Handling Ambiguous Knowledge Base Queries (RAG)

Question

When using Azure's OpenAI service, there is a question about RAG. For instance, the knowledge base contains ‘turn on fog lights when visibility is less than 100 meters’, the question is whether fog lights need to be turned on when visibility is less than 1000 meters, and the expect answer should be "No need to turn on fog lights". In this case, should we use RAG to cover all scenarios, or is another technology required? Thanks.

Answer 1

Thanks for the question, the Retrieval Augmented Generation (RAG) pattern is a technique to retrieve language from information system at query time to augment or generate the answers from. We call this Azure OpenAI on your data and it does not require fine-tuning to achieve this. The AOAI on your data with the RAG pattern doesn't restrict to structured or unstructured data. Just that Azure Cognitive Search is a search engine which is expected to support rich indexing and query syntax over the heterogeneous data sources behind it.

We also have a example where you use Az Cog Search to index the data, then use RAG pattern to use Open AI completion using the matches docs from Az Cog Search.

 RAG and generative AI - Azure Cognitive Search | Microsoft Learn