310 lines
17 KiB
Python
310 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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# --- Relative Imports from Wheatley Package ---
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from .config import (
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PROJECT_ID, LOCATION, TAVILY_API_KEY, DEFAULT_MODEL, FALLBACK_MODEL, # Use GCP config
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DB_PATH, CHROMA_PATH, SEMANTIC_MODEL_NAME, MAX_USER_FACTS, MAX_GENERAL_FACTS,
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# Removed Mood/Personality/Interest/Learning/Goal configs
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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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# Removed Relationship/Sentiment/Interest proactive configs
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TOPIC_UPDATE_INTERVAL, SENTIMENT_UPDATE_INTERVAL,
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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 # Keep background task for potential future use (e.g., cache cleanup)
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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 WheatleyConfig # Import config module for get_wheatley_stats
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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 WheatleyCog(commands.Cog, name="Wheatley"): # Renamed class and Cog name
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"""A special cog for the Wheatley bot that uses Google Vertex AI API""" # Updated docstring
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def __init__(self, bot):
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self.bot = bot
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# GCP Project/Location are used by vertexai.init() in api.py
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self.tavily_api_key = TAVILY_API_KEY # Use imported config
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self.session: Optional[aiohttp.ClientSession] = None # Keep for other potential HTTP requests (e.g., Piston)
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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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# Removed MOOD_OPTIONS
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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 (Simplified for Wheatley) ---
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# Removed mood, personality evolution, interest tracking, learning state
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self.needs_json_reminder = False # Flag to remind AI about JSON format
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# Topic tracking (Kept for context)
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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) # Kept for potential future analysis, not proactive triggers
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})
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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) # Simplified topic tracking
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self.user_relationships = defaultdict(dict) # Kept for potential context/analysis
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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.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 = {} # Kept for basic tracking
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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 (Kept for context/analysis)
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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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# Removed self.sentiment_update_interval as it was only used in analysis
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# Reaction Tracking (Renamed)
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self.wheatley_message_reactions = defaultdict(lambda: {"positive": 0, "negative": 0, "topic": None, "timestamp": 0.0}) # Renamed
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# Background task handle (Kept for potential future tasks like cache cleanup)
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self.background_task: Optional[asyncio.Task] = None
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self.last_stats_push = time.time() # Timestamp for last stats push
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# Removed evolution, reflection, goal timestamps
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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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self.command_functions = setup_commands(self)
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# Store command names for reference - safely handle Command objects
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self.registered_commands = []
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for func in self.command_functions:
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# For app commands, use the name attribute directly
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if hasattr(func, "name"):
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self.registered_commands.append(func.name)
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# For regular functions, use __name__
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elif hasattr(func, "__name__"):
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self.registered_commands.append(func.__name__)
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else:
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self.registered_commands.append(str(func))
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print(f"WheatleyCog initialized with commands: {self.registered_commands}") # Updated print
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async def cog_load(self):
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"""Create aiohttp session, initialize DB, start background task"""
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self.session = aiohttp.ClientSession()
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print("WheatleyCog: aiohttp session created") # Updated print
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# Initialize DB via MemoryManager
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await self.memory_manager.initialize_sqlite_database()
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# Removed loading of baseline personality and interests
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# Vertex AI initialization happens in api.py using PROJECT_ID and LOCATION from config
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print(f"WheatleyCog: Using default model: {self.default_model}") # Updated print
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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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# IMPORTANT: Don't override on_member_join or on_member_remove events
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# Check if the bot already has event listeners for member join/leave
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has_member_join = 'on_member_join' in self.bot.extra_events
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has_member_remove = 'on_member_remove' in self.bot.extra_events
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print(f"WheatleyCog: Bot already has event listeners - on_member_join: {has_member_join}, on_member_remove: {has_member_remove}")
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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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# Ensure commands are processed if using command prefix
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if message.content.startswith(self.bot.command_prefix):
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await self.bot.process_commands(message)
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# Always run the message listener for potential AI responses/tracking
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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("WheatleyCog: Listeners added.") # Updated print
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# Commands will be synced in on_ready
