You can't do it like that. If you have the plain metric http_request_duration_seconds then it is a summary and you could do something like this:
http_request_duration_seconds{quantile="0.95"}
But in your case this doesn't help because you don't know which quantile represents which exact duration.
Usually you just have http_request_duration_seconds_sum and http_request_duration_seconds_count. These metrics get increased which each request. If you want to calculate the average over a given time you do something like:
rate(http_request_duration_seconds_sum[5m])
/
rate(http_request_duration_seconds_count[5m])
as mentioned here: https://prometheus.io/docs/practices/histograms/
But if you want the exact counts and display a histogram you need to expose buckets, also explained in the above mentioned link and here: https://prometheus.io/docs/concepts/metric_types/#histogram
So you have to use a bucket like so (all requests with a duration up to 0.7s in the last minute):
increase(http_request_duration_seconds_bucket{le="0.7"}[1m])
If you use micrometer and spring this could also help: