Embeddings
Quickly learn how to use Mixedbread's Embeddings API to generate vector representations of text. This guide provides a introduction to creating and utilizing embeddings for semantic search and other NLP tasks, with code examples to get you started immediately.
Embeddings are the secret sauce behind semantic search. Our embedding models convert text into dense vector representations, capturing the meaning and context of the content. You can use them for all kinds of tasks. Read more about embeddings.
Prerequisites
To make a request to our APIs, you will need an API key for authentication. You can create this on your dashboard. Remember to replace YOUR_API_KEY with your actual API key in the following examples.
Embeddings API
Here's an example that demonstrates how to generate embeddings for a list of input texts using our Embeddings API and use them for retrieval.
Need Help?
- Contact us if you have any questions or need assistance.
- Join our discord to connect with other developers and get support.
- Read the API documentation for more details.