mirror of
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synced 2026-05-21 23:24:44 +02:00
Wire up all unused modules into main application lifecycle
- 2a: SafetyFilter + UserFilter — check user access before processing, filter LLM responses through SafetyFilter before sending - 2b: RateLimiter — check rate limits before processing, record messages after successful response delivery - 2c: PersonalityManager — pass to MessageRouter, used for system prompt generation instead of raw config.llm.system_prompt - 2d: WebhookClient — start/stop in lifecycle, fire events on message_received, response_sent, error, startup, shutdown - 2e: WebStatusServer — start/stop in lifecycle, record messages, responses, and errors in StatusData - 2f: AnnouncementScheduler — start/stop in lifecycle, uses connector.send_message as callback - 2g: FallbackBackend — wrap primary backend when config.llm.fallback is configured, otherwise use primary directly - 2h: CommandDispatcher — pass prefix, disabled_commands, and custom_commands from config to create_dispatcher() Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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2 changed files with 143 additions and 14 deletions
139
meshai/main.py
139
meshai/main.py
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@ -11,7 +11,8 @@ from pathlib import Path
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from typing import Optional
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from . import __version__
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from .backends import AnthropicBackend, GoogleBackend, LLMBackend, OpenAIBackend
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from .announcements import AnnouncementScheduler
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from .backends import AnthropicBackend, FallbackBackend, GoogleBackend, LLMBackend, OpenAIBackend
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from .cli import run_configurator
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from .commands import CommandDispatcher
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from .commands.dispatcher import create_dispatcher
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@ -20,8 +21,13 @@ from .config import Config, load_config
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from .connector import MeshConnector, MeshMessage
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from .history import ConversationHistory
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from .memory import ConversationSummary
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from .personality import PersonalityManager
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from .rate_limiter import RateLimiter
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from .responder import Responder
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from .router import MessageRouter, RouteType
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from .safety import SafetyFilter, UserFilter
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from .web_status import WebStatusServer, get_status_data
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from .webhook import WebhookClient
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logger = logging.getLogger(__name__)
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@ -37,6 +43,13 @@ class MeshAI:
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self.llm: Optional[LLMBackend] = None
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self.router: Optional[MessageRouter] = None
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self.responder: Optional[Responder] = None
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self.personality: Optional[PersonalityManager] = None
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self.safety_filter: Optional[SafetyFilter] = None
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self.user_filter: Optional[UserFilter] = None
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self.rate_limiter: Optional[RateLimiter] = None
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self.webhook: Optional[WebhookClient] = None
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self.web_status: Optional[WebStatusServer] = None
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self.announcements: Optional[AnnouncementScheduler] = None
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self._running = False
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self._loop: Optional[asyncio.AbstractEventLoop] = None
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self._last_cleanup: float = 0.0
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@ -57,6 +70,14 @@ class MeshAI:
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self._loop = asyncio.get_event_loop()
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self._last_cleanup = time.time()
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# Start async services
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await self.webhook.start()
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await self.webhook.on_startup()
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await self.announcements.start()
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# Start sync services
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self.web_status.start()
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# Write PID file
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self._write_pid()
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@ -76,6 +97,16 @@ class MeshAI:
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logger.info("Stopping MeshAI...")
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self._running = False
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if self.webhook:
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await self.webhook.on_shutdown()
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await self.webhook.stop()
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if self.announcements:
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await self.announcements.stop()
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if self.web_status:
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self.web_status.stop()
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if self.connector:
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self.connector.disconnect()
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@ -94,8 +125,30 @@ class MeshAI:
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self.history = ConversationHistory(self.config.history)
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await self.history.initialize()
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# Command dispatcher
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self.dispatcher = create_dispatcher()
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# Command dispatcher (2h: pass config)
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self.dispatcher = create_dispatcher(
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prefix=self.config.commands.prefix,
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disabled_commands=self.config.commands.disabled_commands,
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custom_commands=self.config.commands.custom_commands,
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)
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# Safety and user filters (2a)
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self.user_filter = UserFilter(
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blocklist=self.config.users.blocklist,
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allowlist=self.config.users.allowlist,
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allowlist_only=self.config.users.allowlist_only,
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admin_nodes=self.config.users.admin_nodes,
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)
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self.safety_filter = SafetyFilter(self.config.safety)
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# Rate limiter (2b)
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self.rate_limiter = RateLimiter(
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self.config.rate_limits,
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vip_nodes=self.config.users.vip_nodes,
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)
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# Personality manager (2c)
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self.personality = PersonalityManager(self.config.personality)
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# LLM backend
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api_key = self.config.resolve_api_key()
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@ -107,51 +160,100 @@ class MeshAI:
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window_size = mem_cfg.window_size if mem_cfg.enabled else 0
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summarize_threshold = mem_cfg.summarize_threshold
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# Create primary backend
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backend = self.config.llm.backend.lower()
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if backend == "openai":
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self.llm = OpenAIBackend(
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primary = OpenAIBackend(
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self.config.llm, api_key, window_size, summarize_threshold
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)
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elif backend == "anthropic":
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self.llm = AnthropicBackend(
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primary = AnthropicBackend(
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self.config.llm, api_key, window_size, summarize_threshold
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)
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elif backend == "google":
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self.llm = GoogleBackend(
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primary = GoogleBackend(
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self.config.llm, api_key, window_size, summarize_threshold
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)
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else:
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logger.warning(f"Unknown backend '{backend}', defaulting to OpenAI")
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self.llm = OpenAIBackend(
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primary = OpenAIBackend(
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self.config.llm, api_key, window_size, summarize_threshold
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)
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# Wrap in FallbackBackend if fallback is configured (2g)
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if self.config.llm.fallback:
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self.llm = FallbackBackend(
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self.config.llm, api_key, window_size, summarize_threshold
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)
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else:
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self.llm = primary
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# Load persisted summaries into memory cache
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await self._load_summaries()
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# Meshtastic connector
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self.connector = MeshConnector(self.config.connection)
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# Message router
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# Message router (pass personality manager)
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self.router = MessageRouter(
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self.config, self.connector, self.history, self.dispatcher, self.llm
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self.config, self.connector, self.history, self.dispatcher, self.llm,
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personality=self.personality,
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)
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# Responder
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self.responder = Responder(self.config.response, self.connector)
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# Webhook client (2d)
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self.webhook = WebhookClient(self.config.integrations.webhook)
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# Web status server (2e)
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self.web_status = WebStatusServer(self.config.web_status)
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# Announcement scheduler (2f)
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async def _send_announcement(text: str, channel: int) -> None:
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self.connector.send_message(text=text, channel=channel)
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self.announcements = AnnouncementScheduler(
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self.config.announcements,
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send_callback=_send_announcement,
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)
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async def _on_message(self, message: MeshMessage) -> None:
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"""Handle incoming message."""
