this didnt fucking commit i fucking hate you git

modules/markovmemory.py

@@ -7,41 +7,46 @@ from modules.volta.main import _
 import logging
 logger = logging.getLogger("goober")
 
-def get_file_info(file_path):
+def get_file_info(file_path: str) -> dict:
     try:
         file_size = os.path.getsize(file_path)
         with open(file_path, "r") as f:
             lines = f.readlines()
-        return {"file_size_bytes": file_size, "line_count": len(lines)}
+        return {
+            "file_size_bytes": file_size,
+            "line_count": len(lines)
+        }
     except Exception as e:
         return {"error": str(e)}
-def load_memory():
+
-    data = []
+def load_memory() -> list:
     try:
         with open(MEMORY_FILE, "r") as f:
-            data = json.load(f)
+            return json.load(f)
     except FileNotFoundError:
-        pass
+        return []
 
-    return data
+def save_memory(memory: list) -> None:
-def save_memory(memory):
     with open(MEMORY_FILE, "w") as f:
         json.dump(memory, f, indent=4)
-def train_markov_model(memory, additional_data=None):
+
-    if not memory:
+def train_markov_model(memory: list, additional_data: list = None):
-        return None
+    lines = [line for line in (memory or []) if isinstance(line, str)]
-    filtered_memory = [line for line in memory if isinstance(line, str)]
+
     if additional_data:
-        filtered_memory.extend(line for line in additional_data if isinstance(line, str))
+        lines.extend(line for line in additional_data if isinstance(line, str))
-    if not filtered_memory:
+
+    if not lines:
         return None
-    text = "\n".join(filtered_memory)
+
-    model = markovify.NewlineText(text, state_size=2)
+    text = "\n".join(lines)
-    return model
+    return markovify.NewlineText(text, state_size=2)
-def save_markov_model(model, filename='markov_model.pkl'):
+
+def save_markov_model(model, filename: str = 'markov_model.pkl') -> None:
     with open(filename, 'wb') as f:
         pickle.dump(model, f)
-def load_markov_model(filename='markov_model.pkl'):
+
+def load_markov_model(filename: str = 'markov_model.pkl'):
     try:
         with open(filename, 'rb') as f:
             model = pickle.load(f)