Rebase onto upstream (a4d95fd) #12

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wylab wants to merge 144 commits from rebase-onto-upstream into main
2 changed files with 486 additions and 523 deletions
Showing only changes of commit 8940b97a1f - Show all commits
+433 -344
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@@ -1,34 +1,27 @@
"""Agent loop: the core processing engine."""
from __future__ import annotations
import asyncio
import json
import re
from contextlib import AsyncExitStack
import time
from pathlib import Path
from typing import TYPE_CHECKING, Any, Awaitable, Callable
from typing import Any
from loguru import logger
from nanobot.agent.context import ContextBuilder
from nanobot.agent.memory import MemoryStore
from nanobot.agent.subagent import SubagentManager
from nanobot.agent.tools.cron import CronTool
from nanobot.agent.tools.filesystem import EditFileTool, ListDirTool, ReadFileTool, WriteFileTool
from nanobot.agent.tools.message import MessageTool
from nanobot.agent.tools.registry import ToolRegistry
from nanobot.agent.tools.shell import ExecTool
from nanobot.agent.tools.spawn import SpawnTool
from nanobot.agent.tools.web import WebFetchTool, WebSearchTool
from nanobot.bus.events import InboundMessage, OutboundMessage
from nanobot.bus.queue import MessageBus
from nanobot.providers.base import LLMProvider
from nanobot.session.manager import Session, SessionManager
if TYPE_CHECKING:
from nanobot.config.schema import ChannelsConfig, ExecToolConfig
from nanobot.cron.service import CronService
from nanobot.agent.context import ContextBuilder
from nanobot.agent.tools.registry import ToolRegistry
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
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
class AgentLoop:
@@ -43,35 +36,27 @@ class AgentLoop:
5. Sends responses back
"""
_TOOL_RESULT_MAX_CHARS = 500
def __init__(
self,
bus: MessageBus,
provider: LLMProvider,
workspace: Path,
model: str | None = None,
max_iterations: int = 40,
temperature: float = 0.1,
max_tokens: int = 4096,
memory_window: int = 100,
max_iterations: int = 20,
memory_window: int = 50,
brave_api_key: str | None = None,
exec_config: ExecToolConfig | None = None,
cron_service: CronService | None = None,
exec_config: "ExecToolConfig | None" = None,
cron_service: "CronService | None" = None,
restrict_to_workspace: bool = False,
session_manager: SessionManager | None = None,
mcp_servers: dict | None = None,
channels_config: ChannelsConfig | None = None,
):
from nanobot.config.schema import ExecToolConfig
from nanobot.cron.service import CronService
self.bus = bus
self.channels_config = channels_config
self.provider = provider
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()
@@ -86,96 +71,238 @@ 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,
)
self._running = False
self._mcp_servers = mcp_servers or {}
self._mcp_stack: AsyncExitStack | None = None
self._mcp_connected = False
self._mcp_connecting = False
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._quota_cache: dict[str, Any] = {} # {model: str, cached_at: float}
self._quota_cache_ttl: float = 300.0 # 5 minutes
self._register_default_tools()
def _register_default_tools(self) -> None:
"""Register the default set of tools."""
# File tools (restrict to workspace if configured)
allowed_dir = self.workspace if self.restrict_to_workspace else None
for cls in (ReadFileTool, WriteFileTool, EditFileTool, ListDirTool):
self.tools.register(cls(workspace=self.workspace, allowed_dir=allowed_dir))
self.tools.register(ReadFileTool(allowed_dir=allowed_dir))
self.tools.register(WriteFileTool(allowed_dir=allowed_dir))
self.tools.register(EditFileTool(allowed_dir=allowed_dir))
self.tools.register(ListDirTool(allowed_dir=allowed_dir))
# Shell tool
self.tools.register(ExecTool(
working_dir=str(self.workspace),
timeout=self.exec_config.timeout,
restrict_to_workspace=self.restrict_to_workspace,
path_append=self.exec_config.path_append,
))
# Web tools
self.tools.register(WebSearchTool(api_key=self.brave_api_key))
self.tools.register(WebFetchTool())
self.tools.register(MessageTool(send_callback=self.bus.publish_outbound))
self.tools.register(SpawnTool(manager=self.subagents))
# Message tool
message_tool = MessageTool(send_callback=self.bus.publish_outbound)
self.tools.register(message_tool)
# Spawn tool (for subagents)
spawn_tool = SpawnTool(manager=self.subagents)
self.tools.register(spawn_tool)
# Cron tool (for scheduling)
if self.cron_service:
self.tools.register(CronTool(self.cron_service))
async def _connect_mcp(self) -> None:
"""Connect to configured MCP servers (one-time, lazy)."""
