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from __future__ import annotations
import contextlib
import copy
import importlib
import inspect
import io
import json
import os
import queue
import sys
import threading
import time
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Iterator, Sequence
from PIL import Image
from shared.utils.process_locks import set_main_generation_running
from shared.utils.thread_utils import AsyncStream
_RUNTIME_LOCK = threading.RLock()
_GENERATION_LOCK = threading.RLock()
_RUNTIME: "_WanGPRuntime | None" = None
_BANNER_PRINTED = False
@dataclass(frozen=True)
class StreamMessage:
stream: str
text: str
@dataclass(frozen=True)
class ProgressUpdate:
phase: str
status: str
progress: int
current_step: int | None
total_steps: int | None
raw_phase: str | None = None
unit: str | None = None
@dataclass(frozen=True)
class PreviewUpdate:
image: Image.Image | None
phase: str
status: str
progress: int
current_step: int | None
total_steps: int | None
@dataclass(frozen=True)
class SessionEvent:
kind: str
data: Any = None
timestamp: float = field(default_factory=time.time)
@dataclass(frozen=True)
class GenerationResult:
success: bool
generated_files: list[str]
errors: list["GenerationError"]
total_tasks: int
successful_tasks: int
failed_tasks: int
@dataclass(frozen=True)
class GenerationError:
message: str
task_index: int | None = None
task_id: Any = None
stage: str | None = None
def __str__(self) -> str:
return self.message
class SessionStream:
def __init__(self) -> None:
self._queue: queue.Queue[SessionEvent | object] = queue.Queue()
self._closed = threading.Event()
self._sentinel = object()
def put(self, kind: str, data: Any = None) -> None:
if self._closed.is_set():
return
self._queue.put(SessionEvent(kind=kind, data=data))
def close(self) -> None:
if self._closed.is_set():
return
self._closed.set()
self._queue.put(self._sentinel)
def get(self, timeout: float | None = None) -> SessionEvent | None:
try:
item = self._queue.get(timeout=timeout)
except queue.Empty:
return None
if item is self._sentinel:
return None
return item
def iter(self, timeout: float | None = None) -> Iterator[SessionEvent]:
while True:
event = self.get(timeout=timeout)
if event is None:
if self._closed.is_set():
break
continue
yield event
@property
def closed(self) -> bool:
return self._closed.is_set()
class _OutputCapture(io.TextIOBase):
def __init__(
self,
stream_name: str,
emit_line,
console: io.TextIOBase | None = None,
*,
console_isatty: bool = True,
) -> None:
self._stream_name = stream_name
self._emit_line = emit_line
self._console = console
self._console_isatty = bool(console_isatty)
self._buffer = ""
def writable(self) -> bool:
return True
@property
def encoding(self) -> str:
return str(getattr(self._console, "encoding", "utf-8"))
def isatty(self) -> bool:
return self._console_isatty
def write(self, text: str) -> int:
if not text:
return 0
if self._console is not None:
self._console.write(text)
self._buffer += text
self._drain(False)
return len(text)
def flush(self) -> None:
if self._console is not None:
self._console.flush()
self._drain(True)
def _drain(self, flush_all: bool) -> None:
while True:
split_at = -1
for delimiter in ("\r", "\n"):
index = self._buffer.find(delimiter)
if index >= 0 and (split_at < 0 or index < split_at):
split_at = index
if split_at < 0:
break
line = self._buffer[:split_at]
self._buffer = self._buffer[split_at + 1 :]
if line:
self._emit_line(self._stream_name, line)
if flush_all and self._buffer:
self._emit_line(self._stream_name, self._buffer)
self._buffer = ""
@dataclass(frozen=True)
class _WanGPRuntime:
module: Any
root: Path
config_path: Path
cli_args: tuple[str, ...]
