_request(req)
if self.config.proxy:
builder = builder.proxy(self.config.proxy).get_updates_proxy(self.config.proxy)
self._app = builder.build()
self._app.add_error_handler(self._on_error)
# Add command handlers
self._app.add_handler(CommandHandler("start", self._on_start))
self._app.add_handler(CommandHandler("reset", self._on_reset))
self._app.add_handler(CommandHandler("help", self._on_help))
self._app.add_handler(CommandHandler("new", self._forward_command))
self._app.add_handler(CommandHandler("help", self._forward_command))
# Add message handler for text, photos, voice, documents
self._app.add_handler(
@@ -226,40 +222,15 @@ class TelegramChannel(BaseChannel):
"Type /help to see available commands."
)
async def _on_reset(self, update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Handle /reset command — clear conversation history."""
async def _forward_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Forward slash commands to the bus for unified handling in AgentLoop."""
if not update.message or not update.effective_user:
return
chat_id = str(update.message.chat_id)
session_key = f"{self.name}:{chat_id}"
if self.session_manager is None:
logger.warning("/reset called but session_manager is not available")
await update.message.reply_text("⚠️ Session management is not available.")
return
session = self.session_manager.get_or_create(session_key)
msg_count = len(session.messages)
session.clear()
self.session_manager.save(session)
logger.info(f"Session reset for {session_key} (cleared {msg_count} messages)")
await update.message.reply_text("🔄 Conversation history cleared. Let's start fresh!")
async def _on_help(self, update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Handle /help command — show available commands."""
if not update.message:
return
help_text = (
"🐈 <b>nanobot commands</b>\n\n"
"/start — Start the bot\n"
"/reset — Reset conversation history\n"
"/help — Show this help message\n\n"
"Just send me a text message to chat!"
await self._handle_message(
sender_id=str(update.effective_user.id),
chat_id=str(update.message.chat_id),
content=update.message.text,
)
await update.message.reply_text(help_text, parse_mode="HTML")
async def _on_message(self, update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Handle incoming messages (text, photos, voice, documents)."""
@@ -386,6 +357,10 @@ class TelegramChannel(BaseChannel):
except Exception as e:
logger.debug(f"Typing indicator stopped for {chat_id}: {e}")
async def _on_error(self, update: object, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Log polling / handler errors instead of silently swallowing them."""
logger.error(f"Telegram error: {context.error}")
def _get_extension(self, media_type: str, mime_type: str | None) -> str:
"""Get file extension based on media type."""
if mime_type:
nanobot/channels/whatsapp.py
+3
View File
@@ -42,6 +42,9 @@ class WhatsAppChannel(BaseChannel):
try:
async with websockets.connect(bridge_url) as ws:
self._ws = ws
# Send auth token if configured
if self.config.bridge_token:
await ws.send(json.dumps({"type": "auth", "token": self.config.bridge_token}))
self._connected = True
logger.info("Connected to WhatsApp bridge")
nanobot/cli/commands.py
+41 -13
View File
@@ -155,7 +155,7 @@ def main(
@app.command()
def onboard():
"""Initialize nanobot configuration and workspace."""
from nanobot.config.loader import get_config_path, save_config
from nanobot.config.loader import get_config_path, load_config, save_config
from nanobot.config.schema import Config
from nanobot.utils.helpers import get_workspace_path
@@ -163,17 +163,26 @@ def onboard():
if config_path.exists():
console.print(f"[yellow]Config already exists at {config_path}[/yellow]")
if not typer.confirm("Overwrite?"):
raise typer.Exit()
# Create default config
config = Config()
save_config(config)
console.print(f"[green]✓[/green] Created config at {config_path}")
console.print(" [bold]y[/bold] = overwrite with defaults (existing values will be lost)")
console.print(" [bold]N[/bold] = refresh config, keeping existing values and adding new fields")
if typer.confirm("Overwrite?"):
config = Config()
save_config(config)
console.print(f"[green]✓[/green] Config reset to defaults at {config_path}")
else:
config = load_config()
save_config(config)
console.print(f"[green]✓[/green] Config refreshed at {config_path} (existing values preserved)")
else:
save_config(Config())
console.print(f"[green]✓[/green] Created config at {config_path}")
# Create workspace
workspace = get_workspace_path()
console.print(f"[green]✓[/green] Created workspace at {workspace}")
if not workspace.exists():
workspace.mkdir(parents=True, exist_ok=True)
console.print(f"[green]✓[/green] Created workspace at {workspace}")
# Create default bootstrap files
_create_workspace_templates(workspace)
@@ -200,7 +209,7 @@ You are a helpful AI assistant. Be concise, accurate, and friendly.
