cleanup (#9923)

Co-authored-by: riship <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

torch_geometric/nn/nlp/txt2kg.py

@@ -9,7 +9,7 @@
 
 CLIENT = None
 GLOBAL_NIM_KEY = ""
-SYSTEM_PROMPT = "Please convert the above text into a list of knowledge triples with the form ('entity', 'relation', 'entity'). Seperate each with a new line. Do not output anything else. Try to focus on key triples that form a connected graph.”"
+SYSTEM_PROMPT = "Please convert the above text into a list of knowledge triples with the form ('entity', 'relation', 'entity'). Seperate each with a new line. Do not output anything else. Try to focus on key triples that form a connected graph.”"  #noqa
 
 
 class TXT2KG():
@@ -30,13 +30,16 @@ class TXT2KG():
 
     Args:
         NVIDIA_NIM_MODEL : str, optional
-            The name of the NVIDIA NIM model to use (default: "nvidia/llama-3.1-nemotron-70b-instruct").
+            The name of the NVIDIA NIM model to use.
+            (default: "nvidia/llama-3.1-nemotron-70b-instruct").
         NVIDIA_API_KEY : str, optional
             The API key for accessing NVIDIA's NIM models (default: "").
         local_LM : bool, optional
-            A flag indicating whether a local Language Model (LM) should be used (default: False).
+            A flag indicating whether a local Language Model (LM)
+            should be used (default: False).
         chunk_size : int, optional
-            The size of the chunks in which the text data is processed (default: 512).
+            The size of the chunks in which the text data is processed
+            (default: 512).
     """
     def __init__(
         self,
@@ -89,15 +92,15 @@ def _chunk_to_triples_str_local(self, txt: str) -> str:
         # for debug
         self.total_chars_parsed += len(txt)
         self.time_to_parse += round(time.time() - chunk_start_time, 2)
-        self.avg_chars_parsed_per_sec = self.total_chars_parsed / self.time_to_parse
+        self.avg_chars_parsed_per_sec = self.total_chars_parsed / self.time_to_parse  #noqa
         return out_str
 
     def add_doc_2_KG(
         self,
         txt: str,
         QA_pair: Optional[Tuple[str, str]] = None,
     ) -> None:
-        """Add a document to the Knowledge Graph (KG) by extracting triples from the text.
+        """Add a document to the Knowledge Graph (KG).
 
         Args:
             txt (str): The text to extract triples from.
@@ -109,8 +112,8 @@ def add_doc_2_KG(
         - None
         """
         # Ensure NVIDIA_API_KEY is set before proceeding
-        assert self.NVIDIA_API_KEY != '', "Please init TXT2KG w/ NVIDIA_API_KEY or set local_lm flag to True"
-
+        assert self.NVIDIA_API_KEY != '', \
+            "Please init TXT2KG w/ NVIDIA_API_KEY or set local_lm=True"
         if QA_pair:
             # QA_pairs should be unique keys, so check if it already exists in the KG
             assert QA_pair not in self.relevant_triples.keys()