Search · Similarity · RAG

Embedding

Beta

Turn text into vectors for semantic search, similarity, and RAG pipelines.

Overview

Embedding

Generate embedding vectors for semantic search, clustering, deduplication, recommendation, and RAG (retrieval-augmented generation).

Endpoint: /v1/embeddings
Example model: nomic-embed-text-v1.5

API

API example

# 1) discover an online embedding model — Grid's set changes constantly,
#    don't hardcode an id in your code.
MODEL=$(curl -s https://api.openalchemy.io/v1/models \
  -H "Authorization: Bearer $OPENALCHEMY_API_KEY" \
  | jq -r '.data[] | select(.online and .endpoint_type=="embedding") | .id' \
  | head -1)

# 2) embed
curl https://api.openalchemy.io/v1/embeddings \
  -H "Authorization: Bearer $OPENALCHEMY_API_KEY" \
  -H "X-Project-Id: $YOUR_PROJECT_ID" \
  -H "Content-Type: application/json" \
  -d "{
    \"model\": \"$MODEL\",
    \"input\": \"Where is the best ramen in Tokyo?\"
  }"

Status

Quota and pricing (per project)

Allotments and rate limits apply to the project that issued the API key. A second domain-scoped policy layer constrains which origins may invoke each modality.

Read the docs for this modality →

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