#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Prompt Compiler for Tran_Empire AI Cinema Production Extracts 10-second shots from screenplay markdown files and compiles them into ready-to-use AI generation prompts (Keyframes & Motion prompts). """ import os import re import json import argparse from pathlib import Path def load_json(file_path): if os.path.exists(file_path): with open(file_path, "r", encoding="utf-8") as f: return json.load(f) return {} def compile_screenplay_prompts(screenplay_path, rules_path, characters_path, output_json_path=None): screenplay_file = Path(screenplay_path) if not screenplay_file.exists(): print(f"Error: Screenplay file {screenplay_path} not found.") return [] rules = load_json(rules_path) characters = load_json(characters_path).get("characters", {}) with open(screenplay_file, "r", encoding="utf-8") as f: text = f.read() # Pattern to capture shot blocks with dynamic duration (2s - 10s) # e.g.: ##### Shot 01: `ep01_scene01_shot01` (10s) or (3s - REACTION CUT) shot_pattern = re.compile( r"#####\s+Shot\s+(\d+):\s*`([^`]+)`(?:\s*\(([^)]*)\))?\s*\n" r"(.*?)(?=(?:#####\s+Shot|\n####\s+CẢNH|\n##\s+HỒI|\Z))", re.DOTALL | re.IGNORECASE ) shots_compiled = [] style_suffix = ", ".join(rules.get("master_style_tokens", [ "cinematic historical epic", "13th century Dai Viet Tran Dynasty aesthetic", "authentic Vietnamese archaeological fidelity", "chiaroscuro lighting", "8k resolution master shot" ])) negative_prompt = ", ".join(rules.get("negative_prompts", [])) for match in shot_pattern.finditer(text): shot_num = match.group(1) shot_id = match.group(2) paren_text = match.group(3) or "" shot_duration = 10 if paren_text: dur_m = re.search(r"(\d+)\s*(?:s|giây)", paren_text, re.IGNORECASE) if dur_m: shot_duration = int(dur_m.group(1)) shot_body = match.group(4).strip() # Extract Visual description (FlowKit: Bối cảnh & Ánh sáng or Thị giác) visual_match = re.search(r"-\s*\*\*(?:Bối cảnh & Ánh sáng|Thị giác)\*\*:\s*(.*?)(?=\n-\s*\*\*|\Z)", shot_body, re.DOTALL) visual_desc = visual_match.group(1).strip() if visual_match else "" # Extract Camera framing (FlowKit: Góc máy & Tiêu cự or Cỡ cảnh & Máy quay) camera_match = re.search(r"-\s*\*\*(?:Góc máy & Tiêu cự|Góc máy|Cỡ cảnh & Máy quay)\*\*:\s*(.*?)(?=\n-\s*\*\*|\Z)", shot_body, re.DOTALL) camera_desc = camera_match.group(1).strip() if camera_match else "Cinematic Medium Shot" # Extract Camera Motion (FlowKit: Chuyển động Camera) motion_match = re.search(r"-\s*\*\*Chuyển động Camera\*\*:\s*(.*?)(?=\n-\s*\*\*|\Z)", shot_body, re.DOTALL) cam_motion_desc = motion_match.group(1).strip() if motion_match else "continuous smooth cinematic motion" # Extract Character & Performance (FlowKit: Nhân vật & Diễn xuất) perf_match = re.search(r"-\s*\*\*Nhân vật & Diễn xuất.*?\*\*:\s*(.*?)(?=\n-\s*\*\*|\Z)", shot_body, re.DOTALL) perf_desc = perf_match.group(1).strip() if perf_match else "" # Extract Vocal / Dialogue / Lip Guard vocal_match = re.search(r"-\s*\*\*Thoại & Khẩu hình\*\*:\s*(.*?)(?=\n-\s*\*\*|\Z)", shot_body, re.DOTALL) if not vocal_match: vocal_match = re.search(r"\*Stem 4 \(Vocal\)\*:\s*(.*?)(?=\n\s*-|\Z)", shot_body, re.DOTALL) vocal_desc = vocal_match.group(1).strip() if vocal_match else "None" # Extract First Frame and Last Frame first_frame_m = re.search(r"-\s*\*\*First Frame\*\*:\s*(.