import gradio as gr
import random
from datetime import datetime
import tempfile
import os
import edge_tts
import asyncio
import warnings
import pytz
import re
import json
import pandas as pd
from pathlib import Path
from gradio_client import Client
warnings.filterwarnings('ignore')
# Initialize story starters with added comedy section
STORY_STARTERS = [
['Adventure', 'In a hidden temple deep in the Amazon...'],
['Mystery', 'The detective found an unusual note...'],
['Romance', 'Two strangers meet on a rainy evening...'],
['Sci-Fi', 'The space station received an unexpected signal...'],
['Fantasy', 'A magical portal appeared in the garden...'],
['Comedy-Sitcom', 'The new roommate arrived with seven emotional support animals...'],
['Comedy-Workplace', 'The office printer started sending mysterious messages...'],
['Comedy-Family', 'Grandma decided to become a social media influencer...'],
['Comedy-Supernatural', 'The ghost haunting the house was absolutely terrible at scaring people...'],
['Comedy-Travel', 'The GPS insisted on giving directions in interpretive dance descriptions...']
]
# Initialize client outside of interface definition
arxiv_client = None
def init_client():
global arxiv_client
if arxiv_client is None:
arxiv_client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
return arxiv_client
def save_story(story, audio_path):
"""Save story and audio to gallery with markdown formatting"""
try:
# Create gallery directory if it doesn't exist
gallery_dir = Path("gallery")
gallery_dir.mkdir(exist_ok=True)
# Generate timestamp and sanitize first line for filename
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
first_line = story.split('\n')[0].strip()
safe_name = re.sub(r'[^\w\s-]', '', first_line)[:50] # First 50 chars, sanitized
# Save story text as markdown
story_path = gallery_dir / f"story_{timestamp}_{safe_name}.md"
with open(story_path, "w") as f:
f.write(f"# {first_line}\n\n{story}")
# Copy audio file to gallery with matching name
new_audio_path = None
if audio_path:
new_audio_path = gallery_dir / f"audio_{timestamp}_{safe_name}.mp3"
os.system(f"cp {audio_path} {str(new_audio_path)}")
return str(story_path), str(new_audio_path) if new_audio_path else None
except Exception as e:
print(f"Error saving to gallery: {str(e)}")
return None, None
def load_gallery():
"""Load all stories and audio from gallery with markdown support"""
try:
gallery_dir = Path("gallery")
if not gallery_dir.exists():
return []
files = []
for story_file in sorted(gallery_dir.glob("story_*.md"), reverse=True):
# Extract timestamp and name from filename
parts = story_file.stem.split('_', 2)
timestamp = f"{parts[1]}"
# Find matching audio file
audio_pattern = f"audio_{timestamp}_*.mp3"
audio_files = list(gallery_dir.glob(audio_pattern))
audio_file = audio_files[0] if audio_files else None
# Read story content and get preview
with open(story_file) as f:
content = f.read()
# Skip markdown header and get preview
preview = content.split('\n\n', 1)[1][:100] + "..."
files.append([
timestamp,
f"[{preview}]({str(story_file)})", # Markdown link to story
str(story_file),
str(audio_file) if audio_file else None
])
return files
except Exception as e:
print(f"Error loading gallery: {str(e)}")
return []
# Keep all other functions unchanged
def generate_story(prompt, model_choice):
"""Generate story using specified model"""
try:
client = init_client()
if client is None:
return "Error: Story generation service is not available."
result = client.predict(
prompt=prompt,
llm_model_picked=model_choice,
stream_outputs=True,
api_name="/ask_llm"
)
return result
except Exception as e:
return f"Error generating story: {str(e)}"
async def generate_speech(text, voice="en-US-AriaNeural"):
"""Generate speech from text"""
try:
communicate = edge_tts.Communicate(text, voice)
with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp_file:
tmp_path = tmp_file.name
await communicate.save(tmp_path)
return tmp_path
except Exception as e:
print(f"Error in text2speech: {str(e)}")
return None
def process_story_and_audio(prompt, model_choice):
"""Process story, generate audio, and save to gallery"""
try:
# Generate story
story = generate_story(prompt, model_choice)
if isinstance(story, str) and story.startswith("Error"):
return story, None, None
# Generate audio
audio_path = asyncio.run(generate_speech(story))
# Save to gallery
story_path, saved_audio_path = save_story(story, audio_path)
return story, audio_path, load_gallery()
except Exception as e:
return f"Error: {str(e)}", None, None
def play_gallery_audio(evt: gr.SelectData, gallery_data):
"""Play audio from gallery selection"""
try:
selected_row = gallery_data[evt.index[0]]
audio_path = selected_row[3] # Audio path is the fourth element
if audio_path and os.path.exists(audio_path):
return audio_path
return None
except Exception as e:
print(f"Error playing gallery audio: {str(e)}")
return None
# Create the Gradio interface (keep unchanged)
with gr.Blocks(title="AI Story Generator") as demo:
gr.Markdown("""
# 🎠AI Story Generator & Narrator
Generate creative stories, listen to them, and build your gallery!
""")
with gr.Row():
with gr.Column(scale=3):
with gr.Row():
prompt_input = gr.Textbox(
label="Story Concept",
placeholder="Enter your story idea...",
lines=3
)
with gr.Row():
model_choice = gr.Dropdown(
label="Model",
choices=[
"mistralai/Mixtral-8x7B-Instruct-v0.1",
"mistralai/Mistral-7B-Instruct-v0.2"
],
value="mistralai/Mixtral-8x7B-Instruct-v0.1"
)
generate_btn = gr.Button("Generate Story")
with gr.Row():
story_output = gr.Textbox(
label="Generated Story",
lines=10,
interactive=False
)
with gr.Row():
audio_output = gr.Audio(
label="Story Narration",
type="filepath"
)
# Sidebar with Story Starters and Gallery
with gr.Column(scale=1):
gr.Markdown("### 📚 Story Starters")
story_starters = gr.Dataframe(
value=STORY_STARTERS,
headers=["Category", "Starter"],
interactive=False
)
gr.Markdown("### 🎬 Gallery")
gallery = gr.Dataframe(
value=load_gallery(),
headers=["Timestamp", "Preview", "Story Path", "Audio Path"],
interactive=False
)
# Event handlers
def update_prompt(evt: gr.SelectData):
return STORY_STARTERS[evt.index[0]][1]
story_starters.select(update_prompt, None, prompt_input)
generate_btn.click(
fn=process_story_and_audio,
inputs=[prompt_input, model_choice],
outputs=[story_output, audio_output, gallery]
)
gallery.select(
fn=play_gallery_audio,
inputs=[gallery],
outputs=[audio_output]
)
if __name__ == "__main__":
demo.launch()