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import gradio as gr
import openai
import whisper
from PIL import Image
from diffusers import StableDiffusionPipeline
# Set your OpenAI API key
openai.api_key = ""
# Initialize text generation and image generation pipelines
text_generation_pipe = openai.Completion.create
image_generation_pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4")
# Initialize Whisper API key for text-to-speech
whisper_api_key = ""
# Define function for generating stories and illustrations
def generate_story_and_illustration(prompt, character_name):
# Generate story
story_text = text_generation_pipe(engine="text-davinci-003", prompt=f"Once upon a time, {character_name}... {prompt}", max_tokens=150)["choices"][0]["text"]
# Generate image based on story
image = image_generation_pipe(story_text)
# Convert story text to speech using Whisper API
tts_result = whisper.transcribe(audio="content.flac", language="en", api_key=whisper_api_key)
audio_data = tts_result["segments"][0]["alternatives"][0]["text"]
# Return story text, audio data, and image
return story_text, audio_data, image.images[0]
# Create Gradio interface
interface = gr.Interface(
fn=generate_story_and_illustration,
inputs=[
gr.Textbox(label="Start your story with..."),
gr.Textbox(label="Give your character a name:"),
],
outputs=[
gr.Textbox(label="Story"),
gr.Audio(label="Listen to the story"),
gr.Image(label="See the story come alive"),
],
title="Storyteller Playground",
description="Create amazing stories with the help of AI!",
theme="kids",
)
# Launch the app on Hugging Face Spaces
interface.launch()
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