*?)(?=\n-\s*\*\*|\Z)", shot_body, re.DOTALL) first_frame_desc = first_frame_m.group(1).strip() if first_frame_m else "" last_frame_m = re.search(r"-\s*\*\*Last Frame\*\*:\s*(.*?)(?=\n-\s*\*\*|\Z)", shot_body, re.DOTALL) last_frame_desc = last_frame_m.group(1).strip() if last_frame_m else "" # Build Midjourney / Imagen 3 Keyframe Prompt keyframe_prompt = f"{camera_desc}, {visual_desc}, {style_suffix} --ar 16:9" # Build Video Motion Prompt (Wan2.1 / LTX-Video / Muse / Kling) # AUDIO GUARD DIRECTIVE: Strictly NO BGM in shot prompts to prevent audio desynchronization across cuts. # BGM is exclusively mixed in post-production on DaVinci Resolve. action_summary = f"{perf_desc}; {visual_desc}" if perf_desc else visual_desc motion_prompt = ( f"{camera_desc}, {cam_motion_desc}, {action_summary}, " f"realistic water and fabric physics, high production value {shot_duration}s shot. " f"[AUDIO GUARD: No background music, no soundtrack, ambient environment and foley only]" ) audio_negative_tokens = "background music, musical soundtrack, singing, orchestral music, disco, electronic beat, jarring music cuts" final_negative = f"{negative_prompt}, {audio_negative_tokens}" if negative_prompt else audio_negative_tokens shot_item = { "shot_id": shot_id, "shot_number": int(shot_num), "camera_framing": camera_desc, "camera_motion": cam_motion_desc, "visual_action": visual_desc, "character_performance": perf_desc, "dialogue_vocal": vocal_desc, "first_frame": first_frame_desc, "last_frame": last_frame_desc, "keyframe_ai_prompt": keyframe_prompt, "motion_video_prompt": motion_prompt, "audio_guard": "STRICT_NO_BGM_POST_PRODUCTION_ONLY", "negative_prompt": final_negative, "duration_sec": shot_duration } shots_compiled.append(shot_item) if output_json_path: out_p = Path(output_json_path) out_p.parent.mkdir(parents=True, exist_ok=True) with open(out_p, "w", encoding="utf-8") as f: json.dump({ "screenplay": screenplay_file.name, "total_shots": len(shots_compiled), "total_duration_sec": sum(s["duration_sec"] for s in shots_compiled), "shots": shots_compiled }, f, ensure_ascii=False, indent=2) print(f"Compiled {len(shots_compiled)} shots to {output_json_path}") return shots_compiled def main(): parser = argparse.ArgumentParser(description="Compile screenplay to AI generation prompts") parser.add_argument("screenplay", help="Path to screenplay markdown file") parser.add_argument("--rules", default=None, help="Path to master prompt rules") parser.add_argument("--chars", default=None, help="Path to character prompts") parser.add_argument("--output", help="Output JSON path") args = parser.parse_args() rules_path = args.rules if not rules_path: for candidate in ["02_AI_Prompts/master_prompt_rules.json", "Tran_Empire/02_AI_Prompts/master_prompt_rules.json"]: if os.path.exists(candidate): rules_path = candidate break chars_path = args.chars if not chars_path: for candidate in ["02_AI_Prompts/characters_consistent_prompts.json", "Tran_Empire/02_AI_Prompts/characters_consistent_prompts.json"]: if os.path.exists(candidate): chars_path = candidate break compile_screenplay_prompts(args.screenplay, rules_path, chars_path, args.output) if __name__ == "__main__": main()