Update app.py

app.py

@@ -19,8 +19,6 @@ import yt_dlp  # Added import for yt-dlp
 MODEL_NAME = "NbAiLab/nb-whisper-large"
 lang = "no"
 
-logo_path = "/home/angelina/Nedlastinger/Screenshot 2024-10-10 at 13-30-13 Nasjonalbiblioteket — Melkeveien designkontor.png"
-
 share = (os.environ.get("SHARE", "False")[0].lower() in "ty1") or None
 auth_token = os.environ.get("AUTH_TOKEN") or True
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
@@ -64,7 +62,7 @@ def transcribe(file, return_timestamps=False):
             line = f"[{start_time} -> {end_time}] {chunk['text']}"
             text.append(line)
         formatted_text = "\n".join(text)
-    formatted_text += "\n\nTranskribert med NB-Whisper demo"
+    formatted_text += "\n\n<i>Transkribert med NB-Whisper demo</i>"
     return formatted_text
 
 def _return_yt_html_embed(yt_url):
@@ -100,7 +98,7 @@ def yt_transcribe(yt_url, return_timestamps=False):
 demo = gr.Blocks()
 
 with demo:
-    gr.Image(value=logo_path, label="Nasjonalbibliotek Logo", elem_id="logo")  # No tool parameter for static display
+    gr.HTML('<center><img src="Logo.png" alt="Nasjonalbiblioteket Logo" width="300"></center>')
     mf_transcribe = gr.Interface(
         fn=transcribe,
         inputs=[
@@ -136,4 +134,4 @@ with demo:
     # )
 
 # Start demoen uten faner
-demo.launch(share=share).queue()
+demo.launch(share=share, show_api=False, show_tips=False).queue()