docs/API.md

WanGP Python API

shared/api.py provides a lightweight in-process wrapper over WanGP's existing generation path.

The main goal is to let third-party code call WanGP directly, keep the last loaded model alive across requests, receive structured progress updates, and still capture the same stdout/stderr output that would normally go to the console.

Please note that use of the WanGP API is subject to the WanGP Terms and Conditions. Any product that integrates WanGP should clearly disclose that it uses WanGP in both its user interface and its documentation.

Quick Start

from pathlib import Path

from shared.api import init

session = init(
    root=Path(r"C:\WanGP"),
    cli_args=["--attention", "sdpa", "--profile", "4"],
)

settings = {
    "model_type": "ltx2_22B_distilled",
    "prompt": "Cinematic shot of a neon train entering a rainy station",
    "resolution": "1280x704",
    "num_inference_steps": 8,
    "video_length": 97,
    "duration_seconds": 4,
    "force_fps": 24,
}

job = session.submit_task(settings)

for event in job.events.iter(timeout=0.2):
    if event.kind == "progress":
        progress = event.data
        print(progress.phase, progress.progress, progress.current_step, progress.total_steps)
    elif event.kind == "preview":
        preview = event.data
        if preview.image is not None:
            preview.image.save("preview.png")
    elif event.kind == "stream":
        line = event.data
        print(f"[{line.stream}] {line.text}")

result = job.result()
if result.success:
    print(result.generated_files)
else:
    for error in result.errors:
        print(error.message)

Main Entry Points

• init(...) -> WanGPSession
  • Creates a reusable session and eagerly loads the runtime.
• WanGPSession.submit(source) -> SessionJob
  • Starts a job from a settings dict, a manifest list, or a saved .json / .zip file.
• WanGPSession.submit_task(settings) -> SessionJob
  • Preferred single-task entrypoint.
• WanGPSession.submit_manifest(settings_list) -> SessionJob
  • Batch entrypoint for multiple tasks.
• SessionJob.result() -> GenerationResult
  • Waits for completion and returns a structured result object.
• SessionJob.cancel()
  • Requests cancellation of the active generation.

init(...) Parameters

session = init(
    root=Path(r"C:\WanGP"),
    config_path=Path(r"C:\WanGP\wgp_config.json"),  # optional
    output_dir=Path(r"C:\WanGP\outputs_override"),  # optional
    callbacks=MyCallbacks(),                        # optional
    cli_args=["--attention", "sdpa"],              # optional
    console_output=True,                           # optional, default=True
    console_isatty=True,                           # optional, default=True
)

• root

  • Path to the WanGP installation folder.
  • Example: C:\WanGP

• config_path

  • Optional path to wgp_config.json.
  • If omitted, WanGP uses C:\WanGP\wgp_config.json.
  • This must point to a file named wgp_config.json.

• output_dir

  • Optional override for generated outputs.
  • If omitted, WanGP uses the output paths defined in the config file.

• callbacks

  • Optional callback object. See the callback section below.

• cli_args

  • Optional WanGP startup flags.
  • Example: ["--attention", "sdpa", "--profile", "4"]

• console_output

  • Enables or disables writing WanGP stdout/stderr to the real console.
  • Default: True
  • The stream object always receives a copy of stdout/stderr, regardless of this setting.

• console_isatty

  • Controls the TTY capability reported by the API's console capture wrapper.
  • Default: True
  • Keep this enabled if you want tqdm or other terminal-style progress output to behave like a live console stream even when WanGP is called from another Python process.

Accepted Input Shapes

Relative attachment paths are normalized to absolute paths when the job is submitted.

• For direct settings dictionaries and .json settings files, the base is the API caller's current working directory at submit time.
• For .zip queue files, WanGP keeps the queue bundle behavior and resolves bundled media from the extracted queue contents.
• A few WanGP string-like fields are normalized for convenience. For example, force_fps may be passed as 24 or "24".

