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import random
import gradio as gr
import ollama
from huggingface_hub import InferenceClient
import os
def chat_short_story(length, genre, theme, tone, writing_style):
"""
Generates a creative short story using a Hugging Face model.
Parameters:
length (int): The approximate word count for the story.
genre (str): The genre of the story (e.g., fantasy, mystery).
theme (str): The central theme of the story.
tone (str): The tone of the story (e.g., humorous, serious).
writing_style (str): The writing style (e.g., poetic, conversational).
Returns:
str: The generated short story, or an error message if unsuccessful.
"""
# System message to define the assistant's role
system_message = (
"You are a highly creative short story writer capable of crafting stories across any genre. "
"For every story created, ensure you generate a suitable title."
)
# Construct the user prompt
prompt = (
f"Write a creative short story of approximately {length} words in the {genre} genre. "
f"Use a {writing_style} writing style with a {tone} tone. "
f"The story should revolve around the theme of {theme}. "
f"Ensure the narrative is compelling and includes a suitable title."
)
# Retrieve the Hugging Face API key from the environment
HUGGINGFACE_API_KEY = os.getenv("HUGGINGFACE_API_KEY")
if not HUGGINGFACE_API_KEY:
return "Error: Hugging Face API key not found. Please set the HUGGINGFACE_API_KEY environment variable."
# Initialize the Hugging Face Inference Client
try:
client = InferenceClient(api_key=HUGGINGFACE_API_KEY)
except Exception as e:
return f"Error: Failed to initialize Hugging Face client. Details: {e}"
# Interact with the model
try:
result = client.chat.completions.create(
model="meta-llama/Llama-3.2-3B-Instruct",
messages=[
{"role": "system", "content": system_message},
{"role": "user", "content": prompt},
]
)
except Exception as e:
return f"Error: Failed to interact with the model. Details: {e}"
# Extract the story content from the response
if "choices" in result and len(result["choices"]) > 0:
return result["choices"][0]["message"]["content"]
else:
return "Error: No story generated. Please check your prompt or model configuration."
# Predefined options
Length = [100, 250, 750]
Length = [l for l in Length if l >= 100]
r_length = random.choice(Length)
Genre = [
"Fiction", "Nonfiction", "Drama", "Poetry", "Fantasy", "Horror", "Mystery",
"Science Fiction", "Suspense", "Women's fiction", "Supernatural/Paranormal", "Young adult"
]
r_genre = random.choice(Genre)
Themes = [
"Love", "Redemption", "Forgiveness", "Coming of age", "Revenge", "Good vs evil",
"Bravery and hardship", "The power of social status", "The destructive nature of love",
"The fallibility of the human condition"
]
r_themes = random.choice(Themes)
Writing_Styles = ["Expository", "Narrative", "Descriptive", "Persuasive", "Creative"]
r_Style = random.choice(Writing_Styles)
Tones = ["Formal", "Optimistic", "Worried", "Friendly", "Curious", "Assertive", "Encouraging"]
r_tones = random.choice(Tones)
# Gradio Interface setup
iface = gr.Interface(
fn=chat_short_story,
inputs=[
gr.Slider(value=100, label="Story_Length", minimum=100, maximum=2500),
gr.Dropdown(label="Story_Genre", choices=Genre),
gr.Dropdown(label="Story_Theme", choices=Themes),
gr.Dropdown(label="Writing_Styles", choices=Writing_Styles),
gr.Dropdown(label="Story_Tone", choices=Tones)
],
outputs=gr.Text(),
title="Welcome to the Patrick's Story Generator"
)
iface.launch()
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