chore: vscode ruff, and format

packages/leann-core/src/leann/api.py

@@ -614,7 +614,7 @@ class LeannSearcher:
             zmq_port=zmq_port,
         )
         # logger.info(f"  Generated embedding shape: {query_embedding.shape}")
-        time.time() - start_time
+        # time.time() - start_time
         # logger.info(f"  Embedding time: {embedding_time} seconds")
 
         start_time = time.time()
@@ -680,8 +680,9 @@ class LeannSearcher:
         This method should be called after you're done using the searcher,
         especially in test environments or batch processing scenarios.
         """
-        if hasattr(self.backend_impl, "embedding_server_manager"):
-            self.backend_impl.embedding_server_manager.stop_server()
+        backend = getattr(self.backend_impl, "embedding_server_manager", None)
+        if backend is not None:
+            backend.stop_server()
 
     # Enable automatic cleanup patterns
     def __enter__(self):

packages/leann-core/src/leann/chat.py

@@ -707,20 +707,28 @@ class GeminiChat(LLMInterface):
         logger.info(f"Sending request to Gemini with model {self.model}")
 
         try:
-            # Set generation configuration
-            generation_config = {
-                "temperature": kwargs.get("temperature", 0.7),
-                "max_output_tokens": kwargs.get("max_tokens", 1000),
-            }
+            from google.genai.types import GenerateContentConfig
+
+            generation_config = GenerateContentConfig(
+                temperature=kwargs.get("temperature", 0.7),
+                max_output_tokens=kwargs.get("max_tokens", 1000),
+            )
 
             # Handle top_p parameter
             if "top_p" in kwargs:
-                generation_config["top_p"] = kwargs["top_p"]
+                generation_config.top_p = kwargs["top_p"]
 
             response = self.client.models.generate_content(
-                model=self.model, contents=prompt, config=generation_config
+                model=self.model,
+                contents=prompt,
+                config=generation_config,
             )
-            return response.text.strip()
+            # Handle potential None response text
+            response_text = response.text
+            if response_text is None:
+                logger.warning("Gemini returned None response text")
+                return ""
+            return response_text.strip()
         except Exception as e:
             logger.error(f"Error communicating with Gemini: {e}")
             return f"Error: Could not get a response from Gemini. Details: {e}"

packages/leann-core/src/leann/cli.py

@@ -1,7 +1,7 @@
 import argparse
 import asyncio
 from pathlib import Path
-from typing import Union
+from typing import Optional, Union
 
 from llama_index.core import SimpleDirectoryReader
 from llama_index.core.node_parser import SentenceSplitter
@@ -647,7 +647,7 @@ Examples:
             return False
 
     def _delete_index_directory(
-        self, index_dir: Path, index_name: str, project_path: Path | None = None
+        self, index_dir: Path, index_name: str, project_path: Optional[Path] = None
     ):
         """Actually delete the index directory"""
         try:

packages/leann-core/src/leann/registry.py

@@ -5,7 +5,7 @@ import importlib.metadata
 import json
 import logging
 from pathlib import Path
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, Optional, Union
 
 if TYPE_CHECKING:
     from leann.interface import LeannBackendFactoryInterface
@@ -47,7 +47,7 @@ def autodiscover_backends():
     # print("INFO: Backend auto-discovery finished.")
 
 
-def register_project_directory(project_dir: str | Path | None = None):
+def register_project_directory(project_dir: Optional[Union[str, Path]] = None):
     """
     Register a project directory in the global LEANN registry.