Create app.py

app.py

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+import openai
+from gtts import gTTS
+import pyttsx3
+from IPython.display import Audio
+import gradio as gr
+
+openai.api_key = "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"
+
+def translate_audio(audio_file):
+    file1 = open(audio_file, "rb")
+    text = openai.Audio.translate(
+        model="whisper-1",
+        file=file1
+    )
+    return text["text"]
+
+def text_response(t):
+    messages = [{"role": "system", "content": "You are a therapist, you are supposed to answer questions related to stress, mental health. For the rest of the questions, respond you don't know. Respond to all input in 100 words or less."}]
+    messages.append({"role": "user", "content": t})
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo",
+        messages=messages
+    )
+    message = response["choices"][0]["message"]["content"]
+    return message
+
+from gtts import gTTS
+
+def audio_response(t):
+    tts = gTTS(text=t, lang='en', slow=False)
+    tts.save("output.mp3")
+    mp3_file_path = "output.mp3"
+    return mp3_file_path
+
+from IPython.display import Audio
+
+def transcribe(a):
+    t1 = translate_audio(a)
+    t2 = text_response(t1)
+    t3 = audio_response(t2)
+    return (t1, t2, t3)
+
+import gradio as gr
+
+output_1 = gr.Textbox(label="Speech to Text")
+output_2 = gr.Textbox(label="ChatGPT Output")
+output_3 = gr.Audio(label="ChatGPT output to audio")
+
+gr.Interface(
+    title='AI Voice Assistant',
+    fn=transcribe,
+    inputs=[
+        gr.Audio(sources="microphone", type="filepath"),
+    ],
+    outputs=[
+        output_1, output_2, output_3
+    ]
+).launch(share=True)