Update app.py

app.py

@@ -9,6 +9,7 @@ tokenizer = AutoTokenizer.from_pretrained("Xibanya/DS9Bot")
 model = AutoModelForCausalLM.from_pretrained("Xibanya/DS9Bot")
 
 def generate(prompt):
+    torch.Generator().manual_seed(cfg['seed'] if cfg['seed'] is not None else torch.seed())
     prompt = '[Promenade] ' if prompt is None else prompt
     encoded_prompt = tokenizer(prompt, return_tensors="pt").input_ids
     encoded_prompt = encoded_prompt.to(model.device)
@@ -24,14 +25,18 @@ def generate(prompt):
             num_return_sequences=1
             )
     text = tokenizer.batch_decode(
-            output, skip_special_tokens=True, clean_up_tokenization_spaces=True)[0].strip()
+            output, skip_special_tokens=True, clean_up_tokenization_spaces=True)[0]
     for string in cfg['split']:
             text = text.replace(string, '\n' + string)
-    return text
+    return text.strip()
     
 title = 'Deep Space Nine Script Generator'
 description = 'AI-generated scripts for the best Trek' 
 
-iface = gr.Interface(fn=generate, inputs="text", outputs="text", title=title, description=description,
-        theme='dark', examples=['[Promenade]', 'QUARK: ', '[Ops]', 'GARAK: '])
+iface = gr.Interface(fn=generate, 
+        inputs=[gr.inputs.Textbox(label="Prompt", placeholder='Enter a prompt to generate a script from')], 
+        outputs=[gr.outputs.TextBox(type="auto", label="Script Generated")], 
+        title=title, 
+        description=description,
+        theme='seafoam', examples=['[Promenade]', 'QUARK: ', "Commander's log, stardate 46924.5."])
 iface.launch()