pydantic-ai

Supports virtually every model and provider, from OpenAI and Anthropic to custom implementations, as detailed in the README's extensive model list, ensuring no vendor lock-in.

Tightly integrates with Pydantic Logfire for real-time debugging and cost tracking via OpenTelemetry, mentioned in the seamless observability section, though alternative backends are supported.

Leverages Python type hints to move errors to write-time, providing robust static type checking that mimics Rust's 'if it compiles, it works' feel, as emphasized in the fully type-safe feature.

Enables systematic testing and monitoring of agent performance over time with evals, integrated into Logfire for production-grade oversight, as described in the powerful evals section.

Build agents from composable capabilities that bundle tools and instructions into reusable units, with support for YAML/JSON agent definitions and third-party packages, per the extensible by design feature.