"""Propaga o contrato nativo de pending_topics às cópias de Tuning-Performance.""" from pathlib import Path ROOT = Path(__file__).resolve().parents[1] def replace_once(text: str, old: str, new: str, path: Path) -> str: if old not in text: raise RuntimeError(f"Marcador não encontrado em {path}: {old[:60]!r}") return text.replace(old, new, 1) def update_state(path: Path) -> None: text = path.read_text(encoding="utf-8") if " pending_topics: list[dict[str, Any]]" in text: return text = replace_once( text, " supervisor_results: list[dict[str, Any]]\n", " supervisor_results: list[dict[str, Any]]\n" " pending_topics: list[dict[str, Any]]\n" " handled_topics: list[dict[str, Any]]\n", path, ) path.write_text(text, encoding="utf-8") def update_graph(path: Path) -> None: text = path.read_text(encoding="utf-8") if "from agent_framework.routing.pending_topics import drain_pending_topics" in text: return text = replace_once( text, "from agent_framework.routing.enterprise_router import EnterpriseRouter\n", "from agent_framework.routing.enterprise_router import EnterpriseRouter\n" "from agent_framework.routing.pending_topics import drain_pending_topics\n", path, ) text = replace_once( text, " } if decision.method == \"continuity\" else {},\n }\n\n async def billing_agent", " } if decision.method == \"continuity\" else {},\n" " \"pending_topics\": (\n" " (decision.metadata or {}).get(\"multi_intent_plan\", {}).get(\"operations\", [])[1:]\n" " if (decision.metadata or {}).get(\"multi_intent_plan\") else []\n" " ),\n" " }\n\n async def billing_agent", path, ) marker = " async def output_supervisor(self, state):" before, output = text.split(marker, 1) old = """ if not bool(getattr(self.settings, \"ENABLE_OUTPUT_SUPERVISOR\", True)): return { \"output_guardrails_already_applied\": False, \"supervisor_action\": \"disabled\", \"supervisor_attempt\": int(state.get(\"supervisor_attempt\", 0)), } candidate = state.get(\"answer\") or \"\" """ new = """ drained = await drain_pending_topics( state, str(state.get(\"answer\") or \"\"), { \"billing_agent\": self.billing.run, \"product_agent\": self.product.run, \"orders_agent\": self.orders.run, \"support_agent\": self.support.run, }, ) candidate = drained.answer if not bool(getattr(self.settings, \"ENABLE_OUTPUT_SUPERVISOR\", True)): return { \"answer\": candidate, \"final_answer\": candidate, \"pending_topics\": drained.pending_topics, \"handled_topics\": drained.handled_topics, \"output_guardrails_already_applied\": False, \"supervisor_action\": \"disabled\", \"supervisor_attempt\": int(state.get(\"supervisor_attempt\", 0)), } """ output = replace_once(output, old, new, path) output = replace_once( output, " \"output_guardrails_already_applied\": True,\n", " \"output_guardrails_already_applied\": True,\n" " \"pending_topics\": drained.pending_topics,\n" " \"handled_topics\": drained.handled_topics,\n", path, ) path.write_text(before + marker + output, encoding="utf-8") def update_evidence_propagation(path: Path) -> None: text = path.read_text(encoding="utf-8") marker = ' "handled_topics": drained.handled_topics,\n' replacement = marker + ' "mcp_results": drained.mcp_results,\n' if replacement in text: return if marker not in text: raise RuntimeError(f"Marcador de evidências não encontrado em {path}") path.write_text(text.replace(marker, replacement), encoding="utf-8") def update_guardrail_evidence_context(path: Path) -> None: text = path.read_text(encoding="utf-8") marker = " context = {\n **(state.get(\"context\") or {}),\n" addition = ( marker + ' "evidence": drained.mcp_results or (state.get("context") or {}).get("evidence"),\n' + ' "tool_result": drained.mcp_results or (state.get("context") or {}).get("tool_result"),\n' + ' "tool_executed": any(isinstance(item, dict) and item.get("ok") for item in drained.mcp_results),\n' + ' "mcp_results": drained.mcp_results,\n' ) if addition in text: return text = replace_once(text, marker, addition, path) path.write_text(text, encoding="utf-8") def main() -> None: tuning = ROOT / "Tuning-Performance" states = sorted(tuning.glob("**/app/state.py")) graphs = sorted(tuning.glob("**/app/workflows/agent_graph.py")) for path in states: update_state(path) for path in graphs: update_graph(path) update_evidence_propagation(path) update_guardrail_evidence_context(path) print(f"pending_topics sincronizado: {len(states)} states, {len(graphs)} graphs") if __name__ == "__main__": main()