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"""
scripts/utils.py
Utility functions used across the DarkMedia‑X dashboard server.
All helpers are pure, type‑annotated and focus on a single task,
making the codebase easier to test and maintain.
"""
import json
import os
import re
import subprocess
import sys
import time
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple
import psutil
# ----------------------------------------------------------------------
# JSON helpers
# ----------------------------------------------------------------------
def load_json(file_path: Path) -> Dict[str, Any]:
"""Load a JSON file and return its content as a dict."""
with file_path.open("r", encoding="utf-8") as f:
return json.load(f)
def write_json(file_path: Path, data: Dict[str, Any]) -> None:
"""Write a dict to a JSON file with UTF‑8 encoding."""
with file_path.open("w", encoding="utf-8") as f:
json.dump(data, f, ensure_ascii=False, indent=2)
# ----------------------------------------------------------------------
# Process helpers
# ----------------------------------------------------------------------
def is_process_running(command_substring: str) -> bool:
"""
Return True if any running process contains ``command_substring`` in its
name or full command line (case‑insensitive).
"""
for proc in psutil.process_iter(["name", "cmdline"]):
try:
name = proc.info["name"] or ""
cmdline = " ".join(proc.info["cmdline"] or [])
if command_substring.lower() in name.lower() or command_substring.lower() in cmdline.lower():
return True
except (psutil.NoSuchProcess, psutil.AccessDenied):
continue
return False
def start_detached_process(
executable: str,
args: List[str],
cwd: Path,
creationflags: int = 0,
) -> subprocess.Popen:
"""
Launch a detached subprocess (cross‑platform). Returns the Popen object.
"""
kwargs: Dict[str, Any] = {"cwd": str(cwd), "close_fds": True}
if sys.platform == "win32":
kwargs["creationflags"] = creationflags
return subprocess.Popen([executable] + args, **kwargs)
# ----------------------------------------------------------------------
# GPU statistics
# ----------------------------------------------------------------------
def get_gpu_stats() -> Optional[Dict[str, str]]:
"""Query nvidia‑smi and return a dict with load, temperature and VRAM usage."""
try:
cmd = (
"nvidia-smi --query-gpu=utilization.gpu,temperature.gpu,"
"memory.used,memory.total --format=csv,noheader,nounits"
)
kwargs: Dict[str, Any] = {"shell": True}
if sys.platform == "win32":
kwargs["creationflags"] = 0x08000000
raw = subprocess.check_output(cmd, **kwargs).decode("utf-8").strip()
if raw:
load, temp, used, total = [p.strip() for p in raw.split(",")]
return {
"load": f"{load}%",
"temp": f"{temp}°C",
"vram_used": f"{round(int(used) / 1024, 1)} GB",
"vram_total": f"{round(int(total) / 1024, 1)} GB",
}
except Exception as exc:
print(f"[GPU Stats] {exc}")
return None
# ----------------------------------------------------------------------
# File‑system helpers
# ----------------------------------------------------------------------
def ensure_directory(path: Path) -> None:
"""Create ``path`` if it does not exist."""
path.mkdir(parents=True, exist_ok=True)
def count_scenes(file_path: Path) -> int:
"""
Count the number of scenes in a markdown file by looking for '## Scene' or '## Scène'.
"""
if not file_path.exists():
return 0
try:
content = file_path.read_text(encoding="utf-8")
# Matches '## Scene X' or '## Scène X' at the beginning of any line
matches = re.findall(r"^##\s*(?:Scene|Scène)\s*\d+", content, flags=re.MULTILINE | re.IGNORECASE)
return len(matches)
except Exception:
return 0
def list_markdown_stories(root: Path) -> List[Dict[str, Any]]:
"""
Scan ``root`` for markdown story files and return a list of dictionaries
containing id, title, relative path, category and processed flag.
"""
stories: List[Dict[str, Any]] = []
if not root.exists():
return stories
for dirpath, _, filenames in os.walk(str(root)):
for filename in filenames:
if not filename.endswith(".md") or filename.startswith("README") or filename == "music_prompt.md":
continue
file_path = Path(dirpath) / filename
rel_path = file_path.relative_to(root)
story_id = str(rel_path.parent).replace("\\", "/")
title = filename.replace(".md", "").replace("_", " ").strip()
if title.lower() in {"story", "index", "readme"}:
title = story_id.replace("_", " ").strip()
story_dir = file_path.parent
image_dir = story_dir / "assets" / "images"
if not image_dir.exists():
image_dir = story_dir / "images"
image_count = 0
if image_dir.exists() and image_dir.is_dir():
image_count = len([f for f in os.listdir(str(image_dir)) if f.lower().endswith(('.png', '.jpg', '.jpeg'))])
total_scenes = count_scenes(file_path)
if total_scenes == 0: total_scenes = 10 # Fallback
processed = (story_dir / "final_video.mp4").exists() or (
story_dir / f"TT_{story_id.replace(' ', '_').replace('/', '_')}_final.mp4"
).exists()
stories.append(
{
"id": story_id,
"title": title,
"path": str(rel_path).replace("\\", "/"),
"category": file_path.parent.parent.name
if file_path.parent.parent != root
else "General",
"processed": processed,
"image_count": image_count,
"total_scenes": total_scenes,
"ready": image_count >= total_scenes
}
)
return sorted(stories, key=lambda s: s["title"])
def list_videos(videos_dir: Path) -> List[Dict[str, Any]]:
"""Return a list of video metadata dictionaries from ``videos_dir``."""