if self._mcp_connected or self._mcp_connecting or not self._mcp_servers:
return
self._mcp_connecting = True
from nanobot.agent.tools.mcp import connect_mcp_servers
async def run(self) -> None:
"""Run the agent loop, processing messages from the bus."""
self._running = True
logger.info("Agent loop started")
while self._running:
try:
self._mcp_stack = AsyncExitStack()
await self._mcp_stack.__aenter__()
await connect_mcp_servers(self._mcp_servers, self.tools, self._mcp_stack)
self._mcp_connected = True
# 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("Failed to connect MCP servers (will retry next message): {}", e)
if self._mcp_stack:
logger.error(f"Error processing message: {e}")
# Send error response
await self.bus.publish_outbound(OutboundMessage(
channel=msg.channel,
chat_id=msg.chat_id,
content=f"Sorry, I encountered an error: {str(e)}"
))
except asyncio.TimeoutError:
continue
def stop(self) -> None:
"""Stop the agent loop."""
self._running = False
logger.info("Agent loop stopping")
def _select_model_based_on_quota(self) -> str:
"""Select Opus or Sonnet based on rolling weekly quota burn rate."""
# Check cache
now = time.time()
if self._quota_cache and (now - self._quota_cache.get("cached_at", 0)) < self._quota_cache_ttl:
return self._quota_cache["model"]
# Default models
OPUS = "claude-opus-4-6"
SONNET = "claude-sonnet-4-5"
TOLERANCE = 1.17 # 17% overage triggers downgrade
# Read rate limits
rate_limits_path = self.workspace / "memory" / "rate_limits.json"
if not rate_limits_path.exists():
logger.warning("rate_limits.json not found, defaulting to Sonnet")
return SONNET
try:
await self._mcp_stack.aclose()
except Exception:
pass
self._mcp_stack = None
finally:
self._mcp_connecting = False
with open(rate_limits_path) as f:
limits = json.load(f)
def _set_tool_context(self, channel: str, chat_id: str, message_id: str | None = None) -> None:
"""Update context for all tools that need routing info."""
for name in ("message", "spawn", "cron"):
if tool := self.tools.get(name):
if hasattr(tool, "set_context"):
tool.set_context(channel, chat_id, *([message_id] if name == "message" else []))
actual_usage = limits.get("weekly_all_models")
weekly_reset = limits.get("weekly_reset")
@staticmethod
def _strip_think(text: str | None) -> str | None:
"""Remove <think>…</think> blocks that some models embed in content."""
if not text:
return None
return re.sub(r"<think>[\s\S]*?</think>", "", text).strip() or None
if actual_usage is None or weekly_reset is None:
logger.warning("Rate limit data incomplete, defaulting to Sonnet")
return SONNET
@staticmethod
def _tool_hint(tool_calls: list) -> str:
"""Format tool calls as concise hint, e.g. 'web_search("query")'."""
def _fmt(tc):
val = next(iter(tc.arguments.values()), None) if tc.arguments else None
if not isinstance(val, str):
return tc.name
return f'{tc.name}("{val[:40]}")' if len(val) > 40 else f'{tc.name}("{val}")'
return ", ".join(_fmt(tc) for tc in tool_calls)
# Calculate expected usage
actual_pct = actual_usage * 100
week_start = weekly_reset - (168 * 3600)
hours_elapsed = max(0, min((now - week_start) / 3600, 168))
expected_pct = (hours_elapsed / 168) * 100
threshold = expected_pct * TOLERANCE
async def _run_agent_loop(
self,
initial_messages: list[dict],
on_progress: Callable[..., Awaitable[None]] | None = None,
) -> tuple[str | None, list[str], list[dict]]:
"""Run the agent iteration loop. Returns (final_content, tools_used, messages)."""
