It does use a vector database (pinecone, weaviate, etc.) to store embeddings. The embeddings are created using OpenAI's text-embedding-ada-002 model, but that's not a requirement. In fact we are looking at embeddings generation through BERT or RoBERTa to benchmark performance.
At prompt time, the plugin retrieves the nearest embeddings to the prompt, and inserts them into a more complete prompt before sending it to the model.
It does use a vector database (pinecone, weaviate, etc.) to store embeddings. The embeddings are created using OpenAI's text-embedding-ada-002 model, but that's not a requirement. In fact we are looking at embeddings generation through BERT or RoBERTa to benchmark performance.
At prompt time, the plugin retrieves the nearest embeddings to the prompt, and inserts them into a more complete prompt before sending it to the model.