fix(memory): accept llm kwarg in sync Memory.add()/_create_procedural_memory (#5911) (#5953)

Co-authored-by: ly-wang19 <ly-wang19@users.noreply.github.com>

mem0/memory/main.py

@@ -726,6 +726,7 @@ class Memory(MemoryBase):
         infer: bool = True,
         memory_type: Optional[str] = None,
         prompt: Optional[str] = None,
+        llm=None,
     ):
         """
         Create a new memory.
@@ -802,7 +803,7 @@ class Memory(MemoryBase):
             )
 
         if agent_id is not None and memory_type == MemoryType.PROCEDURAL.value:
-            results = self._create_procedural_memory(messages, metadata=processed_metadata, prompt=prompt)
+            results = self._create_procedural_memory(messages, metadata=processed_metadata, prompt=prompt, llm=llm)
             scale_threshold_notice = detect_scale_threshold_from_add_result(self, results)
             if temporal_usage_notice:
                 display_temporal_usage_notice(self, "sync", "add", *temporal_usage_notice)
@@ -1910,15 +1911,27 @@ class Memory(MemoryBase):
         )
         return memory_id
 
-    def _create_procedural_memory(self, messages, metadata=None, prompt=None):
+    def _create_procedural_memory(self, messages, metadata=None, llm=None, prompt=None):
         """
         Create a procedural memory
 
         Args:
             messages (list): List of messages to create a procedural memory from.
             metadata (dict): Metadata to create a procedural memory from.
+            llm (llm, optional): LLM to use for the procedural memory creation. Defaults to None.
             prompt (str, optional): Prompt to use for the procedural memory creation. Defaults to None.
         """
+        if llm is not None:
+            try:
+                from langchain_core.messages.utils import (
+                    convert_to_messages,  # type: ignore
+                )
+            except Exception:
+                logger.error(
+                    "Import error while loading langchain-core. Please install 'langchain-core' to use procedural memory."
+                )
+                raise
+
         logger.info("Creating procedural memory")
 
         parsed_messages = [
@@ -1931,8 +1944,12 @@ class Memory(MemoryBase):
         ]
 
         try:
-            procedural_memory = self.llm.generate_response(messages=parsed_messages)
-            procedural_memory = remove_code_blocks(procedural_memory)
+            if llm is not None:
+                response = llm.invoke(input=convert_to_messages(parsed_messages))
+                procedural_memory = remove_code_blocks(response.content)
+            else:
+                procedural_memory = self.llm.generate_response(messages=parsed_messages)
+                procedural_memory = remove_code_blocks(procedural_memory)
         except Exception as e:
             logger.error(f"Error generating procedural memory summary: {e}")
             raise