app.py allow for default dataset

app.py

@@ -40,7 +40,7 @@ def load_and_predict_with_classifier(x, model_path, output_path, save):
     return y_pred
 
 
-def main(input_file_path, species):
+def main(input_file_path, species, default_dataset):
 
     # Get the current working directory
     current_working_directory = os.getcwd()
@@ -64,6 +64,15 @@ def main(input_file_path, species):
     # Add the directory to the Python path
     sys.path.append(new_directory)
 
+    # Set default dataset path
+    default_dataset_1_path = hf_hub_download(repo_id="minwoosun/uce-misc", filename="100_pbmcs_proc_subset.h5ad")
+    default_dataset_2_path = hf_hub_download(repo_id="minwoosun/uce-misc", filename="1k_pbmcs_proc_subset.h5ad")
+
+    # If the user selects a default dataset, use that instead of the uploaded file
+    if default_dataset == "Default Dataset 1: PBMC 100 cells":
+        input_file_path = default_dataset_1_path
+    elif default_dataset == "Default Dataset 2: PBMC 1000 cells":
+        input_file_path = default_dataset_2_path
 
     ##############
     #     UCE    #
@@ -223,8 +232,11 @@ if __name__ == "__main__":
         )
 
         # Define Gradio inputs and outputs
-        file_input = gr.File(label="Upload a .h5ad single cell gene expression file")
-        species_input = gr.Dropdown(choices=["human", "mouse"], label="Select species")
+        file_input = gr.File(label="Upload a .h5ad single cell gene expression file or select a default dataset below")
+        # species_input = gr.Dropdown(choices=["human", "mouse"], label="Select species")
+        with gr.Row():
+            species_input = gr.Dropdown(choices=["human", "mouse"], label="Select species")
+            default_dataset_input = gr.Dropdown(choices=["None", "PBMC 100 cells", "PBMC 1000 cells"], label="Select default dataset")
         run_button = gr.Button("Run")
         
         # Arrange UMAP plot and file output side by side
@@ -236,7 +248,7 @@ if __name__ == "__main__":
         # Add the components and link to the function
         run_button.click(
             fn=main, 
-            inputs=[file_input, species_input], 
+            inputs=[file_input, species_input, default_dataset_input], 
             outputs=[image_output, file_output, pred_output]
         )