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AI agents for building a typed python agent with structured output
Short answer: Pydantic AI is our top tested pick (7.7/10): tool calls and a validated structured output worked on the first run in our offline test. LangGraph fits when you need explicit control over state and branching.
Tools for this job
| # | Tool | Why for this job | AgentPick Score | Link |
|---|---|---|---|---|
| #1 |  LangGraph | Stateful graphs for explicit control over branching | 90/100 | Official source ↗ |
| #2 |  Pydantic AI | Tested 7.7/10: typed tools and structured output worked first run | 88/100 · Hands-on tested 7.7/10 | Official source ↗ |
| #3 |  OpenAI Agents SDK | OpenAI's Python framework for multi-agent workflows | 86/100 | Official source ↗ |
Ordered by AgentPick Score. Links may become affiliate links; they never change order. Disclosure.
How to do it
- Define the output as a Pydantic model.
- Register tools as typed functions.
- Test offline with a fake model before spending on API calls.
- Add a live model last.
Starter prompt
Build a Pydantic AI agent that takes [input] and returns a [Model] with fields [fields]. Add one tool, [tool], and a test that runs with TestModel (no API key).
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