- Always explain what you're doing before taking actions
- Ask for clarification when the request is ambiguous
- Use tools to help accomplish tasks
- Remember important information in your memory files
- Remember important information in memory/MEMORY.md; past events are logged in memory/HISTORY.md
""",
"SOUL.md": """# Soul
@@ -258,6 +267,11 @@ This file stores important information that should persist across sessions.
(Things to remember)
""")
console.print(" [dim]Created memory/MEMORY.md[/dim]")
history_file = memory_dir / "HISTORY.md"
if not history_file.exists():
history_file.write_text("")
console.print(" [dim]Created memory/HISTORY.md[/dim]")
# Create skills directory for custom user skills
skills_dir = workspace / "skills"
@@ -323,7 +337,10 @@ def gateway(
provider=provider,
workspace=config.workspace_path,
model=config.agents.defaults.model,
temperature=config.agents.defaults.temperature,
max_tokens=config.agents.defaults.max_tokens,
max_iterations=config.agents.defaults.max_tool_iterations,
memory_window=config.agents.defaults.memory_window,
brave_api_key=config.tools.web.search.api_key or None,
exec_config=config.tools.exec,
cron_service=cron,
@@ -364,7 +381,7 @@ def gateway(
)
# Create channel manager
channels = ChannelManager(config, bus, session_manager=session_manager)
channels = ChannelManager(config, bus)
if channels.enabled_channels:
console.print(f"[green]✓[/green] Channels enabled: {', '.join(channels.enabled_channels)}")
@@ -407,7 +424,7 @@ def gateway(
@app.command()
def agent(
message: str = typer.Option(None, "--message", "-m", help="Message to send to the agent"),
session_id: str = typer.Option("cli:default", "--session", "-s", help="Session ID"),
session_id: str = typer.Option("cli:direct", "--session", "-s", help="Session ID"),
markdown: bool = typer.Option(True, "--markdown/--no-markdown", help="Render assistant output as Markdown"),
logs: bool = typer.Option(False, "--logs/--no-logs", help="Show nanobot runtime logs during chat"),
):
@@ -431,6 +448,11 @@ def agent(
bus=bus,
provider=provider,
workspace=config.workspace_path,
model=config.agents.defaults.model,
temperature=config.agents.defaults.temperature,
max_tokens=config.agents.defaults.max_tokens,
max_iterations=config.agents.defaults.max_tool_iterations,
memory_window=config.agents.defaults.memory_window,
brave_api_key=config.tools.web.search.api_key or None,
exec_config=config.tools.exec,
restrict_to_workspace=config.tools.restrict_to_workspace,
@@ -635,14 +657,20 @@ def _get_bridge_dir() -> Path:
def channels_login():
"""Link device via QR code."""
import subprocess
from nanobot.config.loader import load_config
config = load_config()
bridge_dir = _get_bridge_dir()
console.print(f"{__logo__} Starting bridge...")
console.print("Scan the QR code to connect.\n")
env = {**os.environ}
if config.channels.whatsapp.bridge_token:
env["BRIDGE_TOKEN"] = config.channels.whatsapp.bridge_token
try:
subprocess.run(["npm", "start"], cwd=bridge_dir, check=True)
subprocess.run(["npm", "start"], cwd=bridge_dir, check=True, env=env)
except subprocess.CalledProcessError as e:
console.print(f"[red]Bridge failed: {e}[/red]")
except FileNotFoundError:
nanobot/config/schema.py
+3
View File
@@ -9,6 +9,7 @@ class WhatsAppConfig(BaseModel):
"""WhatsApp channel configuration."""
enabled: bool = False
bridge_url: str = "ws://localhost:3001"
bridge_token: str = "" # Shared token for bridge auth (optional, recommended)
allow_from: list[str] = Field(default_factory=list) # Allowed phone numbers
@@ -161,6 +162,7 @@ class AgentDefaults(BaseModel):
max_tokens: int = 8192
temperature: float = 0.7
max_tool_iterations: int = 20
memory_window: int = 50
class AgentsConfig(BaseModel):
@@ -177,6 +179,7 @@ class ProviderConfig(BaseModel):
class ProvidersConfig(BaseModel):
"""Configuration for LLM providers."""
