FTS in all databases suck for non-English languages. Even the larger dedicated search systems often fail at even the simplest searches or need arcane configurations to work properly.
To overcome the need for those arcane configurations, semantic search with vectors from text embeddings are slowly getting traction.
Here [1] is an article that shows how to do that with the modern Postgres extension pgvector [2].
The downside is the reliance on a ML model to generate the embeddings, either from OpenAI as mentioned in the article from Supabase, or from an open-source library.
[1] https://supabase.com/blog/openai-embeddings-postgres-vector [2] https://github.com/pgvector/pgvector