321 lines
17 KiB
Python
321 lines
17 KiB
Python
import discord
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from discord.ext import commands
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import asyncio
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import os
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import json
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import aiohttp
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import random
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import time
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from collections import defaultdict, deque
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from typing import Dict, List, Any, Optional, Tuple, Set, Union
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# Third-party imports needed by the Cog itself or its direct methods
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from dotenv import load_dotenv
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from tavily import TavilyClient # Needed for tavily_client init
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# Interpreter and docker might only be needed by tools.py now
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# --- Relative Imports from Gurt Package ---
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from .config import (
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API_KEY, TAVILY_API_KEY, OPENROUTER_API_URL, DEFAULT_MODEL, FALLBACK_MODEL,
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DB_PATH, CHROMA_PATH, SEMANTIC_MODEL_NAME, MAX_USER_FACTS, MAX_GENERAL_FACTS,
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MOOD_OPTIONS, BASELINE_PERSONALITY, BASELINE_INTERESTS, MOOD_CHANGE_INTERVAL_MIN,
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MOOD_CHANGE_INTERVAL_MAX, CHANNEL_TOPIC_CACHE_TTL, CONTEXT_WINDOW_SIZE,
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API_TIMEOUT, SUMMARY_API_TIMEOUT, API_RETRY_ATTEMPTS, API_RETRY_DELAY,
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PROACTIVE_LULL_THRESHOLD, PROACTIVE_BOT_SILENCE_THRESHOLD, PROACTIVE_LULL_CHANCE,
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PROACTIVE_TOPIC_RELEVANCE_THRESHOLD, PROACTIVE_TOPIC_CHANCE,
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PROACTIVE_RELATIONSHIP_SCORE_THRESHOLD, PROACTIVE_RELATIONSHIP_CHANCE,
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INTEREST_UPDATE_INTERVAL, INTEREST_DECAY_INTERVAL_HOURS,
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LEARNING_UPDATE_INTERVAL, TOPIC_UPDATE_INTERVAL, SENTIMENT_UPDATE_INTERVAL,
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EVOLUTION_UPDATE_INTERVAL, RESPONSE_SCHEMA, TOOLS # Import necessary configs
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)
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# Import functions/classes from other modules
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from .memory import MemoryManager # Import from local memory.py
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from .background import background_processing_task
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from .commands import setup_commands # Import the setup helper
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from .listeners import on_ready_listener, on_message_listener, on_reaction_add_listener, on_reaction_remove_listener # Import listener functions
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from . import config as GurtConfig # Import config module for get_gurt_stats
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# Tool mapping is used internally by api.py/process_requested_tools, no need to import here directly unless cog methods call tools directly (they shouldn't)
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# Analysis, context, prompt, api, utils functions are called by listeners/commands/background task, not directly by cog methods here usually.
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# Load environment variables (might be loaded globally in main bot script too)
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load_dotenv()
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class GurtCog(commands.Cog, name="Gurt"): # Added explicit Cog name
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"""A special cog for the Gurt bot that uses OpenRouter API"""
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def __init__(self, bot):
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self.bot = bot
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self.api_key = API_KEY # Use imported config
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self.tavily_api_key = TAVILY_API_KEY # Use imported config
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self.api_url = OPENROUTER_API_URL # Use imported config
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self.session: Optional[aiohttp.ClientSession] = None # Initialize session as None
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self.tavily_client = TavilyClient(api_key=self.tavily_api_key) if self.tavily_api_key else None
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self.default_model = DEFAULT_MODEL # Use imported config
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self.fallback_model = FALLBACK_MODEL # Use imported config
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self.current_channel: Optional[Union[discord.TextChannel, discord.Thread, discord.DMChannel]] = None # Type hint current channel
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# Instantiate MemoryManager
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self.memory_manager = MemoryManager(
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db_path=DB_PATH,
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max_user_facts=MAX_USER_FACTS,
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max_general_facts=MAX_GENERAL_FACTS,
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chroma_path=CHROMA_PATH,
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semantic_model_name=SEMANTIC_MODEL_NAME
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)
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# --- State Variables ---
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# Keep state directly within the cog instance for now
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self.current_mood = random.choice(MOOD_OPTIONS)
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self.last_mood_change = time.time()
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self.needs_json_reminder = False # Flag to remind AI about JSON format
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# Learning variables (Consider moving to a dedicated state/learning manager later)
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self.conversation_patterns = defaultdict(list)
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self.user_preferences = defaultdict(dict)
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self.response_effectiveness = {}
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self.last_learning_update = time.time()
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# self.learning_update_interval = LEARNING_UPDATE_INTERVAL # Interval used in background task
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# Topic tracking
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self.active_topics = defaultdict(lambda: {
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"topics": [], "last_update": time.time(), "topic_history": [],
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"user_topic_interests": defaultdict(list)
