Feat/fix execution

agents/planner.py

@@ -34,7 +34,7 @@
     retrieve_relevant_cases,
     compute_memory_influence,
     derive_strategy_rationale,
-    build_strategic_prompt,
+    build_memory_prompt,
 )
 from simulation.evaluator import evaluate_candidate_plan
 
@@ -910,7 +910,6 @@ def run(self, state: SystemState, event: Event | None = None) -> AgentProposal:
                 feasible_candidates.append(act)
             else:
                 infeasible_reasons[act.action_id] = vios
-
         if not feasible_candidates and candidate_actions:
             feasible_candidates = [
                 Action(
@@ -923,23 +922,17 @@ def run(self, state: SystemState, event: Event | None = None) -> AgentProposal:
             ]
         action_limit = _action_limit_for_mode(state, len(feasible_candidates))
 
-        effective_event = event or (
-            state.active_events[-1] if state.active_events else None
-        )
-        historical_cases = retrieve_relevant_cases(
-            effective_event, state.memory, top_k=3
-        )
+        effective_event = event or (state.active_events[-1] if state.active_events else None)
+        historical_cases = retrieve_relevant_cases(effective_event, state.memory, top_k=3)
         memory_influence = compute_memory_influence(historical_cases)
-        strategic_prompt = build_strategic_prompt(
-            mode=state.mode.value,
-            event=effective_event,
-            historical_cases=historical_cases,
-            candidate_actions=feasible_candidates,
+        memory_prompt = build_memory_prompt(
+            mode=state.mode.value, historical_cases=historical_cases
         )
 
         before_kpis = state.kpis.model_copy(deep=True)
         llm_drafts, planner_error = generate_candidate_plan_drafts(
-            state=state, event=event, candidate_actions=feasible_candidates
+            state=state, event=event, candidate_actions=feasible_candidates,
+            memory_prompt=memory_prompt
         )
         logger.info(
             "planner candidate generation result llm_drafts=%s planner_error=%s feasible_candidates=%s suppress_no_op=%s action_limit=%s",
@@ -1149,7 +1142,7 @@ def run(self, state: SystemState, event: Event | None = None) -> AgentProposal:
             referenced_cases=historical_cases,
             memory_influence_score=memory_influence,
             strategy_rationale=strategy_rationale,
-            strategic_prompt=strategic_prompt,
+            strategic_prompt=memory_prompt
         )
 
         winning_factors = build_winning_factors(
@@ -1198,7 +1191,6 @@ def run(self, state: SystemState, event: Event | None = None) -> AgentProposal:
         state.latest_plan_id = final_plan.plan_id
         state.pending_plan = final_plan if final_plan.approval_required else None
         state.decision_logs.append(decision_log)
-
         proposal.observations.append(
             f"built {final_plan.plan_id} using {final_plan.strategy_label} with score {final_plan.score:.4f}"
         )

app_api/services.py

@@ -592,28 +592,29 @@ def dispatch_plan(self, plan_id: str, mode: str) -> dict[str, Any]:
 
         if plan is None:
             raise_not_found("plan", plan_id)
+        existing_commit_records = [
+            ActionExecutionRecord.model_validate(item)
+            for item in self.store.list_action_execution_records(limit=None)
+            if item.get("plan_id") == plan_id
+            and item.get("dispatch_mode") == "commit"
+        ]
 
-        if mode == "commit":
-            existing_records = [
-                ActionExecutionRecord.model_validate(item)
-                for item in self.store.list_action_execution_records(limit=None)
-                if item.get("plan_id") == plan_id
-                and item.get("dispatch_mode", "dry_run") == mode
-            ]
-            if existing_records:
-                existing_records.sort(key=lambda record: record.created_at)
-                return {
-                    "plan_id": plan_id,
-                    "dispatch_mode": mode,
-                    "plan_execution_status": compute_plan_execution_status(
-                        existing_records
-                    ).value,
-                    "overall_progress": compute_overall_progress(existing_records),
-                    "records": [
-                        action_execution_record_view(r) for r in existing_records
-                    ],
-                    "compensation_hints": [],
-                }
+        if existing_commit_records:
+            existing_commit_records.sort(key=lambda record: record.created_at)
+            reported_mode = "dry_run" if mode == "dry_run" else "commit"
+
+            return {
+                "plan_id": plan_id,
+                "dispatch_mode": reported_mode,
+                "plan_execution_status": compute_plan_execution_status(
+                    existing_commit_records
+                ).value,
+                "overall_progress": compute_overall_progress(existing_commit_records),
+                "records": [
+                    action_execution_record_view(r) for r in existing_commit_records
+                ],
+                "compensation_hints": [], # Historic records don't have active hints
+            }
 
         summary = self.dispatch_service.dispatch_plan(plan, mode=mode)
 
@@ -1712,3 +1713,7 @@ def build_event_from_envelope(envelope: EventEnvelope) -> Event:
         payload=envelope.payload,
         dedupe_key=envelope.idempotency_key,
     )
+
+
+
+