feat(huggingface_restapi.py): Support multiple hf embedding types + async hf embeddings

Closes https://github.com/BerriAI/litellm/issues/3261

litellm/tests/test_embedding.py

@@ -409,6 +409,62 @@ def test_hf_embedding():
 
 # test_hf_embedding()
 
+from unittest.mock import MagicMock, patch
+
+
+def tgi_mock_post(*args, **kwargs):
+    import json
+
+    expected_data = {
+        "inputs": {
+            "source_sentence": "good morning from litellm",
+            "sentences": ["this is another item"],
+        }
+    }
+    assert (
+        json.loads(kwargs["data"]) == expected_data
+    ), "Data does not match the expected data"
+    mock_response = MagicMock()
+    mock_response.status_code = 200
+    mock_response.headers = {"Content-Type": "application/json"}
+    mock_response.json.return_value = [0.7708950042724609]
+    return mock_response
+
+
+from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
+
+
+@pytest.mark.parametrize("sync_mode", [True, False])
+@pytest.mark.asyncio
+async def test_hf_embedding_sentence_sim(sync_mode):
+    try:
+        # huggingface/microsoft/codebert-base
+        # huggingface/facebook/bart-large
+        if sync_mode is True:
+            client = HTTPHandler(concurrent_limit=1)
+        else:
+            client = AsyncHTTPHandler(concurrent_limit=1)
+        with patch.object(client, "post", side_effect=tgi_mock_post) as mock_client:
+            data = {
+                "model": "huggingface/TaylorAI/bge-micro-v2",
+                "input": ["good morning from litellm", "this is another item"],
+                "client": client,
+            }
+            if sync_mode is True:
+                response = embedding(**data)
+            else:
+                response = await litellm.aembedding(**data)
+
+            print(f"response:", response)
+
+            mock_client.assert_called_once()
+
+        assert isinstance(response.usage, litellm.Usage)
+
+    except Exception as e:
+        # Note: Huggingface inference API is unstable and fails with "model loading errors all the time"
+        raise e
+
 
 # test async embeddings
 def test_aembedding():