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To make an LLM return JSON that fits your application, send a schema-constrained response format, parse the result, and validate its meaning in your own code. Structured outputs can make the response predictable and easier to consume; they do not prove that its values are true, safe, or valid under your business rules.
What structured outputs do—and do not—guarantee
Structured outputs are a provider feature that constrains a model’s response to a specified shape, commonly described with JSON Schema. They are useful when an application needs a predictable payload for tasks such as extraction or classification. Google’s Gemini structured-output guide describes these kinds of uses.
A response can be valid JSON and conform to its schema while still containing a false, incomplete, or unusable value. A schema can require a string called date, for example, but that alone does not establish that the date is real or appropriate for the transaction. Treat schema conformance as a formatting and type check—not a substitute for application validation.
How to add structured output to an application
- Define a narrow schema. Specify only the fields the application needs, use precise types, and use enums where the allowed values are known. Include clear descriptions to guide the model. Keep in mind that providers support only a subset of JSON Schema features.
- Configure the provider’s schema mode. Send the schema using the response-format option documented for the provider and endpoint you use. For example, OpenAI’s API reference describes a
json_schemaresponse format and astrictoption; it also retainsjson_objectas an older JSON mode. Check the current OpenAI API reference for the exact configuration and supported subset. - Parse the returned content. Treat the response as untrusted input. Parse it with your language’s JSON parser and handle parse failures rather than assuming the model always returned a complete payload.
- Validate meaning and invariants. Check domain rules that the schema cannot express or that the provider may not enforce: ranges, cross-field consistency, permitted identifiers, authorization, and whether required information is actually present.
- Handle non-success paths. Decide what the application should do when the model refuses, the response is incomplete, the API call fails, or the schema is incompatible with the provider’s supported subset. Depending on the task, that may mean retrying with a corrected request, asking for missing information, or stopping and surfacing an error.
Google’s guide recommends clear schema descriptions, strong typing, explicit prompts, validation, and robust error handling. Those practices remain necessary even when a provider offers a strict mode.
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Choose structured output or function calling by the job
Use structured output when the model’s final answer should have a defined format. Use function calling when the model needs to request a tool or take an intermediate action during a conversation. They address different stages of a workflow and can be combined where an application needs both a tool action and a structured final response. Google explains this distinction in its Gemini tools guide.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What to check before relying on a provider’s schema mode
Do not assume that “strict” means every JSON Schema keyword is enforced. Google documents support for a subset of JSON Schema, and OpenAI likewise limits strict mode to a subset. Confirm that the exact types, constraints, and keywords your schema depends on are supported by the endpoint and model you plan to use.
- Schema coverage: Which JSON Schema keywords and constraints are accepted and enforced?
- Request configuration: What response-format field or SDK configuration enables the mode, and how is strict behavior specified?
- Failure behavior: How are refusals, incomplete responses, incompatible schemas, and API errors surfaced?
- Tool interoperability: Can the workflow use tool calls and still produce the final structured response you need?
- Application checks: Which semantic validations and recovery paths must your code implement regardless of provider guarantees?
Official documentation explains capabilities and configuration, but it does not establish a comparable reliability ranking across providers. Do not interpret schema support as a measured success rate or as evidence that one provider is categorically more reliable.
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