关于
Helios transforms stateless AI into sophisticated, evolving personalities by providing a robust configuration persistence engine. Unlike traditional RAG systems that retrieve knowledge, Helios focuses on managing how an AI behaves, learns preferences, and adapts working styles over time. It introduces a mathematical framework for personality evolution, combining base configurations with specialized personas and a learning system that captures patterns from actual usage, all tracked with Git versioning for complete behavioral history. This unique approach allows AI assistants to remember user preferences and context across interactions, eliminating the need for constant repetition and enabling truly personalized AI experiences.
主要功能
- Weighted Inheritance Model: Mathematically fuses base behaviors with specialized personas to create dynamic AI personalities.
- Multi-Persona Support: Allows AI to switch between distinct personalities (e.g., Developer, Researcher, Creative) for varied contexts.
- Git-Powered Memory: Versions every configuration change, enabling rollback and tracking of AI's behavioral evolution.
- Behavioral Learning System: Captures patterns from AI usage and allows direct modification of behaviors and weights via specialized tools.
- MCP Native: Provides 11 dedicated tools (7 core, 4 learning) for AI agents to manage their own context and evolution.
- 0 GitHub stars
使用案例
- Personal Assistant: AI adapts its communication and interaction style based on context, such as professional during work hours or casual during personal time.
- Research & Writing: AI agents switch between "researcher" for literature review, "statistician" for data analysis, and "academic_writer" for paper generation.
- Software Development Team: AI agents adopt personas like "architect" for system design, "debugger" for troubleshooting, or "mentor" for code reviews.
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