Files
robertvoy-ComfyUI-Distributed/api/orchestration/dispatch.py
T
Robert Wojciechowski 7ed60b93ca feat: dynamically distribute image lists across direct workers (#98)
* feat: add Runpod serverless image collector pools

* fix: prevent worker settings clipping and remove preview copy

* fix: initialize worker settings before mounting the form

* fix: validate complete serverless requests against 10 MB limit

* fix: simplify serverless cards and keep status dots circular

* fix: match serverless endpoint box to master card

* fix: preserve serverless capacity and recovery across job failures

Retain durable reservations until provider termination or explicit recovery, protect unresolved pools and credentials, and add scoped reconciliation. Consolidate lifecycle and secret policies and split prompt/media stages with regression coverage.

* feat: add dynamic per-image list queue with Start and End nodes

* fix(image-list): reject upstream data bypasses around Start

* fix(image-list): make optional End text a connection-only input

* fix(image-list): isolate unavailable workers during preflight

* fix(image-list): bound acknowledgements and configure run deadline

* fix(media-sync): preserve output and temp source roots

* fix(image-list): own job lifecycle and preserve worker preparation

* feat(image-list): let master participate unless orchestrator-only

* feat(image-list)!: replace fixed Start extras with growable value_N slots

Distributed Image List Start no longer has reference_image, text,
strength, seed or per-slot mode dropdowns. It now takes images, mask and
up to 10 generic value_N inputs (IMAGE, MASK, STRING, INT, FLOAT,
BOOLEAN) that grow via native V3 Autogrow, each with a matching output.

- One value is shared by every image; one per image pairs in order; any
  other count fails before dispatch. Only images is split into frames.
- Outputs are declared up front (image, mask, item_index, context,
  value_1..value_10). web/imageListStart.js hides unused value outputs,
  mirrors input types, and follows Autogrow compaction so downstream
  links keep their value.
- Image-list protocol bumped to v2; older workers fail preflight.

Breaking: saved workflows using the old Start inputs must recreate Start.

* fix(serverless): disable Clear saved API key while the worker is enabled

The checkbox read "Clear saved API key (disable pool first)", but the
panel never defines "pool" and saving with it ticked on an enabled worker
was rejected by the backend.

- Disable the checkbox while the worker is enabled, with a tooltip saying
  to turn the worker off first. Also disable it when no key is saved.
- Use "worker" instead of "pool" in user-facing serverless errors, the
  serverless guide and the README entry.

* feat(serverless): replace Concurrent jobs with a single Images per run setting

- Remove the separate Concurrent jobs field; rename Jobs per run to
  Images per run (1-16) with a tooltip explaining that Runpod's max
  workers decides how many GPUs run them.
- Backend uses a fixed per-worker limit of 16 outstanding jobs, so all
  images of a run are submitted at once. Unresolved jobs still count
  against it. The limit is constant, so it never has to change while
  jobs are unresolved.
- Legacy 'concurrency' in saved configs and older browser tabs is
  accepted and ignored/dropped; it no longer triggers the busy guard.
- Revert the enable toggle and show the reason when the backend rejects it.
- Trim a pasted api.runpod.ai/v2/<id> URL to the endpoint ID; plainer
  endpoint-ID error otherwise.
- Confirm before a type change deletes a saved Runpod API key.
- Update docs and tests.
2026-10-13 15:20:05 -07:00

