TypeChat is a library that enables building natural language interfaces by leveraging type definitions (TypeScript interfaces, Zod schemas, Python TypedDicts/dataclasses) to structure LLM interactions. Instead of prompt engineering, it uses schema engineering: types define the expected output structure, which is used to construct prompts, validate LLM responses, and repair invalid outputs through iterative LLM calls. The library provides a clean abstraction over LLM APIs (OpenAI/Azure OpenAI) with retry, timeout, proxy, and response-size limiting. It supports both direct JSON translation and program generation (multi-step function calls). Implemented in TypeScript and Python with parallel APIs, it includes a rich set of examples (sentiment analysis, coffee shop ordering, calendar management, music control, math, drawing, health data, crossword, multi-agent routing) and comprehensive test suites. The codebase demonstrates strong engineering practices: clean separation of concerns (model, validator, translator), well-tested schema conversion (Python types to TypeScript declarations), and safe program interpretation. While still in early version (0.1.4), it is actively maintained with CI/CD, dependabot alerts, and a documentation site.