#2121st of 33 in Agent frameworks and SDKs
pydantic-ai
Typed Python SDK for building agents with swappable model providers
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- Stars
- 20.5k
- License
- MIT
- Last commit
- Oct 2026
- Last release
- Oct 2026
- Language
- Python
Missed the latest GitHub check; these facts may be older.
Overview
Pydantic AI is a Python agent framework where tools, dependencies and outputs are typed with Pydantic models, and the model is chosen by a provider string (OpenAI, Anthropic, Google, Bedrock, Ollama and others). The same agent can run as a CLI, web chat, realtime voice session, or on durable execution engines such as Temporal, DBOS and Prefect. A separate Harness package adds memory, guardrails, sub-agents and a coding agent as composable capabilities.
Who it is for: Python developers building typed LLM agents and production workflows
Strengths
- Validated structured output and typed dependency injection checked by IDE and type checker
- Model swap by string across OpenAI, Anthropic, Google, Bedrock, Ollama and many more
- Durable execution integrations for Temporal, DBOS, Prefect, Restate and others
- OpenTelemetry instrumentation works with any OTel backend, not only Logfire
Weaknesses
- Python only
- Memory, guardrails, sub-agents and coding agent live in a separate pydantic-ai-harness package
- Pydantic Graph and Pydantic Evals are separate packages to install
- README promotes Logfire and the Gateway, which are commercial Pydantic products
What it needs
- no GPU
- Needs Model provider API key or local model server such as Ollama, Temporal, DBOS or Prefect (optional, for durable execution)
- Models: OpenAI, Anthropic, Google, Bedrock, Azure AI Foundry
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