391 lines
15 KiB
Python

import asyncio
import json
import uuid
import aiohttp
from ...utils.logging import debug_log, log
from ...utils.network import build_worker_url, get_client_session, probe_worker
# Must match image_list.runtime.PROTOCOL_VERSION (kept local so this module
# stays importable without the image-list runtime; a test pins them equal).
IMAGE_LIST_PROTOCOL_VERSION = 2
try:
from ...utils.trace_logger import trace_debug, trace_info
except ImportError:
def trace_debug(*_args, **_kwargs):
return None
def trace_info(*_args, **_kwargs):
return None
try:
from ..schemas import parse_positive_int
except ImportError:
def parse_positive_int(value, default):
try:
parsed = int(value)
return parsed if parsed > 0 else default
except (TypeError, ValueError):
return default
_least_busy_rr_index = 0
async def worker_is_active(worker):
"""Ping worker's /prompt endpoint to confirm it's reachable."""
url = build_worker_url(worker)
return await probe_worker(url, timeout=3.0) is not None
async def worker_ws_is_active(worker):
"""Ping worker's websocket endpoint to confirm it's reachable."""
session = await get_client_session()
url = build_worker_url(worker, "/distributed/worker_ws")
try:
ws = await session.ws_connect(url, heartbeat=20, timeout=3)
await ws.close()
return True
except asyncio.TimeoutError:
debug_log(f"[Distributed] Worker WS probe timed out: {url}")
return False
except aiohttp.ClientConnectorError:
debug_log(f"[Distributed] Worker WS unreachable: {url}")
return False
except Exception as e:
debug_log(f"[Distributed] Worker WS probe unexpected error: {e}")
return False
async def _probe_worker_active(worker, use_websocket, semaphore):
async with semaphore:
if worker.get("type") == "serverless":
from .serverless_runtime import get_manager
# Authentication/configuration failures must surface, not silently skip paid work.
status = await get_manager().health(worker)
return worker, status["ok"]
is_active = await (worker_ws_is_active(worker) if use_websocket else worker_is_active(worker))
return worker, is_active
async def _dispatch_via_websocket(worker_url, payload, client_id, timeout=60.0):
"""Open a fresh worker websocket, dispatch one prompt, wait for ack, then close."""
request_id = uuid.uuid4().hex
ws_payload = {
"type": "dispatch_prompt",
"request_id": request_id,
"prompt": payload.get("prompt"),
"workflow": payload.get("workflow"),
"client_id": client_id,
}
ws_url = worker_url.replace("http://", "ws://").replace("https://", "wss://")
ws_url = f"{ws_url}/distributed/worker_ws"
session = await get_client_session()
loop = asyncio.get_running_loop()
deadline = loop.time() + timeout
ws = None
try:
async with asyncio.timeout_at(deadline):
ws = await session.ws_connect(ws_url, heartbeat=20)
await ws.send_json(ws_payload)
while True:
msg = await ws.receive()
if msg.type == aiohttp.WSMsgType.TEXT:
data = json.loads(msg.data or "{}")
if data.get("type") == "dispatch_ack" and data.get("request_id") == request_id:
if data.get("ok"):
return data.get("prompt_id")
error_text = data.get("error") or "Worker rejected websocket dispatch."
validation_error = data.get("validation_error")
node_errors = data.get("node_errors")
if validation_error:
error_text = f"{error_text} | validation_error={validation_error}"
if node_errors:
error_text = f"{error_text} | node_errors={node_errors}"
raise RuntimeError(error_text)
elif msg.type in (aiohttp.WSMsgType.ERROR, aiohttp.WSMsgType.CLOSE, aiohttp.WSMsgType.CLOSED):
raise RuntimeError(f"Worker websocket closed before acknowledgement: {msg.type}; submission status is ambiguous")
except asyncio.TimeoutError as exc:
raise RuntimeError(
"Worker websocket dispatch timed out before dispatch_ack; submission status is ambiguous."
) from exc
finally:
if ws is not None:
# Closing must not discard an already acknowledged prompt ID or
# replace a definite rejection with an ambiguous timeout.
try:
async with asyncio.timeout_at(min(deadline, loop.time() + 1.0)):
await ws.close()
except (asyncio.TimeoutError, aiohttp.ClientError):
pass
async def dispatch_worker_prompt(
worker,
prompt_obj,
workflow_meta,
client_id=None,
use_websocket=False,
trace_execution_id=None,
