In the wake of the generative AI boom, developers began working with an expanding array of LLM providers, each offering distinct APIs, SDKs, and usage patterns. This fragmentation, combined with performance constraints in web environments, led to challenges in building efficient and portable LLM-powered applications. Libraries offering unified interfaces often introduced overhead, complexity, or sacrificed access to model-specific features. We decided to look for a solution.

Goals included:

• Enable easy, lightweight integration with multiple LLM APIs in web applications
• Preserve all model provider specific features, avoiding restrictive abstraction
• Ensure compatibility across environments with a single dependency (Node.js, browser, serverless)
• Optimize for performance, modularity, and simplicity

We developed GenerativeTS, a modular TypeScript library built for modern LLM app development. Designed to be both lightweight and flexible, GenerativeTS:

• Provides 1:1 TypeScript interfaces for major LLM services like OpenAI, Cohere, AWS Bedrock, GCP Vertex AI, Groq, and Huggingface.
• Offers multiple build formats (\~22kB bundles) including ESM, CJS, and UMD for full platform portability.
• Includes runtime type checking of LLM responses for production-grade robustness.
• Introduces minimal abstractions for common use cases like chat prompts and tool use, without hiding native API capabilities.
• Implements obsessive testing: unit, integration, E2E, and even live-tested README examples.

GenerativeTS delivers significant value across the development lifecycle. It enhances developer efficiency by drastically simplifying integration with LLM services, removing the need to learn multiple SDKs and reducing boilerplate code. Its web-optimized builds ensure lightweight payloads and improved application responsiveness, resulting in measurable performance gains. The modular architecture also provides both scalability and flexibility, allowing teams to plug in individual providers or build custom abstractions as needed. With built-in runtime type safety, extensive test coverage, and thorough documentation, GenerativeTS supports confident, reliable deployment at scale.