Inference rulesNested objects become separate BaseModels; field names become snake_case with an alias when they differ from the original key; optional fields use Optional and default to None; mixed types become Union.Runs locally — no fixed size limit (bounded by browser memory)

Sample JSONJSON

Paste or type JSON

Generated schemaPydantic

Paste or type JSON

JSON → BaseModel · runs locally · no upload

JSON to Pydantic Model Generator

Sample JSON → Pydantic v2 BaseModel · nested models · aliases · Optional fields

🔒Your data is processed locally in the browser — never uploaded, never stored

No upload, no storage

JSON is processed in memory and never sent to a server.

Share via URL fragment

Share links encode data in the # anchor — never sent to a server.

Remember last edit

Optionally keep your last input locally; clear it with one click.

Why generate Pydantic models from JSON

Generate BaseModels

Nested objects split into their own BaseModels, defined before use and ready to import.

Validation, not just type hints

Unlike our JSON to Python dataclass page, this one emits Pydantic models that validate at runtime.

snake_case with aliases

Fields follow Python convention. When a name differs from the JSON key, an alias is added and populate_by_name is enabled.

Optional and Union

Missing or nullable fields use Optional with a None default, mixed types become Union, and optional fields sort after required ones.

Runs locally — no upload

Generation happens entirely in your browser. Nothing is uploaded or stored.