return_prompt_id=False,
):
"""Send the prepared prompt to a worker ComfyUI instance."""
worker_url = build_worker_url(worker)
url = build_worker_url(worker, "/prompt")
payload = {"prompt": prompt_obj}
extra_data = {}
if workflow_meta:
extra_data.setdefault("extra_pnginfo", {})["workflow"] = workflow_meta
if extra_data:
payload["extra_data"] = extra_data
if use_websocket:
try:
prompt_id = await _dispatch_via_websocket(
worker_url,
{
"prompt": prompt_obj,
"workflow": workflow_meta,
},
client_id,
)
if return_prompt_id and (not isinstance(prompt_id, str) or not prompt_id):
raise RuntimeError("Worker websocket acknowledgement omitted prompt_id")
return prompt_id if return_prompt_id else None
except Exception as exc:
worker_id = worker.get("id")
if trace_execution_id:
trace_info(trace_execution_id, f"Websocket dispatch failed for worker {worker_id}: {exc}")
else:
log(f"[Distributed] Websocket dispatch failed for worker {worker_id}: {exc}")
raise
session = await get_client_session()
async with session.post(
url,
json=payload,
timeout=aiohttp.ClientTimeout(total=60),
) as resp:
resp.raise_for_status()
if not return_prompt_id:
return None
try:
response_data = await resp.json()
except Exception as exc:
raise RuntimeError("Worker /prompt response did not contain JSON acknowledgement") from exc
prompt_id = response_data.get("prompt_id") if isinstance(response_data, dict) else None
if not isinstance(prompt_id, str) or not prompt_id:
raise RuntimeError("Worker /prompt response omitted prompt_id")
return prompt_id if return_prompt_id else None
async def preflight_image_list_workers(workers, require_idle=True, timeout=3.0):
"""Require protocol/node support and report which direct workers are idle.
This performs read-only GETs only; it never submits a prompt or contacts a
serverless provider. Unsupported worker releases fail before master inputs run.
"""
if not workers:
raise RuntimeError("Distributed Image List requires at least one selected direct worker")
session = await get_client_session()
required_nodes = {"DistributedImageListStart", "DistributedImageListEnd"}
semaphore = asyncio.Semaphore(8)
async def inspect(worker):
worker_id = str(worker.get("id") or "unknown")
check = "capability"
try:
async with semaphore:
cap_url = build_worker_url(worker, "/distributed/image-list/capabilities")
async with session.get(cap_url, timeout=aiohttp.ClientTimeout(total=timeout)) as response:
if response.status != 200:
raise RuntimeError(
f"Image-list worker {worker_id} does not expose the capability endpoint "
f"(HTTP {response.status}); upgrade that worker before running this feature"
)
capability = await response.json()
if not isinstance(capability, dict):
raise RuntimeError(f"Image-list worker {worker_id} returned malformed capability data")
supported = capability.get("supported")
protocol_version = capability.get("protocol_version")
nodes = capability.get("node_ids")
if (
not isinstance(supported, bool)
or type(protocol_version) is not int
or not isinstance(nodes, list)
or any(not isinstance(node_id, str) for node_id in nodes)
):
raise RuntimeError(f"Image-list worker {worker_id} returned malformed capability data")
if (
supported is not True
or protocol_version != IMAGE_LIST_PROTOCOL_VERSION
or not required_nodes.issubset(nodes)
):
raise RuntimeError(
f"Image-list worker {worker_id} is incompatible: requires protocol "
f"v{IMAGE_LIST_PROTOCOL_VERSION} and nodes "
f"{sorted(required_nodes)}; no work was submitted"
)
check = "queue"
queue_url = build_worker_url(worker, "/queue")
async with session.get(queue_url, timeout=aiohttp.ClientTimeout(total=timeout)) as response:
if response.status != 200:
raise RuntimeError(f"Image-list worker {worker_id} queue preflight returned HTTP {response.status}")
queue = await response.json()
if (
not isinstance(queue, dict)
or not isinstance(queue.get("queue_running"), list)
or not isinstance(queue.get("queue_pending"), list)
):
raise RuntimeError(f"Image-list worker {worker_id} returned malformed /queue state")
idle = not queue["queue_running"] and not queue["queue_pending"]
return worker_id, idle
except (asyncio.TimeoutError, aiohttp.ClientConnectionError) as exc:
