community: Added functions to make async calls to HuggingFaceHub's embedding endpoint in HuggingFaceHubEmbeddings class (#15737)

**Description:**
Added aembed_documents() and aembed_query() async functions in
HuggingFaceHubEmbeddings class in
langchain_community\embeddings\huggingface_hub.py file. It will support
to make async calls to HuggingFaceHub's
embedding endpoint and generate embeddings asynchronously.

Test Cases: Added test_huggingfacehub_embedding_async_documents() and
test_huggingfacehub_embedding_async_query()
functions in test_huggingface_hub.py file to test the two async
functions created in HuggingFaceHubEmbeddings class.

Documentation: Updated huggingfacehub.ipynb with steps to install
huggingface_hub package and use
HuggingFaceHubEmbeddings.

**Dependencies:** None,
**Twitter handle:** I do not have a Twitter account

---------

Co-authored-by: H161961 <Raunak.Raunak@Honeywell.com>

docs/docs/integrations/text_embedding/huggingfacehub.ipynb

@@ -106,7 +106,7 @@
    "metadata": {},
    "outputs": [
     {
-     "name": "stdin",
+     "name": "stdout",
      "output_type": "stream",
      "text": [
       "Enter your HF Inference API Key:\n",
@@ -148,6 +148,75 @@
     "query_result = embeddings.embed_query(text)\n",
     "query_result[:3]"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "19ef2d31",
+   "metadata": {},
+   "source": [
+    "## Hugging Face Hub\n",
+    "We can also generate embeddings locally via the Hugging Face Hub package, which requires us to install ``huggingface_hub ``"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "39e85945",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install huggingface_hub"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c78a2779",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain_community.embeddings import HuggingFaceHubEmbeddings"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "116f3ce7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "embeddings = HuggingFaceHubEmbeddings()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d6f97ee9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "text = \"This is a test document.\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fb6adc67",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "query_result = embeddings.embed_query(text)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1f42c311",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "query_result[:3]"
+   ]
   }
  ],
  "metadata": {