user_query: placeholder
tree_str_mr: [__DG_INFORM__ [__ARG_TASK__ get_forecast ] [__ARG_TEMP_LOW__ 39 ] [__ARG_TEMP_HIGH__ 61 ] [__ARG_TEMP_UNIT__ fahrenheit ] [__ARG_CLOUD_COVERAGE__ cloudy ] [__ARG_DATE_TIME__ [__ARG_COLLOQUIAL__ Today ] ] [__ARG_LOCATION__ [__ARG_CITY__ Cancún ] [__ARG_COUNTRY__ Mexico ] [__ARG_REGION__ Quintana Roo ] ] ]
response: [__DG_INFORM__ [__ARG_DATE_TIME__ [__ARG_COLLOQUIAL__ Today ] ] [__ARG_LOCATION__ in [__ARG_CITY__ __ARG_CITY__ ] Q [__ARG_REGION__ __ARG_REGION__ ] M [__ARG_COUNTRY__ __ARG_COUNTRY__ ] ] it will be c [__ARG_CLOUD_COVERAGE__ loudy ] with a high of <number>  [__ARG_TEMP_HIGH__ __ARG_TEMP_HIGH__ ] d [__ARG_TEMP_UNIT__ __ARG_TEMP_UNIT__ ] and a low of <number>  [__ARG_TEMP_LOW__ __ARG_TEMP_LOW__ ] ]
target: [__DG_INFORM__ [__ARG_DATE_TIME__ [__ARG_COLLOQUIAL__ Today ] ] [__ARG_LOCATION__ in [__ARG_CITY__ __ARG_CITY__ ] Q [__ARG_REGION__ __ARG_REGION__ ] M [__ARG_COUNTRY__ __ARG_COUNTRY__ ] ] it will be c [__ARG_CLOUD_COVERAGE__ loudy ] with a high of <number>  [__ARG_TEMP_HIGH__ __ARG_TEMP_HIGH__ ] d [__ARG_TEMP_UNIT__ __ARG_TEMP_UNIT__ ] and a low of <number>  [__ARG_TEMP_LOW__ __ARG_TEMP_LOW__ ] ]
references: [__DG_INFORM__ [__ARG_DATE_TIME__ [__ARG_COLLOQUIAL__ Today ] ] [__ARG_LOCATION__ in [__ARG_CITY__ __ARG_CITY__ ] Q [__ARG_REGION__ __ARG_REGION__ ] M [__ARG_COUNTRY__ __ARG_COUNTRY__ ] ] it will be c [__ARG_CLOUD_COVERAGE__ loudy ] with a high of <number>  [__ARG_TEMP_HIGH__ __ARG_TEMP_HIGH__ ] d [__ARG_TEMP_UNIT__ __ARG_TEMP_UNIT__ ] and a low of <number>  [__ARG_TEMP_LOW__ __ARG_TEMP_LOW__ ] ]