user_query: it is warm?
tree_str_mr: [__DG_INFORM__ [__ARG_TASK__ get_forecast ] [__ARG_DATE_TIME__ [__ARG_COLLOQUIAL__ today ] ] [__ARG_LOCATION__ [__ARG_CITY__ Mesa ] ] [__ARG_TEMP_HIGH__ 103 ] ] [__DG_INFORM__ [__ARG_TASK__ get_forecast ] [__ARG_TEMP_LOW_SUMMARY__ mid 90s ] [__ARG_DATE_TIME__ [__ARG_COLLOQUIAL__ today ] ] [__ARG_LOCATION__ [__ARG_CITY__ Mesa ] ] ]
response: [__DG_INFORM__ Expect a high of [__ARG_TEMP_HIGH__ __ARG_TEMP_HIGH__ ] [__ARG_DATE_TIME__ [__ARG_COLLOQUIAL__ today ] ] [__ARG_LOCATION__ in [__ARG_CITY__ __ARG_CITY__ ] ] ] with [__DG_INFORM__ lows in the [__ARG_TEMP_LOW_SUMMARY__ mid <number>  ] ]
target: [__DG_INFORM__ Expect a high of [__ARG_TEMP_HIGH__ __ARG_TEMP_HIGH__ ] [__ARG_DATE_TIME__ [__ARG_COLLOQUIAL__ today ] ] [__ARG_LOCATION__ in [__ARG_CITY__ __ARG_CITY__ ] ] ] with [__DG_INFORM__ lows in the [__ARG_TEMP_LOW_SUMMARY__ mid <number>  ] ]
references: [__DG_INFORM__ Expect a high of [__ARG_TEMP_HIGH__ __ARG_TEMP_HIGH__ ] [__ARG_DATE_TIME__ [__ARG_COLLOQUIAL__ today ] ] [__ARG_LOCATION__ in [__ARG_CITY__ __ARG_CITY__ ] ] ] with [__DG_INFORM__ lows in the [__ARG_TEMP_LOW_SUMMARY__ mid <number>  ] ]