messages = initial_messages
# Decision logic
if actual_pct > threshold:
model = SONNET
logger.info(
f"Quota: {actual_pct:.1f}% used, expected {expected_pct:.1f}%, "
f"threshold {threshold:.1f}% → Sonnet"
)
else:
model = OPUS
logger.info(
f"Quota: {actual_pct:.1f}% used, expected {expected_pct:.1f}%, "
f"threshold {threshold:.1f}% → Opus"
)
# Cache decision
self._quota_cache = {"model": model, "cached_at": now}
return model
except Exception as e:
logger.error(f"Error checking quota: {e}, defaulting to Sonnet")
return SONNET
def _get_quota_status(self) -> str:
"""Return human-readable quota status."""
rate_limits_path = self.workspace / "memory" / "rate_limits.json"
if not rate_limits_path.exists():
return "⚠️ No quota data available yet."
try:
with open(rate_limits_path) as f:
limits = json.load(f)
actual_pct = limits.get("weekly_all_models", 0) * 100
reset_ts = limits.get("weekly_reset", 0)
now = time.time()
hours_until_reset = (reset_ts - now) / 3600
week_start = reset_ts - (168 * 3600)
hours_elapsed = max(0, (now - week_start) / 3600)
expected_pct = (hours_elapsed / 168) * 100
model = self._select_model_based_on_quota()
return f"""📊 Quota Status:
• Used: {actual_pct:.1f}% (expected {expected_pct:.1f}%)
• Resets in: {hours_until_reset:.1f}h
• Current model: {model}
• Burn rate: {actual_pct / max(expected_pct, 0.01):.2f}x target"""
except Exception as e:
return f"⚠️ Error reading quota: {e}"
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
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
key = session_key or msg.session_key
session = self.sessions.get_or_create(key)
# Handle slash commands
cmd = msg.content.strip().lower()
if cmd == "/new":
await self._consolidate_memory(session, archive_all=True)
session.clear()
self.sessions.save(session)
return OutboundMessage(channel=msg.channel, chat_id=msg.chat_id,
content="🐈 New session started. Memory consolidated.")
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\n/quota — Show quota status")
if cmd == "/quota":
status = self._get_quota_status()
return OutboundMessage(channel=msg.channel, chat_id=msg.chat_id, content=status)
# Consolidate memory before processing if session is too large
if len(session.messages) > self.memory_window:
await self._consolidate_memory(session)
# Update tool contexts
message_tool = self.tools.get("message")
if isinstance(message_tool, MessageTool):
message_tool.set_context(msg.channel, msg.chat_id)
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(),
current_message=msg.content,
media=msg.media if msg.media else None,
channel=msg.channel,
chat_id=msg.chat_id,
)
# Select model based on quota
selected_model = self._select_model_based_on_quota()
# Agent loop
iteration = 0
final_content = None
tools_used: list[str] = []
@@ -183,28 +310,136 @@ class AgentLoop:
while iteration < self.max_iterations:
iteration += 1
# Call LLM
response = await self.provider.chat(
messages=messages,
tools=self.tools.get_definitions(),
model=self.model,
temperature=self.temperature,
max_tokens=self.max_tokens,
model=selected_model
)
# Handle tool calls
if response.has_tool_calls:
if on_progress:
clean = self._strip_think(response.content)
if clean:
await on_progress(clean)
await on_progress(self._tool_hint(response.tool_calls), tool_hint=True)
# Add assistant message with tool calls
tool_call_dicts = [
{
"id": tc.id,
"type": "function",
"function": {
"name": tc.name,
"arguments": json.dumps(tc.arguments, ensure_ascii=False)
"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:
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
)
# Interleaved CoT: reflect before next action
messages.append({"role": "user", "content": "Reflect on the results and decide next steps."})
else:
# No tool calls, we're done
final_content = response.content
break
if final_content is None:
if iteration >= self.max_iterations:
final_content = f"Reached {self.max_iterations} iterations without completion."
