Oracle Cloud Infrastructure GenAI

Generative AI Service provides access to pretrained, foundational models from Cohere and Meta. See AI model availability here.

With dedicated AI clusters, you can host foundational models on dedicated GPUs that are private to you. These clusters provide stable, high-throughput performance that’s required for production use cases and can support hosting and fine-tuning workloads.

Maven Dependency

xml

<dependency>
    <groupId>dev.langchain4j</groupId>
    <artifactId>langchain4j-community-oci-genai</artifactId>
    <version>1.11.8-beta19</version>
</dependency>

Additionally, you have to select HTTP client for OCI SDK, by default, use a Jersey 3 based version:

xml

<dependency>
    <groupId>com.oracle.oci.sdk</groupId>
    <artifactId>oci-java-sdk-common-httpclient-jersey3</artifactId>
    <version>${oci-sdk.version}</version>
</dependency>

In case use are on Java EE/Jakarta EE 8 or older runtime, please use Jersey 2 based version:

xml

<dependency>
    <groupId>com.oracle.oci.sdk</groupId>
    <artifactId>oci-java-sdk-common-httpclient-jersey</artifactId>
    <version>${oci-sdk.version}</version>
</dependency>

More information can be found in OCI SDK documentation.

APIs

Package dev.langchain4j.community.model.oracle.oci.genai

API is separated for Cohere and Meta models as the configuration differs.

Meta models:

OciGenAiChatModel - for all OCI GenAi generic chat models(llama)
OciGenAiStreamingChatModel - streaming API for OCI GenAi generic chat models

Cohere models:

OciGenAiCohereChatModel - for all OCI GenAi Cohere chat models
OciGenAiCohereStreamingChatModel - streaming API for OCI GenAi Cohere chat models

Examples

Example of synchronous Cohere chat model usage with tool call:

java

var model = OciGenAiCohereChatModel.builder()
      .modelName("cohere.command-r-08-2024")
      .compartmentId("ocid1.tenancy.oc1..aa....")
      .authProvider(new ConfigFileAuthenticationDetailsProvider("DEFAULT"))
      .maxTokens(600)
      .temperature(0.2)
      .topP(0.75)
      .build();

Assistant assistant = AiServices.builder(Assistant.class)
        .chatModel(model)
        .tools(new Calculator())
        .chatMemory(MessageWindowChatMemory.withMaxMessages(10))
        .build();

String answer = assistant.chat("Calculate square root of 16");

Example of streaming Meta chat model usage:

java

var model = OciGenAiStreamingChatModel.builder()
                .modelName("meta.llama-3.3-70b-instruct")
                .compartmentId("ocid1.tenancy.oc1..aa....")
                .authProvider(new ConfigFileAuthenticationDetailsProvider("DEFAULT"))
                .build();

CompletableFuture<ChatResponse> futureResponse = new CompletableFuture<>();   

model.doChat(ChatRequest.builder()
        .messages(UserMessage.from("Tell me a joke about Java"))
        .build(), 
new StreamingChatResponseHandler() {
    @Override
    public void onPartialResponse(String partialResponse) {
        System.out.print(partialResponse);
    }
    @Override
    public void onCompleteResponse(ChatResponse completeResponse) {
        futureResponse.complete(completeResponse);
    }
    @Override
    public void onError(Throwable error) {
        futureResponse.completeExceptionally(error);
    }
});
futureResponse.join();