BUG: inconsistent groupby behavior when groupby.apply return dataframe

[GYHHAHA]

Pandas version checks

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the master branch of pandas.

Reproducible Example

>>> df = pd.DataFrame({"A":[1,2,1,2]})
>>> df.groupby("A").apply(lambda x: x)
   A
0  1
1  2
2  1
3  2
>>> df.groupby("A").apply(lambda x: x.copy())
     A
A     
1 0  1
  2  1
2 1  2
  3  2

Issue Description

I think both two cases should return a multi-index (just like the second case). Is this actually a bug? or just on purpose?

Expected Behavior

>>> df = pd.DataFrame({"A":[1,2,1,2]})
>>> df.groupby("A").apply(lambda x: x)
     A
A     
1 0  1
  2  1
2 1  2
  3  2

Installed Versions

1.3.5

[LucasG0]

It looks like a duplicate of 44803

[GYHHAHA]

sorry for duplication, close