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})
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# self.topic_update_interval = TOPIC_UPDATE_INTERVAL # Used in analysis
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# Conversation tracking / Caches
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self.conversation_history = defaultdict(lambda: deque(maxlen=100))
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self.thread_history = defaultdict(lambda: deque(maxlen=50))
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self.user_conversation_mapping = defaultdict(set)
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self.channel_activity = defaultdict(lambda: 0.0) # Use float for timestamp
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self.conversation_topics = defaultdict(str)
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self.user_relationships = defaultdict(dict)
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self.conversation_summaries: Dict[int, Dict[str, Any]] = {} # Store dict with summary and timestamp
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self.channel_topics_cache: Dict[int, Dict[str, Any]] = {} # Store dict with topic and timestamp
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# self.channel_topic_cache_ttl = CHANNEL_TOPIC_CACHE_TTL # Used in prompt building
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self.message_cache = {
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'by_channel': defaultdict(lambda: deque(maxlen=CONTEXT_WINDOW_SIZE)), # Use config
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'by_user': defaultdict(lambda: deque(maxlen=50)),
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'by_thread': defaultdict(lambda: deque(maxlen=50)),
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'global_recent': deque(maxlen=200),
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'mentioned': deque(maxlen=50),
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'replied_to': defaultdict(lambda: deque(maxlen=20))
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}
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self.active_conversations = {}
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self.bot_last_spoke = defaultdict(float)
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self.message_reply_map = {}
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# Enhanced sentiment tracking
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self.conversation_sentiment = defaultdict(lambda: {
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"overall": "neutral", "intensity": 0.5, "recent_trend": "stable",
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"user_sentiments": {}, "last_update": time.time()
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})
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self.sentiment_update_interval = SENTIMENT_UPDATE_INTERVAL # Used in analysis
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# Interest Tracking State
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self.gurt_participation_topics = defaultdict(int)
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self.last_interest_update = time.time()
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self.gurt_message_reactions = defaultdict(lambda: {"positive": 0, "negative": 0, "topic": None, "timestamp": 0.0}) # Added timestamp
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# Background task handle
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self.background_task: Optional[asyncio.Task] = None
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self.last_evolution_update = time.time() # Used in background task
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# --- Stats Tracking ---
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self.api_stats = defaultdict(lambda: {"success": 0, "failure": 0, "retries": 0, "total_time": 0.0, "count": 0}) # Keyed by model name
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self.tool_stats = defaultdict(lambda: {"success": 0, "failure": 0, "total_time": 0.0, "count": 0}) # Keyed by tool name
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# --- Setup Commands and Listeners ---
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# Add commands defined in commands.py
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setup_commands(self)
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# Add listeners defined in listeners.py
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# Note: Listeners need to be added to the bot instance, not the cog directly in this pattern.
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# We'll add them in cog_load or the main setup function.
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print("GurtCog initialized.")
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async def cog_load(self):
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"""Create aiohttp session, initialize DB, load baselines, start background task"""
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self.session = aiohttp.ClientSession()
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print("GurtCog: aiohttp session created")
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# Initialize DB via MemoryManager
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await self.memory_manager.initialize_sqlite_database()
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await self.memory_manager.load_baseline_personality(BASELINE_PERSONALITY)
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await self.memory_manager.load_baseline_interests(BASELINE_INTERESTS)
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if not self.api_key:
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print("WARNING: OpenRouter API key not configured (AI_API_KEY).")
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else:
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print(f"GurtCog: Using model: {self.default_model}")
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if not self.tavily_api_key:
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print("WARNING: Tavily API key not configured (TAVILY_API_KEY). Web search disabled.")
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# Add listeners to the bot instance
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# We need to define the listener functions here to properly register them
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@self.bot.event
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async def on_ready():
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await on_ready_listener(self)
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@self.bot.event
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async def on_message(message):
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await self.bot.process_commands(message) # Process commands first
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await on_message_listener(self, message)
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@self.bot.event
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async def on_reaction_add(reaction, user):
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await on_reaction_add_listener(self, reaction, user)
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@self.bot.event
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async def on_reaction_remove(reaction, user):
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await on_reaction_remove_listener(self, reaction, user)
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print("GurtCog: Listeners added.")
