Update app.py

app.py

@@ -21,6 +21,8 @@ def query(api_url, payload=None, data=None):
 
 # Define the function to translate speech
 # Define the function to translate speech
+def translate_speech(audio_file):
+   # Define the function to translate speech
 def translate_speech(audio_file):
     print(f"Type of audio: {type(audio_file)}, Value of audio: {audio_file}")  # Debug line
 
@@ -29,6 +31,14 @@ def translate_speech(audio_file):
     output = query(ASR_API_URL, data=data)
     print(f"Output: {output}")  # Debug line
 
+    # Check if 'error' key exists in the output
+    if 'error' in output:
+        print(f"Error: {output['error']}")
+        estimated_time = output.get('estimated_time')
+        if estimated_time:
+            print(f"Estimated time for the model to load: {estimated_time} seconds")
+        return
+
     # Check if 'text' key exists in the output
     if 'text' in output:
         transcription = output["text"]
@@ -46,6 +56,30 @@ def translate_speech(audio_file):
     # Display the audio output
     return Audio(audio_bytes)
 
+    # print(f"Type of audio: {type(audio_file)}, Value of audio: {audio_file}")  # Debug line
+
+    # # Use the ASR pipeline to transcribe the audio
+    # data = audio_file.read()
+    # output = query(ASR_API_URL, data=data)
+    # print(f"Output: {output}")  # Debug line
+
+    # # Check if 'text' key exists in the output
+    # if 'text' in output:
+    #     transcription = output["text"]
+    # else:
+    #     print("Key 'text' does not exist in the output.")
+    #     return
+
+    # # Use the translation pipeline to translate the transcription
+    # translated_text = query(TRANSLATION_API_URL, {"inputs": transcription})
+
+    # # Use the TTS pipeline to synthesize the translated text
+    # response = requests.post(TTS_API_URL, headers=headers, json={"inputs": translated_text})
+    # audio_bytes = response.content
+
+    # # Display the audio output
+    # return Audio(audio_bytes)
+
 
 # Define the Gradio interface
 iface = gr.Interface(