diff --git a/pdelfin/silver_data/runopenaibatch.py b/pdelfin/silver_data/runopenaibatch.py
index 4bbdee4..7aff239 100644
--- a/pdelfin/silver_data/runopenaibatch.py
+++ b/pdelfin/silver_data/runopenaibatch.py
@@ -53,6 +53,8 @@ def download_batch_result(batch_id, output_folder):
         print(f"WARNING: {batch_id} is completed, but not output file was generated")
         return batch_id, False
 
+    print(f"Downloading batch data for {batch_id}")
+
     file_response = client.files.content(batch_data.output_file_id)
 
     # Define output file path
@@ -149,12 +151,15 @@ def get_done_total(folder_path):
 def process_folder(folder_path: str, max_gb: int):
     output_folder = f"{folder_path}_done"
     os.makedirs(output_folder, exist_ok=True)
+    last_loop_time = datetime.datetime.now()
 
     starting_free_space = MAX_OPENAI_DISK_SPACE - get_total_space_usage()
 
     if starting_free_space < max_gb * 2:
         raise ValueError(f"Insufficient free space in OpenAI's file storage: Only {starting_free_space} GB left, but 2x{max_gb} GB are required (1x for your uploads, 1x for your results).")
 
+    starting_free_space = 250 * 1024 * 1024
+
     while not all(state["state"] in FINISHED_STATES for state in get_state(folder_path).values()):
         done, total = get_done_total(folder_path)
         print(f"Total items {total}, done {done}, {done/total*100:.1f}%")
@@ -163,7 +168,7 @@ def process_folder(folder_path: str, max_gb: int):
         print(f"Processing {os.path.basename(work_item['filename'])}, cur status = {work_item['state']}")
 
         # If all work items have been checked on, then you need to sleep a bit
-        if work_item["last_checked"] > datetime.datetime.now() - datetime.timedelta(seconds=1):
+        if last_loop_time > datetime.datetime.now() - datetime.timedelta(seconds=1):
             time.sleep(1)
 
         if work_item["state"] == "init":
@@ -176,6 +181,8 @@ def process_folder(folder_path: str, max_gb: int):
                     update_state(folder_path, work_item["filename"], state="init")
             else:
                 print("waiting for something to finish processing before uploading more")
+                # Update the time you checked so you can move onto the next time
+                update_state(folder_path, work_item["filename"])
         elif work_item["state"] == "processing":
             batch_data = client.batches.retrieve(work_item["batch_id"])
 
@@ -207,7 +214,9 @@ def process_folder(folder_path: str, max_gb: int):
                     print("Could not delete old file data")
             else:
                 # Update the time you checked so you can move onto the next time
-                update_state(folder_path, work_item["filename"], state="processing")
+                update_state(folder_path, work_item["filename"])
+
+        last_loop_time = datetime.datetime.now()
 
     print("All work has been completed")
 
@@ -215,9 +224,17 @@ if __name__ == "__main__":
     # Set up argument parsing for folder input
     parser = argparse.ArgumentParser(description='Upload .jsonl files and process batches in OpenAI API.')
     parser.add_argument("--max_gb", type=int, default=25, help="Max number of GB of batch processing files to upload at one time")
+    parser.add_argument("--clear_all_files", action="store_true", help="Helper to delete ALL files stored in your openai account")
     parser.add_argument('folder', type=str, help='Path to the folder containing .jsonl files')
     
     args = parser.parse_args()
 
+    if args.clear_all_files:
+        all_files = list(client.files.list())
+        if input(f"Are you sure you want to delete {len(all_files)} files from your OpenAI account? [y/N]").lower() == "y":
+            for file in tqdm(all_files):
+                client.files.delete(file.id)
+        quit()
+
     # Process the folder and start batches
     process_folder(args.folder, args.max_gb)