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JSON to Pydantic Model Converter
x402
JSON to Pydantic Model Converter is a paid API for AI agents from api.strale.io, paid per call via x402, $0.054/call, status unknown (last checked 2026-09-13).
Converts a JSON string or object into Python Pydantic model class definitions, handling nested objects, arrays, and optional fields.
Price / call$0.054
Success—
StatusUnknown
How this service works
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Output
Returns Python source code containing Pydantic model class definitions that reflect the structure of the provided JSON input, including nested models for sub-objects, typed list fields for arrays, and optional field annotations where applicable.
Example use cases
Scaffold models from API response
“I got this JSON back from a third-party API and need Pydantic models to work with it in my Python service — can you generate the classes? Here's the JSON: {"orderId": "abc-123", "customer": {"id": 9, "email": "joe@example.com"}, "items": [{"sku": "X1", "qty": 2}]}, use 'Order' as the root name.”
Type-safe config model generation
“Turn this config JSON into Pydantic classes so I can validate it at runtime in my Python app — root name should be 'AppConfig': {"database": {"host": "localhost", "port": 5432}, "debug": true, "allowed_hosts": ["example.com"]}”
Data pipeline schema modeling
“I have this sample JSON record from our data pipeline and I need Pydantic models for it — call the root class 'EventRecord': {"eventId": "e-001", "timestamp": "2024-01-01T00:00:00Z", "payload": {"userId": 42, "action": "click", "meta": {"page": "/home"}}}”
Technical details
Endpoint
GEThttps://api.strale.io/x402/v2/json-to-pydanticWhen to prefer
Choose this endpoint when you need to quickly scaffold Pydantic model classes from existing JSON data or API responses without manually writing Python type definitions. Ideal for developers integrating third-party APIs, building data pipelines, or enforcing type safety in Python projects. Prefer this over manual authoring when the JSON structure is complex or deeply nested.
Side effects
- Invalid or malformed JSON input causes a parse error response
- Missing required 'json' query parameter returns a validation error
- Extremely deeply nested JSON may hit recursion or size limits
- Non-standard JSON types (e.g. dates as strings) may not receive specialized Pydantic validators
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object |
Tags
x402
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