| Hey HN, I built batch-ai, a TypeScript SDK that simplifies batch processing across AI model providers (OpenAI, Anthropic, and soon Google Gemini & xAI Grok). Why? If you've ever tried running AI workloads in batch mode, you know how frustrating it is: OpenAI requires file uploads for batch processing. Anthropic doesn't, but has different request/response formats. Cost savings are significant (~50% vs. real-time API calls), but every provider handles batching differently. I wanted a simple way to process large volumes of AI requests across different providers without dealing with writing code for all of them. batch-ai provides a single interface to handle batch requests efficiently. Features: Unified batch processing API for OpenAI & Anthropic (more coming). Define output schemas with Zod for structured responses. Reduce costs by using batch APIs instead of real-time calls. Easily switch providers without changing request logic. Who is this for? AI moderation tools (like Filtyr, my AI content moderation SaaS). https://filtyr.com Large-scale AI processing (e.g., sentiment analysis, classification). Researchers & enterprises handling structured AI output at scale. What’s next? Support for Google Gemini & xAI Grok. More batch API options (e.g., generateTextBatch). Smarter retries & error handling. Repo: GitHub – grantsingleton/batch-ai Would love feedback from anyone working with batch AI APIs. What’s your experience? What pain points have you run into? |