custom: ProviderConfig = Field(default_factory=ProviderConfig) # Any OpenAI-compatible endpoint
anthropic: ProviderConfig = Field(default_factory=ProviderConfig)
openai: ProviderConfig = Field(default_factory=ProviderConfig)
openrouter: ProviderConfig = Field(default_factory=ProviderConfig)
nanobot/cron/service.py
+8 -3
View File
@@ -4,6 +4,7 @@ import asyncio
import json
import time
import uuid
from datetime import datetime
from pathlib import Path
from typing import Any, Callable, Coroutine
@@ -30,9 +31,13 @@ def _compute_next_run(schedule: CronSchedule, now_ms: int) -> int | None:
if schedule.kind == "cron" and schedule.expr:
try:
from croniter import croniter
cron = croniter(schedule.expr, time.time())
next_time = cron.get_next()
return int(next_time * 1000)
from zoneinfo import ZoneInfo
base_time = time.time()
tz = ZoneInfo(schedule.tz) if schedule.tz else datetime.now().astimezone().tzinfo
base_dt = datetime.fromtimestamp(base_time, tz=tz)
cron = croniter(schedule.expr, base_dt)
next_dt = cron.get_next(datetime)
return int(next_dt.timestamp() * 1000)
except Exception:
return None
nanobot/providers/litellm_provider.py
+4
View File
@@ -122,6 +122,10 @@ class LiteLLMProvider(LLMProvider):
"""
model = self._resolve_model(model or self.default_model)
# Clamp max_tokens to at least 1 — negative or zero values cause
# LiteLLM to reject the request with "max_tokens must be at least 1".
max_tokens = max(1, max_tokens)
kwargs: dict[str, Any] = {
"model": model,
"messages": messages,
nanobot/providers/registry.py
+14
View File
@@ -62,6 +62,20 @@ class ProviderSpec:
PROVIDERS: tuple[ProviderSpec, ...] = (
# === Custom (user-provided OpenAI-compatible endpoint) =================
# No auto-detection — only activates when user explicitly configures "custom".
ProviderSpec(
name="custom",
keywords=(),
env_key="OPENAI_API_KEY",
display_name="Custom",
litellm_prefix="openai",
skip_prefixes=("openai/",),
is_gateway=True,
strip_model_prefix=True,
),
# === Gateways (detected by api_key / api_base, not model name) =========
# Gateways can route any model, so they win in fallback.
nanobot/session/manager.py
+30 -53
View File
@@ -15,15 +15,20 @@ from nanobot.utils.helpers import ensure_dir, safe_filename
class Session:
"""
A conversation session.
Stores messages in JSONL format for easy reading and persistence.
Important: Messages are append-only for LLM cache efficiency.
The consolidation process writes summaries to MEMORY.md/HISTORY.md
but does NOT modify the messages list or get_history() output.
"""
key: str # channel:chat_id
messages: list[dict[str, Any]] = field(default_factory=list)
created_at: datetime = field(default_factory=datetime.now)
updated_at: datetime = field(default_factory=datetime.now)
metadata: dict[str, Any] = field(default_factory=dict)
last_consolidated: int = 0 # Number of messages already consolidated to files
def add_message(self, role: str, content: str, **kwargs: Any) -> None:
"""Add a message to the session."""
@@ -36,35 +41,24 @@ class Session:
self.messages.append(msg)
self.updated_at = datetime.now()
def get_history(self, max_messages: int = 50) -> list[dict[str, Any]]:
"""
Get message history for LLM context.
Args:
max_messages: Maximum messages to return.
Returns:
List of messages in LLM format.
"""
# Get recent messages
recent = self.messages[-max_messages:] if len(self.messages) > max_messages else self.messages
# Convert to LLM format (just role and content)
return [{"role": m["role"], "content": m["content"]} for m in recent]
def get_history(self, max_messages: int = 500) -> list[dict[str, Any]]:
"""Get recent messages in LLM format (role + content only)."""
return [{"role": m["role"], "content": m["content"]} for m in self.messages[-max_messages:]]
def clear(self) -> None:
"""Clear all messages in the session."""
"""Clear all messages and reset session to initial state."""
self.messages = []
self.last_consolidated = 0
self.updated_at = datetime.now()
class SessionManager:
"""
Manages conversation sessions.
Sessions are stored as JSONL files in the sessions directory.
"""
def __init__(self, workspace: Path):
self.workspace = workspace
self.sessions_dir = ensure_dir(Path.home() / ".nanobot" / "sessions")
@@ -85,11 +79,9 @@ class SessionManager:
Returns:
The session.
