Generate text embeddings for semantic search, RAG, clustering, and similarity matching. Compatible with the OpenAI embeddings endpoint.
POST https://aiwave.live/v1/embeddings
curl https://aiwave.live/v1/embeddings \
-H "Authorization: Bearer sk-YOUR_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "text-embedding-3-small",
"input": "The quick brown fox jumps over the lazy dog"
}'
Store document embeddings in a vector database, retrieve relevant chunks at query time. Learn more →
Find similar documents, products, or content based on meaning, not just keywords.