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Error : object ‘items_bands’ not exported by 'namespace:rstac'

devtools::session_info()
─ Session info ─────────────────────────────────────────────────────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.2.2 (2022-10-31)
 os       Ubuntu 20.04.4 LTS
 system   x86_64, linux-gnu
 ui       RStudio
 language (EN)
 collate  fr_FR.UTF-8
 ctype    fr_FR.UTF-8
 tz       Europe/Paris
 date     2023-02-06
 rstudio  2022.12.0+353 Elsbeth Geranium (desktop)
 pandoc   NA
─ Packages ────────────────────────────────────────────────────
 package          * version    date (UTC) lib source
mapme.vegetation * 0.0.0.9010 2023-02-06 [1] Github (gse-cc-git/mapme.vegetation@a08a299)
rstac              0.9.2-2    2023-02-01 [1] CRAN (R 4.2.2)

    I'm also stuck with the scl_buffer now. But I'm not sure if my error is related to GRASS or more to GDAL

scl_buffer(scl_files = scl_files, 
+            mask_values = c(1,2,3,7,8,9,10,11), # which values to mask?
+            mask_buffer = 100, 
+            grass_bin = "C:/OSGeo4W64/apps/grass/grass79", 
+            threads = 1, 
+            outdir = "C:/SOM-Togdheer/R-programs/CM_S2A")
  |                                                             |   0%Error in system(rcl_command, intern = T) : 
  'CreateProcess' failed to run 'C:\OSGEO4~1\apps\gdal2\pymod3\scripts\GDAL_C~1.PY -A C:/SOM-Togdheer/R-programs/S2A/S2A_38PMR_20220904_0_L2A_SCL.tif --outfile=C:\Users\stp.CES\AppData\Local\Temp\Rtmpy2M6cL\file4db4395f70c8.tif --calc="1*(A==1)+1*(A==2)+1*(A==3)+1*(A==7)+1*(A==8)+1*(A==9)+1*(A==10)+1*(A==11)"'

items = download_aws(assets="overview",
+                      bbox = bbox,
+                      after = "2022-09-02",
+                      before = "2022-09-04",
+                      timeframe = "full",
+                      max.cloud = 30, outdir = "C:\\SOM-Togdheer\\R-programs",
+                      overwrite = TRUE,
+                      verbose = T,
+                      query_only = F,
+                      )
STAC version: 1.0.0-beta.2
Querying data for temporal window 2022-09-02/2022-09-04
The following items matched the specified spatiotemporal extent.
###STACItemCollection
- matched feature(s): 4
- features (4 item(s) / 0 not fetched):
  - S2A_38PMR_20220904_0_L2A
  - S2A_38PNR_20220904_0_L2A
  - S2A_38PMS_20220904_0_L2A
  - S2A_38PNS_20220904_0_L2A
- assets: 
thumbnail, overview, info, metadata, visual, B01, B02, B03, B04, B05, B06, B07, B08, B8A, B09, B11, B12, AOT, WVP, SCL
- other field(s): 
type, stac_version, stac_extensions, context, numberMatched, numberReturned, features, links
Starting download...
  |=========================                         |  50%Error: Error while downloading https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/38/P/NR/2022/9/S2A_38PNR_20220904_0_L2A/L2A_PVI.tif. 
Path exists and overwrite is FALSE

Starting download...
  |============                                      |  25%Error: Error while downloading https://roda.sentinel-hub.com/sentinel-s2-l1c/tiles/38/P/MR/2022/9/4/0/preview.jpg. 
Unrecognized content encoding type. libcurl understands deflate, gzip content encodings.

after = "2022-09-24" # start date
before = "2022-10-03" # end date
dx = 10 # desired outcome resolution in x direction
dy = 10 # desired outcome resolution in y direction
dt = "P10D" # desired temporal resolution - here 1 month
srs = "EPSG:32638" # desired CRS of the outcome raster - bbox must be specified in that crs
label = "NDVI-" # appended to filename
aggregation = "max" # aggregation method for scene within the same time step
resampling = "cubic" # GDAL resampling method to match the outcome grid size
fill_ndvi = smooth_cube(files = raw_ndvi$files,
+                         bands = raw_ndvi$band_order, 
+                         times = raw_ndvi$time,
+                         dx = dx, 
+                         dy = dy, 
+                         dt = dt, 
+                         srs = srs, 
+                         after = after, 
+                         before = before, 
+                         bbox = bbox, 
+                         aggregation = aggregation, 
+                         resampling = resampling, 
+                         outdir = rundir, 
+                         label = label,
+                         overwrite = TRUE,
+                         chunking = c(1,50,50),
+                         creation_options = list("COMPRESS" = "DEFLATE"))
[==================================================>] 100 %
[ERROR] worker process #0 returned 1
## Size of the cube in x direction does not align with dx, extent will be enlarged by 3.552875 at both sides.
## Size of the cube in y direction does not align with dy, extent will be enlarged by 2.559135 at both sides.
Current cube view is:
A data cube view object

Dimensions:
               low             high count pixel_size
t       2022-09-24       2022-10-03     1       P10D
y 1003861.03099573 1103951.03099573 10009         10
x 472148.818176792 584708.818176792 11256         10

SRS: "EPSG:32638"
Temporal aggregation method: "max"
Spatial resampling method: "cubic"

No smoothing function specified.
Using Linear Interpolation and Savitzkiy-Golay-Filter with standard parameters.
Error in gdalcubes:::gc_exec_worker(j$cube, j$worker_id, j$worker_count,  : 
  c++ exception (unknown reason)
Execution halted
[WORKER #0] [ERROR] Child process failed with exit code 1
[WORKER #0] [ERROR] Child process output: Loading required package: gdalcubes
[WORKER #0] Error in x[(len - n + 1):len] : 
[WORKER #0]   only 0's may be mixed with negative subscripts
[WORKER #0] Calls: write_chunk_from_array ... apply_time.array -> apply -> FUN -> lapply -> FUN -> <Anonymous>
[WORKER #0] Execution halted
Error in gc_write_tif(x, dir, prefix, overviews, COG, creation_options,  : 
  one or more worker processes failed to compute data cube chunks