Single Task

For single-task use, the intended input is the task settings dictionary itself:

settings = {
    "model_type": "qwen_image_20B",
    "prompt": "A red bicycle parked in front of a bakery",
    "resolution": "1024x1024",
    "num_inference_steps": 4,
    "image_mode": 1,
}

job = session.submit_task(settings)

Manifest

submit_manifest(...) accepts a list of settings dictionaries:

settings_list = [
    {
        "model_type": "qwen_image_20B",
        "prompt": "A quiet library at sunrise",
        "resolution": "1024x1024",
        "num_inference_steps": 4,
        "image_mode": 1,
    },
    {
        "model_type": "qwen_image_20B",
        "prompt": "A rainy alley with neon signs",
        "resolution": "1024x1024",
        "num_inference_steps": 4,
        "image_mode": 1,
    },
]

job = session.submit_manifest(settings_list)

Saved Queue / Settings File

submit(...) also accepts:

• a .json settings file path
• a .zip saved queue path

Example:

job = session.submit(Path(r"C:\WanGP\my_queue.zip"))

Streaming Events

Each job exposes job.events, a SessionStream.

The stream yields SessionEvent objects:

SessionEvent(
    kind="progress",
    data=ProgressUpdate(...),
    timestamp=1710000000.0,
)

Known kind values:

• started
  • Job accepted and session processing started.
• progress
  • Structured progress update.
• preview
  • RGB preview update.
• stream
  • One stdout/stderr line.
• status
  • WanGP status message.
• info
  • WanGP informational message.
• output
  • Raw output refresh event from WanGP.
• refresh_models
  • Raw model-refresh event from WanGP.
• completed
  • Final GenerationResult.
• error
  • One GenerationError record.

Returned Objects

GenerationResult

Returned by job.result():

GenerationResult(
    success=False,
    generated_files=[
        r"C:\WanGP\outputs\clip_001.mp4",
    ],
    errors=[
        GenerationError(
            message="Task 2 failed validation",
            task_index=2,
            task_id=2,
            stage="validation",
        ),
    ],
    total_tasks=3,
    successful_tasks=2,
    failed_tasks=1,
)

Fields:

• success: bool
  • True only when every submitted task completed without error.
• generated_files: list[str]
  • Absolute paths to every file generated by the job, including partial-success runs.
• errors: list[GenerationError]
  • Structured error records collected during the run.
• total_tasks: int
  • Number of tasks submitted in the job.
• successful_tasks: int
  • Number of tasks that completed successfully.
• failed_tasks: int
  • Number of tasks that failed or were cancelled.

job.result() does not raise generation-task failures. Instead, inspect result.success and result.errors.

GenerationError

Delivered through error events, on_error(...), and GenerationResult.errors:

GenerationError(
    message="Task 2 did not complete successfully",
    task_index=2,
    task_id=2,
    stage="generation",
)

Fields:

• message: str
  • Human-readable error message.
• task_index: int | None
  • One-based task index when the error is associated with a specific task.
• task_id: Any
  • Task identifier from the manifest when available.
• stage: str | None
  • Error stage such as validation, generation, cancelled, or runtime.

ProgressUpdate

Delivered through progress events and on_progress(...):

ProgressUpdate(
    phase="inference",
    status="Prompt 1/1 | Denoising | 7.2s",
    progress=54,
    current_step=4,
    total_steps=8,
    raw_phase="Denoising",
    unit=None,
)

Fields:

• phase: str
  • Normalized phase. Typical values:
  • loading_model
  • encoding_text
  • inference
  • decoding
  • downloading_output
  • cancelled
• status: str
  • Human-readable status string produced by WanGP.
• progress: int
  • Estimated percentage from 0 to 100.
• current_step: int | None
  • Current inference step when available.
• total_steps: int | None
  • Total inference steps when available.
• raw_phase: str | None
  • Original WanGP phase label before normalization.
• unit: str | None
  • Optional progress unit if WanGP provides one.

