app.py

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 constants
PAGE_SIZE = 10
FILE_DIR_PATH = "gallery"

# Initialize story starters
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"""
    try:
        # Create gallery directory if it doesn't exist
        gallery_dir = Path(FILE_DIR_PATH)
        gallery_dir.mkdir(exist_ok=True)
        
        # Generate timestamp for unique filename
        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
        
        # Get first line for title
        first_line = story.split('\n')[0].strip()
        safe_name = re.sub(r'[^\w\s-]', '', first_line)[:50]
        
        # 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
        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 list_all_outputs(generation_history):
    """Load all story generations for community view"""
    try:
        directory_path = FILE_DIR_PATH
        if not os.path.exists(directory_path):
            return "", gr.update(visible=True)
            
        # Get all matched pairs of story/audio files
        file_pairs = []
        for story_file in Path(directory_path).glob("story_*.md"):
            timestamp = story_file.stem.split('_')[1]
            audio_pattern = f"audio_{timestamp}_*.mp3"
            audio_files = list(Path(directory_path).glob(audio_pattern))
            
            if audio_files:  # Only include if we have both story and audio
                file_pairs.append((story_file, audio_files[0]))
        
        # Sort by modification time, newest first
        file_pairs.sort(key=lambda x: os.path.getmtime(x[0]), reverse=True)
        
        history_list = generation_history.split(',') if generation_history else []
        updated_files = [str(audio) for _, audio in file_pairs if str(audio) not in history_list]
        updated_history = updated_files + history_list
        
        return ','.join(updated_history), gr.update(visible=True)
    except Exception as e:
        print(f"Error loading community generations: {str(e)}")
        return "", gr.update(visible=True)

def increase_list_size(list_size):
    """Increase the number of visible community generations"""
    return list_size + PAGE_SIZE

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
        
        # 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
    except Exception as e:
        return f"Error: {str(e)}", None

# Add CSS for community generations
css = '''
#live_gen:before {
    content: '';
    animation: svelte-z7cif2-pulseStart 1s cubic-bezier(.4,0,.6,1), svelte-z7cif2-pulse 2s cubic-bezier(.4,0,.6,1) 1s infinite;
    border: 2px solid var(--color-accent);
    background: transparent;
    z-index: var(--layer-1);
    pointer-events: none;
    position: absolute;
    height: 100%;
    width: 100%;
    border-radius: 7px;
}
#live_gen_items{
    max-height: 570px;
    overflow-y: scroll;
}
'''

# Create the Gradio interface
with gr.Blocks(title="AI Story Generator", css=css) as demo:
    gr.Markdown("""
    # 🎭 AI Story Generator & Narrator
    Generate creative stories, listen to them, and build your gallery!
    """)
    
    # Add hidden state for community generations
    generation_history = gr.Textbox(visible=False)
    list_size = gr.Number(value=PAGE_SIZE, visible=False)
    
    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 Community Generations
        with gr.Column(scale=1):
            gr.Markdown("### 📚 Story Starters")
            story_starters = gr.Dataframe(
                value=STORY_STARTERS,
                headers=["Category", "Starter"],
                interactive=False
            )
            
            # Community Generations section
            with gr.Column(elem_id="live_gen") as community_list:
                gr.Markdown("### 🎬 Community Stories")
                with gr.Column(elem_id="live_gen_items"):
                    @gr.render(inputs=[generation_history, list_size])
                    def show_output_list(generation_history, list_size):
                        history_list = generation_history.split(',') if generation_history else []
                        history_list_latest = history_list[:list_size]
                        
                        for audio_path in history_list_latest:
                            if not audio_path or not os.path.exists(audio_path):
                                continue
                                
                            try:
                                # Get corresponding story file
                                story_path = audio_path.replace('audio_', 'story_').replace('.mp3', '.md')
                                if not os.path.exists(story_path):
                                    continue
                                    
                                # Read story content
                                with open(story_path, 'r') as file:
                                    story_content = file.read()
                                    # Extract title from markdown
                                    title = story_content.split('\n')[0].replace('# ', '')
                                
                                with gr.Group():
                                    gr.Markdown(value=f"### {title}")
                                    gr.Audio(value=audio_path)
                            except Exception as e:
                                print(f"Error showing generation: {str(e)}")
                                continue
                
                load_more = gr.Button("Load More Stories")
                load_more.click(fn=increase_list_size, inputs=list_size, outputs=list_size)
    
    # 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]
    )
    
    # Auto-refresh for community generations
    demo.load(fn=list_all_outputs, inputs=generation_history, outputs=[generation_history, community_list], every=2)

if __name__ == "__main__":
    demo.launch()