Embeddings
Embeddings are numerical vectors that represent text’s meaning, enabling machines to compare and analyze language. They power tasks like search, classification, and recommendations by capturing semantic relationships in a compact form.
To get a full list of embedding models visit cortecs.ai and filter by the Embedding tag.
from openai import OpenAI
client = OpenAI(
base_url="https://cortecs.ai/api/v1/models/serverless/embeddings",
api_key="<API_KEY>",
)
response = client.embeddings.create(
input="Your text string goes here",
model="<MODEL_NAME>"
)
print(response.data[0].embedding)
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