simplify paths

app.py

@@ -78,28 +78,13 @@ def toggle_file_input(default_dataset):
 
 
 def main(input_file_path, species, default_dataset):
-
-    # Get the current working directory
-    current_working_directory = os.getcwd()
-    
-    # Print the current working directory
-    print("Current Working Directory:", current_working_directory)
-
+ 
     # clone and cd into UCE repo
     os.system('git clone https://github.com/minwoosun/UCE.git')
-    os.chdir('/home/user/app/UCE')
-
-    # Get the current working directory
-    current_working_directory = os.getcwd()
-    
-    # Print the current working directory
-    print("Current Working Directory:", current_working_directory)
-
-    # Specify the path to the directory you want to add
-    new_directory = "/home/user/app/UCE"
+    os.chdir(base_path)
     
     # Add the directory to the Python path
-    sys.path.append(new_directory)
+    sys.path.append(base_path)
 
     # Set default dataset path
     default_dataset_1_path = hf_hub_download(repo_id="minwoosun/uce-misc", filename="100_pbmcs_proc_subset.h5ad")
@@ -117,17 +102,17 @@ def main(input_file_path, species, default_dataset):
     from evaluate import AnndataProcessor
     from accelerate import Accelerator
 
-    dir_path = '/home/user/app/UCE/'
+    base_path = '/home/user/app/UCE/'
     model_loc = 'minwoosun/uce-100m'
 
     print(input_file_path)
-    print(dir_path)
+    print(base_path)
     print(model_loc)
     
     # Construct the command
     command = [
         'python', 
-        '/home/user/app/UCE/eval_single_anndata.py', 
+        base_path + 'eval_single_anndata.py', 
         '--adata_path', input_file_path, 
         '--dir', dir_path, 
         '--model_loc', model_loc
@@ -149,12 +134,12 @@ def main(input_file_path, species, default_dataset):
     # Set output file path
     file_name_with_ext = os.path.basename(input_file_path)
     file_name = os.path.splitext(file_name_with_ext)[0]
-    pred_file = "/home/user/app/UCE/" + f"{file_name}_predictions.csv"
+    pred_file = base_path + f"{file_name}_predictions.csv"
     model_path = hf_hub_download(repo_id="minwoosun/uce-misc", filename="tabula_sapiens_v1_logistic_regression_model_weights.json")
 
     file_name_with_ext = os.path.basename(input_file_path)
     file_name = os.path.splitext(file_name_with_ext)[0]
-    output_file = "/home/user/app/UCE/" + f"{file_name}_uce_adata.h5ad"
+    output_file = base_path + f"{file_name}_uce_adata.h5ad"
     adata = sc.read_h5ad(output_file)
     x = adata.obsm['X_uce']