Spaces:
Sleeping
Sleeping
Add AI Storyteller application
Browse files
app.py
ADDED
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| 1 |
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import torch
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| 2 |
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import transformers
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import gradio as gr
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import random
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import re
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from typing import Dict, List
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import warnings
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import os
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warnings.filterwarnings('ignore')
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# Set environment variables for better performance
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os.environ['TOKENIZERS_PARALLELISM'] = 'false'
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class AIStoryteller:
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"""AI Storyteller optimized for Hugging Face Spaces"""
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def __init__(self):
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self.model = None
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self.tokenizer = None
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self.model_loaded = False
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self.load_model()
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def load_model(self):
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"""Load the AI model"""
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try:
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print("π₯ Loading DistilGPT-2 model...")
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model_name = "distilgpt2"
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self.tokenizer = AutoTokenizer.from_pretrained(model_name)
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self.model = AutoModelForCausalLM.from_pretrained(
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model_name,
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torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
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)
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if self.tokenizer.pad_token is None:
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self.tokenizer.pad_token = self.tokenizer.eos_token
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self.model_loaded = True
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print("β
Model loaded successfully!")
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return True
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except Exception as e:
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print(f"β Model loading failed: {e}")
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return False
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def generate_story(self, prompt, max_length=100):
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"""Generate a story from a prompt"""
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if not self.model_loaded:
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return "β Model not loaded. Please try again."
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try:
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inputs = self.tokenizer.encode(prompt, return_tensors='pt', max_length=256, truncation=True)
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with torch.no_grad():
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outputs = self.model.generate(
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inputs,
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max_length=min(inputs.shape[1] + max_length, 256),
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temperature=0.8,
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do_sample=True,
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top_p=0.9,
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top_k=50,
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pad_token_id=self.tokenizer.eos_token_id,
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no_repeat_ngram_size=2,
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repetition_penalty=1.1
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)
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full_story = self.tokenizer.decode(outputs[0], skip_special_tokens=True)
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if full_story.startswith(prompt):
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generated_part = full_story[len(prompt):].strip()
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return f"{prompt} {generated_part}"
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else:
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return full_story
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except Exception as e:
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return f"β Error generating story: {str(e)}"
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# Initialize the storyteller
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print("π Initializing AI Storyteller...")
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storyteller = AIStoryteller()
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def generate_story_interface(prompt, genre, story_length):
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"""Main interface function"""
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if not prompt or not prompt.strip():
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return "β Please enter a story prompt!"
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genre_starters = {
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"Fantasy": "In a realm of magic and wonder,",
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"Sci-Fi": "In the distant future among the stars,",
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"Mystery": "On a foggy night filled with secrets,",
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"Horror": "In the darkness where nightmares dwell,",
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"Romance": "When two hearts found each other,",
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"Adventure": "On a daring quest for glory,",
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"Comedy": "In a world of laughter and mishaps,",
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"Drama": "In a tale of human emotion,"
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}
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if genre in genre_starters:
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full_prompt = f"{genre_starters[genre]} {prompt.strip()}"
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else:
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full_prompt = prompt.strip()
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return storyteller.generate_story(full_prompt, max_length=int(story_length))
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# Create Gradio interface
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interface = gr.Interface(
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fn=generate_story_interface,
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inputs=[
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gr.Textbox(
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label="π Story Prompt",
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placeholder="Enter your story idea (e.g., 'a detective finds a mysterious letter')",
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lines=3
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),
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gr.Dropdown(
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choices=["Fantasy", "Sci-Fi", "Mystery", "Horror", "Romance", "Adventure", "Comedy", "Drama"],
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label="π Genre",
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value="Fantasy"
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),
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gr.Slider(
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minimum=30,
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maximum=120,
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value=80,
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label="π Story Length"
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)
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],
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outputs=gr.Textbox(
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label="π Generated Story",
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lines=8
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),
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title="π AI Storyteller",
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description="""
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π **Create Amazing Stories with AI!** π
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Enter a creative prompt, choose your favorite genre, and let AI craft a unique story for you!
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Perfect for writers, students, and anyone who loves creative storytelling.
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""",
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examples=[
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["a young wizard discovers a hidden library", "Fantasy", 100],
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["a detective receives a cryptic phone call", "Mystery", 80],
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["robots develop feelings", "Sci-Fi", 90],
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["two strangers meet in a coffee shop", "Romance", 70],
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["an explorer finds a secret cave", "Adventure", 85]
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],
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theme=gr.themes.Soft()
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)
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# Launch the app
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if __name__ == "__main__":
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interface.launch()
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