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| """Frozen GPT-5.6-Luna function-call controller for legal high-level actions.""" | |
| from __future__ import annotations | |
| import json | |
| import os | |
| from urllib.request import Request, urlopen | |
| class LunaToolController: | |
| def __init__(self, *, requester=None) -> None: | |
| self.requester = requester or self._request | |
| def _request(payload: dict) -> dict: | |
| key = os.environ.get("OPENAI_API_KEY") | |
| if not key: | |
| raise RuntimeError("OPENAI_API_KEY is required for the Luna controller") | |
| request = Request( | |
| "https://api.openai.com/v1/responses", | |
| data=json.dumps(payload).encode("utf-8"), | |
| headers={"Authorization": f"Bearer {key}", "Content-Type": "application/json"}, | |
| method="POST", | |
| ) | |
| with urlopen(request, timeout=60) as response: | |
| return json.load(response) | |
| def choose(self, legal_actions: list[str], public_context: dict) -> str: | |
| if not legal_actions: | |
| raise ValueError("controller needs at least one legal action") | |
| forbidden = ("private", "ground_truth", "true_state", "target_position_xyz", | |
| "oracle_shortest_path") | |
| if any(token in str(key).lower() for key in public_context for token in forbidden): | |
| raise ValueError("evaluator-private field in controller context") | |
| payload = { | |
| "model": "gpt-5.6-luna", | |
| "input": [ | |
| {"role": "system", "content": ( | |
| "You are a frozen embodied-search tool controller. Choose one legal high-level " | |
| "action using only the supplied public belief, memory, costs and evidence. " | |
| "Prefer the maximum paper utility and never infer evaluator-private truth." | |
| )}, | |
| {"role": "user", "content": json.dumps(public_context, ensure_ascii=False)}, | |
| ], | |
| "tools": [{ | |
| "type": "function", "name": "select_action", | |
| "description": "Choose one legal EvolvingNav high-level action.", | |
| "strict": True, | |
| "parameters": { | |
| "type": "object", | |
| "properties": {"action": {"type": "string", "enum": legal_actions}}, | |
| "required": ["action"], "additionalProperties": False, | |
| }, | |
| }], | |
| "tool_choice": {"type": "function", "name": "select_action"}, | |
| } | |
| response = self.requester(payload) | |
| calls = [item for item in response.get("output", []) | |
| if item.get("type") == "function_call" and item.get("name") == "select_action"] | |
| if len(calls) != 1: | |
| raise ValueError("Luna did not return exactly one select_action call") | |
| action = json.loads(calls[0]["arguments"])["action"] | |
| if action not in legal_actions: | |
| raise ValueError("Luna selected an illegal action") | |
| return action | |