Major Improvements in AI16Z's Eliza Framework: From V1 to V2

Recently, the AI Agent framework Eliza of AI16Z is about to launch version V2, with the alpha test version expected to be released in 2-3 weeks. This upgrade brings several important improvements aimed at enhancing the framework's performance, scalability, and user experience.

The current version of the Eliza framework is mainly composed of three layers: the interface layer, the core functionality layer, and the model layer. The interface layer is responsible for interacting with external platforms such as Discord, Twitter, and Telegram, and provides API interfaces for other systems to call. The core functionality layer includes the memory system, behavior system, and configuration system, which are responsible for storage and document processing, custom behavior management, and configuration management, respectively. The model layer supports various large language models, such as OpenAI, Anthropic, Llama, and Grok, and provides a unified model interface abstraction.

The V2 version of the Eliza framework has undergone a comprehensive upgrade based on this.

1. Interface Layer Improvement: Introduced a unified message bus, integrating the originally scattered clients into a cohesive message processing system. Each platform now acts as an adapter for the message bus, simplifying client development and maintenance work, while providing a more consistent message processing experience.

2. Core Functionality Layer Upgrade: A unified proxy wallet has been launched, integrating previously scattered wallet configurations, providing unified multi-chain wallet management, and simplifying cross-chain operations. At the same time, the core interface has been redesigned to make it more versatile, enhancing the framework's extensibility and plugin integration mechanism.

3. Model Layer Innovation: Introduce a model registry mechanism that supports dynamic registration and overriding of models. Models are divided into two categories: LLMs and Embeddings, providing a more flexible way to call models.

4. Plugin System Optimization: Improved plugin management and committed to achieving 100% test coverage to ensure plugin quality.

This upgrade has made the Eliza framework more modular and unified, with clearer interactions between components, laying a better foundation for future expansion. From a functional perspective, the V2 version will create new growth opportunities for functional extension plugins such as AgentTank, and is expected to drive further development of the AI Agent ecosystem.