class SessionJob:
def __init__(self, session: "WanGPSession") -> None:
self._session = session
self.events = SessionStream()
self._done = threading.Event()
self._cancel_requested = threading.Event()
self._thread: threading.Thread | None = None
self._result: GenerationResult | None = None
def _bind_thread(self, thread: threading.Thread) -> None:
self._thread = thread
def _set_result(self, result: GenerationResult) -> None:
self._result = result
self._done.set()
def cancel(self) -> None:
self._cancel_requested.set()
def result(self, timeout: float | None = None) -> GenerationResult:
if not self._done.wait(timeout=timeout):
raise TimeoutError("WanGP session job timed out")
return self._result or GenerationResult(
success=False,
generated_files=[],
errors=[],
total_tasks=0,
successful_tasks=0,
failed_tasks=0,
)
def join(self, timeout: float | None = None) -> GenerationResult:
return self.result(timeout=timeout)
@property
def done(self) -> bool:
return self._done.is_set()
@property
def cancel_requested(self) -> bool:
return self._cancel_requested.is_set()
class WanGPSession:
def __init__(
self,
*,
root: str | os.PathLike[str] | None = None,
config_path: str | os.PathLike[str] | None = None,
output_dir: str | os.PathLike[str] | None = None,
callbacks: object | None = None,
cli_args: Sequence[str] = (),
console_output: bool = True,
console_isatty: bool = True,
) -> None:
self._root = Path(root or Path(__file__).resolve().parents[1]).resolve()
self._config_path = Path(config_path).resolve() if config_path is not None else (self._root / "wgp_config.json").resolve()
self._output_dir = Path(output_dir).resolve() if output_dir is not None else None
self._callbacks = callbacks
self._cli_args = tuple(str(arg) for arg in cli_args)
self._console_output = bool(console_output)
self._console_isatty = bool(console_isatty)
self._state = self._create_headless_state()
self._active_job: SessionJob | None = None
self._job_lock = threading.Lock()
self._attachment_keys: tuple[str, ...] | None = None
def ensure_ready(self) -> "WanGPSession":
self._ensure_runtime()
return self
def submit(self, source: str | os.PathLike[str] | dict[str, Any] | list[dict[str, Any]]) -> SessionJob:
tasks = self._normalize_source(source, caller_base_path=self._get_caller_base_path())
return self._submit_tasks(tasks)
def submit_task(self, settings: dict[str, Any]) -> SessionJob:
caller_base_path = self._get_caller_base_path()
task = self._normalize_task(settings, task_index=1)
return self._submit_tasks([self._absolutize_task_paths(task, caller_base_path)])
def submit_manifest(self, settings_list: list[dict[str, Any]]) -> SessionJob:
caller_base_path = self._get_caller_base_path()
tasks = [
self._absolutize_task_paths(self._normalize_task(settings, task_index=index + 1), caller_base_path)
for index, settings in enumerate(settings_list)
]
return self._submit_tasks(tasks)
def run(self, source: str | os.PathLike[str] | dict[str, Any] | list[dict[str, Any]]) -> GenerationResult:
return self.submit(source).result()
def run_task(self, settings: dict[str, Any]) -> GenerationResult:
return self.submit_task(settings).result()
def run_manifest(self, settings_list: list[dict[str, Any]]) -> GenerationResult:
return self.submit_manifest(settings_list).result()
def close(self) -> None:
runtime = self._ensure_runtime()
with _GENERATION_LOCK, _pushd(runtime.root):
runtime.module.release_model()
def cancel(self) -> None:
with self._job_lock:
job = self._active_job
if job is not None:
job.cancel()
@staticmethod
def _create_headless_state() -> dict[str, Any]:
return {
"gen": {
"queue": [],
"in_progress": False,
"file_list": [],
"file_settings_list": [],
"audio_file_list": [],
"audio_file_settings_list": [],
"selected": 0,
"audio_selected": 0,
"prompt_no": 0,
"prompts_max": 0,
"repeat_no": 0,
"total_generation": 1,
"window_no": 0,
"total_windows": 0,
"progress_status": "",
"process_status": "process:main",
},
"loras": [],
}
def _submit_tasks(self, tasks: list[dict[str, Any]]) -> SessionJob:
with self._job_lock:
if self._active_job is not None and not self._active_job.done:
raise RuntimeError("WanGP session already has a generation in progress")
job = SessionJob(self)
thread = threading.Thread(
target=self._run_job,
