I apologize for being rather vague! This would be for a task-based analysis. fmriprep yields preprocessed files along with a .tsv file of nuisance regressors. Ideally, I would like to implement something like Example 6b, but starting after blur:

afni_proc.py \
-subj_id FT.e6b \
-copy_anat Qwarp/anat_warped/anatSS.FT.nii \
-anat_has_skull no \
-anat_follower anat_w_skull anat FT/FT_anat+orig \
-dsets FT/FT_epi_r?+orig.HEAD \
-blocks tshift align tlrc volreg blur mask scale regress \
-radial_correlate_blocks tcat volreg \
-tcat_remove_first_trs 2 \
-align_opts_aea -cost lpc+ZZ -giant_move -check_flip \
-tlrc_base MNI152_2009_template_SSW.nii.gz \
-tlrc_NL_warp \
-tlrc_NL_warped_dsets Qwarp/anat_warped/anatQQ.FT.nii \
Qwarp/anat_warped/anatQQ.FT.aff12.1D \
Qwarp/anat_warped/anatQQ.FT_WARP.nii \
-volreg_align_to MIN_OUTLIER \
-volreg_align_e2a \
-volreg_tlrc_warp \
-mask_epi_anat yes \
-blur_size 4.0 \
-regress_stim_times FT/AV1_vis.txt FT/AV2_aud.txt \
-regress_stim_labels vis aud \
-regress_basis 'BLOCK(20,1)' \
-regress_opts_3dD -jobs 2 -gltsym 'SYM: vis -aud' \
-glt_label 1 V-A \
-regress_motion_per_run \
-regress_censor_motion 0.3 \
-regress_censor_outliers 0.05 \
-regress_3dD_stop \
-regress_reml_exec \
-regress_compute_fitts \
-regress_make_ideal_sum sum_ideal.1D \
-regress_est_blur_epits \
-regress_est_blur_errts \
-regress_run_clustsim no \
-html_review_style pythonic \
-execute

I have already implemented post-fmriprep first-level analysis using 3DDeconvolve (somewhat) through nipype, using the ortvec option to adjust for a subset of regressors from the .tsv file. But I think that it may be better to use afni_proc.py if I am using AFNI, for a number of reasons. I guess my more precise question is: Is there a way to directly imput the preprocessed file and "ortvec" option into the -regress line of afni_proc.py task-based analysis? Thank you!!