External vectors

First of all, thank you for adding this feature!

I am attempting to recreate the example locally from the docs:

import numpy as np
import requests
from txtai.embeddings import Embeddings

data = ['test', 'test2']
def transform(inputs):
  response = requests.post("https://api-inference.huggingface.co/pipeline/feature-extraction/sentence-transformers/nli-mpnet-base-v2",
                           json={"inputs": inputs})

  return np.array(response.json(), dtype=np.float32)

# Index data using vectors from Inference API
embeddings = Embeddings({"method": "external", "transform": transform, "content": True})
embeddings.index([(uid, text, None) for uid, text in enumerate(data)])

print("%-20s %s" % ("Query", "Best Match"))
print("-" * 50)

print(embeddings.search('test', 1))

when I run the search, I receive an empty array. Perhaps data must be a tuple?

[davidmezzetti]

Hi @bramses

I see the settings here use external vectors but faiss is the default ANN storage engine. When external vectors are used, it just uses the transform function to vectorize text but vectors are still stored internally.

Did you intend to have data stored externally?

[luquitared]

Worked like a charm!!!