args=(job, copy.deepcopy(tasks)),
daemon=True,
name="wangp-session-job",
)
job._bind_thread(thread)
self._active_job = job
thread.start()
return job
def _run_job(self, job: SessionJob, tasks: list[dict[str, Any]]) -> None:
stream = AsyncStream()
gen = self._state["gen"]
worker_done = threading.Event()
base_file_count = len(gen["file_list"])
base_audio_count = len(gen["audio_file_list"])
total_tasks = len(tasks)
runtime: _WanGPRuntime | None = None
task_summary: dict[str, Any] = {
"errors": [],
"successful_tasks": 0,
"failed_tasks": 0,
"total_tasks": total_tasks,
}
try:
runtime = self._ensure_runtime()
with _GENERATION_LOCK, _pushd(runtime.root):
self._configure_runtime(runtime)
self._prepare_state_for_run(tasks)
job.events.put("started", {"tasks": len(tasks)})
def worker() -> None:
stdout_capture = _OutputCapture(
"stdout",
lambda stream_name, line: self._emit_stream(job, stream_name, line),
console=sys.__stdout__ if self._console_output else None,
console_isatty=self._console_isatty,
)
stderr_capture = _OutputCapture(
"stderr",
lambda stream_name, line: self._emit_stream(job, stream_name, line),
console=sys.__stderr__ if self._console_output else None,
console_isatty=self._console_isatty,
)
try:
with contextlib.redirect_stdout(stdout_capture), contextlib.redirect_stderr(stderr_capture):
self._run_tasks_worker(runtime.module, tasks, stream, job, task_summary)
except BaseException as exc:
failure = self._make_generation_error(
exc,
task_index=None,
task_id=None,
stage="runtime",
)
task_summary["errors"].append(failure)
stream.output_queue.push("error", failure)
finally:
stdout_capture.flush()
stderr_capture.flush()
stream.output_queue.push("worker_exit", None)
worker_done.set()
worker_thread = threading.Thread(target=worker, daemon=True, name="wangp-session-worker")
worker_thread.start()
while True:
if job.cancel_requested:
self._request_cancel_unlocked(runtime.module)
item = stream.output_queue.pop()
if item is None:
if worker_done.is_set() and not worker_thread.is_alive():
break
time.sleep(0.01)
continue
command, data = item
if command == "worker_exit":
break
self._handle_command(job, runtime.module, tasks, command, data)
worker_thread.join(timeout=0.1)
outputs = self._collect_outputs(base_file_count, base_audio_count)
if job.cancel_requested and not task_summary["errors"]:
task_summary["errors"].append(
GenerationError(message="Generation was cancelled", stage="cancelled")
)
task_summary["failed_tasks"] = max(task_summary["failed_tasks"], 1)
result = GenerationResult(
success=not task_summary["errors"],
generated_files=outputs,
errors=list(task_summary["errors"]),
total_tasks=task_summary["total_tasks"],
successful_tasks=task_summary["successful_tasks"],
failed_tasks=task_summary["failed_tasks"],
)
job.events.put("completed", result)
self._emit_callback("on_complete", result)
job._set_result(result)
except BaseException as exc:
failure = self._make_generation_error(exc, task_index=None, task_id=None, stage="runtime")
result = GenerationResult(
success=False,
generated_files=[],
errors=[failure],
total_tasks=total_tasks,
successful_tasks=task_summary["successful_tasks"],
failed_tasks=max(task_summary["failed_tasks"], 1 if total_tasks > 0 else 0),
)
job.events.put("error", failure)
self._emit_callback("on_error", failure)
job.events.put("completed", result)
self._emit_callback("on_complete", result)
job._set_result(result)
finally:
job.events.close()
if runtime is not None:
self._reset_state_after_run()
with self._job_lock:
if self._active_job is job:
self._active_job = None
def _run_tasks_worker(
self,
wgp,
tasks: list[dict[str, Any]],
stream: AsyncStream,
job: SessionJob,
task_summary: dict[str, Any],
) -> None:
expected_args = set(inspect.signature(wgp.generate_video).parameters.keys())
total_tasks = len(tasks)
for task_index, task in enumerate(tasks, start=1):
if job.cancel_requested:
break
self._state["gen"]["prompt_no"] = task_index
self._state["gen"]["prompts_max"] = total_tasks
self._state["gen"]["queue"] = tasks
task_id = task.get("id")
task_errors: list[GenerationError] = []
def send_cmd(command: str, data: Any = None) -> None:
if command == "error":
failure = self._make_generation_error(
data,
task_index=task_index,
task_id=task_id,
stage="generation",
