The EVM Agent Kit offers a modular architecture to construct intelligent agents that seamlessly interact with Ethereum networks. At its core, it leverages large language models to generate instruction chains parsed into JSON-RPC calls for on-chain data retrieval and transaction execution. Developers can plug in custom logic for wallet management, gas estimation, and result validation. The kit includes templates for scenarios like token swaps, contract audits, and on-chain analytics. By abstracting low-level EVM complexities, it enables rapid prototyping of agents that can monitor wallet balances, decode smart contract events, and autonomously execute trades based on predefined strategies. Extensible connectors allow integration with major LLM providers and blockchain networks, ensuring flexibility in agent design.

gym-fx is an open-source Python library that implements a simulated Forex trading environment using the OpenAI Gym interface. It offers support for multiple currency pairs, integration of historical price feeds, technical indicators, and fully customizable reward functions. By providing a standardized API, gym-fx simplifies the process of benchmarking and developing reinforcement learning algorithms for algorithmic trading. Users can configure market slippage, transaction costs, and observation spaces to closely mimic live trading scenarios, facilitating robust strategy development and evaluation.