fix: llm call enable thinking bug

src/memos/mem_reader/multi_modal_struct.py

@@ -646,6 +646,7 @@ def _merge_memories_with_llm(
 
         return None
 
+    @timed
     def _process_string_fine(
         self,
         fast_memory_items: list[TextualMemoryItem],
@@ -883,6 +884,7 @@ def _get_llm_tool_trajectory_response(self, mem_str: str) -> dict:
             logger.error(f"[MultiModalFine] Error calling LLM for tool trajectory: {e}")
             return []
 
+    @timed
     def _process_tool_trajectory_fine(
         self, fast_memory_items: list[TextualMemoryItem], info: dict[str, Any], **kwargs
     ) -> list[TextualMemoryItem]:

src/memos/mem_reader/read_multi_modal/multi_modal_parser.py

@@ -11,6 +11,7 @@
 from memos.log import get_logger
 from memos.memories.textual.item import SourceMessage, TextualMemoryItem
 from memos.types import MessagesType
+from memos.utils import timed
 
 from .assistant_parser import AssistantParser
 from .base import BaseMessageParser
@@ -120,6 +121,7 @@ def _get_parser(self, message: Any) -> BaseMessageParser | None:
         logger.warning(f"[MultiModalParser] Could not determine parser for message: {message}")
         return None
 
+    @timed
     def parse(
         self,
         message: MessagesType,
@@ -157,6 +159,7 @@ def parse(
             logger.error(f"[MultiModalParser] Error parsing message: {e}")
             return []
 
+    @timed
     def parse_batch(
         self,
         messages: list[MessagesType],
@@ -182,6 +185,7 @@ def parse_batch(
             results.append(items)
         return results
 
+    @timed
     def process_transfer(
         self,
         source: SourceMessage,

src/memos/mem_reader/read_skill_memory/process_skill_memory.py

@@ -36,6 +36,7 @@
     TOOL_GENERATION_PROMPT,
 )
 from memos.types import MessageList
+from memos.utils import timed
 
 
 load_dotenv()
@@ -64,6 +65,7 @@ def _generate_content_by_llm(llm: BaseLLM, prompt_template: str, **kwargs) -> An
         return {} if "json" in prompt_template.lower() else ""
 
 
+@timed
 def _batch_extract_skills(
     task_chunks: dict[str, MessageList],
     related_memories_map: dict[str, list[TextualMemoryItem]],
@@ -97,6 +99,7 @@ def _batch_extract_skills(
     return results
 
 
+@timed
 def _batch_generate_skill_details(
     raw_skills_data: list[tuple[dict[str, Any], str, MessageList]],
     related_skill_memories_map: dict[str, list[TextualMemoryItem]],
@@ -756,6 +759,7 @@ def _delete_skills(
             logger.warning(f"Error deleting local file: {e}")
 
 
+@timed
 def _write_skills_to_file(
     skill_memory: dict[str, Any], info: dict[str, Any], skills_dir_config: dict[str, Any]
 ) -> str:
@@ -1000,6 +1004,7 @@ def _get_skill_file_storage_location() -> str:
         return "LOCAL"
 
 
+@timed
 def process_skill_memory_fine(
     fast_memory_items: list[TextualMemoryItem],
     info: dict[str, Any],
@@ -1064,6 +1069,7 @@ def process_skill_memory_fine(
                 )
                 related_skill_memories_by_task[task_name] = []
 
+    @timed
     def _simple_extract():
         # simple extract skill memory, only one stage
         memories = []
@@ -1096,6 +1102,7 @@ def _simple_extract():
                     )
         return memories
 
+    @timed
     def _full_extract():
         # full extract skill memory, include two stage
         raw_extraction_results = _batch_extract_skills(