log(
f"[Distributed] Image-list worker {worker_id} unavailable during {check} check; "
f"skipping: {exc}"
)
return worker_id, None
statuses = await asyncio.gather(*(inspect(worker) for worker in workers))
idle_workers = {
worker_id: True
for worker_id, idle in statuses
if idle is True
}
if require_idle and not idle_workers:
raise RuntimeError("No selected feature-compatible direct worker is idle; unrelated worker prompts were left untouched")
return idle_workers
async def select_active_workers(
workers,
use_websocket,
delegate_master,
trace_execution_id=None,
probe_concurrency=8,
):
"""Probe workers and return (active_workers, updated_delegate_master)."""
probe_limit = parse_positive_int(probe_concurrency, 8)
probe_semaphore = asyncio.Semaphore(probe_limit)
if trace_execution_id and workers:
trace_debug(
trace_execution_id,
f"Probing {len(workers)} workers with probe_concurrency={probe_limit}",
)
probe_results = await asyncio.gather(
*[
_probe_worker_active(worker, use_websocket, probe_semaphore)
for worker in workers
]
)
active_workers = []
for worker, is_active in probe_results:
if is_active:
active_workers.append(worker)
else:
if trace_execution_id:
trace_info(trace_execution_id, f"Worker {worker['name']} ({worker['id']}) is offline, skipping.")
else:
log(f"[Distributed] Worker {worker['name']} ({worker['id']}) is offline, skipping.")
if trace_execution_id and workers:
trace_debug(
trace_execution_id,
f"Worker probe complete: active={len(active_workers)}/{len(workers)}",
)
if not active_workers and delegate_master:
if trace_execution_id:
trace_debug(trace_execution_id, "All workers offline while delegate-only requested; enabling master participation.")
else:
debug_log("All workers offline while delegate-only requested; enabling master participation.")
delegate_master = False
return active_workers, delegate_master
def _extract_queue_remaining(payload):
if not isinstance(payload, dict):
return 0
try:
queue_remaining = int(payload.get("exec_info", {}).get("queue_remaining", 0))
except (TypeError, ValueError):
queue_remaining = 0
return max(queue_remaining, 0)
async def _probe_worker_queue(worker, semaphore, probe_timeout):
async with semaphore:
if worker.get("type") == "serverless":
from .serverless_runtime import get_manager
status = await get_manager().health(worker)
return {"worker": worker, "queue_remaining": status["queueRemaining"]}
worker_url = build_worker_url(worker)
payload = await probe_worker(worker_url, timeout=probe_timeout)
if payload is None:
return None
return {
"worker": worker,
"queue_remaining": _extract_queue_remaining(payload),
}
def _select_idle_round_robin(statuses):
global _least_busy_rr_index
if not statuses:
return None
index = _least_busy_rr_index % len(statuses)
_least_busy_rr_index += 1
return statuses[index]
async def select_least_busy_worker(
workers,
trace_execution_id=None,
probe_concurrency=8,
probe_timeout=3.0,
):
"""Select one worker by queue depth, round-robin among idle workers."""
if not workers:
return None
probe_limit = parse_positive_int(probe_concurrency, 8)
probe_semaphore = asyncio.Semaphore(probe_limit)
statuses = await asyncio.gather(
*[
_probe_worker_queue(worker, probe_semaphore, probe_timeout)
for worker in workers
]
)
statuses = [status for status in statuses if status is not None]
if not statuses:
if trace_execution_id:
trace_info(trace_execution_id, "Least-busy selection failed: no worker queue probes succeeded.")
else:
log("[Distributed] Least-busy selection failed: no worker queue probes succeeded.")
return None
idle_statuses = [status for status in statuses if status["queue_remaining"] == 0]
if idle_statuses:
selected = _select_idle_round_robin(idle_statuses)
else:
selected = min(statuses, key=lambda status: status["queue_remaining"])
worker = selected["worker"]
queue_remaining = selected["queue_remaining"]
if trace_execution_id:
trace_debug(
trace_execution_id,
f"Least-busy worker selected: {worker.get('name')} ({worker.get('id')}), queue_remaining={queue_remaining}",
)
else:
debug_log(
f"Least-busy worker selected: {worker.get('name')} ({worker.get('id')}), queue_remaining={queue_remaining}"
)
return worker