Update app.py

app.py

@@ -19,6 +19,8 @@ import yt_dlp  # Added import for yt-dlp
 MODEL_NAME = "NbAiLab/nb-whisper-large"
 lang = "no"
 
+logo_path = os.path.join(os.path.dirname(__file__), "Logo.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")
@@ -62,7 +64,7 @@ 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\n<i>Transkribert med NB-Whisper demo</i>"
+    formatted_text += "<br><br><i>Transkribert med NB-Whisper demo</i>"
     return formatted_text
 
 def _return_yt_html_embed(yt_url):
@@ -98,14 +100,14 @@ def yt_transcribe(yt_url, return_timestamps=False):
 demo = gr.Blocks()
 
 with demo:
-    gr.HTML('<center><img src="Logo.png" alt="Nasjonalbiblioteket Logo" width="300"></center>')
+    gr.Image(value=logo_path, type="filepath", elem_id="logo", label=None).style(width=100)  # Adjust width as needed
     mf_transcribe = gr.Interface(
         fn=transcribe,
         inputs=[
             gr.components.Audio(sources=['upload', 'microphone'], type="filepath"),
             gr.components.Checkbox(label="Inkluder tidsstempler"),
         ],
-        outputs="text",
+        outputs=gr.HTML(label="text"),
         title="NB-Whisper",
         description=(
             "Transkriber lange lydopptak fra mikrofon eller lydfiler med et enkelt klikk! Demoen bruker den fintunede"