Hi Pinecone support, I am trying to use Pinecone to implement a common text/semantic search problem. Not sure whether it is an ideal application for Pincecone.
Taking an e-commerce website as an exmaple, the search sceanrios can be these:
- Customers can search all type of IPhones by enter “IPhone”, the system will return all available IPhones like “IPhone 16”, “IPhone 15”, etc. This is straigtforward to implement I guess.
- The system defines product categories (e.g., cell phone, latop, desktop) behind the scenses. Customers are allowed to enter “cell phone”. The system will returne all available cell phones such as “samsung s24”, “vivo x100”, “IPhone 16”, etc. Of course, customers may just enter “phone” and the system will semantically match “cell phone”, returning the same results of “cell phone”.
- Customers may enter hardware specifications like “memory 512G”. The system will return all products (no matter cell phones, laptops) with any kind of memories (e.g., SSD) of 512G
#2,3 are my primay questiones. How do I use Pinecone to implement the search functions by the product category, specifications and more possible attributes.
PS Previously, we implemented similar search functions over in-memory data structues (e.g., array, hashtable) to leverage their out-of-the-box methods (e.g., string.contain) to do the search, but the performance, scalability are not quite ideal. After I learn Pinecone thanks to RAG, I feel this kind of search problems may be solved by it too. I imagine customers can flexibily enter either a simple term (IPhone 16) or a sentence (list all IPhones) to get the desired results. If they mistakenly enter a word, vector DB still return most semantically close items.
Thanks a lot for reading the lengthy question. Hope you would offer some recommendation or releated artices.
Regards,
Ricky