I work on Typesense [1] - historically considered an open source alternative to Algolia.
We then launched vector search in Jan 2023, and just last week we launched the ability to generate embeddings from within Typesense.
You'd just need to send JSON data, and Typesense can generate embeddings for your data using OpenAI, PaLM API, or built-in models like S-BERT, E-5, etc (running on a GPU if you prefer) [2]
You can then do a hybrid (keyword + semantic) search by just sending the search keywords to Typesense, and Typesense will automatically generate embeddings for you internally and return a ranked list of keyword results weaved with semantic results (using Rank Fusion).
You can also combine filtering, faceting, typo tolerance, etc - the things Typesense already had - with semantic search.
For context, we serve over 1.3B searches per month on Typesense Cloud [3]
We then launched vector search in Jan 2023, and just last week we launched the ability to generate embeddings from within Typesense.
You'd just need to send JSON data, and Typesense can generate embeddings for your data using OpenAI, PaLM API, or built-in models like S-BERT, E-5, etc (running on a GPU if you prefer) [2]
You can then do a hybrid (keyword + semantic) search by just sending the search keywords to Typesense, and Typesense will automatically generate embeddings for you internally and return a ranked list of keyword results weaved with semantic results (using Rank Fusion).
You can also combine filtering, faceting, typo tolerance, etc - the things Typesense already had - with semantic search.
For context, we serve over 1.3B searches per month on Typesense Cloud [3]
[1] https://github.com/typesense/typesense
[2] https://typesense.org/docs/0.25.0/api/vector-search.html
[3] https://cloud.typesense.org