)
task_errors.append(failure)
stream.output_queue.push("error", failure)
return
stream.output_queue.push(command, data)
validated_settings, validation_error = wgp.validate_task(task, self._state)
if validated_settings is None:
failure = GenerationError(
message=validation_error or f"Task {task_index} failed validation",
task_index=task_index,
task_id=task_id,
stage="validation",
)
task_summary["errors"].append(failure)
task_summary["failed_tasks"] += 1
stream.output_queue.push("error", failure)
continue
task_settings = validated_settings.copy()
task_settings["state"] = self._state
filtered_params = {key: value for key, value in task_settings.items() if key in expected_args}
plugin_data = task.get("plugin_data", {})
try:
success = wgp.generate_video(task, send_cmd, plugin_data=plugin_data, **filtered_params)
except BaseException as exc:
if not task_errors:
task_errors.append(
self._make_generation_error(
exc,
task_index=task_index,
task_id=task_id,
stage="generation",
)
)
stream.output_queue.push("error", task_errors[-1])
success = False
if self._state["gen"].get("abort", False) or job.cancel_requested:
task_errors.append(
GenerationError(
message="Generation was cancelled",
task_index=task_index,
task_id=task_id,
stage="cancelled",
)
)
stream.output_queue.push("error", task_errors[-1])
task_summary["errors"].extend(task_errors)
task_summary["failed_tasks"] += 1
break
if task_errors:
task_summary["errors"].extend(task_errors)
task_summary["failed_tasks"] += 1
continue
if not success:
failure = GenerationError(
message=f"Task {task_index} did not complete successfully",
task_index=task_index,
task_id=task_id,
stage="generation",
)
task_summary["errors"].append(failure)
task_summary["failed_tasks"] += 1
stream.output_queue.push("error", failure)
continue
task_summary["successful_tasks"] += 1
def _handle_command(self, job: SessionJob, wgp, tasks: list[dict[str, Any]], command: str, data: Any) -> None:
if command == "progress":
progress = self._build_progress_update(data)
job.events.put("progress", progress)
self._emit_callback("on_progress", progress)
return
if command == "preview":
preview = self._build_preview_update(wgp, tasks, data)
if preview is not None:
job.events.put("preview", preview)
self._emit_callback("on_preview", preview)
return
if command == "status":
text = str(data or "")
job.events.put("status", text)
self._emit_callback("on_status", text)
return
if command == "info":
text = str(data or "")
job.events.put("info", text)
self._emit_callback("on_info", text)
return
if command == "output":
job.events.put("output", data)
self._emit_callback("on_output", data)
return
if command == "refresh_models":
job.events.put("refresh_models", data)
return
if command == "error":
error = data if isinstance(data, GenerationError) else self._make_generation_error(data)
job.events.put("error", error)
self._emit_callback("on_error", error)
return
job.events.put(command, data)
def _build_progress_update(self, data: Any) -> ProgressUpdate:
current_step: int | None = None
total_steps: int | None = None
status = ""
unit: str | None = None
if isinstance(data, list) and data:
head = data[0]
if isinstance(head, tuple) and len(head) == 2:
current_step = int(head[0])
total_steps = int(head[1])
status = str(data[1] if len(data) > 1 else "")
if len(data) > 3:
unit = str(data[3])
else:
status = str(data[1] if len(data) > 1 else head)
else:
status = str(data or "")
raw_phase = None
progress_phase = self._state["gen"].get("progress_phase")
if isinstance(progress_phase, tuple) and progress_phase:
raw_phase = str(progress_phase[0] or "")
phase = self._normalize_phase(raw_phase or status)
progress = self._estimate_progress(phase, current_step, total_steps)
return ProgressUpdate(
phase=phase,
status=status,
progress=progress,
current_step=current_step,
total_steps=total_steps,
raw_phase=raw_phase,
unit=unit,
)
def _build_preview_update(self, wgp, tasks: list[dict[str, Any]], payload: Any) -> PreviewUpdate | None:
progress = self._build_progress_update([0, self._state["gen"].get("progress_status", "")])
model_type = ""
queue_tasks = self._state["gen"].get("queue") or tasks
if queue_tasks:
model_type = str(self._get_task_settings(queue_tasks[0]).get("model_type", ""))
