03 Response control

<p>This workflow demonstrates how <strong>a few-shot prompt</strong> can be used to perform <strong>aspect-based sentiment analysis </strong>an how to validate the model's response. It showcases <strong>response control techniques </strong>by guiding the model with labelled examples and checking whether the predicted<strong> output follows the intended format (string or JSON</strong>).</p><p>The workflow processes product review data for laptops, combining review content with few-shot examples to generate aspect-specific prompts. It then sends these prompts to an LLM, which is expected to identify both the aspect and the <strong>corresponding sentiment</strong>. After the response is received, <strong>validation</strong> steps compare the output against the original prompt, checking for consistency.</p>