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print("WheatleyCog: Commands will be synced when the bot is ready.") # Updated print
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# Start background task (kept for potential future use)
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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("WheatleyCog: Started background processing task.") # Updated print
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else:
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print("WheatleyCog: Background processing task already running.") # Updated print
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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("WheatleyCog: aiohttp session closed") # Updated print
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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("WheatleyCog: Cancelled background processing task.") # Updated print
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print("WheatleyCog: Listeners will be removed when bot is closed.") # Updated print
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print("WheatleyCog unloaded.") # Updated print
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# --- Helper methods that might remain in the cog ---
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# _update_relationship kept for potential context/analysis use
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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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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_wheatley_stats(self) -> Dict[str, Any]: # Renamed method
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"""Collects various internal stats for Wheatley.""" # Updated docstring
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stats = {"config": {}, "runtime": {}, "memory": {}, "api_stats": {}, "tool_stats": {}}
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# --- Config (Simplified) ---
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stats["config"]["default_model"] = WheatleyConfig.DEFAULT_MODEL
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stats["config"]["fallback_model"] = WheatleyConfig.FALLBACK_MODEL
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stats["config"]["safety_check_model"] = WheatleyConfig.SAFETY_CHECK_MODEL
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stats["config"]["db_path"] = WheatleyConfig.DB_PATH
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stats["config"]["chroma_path"] = WheatleyConfig.CHROMA_PATH
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stats["config"]["semantic_model_name"] = WheatleyConfig.SEMANTIC_MODEL_NAME
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stats["config"]["max_user_facts"] = WheatleyConfig.MAX_USER_FACTS
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stats["config"]["max_general_facts"] = WheatleyConfig.MAX_GENERAL_FACTS
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stats["config"]["context_window_size"] = WheatleyConfig.CONTEXT_WINDOW_SIZE
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stats["config"]["api_timeout"] = WheatleyConfig.API_TIMEOUT
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stats["config"]["summary_api_timeout"] = WheatleyConfig.SUMMARY_API_TIMEOUT
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stats["config"]["proactive_lull_threshold"] = WheatleyConfig.PROACTIVE_LULL_THRESHOLD
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stats["config"]["proactive_bot_silence_threshold"] = WheatleyConfig.PROACTIVE_BOT_SILENCE_THRESHOLD
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stats["config"]["topic_update_interval"] = WheatleyConfig.TOPIC_UPDATE_INTERVAL
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stats["config"]["sentiment_update_interval"] = WheatleyConfig.SENTIMENT_UPDATE_INTERVAL
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stats["config"]["docker_command_timeout"] = WheatleyConfig.DOCKER_COMMAND_TIMEOUT
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stats["config"]["project_id_set"] = bool(WheatleyConfig.PROJECT_ID != "your-gcp-project-id")
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stats["config"]["location_set"] = bool(WheatleyConfig.LOCATION != "us-central1")
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stats["config"]["tavily_api_key_set"] = bool(WheatleyConfig.TAVILY_API_KEY)
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stats["config"]["piston_api_url_set"] = bool(WheatleyConfig.PISTON_API_URL)
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# --- Runtime (Simplified) ---
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# Removed mood, evolution
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stats["runtime"]["needs_json_reminder"] = self.needs_json_reminder
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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) # Simplified topic tracking
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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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# Removed Gurt participation topics
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stats["runtime"]["wheatley_message_reactions_tracked"] = len(self.wheatley_message_reactions) # Renamed
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# --- Memory (Simplified) ---
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try:
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# Removed Personality, Interests
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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
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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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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
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for model, data in stats["api_stats"].items():
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if data["count"] > 0: data["average_time_ms"] = round((data["total_time"] / data["count"]) * 1000, 2)
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else: 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: data["average_time_ms"] = round((data["total_time"] / data["count"]) * 1000, 2)
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else: data["average_time_ms"] = 0
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return stats
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async def sync_commands(self):
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"""Manually sync commands with Discord."""
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try:
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print("WheatleyCog: Manually syncing commands with Discord...") # Updated print
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synced = await self.bot.tree.sync()
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print(f"WheatleyCog: Synced {len(synced)} command(s)") # Updated print
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# List the synced commands
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wheatley_commands = [cmd.name for cmd in self.bot.tree.get_commands() if cmd.name.startswith("wheatley")] # Updated prefix
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print(f"WheatleyCog: Available Wheatley commands: {', '.join(wheatley_commands)}") # Updated print
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return synced, wheatley_commands
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except Exception as e:
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print(f"WheatleyCog: Failed to sync commands: {e}") # Updated print
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import traceback
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traceback.print_exc()
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return [], []
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# Setup function for loading the cog
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async def setup(bot):
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"""Add the WheatleyCog to the bot.""" # Updated docstring
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await bot.add_cog(WheatleyCog(bot)) # Use renamed class
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print("WheatleyCog setup complete.") # Updated print
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