Pydantic AI
Featured Analysis
Pydantic AI positions itself as a typed, extensible Python AI SDK for building agents that can run across multiple models, interfaces, and execution environments.
Who it is for: Developers building AI agents, tool calls, and structured outputs in Python; development teams needing support for complex, long-running tasks, memory, sub-agents, or context management; teams needing to reuse agent definitions across multiple model providers, speech, background queues, or terminals.
Core capabilities
- Typed Agent Loop with Structured Output: Constrain agent inputs, tool parameters, and return results through typed agent loops, typed dependency injection, typed tools, and structured output.
- Multi-Model and Provider Switching: The official website lists multiple models or providers such as OpenAI, Anthropic, Google, Bedrock, Azure AI Foundry, Groq, Mistral, xAI, and Ollama, and supports switching via strings or Pydantic AI Gateway.
- Observability and Agent Evaluation: Supports OpenTelemetry-native instrumentation, debugging, tracing, and cost tracking with Pydantic Logfire, and agent behavior testing with Pydantic Evals.
- Composable Capability and Agent Specs: Capabilities can combine tools, instructions, hooks, and model settings, and support YAML/JSON agent specs.
- Real-Time Speech and Multi-Interface Execution: The official site states that the same agent can run in web frontends, terminals, voice calls, and regular run() calls, listing OpenAI Realtime, Gemini Live, Azure, and xAI Grok Voice.
Pricing
Not disclosed/under verification. The $123.45 on the page is an example of account balance output from a bank customer service scenario and is not a product plan price.
Updated 2026-08-18