Worked on the livekit/agents repository to deliver dependency-injected LLM client parameterization, enabling more flexible and efficient instantiation of language model clients. The approach involved refactoring backend Python code to accept a client parameter, aligning with dependency injection patterns and asynchronous programming best practices. This change improved configurability and testability by allowing easy mocking and CI-friendly injections, while also reducing redundant client creation and clarifying the client lifecycle. The update enhanced resource efficiency, lowered startup latency, and supported more scalable deployments. The work focused on API integration and backend development, resulting in more reliable and cost-effective LLM integrations for the project.