Run Embedding Inference

Generates vector embeddings for the provided dataset using a trained embedding model. Returns a mapping of row indices to embedding vectors.

POST /api/models/embedding/{model_id}/infer

Python

Python

import os
from woodwide import WoodWide

client = WoodWide(
    api_key=os.environ.get("WOOD_WIDE_AI_API_KEY"),  # This is the default and can be omitted
)
response = client.api.models.embedding.infer(
    model_id="model_id",
)
print(response.embeddings)

200

{
  "embeddings": {}
}

Authorizations

Authorization · string · header · required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Path Parameters

model_id · string | null · required

Query Parameters

dataset_id · string | null

dataset_name · string | null

model_name · string | null

Body

application/x-www-form-urlencoded

coerce_schema · boolean · default: true

Response

200

application/json

Successful Response

Response for embedding models. 'embeddings' key contains a map of row indices to their vector embeddings.

embeddings · Embeddings · object · required

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