"""
# Check cache
if key in self._cache:
return self._cache[key]
# Try to load from disk
session = self._load(key)
if session is None:
session = Session(key=key)
@@ -100,34 +92,37 @@ class SessionManager:
def _load(self, key: str) -> Session | None:
"""Load a session from disk."""
path = self._get_session_path(key)
if not path.exists():
return None
try:
messages = []
metadata = {}
created_at = None
last_consolidated = 0
with open(path) as f:
for line in f:
line = line.strip()
if not line:
continue
data = json.loads(line)
if data.get("_type") == "metadata":
metadata = data.get("metadata", {})
created_at = datetime.fromisoformat(data["created_at"]) if data.get("created_at") else None
last_consolidated = data.get("last_consolidated", 0)
else:
messages.append(data)
return Session(
key=key,
messages=messages,
created_at=created_at or datetime.now(),
metadata=metadata
metadata=metadata,
last_consolidated=last_consolidated
)
except Exception as e:
logger.warning(f"Failed to load session {key}: {e}")
@@ -136,42 +131,24 @@ class SessionManager:
def save(self, session: Session) -> None:
"""Save a session to disk."""
path = self._get_session_path(session.key)
with open(path, "w") as f:
# Write metadata first
metadata_line = {
"_type": "metadata",
"created_at": session.created_at.isoformat(),
"updated_at": session.updated_at.isoformat(),
"metadata": session.metadata
"metadata": session.metadata,
"last_consolidated": session.last_consolidated
}
f.write(json.dumps(metadata_line) + "\n")
# Write messages
for msg in session.messages:
f.write(json.dumps(msg) + "\n")
self._cache[session.key] = session
def delete(self, key: str) -> bool:
"""
Delete a session.
Args:
key: Session key.
Returns:
True if deleted, False if not found.
"""
# Remove from cache
def invalidate(self, key: str) -> None:
"""Remove a session from the in-memory cache."""
self._cache.pop(key, None)
# Remove file
path = self._get_session_path(key)
if path.exists():
path.unlink()
return True
return False
def list_sessions(self) -> list[dict[str, Any]]:
"""
nanobot/skills/cron/SKILL.md
+8 -1
View File
@@ -7,10 +7,11 @@ description: Schedule reminders and recurring tasks.
Use the `cron` tool to schedule reminders or recurring tasks.
## Two Modes
## Three Modes
1. **Reminder** - message is sent directly to user
2. **Task** - message is a task description, agent executes and sends result
3. **One-time** - runs once at a specific time, then auto-deletes
## Examples
@@ -24,6 +25,11 @@ Dynamic task (agent executes each time):
cron(action="add", message="Check HKUDS/nanobot GitHub stars and report", every_seconds=600)
```
One-time scheduled task (compute ISO datetime from current time):
```
cron(action="add", message="Remind me about the meeting", at="<ISO datetime>")
```
List/remove:
```
cron(action="list")
@@ -38,3 +44,4 @@ cron(action="remove", job_id="abc123")
| every hour | every_seconds: 3600 |
| every day at 8am | cron_expr: "0 8 * * *" |
| weekdays at 5pm | cron_expr: "0 17 * * 1-5" |
| at a specific time | at: ISO datetime string (compute from current time) |
nanobot/skills/memory/SKILL.md
+31
View File
@@ -0,0 +1,31 @@
---
name: memory
description: Two-layer memory system with grep-based recall.
always: true
---
# Memory
## Structure
- `memory/MEMORY.md` — Long-term facts (preferences, project context, relationships). Always loaded into your context.
- `memory/HISTORY.md` — Append-only event log. NOT loaded into context. Search it with grep.
## Search Past Events
```bash
grep -i "keyword" memory/HISTORY.md
```
Use the `exec` tool to run grep. Combine patterns: `grep -iE "meeting|deadline" memory/HISTORY.md`
## When to Update MEMORY.md
Write important facts immediately using `edit_file` or `write_file`:
- User preferences ("I prefer dark mode")
- Project context ("The API uses OAuth2")
- Relationships ("Alice is the project lead")
## Auto-consolidation
Old conversations are automatically summarized and appended to HISTORY.md when the session grows large. Long-term facts are extracted to MEMORY.md. You don't need to manage this.
nanobot/utils/helpers.py
-11
View File
@@ -37,23 +37,12 @@ def get_sessions_path() -> Path:
return ensure_dir(get_data_path() / "sessions")
def get_memory_path(workspace: Path | None = None) -> Path:
"""Get the memory directory within the workspace."""
ws = workspace or get_workspace_path()
return ensure_dir(ws / "memory")
def get_skills_path(workspace: Path | None = None) -> Path:
"""Get the skills directory within the workspace."""
ws = workspace or get_workspace_path()
return ensure_dir(ws / "skills")
def today_date() -> str:
"""Get today's date in YYYY-MM-DD format."""
return datetime.now().strftime("%Y-%m-%d")
def timestamp() -> str:
"""Get current timestamp in ISO format."""
return datetime.now().isoformat()