Pydantic – Data validation using Python 3.6 type hinting
Documentation for the Pydantic stack. Validate data with Pydantic Validation, build production AI agents with Pydantic AI, and monitor LLM calls, agent behavior, and costs with Pydantic Logfire.
Pydantic – Data validation using Python 3.6 type hinting launched on June 3, 2017 with 120 votes, #337 of 3,107 launches that month and more than 95% of that year's launches. The site was still online in September 2026, 9 years on.
In plain words
Pydantic is a Python library that validates data using type hints and provides an AI engineering stack. It includes Pydantic Validation for data validation, Pydantic AI for building production agents, and Pydantic Logfire for monitoring LLM calls, agent behavior, and costs. The tools help developers work with untrusted data, build type-safe AI agents, and observe agent performance across any language or framework in production environments.
written from the facts on this page · September 2026
From the sources
Pydantic is the end-to-end AI Engineering stack. Validate untrusted data and build agents you’ll actually ship to production using our Python libraries. Observe, govern, and optimize agents written in any language or framework once they’re live. Observability and governance for AI agents, LLMs, applications, services, and hosts. The batteries-included type-safe framework for building production agents. A minimal, secure Python interpreter in Rust, for running the code your agent writes. Data validation from Python type hints. Parse, validate, and serialize with confidence. A next-generation HTTP client. Sync and async APIs, HTTP/1.1 andfrom pydantic-docs.helpmanual.io
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