convert Jupyter notebook to .py file

merge_NEW_mm.py

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+#!/usr/bin/env python
+# coding: utf-8
+
+# In[1]:
+
+
+# pip install langdetect
+# pip install sentencepiece
+# pip install boto3
+# pip install awscli
+# pip install sacremoses
+
+
+# In[2]:
+
+
+import gradio as gr
+from transformers import pipeline, AutoTokenizer, TFAutoModelForSeq2SeqLM
+from dotenv import load_dotenv
+import os
+import subprocess
+import torch
+import tempfile
+from langdetect import detect
+from transformers import MarianMTModel, MarianTokenizer
+import re
+import boto3
+
+
+# In[3]:
+
+
+# import functions from functions file
+
+from functions_mm import handle_query, transcribe_audio_original, submit_question, polly_text_to_speech, translate, translate_and_speech, clear_inputs, voice_map, language_map, default_language, languages
+
+
+
+# In[4]:
+
+
+# Load environment variables.
+load_dotenv()
+
+# Set the model name for our LLMs.
+OPENAI_MODEL = "gpt-3.5-turbo"
+# Store the API key in a variable.
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
+
+
+# In[5]:
+
+
+instructions = """
+# Diabetes Chatbot
+#### Step 1: Record your audio OR input text (NOT both!)
+#### Step 2: Would you like response in new language? Choose your language  
+#### Step 3: Submit question
+#### Step 4: Translate response
+#### Step 5: Clear inputs and start fresh
+"""
+
+
+with gr.Blocks() as app2:
+    
+    with gr.Row():
+        gr.Markdown(instructions)
+        
+    with gr.Row():
+        input_audio = gr.Audio(
+            label="Ask a question about Diabetes, then click 'Transcribe audio",
+            type="filepath")
+        language_dropdown = gr.Dropdown(label="Click the middle of the dropdown bar to select translation language",
+                                        choices=list(language_map.keys()), value=default_language, type='value')
+        
+    with gr.Row():
+        transcribe_button = gr.Button("Transcribe audio")
+        submit_button = gr.Button("Submit your question")
+        translate_button = gr.Button("Translate the response")
+        clear_button = gr.Button("Clear All")
+    
+    #Divide the screen horizontally into 2 columns
+    with gr.Row():
+            #This column will be on the left side of screen
+            with gr.Column():
+                query_text = gr.Textbox(label="Type your question here. If there is audio recorded AND question text, app will submit question text. Click transcribe button to populate with audio text")
+                # output_original_speech = gr.Audio(label="Text to speech here")
+            
+            with gr.Column():
+                response_text = gr.Textbox(label="Chatbot response")
+                response_speech = gr.Audio(label="Chatbot response speech")    
+        
+            #This column will be on the right side of screen
+            with gr.Column():    
+                output_translated = gr.Textbox(label="Translated text")
+                output_translated_speech = gr.Audio(label="Translated speech")
+
+    # Audio transcription
+    transcribe_button.click(
+        fn=transcribe_audio_original,
+        inputs=[input_audio],
+        outputs=[query_text]
+    )
+    
+    submit_button.click(
+        fn=submit_question,
+        inputs=[input_audio, query_text, language_dropdown],
+        outputs=[response_text, response_speech]
+    )
+        
+    # Translation
+    translate_button.click(
+        fn=translate_and_speech,
+        inputs=[response_text, language_dropdown],
+        outputs=[output_translated, output_translated_speech]
+    )
+        
+    #Clearing all inputs and outputs
+    clear_button.click(
+    fn=clear_inputs,
+    inputs=[],
+    outputs=[input_audio, query_text, response_text, response_speech, output_translated, output_translated_speech]
+    )
+
+app2.launch(show_error=True, share=True)
+