else:
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 (include tool names so consolidation sees what happened)
session.add_message("user", msg.content)
session.add_message("assistant", final_content,
tools_used=tools_used if tools_used else None)
self.sessions.save(session)
return OutboundMessage(
channel=msg.channel,
chat_id=msg.chat_id,
content=final_content,
metadata=msg.metadata or {}, # Pass through for channel-specific needs (e.g. Slack thread_ts)
)
async def _process_system_message(self, msg: InboundMessage) -> OutboundMessage | None:
"""
Process a system message (e.g., subagent announce).
The chat_id field contains "original_channel:original_chat_id" to route
the response back to the correct destination.
"""
logger.info(f"Processing system message from {msg.sender_id}")
# Parse origin from chat_id (format: "channel:chat_id")
if ":" in msg.chat_id:
parts = msg.chat_id.split(":", 1)
origin_channel = parts[0]
origin_chat_id = parts[1]
else:
# Fallback
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(),
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
@@ -215,258 +450,97 @@ class AgentLoop:
)
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("Tool call: {}({})", tool_call.name, args_str[:200])
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
)
# Interleaved CoT: reflect before next action
messages.append({"role": "user", "content": "Reflect on the results and decide next steps."})
else:
clean = self._strip_think(response.content)
messages = self.context.add_assistant_message(
messages, clean, reasoning_content=response.reasoning_content,
)
final_content = clean
final_content = response.content
break
if final_content is None and iteration >= self.max_iterations:
logger.warning("Max iterations ({}) reached", self.max_iterations)
final_content = (
f"I reached the maximum number of tool call iterations ({self.max_iterations}) "
"without completing the task. You can try breaking the task into smaller steps."
)
return final_content, tools_used, messages
async def run(self) -> None:
"""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)
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:
try:
await self._mcp_stack.aclose()
except (RuntimeError, BaseExceptionGroup):
pass # MCP SDK cancel scope cleanup is noisy but harmless
self._mcp_stack = None
def stop(self) -> None:
"""Stop the agent loop."""
self._running = False
logger.info("Agent loop stopping")
async def _process_message(
self,
msg: InboundMessage,
session_key: str | None = None,
on_progress: Callable[[str], Awaitable[None]] | None = None,
) -> OutboundMessage | None:
"""Process a single inbound message and return the response."""
# System messages: parse origin from chat_id ("channel:chat_id")
if msg.channel == "system":
channel, chat_id = (msg.chat_id.split(":", 1) if ":" in msg.chat_id
else ("cli", msg.chat_id))
logger.info("Processing system message from {}", msg.sender_id)
key = f"{channel}:{chat_id}"
session = self.sessions.get_or_create(key)
self._set_tool_context(channel, chat_id, msg.metadata.get("message_id"))
history = session.get_history(max_messages=self.memory_window)
messages = self.context.build_messages(
history=history,
current_message=msg.content, channel=channel, chat_id=chat_id,
)
final_content, _, all_msgs = await self._run_agent_loop(messages)
self._save_turn(session, all_msgs, 1 + len(history))
self.sessions.save(session)
return OutboundMessage(channel=channel, chat_id=chat_id,
content=final_content or "Background task completed.")
