Make memory JSON-serializable by default; simplify conversation history; remove run-id result storage (#68)

* refactor: standard_agent memory serializability, removing using deque for the rolling window storing conversation history

Author: rishikesh-jentic

agents/standard_agent.py

@@ -8,7 +8,6 @@
 from __future__ import annotations
 
 from  collections.abc import MutableMapping
-from  collections import deque
 from  agents.reasoner.base import BaseReasoner, ReasoningResult
 from  agents.llm.base_llm import BaseLLM
 from  agents.tools.base import JustInTimeToolingBase
@@ -61,7 +60,8 @@ def __init__(
         self.reasoner = reasoner
 
         self.goal_preprocessor = goal_preprocessor
-        self.memory.setdefault("conversation_history", deque(maxlen=conversation_history_window))
+        self.conversation_history_window = conversation_history_window
+        self.memory.setdefault("conversation_history", [])
 
         self._state: AgentState = AgentState.READY
 
@@ -77,19 +77,17 @@ def solve(self, goal: str) -> ReasoningResult:
         if self.goal_preprocessor:
             revised_goal, intervention_message = self.goal_preprocessor.process(goal, self.memory.get("conversation_history"))
             if intervention_message:
-                self.memory["conversation_history"].append({ "goal": goal, "result": f"user intervention message: {intervention_message}"})
+                self._record_interaction({"goal": goal, "result": f"user intervention message: {intervention_message}"})
                 return ReasoningResult(success=False, final_answer=intervention_message)
             goal = revised_goal
 
-        self.memory[f"goal:{run_id}"] = goal
         self._state = AgentState.BUSY
 
         try:
             result = self.reasoner.run(goal)
             result.final_answer = self.llm.prompt(_PROMPTS["summarize"].format(goal=goal, history=getattr(result, "transcript", "")))
 
-            self.memory[f"result:{run_id}"] = result
-            self.memory["conversation_history"].append({"goal": goal, "result": result.final_answer})
+            self._record_interaction({"goal": goal, "result": result.final_answer})
             self._state = AgentState.READY
 
             duration_ms = int((time.perf_counter() - start_time) * 1000)
@@ -109,3 +107,9 @@ def solve(self, goal: str) -> ReasoningResult:
         except Exception:
             self._state = AgentState.NEEDS_ATTENTION
             raise
+
+    def _record_interaction(self, entry: dict) -> None:
+        if self.conversation_history_window <= 0:
+            return
+        self.memory["conversation_history"].append(entry)
+        self.memory["conversation_history"][:] = self.memory["conversation_history"][-self.conversation_history_window:]

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "standard-agent"
-version = "0.1.2"
+version = "0.1.3"
 description = "A simple, modular library for building AI agents—with a composable core and plug‑in components."
 requires-python = ">=3.11"
 readme = "README.md"

tests/agents/test_standard_agent.py

@@ -1,6 +1,7 @@
 from typing import Any, Deque, Dict, List, Optional, Tuple
 
 import pytest
+import json
 
 from agents.standard_agent import StandardAgent, AgentState
 from agents.reasoner.base import BaseReasoner, ReasoningResult
@@ -88,10 +89,6 @@ def test_agent_solve_sets_final_answer_from_summarizer_and_records_history(monke
     assert hist[-1]["goal"] == "find answer"
     assert hist[-1]["result"] == "SUMMARIZED"
 
-    # Goal and result stored with deterministic run id
-    assert memory.get("goal:RUN123") == "find answer"
-    assert isinstance(memory.get("result:RUN123"), ReasoningResult)
-
 
 def test_agent_uses_goal_preprocessor_and_returns_intervention_message(monkeypatch):
     _fixed_uuid4(monkeypatch, "RUNINT")
@@ -210,3 +207,29 @@ def test_agent_initial_state_is_ready():
     assert agent.state == AgentState.READY
 
 
+
+def test_agent_memory_is_json_serializable(monkeypatch):
+    llm = DummyLLM(text_queue=["S1", "S2"])
+    tools = DummyTools()
+    memory: Dict[str, Any] = DictMemory()
+    agent = StandardAgent(llm=llm, tools=tools, memory=memory, reasoner=DummyReasoner(), conversation_history_window=2)
+
+    agent.solve("g1")
+    agent.solve("g2")
+
+    dumped = json.dumps(agent.memory)
+    assert isinstance(dumped, str)
+    assert isinstance(agent.memory.get("conversation_history"), list)
+    assert len(agent.memory["conversation_history"]) == 2
+
+
+def test_agent_conversation_history_disabled_window():
+    llm = DummyLLM(text_queue=["S"])  # summarizer output
+    tools = DummyTools()
+    memory: Dict[str, Any] = DictMemory()
+    agent = StandardAgent(llm=llm, tools=tools, memory=memory, reasoner=DummyReasoner(), conversation_history_window=0)
+
+    agent.solve("g1")
+
+    assert memory.get("conversation_history") == []
+