Developed a unified API layer for large language model access by integrating the Apertis LLM API across multiple providers in the run-llama/llama_index repository, enabling seamless interaction with over 470 models. Leveraged Python and TypeScript to implement OpenAI-compatible endpoints and example Jupyter notebooks, supporting both chat and embedding workflows. Integrated Apertis as a community provider within the vercel/ai SDK, broadening model accessibility through a single API gateway. Enhanced documentation and code quality to streamline developer onboarding and experimentation, reducing integration effort and accelerating adoption of machine learning solutions through clear examples and comprehensive provider documentation updates.