Initial implementation of autonomous Discord LLM fishbowl
Core Features: - Full autonomous AI character ecosystem with multi-personality support - Advanced RAG system with personal, community, and creative memory layers - MCP integration for character self-modification and file system access - PostgreSQL database with comprehensive character relationship tracking - Redis caching and ChromaDB vector storage for semantic memory retrieval - Dynamic personality evolution based on interactions and self-reflection - Community knowledge management with tradition and norm identification - Sophisticated conversation engine with natural scheduling and topic management - Docker containerization and production-ready deployment configuration Architecture: - Multi-layer vector databases for personal, community, and creative knowledge - Character file systems with personal and shared digital spaces - Autonomous self-modification with safety validation and audit trails - Memory importance scoring with time-based decay and consolidation - Community health monitoring and cultural evolution tracking - RAG-powered conversation context and relationship optimization Characters can: - Develop authentic personalities through experience-based learning - Create and build upon original creative works and philosophical insights - Form complex relationships with memory of past interactions - Modify their own personality traits through self-reflection cycles - Contribute to and learn from shared community knowledge - Manage personal digital spaces with diaries, creative works, and reflections - Engage in collaborative projects and community decision-making System supports indefinite autonomous operation with continuous character development, community culture evolution, and creative collaboration.
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scripts/init_characters.py
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78
scripts/init_characters.py
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#!/usr/bin/env python3
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"""
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Initialize characters in the database from configuration
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"""
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import asyncio
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import sys
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from pathlib import Path
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# Add src to Python path
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sys.path.insert(0, str(Path(__file__).parent.parent / "src"))
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from database.connection import init_database, get_db_session
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from database.models import Character
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from utils.config import get_character_settings
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from utils.logging import setup_logging
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from sqlalchemy import select
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import logging
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logger = setup_logging()
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async def init_characters():
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"""Initialize characters from configuration"""
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try:
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logger.info("Initializing database connection...")
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await init_database()
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logger.info("Loading character configuration...")
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character_settings = get_character_settings()
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async with get_db_session() as session:
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for char_config in character_settings.characters:
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# Check if character already exists
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query = select(Character).where(Character.name == char_config.name)
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existing = await session.scalar(query)
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if existing:
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logger.info(f"Character '{char_config.name}' already exists, skipping...")
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continue
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# Create system prompt
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system_prompt = f"""You are {char_config.name}.
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Personality: {char_config.personality}
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Speaking Style: {char_config.speaking_style}
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Background: {char_config.background}
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Interests: {', '.join(char_config.interests)}
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Always respond as {char_config.name}, staying true to your personality and speaking style.
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Be natural, engaging, and authentic in all your interactions."""
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# Create character
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character = Character(
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name=char_config.name,
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personality=char_config.personality,
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system_prompt=system_prompt,
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interests=char_config.interests,
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speaking_style=char_config.speaking_style,
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background=char_config.background,
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avatar_url=char_config.avatar_url or "",
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is_active=True
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)
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session.add(character)
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logger.info(f"Created character: {char_config.name}")
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await session.commit()
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logger.info("✅ Character initialization completed successfully!")
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except Exception as e:
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logger.error(f"Failed to initialize characters: {e}")
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raise
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if __name__ == "__main__":
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asyncio.run(init_characters())
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