Requirements

• Java 21 (use sdkman)
• TCC and GPU enabled zone or run Ollama locally
• OpenAI API key openai.api-key defined in src/main/resources/application.properties or provided as an environment variable OPENAI_API_KEY

Description

This project serves as an example of how to test GenAI applications by using a Large Language Model (LLM).

The main challenge with verifying answers from LLMs is that they generate responses in natural language that are non-deterministic, making traditional testing methods, which rely on predictable outcomes, unsuitable. To address this, the proposed solution involves using one LLM to assess the adequacy of another LLM's responses. This involves setting detailed validation criteria and employing an LLM as a 'Validator Agent' to ensure the responses meet these criteria. This method can be used to validate answers that require both general and specialized knowledge:

    String question = "Does 'good' have the same meaning as 'bad'?";
    String reference = "good is the opposite of bad";

    @Test
    void verifyValidatorDetectsWrongAnswer() {
        String answer = "Yes";
        ValidatorAgent.ValidatorResponse validate = validatorAgent.validate(question, answer, reference);
        assertThat(validate.response()).isEqualTo("no");
    }

    @Test
    void verifyValidatorDetectsGoodAnswer() {
        String answer = "No";
        ValidatorAgent.ValidatorResponse validate = validatorAgent.validate(question, answer, reference);
        assertThat(validate.response()).isEqualTo("yes");
    }

The ValidatorAgent is an AI Service responsible for validating the answers. It will verify if the answer is correct or not based on the reference provided.

Learn more about the details in the blog post: A Promising Methodology for Testing GenAI Applications in Java

How to run tests

./gradlew test

How to run backend

./gradlew run

How to run frontend

cd frontend
npm install
npm start