preview = msg.content[:80] + "..." if len(msg.content) > 80 else msg.content
logger.info("Processing message from {}:{}: {}", msg.channel, msg.sender_id, preview)
key = session_key or msg.session_key
session = self.sessions.get_or_create(key)
# Slash commands
cmd = msg.content.strip().lower()
if cmd == "/new":
lock = self._consolidation_locks.setdefault(session.key, asyncio.Lock())
self._consolidating.add(session.key)
try:
async with lock:
snapshot = session.messages[session.last_consolidated:]
if snapshot:
temp = Session(key=session.key)
temp.messages = list(snapshot)
if not await self._consolidate_memory(temp, archive_all=True):
return OutboundMessage(
channel=msg.channel, chat_id=msg.chat_id,
content="Memory archival failed, session not cleared. Please try again.",
)
except Exception:
logger.exception("/new archival failed for {}", session.key)
return OutboundMessage(
channel=msg.channel, chat_id=msg.chat_id,
content="Memory archival failed, session not cleared. Please try again.",
)
finally:
self._consolidating.discard(session.key)
if not lock.locked():
self._consolidation_locks.pop(session.key, None)
session.clear()
self.sessions.save(session)
self.sessions.invalidate(session.key)
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,
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):
self._consolidating.add(session.key)
lock = self._consolidation_locks.setdefault(session.key, asyncio.Lock())
async def _consolidate_and_unlock():
try:
async with lock:
await self._consolidate_memory(session)
finally:
self._consolidating.discard(session.key)
if not lock.locked():
self._consolidation_locks.pop(session.key, None)
_task = asyncio.current_task()
if _task is not None:
self._consolidation_tasks.discard(_task)
_task = asyncio.create_task(_consolidate_and_unlock())
self._consolidation_tasks.add(_task)
self._set_tool_context(msg.channel, msg.chat_id, msg.metadata.get("message_id"))
if message_tool := self.tools.get("message"):
if isinstance(message_tool, MessageTool):
message_tool.start_turn()
history = session.get_history(max_messages=self.memory_window)
initial_messages = self.context.build_messages(
history=history,
current_message=msg.content,
media=msg.media if msg.media else None,
channel=msg.channel, chat_id=msg.chat_id,
)
async def _bus_progress(content: str, *, tool_hint: bool = False) -> None:
meta = dict(msg.metadata or {})
meta["_progress"] = True
meta["_tool_hint"] = tool_hint
await self.bus.publish_outbound(OutboundMessage(
channel=msg.channel, chat_id=msg.chat_id, content=content, metadata=meta,
))
final_content, _, all_msgs = await self._run_agent_loop(
initial_messages, on_progress=on_progress or _bus_progress,
)
if final_content is None:
final_content = "I've completed processing but have no response to give."
final_content = "Background task completed."
self._save_turn(session, all_msgs, 1 + len(history))
# 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)
if (mt := self.tools.get("message")) and isinstance(mt, MessageTool) and mt._sent_in_turn:
return None
preview = final_content[:120] + "..." if len(final_content) > 120 else final_content
logger.info("Response to {}:{}: {}", msg.channel, msg.sender_id, preview)
return OutboundMessage(
channel=msg.channel, chat_id=msg.chat_id, content=final_content,
metadata=msg.metadata or {},
channel=origin_channel,
chat_id=origin_chat_id,
content=final_content
)
def _save_turn(self, session: Session, messages: list[dict], skip: int) -> None:
"""Save new-turn messages into session, truncating large tool results."""
from datetime import datetime
for m in messages[skip:]:
entry = {k: v for k, v in m.items() if k != "reasoning_content"}
role, content = entry.get("role"), entry.get("content")
if role == "tool" and isinstance(content, str) and len(content) > self._TOOL_RESULT_MAX_CHARS:
entry["content"] = content[:self._TOOL_RESULT_MAX_CHARS] + "\n... (truncated)"
elif role == "user":
if isinstance(content, str) and content.startswith(ContextBuilder._RUNTIME_CONTEXT_TAG):
async def _consolidate_memory(self, session, archive_all: bool = False) -> None:
"""Consolidate old messages into MEMORY.md + HISTORY.md, then trim session."""
if not session.messages:
return
memory = MemoryStore(self.workspace)
if archive_all:
old_messages = session.messages
keep_count = 0
else:
keep_count = min(10, max(2, self.memory_window // 2))
old_messages = session.messages[:-keep_count]
if not old_messages:
return
logger.info(f"Memory consolidation started: {len(session.messages)} messages, archiving {len(old_messages)}, keeping {keep_count}")
# Format messages for LLM (include tool names when available)
lines = []
for m in old_messages:
if not m.get("content"):
continue
if isinstance(content, list):
entry["content"] = [
{"type": "text", "text": "[image]"} if (
c.get("type") == "image_url"
and c.get("image_url", {}).get("url", "").startswith("data:image/")
) else c for c in content
]
entry.setdefault("timestamp", datetime.now().isoformat())
session.messages.append(entry)
session.updated_at = datetime.now()
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()
async def _consolidate_memory(self, session, archive_all: bool = False) -> bool:
"""Delegate to MemoryStore.consolidate(). Returns True on success."""
