ACTION_NUMBER
1

ACTION_PROMPT
TASK: {'description': 'Go to the next room', 'priority': 'medium'}. Your final task is to NAVIGATE TO THE NEAREST BED, and get as close to it as possible. There are 5 red arrows superimposed onto your observation, which represent potential actions. These are labeled with a number in a white circle, which represent the location you would move to if you took that action. NOTE: choose action 0 if you want to TURN AROUND or DONT SEE ANY GOOD ACTIONS. In order to complete the subtask {'description': 'Go to the next room', 'priority': 'medium'} and eventually the final task NAVIGATING TO THE NEAREST BED. Explain which action acheives that best. 

🎯 SCENE ANALYSIS for current direction (30°):

💡 Use this spatial information to make more informed navigation decisions!
Return your answer as {{'action': <action_key>}}. Note you CANNOT GO THROUGH CLOSED DOORS, and you DO NOT NEED TO GO UP OR DOWN STAIRS

ACTION_RESPONSE
Action 1 leads directly into the next room, which is the best way to complete the subtask "Go to the next room". This will also help with the final task of navigating to the nearest bed, as it is likely in another room.

{{'action': 1}}

COT_EVALUATOR_RESPONSE
{'goal_rotate_degrees': 30, 'explorable_value': {'30': 3.0, '90': 3.0, '150': 3.0, '210': 3.0, '270': 3.0, '330': 3.0}, 'reason': {'30': 'Regex-extracted data for direction 30', '90': 'Default entry for missing direction 90', '150': 'Default entry for missing direction 150', '210': 'Default entry for missing direction 210', '270': 'Default entry for missing direction 270', '330': 'Default entry for missing direction 330'}, 'cot_stats': {}}

COT_PLANNING_RESPONSE
{'goal_flag': False, 'subtask': {'description': 'Go to the next room', 'priority': 'medium'}, 'goal_reason': 'Regex-extracted data for direction 30'}

GOAL_SUBGRAPH_RESPONSE
{'target_object': 'bed', 'subgraph_info': {'target_rooms': [], 'nodes_count': 0, 'edges_count': 0, 'vlm_semantic_hints': {}, 'subgraph_cached': True, 'construction_method': 'llm_generated'}, 'step_number': 8, 'episode_id': 450}