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# Start background task
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if self.background_task is None or self.background_task.done():
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self.background_task = asyncio.create_task(background_processing_task(self))
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print("GurtCog: Started background processing task.")
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else:
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print("GurtCog: Background processing task already running.")
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async def cog_unload(self):
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"""Close session and cancel background task"""
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if self.session and not self.session.closed:
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await self.session.close()
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print("GurtCog: aiohttp session closed")
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if self.background_task and not self.background_task.done():
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self.background_task.cancel()
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print("GurtCog: Cancelled background processing task.")
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# Note: When using @bot.event, we can't easily remove the listeners
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# The bot will handle this automatically when it's closed
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print("GurtCog: Listeners will be removed when bot is closed.")
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print("GurtCog unloaded.")
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# --- Helper methods that might remain in the cog ---
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# (Example: _update_relationship needs access to self.user_relationships)
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# Moved to utils.py, but needs access to cog state. Pass cog instance.
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def _update_relationship(self, user_id_1: str, user_id_2: str, change: float):
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"""Updates the relationship score between two users."""
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# This method accesses self.user_relationships, so it stays here or utils needs cog passed.
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# Let's keep it here for simplicity for now.
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if user_id_1 > user_id_2: user_id_1, user_id_2 = user_id_2, user_id_1
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if user_id_1 not in self.user_relationships: self.user_relationships[user_id_1] = {}
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current_score = self.user_relationships[user_id_1].get(user_id_2, 0.0)
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new_score = max(0.0, min(current_score + change, 100.0)) # Clamp 0-100
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self.user_relationships[user_id_1][user_id_2] = new_score
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# print(f"Updated relationship {user_id_1}-{user_id_2}: {current_score:.1f} -> {new_score:.1f} ({change:+.1f})") # Debug log
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async def get_gurt_stats(self) -> Dict[str, Any]:
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"""Collects various internal stats for Gurt."""
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stats = {"config": {}, "runtime": {}, "memory": {}, "api_stats": {}, "tool_stats": {}}
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# --- Config ---
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# Selectively pull relevant config values, avoid exposing secrets
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stats["config"]["default_model"] = GurtConfig.DEFAULT_MODEL
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stats["config"]["fallback_model"] = GurtConfig.FALLBACK_MODEL
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stats["config"]["safety_check_model"] = GurtConfig.SAFETY_CHECK_MODEL
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stats["config"]["db_path"] = GurtConfig.DB_PATH
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stats["config"]["chroma_path"] = GurtConfig.CHROMA_PATH
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stats["config"]["semantic_model_name"] = GurtConfig.SEMANTIC_MODEL_NAME
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stats["config"]["max_user_facts"] = GurtConfig.MAX_USER_FACTS
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stats["config"]["max_general_facts"] = GurtConfig.MAX_GENERAL_FACTS
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stats["config"]["mood_change_interval_min"] = GurtConfig.MOOD_CHANGE_INTERVAL_MIN
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stats["config"]["mood_change_interval_max"] = GurtConfig.MOOD_CHANGE_INTERVAL_MAX
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stats["config"]["evolution_update_interval"] = GurtConfig.EVOLUTION_UPDATE_INTERVAL
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stats["config"]["context_window_size"] = GurtConfig.CONTEXT_WINDOW_SIZE
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stats["config"]["api_timeout"] = GurtConfig.API_TIMEOUT
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stats["config"]["summary_api_timeout"] = GurtConfig.SUMMARY_API_TIMEOUT
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stats["config"]["proactive_lull_threshold"] = GurtConfig.PROACTIVE_LULL_THRESHOLD
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stats["config"]["proactive_bot_silence_threshold"] = GurtConfig.PROACTIVE_BOT_SILENCE_THRESHOLD
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stats["config"]["interest_update_interval"] = GurtConfig.INTEREST_UPDATE_INTERVAL
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stats["config"]["interest_decay_interval_hours"] = GurtConfig.INTEREST_DECAY_INTERVAL_HOURS
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stats["config"]["learning_update_interval"] = GurtConfig.LEARNING_UPDATE_INTERVAL
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stats["config"]["topic_update_interval"] = GurtConfig.TOPIC_UPDATE_INTERVAL
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stats["config"]["sentiment_update_interval"] = GurtConfig.SENTIMENT_UPDATE_INTERVAL
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stats["config"]["docker_command_timeout"] = GurtConfig.DOCKER_COMMAND_TIMEOUT
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stats["config"]["api_key_set"] = bool(GurtConfig.API_KEY) # Don't expose key itself
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stats["config"]["tavily_api_key_set"] = bool(GurtConfig.TAVILY_API_KEY)
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stats["config"]["piston_api_url_set"] = bool(GurtConfig.PISTON_API_URL)
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# --- Runtime ---
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stats["runtime"]["current_mood"] = self.current_mood
