fix(embeddings): huggingface hub embeddings and TEI (#14489)

**Description:** This PR fixes `HuggingFaceHubEmbeddings` by making the
API token optional (as in the client beneath). Most models don't require
one. I also updated the notebook for TEI (text-embeddings-inference)
accordingly as requested here #14288. In addition, I fixed a mistake in
the POST call parameters.

**Tag maintainers:** @baskaryan

libs/community/langchain_community/embeddings/huggingface_hub.py

@@ -1,9 +1,9 @@
 import json
+import os
 from typing import Any, Dict, List, Optional
 
 from langchain_core.embeddings import Embeddings
 from langchain_core.pydantic_v1 import BaseModel, Extra, root_validator
-from langchain_core.utils import get_from_dict_or_env
 
 DEFAULT_MODEL = "sentence-transformers/all-mpnet-base-v2"
 VALID_TASKS = ("feature-extraction",)
@@ -48,9 +48,10 @@ class HuggingFaceHubEmbeddings(BaseModel, Embeddings):
     @root_validator()
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
-        huggingfacehub_api_token = get_from_dict_or_env(
-            values, "huggingfacehub_api_token", "HUGGINGFACEHUB_API_TOKEN"
+        huggingfacehub_api_token = values["huggingfacehub_api_token"] or os.getenv(
+            "HUGGINGFACEHUB_API_TOKEN"
         )
+
         try:
             from huggingface_hub import InferenceClient
 
@@ -92,7 +93,7 @@ class HuggingFaceHubEmbeddings(BaseModel, Embeddings):
         texts = [text.replace("\n", " ") for text in texts]
         _model_kwargs = self.model_kwargs or {}
         responses = self.client.post(
-            json={"inputs": texts, "parameters": _model_kwargs, "task": self.task}
+            json={"inputs": texts, "parameters": _model_kwargs}, task=self.task
         )
         return json.loads(responses.decode())