Metal is a managed service for ML Embeddings.
This notebook shows how to use Metal’s retriever. First, you will need to sign up for Metal and get an API key. You can do so here 
%pip install -qU  metal_sdk

from metal_sdk.metal import Metal

API_KEY = ""
CLIENT_ID = ""
INDEX_ID = ""

metal = Metal(API_KEY, CLIENT_ID, INDEX_ID)

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Ingest Documents

You only need to do this if you haven’t already set up an index 
metal.index({"text": "foo1"})
metal.index({"text": "foo"})

{'data': {'id': '642739aa7559b026b4430e42',
  'text': 'foo',
  'createdAt': '2023-03-31T19:51:06.748Z'}}

​
Query

Now that our index is set up, we can set up a retriever and start querying it. 
from langchain_community.retrievers import MetalRetriever

retriever = MetalRetriever(metal, params={"limit": 2})

retriever.invoke("foo1")

[Document(page_content='foo1', metadata={'dist': '1.19209289551e-07', 'id': '642739a17559b026b4430e40', 'createdAt': '2023-03-31T19:50:57.853Z'}),
 Document(page_content='foo1', metadata={'dist': '4.05311584473e-06', 'id': '642738f67559b026b4430e3c', 'createdAt': '2023-03-31T19:48:06.769Z'})]