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stats["runtime"]["last_mood_change_timestamp"] = self.last_mood_change
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stats["runtime"]["needs_json_reminder"] = self.needs_json_reminder
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stats["runtime"]["last_learning_update_timestamp"] = self.last_learning_update
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stats["runtime"]["last_interest_update_timestamp"] = self.last_interest_update
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stats["runtime"]["last_evolution_update_timestamp"] = self.last_evolution_update
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stats["runtime"]["background_task_running"] = bool(self.background_task and not self.background_task.done())
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stats["runtime"]["active_topics_channels"] = len(self.active_topics)
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stats["runtime"]["conversation_history_channels"] = len(self.conversation_history)
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stats["runtime"]["thread_history_threads"] = len(self.thread_history)
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stats["runtime"]["user_conversation_mappings"] = len(self.user_conversation_mapping)
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stats["runtime"]["channel_activity_tracked"] = len(self.channel_activity)
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stats["runtime"]["conversation_topics_tracked"] = len(self.conversation_topics)
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stats["runtime"]["user_relationships_pairs"] = sum(len(v) for v in self.user_relationships.values())
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stats["runtime"]["conversation_summaries_cached"] = len(self.conversation_summaries)
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stats["runtime"]["channel_topics_cached"] = len(self.channel_topics_cache)
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stats["runtime"]["message_cache_global_count"] = len(self.message_cache['global_recent'])
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stats["runtime"]["message_cache_mentioned_count"] = len(self.message_cache['mentioned'])
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stats["runtime"]["active_conversations_count"] = len(self.active_conversations)
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stats["runtime"]["bot_last_spoke_channels"] = len(self.bot_last_spoke)
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stats["runtime"]["message_reply_map_size"] = len(self.message_reply_map)
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stats["runtime"]["conversation_sentiment_channels"] = len(self.conversation_sentiment)
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stats["runtime"]["gurt_participation_topics_count"] = len(self.gurt_participation_topics)
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stats["runtime"]["gurt_message_reactions_tracked"] = len(self.gurt_message_reactions)
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# --- Memory (via MemoryManager) ---
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try:
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# Personality
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personality = await self.memory_manager.get_all_personality_traits()
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stats["memory"]["personality_traits"] = personality
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# Interests
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interests = await self.memory_manager.get_interests(limit=20, min_level=0.01) # Get top 20
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stats["memory"]["top_interests"] = interests
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# Fact Counts (Requires adding methods to MemoryManager or direct query)
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# Example placeholder - needs implementation in MemoryManager or here
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user_fact_count = await self.memory_manager._db_fetchone("SELECT COUNT(*) FROM user_facts")
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general_fact_count = await self.memory_manager._db_fetchone("SELECT COUNT(*) FROM general_facts")
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stats["memory"]["user_facts_count"] = user_fact_count[0] if user_fact_count else 0
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stats["memory"]["general_facts_count"] = general_fact_count[0] if general_fact_count else 0
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# ChromaDB Stats (Placeholder - ChromaDB client API might offer this)
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stats["memory"]["chromadb_message_collection_count"] = await asyncio.to_thread(self.memory_manager.semantic_collection.count) if self.memory_manager.semantic_collection else "N/A"
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stats["memory"]["chromadb_fact_collection_count"] = await asyncio.to_thread(self.memory_manager.fact_collection.count) if self.memory_manager.fact_collection else "N/A"
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except Exception as e:
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stats["memory"]["error"] = f"Failed to retrieve memory stats: {e}"
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# --- API & Tool Stats ---
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# Convert defaultdicts to regular dicts for JSON serialization
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stats["api_stats"] = dict(self.api_stats)
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stats["tool_stats"] = dict(self.tool_stats)
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# Calculate average times where count > 0
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for model, data in stats["api_stats"].items():
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if data["count"] > 0:
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data["average_time_ms"] = round((data["total_time"] / data["count"]) * 1000, 2)
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else:
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data["average_time_ms"] = 0
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for tool, data in stats["tool_stats"].items():
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if data["count"] > 0:
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data["average_time_ms"] = round((data["total_time"] / data["count"]) * 1000, 2)
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else:
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data["average_time_ms"] = 0
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return stats
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# Setup function for loading the cog
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async def setup(bot):
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"""Add the GurtCog to the bot."""
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await bot.add_cog(GurtCog(bot))
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print("GurtCog setup complete.")
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