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try:
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# Check user filter (2a)
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allowed, reason = self.user_filter.is_allowed(message.sender_id)
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if not allowed:
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logger.debug(f"Blocked message from {message.sender_id}: {reason}")
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return
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# Check if we should respond
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if not self.router.should_respond(message):
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return
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# Check rate limiter (2b)
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allowed, reason = self.rate_limiter.is_allowed(message.sender_id)
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if not allowed:
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logger.debug(f"Rate limited {message.sender_id}: {reason}")
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return
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logger.info(
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f"Processing message from {message.sender_name} ({message.sender_id}): "
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f"{message.text[:50]}..."
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)
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# Record in web status (2e)
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get_status_data().record_message(message.sender_id, message.sender_name)
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# Send webhook event (2d)
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await self.webhook.on_message_received(
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sender_id=message.sender_id,
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sender_name=message.sender_name,
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text=message.text,
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channel=message.channel,
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is_dm=message.is_dm,
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)
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# Route the message
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result = await self.router.route(message)
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@ -169,16 +271,18 @@ class MeshAI:
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if not response:
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return
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# Apply safety filter to LLM responses (2a)
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if result.route_type == RouteType.LLM:
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response = self.safety_filter.filter_response(response)
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# Send response
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if message.is_dm:
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# Reply as DM
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await self.responder.send_response(
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text=response,
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destination=message.sender_id,
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channel=message.channel,
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)
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else:
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# Reply on channel
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formatted = self.responder.format_channel_response(
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response, message.sender_name, mention_sender=True
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)
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@ -188,8 +292,21 @@ class MeshAI:
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channel=message.channel,
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)
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# Record response in rate limiter and status (2b, 2e)
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self.rate_limiter.record_message(message.sender_id)
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get_status_data().record_response()
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# Send webhook event (2d)
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await self.webhook.on_response_sent(
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recipient_id=message.sender_id if message.is_dm else None,
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text=response,
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channel=message.channel,
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)
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except Exception as e:
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logger.error(f"Error handling message: {e}", exc_info=True)
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get_status_data().record_error(str(e))
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await self.webhook.on_error(str(e))
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async def _load_summaries(self) -> None:
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"""Load persisted summaries from database into memory cache."""
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@ -11,6 +11,7 @@ from .commands import CommandContext, CommandDispatcher
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from .config import Config
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from .connector import MeshConnector, MeshMessage
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from .history import ConversationHistory
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from .personality import PersonalityManager
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logger = logging.getLogger(__name__)
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@ -42,12 +43,14 @@ class MessageRouter:
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history: ConversationHistory,
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dispatcher: CommandDispatcher,
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llm_backend: LLMBackend,
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personality: Optional[PersonalityManager] = None,
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):
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self.config = config
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self.connector = connector
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self.history = history
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self.dispatcher = dispatcher
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self.llm = llm_backend
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self.personality = personality
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# Compile mention pattern
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bot_name = re.escape(config.bot.name)
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@ -68,6 +71,10 @@ class MessageRouter:
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# Check if DM
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if message.is_dm:
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# In DMs, let commands through to dispatcher but skip !commands
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# that should be handled by other bots (like MeshMonitor)
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if self.dispatcher.is_command(message.text):
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return True
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return self.config.bot.respond_to_dms
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# Check channel filtering
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# Get conversation history
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history = await self.history.get_history_for_llm(message.sender_id)
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# Generate response with user_id for memory optimization
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# Use system prompt only if enabled in config
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# Get system prompt from personality manager or config
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system_prompt = ""
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if getattr(self.config.llm, 'use_system_prompt', True):
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if self.personality:
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system_prompt = self.personality.get_system_prompt(
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sender_name=message.sender_name,
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channel=message.channel,
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)
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else:
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system_prompt = self.config.llm.system_prompt
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try:
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