Is there a way to use evaluation flow to improve prompt flow performance?

Question

I am working on a RAG app and I currently have a working custom prompt flow.

Is there a way to iteratively improve the performance of the flow? Maybe using a set of predefined questions and answers.

Could I make use of evaluation flow to achieve this?

Answer 1

Start with creating a comprehensive test set of predefined questions and their expected answers, covering various scenarios your RAG app is designed to handle.

With this test set in hand, you can leverage Azure AI evaluation flows to assess the quality of your prompt flow outputs. These evaluation flows run your test set through your current prompt flow, compare the outputs to the expected answers, and generate metrics on accuracy, relevance, and other crucial factors.

The heart of the improvement process lies in iterative refinement. By analyzing the results from the evaluation flow, you can identify areas where the prompt flow underperforms. This insight allows you to make targeted adjustments to your prompts, retrieval strategy, or other components of your flow. After each adjustment, re-running the evaluation helps measure the impact of your changes.

To further optimize your system, consider implementing A/B testing. Create multiple versions of your prompt flow and use the evaluation flow to compare their performance. This approach can help you identify the most effective configurations for your specific use case.

While Azure doesn't directly offer automated optimization for prompt flows, you could potentially develop a system that uses the evaluation results to automatically suggest or implement improvements.