videos: List[Dict[str, Any]] = []
if not videos_dir.exists():
return videos
for dirpath, _, filenames in os.walk(str(videos_dir)):
for filename in filenames:
if filename.endswith(".mp4") and "_published" not in dirpath:
file_path = Path(dirpath) / filename
rel_path = file_path.relative_to(videos_dir)
videos.append(
{
"title": filename.replace(".mp4", "").replace("_", " "),
"filename": filename,
"path": str(rel_path),
"story": file_path.parent.name.replace("_", " "),
"timestamp": file_path.stat().st_mtime,
}
)
return sorted(videos, key=lambda v: v["timestamp"], reverse=True)
def list_generated_images(task_file: Path, stories_root: Path) -> List[Dict[str, Any]]:
"""
Return the most recent generated images (max 50) for the currently active story.
"""
images: List[Dict[str, Any]] = []
if not task_file.exists():
return images
task = load_json(task_file)
story_path = Path(task.get("story_path", ""))
story_id = task.get("story_id", "")
# Primary location: assets/images inside the explicit story_path
img_dir = story_path / "assets" / "images"
if not img_dir.is_dir() and story_id:
# Fallback: search for a folder that contains the story_id and an assets/images sub‑folder
for dirpath, _, _ in os.walk(str(stories_root)):
if story_id in dirpath and "assets" in dirpath:
candidate = Path(dirpath) / "images"
if candidate.is_dir():
img_dir = candidate
break
if img_dir.is_dir():
for img_file in sorted(img_dir.glob("*.png")) + sorted(img_dir.glob("*.jpg")):
if img_file.is_file():
images.append(
{
"path": f"/assets/images/{img_file.name}",
"filename": img_file.name,
"timestamp": img_file.stat().st_mtime,
"size": img_file.stat().st_size,
}
)
images.sort(key=lambda i: i["timestamp"], reverse=True)
return images[:50]
def list_library_images(stories_root: Path) -> List[Dict[str, Any]]:
"""
Scan all story folders for generated scene images and return a flat list
(max 200 entries) ordered by newest first.
"""
library: List[Dict[str, Any]] = []
for dirpath, _, filenames in os.walk(str(stories_root)):
if "assets" in dirpath and "images" in dirpath:
story_dir = Path(dirpath).parent.parent
story_name = story_dir.name
for filename in filenames:
if filename.endswith(".png") and filename.startswith("scene_"):
rel_path = Path(dirpath).joinpath(filename).relative_to(stories_root)
url = f"/stories/{rel_path.as_posix()}"
library.append(
{
"story": story_name,
"filename": filename,
"url": url,
"timestamp": (Path(dirpath) / filename).stat().st_mtime,
}
)
library.sort(key=lambda i: i["timestamp"], reverse=True)
return library[:200]
# ----------------------------------------------------------------------
# Audio / TTS helpers
# ----------------------------------------------------------------------
def clean_old_previews(voice_dir: Path, max_age_seconds: int = 300) -> None:
"""Remove preview files older than ``max_age_seconds``."""
for old_file in voice_dir.glob("ui_preview_*.mp3"):
if time.time() - old_file.stat().st_mtime > max_age_seconds:
try:
old_file.unlink()
except Exception:
pass
def generate_tts(
text: str,
voice: str,
rate: str,
pitch: str,
effect: str,
voice_dir: Path,
python_exe: str,
) -> Tuple[bool, str]:
"""
Run ``edge_tts`` to synthesize ``text`` and optionally post‑process with FFmpeg.
Returns ``(success, message_or_url)``.
"""
import imageio_ffmpeg
ts = int(time.time() * 1000)
raw_path = voice_dir / f"raw_{ts}.mp3"
out_path = voice_dir / f"ui_preview_{ts}.mp3"
# 1️⃣ Generate raw TTS
tts_cmd = [
python_exe,
"-m",
"edge_tts",
"--voice",
voice,
"--text",
text[:200],
"--write-media",
str(raw_path),
f"--rate={rate}",
f"--pitch={pitch}",
]
result = subprocess.run(tts_cmd, capture_output=True, text=True)
if result.returncode != 0:
return False, f"TTS engine error: {result.stderr}"
# 2️⃣ Apply optional FFmpeg filter
ffmpeg_filters = {
"demonic": "aecho=0.8:0.88:60:0.4,asetrate=44100*0.8,aresample=44100",
"ghostly": "aecho=0.8:0.88:100:0.6,asetrate=44100*1.2,aresample=44100",
"radio": "highpass=f=500,lowpass=f=3000",
"reverb": "aecho=0.8:0.88:60:0.4",
"none": "anull",
}
filter_chain = ffmpeg_filters.get(effect, "anull")
ffmpeg_exe = "ffmpeg"
try:
subprocess.run([ffmpeg_exe, "-version"], capture_output=True, check=True)
except Exception:
ffmpeg_exe = imageio_ffmpeg.get_ffmpeg_exe()
ffmpeg_cmd = [
ffmpeg_exe,
"-y",
"-i",
str(raw_path),
"-af",
filter_chain,
str(out_path),
]
ffmpeg_res = subprocess.run(ffmpeg_cmd, capture_output=True, text=True)
if ffmpeg_res.returncode != 0:
# Fallback: copy raw file unchanged
out_path.write_bytes(raw_path.read_bytes())
# Clean up temporary raw file
try:
raw_path.unlink()
except Exception:
pass
return True, f"/assets/voice_samples/{out_path.name}" |