Initially I thought we need a dedicated vector database but as we tried to build even a simple gen-ai applicaitons we realized that we need another "regular" database to build a complete application.
Instead with DataStax's Vector Search, we designed a document style API and corresponding clients that give you a Vector Native experience to do CRUD of vector and meta-data as well CRUD of other data models. Here is one client ref for example https://docs.datastax.com/en/astra/astra-db-vector/clients/p...
We will be publishing the github repo in the next couple of weeks. As you can imagine this is happening in real time and we want to cross check few things before we publish the repo.
I will reply to this thread once that has happened.
I’m not sure exactly what you mean by data requirements, but we’re using Lang chain and still calling to GPT on the backend.
We’re building agents that are a little bit less autonomous than what is popular right now, mostly using them as chat bots that can interface with a workspace or chained into a type of workflow. Basically everything in our workspace will be accessible to the agents.
This is interesting because it does not mention Vector database powered by Apache Cassandra or the hosted serverless version DataStax Astra. Here is write up we did on 5 hard problems in Vector database and how we solved them. https://thenewstack.io/5-hard-problems-in-vector-search-and-...
In full transparency: I work for DataStatx and lead engineering for Vector database.
