How to return values in multiple columns based on conditions in another dataframe column python

I have a main dataframe say DF1 with column values, Category, Subcategory, Group, Text. I need to validate if correct category and subcategory is against each group and text columns.

I have another dataframe say DF2 with same 4 columns and the expected category and subcategory for group and strings to be contained in text column.

DF1:

Category	Subcategory	Group	Text
Sweet	Cake	G6	mandatory for birthdays and weddings
chocolate	DairyMilk	G1	Packed in blue, has dark and white combo
Chips	Lays	G2	Multicolor wraps, different flavors and is liked by many
Chips	Bingo	G3	Triangle in shape and has multiple flavors
chocolate	DairyMilk	G5	Blue wrapper

DF2:

Category	Subcategory	Group	Text
Sweet	Cake	G6,G8,G7
chocolate	DairyMilk	G1,G10,G5	blue, dark and white
Chips	Bingo	G3,G4	Triangle, flavours
Chips	Lays	G 2	Multicolor , flavors

I need to add predicted category and subcategory in DF1 based on DF2 values. Example if Condition1:

DF1['Group'] is G6 or G8 or G7, DF1['predictedCategory']=='Sweet' and DF1['predictedSubcategory'] == 'Cake'

Condition2:

DF1['Group'] is G1 or G10 or G5 and DF1['Text'] contains blue or dark and white, DF1['predictedCategory']=='chocolate' and DF1['predictedSubcategory'] == 'DairyMilk'.

Would need a precise approach which would also save time in running the code. I tried writing if else statement with multiple conditions but it returns empty in predicted columns. Would appreciate any leads.