Memory Retention

.gitignore

@@ -3,4 +3,5 @@
 .DS_Store
 dist/
 README_hidden.md
-**/__pycache__/
+**/__pycache__/
+.idea

README.md

@@ -53,6 +53,8 @@ memary will default to the locally run models unless explicitly specified.
 ```
 OPENAI_API_KEY="YOUR_API_KEY"
 NEO4J_PW="YOUR_NEO4J_PW"
+NEO4J_USER="YOUR_NEO4J_USER"
+NEO4J_DB="YOUR_NEO4J_DATABASE"
 NEO4J_URL="YOUR_NEO4J_URL"
 PERPLEXITY_API_KEY="YOUR_API_KEY"
 GOOGLEMAPS_API_KEY="YOUR_API_KEY"

src/memary/agent/base_agent.py

@@ -71,10 +71,15 @@ def __init__(
         pplx_api_key = os.getenv("PERPLEXITY_API_KEY")
 
         # Neo4j credentials
-        self.neo4j_username = "neo4j"
+        # self.neo4j_username = "neo4j"
+        # Rajib - Neo4J user was hardcoded.
+        # Moved it to .env
+        self.neo4j_username = os.getenv("NEO4J_USER")
         self.neo4j_password = os.getenv("NEO4J_PW")
         self.neo4j_url = os.getenv("NEO4J_URL")
-        database = "neo4j"
+        # Adding the database also as env variable
+        database = os.getenv("NEO4J_DB")
+        # database = "neo4j"
 
         # initialize APIs
         self.load_llm_model(llm_model_name)

src/memary/memory/base_memory.py

@@ -1,5 +1,6 @@
 import json
 import logging
+import math
 
 from abc import ABC, abstractmethod
 from datetime import datetime, timedelta
@@ -77,6 +78,29 @@ def remove_memory_by_index(self, index):
             logging.info("Invalid index. Memory item not removed.")
             return False
 
+    def calculate_retention_score(self, strength:int,days_elapsed_since_last_used:int):
+        """
+        strength: This parameter denotes the strength of the memory.The strenght of the memory
+        is equivalent to the number of times the memory item has been accessed. In case of entity,
+        this will be the number of times(count), the entity has been used
+        days_elapsed_since_last_used: This is the duration in days that has elapsed from today till the
+        memory was last accessed.
+        """
+        score = math.exp(-days_elapsed_since_last_used / strength)
+
+        return score
+
+    def forget_memory(self,threshold_retention_score):
+        """
+        This function calcualtes the retention score for each memory item
+        and then keeps the one whose score is more than threshold
+        """
+        today = datetime.today()
+        self.memory = [item for item in self.return_memory if
+                             self.calculate_retention_score(item.count, (today - item.date).days) >= threshold_retention_score]
+
+        logging.info("Old memory has been forgotten.")
+
     def clear_memory(self):
         self.memory = []
         if self.file_name:

src/memary/memory/entity_knowledge_store.py

@@ -23,7 +23,6 @@ def init_memory(self):
     def return_memory(self):
         return self.knowledge_memory
 
-
     def load_memory_from_file(self):
         try:
             with open(self.file_name, 'r') as file:
@@ -46,10 +45,9 @@ def add_memory(self, memory_stream: list[MemoryItem]):
         Args:
             memory_stream (list): list of MemoryItem
         """
-        knowledge_meory = self._convert_memory_to_knowledge_memory(
+        knowledge_memory = self._convert_memory_to_knowledge_memory(
             memory_stream)
-        self._update_knowledge_memory(knowledge_meory)
-
+        self._update_knowledge_memory(knowledge_memory)
 
     def _update_knowledge_memory(self, knowledge_memory: list):
         """update self.knowledge memory with new knowledge memory items
@@ -87,6 +85,3 @@ def _convert_memory_to_knowledge_memory(
 
     def get_memory(self) -> list[KnowledgeMemoryItem]:
         return self.knowledge_memory
-
-
-