400 Bad Request when using model 'gpt-5' with OpenAI ChatClient (works with gpt-4.1 and Anthropic models)

Description:
When calling the OpenAI API via ChatClient in Spring AI using model: gpt-5, the request fails with a 400 Bad Request response. The same controller method works correctly with gpt-4.1 and Anthropic models (Claude).

Steps to reproduce:

1. Use ChatClient with a BeanOutputConverter in a Spring WebFlux controller.
2. Set model to "gpt-5".
3. Make a GET request to the endpoint.

Expected behavior:
The request should succeed and return the structured JSON output from the GPT-5 model.

Actual behavior:
Spring AI logs show:

org.springframework.web.reactive.function.client.WebClientResponseException$BadRequest: 400 Bad Request from POST https://api.openai.com/v1/chat/completions

2025-08-09T11:21:41.736+02:00 ERROR reactor-http-epoll-4 class=org.springframework.ai.chat.model.MessageAggregator - Aggregation Error
org.springframework.web.reactive.function.client.WebClientResponseException$BadRequest: 400 Bad Request from POST https://api.openai.com/v1/chat/completions
	at org.springframework.web.reactive.function.client.WebClientResponseException.create(WebClientResponseException.java:321)
Suppressed: reactor.core.publisher.FluxOnAssembly$OnAssemblyException: Error has been observed at the following site(s):
	*__checkpoint ⇢ 400 BAD_REQUEST from POST https://api.openai.com/v1/chat/completions [DefaultWebClient]
	

The 400 only occurs with gpt-5.
gpt-4.1, gpt-4.1-mini and Anthropic models work as expected.

Notes:

• Spring AI version: 1.0.1
• OpenAI Java/Spring AI configuration is standard; no special headers are set.
• Possibly related to API payload format changes or missing headers required for gpt-5.
• Might require updating Spring AI's request serialization to support GPT-5’s expected input schema.

Environment:

• Java version: 21
• Spring Boot version: 3.4.3
• Spring AI version: spring-ai-bom:1.0.1

Minimal reproducible example:

@GetMapping(value = "/llm/actors/openai", produces = MediaType.APPLICATION_JSON_VALUE)
public Mono<ActorsFilms> llmActorsOpenAI() {
    String actorName = "Klaus Kinski";
    BeanOutputConverter<ActorsFilms> converter = new BeanOutputConverter<>(ActorsFilms.class);

    return ChatClient.create(this.chatModelOpenAI)
        .prompt()
        .user(u -> u.text("Generate the filmography of 5 movies for {actor}. {format}")
            .param("actor", actorName)
            .param("format", converter.getFormat()))
        .stream()
        .content()
        .collectList()
        .map(chunks -> String.join("", chunks))
        .mapNotNull(converter::convert);
}

public record ActorsFilms(String actor, List<String> films) {}

Start with the ChatClient call in the provided Spring WebFlux controller and reproduce the POST to https://api.openai.com/v1/chat/completions using gpt-5, comparing it with gpt-4.1 and Anthropic models. Trace the request serialization implicated by the 400 response, then verify that the structured JSON output from BeanOutputConverter succeeds.