Best methods to choose between different searching models?

My question here is in regards to best practices and current methods for selecting search models on the fly based on a users query.

Lets say I have four searching models, each optimized for their respective types:

• Model A: Embedding-based, used for sentence queries about scientific topics
• Model B: Embedding-based, used for sentence queries about general news topics
• Model C: TF*IDF-based, used for keyword queries about scientific topics
• Model D: TF*IDF-based, used for keyword queries about general news topics

When users enter a query such as:

• Query: vaccine science
• Query: what caused the stock market to change today

...what are the best ways to determine the model a search engine should use? Are there any design patterns I can use as a reference, or, is this simply another model that I would need to train?

I tried to google terms like models that select other models, or models to determine which models to use, but I have not had much luck there.