Create app.py

Created the main app app.py

app.py

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+import gradio as gr
+import openai, config, subprocess
+import requests
+import json
+
+messages = [{"role": "system", "content": 'You are Steve Jobs. Respond to all input in 25 words or less.'}]
+
+# Set up the API endpoint URL and headers
+url = f"https://api.elevenlabs.io/v1/text-to-speech/{os.environ.get('voice_id')}/stream"
+headers = {
+    "accept": "*/*",
+    "xi-api-key": os.environ.get('elevenlabs_api_key'),
+    "Content-Type": "application/json",
+}
+
+# Define a function to handle the Gradio input and generate the response
+def transcribe(audio):
+    global messages
+
+    # Use OpenAI to transcribe the user's audio input
+    # API call 1
+    audio_file = open(audio, "rb")
+    transcript = openai.Audio.transcribe("whisper-1", audio_file)
+
+    # Append the user's message to the message history
+    messages.append({"role": "user", "content": transcript["text"]})
+
+    # Generate a response using OpenAI's chat API
+    #API call 2
+    response = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=messages)
+
+    # Extract the system message from the API response and append it to the message history
+    system_message = response["choices"][0]["message"]
+    messages.append(system_message)
+    
+    
+    #API Call 3
+    # Use the voice synthesis API to generate an audio response from the system message
+    data = {
+        "text": system_message["content"],
+        "voice_settings": {
+            "stability": 0,
+            "similarity_boost": 0
+        }
+    }
+    response = requests.post(url, headers=headers, data=json.dumps(data), stream=True)
+
+    # Save the audio response to a file
+    if response.ok:
+        with open("output.wav", "wb") as f:
+            for chunk in response.iter_content(chunk_size=1024):
+                f.write(chunk)
+    else:
+        print(f"Error: {response.status_code} - {response.reason}")
+        
+    IPython.display.display(IPython.display.Audio('output.wav'))
+
+    # Generate a chat transcript for display in the Gradio UI
+    chat_transcript = ""
+    for message in messages:
+        if message['role'] != 'system':
+            chat_transcript += message['role'] + ": " + message['content'] + "\n\n"
+
+    return chat_transcript,'output.wav'
+
+# Define the Gradio UI interface
+# ui = gr.Interface(fn=transcribe, inputs=gr.Audio(source="microphone", type="filepath"), outputs="text")
+ui = gr.Interface(fn=transcribe, inputs=gr.Audio(source="microphone", type="filepath"), outputs=['text','audio'])
+ui.launch(share=True)