pandas groupby one column except if one other column has different entry

I have a dataframe that I would like to group by a given column, BUT only if one other column is also the same, while doing a sum on an other column. Given this example:

test=pd.DataFrame({'A':['0','0','0','1'],'B':['AAA','AAA','BBB','CCC'],'C':[0.5,0.2,0.3,0.1]})

    A   B   C
0   0   AAA 0.5
1   0   AAA 0.2
2   0   BBB 0.3
3   1   CCC 0.1

I would like group for A only if B is different. I am targeting following dataframe:

    A   B   C
0   0   AAA 0.7
1   0   BBB 0.3
2   1   CCC 0.1

So far I did not find any way to do it

>Solution :

test=pd.DataFrame({'A':['0','0','0','1'],'B':['AAA','AAA','BBB','CCC'],'C':[0.5,0.2,0.3,0.1]})

test.groupby(['A','B'])['C'].sum()

A  B  
0  AAA    0.7
   BBB    0.3
1  CCC    0.1
Name: C, dtype: float64

test.groupby(['A','B'], as_index=False)['C'].sum()

    A   B   C
0   0   AAA 0.7
1   0   BBB 0.3
2   1   CCC 0.1