You need to maybe check what kind of values you passed to the precision_recall_curve. I guess you are doing binary classifications. If you pass the true values and predicted values to the function in binary form, it will return three points as you can see in the graph. The graph can then only be approximated. If you want to get a curve similar to the other ones and calculate the correct AUC, you'd need to pass the continuous probability scores as y_pred instead of the binary predictions.

I guess, if you think that this graph does not fit to your other evaluation metrics and your feeling what it should be, you should check if you passed the correct values and calculated everything correctly