Class Decision_Testing_Experts

DiscussNav.py:363–405

            sim.makeAction([0], [direction*math.radians(360/len(direction_list))], [0])

class Decision_Testing_Experts:
    def thought_fusion(self, predictions, thoughts):
        matched_dict = dict()
        for pred, thought in zip(predictions, thoughts):
            if pred not in matched_dict.keys():
                matched_dict[pred] = []
            matched_dict[pred].append(thought)
            
        for key, value in matched_dict.items():
            multiple_thoughts = "; ".join(["Thought "+str(idx+1)+": "+thought for idx, thought in enumerate(value)])
            prompt = [
                {"role": "system", "content": "You are a thought fusion expert. Your task is to fuse given thought processes \
                    into one thought. You need to reserve key information related to actions, landmarks, direction changes. You should only answer fused thought without other words."},
                {"role": "user", "content": f"Can you help me fuse the thoughts leading to the same movement direction? The thoughts are :{multiple_thoughts}, Fused thought: "}   
            ]
            one_thought = gpt_response(prompt, "gpt-4", 1)[0]["message"]["content"]  
            logger.info(f"Pred: {key} Fused Thought: {one_thought}")
            matched_dict[key] = one_thought
            
        return matched_dict      
    
    def test_decisions(self, fused_pred_thought, observation, instruction):
        if len(fused_pred_thought.keys()) == 1:
            for key, value in fused_pred_thought.items():
                return key, value
        else:
            fused_pred_thought_ = "; ".join(["Navigation Viewpoint ID: "+key+" Thought: "+value for key, value in fused_pred_thought.items()])
            decision_prompt = [
                {"role": "system", "content": "You are a decision testing expert. Your task is to evaluate the feasibility of each movement \
                    prediction based on thought process and environment. Then, you will make a final decision about navigation viewpoint ID without other words."},
                {"role": "user", "content": f"Can you help me make a final decision? The Observation: {observation}, Navigation Instruction: {instruction}, {fused_pred_thought_}, Final Decision: "}   
            ]
            for _ in range(3):
                next_vp = gpt_response(decision_prompt, "gpt-4", 1, temperature=0)[0]["message"]["content"].strip()
                if len(next_vp) != 32:
                    logger.info(f"{next_vp} Length Problem")
                    continue
                if next_vp not in fused_pred_thought.keys():
                    logger.info(f"{next_vp} not in the candidates")
                    continue
                break
        
        return next_vp, fused_pred_thought[next_vp]

def eval_pred(final_vp, nav_history, shortest_distances, eval_cache, instruction, scanId, des_vp, gt_path):
    path = [item["viewpoint"] for item in nav_history]+[final_vp]