The existing cookbook just touches the surface:
https://github.com/openai/openai-cookbook/blob/main/examples/vector_databases/redis/getting-started-with-redis-and-openai.ipynb

Contribute a Python notebook that demonstrates complex Hybrid queries with Redis VSS and other search features (an ecommerce dataset might work nicely) including

• Numeric range filters
• Tag filters
• Full text search "filters"
• Client-side hybrid scoring combing both BM25 lexical AND semantic search. This could be done in a pipeline to send 1 redis call to fetch both search results (top K) and then merge the sets. Show performance improvement with this technique over pure lexical or pure semantic?