Update app.py

app.py

@@ -9,9 +9,6 @@ import time
 
 is_stopped = False
 
-# seed = random.randint(0,100000)
-setup_seed(4)
-
 def temperature_sampling(logits, temperature):
     logits = logits / temperature
     probabilities = torch.softmax(logits, dim=-1)
@@ -23,7 +20,12 @@ def stop_generation():
     is_stopped = True
     return "Generation stopped."
 
-def CTXGen(X0, X3, X1, X2, τ, g_num, model_name):
+def CTXGen(X0, X3, X1, X2, τ, g_num, model_name, seed):
+    if seed =='random'
+        seed = random.randint(0,100000)
+        setup_seed(seed)
+    else:
+        setup_seed(int(seed))
     global is_stopped
     is_stopped = False
 
@@ -162,7 +164,7 @@ def CTXGen(X0, X3, X1, X2, τ, g_num, model_name):
                             'Subtype_probability': cls_probability_all, 
                             'Potency': X2, 
                             'Potency_probability': act_probability_all, 
-                            'Random_seed': seed
+                            'Random_seed': int(seed)
                         })
                         out.to_csv("output.csv", index=False, encoding='utf-8-sig')
                         count += 1
@@ -198,6 +200,7 @@ with gr.Blocks() as demo:
         τ = gr.Slider(minimum=1, maximum=2, step=0.1, label="τ")
         g_num = gr.Dropdown(choices=[1, 10, 20, 30, 40, 50], label="Number of generations")
         model_name = gr.Dropdown(choices=['model_final.pt','model_C1.pt','model_C2.pt','model_C3.pt','model_C4.pt','model_C5.pt','model_mlm.pt'], label="Model")
+        seed = gr.Textbox(label="Seed", value="random")
     with gr.Row():
         start_button = gr.Button("Start Generation")
         stop_button = gr.Button("Stop Generation")
@@ -206,7 +209,7 @@ with gr.Blocks() as demo:
     with gr.Row():
         output_df = gr.DataFrame(label="Generated Conotoxins")
 
-    start_button.click(CTXGen, inputs=[X0, X3, X1, X2, τ, g_num, model_name], outputs=[output_file, output_df])
+    start_button.click(CTXGen, inputs=[X0, X3, X1, X2, τ, g_num, model_name, seed], outputs=[output_file, output_df])
     stop_button.click(stop_generation, outputs=None)
 
 demo.launch()