return await MemoryStore(self.workspace).consolidate(
session, self.provider, self.model,
archive_all=archive_all, memory_window=self.memory_window,
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="claude-haiku-4-5",
thinking_budget=0,
max_tokens=16384,
)
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)
session.messages = session.messages[-keep_count:] if keep_count else []
self.sessions.save(session)
logger.info(f"Memory consolidation done, session trimmed to {len(session.messages)} messages")
except Exception as e:
logger.error(f"Memory consolidation failed: {e}")
async def process_direct(
self,
@@ -474,10 +548,25 @@ class AgentLoop:
session_key: str = "cli:direct",
channel: str = "cli",
chat_id: str = "direct",
on_progress: Callable[[str], Awaitable[None]] | None = None,
) -> str:
"""Process a message directly (for CLI or cron usage)."""
await self._connect_mcp()
msg = InboundMessage(channel=channel, sender_id="user", chat_id=chat_id, content=content)
response = await self._process_message(msg, session_key=session_key, on_progress=on_progress)
"""
Process a message directly (for CLI or cron usage).
Args:
content: The message content.
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.
"""
msg = InboundMessage(
channel=channel,
sender_id="user",
chat_id=chat_id,
content=content
)
response = await self._process_message(msg, session_key=session_key)
return response.content if response else ""
+33 -159
View File
@@ -5,7 +5,7 @@ from __future__ import annotations
import asyncio
import re
from loguru import logger
from telegram import BotCommand, Update, ReplyParameters
from telegram import BotCommand, Update
from telegram.ext import Application, CommandHandler, MessageHandler, filters, ContextTypes
from telegram.request import HTTPXRequest
@@ -78,26 +78,6 @@ def _markdown_to_telegram_html(text: str) -> str:
return text
def _split_message(content: str, max_len: int = 4000) -> list[str]:
"""Split content into chunks within max_len, preferring line breaks."""
if len(content) <= max_len:
return [content]
chunks: list[str] = []
while content:
if len(content) <= max_len:
chunks.append(content)
break
cut = content[:max_len]
pos = cut.rfind('\n')
if pos == -1:
pos = cut.rfind(' ')
if pos == -1:
pos = max_len
chunks.append(content[:pos])
content = content[pos:].lstrip()
return chunks
class TelegramChannel(BaseChannel):
"""
Telegram channel using long polling.
@@ -111,8 +91,8 @@ 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"),
BotCommand("quota", "Show current quota status"),
]
def __init__(
@@ -127,8 +107,6 @@ class TelegramChannel(BaseChannel):
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
self._media_group_buffers: dict[str, dict] = {}
self._media_group_tasks: dict[str, asyncio.Task] = {}
async def start(self) -> None:
"""Start the Telegram bot with long polling."""
@@ -149,7 +127,8 @@ class TelegramChannel(BaseChannel):
# Add command handlers
self._app.add_handler(CommandHandler("start", self._on_start))
self._app.add_handler(CommandHandler("new", self._forward_command))
self._app.add_handler(CommandHandler("help", self._on_help))
self._app.add_handler(CommandHandler("help", self._forward_command))
self._app.add_handler(CommandHandler("quota", self._forward_command))
# Add message handler for text, photos, voice, documents
self._app.add_handler(
@@ -168,13 +147,13 @@ class TelegramChannel(BaseChannel):
# Get bot info and register command menu
bot_info = await self._app.bot.get_me()
logger.info("Telegram bot @{} connected", bot_info.username)
logger.info(f"Telegram bot @{bot_info.username} connected")
try:
await self._app.bot.set_my_commands(self.BOT_COMMANDS)
logger.debug("Telegram bot commands registered")
except Exception as e:
logger.warning("Failed to register bot commands: {}", e)
logger.warning(f"Failed to register bot commands: {e}")
# Start polling (this runs until stopped)
await self._app.updater.start_polling(
@@ -194,11 +173,6 @@ class TelegramChannel(BaseChannel):
for chat_id in list(self._typing_tasks):
self._stop_typing(chat_id)
for task in self._media_group_tasks.values():
task.cancel()
self._media_group_tasks.clear()
self._media_group_buffers.clear()
if self._app:
logger.info("Stopping Telegram bot...")
