LivePortrait
talking-head
avatar
real-time
conversational-ai
4d-avatar
eden-protocol
lip-sync
tts
asr
Instructions to use AIBRUH/eden-os with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LivePortrait
How to use AIBRUH/eden-os with LivePortrait:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
| """ | |
| EDEN OS — Entry Point | |
| Boots the full operating system and serves: | |
| - EDEN Studio frontend at / | |
| - EDEN OS API at /api/v1/ | |
| - WebSocket stream at /api/v1/sessions/{id}/stream | |
| Deploy to HuggingFace Spaces as Docker SDK. | |
| Space ID: AIBRUH/eden-os | |
| """ | |
| import os | |
| import sys | |
| import time | |
| from pathlib import Path | |
| import yaml | |
| import uvicorn | |
| from loguru import logger | |
| # Configure loguru | |
| logger.remove() | |
| logger.add( | |
| sys.stderr, | |
| format="<green>{time:HH:mm:ss}</green> | <level>{level: <8}</level> | <cyan>{name}</cyan> — <level>{message}</level>", | |
| level=os.getenv("EDEN_LOG_LEVEL", "INFO"), | |
| ) | |
| def detect_hardware() -> dict: | |
| """Auto-detect GPU hardware and select profile.""" | |
| try: | |
| import torch | |
| if torch.cuda.is_available(): | |
| gpu_name = torch.cuda.get_device_name(0) | |
| vram_bytes = torch.cuda.get_device_properties(0).total_mem | |
| vram_gb = vram_bytes / (1024 ** 3) | |
| if "H100" in gpu_name or "A100" in gpu_name: | |
| profile = "h100_cinematic" | |
| elif "4090" in gpu_name: | |
| profile = "rtx4090_production" | |
| elif "3090" in gpu_name or "3080" in gpu_name: | |
| profile = "rtx3090_standard" | |
| elif "L4" in gpu_name or "T4" in gpu_name: | |
| profile = "l4_cloud" | |
| else: | |
| profile = "l4_cloud" # default GPU profile | |
| return { | |
| "gpu": gpu_name, | |
| "vram_gb": round(vram_gb, 1), | |
| "gpu_available": True, | |
| "profile": profile, | |
| } | |
| except Exception: | |
| pass | |
| return { | |
| "gpu": "none", | |
| "vram_gb": 0, | |
| "gpu_available": False, | |
| "profile": "cpu_edge", | |
| } | |
| def load_config(hardware_profile: str = "auto", models_cache: str = "models_cache") -> dict: | |
| """Load and merge configuration.""" | |
| config_dir = Path(__file__).parent / "config" | |
| # Load default config | |
| default_path = config_dir / "default.yaml" | |
| if default_path.exists(): | |
| with open(default_path) as f: | |
| config = yaml.safe_load(f) | |
| else: | |
| config = {} | |
| # Load hardware profile | |
| if hardware_profile != "auto": | |
| profile_path = config_dir / "hardware_profiles" / f"{hardware_profile}.yaml" | |
| if profile_path.exists(): | |
| with open(profile_path) as f: | |
| profile = yaml.safe_load(f) | |
| # Merge profile into config (profile overrides defaults) | |
| _deep_merge(config, profile) | |
| config["models_cache"] = models_cache | |
| config["hardware_profile"] = hardware_profile | |
| return config | |
| def _deep_merge(base: dict, override: dict) -> dict: | |
| """Deep merge override into base.""" | |
| for key, value in override.items(): | |
| if key in base and isinstance(base[key], dict) and isinstance(value, dict): | |
| _deep_merge(base[key], value) | |
| else: | |
| base[key] = value | |
| return base | |
| def boot(): | |
| """Boot EDEN OS.""" | |
| start_time = time.monotonic() | |
| logger.info("=" * 55) | |
| logger.info(" EDEN OS v1.0 — BOOTING") | |
| logger.info("=" * 55) | |
| # Step 1: Detect hardware | |
| hw = detect_hardware() | |
| hardware_profile = os.getenv("EDEN_HARDWARE_PROFILE", "auto") | |
| if hardware_profile == "auto": | |
| hardware_profile = hw["profile"] | |
| logger.info(f"Hardware: {hw['gpu']} — Profile: {hardware_profile}") | |
| # Step 2: Load configuration | |
| models_cache = os.getenv("EDEN_MODELS_CACHE", "models_cache") | |
| config = load_config(hardware_profile, models_cache) | |
| # Step 3: Create FastAPI app | |
| from eden_os.gateway import create_app | |
| host = os.getenv("EDEN_HOST", "0.0.0.0") | |
| port = int(os.getenv("EDEN_PORT", "7860")) | |
| app = create_app( | |
| host=host, | |
| port=port, | |
| hardware_profile=hardware_profile, | |
| models_cache=models_cache, | |
| ) | |
| # Store config and hardware info on app state | |
| app.state.config = config | |
| app.state.hardware = hw | |
| boot_time = time.monotonic() - start_time | |
| logger.info("=" * 55) | |
| logger.info(f" EDEN OS v1.0 — LIVE") | |
| logger.info(f" URL: http://{host}:{port}") | |
| logger.info(f" API: http://{host}:{port}/api/v1/docs") | |
| logger.info(f" Hardware: {hw['gpu']} — Profile: {hardware_profile}") | |
| logger.info(f" Eden Protocol: ACTIVE — Threshold: 0.3") | |
| logger.info(f" Boot time: {boot_time:.1f}s") | |
| logger.info(f" OWN THE SCIENCE.") | |
| logger.info("=" * 55) | |
| return app, host, port | |
| # Create app at module level for uvicorn import | |
| app, _host, _port = boot() | |
| if __name__ == "__main__": | |
| uvicorn.run( | |
| app, | |
| host=_host, | |
| port=_port, | |
| ws_max_size=16 * 1024 * 1024, | |
| log_level="info", | |
| ) | |