image = wgp.generate_preview(model_type, payload) if model_type else None
return PreviewUpdate(
image=image,
phase=progress.phase,
status=progress.status,
progress=progress.progress,
current_step=progress.current_step,
total_steps=progress.total_steps,
)
def _emit_stream(self, job: SessionJob, stream_name: str, line: str) -> None:
message = StreamMessage(stream=stream_name, text=line)
job.events.put("stream", message)
self._emit_callback("on_stream", message)
def _emit_callback(self, method_name: str, payload: Any) -> None:
callback = self._callbacks
if callback is None:
return
method = getattr(callback, method_name, None)
if callable(method):
method(payload)
on_event = getattr(callback, "on_event", None)
if callable(on_event):
on_event(SessionEvent(kind=method_name.removeprefix("on_"), data=payload))
def _configure_runtime(self, runtime: _WanGPRuntime) -> None:
runtime.module.server_config["notification_sound_enabled"] = 0
if self._output_dir is not None:
self._output_dir.mkdir(parents=True, exist_ok=True)
runtime.module.server_config["save_path"] = str(self._output_dir)
runtime.module.server_config["image_save_path"] = str(self._output_dir)
runtime.module.server_config["audio_save_path"] = str(self._output_dir)
runtime.module.save_path = str(self._output_dir)
runtime.module.image_save_path = str(self._output_dir)
runtime.module.audio_save_path = str(self._output_dir)
for output_path in (
runtime.module.save_path,
runtime.module.image_save_path,
runtime.module.audio_save_path,
):
Path(output_path).mkdir(parents=True, exist_ok=True)
def _prepare_state_for_run(self, tasks: list[dict[str, Any]]) -> None:
gen = self._state["gen"]
gen["queue"] = tasks
set_main_generation_running(self._state, True)
gen["process_status"] = "process:main"
gen["progress_status"] = ""
gen["progress_phase"] = ("", -1)
gen["abort"] = False
gen["early_stop"] = False
gen["early_stop_forwarded"] = False
gen["preview"] = None
gen["status"] = "Generating..."
gen["in_progress"] = True
self._ensure_runtime().module.gen_in_progress = True
def _reset_state_after_run(self) -> None:
gen = self._state["gen"]
gen["queue"] = []
set_main_generation_running(self._state, False)
gen["process_status"] = "process:main"
gen["progress_status"] = ""
gen["progress_phase"] = ("", -1)
gen["abort"] = False
gen["early_stop"] = False
gen["early_stop_forwarded"] = False
gen.pop("in_progress", None)
self._ensure_runtime().module.gen_in_progress = False
def _collect_outputs(self, base_file_count: int, base_audio_count: int) -> list[str]:
gen = self._state["gen"]
files = gen["file_list"][base_file_count:]
audio_files = gen["audio_file_list"][base_audio_count:]
return [str(Path(path).resolve()) for path in [*files, *audio_files]]
def _request_cancel_unlocked(self, wgp) -> None:
gen = self._state["gen"]
gen["resume"] = True
gen["abort"] = True
if wgp.wan_model is not None:
wgp.wan_model._interrupt = True
def _normalize_source(
self,
source: str | os.PathLike[str] | dict[str, Any] | list[dict[str, Any]],
*,
caller_base_path: Path,
) -> list[dict[str, Any]]:
if isinstance(source, (str, os.PathLike)):
return self._load_tasks_from_path(self._resolve_source_path(Path(source), caller_base_path), caller_base_path)
if isinstance(source, list):
return [
self._absolutize_task_paths(self._normalize_task(task, task_index=index + 1), caller_base_path)
for index, task in enumerate(source)
]
if isinstance(source, dict):
if isinstance(source.get("tasks"), list):
tasks = source["tasks"]
return [
self._absolutize_task_paths(self._normalize_task(task, task_index=index + 1), caller_base_path)
for index, task in enumerate(tasks)
]
return [self._absolutize_task_paths(self._normalize_task(source, task_index=1), caller_base_path)]
raise TypeError("WanGP session source must be a path, a settings dict, or a manifest list")
def _normalize_task(self, task: dict[str, Any], *, task_index: int) -> dict[str, Any]:
if not isinstance(task, dict):
raise TypeError(f"Task {task_index} must be a dictionary")
normalized = copy.deepcopy(task)
if "settings" in normalized and "params" not in normalized:
normalized["params"] = normalized.pop("settings")
if "params" not in normalized:
normalized = {"id": task_index, "params": normalized, "plugin_data": {}}