await self._app.updater.stop()
@@ -206,87 +180,37 @@ class TelegramChannel(BaseChannel):
await self._app.shutdown()
self._app = None
@staticmethod
def _get_media_type(path: str) -> str:
"""Guess media type from file extension."""
ext = path.rsplit(".", 1)[-1].lower() if "." in path else ""
if ext in ("jpg", "jpeg", "png", "gif", "webp"):
return "photo"
if ext == "ogg":
return "voice"
if ext in ("mp3", "m4a", "wav", "aac"):
return "audio"
return "document"
async def send(self, msg: OutboundMessage) -> None:
"""Send a message through Telegram."""
if not self._app:
logger.warning("Telegram bot not running")
return
# Stop typing indicator for this chat
self._stop_typing(msg.chat_id)
try:
# chat_id should be the Telegram chat ID (integer)
chat_id = int(msg.chat_id)
# Convert markdown to Telegram HTML
html_content = _markdown_to_telegram_html(msg.content)
await self._app.bot.send_message(
chat_id=chat_id,
text=html_content,
parse_mode="HTML"
)
except ValueError:
logger.error("Invalid chat_id: {}", msg.chat_id)
return
reply_params = None
if self.config.reply_to_message:
reply_to_message_id = msg.metadata.get("message_id")
if reply_to_message_id:
reply_params = ReplyParameters(
message_id=reply_to_message_id,
allow_sending_without_reply=True
)
# Send media files
for media_path in (msg.media or []):
try:
media_type = self._get_media_type(media_path)
sender = {
"photo": self._app.bot.send_photo,
"voice": self._app.bot.send_voice,
"audio": self._app.bot.send_audio,
}.get(media_type, self._app.bot.send_document)
param = "photo" if media_type == "photo" else media_type if media_type in ("voice", "audio") else "document"
with open(media_path, 'rb') as f:
await sender(
chat_id=chat_id,
**{param: f},
reply_parameters=reply_params
)
logger.error(f"Invalid chat_id: {msg.chat_id}")
except Exception as e:
filename = media_path.rsplit("/", 1)[-1]
logger.error("Failed to send media {}: {}", media_path, e)
await self._app.bot.send_message(
chat_id=chat_id,
text=f"[Failed to send: {filename}]",
reply_parameters=reply_params
)
# Send text content
if msg.content and msg.content != "[empty message]":
for chunk in _split_message(msg.content):
try:
html = _markdown_to_telegram_html(chunk)
await self._app.bot.send_message(
chat_id=chat_id,
text=html,
parse_mode="HTML",
reply_parameters=reply_params
)
except Exception as e:
logger.warning("HTML parse failed, falling back to plain text: {}", e)
# Fallback to plain text if HTML parsing fails
logger.warning(f"HTML parse failed, falling back to plain text: {e}")
try:
await self._app.bot.send_message(
chat_id=chat_id,
text=chunk,
reply_parameters=reply_params
chat_id=int(msg.chat_id),
text=msg.content
)
except Exception as e2:
logger.error("Error sending Telegram message: {}", e2)
logger.error(f"Error sending Telegram message: {e2}")
async def _on_start(self, update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Handle /start command."""
@@ -300,29 +224,12 @@ class TelegramChannel(BaseChannel):
"Type /help to see available commands."
