Save Time and Resources with the Query Classifier for Neural Search

A query classifier in Haystack helps distinguish between keyword-based and natural language queries, routing them accordingly to optimize performance and accuracy. The classifier can be integrated into various pipelines, including question answering systems, to make smarter decisions before triggering the full pipeline. By using a machine learning model trained on a binary classification task, the classifier can handle complex use cases such as distinguishing between questions and statements, or adapting to different retrieval methods for dense and sparse queries. The query classifier can save time and resources by rerouting keyword queries to a regular document search instead of employing the full semantic search pipeline, resulting in significant computational and time savings. By incorporating a query classifier into question answering pipelines, systems can maximize accuracy while minimizing computation effort and cost.