[pre-commit.ci] auto fixes from pre-commit.com hooks

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Author: pre-commit-ci[bot]

examples/llm/txt2kg_rag.py

@@ -142,9 +142,8 @@ def parse_args():
         '--skip_graph_rag', action="store_true",
         help="Skip the graph RAG step. "
         "Used to compare the performance of Vector+Graph RAG vs Vector RAG.")
-    parser.add_argument(
-        '--omit_text_graph', action="store_true",
-        help="Omit the text graph from the LLM Input.")
+    parser.add_argument('--omit_text_graph', action="store_true",
+                        help="Omit the text graph from the LLM Input.")
     args = parser.parse_args()
 
     assert args.NV_NIM_KEY, "NVIDIA API key is required for TXT2KG and eval"
@@ -405,8 +404,8 @@ def make_dataset(args):
         topk=5,  # nodes
         topk_e=5,  # edges
         cost_e=.5,  # edge cost
-        num_clusters=10, # num clusters
-        with_text_graph= not args.omit_text_graph) # option to omit text graph
+        num_clusters=10,  # num clusters
+        with_text_graph=not args.omit_text_graph)  # option to omit text graph
 
     # number of neighbors for each seed node selected by KNN
     fanout = 100

torch_geometric/utils/rag/backend_utils.py

@@ -368,7 +368,8 @@ class to use. Defaults to LocalFeatureStore.
 def make_pcst_filter(triples: List[Tuple[str, str,
                                          str]], model: SentenceTransformer,
                      topk: int = 5, topk_e: int = 5, cost_e: float = 0.5,
-                     num_clusters: int = 1, with_text_graph: bool = True) -> None:
+                     num_clusters: int = 1,
+                     with_text_graph: bool = True) -> None:
     """Creates a PCST (Prize Collecting Tree) filter.
 
     :param triples: List of triples (head, relation, tail) representing knowledge graph data