import gradio as gr import requests import json import re from typing import List, Dict, Any import os # Hugging Face configuration HF_TOKEN = os.getenv("HUGGING_FACE_API_TOKEN", "") HF_API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-dev" def parse_script(script_text: str) -> Dict[str, Any]: """Parse script text and extract scenes and characters""" lines = script_text.strip().split('\n') scenes = [] characters = set() current_scene = None for line in lines: line = line.strip() if not line: continue # Scene headers (INT./EXT.) if line.upper().startswith(('INT.', 'EXT.', 'SCENE')): if current_scene: scenes.append(current_scene) current_scene = { 'location': line, 'dialogue': [], 'action': [] } # Character dialogue (ALL CAPS followed by dialogue) elif line.isupper() and len(line.split()) <= 3 and current_scene: characters.add(line) current_scene['dialogue'].append({'character': line, 'lines': []}) # Dialogue lines elif current_scene and current_scene['dialogue'] and not line.isupper(): current_scene['dialogue'][-1]['lines'].append(line) # Action lines elif current_scene and not line.isupper(): current_scene['action'].append(line) if current_scene: scenes.append(current_scene) return { 'scenes': scenes, 'characters': list(characters), 'total_scenes': len(scenes) } def generate_shot_list(script_data: Dict[str, Any]) -> List[Dict[str, Any]]: """Generate shot list from parsed script""" shots = [] shot_id = 1 for scene_idx, scene in enumerate(script_data['scenes']): # Establishing shot shots.append({ 'id': shot_id, 'type': 'Establishing Shot', 'description': f"Wide shot of {scene['location']}", 'scene': scene_idx + 1, 'location': scene['location'] }) shot_id += 1 # Character shots dialogue_chars = set() for dialogue in scene['dialogue']: char = dialogue['character'] if char not in dialogue_chars: shots.append({ 'id': shot_id, 'type': 'Medium Shot', 'description': f"Medium shot of {char}", 'scene': scene_idx + 1, 'character': char, 'location': scene['location'] }) dialogue_chars.add(char) shot_id += 1 # Action shots for action in scene['action']: if len(action) > 20: # Only significant action lines shots.append({ 'id': shot_id, 'type': 'Action Shot', 'description': action[:100] + "..." if len(action) > 100 else action, 'scene': scene_idx + 1, 'location': scene['location'] }) shot_id += 1 return shots def generate_image(prompt: str) -> str: """Generate image using Hugging Face API""" if not HF_TOKEN: return "https://via.placeholder.com/512x512?text=No+API+Key" headers = { "Authorization": f"Bearer {HF_TOKEN}", "Content-Type": "application/json" } payload = { "inputs": f"{prompt}, cinematic, professional, high quality" } try: response = requests.post(HF_API_URL, headers=headers, json=payload, timeout=30) if response.status_code == 200: # Save image and return path import base64 image_data = response.content image_b64 = base64.b64encode(image_data).decode() return f"data:image/png;base64,{image_b64}" else: return f"https://via.placeholder.com/512x512?text=API+Error+{response.status_code}" except Exception as e: return f"https://via.placeholder.com/512x512?text=Error" def process_script(script_text: str, generate_images: bool = True): """Main function to process script and generate shot list""" if not script_text.strip(): return "Please enter a script.", "", "" # Parse script script_data = parse_script(script_text) # Generate shot list shots = generate_shot_list(script_data) # Create summary summary = f""" ## Script Analysis Summary - **Total Scenes:** {script_data['total_scenes']} - **Characters:** {', '.join(script_data['characters'])} - **Generated Shots:** {len(shots)} """ # Create shot list display shot_list_html = "
" for shot in shots: # Generate image if requested image_html = "" if generate_images: image_url = generate_image(shot['description']) image_html = f'' shot_list_html += f"""

Shot {shot['id']}: {shot['type']}

Scene: {shot['scene']}

Description: {shot['description']}

{f"

Character: {shot.get('character', 'N/A')}

" if shot.get('character') else ""}

Location: {shot.get('location', 'N/A')}

{image_html}
""" shot_list_html += "
" return summary, shot_list_html, f"Generated {len(shots)} shots successfully!" # Sample script for demo SAMPLE_SCRIPT = """INT. COFFEE SHOP - DAY A bustling coffee shop filled with the morning crowd. Steam rises from espresso machines. SARAH sits at a corner table, typing furiously on her laptop. She glances at her watch nervously. SARAH (muttering to herself) Come on, come on... where is he? The door chimes as MIKE enters, scanning the room. He spots Sarah and approaches. MIKE Sorry I'm late! Traffic was insane. SARAH (relieved) Thank god you're here. I've been going crazy waiting. Mike sits down across from her. MIKE So, what's this big emergency about? Sarah closes her laptop and leans in conspiratorially. SARAH I found something. Something that could change everything. EXT. CITY STREET - DAY Sarah and Mike walk quickly down a busy sidewalk, weaving through pedestrians. MIKE Are you sure about this? SARAH I've never been more sure of anything in my life. They stop at a red light, looking around nervously.""" # Create Gradio interface with gr.Blocks(title="Script to Shots - AI Storyboard Generator") as demo: gr.Markdown(""" # 🎬 Script to Shots - AI Storyboard Generator Transform your scripts into visual shot lists with AI-generated reference images! **How it works:** 1. Paste your script in the text area below 2. Choose whether to generate AI images 3. Get an automated shot list with visual references """) with gr.Row(): with gr.Column(scale=1): script_input = gr.Textbox( label="Script Text", placeholder="Paste your script here...", lines=15, value=SAMPLE_SCRIPT ) with gr.Row(): generate_images_checkbox = gr.Checkbox( label="Generate AI Images", value=True, info="Generate visual references (requires API key)" ) process_btn = gr.Button("Generate Shot List", variant="primary") with gr.Column(scale=1): summary_output = gr.Markdown(label="Analysis Summary") status_output = gr.Textbox(label="Status", interactive=False) with gr.Row(): shot_list_output = gr.HTML(label="Generated Shot List") # Example scripts gr.Markdown("### 📝 Example Scripts") with gr.Row(): example_btn1 = gr.Button("Coffee Shop Scene") example_btn2 = gr.Button("Action Sequence") example_btn3 = gr.Button("Clear Script") # Event handlers process_btn.click( fn=process_script, inputs=[script_input, generate_images_checkbox], outputs=[summary_output, shot_list_output, status_output] ) example_btn1.click( fn=lambda: SAMPLE_SCRIPT, outputs=script_input ) example_btn2.click( fn=lambda: """EXT. ROOFTOP - NIGHT Rain pours down on the city skyline. Lightning illuminates the darkness. ALEX crouches behind an air conditioning unit, breathing heavily. ALEX (into radio) I'm in position. Do you see them? VOICE (V.O.) (filtered) Two guards on the east side. Move now! Alex sprints across the rooftop, water splashing with each step. Suddenly, a spotlight sweeps across the roof. Alex dives behind a chimney just in time. GUARD (shouting) There! On the roof! Gunshots ring out. Alex pulls out a grappling hook and fires it toward the next building.""", outputs=script_input ) example_btn3.click( fn=lambda: "", outputs=script_input ) gr.Markdown(""" ### 🔧 Setup Instructions To enable AI image generation, you need a Hugging Face API token: 1. Get a free token at [huggingface.co/settings/tokens](https://huggingface.co/settings/tokens) 2. Set it as an environment variable: `HUGGING_FACE_API_TOKEN` 3. Restart the application **Note:** Without an API token, placeholder images will be shown instead. """) if __name__ == "__main__": demo.launch()