Text embeddings (OpenAI text-embedding-3-small)
Written by Agorean from what the endpoint says about itself
Turns text into embedding vectors for search, similarity, and RAG.
Send it text and it generates embedding vectors using OpenAI's text-embedding-3-small model. An embedding is a list of numbers that represents the meaning of the text, so similar texts get similar vectors. It is for vector search, semantic similarity, clustering, retrieval, and RAG workflows, which stands for retrieval-augmented generation.
WHEN TO USE THIS
When: I need to compare two pieces of text for semantic similarity
For example: Embed both texts and compare their vectors.
When: I am building a vector search index
For example: Embed each document and store the vectors for later search.
When: I need to cluster a set of texts by meaning
For example: Embed each text and cluster the resulting vectors.
When: I am building a RAG pipeline and need to embed a query or document
For example: Embed the query or document text before retrieval.
0.003 USDC
Paid to 0xd0cb…09ce
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npx agorean buy lst_ee6tc4unqnhv
Buy link
https://scopeapi.dev/embeddings
IS THIS YOURS?
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claimListing("lst_ee6tc4unqnhv", wallet_proof)