text-splitters: add pydocstyle linting (#28127)

As seen in #23188, turned on Google-style docstrings by enabling
`pydocstyle` linting in the `text-splitters` package. Each resulting
linting error was addressed differently: ignored, resolved, suppressed,
and missing docstrings were added.

Fixes one of the checklist items from #25154, similar to #25939 in
`core` package. Ran `make format`, `make lint` and `make test` from the
root of the package `text-splitters` to ensure no issues were found.

---------

Co-authored-by: Erick Friis <erick@langchain.dev>

libs/text-splitters/langchain_text_splitters/sentence_transformers.py

@@ -51,6 +51,20 @@ class SentenceTransformersTokenTextSplitter(TextSplitter):
             )
 
     def split_text(self, text: str) -> List[str]:
+        """Splits the input text into smaller components by splitting text on tokens.
+
+        This method encodes the input text using a private `_encode` method, then
+        strips the start and stop token IDs from the encoded result. It returns the
+        processed segments as a list of strings.
+
+        Args:
+            text (str): The input text to be split.
+
+        Returns:
+            List[str]: A list of string components derived from the input text after
+            encoding and processing.
+        """
+
         def encode_strip_start_and_stop_token_ids(text: str) -> List[int]:
             return self._encode(text)[1:-1]
 
@@ -64,6 +78,17 @@ class SentenceTransformersTokenTextSplitter(TextSplitter):
         return split_text_on_tokens(text=text, tokenizer=tokenizer)
 
     def count_tokens(self, *, text: str) -> int:
+        """Counts the number of tokens in the given text.
+
+        This method encodes the input text using a private `_encode` method and
+        calculates the total number of tokens in the encoded result.
+
+        Args:
+            text (str): The input text for which the token count is calculated.
+
+        Returns:
+            int: The number of tokens in the encoded text.
+        """
         return len(self._encode(text))
 
     _max_length_equal_32_bit_integer: int = 2**32