Update app.py

app.py

@@ -1,22 +1,46 @@
 import gradio as gr
+from transformers import pipeline
+from espnet2.bin.tts_inference import Text2Speech
 
-def my_function(input1, input2):
-  print(input1)
-  print(input2)
-  return input1 + input2
+def generateTextAndAudio(inputText, numGen):
 
-title = 'My gradio app'
-description = "My simple description for my first gradio app"
+  # --- Generating the Text ---
+  # With the provided text from user, generate more text up to `numGen` tokens/sub-words
+  textOutput = textGenerator(inputText, max_length = numGen)
+  # The output of the text generator is a list of dictionaries, grab the first dictionary
+  # then get the generated text from the dictionary using the `generated_text` key
+  genText = textOutput[0]['generated_text']
+  
+  print("Input Text:", inputText)
 
-input1_textbox = gr.Textbox(label="Context Box")
-input2_textbox = gr.Textbox(label="Question Box")
+  print("Generated Text:", genText)
 
-output1_textbox = gr.Textbox()
+  # --- Generating the Audio ---
+  # With the newly generated text, generate some speech
+  audioOutput = audioGenerator(genText)
+  # Get the wav data
+  genAudio = audioOutput['wav']
 
-iface = gr.Interface(fn=my_function, 
-                     inputs=[input1_textbox, input2_textbox], 
-                     outputs=[output1_textbox], 
-                     title=title, 
-                     description=description)
+  # Return two things
+  # 1) Generated Text
+  # 2) 24k sampling rate, and the Generated Audio (wav) as numpy (instead of tensor)
+  return genText, (24000, genAudio.numpy())
+  
+# Main
+textGenerator = pipeline('text-generation', model = 'gpt2')
+audioGenerator = Text2Speech.from_pretrained("espnet/kan-bayashi_ljspeech_joint_finetune_conformer_fastspeech2_hifigan")
 
-iface.launch()
+input1_textbox = gr.Textbox(label="Input text")
+input2_slider = gr.Slider(minimum=1, maximum=100, step=1, default=30, label="Number of words to generate")
+
+output1_textbox = gr.Textbox(label = "Generated Text")
+output2_Audio = gr.Audio(label = "Generated Audio")
+
+title = "Generate Text and it's Audio!"
+description = "Provide the text, and how many subwords to generate"
+
+iface = gr.Interface(fn=generateTextAndAudio, 
+                     inputs=[input1_textbox, input2_slider],
+                     outputs=[output1_textbox, output2_Audio],
+                     title=title,
+                     description=description).launch(debug = True)