normalized.setdefault("id", task_index)
normalized.setdefault("plugin_data", {})
normalized.setdefault("params", {})
settings = normalized["params"]
if isinstance(settings, dict):
self._normalize_settings_values(settings)
normalized.setdefault("prompt", settings.get("prompt", ""))
normalized.setdefault("length", settings.get("video_length"))
normalized.setdefault("steps", settings.get("num_inference_steps"))
normalized.setdefault("repeats", settings.get("repeat_generation", 1))
return normalized
@staticmethod
def _normalize_settings_values(settings: dict[str, Any]) -> None:
force_fps = settings.get("force_fps")
if isinstance(force_fps, (int, float)) and not isinstance(force_fps, bool):
if isinstance(force_fps, float) and not force_fps.is_integer():
settings["force_fps"] = str(force_fps)
else:
settings["force_fps"] = str(int(force_fps))
@staticmethod
def _get_task_settings(task: dict[str, Any]) -> dict[str, Any]:
settings = task.get("params")
if isinstance(settings, dict):
return settings
settings = task.get("settings")
if isinstance(settings, dict):
return settings
return {}
def _load_tasks_from_path(self, path: Path, caller_base_path: Path) -> list[dict[str, Any]]:
runtime = self._ensure_runtime()
if not path.exists():
raise FileNotFoundError(path)
if path.suffix.lower() == ".json":
return self._load_settings_json(path, caller_base_path)
with _pushd(runtime.root):
tasks, error = runtime.module._parse_queue_zip(str(path), self._state)
if error:
raise RuntimeError(error)
return [self._normalize_task(task, task_index=index + 1) for index, task in enumerate(tasks)]
def _load_settings_json(self, path: Path, caller_base_path: Path) -> list[dict[str, Any]]:
with path.open("r", encoding="utf-8") as handle:
payload = json.load(handle)
if isinstance(payload, list):
raw_tasks = payload
elif isinstance(payload, dict) and isinstance(payload.get("tasks"), list):
raw_tasks = payload["tasks"]
elif isinstance(payload, dict):
raw_tasks = [payload]
else:
raise RuntimeError("Settings file must contain a JSON object or a list of tasks")
tasks = [self._normalize_task(task, task_index=index + 1) for index, task in enumerate(raw_tasks)]
return [self._absolutize_task_paths(task, caller_base_path) for task in tasks]
@staticmethod
def _get_caller_base_path() -> Path:
return Path.cwd().resolve()
@staticmethod
def _resolve_source_path(path: Path, caller_base_path: Path) -> Path:
if path.is_absolute():
return path.resolve()
return (caller_base_path / path).resolve()
def _absolutize_task_paths(self, task: dict[str, Any], caller_base_path: Path) -> dict[str, Any]:
normalized = copy.deepcopy(task)
settings = normalized.get("params")
if not isinstance(settings, dict):
return normalized
for key in self._get_attachment_keys():
if key not in settings:
continue
settings[key] = self._absolutize_setting_path(settings[key], caller_base_path)
return normalized
def _get_attachment_keys(self) -> tuple[str, ...]:
if self._attachment_keys is None:
runtime = self._ensure_runtime()
keys = getattr(runtime.module, "ATTACHMENT_KEYS", ())
self._attachment_keys = tuple(str(key) for key in keys)
return self._attachment_keys
def _absolutize_setting_path(self, value: Any, caller_base_path: Path) -> Any:
if isinstance(value, list):
return [self._absolutize_setting_path(item, caller_base_path) for item in value]
if isinstance(value, os.PathLike):
value = os.fspath(value)
if not isinstance(value, str) or not value.strip():
return value
path = Path(value)
if path.is_absolute():
return str(path.resolve())
return str((caller_base_path / path).resolve())
@staticmethod
def _make_generation_error(
error: Any,
*,
task_index: int | None = None,
task_id: Any = None,
stage: str | None = None,
) -> GenerationError:
if isinstance(error, GenerationError):
return error
if isinstance(error, BaseException):
message = str(error) or error.__class__.__name__
else:
message = str(error)
return GenerationError(message=message, task_index=task_index, task_id=task_id, stage=stage)
def _ensure_runtime(self) -> _WanGPRuntime:
global _RUNTIME
with _RUNTIME_LOCK:
if _RUNTIME is not None:
if _RUNTIME.root != self._root or _RUNTIME.config_path != self._config_path or _RUNTIME.cli_args != self._cli_args:
