Fix history from long term memory

prediction_market_agent/agents/microchain_agent/deploy.py

@@ -79,7 +79,6 @@ def build_agent(self, market_type: MarketType) -> Agent:
             unformatted_system_prompt=unformatted_system_prompt,
             allow_stop=True,
             long_term_memory=self.long_term_memory,
-            import_actions_from_memory=self.import_actions_from_memory,
             keys=APIKeys(),
             functions_config=self.functions_config,
             enable_langfuse=self.enable_langfuse,
@@ -107,6 +106,27 @@ def run(
         """
         self.run_general_agent(market_type=market_type)
 
+    def initialise_agent(self) -> None:
+        self.agent.reset()
+        self.agent.build_initial_messages()
+
+        # Inject past history if wanted.
+        if self.import_actions_from_memory:
+            latest_saved_memories = check_not_none(
+                self.long_term_memory,
+                "long_term_memory is needed for this functionality.",
+            ).search(limit=self.import_actions_from_memory)
+            messages_to_insert = [
+                m.metadata_dict
+                for m in latest_saved_memories[
+                    ::-1
+                ]  # Revert the list to have the oldest messages first, as they were in the history.
+                if check_not_none(m.metadata_dict)["role"]
+                != "system"  # Do not include system message as that one is automatically in the beginning of the history.
+            ]
+            # Inject them after the system message.
+            self.agent.history[1:1] = messages_to_insert
+
     @observe()
     def run_general_agent(self, market_type: MarketType) -> None:
         if market_type != MarketType.OMEN:
@@ -118,6 +138,9 @@ def run_general_agent(self, market_type: MarketType) -> None:
         if goal:
             self.agent.prompt = goal.to_prompt()
 
+        # Initialise the agent before our working loop.
+        self.initialise_agent()
+
         # Save formatted system prompt
         initial_formatted_system_prompt = self.agent.system_prompt
 
@@ -130,8 +153,8 @@ def run_general_agent(self, market_type: MarketType) -> None:
 
             starting_history_length = len(self.agent.history)
             try:
-                # After the first iteration, resume=True to not re-initialize the agent.
-                self.agent.run(iterations=1, resume=iteration > 0)
+                # We initialise agent manually because of inserting past history, so force resume=True, to not re-initialise it which would remove the history.
+                self.agent.run(iterations=1, resume=True)
             except Exception as e:
                 logger.error(f"Error while running microchain agent: {e}")
                 raise e

prediction_market_agent/agents/microchain_agent/microchain_agent.py

@@ -13,10 +13,7 @@
 )
 from microchain.functions import Reasoning, Stop
 from prediction_market_agent_tooling.markets.markets import MarketType
-from prediction_market_agent_tooling.tools.utils import (
-    check_not_none,
-    should_not_happen,
-)
+from prediction_market_agent_tooling.tools.utils import should_not_happen
 
 from prediction_market_agent.agents.microchain_agent.agent_functions import (
     AGENT_FUNCTIONS,
@@ -191,7 +188,6 @@ def build_agent(
     enable_langfuse: bool,
     api_base: str = "https://api.openai.com/v1",
     long_term_memory: LongTermMemoryTableHandler | None = None,
-    import_actions_from_memory: int = 0,
     max_tokens: int = 8196,
     allow_stop: bool = True,
     bootstrap: str | None = None,
@@ -240,19 +236,6 @@ def step_end_callback(agent: Agent, step_output: StepOutput) -> None:
         enable_langfuse=enable_langfuse,
     )
 
-    if import_actions_from_memory:
-        latest_saved_memories = check_not_none(
-            long_term_memory, "long_term_memory is needed for this functionality."
-        ).search(limit=import_actions_from_memory)
-        agent.history.extend(
-            m.metadata_dict
-            for m in latest_saved_memories[
-                ::-1
-            ]  # Revert the list to have the oldest messages first, as they were in the history.
-            if check_not_none(m.metadata_dict)["role"]
-            != "system"  # Do not include system message as that one is automatically in the beginning of the history.
-        )
-
     for f in build_agent_functions(
         agent=agent,
         market_type=market_type,