)
async def _on_help(self, update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Handle /help command, bypassing ACL so all users can access it."""
if not update.message:
return
await update.message.reply_text(
"🐈 nanobot commands:\n"
"/new — Start a new conversation\n"
"/stop — Stop the current task\n"
"/help — Show available commands"
)
@staticmethod
def _sender_id(user) -> str:
"""Build sender_id with username for allowlist matching."""
sid = str(user.id)
return f"{sid}|{user.username}" if user.username else sid
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
await self._handle_message(
sender_id=self._sender_id(update.effective_user),
sender_id=str(update.effective_user.id),
chat_id=str(update.message.chat_id),
content=update.message.text,
)
@@ -335,7 +242,11 @@ class TelegramChannel(BaseChannel):
message = update.message
user = update.effective_user
chat_id = message.chat_id
sender_id = self._sender_id(user)
# Use stable numeric ID, but keep username for allowlist compatibility
sender_id = str(user.id)
if user.username:
sender_id = f"{sender_id}|{user.username}"
# Store chat_id for replies
self._chat_ids[sender_id] = chat_id
@@ -389,46 +300,24 @@ class TelegramChannel(BaseChannel):
transcriber = GroqTranscriptionProvider(api_key=self.groq_api_key)
transcription = await transcriber.transcribe(file_path)
if transcription:
logger.info("Transcribed {}: {}...", media_type, transcription[:50])
logger.info(f"Transcribed {media_type}: {transcription[:50]}...")
content_parts.append(f"[transcription: {transcription}]")
else:
content_parts.append(f"[{media_type}: {file_path}]")
else:
content_parts.append(f"[{media_type}: {file_path}]")
logger.debug("Downloaded {} to {}", media_type, file_path)
logger.debug(f"Downloaded {media_type} to {file_path}")
except Exception as e:
logger.error("Failed to download media: {}", e)
logger.error(f"Failed to download media: {e}")
content_parts.append(f"[{media_type}: download failed]")
content = "\n".join(content_parts) if content_parts else "[empty message]"
logger.debug("Telegram message from {}: {}...", sender_id, content[:50])
logger.debug(f"Telegram message from {sender_id}: {content[:50]}...")
str_chat_id = str(chat_id)
# Telegram media groups: buffer briefly, forward as one aggregated turn.
if media_group_id := getattr(message, "media_group_id", None):
key = f"{str_chat_id}:{media_group_id}"
if key not in self._media_group_buffers:
self._media_group_buffers[key] = {
"sender_id": sender_id, "chat_id": str_chat_id,
"contents": [], "media": [],
"metadata": {
"message_id": message.message_id, "user_id": user.id,
"username": user.username, "first_name": user.first_name,
"is_group": message.chat.type != "private",
},
}
self._start_typing(str_chat_id)
buf = self._media_group_buffers[key]
if content and content != "[empty message]":
buf["contents"].append(content)
buf["media"].extend(media_paths)
if key not in self._media_group_tasks:
self._media_group_tasks[key] = asyncio.create_task(self._flush_media_group(key))
return
# Start typing indicator before processing
self._start_typing(str_chat_id)
@@ -447,21 +336,6 @@ class TelegramChannel(BaseChannel):
}
)
async def _flush_media_group(self, key: str) -> None:
"""Wait briefly, then forward buffered media-group as one turn."""
try:
await asyncio.sleep(0.6)
if not (buf := self._media_group_buffers.pop(key, None)):
return
content = "\n".join(buf["contents"]) or "[empty message]"
await self._handle_message(
sender_id=buf["sender_id"], chat_id=buf["chat_id"],
content=content, media=list(dict.fromkeys(buf["media"])),
metadata=buf["metadata"],
)
finally:
self._media_group_tasks.pop(key, None)
def _start_typing(self, chat_id: str) -> None:
"""Start sending 'typing...' indicator for a chat."""
# Cancel any existing typing task for this chat
@@ -483,11 +357,11 @@ class TelegramChannel(BaseChannel):
except asyncio.CancelledError:
pass
except Exception as e:
logger.debug("Typing indicator stopped for {}: {}", chat_id, 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("Telegram error: {}", context.error)
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."""