add: workflow/procedural_memory

reme/workflow/procedural_memory/summarizer/__init__.py

@@ -1,12 +1,15 @@
+"""Summarizer operators for procedural memory workflow.
+
+This package exposes and registers summarization-related operators such as
+`TrajectoryPreprocess` and `SuccessExtraction` to the global operator registry.
+"""
+
 from ....core import R
 from .trajectory_preprocess import TrajectoryPreprocess
 from .success_extraction import SuccessExtraction
 
-__all__ = [
-    "TrajectoryPreprocess",
-    "SuccessExtraction",
-]
+__all__ = ["TrajectoryPreprocess", "SuccessExtraction"]
 
 for name in __all__:
     tool_class = globals()[name]
-    R.op.register()(tool_class)
+    R.op.register()(tool_class)

reme/workflow/procedural_memory/summarizer/success_extraction.py

@@ -6,14 +6,17 @@ trajectories, identifying patterns and strategies that lead to success.
 
 from typing import List
 
+from loguru import logger
 
-from ....core.enumeration import Role
+from ....core.enumeration import MemoryType, Role
 from ....core.op import BaseOp
-from ....core.enumeration import MemoryType
 from ....core.schema.memory_node import MemoryNode
 from ....core.schema.message import Message, Trajectory
-from ....core.utils.llm_utils import merge_messages_content, parse_json_experience_response, get_trajectory_context
-from loguru import logger
+from ....core.utils.llm_utils import (
+    get_trajectory_context,
+    merge_messages_content,
+    parse_json_experience_response,
+)
 
 
 class SuccessExtraction(BaseOp):
@@ -71,7 +74,7 @@ class SuccessExtraction(BaseOp):
         )
 
         def parse_task_memories(message: Message) -> list[MemoryNode]:
-            task_memories_data = parse_json_experience_response(message.content) # extract content
+            task_memories_data = parse_json_experience_response(message.content)  # extract content
             task_memories = []
 
             for tm_data in task_memories_data:

reme/workflow/procedural_memory/summarizer/trajectory_preprocess.py

@@ -4,11 +4,12 @@ This module provides operations to preprocess and classify trajectories
 into success and failure categories based on score thresholds.
 """
 
-from typing import List, Dict
+from typing import Dict, List
+
+from loguru import logger
 
 from ....core.op import BaseOp
 from ....core.schema.message import Trajectory
-from loguru import logger
 
 
 class TrajectoryPreprocess(BaseOp):