We enable you to integrate embedding similarity search capabilities into your products and applications.
Create a dataset and choose
embedding-similarity-search as dataset type. The dataset contains all information about your index.
When importing your embeddings you have to provide a embedding, dataset and a referece which is used for you to reference to your specific results.
The index is built for your specific embedding length that's why we need to know that before you can build the index. We support any arbitrary embedding length.
The index can be build at any time. There is no need to wait till all embeddings are imported (Just rebuild at any required time). Depending on the amount of embeddings the index rebuild might take a while.
You can check if the index build is completed
You can send search requests against your specific endpoint as soon as the index build is completed.
This is currently not possible. The feature is on our roadmap. We will give you soon the possibiltiy to remove embeddings using the reference.
Please check if the API key you are using is the same as configured in our API key management https://app.ioannotator.com/api.