From c806694379deb2bfc00687aff2588062e895928d Mon Sep 17 00:00:00 2001
From: captainmirk <77876380+captainmirk@users.noreply.github.com>
Date: Wed, 3 Dec 2025 11:36:06 +0000
Subject: [PATCH] style: fix linting and trailing whitespace

---
 lightrag/lightrag.py | 18 +++++++++++-------
 1 file changed, 11 insertions(+), 7 deletions(-)

diff --git a/lightrag/lightrag.py b/lightrag/lightrag.py
index b9b50ec9..d8be53d8 100644
--- a/lightrag/lightrag.py
+++ b/lightrag/lightrag.py
@@ -525,7 +525,7 @@ class LightRAG:
         _print_config = ",\n  ".join([f"{k} = {v}" for k, v in global_config.items()])
         logger.debug(f"LightRAG init with param:\n  {_print_config}\n")
 
-       # Init Embedding
+        # Init Embedding
         # Step 1: Capture max_token_size and embedding_dim before applying decorator
         embedding_max_token_size = None
         if self.embedding_func and hasattr(self.embedding_func, "max_token_size"):
@@ -675,14 +675,14 @@ class LightRAG:
             return
 
         meta_file = os.path.join(self.working_dir, "lightrag_meta.json")
-        
+
         if os.path.exists(meta_file):
             with open(meta_file, "r", encoding="utf-8") as f:
                 try:
                     meta_data = json.load(f)
                     saved_dim = meta_data.get("embedding_dim")
                     saved_model = meta_data.get("embedding_model_func", "unknown")
-                    
+
                     if saved_dim and saved_dim != self.embedding_dim:
                         raise ValueError(
                             f"Embedding dimension mismatch! "
@@ -691,18 +691,22 @@ class LightRAG:
                             f"Please clear the '{self.working_dir}' directory or switch back to the original model."
                         )
                 except json.JSONDecodeError:
-                    logger.warning(f"Could not parse {meta_file}. Skipping dimension check.")
+                    logger.warning(
+                        f"Could not parse {meta_file}. Skipping dimension check."
+                    )
         else:
             # First run: Save the metadata
             meta_data = {
                 "embedding_dim": self.embedding_dim,
-                "embedding_model_func": self.embedding_func.__class__.__name__ if self.embedding_func else "unknown",
-                "created_at": str(os.path.abspath(self.working_dir))
+                "embedding_model_func": self.embedding_func.__class__.__name__
+                if self.embedding_func
+                else "unknown",
+                "created_at": str(os.path.abspath(self.working_dir)),
             }
             # Ensure directory exists
             if not os.path.exists(self.working_dir):
                 os.makedirs(self.working_dir)
-                
+
             with open(meta_file, "w", encoding="utf-8") as f:
                 json.dump(meta_data, f, indent=4)