Update app.py

app.py

@@ -1,29 +1,38 @@
 import streamlit as st
 from audio_recorder_streamlit import audio_recorder
-import openai
-API_KEY = 'enter-openai-api-key-here'
+import openai  # Corrected import
 
+API_KEY = 'enter-openai-api-key-here'
 
+# Set the API key
+openai.api_key = API_KEY
 
 def transcribe_text_to_voice(audio_location):
-    client = openai(api_key=API_KEY)
-    audio_file= open(audio_location, "rb")
-    transcript = client.audio.transcriptions.create(model="whisper-1", file=audio_file)
-    return transcript.text
+    # Transcribe audio to text using Whisper API
+    with open(audio_location, "rb") as audio_file:
+        transcript = openai.Audio.transcriptions.create(
+            model="whisper-1", file=audio_file
+        )
+    return transcript['text']
 
 def chat_completion_call(text):
-    client = openai(api_key=API_KEY)
-    messages = [{"role": "user", "content": text}]
-    response = client.chat.completions.create(model="gpt-3.5-turbo-1106", messages=messages)
-    return response.choices[0].message.content
-
+    # Send the text to GPT-3.5 for chat completion
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo-1106", 
+        messages=[{"role": "user", "content": text}]
+    )
+    return response['choices'][0]['message']['content']
 
 def text_to_speech_ai(speech_file_path, api_response):
-    client = openai(api_key=API_KEY)
-    response = client.audio.speech.create(model="tts-1",voice="nova",input=api_response)
-    response.stream_to_file(speech_file_path)
-
-
+    # Convert the text to speech using OpenAI's TTS API
+    response = openai.Audio.speech.create(
+        model="text-to-speech-1",  # TTS model name may differ
+        voice="nova",  # Specify a voice (choose one that is available)
+        input=api_response
+    )
+    # Save the speech response to a file
+    with open(speech_file_path, "wb") as f:
+        f.write(response['audio'])
 
 st.title("🧑‍💻 Skolo Online 💬 Talking Assistant")
 
@@ -33,20 +42,22 @@ Hi🤖 just click on the voice recorder and let me know how I can help you today
 
 audio_bytes = audio_recorder()
 if audio_bytes:
-    ##Save the Recorded File
+    # Save the Recorded Audio File
     audio_location = "audio_file.wav"
     with open(audio_location, "wb") as f:
         f.write(audio_bytes)
 
-    #Transcribe the saved file to text
+    # Transcribe the saved file to text
     text = transcribe_text_to_voice(audio_location)
     st.write(text)
 
-    #Use API to get an AI response
+    # Get AI response from GPT-3.5
     api_response = chat_completion_call(text)
     st.write(api_response)
 
-    # Read out the text response using tts
+    # Convert the response to speech and save it as a file
     speech_file_path = 'audio_response.mp3'
     text_to_speech_ai(speech_file_path, api_response)
-    st.audio(speech_file_path)
+
+    # Play the audio response in the app
+    st.audio(speech_file_path)