LangChain4j

Add the dependency

<dependency>
  <groupId>dev.langchain4j</groupId>
  <artifactId>langchain4j-open-ai</artifactId>
  <version>1.19.0</version>
</dependency>

Plain Java

Use auto for Laminarity selection and fallback. Set modelName to an id returned by /v1/models only when you intentionally want a direct, no-fallback request.

import dev.langchain4j.model.chat.ChatModel;
import dev.langchain4j.model.openai.OpenAiChatModel;

ChatModel model = OpenAiChatModel.builder()
    .baseUrl("https://api.laminarity.ai/v1")
    .apiKey(System.getenv("LAMINARITY_API_KEY"))
    .modelName("auto")
    .maxCompletionTokens(300)
    .build();

String answer = model.chat("Give me one launch checklist item.");
System.out.println(answer);

Spring Boot

langchain4j.open-ai.chat-model.base-url=https://api.laminarity.ai/v1
langchain4j.open-ai.chat-model.api-key=${LAMINARITY_API_KEY}
langchain4j.open-ai.chat-model.model-name=auto
langchain4j.open-ai.chat-model.max-completion-tokens=300
langchain4j.open-ai.chat-model.max-retries=0

Reasoning and token limits

Prefer maxCompletionTokens over the deprecated maxTokens. Laminarity accepts both and translates the legacy field for modern compatible models.

Set reasoningEffort only when using a concrete model that advertises the requested effort in /v1/models. Leave it unset for auto, because Laminarity applies the selected model's execution profile.

OpenAiChatModel model = OpenAiChatModel.builder()
    .baseUrl("https://api.laminarity.ai/v1")
    .apiKey(System.getenv("LAMINARITY_API_KEY"))
    .modelName("gpt-5.6-sol")
    .reasoningEffort("high")
    .maxCompletionTokens(1200)
    .maxRetries(0)
    .build();

Streaming and tools

Use OpenAiStreamingChatModel for token streaming and LangChain4j AI Services or normal tool specifications for function calls. Begin with auto; pin a concrete model only when its tool and reasoning behavior is required.

Some wrappers do not retain Laminarity's additive router_metadata. Use the raw REST response or an OpenAI SDK when the selected provider and fallback trace must be inspected.

OpenCode Java-port mapping

Treat the OpenCode provider id as UI configuration and LangChain4j as the HTTP transport. Resolve the selected OpenCode model to modelName, translate the selected variant to reasoningEffort, and never hard-code the project key in Java source.

Cache model discovery only briefly or refresh it on demand. /v1/models is project-specific, so a list obtained with one key must not be reused as an authority for another project.

Compatibility boundary

Laminarity supports the Chat Completions path used by OpenAiChatModel and OpenAiStreamingChatModel. It does not provide LangChain4j embedding, image-generation, audio, or moderation endpoints.

Do not enable request and response logging in production when prompts may contain secrets or personal data.