Create app.py

app.py

@@ -0,0 +1,57 @@
+import gradio as gr
+import openai
+from decouple import config
+from gtts import gTTS
+import os
+import win32com.client
+import pythoncom
+import config 
+
+openai.api_key = config.API_KEYS['openai']
+
+# The Models Job or role
+messages = [
+    {"role": "system", "content": "You are a helpful assistant."},
+]
+
+
+#  language = 'en'
+
+
+# Main method goes here
+def decipher(audio):
+    global messages
+
+    # Using openAI's speech to text model
+    audio_file = open(audio, "rb")
+    transcript = openai.Audio.transcribe("whisper-1", audio_file)
+
+    messages.append({"role": "user", "content": transcript["text"]})
+
+    response =  openai.ChatCompletion.create(
+        model="gpt-3.5-turbo",
+        messages=messages
+    )
+
+    system_message = response["choices"][0]["message"]["content"]
+    pythoncom.CoInitialize()
+    speaker = win32com.client.Dispatch("SAPI.SpVoice")
+    speaker.Speak(system_message)
+    # myobj = gTTS(text=system_message, lang=language, slow=False)
+    # myobj.save("welcome.mp3")
+    # # Playing the converted file
+    # os.system("start welcome.mp3")
+    messages.append({"role": "assistant", "content": system_message},)
+
+    chat_transcript = ""
+    for message in messages:
+        if message['role'] != 'system':
+            chat_transcript += message['role'] + ": " + message['content'] + "\n\n"
+
+    return chat_transcript
+
+
+# Using Gradio's audio Interface 
+interface = gr.Interface(fn=decipher, inputs=gr.Audio(
+    source="microphone", type="filepath"), outputs="text")
+interface.launch(share=True)