Response Streaming

note

This page describes response streaming with a low-level LLM API. See AI Services for a high-level LLM API.

LLMs generate text one token at a time, so many LLM providers offer a way to stream the response token-by-token instead of waiting for the entire text to be generated. This significantly improves the user experience, as the user does not need to wait an unknown amount of time and can start reading the response almost immediately.

For the ChatModel and LanguageModel interfaces, there are corresponding StreamingChatModel and StreamingLanguageModel interfaces. These have a similar API but can stream the responses. They accept an implementation of the StreamingChatResponseHandler interface as an argument.

public interface StreamingChatResponseHandler {

    default void onPartialResponse(String partialResponse) {}
    default void onPartialResponse(PartialResponse partialResponse, PartialResponseContext context) {}

    default void onPartialThinking(PartialThinking partialThinking) {}
    default void onPartialThinking(PartialThinking partialThinking, PartialThinkingContext context) {}

    default void onPartialToolCall(PartialToolCall partialToolCall) {}
    default void onPartialToolCall(PartialToolCall partialToolCall, PartialToolCallContext context) {}

    default void onCompleteToolCall(CompleteToolCall completeToolCall) {}

    void onCompleteResponse(ChatResponse completeResponse);

    void onError(Throwable error);
}

By implementing StreamingChatResponseHandler, you can define actions for the following events:

When the next partial textual response is generated: either onPartialResponse(String) or onPartialResponse(PartialResponse, PartialResponseContext) is invoked (you can implement either of these methods). Depending on the LLM provider, partial response text can consist of a single or more tokens. For instance, you can send the token directly to the UI as soon as it becomes available.
When the next partial thinking/reasoning text is generated: either onPartialThinking(PartialThinking) or onPartialThinking(PartialThinking, PartialThinkingContext) is invoked (you can implement either of these methods). Depending on the LLM provider, partial thinking text can consist of a single or more tokens.
When the next partial tool call is generated: either onPartialToolCall(PartialToolCall) or onPartialToolCall(PartialToolCall, PartialToolCallContext) is invoked (you can implement either of these methods).
When the LLM has completed streaming for a single tool call: onCompleteToolCall(CompleteToolCall) is invoked.
When the LLM has completed generation: onCompleteResponse(ChatResponse) is invoked. The ChatResponse object contains the complete response (AiMessage) as well as ChatResponseMetadata.
When an error occurs: onError(Throwable error) is invoked.

Below is an example of how to implement streaming with StreamingChatModel:

StreamingChatModel model = OpenAiStreamingChatModel.builder()
    .apiKey(System.getenv("OPENAI_API_KEY"))
    .modelName(GPT_4_O_MINI)
    .build();

String userMessage = "Tell me a joke";

model.chat(userMessage, new StreamingChatResponseHandler() {

    @Override
    public void onPartialResponse(String partialResponse) {
        System.out.println("onPartialResponse: " + partialResponse);
    }

    @Override
    public void onPartialThinking(PartialThinking partialThinking) {
        System.out.println("onPartialThinking: " + partialThinking);
    }

    @Override
    public void onPartialToolCall(PartialToolCall partialToolCall) {
        System.out.println("onPartialToolCall: " + partialToolCall);
    }

    @Override
    public void onCompleteToolCall(CompleteToolCall completeToolCall) {
        System.out.println("onCompleteToolCall: " + completeToolCall);
    }

    @Override
    public void onCompleteResponse(ChatResponse completeResponse) {
        System.out.println("onCompleteResponse: " + completeResponse);
    }

    @Override
    public void onError(Throwable error) {
        error.printStackTrace();
    }
});

A more compact way to stream the response is to use the LambdaStreamingResponseHandler class. This utility class provides static methods to create a StreamingChatResponseHandler using lambda expressions. The way to use lambdas to stream the response is quite simple. You just call the onPartialResponse() static method with a lambda expression that defines what to do with the partial response:

import static dev.langchain4j.model.LambdaStreamingResponseHandler.onPartialResponse;

model.chat("Tell me a joke", onPartialResponse(System.out::print));

The onPartialResponseAndError() method allows you to define actions for both the onPartialResponse() and onError() events:

import static dev.langchain4j.model.LambdaStreamingResponseHandler.onPartialResponseAndError;

model.chat("Tell me a joke", onPartialResponseAndError(System.out::print, Throwable::printStackTrace));

Streaming Cancellation

If you wish to cancel the streaming, you can do so from one of the following methods:

onPartialResponse(PartialResponse, PartialResponseContext)
onPartialThinking(PartialThinking, PartialThinkingContext)
onPartialToolCall(PartialToolCall, PartialToolCallContext)

The context object contains the StreamingHandle, which can be used to cancel the streaming:

model.chat(userMessage, new StreamingChatResponseHandler() {

    @Override
    public void onPartialResponse(PartialResponse partialResponse, PartialResponseContext context) {
        process(partialResponse);
        if (shouldCancel()) {
            context.streamingHandle().cancel();
        }
    }

    @Override
    public void onCompleteResponse(ChatResponse completeResponse) {
        System.out.println("onCompleteResponse: " + completeResponse);
    }

    @Override
    public void onError(Throwable error) {
        error.printStackTrace();
    }
});

When StreamingHandle.cancel() is called, LangChain4j will close the connection and stop the streaming. Once StreamingHandle.cancel() has been called, StreamingChatResponseHandler will not receive any further callbacks.

Streaming Cancellation​

Streaming Cancellation