Update app.py

app.py

@@ -3,11 +3,10 @@ os.system("pip install git+https://github.com/openai/whisper.git")
 import gradio as gr
 import whisper
 
-#from share_btn import community_icon_html, loading_icon_html, share_js
+from share_btn import community_icon_html, loading_icon_html, share_js
 
 model = whisper.load_model("medium.en")
 
-
         
 def inference(audio):
     audio = whisper.load_audio(audio)
@@ -98,6 +97,15 @@ css = """
                 transform: rotate(360deg);
             }
         }
+        #share-btn-container {
+            display: flex; margin-top: 1.5rem !important; padding-left: 0.5rem !important; padding-right: 0.5rem !important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px !important; width: 13rem;
+        }
+        #share-btn {
+            all: initial; color: #ffffff;font-weight: 600; cursor:pointer; font-family: 'IBM Plex Sans', sans-serif; margin-left: 0.5rem !important; padding-top: 0.25rem !important; padding-bottom: 0.25rem !important;
+        }
+        #share-btn * {
+            all: unset;
+        }
 """
 
 block = gr.Blocks(css=css)
@@ -150,11 +158,11 @@ with block:
                   <rect x="23" y="69" width="23" height="23" fill="black"></rect>
                 </svg>
                 <h1 style="font-weight: 900; margin-bottom: 7px;">
-                  Talking Yak Speech Engine
+                  Whisper
                 </h1>
               </div>
               <p style="margin-bottom: 10px; font-size: 94%">
-                To turn the microphone off: Tap the stop button 
+                Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech translation and language identification. This demo cuts audio after around 30 secs.
               </p>
             </div>
         """
@@ -171,12 +179,20 @@ with block:
 
                 btn = gr.Button("Transcribe")
         text = gr.Textbox(show_label=False, elem_id="result-textarea")
- 
-        btn.click(inference, inputs=[audio], outputs=[text])
+        with gr.Group(elem_id="share-btn-container"):
+            community_icon = gr.HTML(community_icon_html, visible=False)
+            loading_icon = gr.HTML(loading_icon_html, visible=False)
+            share_button = gr.Button("Share to community", elem_id="share-btn", visible=False)
+        
+
+
+        
+        btn.click(inference, inputs=[audio], outputs=[text, community_icon, loading_icon, share_button])
+        share_button.click(None, [], [], _js=share_js)
  
         gr.HTML('''
         <div class="footer">
-                    🤗 Hugging Face
+                    <p>Model by <a href="https://github.com/openai/whisper" style="text-decoration: underline;" target="_blank">OpenAI</a> - Gradio Demo by 🤗 Hugging Face
                     </p>
         </div>
         ''')