light theme

.streamlit/config.toml

@@ -1,4 +1,4 @@
 [theme]
-base = 'dark'
+#base = 'dark'
 primaryColor = 'F63366'
 font = 'sans serif'

aws/synthesize_speech.py

@@ -13,14 +13,11 @@
     )
 
 def synthesize_speech(text):
-
     Polly = Session.client("polly")
-
     response = Polly.synthesize_speech(
         Text=text,
         OutputFormat="mp3",
         VoiceId="Joanna")
-
     if "AudioStream" in response:
         # Note: Closing the stream is important because the service throttles on the
         # number of parallel connections. Here we are using contextlib.closing to
@@ -37,12 +34,10 @@ def synthesize_speech(text):
                 # Could not write to file, exit gracefully
                 print(error)
                 sys.exit(-1)
-
     else:
         # The response didn't contain audio data, exit gracefully
         print("Could not stream audio")
         sys.exit(-1)
-
     '''
     # Play the audio using the platform's default player
     if sys.platform == "win32":
@@ -51,5 +46,4 @@ def synthesize_speech(text):
         # The following works on macOS and Linux. (Darwin = mac, xdg-open = linux).
         opener = "open" if sys.platform == "darwin" else "xdg-open"
         subprocess.call([opener, output])'''
-
     return output

pages/Resume Screen.py

@@ -136,17 +136,14 @@ def answer_call_back():
                 llm_answer = st.session_state.resume_screen.run(input)
                 # speech synthesis and speak out
                 audio_file_path = synthesize_speech(llm_answer)
-
                 st.session_state.audio_file_path = audio_file_path
                 # create audio widget with autoplay
                 audio_widget = Audio(audio_file_path, autoplay=True)
-
                 # save audio data to history
                 st.session_state.resume_history.append(
                     Message("ai", llm_answer)
                 )
                 st.session_state.token_count += cb.total_tokens
-
                 return audio_widget
             except:
                 st.session_state.resume_history.append(Message("ai", "Sorry, I didn't get that. Please try again."))