fix : force process_step as abstractmethod in base class

Author: colinfrisch

mesa_llm/memory/episodic_memory.py

@@ -131,3 +131,14 @@ def get_communication_history(self) -> str:
                 if "message" in entry.content
             ]
         )
+
+    def process_step(self, pre_step: bool = False):
+        """
+        Process the step of the agent :
+        - Add the new entry to the memory
+        - Display the new entry
+        """
+        if pre_step:
+            self.add_to_memory(type="observation", content=self.step_content)
+            self.step_content = {}
+            return

mesa_llm/memory/memory.py

@@ -111,6 +111,15 @@ def get_communication_history(self) -> str:
         Get the communication history in a format that can be used for reasoning
         """
 
+    @abstractmethod
+    def process_step(self, pre_step: bool = False):
+        r"""
+        A function that is called before and after the step of the agent is called.
+        It is implemented to ensure that the memory is up to date when the agent is starting a new step.
+
+        /!\ If you consider that you do not need this function, you can write "pass" in its implementation.
+        """
+
     def add_to_memory(self, type: str, content: dict):
         """
         Add a new entry to the memory

mesa_llm/memory/st_lt_memory.py

@@ -101,15 +101,15 @@ def process_step(self, pre_step: bool = False):
             return
 
         elif not self.short_term_memory[-1].content.get("step", None):
-            pre_step = self.short_term_memory.pop()
-            self.step_content.update(pre_step.content)
-            new_entry = MemoryEntry(
+            pre_step_entry = self.short_term_memory.pop()
+            self.step_content.update(pre_step_entry.content)
+            new_st_entry = MemoryEntry(
                 agent=self.agent,
                 content=self.step_content,
                 step=self.agent.model.steps,
             )
 
-            self.short_term_memory.append(new_entry)
+            self.short_term_memory.append(new_st_entry)
             self.step_content = {}
 
         # Consolidate memory if the short term memory is over capacity