Using your knowledge of Alfworld and Python programming, please implement the following rule as a Python function. The function should evaluate the current state and an action to return a Boolean value based on specified conditions.

The function should be defined as follows:

```python
def expected_rule_code(state, action):
    # Your code here
    return feedback, success, suggestion
where
feedback: a string, give the action feedback based on success or not.
success: a bool, whether the action is executed successfully, give 'True' or 'False'. If the action type is not the action type in the rule, count as success (e.g., success = True).
suggestion: a string, if the 'action' fails, 'suggestion' would be given based on 'rule', 'state' and 'action'.


Here is several examples of the input format:

state:
{
    "reachable_locations": [
        "cabinet 13",
        "cabinet 12",
        "cabinet 11",
        "cabinet 10",
        "cabinet 9",
        "cabinet 8",
        "cabinet 7",
        "cabinet 6",
        "cabinet 5",
        "cabinet 4",
        "cabinet 3",
        "cabinet 2",
        "cabinet 1",
        "coffeemachine 1",
        "countertop 2",
        "countertop 1",
        "diningtable 1",
        "drawer 4",
        "drawer 3",
        "drawer 2",
        "drawer 1",
        "fridge 1",
        "garbagecan 1",
        "microwave 1",
        "shelf 3",
        "shelf 2",
        "shelf 1",
        "sinkbasin 1",
        "stoveburner 4",
        "stoveburner 3",
        "stoveburner 2",
        "stoveburner 1",
        "toaster 1"
    ],
    "items_in_locations": {
        "fridge 1": [
            "lettuce 2",
            "mug 2",
            "potato 3"
        ],
        "microwave 1": []
    },
    "item_in_hand": {
        "item_name": "cup 1",
        "status": "normal"
    },
    "current_position": {
        "location_name": "microwave 1",
        "status": "open"
    }
}

action:
{
    "name": "go_to",
    "args": {
        "target": target
    }
},
{
    "name": "open",
    "args": {
        "target": target
    }
},
{
    "name": "close",
    "args": {
        "target": target
    }
},
{
    "name": "take",
    "args": {
        "obj": obj,
        "source": source
    }
},
{
    "name": "put",
    "args": {
        "obj": obj,
        "target": target
    }
},
{
    "name": "clean",
    "args": {
        "obj": obj,
        "tool": tool
    }
},
{
    "name": "heat",
    "args": {
        "obj": obj,
        "tool": tool
    }
},
{
    "name": "cool",
    "args": {
        "obj": obj,
        "tool": tool
    }
},
{
    "name": "use",
    "args": {
        "obj": obj
    }
}


The function should return a Boolean (True or False) based on an internal rule which you must implement.

Ensure that the function handles the input and outputs the expected result based on Alfworld mechanics and the provided state and action.


If the rule involves the need to use your knowledge to make a judgement about an item or action then write the function, LLM_request("question"). 
LLM_request would send the "question" to gpt4, and return the gpt4's response. you just need to write the "question" in the LLM_request. 
LLM_request("question"+"response format") has already been predefined, you can just use it dirtectly. Do not need to define it again in your response. But you need to define the "question" and "response format" carefully.

example: i want to know if the item can be destroyed
the LLM function: LLM_request(f"if the {item} can be destroyed in the Alfworld?" + "only reply True or False")


You should only respond in the format as described below, and do not give example usage or anything else:
RESPONSE FORMAT:
def expected_rule_code(state, action):
    # Your code here


