Loaded the embedding model via api

my_agent/utils/models_loader.py

@@ -7,6 +7,7 @@ from dotenv import load_dotenv
 load_dotenv()
 import os
 import requests
+import numpy as np
 # from langchain_huggingface import HuggingFaceEndpoint
 os.environ['HUGGINGFACEHUB_ACCESS_TOKEN']=os.getenv('HUGGINGFACEHUB_ACCESS_TOKEN')
 login(os.environ['HUGGINGFACEHUB_ACCESS_TOKEN'])
@@ -38,7 +39,8 @@ class HFEmbeddingAPI:
             json={"inputs": texts}
         )
         response.raise_for_status()
-        return response.json()
+        embeddings=response.json()
+        return np.array(embeddings[0]) if len(embeddings) == 1 else np.array(embeddings)
 
 # Instantiate your API-backed "SentenceTransformer"
 ST = HFEmbeddingAPI(