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app.py
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# Import libraries
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import gradio as gr
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from transformers import pipeline
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from gtts import gTTS
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from io import BytesIO
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from PIL import Image
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# Create a text generation pipeline with GPT-2
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story_generator = pipeline("text-generation", model="EleutherAI/gpt-neo-1.3B")
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# Set the context for the storyteller
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messages = [{"role": "system", "content": "You are a magical storyteller, creating wonderful tales for kids. Make them imaginative and full of joy!"}]
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# Define the Storyteller function
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def StorytellerGPT(character, child_name, lesson_choice, tell_story):
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# Set the characters and lesson based on user choices
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character_info = f"Once upon a time, {child_name} met {character}. "
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lesson_info = f"Today's lesson is about {lesson_choice}. "
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messages.append({"role": "user", "content": tell_story})
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# Generate story using Hugging Face's GPT-2
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story_reply = story_generator(character_info + lesson_info + tell_story, max_length=150, num_return_sequences=1)[0]['generated_text']
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messages.append({"role": "assistant", "content": story_reply})
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# Convert text to speech
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tts = gTTS(text=story_reply, lang='en', slow=False)
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audio_io = BytesIO()
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tts.save(audio_io)
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audio_io.seek(0)
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# Convert text to image
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image = Image.new("RGB", (300, 300), (255, 255, 255))
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image_path = "/path/to/output/image.png"
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image.save(image_path)
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return story_reply, Audio(data=audio_io.read(), autoplay=True), image
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# Create the Gradio Interface
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demo = gr.Interface(
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fn=StorytellerGPT,
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inputs=[
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gr.Textbox("text", label="Child's Name"),
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gr.Dropdown(["unicorn", "dragon", "wizard"], label="Choose a Character"),
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gr.Dropdown(["kindness", "creativity", "bravery"], label="Choose a Lesson"),
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gr.Textbox("text", label="Start the Story with"),
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],
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outputs=["text", "audio", "image"],
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title="📖 Storytelling Magic",
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description="A magical storyteller app for kids! Choose characters, add your name, and select the lesson you want to learn.",
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)
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# Launch the Gradio Interface
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demo.launch(
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