2.1 KiB
2.1 KiB
Multi-Agent Roleplay System with Stanford Memory Architecture
This is a Python-based multi-agent roleplay system that implements Stanford's proven "Generative Agents" memory architecture for creating believable AI characters with long-term memory, reflection, and emergent behaviors.
Core Architecture
Memory System (Stanford's Approach)
- Memory Stream: Each agent maintains observations, reflections, and plans
- Smart Retrieval: Combines recency (exponential decay), importance (1-10 scale), and relevance (cosine similarity)
- Auto-Reflection: When importance threshold (150) is hit, generates higher-level insights
- Natural Forgetting: Older memories become less accessible over time
Agent Components
- Character: Core personality, background, relationships, goals
- CharacterAgent: Handles memory, planning, reactions based on Stanford architecture
- MemoryStream: Implements the full memory/reflection/planning system
- SceneManager: Orchestrates multi-agent interactions and scene state
Key Features
- Real-time character interactions with persistent memory
- Automatic insight generation (reflections) from accumulated experiences
- Time advancement that triggers planning and memory decay
- Character-to-character conversations with relationship memory
- Emergent behaviors through memory-driven decision making
Technology Stack
- Python 3.8+
- OpenAI GPT API (gpt-3.5-turbo for agents, gpt-4o-mini for scene management)
- OpenAI Embeddings API for memory relevance scoring
- scikit-learn for cosine similarity calculations
- Rich character personalities with background relationships and goals
Research Basis
Based on Stanford's 2023 "Generative Agents" paper that successfully created 25 AI agents in a virtual town who formed relationships, spread information, and coordinated group activities entirely through emergent behavior.
Development Focus
The system emphasizes psychological realism over game mechanics - agents should behave like real people with genuine memory limitations, emotional consistency, and relationship development over time.