raise RuntimeError("WanGP runtime already loaded with different root/config/cli args")
return _RUNTIME
argv = ["wgp.py", *self._cli_args]
default_config_path = (self._root / "wgp_config.json").resolve()
if self._config_path.name != "wgp_config.json":
raise ValueError("config_path must point to a file named 'wgp_config.json'")
if self._config_path != default_config_path:
self._config_path.parent.mkdir(parents=True, exist_ok=True)
if "--config" not in argv:
argv.extend(["--config", str(self._config_path.parent)])
if str(self._root) not in sys.path:
sys.path.insert(0, str(self._root))
with _pushd(self._root), _temporary_argv(argv):
module = importlib.import_module("wgp")
module_root = Path(module.__file__).resolve().parent
if module_root != self._root:
raise RuntimeError(f"WanGP module already loaded from {module_root}, expected {self._root}")
if not hasattr(module, "app"):
module.app = module.WAN2GPApplication()
module.download_ffmpeg()
_RUNTIME = _WanGPRuntime(
module=module,
root=self._root,
config_path=self._config_path,
cli_args=self._cli_args,
)
_print_banner_once(module)
return _RUNTIME
@staticmethod
def _normalize_phase(text: str | None) -> str:
lowered = str(text or "").lower()
if "denoising first pass" in lowered or "denoising 1st pass" in lowered:
return "inference_stage_1"
if "denoising second pass" in lowered or "denoising 2nd pass" in lowered:
return "inference_stage_2"
if "denoising third pass" in lowered or "denoising 3rd pass" in lowered:
return "inference_stage_3"
if "loading model" in lowered or lowered.startswith("loading"):
return "loading_model"
if "enhancing prompt" in lowered or "encoding prompt" in lowered or "encoding" in lowered:
return "encoding_text"
if "vae decoding" in lowered or "decoding" in lowered:
return "decoding"
if "saved" in lowered or "completed" in lowered or "output" in lowered:
return "downloading_output"
if "cancel" in lowered or "abort" in lowered:
return "cancelled"
return "inference"
@staticmethod
def _estimate_progress(phase: str, current_step: int | None, total_steps: int | None) -> int:
if total_steps is None or total_steps <= 0 or current_step is None:
if phase == "loading_model":
return 10
if phase == "encoding_text":
return 18
if phase == "inference_stage_1":
return 25
if phase == "inference_stage_2":
return 70
if phase == "inference_stage_3":
return 80
if phase == "decoding":
return 90
if phase == "downloading_output":
return 95
if phase == "cancelled":
return 0
return 15
ratio = max(0.0, min(1.0, current_step / total_steps))
if phase == "loading_model":
return min(15, 5 + int(ratio * 10))
if phase == "encoding_text":
return min(22, 12 + int(ratio * 10))
if phase == "inference_stage_1":
return min(68, 20 + int(ratio * 48))
if phase == "inference_stage_2":
return min(88, 68 + int(ratio * 20))
if phase == "inference_stage_3":
return min(89, 80 + int(ratio * 9))
if phase == "decoding":
return min(95, 85 + int(ratio * 10))
if phase == "downloading_output":
return min(98, 92 + int(ratio * 6))
if phase == "cancelled":
return 0
return min(90, 20 + int(ratio * 65))
def init(
*,
root: str | os.PathLike[str] | None = None,
config_path: str | os.PathLike[str] | None = None,
output_dir: str | os.PathLike[str] | None = None,
callbacks: object | None = None,
cli_args: Sequence[str] = (),
console_output: bool = True,
) -> WanGPSession:
"""Create and eagerly initialize a reusable WanGP session."""
return WanGPSession(
root=root,
config_path=config_path,
output_dir=output_dir,
callbacks=callbacks,
cli_args=cli_args,
console_output=console_output,
).ensure_ready()
@contextlib.contextmanager
def _pushd(path: Path) -> Iterator[None]:
previous = Path.cwd()
os.chdir(path)
try:
yield
finally:
os.chdir(previous)
@contextlib.contextmanager
def _temporary_argv(argv: Sequence[str]) -> Iterator[None]:
previous = list(sys.argv)
sys.argv = list(argv)
try:
yield
finally:
sys.argv = previous
def _print_banner_once(module) -> None:
global _BANNER_PRINTED
if _BANNER_PRINTED:
return
_BANNER_PRINTED = True
banner = f"Powered by WanGP v{module.WanGP_version} - a DeepBeepMeep Production\n"
console = sys.__stdout__ if sys.__stdout__ is not None else sys.stdout
if console is not None:
console.write(banner)
console.flush()
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