PreviewUpdate

Delivered through preview events and on_preview(...):

PreviewUpdate(
    image=<PIL.Image.Image image mode=RGB size=800x200>,
    phase="inference",
    status="Prompt 1/1 | Denoising",
    progress=54,
    current_step=4,
    total_steps=8,
)

Fields:

• image: PIL.Image.Image | None
  • RGB preview image generated from WanGP's latent preview payload.
• phase, status, progress, current_step, total_steps
  • Same interpretation as ProgressUpdate.

StreamMessage

Delivered through stream events and on_stream(...):

StreamMessage(
    stream="stdout",
    text="New video saved to Path: C:\\WanGP\\outputs\\clip_001.mp4",
)

Fields:

• stream: str
  • Usually stdout or stderr.
• text: str
  • One redirected line of console output.

SessionEvent

Generic event wrapper:

SessionEvent(
    kind="stream",
    data=StreamMessage(stream="stdout", text="Model loaded"),
    timestamp=1710000000.0,
)

Fields:

• kind: str
  • Event type.
• data: Any
  • Payload object for that event.
• timestamp: float
  • Event creation time.

Callback Object

You can pass a callback object to init(...) or WanGPSession(...).

Supported callback methods:

• on_progress(progress_update)

  • Called when WanGP emits a structured progress update.
  • Use this for progress bars, step counters, and status text.

• on_preview(preview_update)

  • Called when a preview image is available.
  • Use this when you want live RGB preview frames during inference.

• on_stream(stream_message)

  • Called for every redirected stdout/stderr line.
  • This is the programmatic equivalent of watching the terminal output.

• on_status(text)

  • Called for WanGP status messages.
  • Use this if you want coarse status without parsing full progress objects.

• on_info(text)

  • Called for informational messages.

• on_output(data)

  • Called for raw WanGP output refresh events.
  • This is a low-level hook and is usually not needed by third-party integrations.

• on_complete(result)

  • Called when the job finishes.
  • Receives a GenerationResult.

• on_error(error)

  • Called each time WanGP reports a task or runtime error.
  • Receives a GenerationError.

• on_event(session_event)

  • Generic catch-all event hook.
  • Called alongside the specific callback above, not instead of it.

Example:

class Callbacks:
    def on_progress(self, progress):
        print("progress:", progress.progress, progress.phase)

    def on_preview(self, preview):
        if preview.image is not None:
            preview.image.save("latest_preview.png")

    def on_stream(self, line):
        print(f"[{line.stream}] {line.text}")

    def on_complete(self, result):
        print("success:", result.success)
        print("generated:", result.generated_files)

    def on_error(self, error):
        print("error:", error.message)

Full signature example:

from shared.api import GenerationError, GenerationResult, PreviewUpdate, ProgressUpdate, SessionEvent, StreamMessage


class VerboseCallbacks:
    def on_progress(self, progress: ProgressUpdate) -> None:
        print("progress", progress.progress, progress.current_step, progress.total_steps)

    def on_preview(self, preview: PreviewUpdate) -> None:
        print("preview", preview.phase, preview.image.size if preview.image is not None else None)

    def on_stream(self, line: StreamMessage) -> None:
        print(line.stream, line.text)

    def on_status(self, text: str) -> None:
        print("status", text)

    def on_info(self, text: str) -> None:
        print("info", text)

    def on_output(self, data: object) -> None:
        print("output", data)

    def on_complete(self, result: GenerationResult) -> None:
        print("success", result.success)
        print("files", result.generated_files)

    def on_error(self, error: GenerationError) -> None:
        print("error", error.stage, error.task_index, error.message)

    def on_event(self, event: SessionEvent) -> None:
        print("event", event.kind)

Cancellation

job = session.submit_task(settings)
job.cancel()

Cancellation is cooperative and forwards WanGP's normal abort signal to the active model. A cancelled run completes with result.success == False and a cancellation entry in result.errors.