diff --git a/main/astrodatadownloader/astrodatadownloader.py b/main/astrodatadownloader/astrodatadownloader.py
index 9333403..4430c29 100644
--- a/main/astrodatadownloader/astrodatadownloader.py
+++ b/main/astrodatadownloader/astrodatadownloader.py
@@ -1,4 +1,5 @@
 from astroquery.mast import Observations
+from astropy import table
 import numpy as np
 from enum import Enum
 from copy import deepcopy
@@ -70,67 +71,19 @@ def getStarObservations(starName: str, sources: list[ObservationSource], sequenc
 
     return obs[obsWantedFilter]
 
-def fitsFilenameFilterFunc(table, key_colnames):
-    if(str(table["productFilename"]).lower().endswith(".fits")):
-        return True
-    return False
-
-sequencesFilter: list[int] = []
-
-def fullSequenceOnlyFiles(table, key_colnames):
-    if(len(sequencesFilter) > 1):
-        seqStr = f"s{sequencesFilter[0]:04d}-s{sequencesFilter[1]:04d}"
-    else:
-        seqStr = f"s{sequencesFilter[0]:04d}"
-
-    if(seqStr in str(table["productFilename"]).lower()):
-        return True
-    return False
-
-def downloadStarProducts(starName: str, sequences: list[int], dataType: DataType,
-                          downloadPath: str = "./", fitsOnly: bool = True,
-                          fullSectorOnly: bool = True) -> str:
-
-    obs_wanted = getStarObservations(starName, sequences)
+def downloadStarProducts(obs_wanted):
     dataProducts = Observations.get_product_list(obs_wanted)
 
-    productSubGroups = []
-    match dataType:
-        case DataType.DataValidation:
-            productSubGroups.append("DVT")
-            productSubGroups.append("DVM")
-            productSubGroups.append("DVS")
-            productSubGroups.append("DVR")
-
-        case DataType.LightCurve:
-            productSubGroups.append("LC")
-
-        case DataType.TargetPixel:
-            productSubGroups.append("TP")
+    # LC:  TESS lightcurve
+    # SLC: Kepler short cadence lightcurve
+    # LLC: Kepler long cadence lightcurve
+    productSubGroups = ["LC", "SLC"]
 
     productsWanted = Observations.filter_products(dataProducts,
                                                   productSubGroupDescription=productSubGroups)
 
     productsWanted = productsWanted.group_by("productFilename")
 
-    if(fitsOnly):
-        productsWanted = productsWanted.groups.filter(fitsFilenameFilterFunc)
-
-    if(len(sequences) == 0):
-        fullSectorOnly = False
-
-    if(fullSectorOnly):
-        global sequencesFilter
-        if(len(sequences) == 1 and not
-           (dataType == DataType.LightCurve or dataType == DataType.TargetPixel)):
-            sequencesFilter = (sequences[0], sequences[0])
-        elif(len(sequences) > 1 and
-             (dataType == DataType.LightCurve or dataType == DataType.TargetPixel)):
-            sequencesFilter = [sequences[0]]
-        else:
-            sequencesFilter = sequences
-        productsWanted = productsWanted.groups.filter(fullSequenceOnlyFiles)
-
     filenames = Observations.download_products(productsWanted)
     return parse_manifest(filenames)