During January 2026, Runixer developed an asynchronous Anthropic client integration for the BerriAI/litellm repository, focusing on optimizing the proxy layer’s token counting process. By leveraging Python and asynchronous programming techniques, Runixer implemented client instance caching to prevent event loop blocking and reduce socket exhaustion, which improved throughput and stabilized performance under load. The work included refactoring the proxy to support non-blocking operations, enhancing reliability for concurrent requests. Runixer also created unit tests to validate the caching mechanism’s correctness and efficiency. This contribution demonstrated a thoughtful approach to API integration and performance optimization within a production-grade Python codebase.