app.py

import os
os.system('pip install ipython')
from IPython.display import clear_output
os.system('pip install python-dotenv pydub ffmpeg-python nltk gradio==3.48.0  OpenAI gradio_client emoji')
from utils.tts import *
from utils.llm import *
clear_output()
import gradio as gr
# Define the main function for the API endpoint that takes the input text and chatbot role
def generate_story(secret_token, input_text, chatbot_role):
    if secret_token != SECRET_TOKEN:
        raise gr.Error(
            f'Invalid secret token.  Secret Token: secret')
    # Initialize a list of lists for history with the user input as the first entry
    history = [[input_text, None]]
    story_sentences = get_sentence(history, chatbot_role)  # get_sentence function generates text

    story_text = ""  # Initialize variable to hold the full story text
    last_history = None  # To store the last history after all sentences

    # Iterate over the sentences generated by get_sentence and concatenate them
    for sentence, updated_history in story_sentences:
        if sentence:
            story_text += sentence.strip() + " "  # Add each sentence to the story_text
            last_history = updated_history  # Keep track of the last history update

    if last_history is not None:
        # Convert the list of lists back into a list of tuples for the history
        history_tuples = [tuple(entry) for entry in last_history]
        #return history_tuples, chatbot_role, story_text
        return generate_speech_from_history2(history_tuples, chatbot_role, story_text)

    else:
        return []
    
    # Create a Gradio Interface using only the `generate_story_and_speech()` function and the 'json' output type
demo = gr.Interface(
    fn=generate_story,
    inputs=[gr.Text(label='Secret Token'),gr.Textbox(placeholder="Enter your text here"), gr.Dropdown(choices=ROLES, label="Select Chatbot Role")],
    outputs="json"
)
demo.queue()
demo.launch(debug=True)