Compare commits
4 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| e756f61b9a | |||
| 8cb98c84f9 | |||
| e251afda2b | |||
| 74bd932327 |
+13
-84
@@ -5,7 +5,7 @@ import base64
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import subprocess
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import dataclasses
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import logging
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from asyncio import wait, sleep, gather, Semaphore, FIRST_COMPLETED, create_task, get_running_loop
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from asyncio import wait, sleep, gather, Semaphore, FIRST_COMPLETED, create_task
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from typing import Tuple, Awaitable, NoReturn, List, Union, Callable, Optional
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from functools import cached_property
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from distutils.util import strtobool
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@@ -26,8 +26,7 @@ from lib.data_types import (
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LogAction,
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ApiPayload_T,
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JsonDataException,
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RequestMetrics,
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BenchmarkResult
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RequestMetrics
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)
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VERSION = "0.1.0"
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@@ -74,11 +73,6 @@ class Backend:
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self._pubkey = self._fetch_pubkey()
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self.__start_healthcheck: bool = False
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# NEW: FIFO queue + worker count
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self.request_queue: "asyncio.Queue[tuple[EndpointHandler[ApiPayload_T], web.Request, asyncio.Future]]" = asyncio.Queue()
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# If parallel allowed, let multiple workers drain the queue (order preserved by FIFO per worker; overall start order is FIFO).
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self._num_workers: int = 1 if not self.allow_parallel_requests else int(os.environ.get("WORKERS", "4"))
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@property
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def pubkey(self) -> Optional[RSA.RsaKey]:
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if self._pubkey is None:
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@@ -96,22 +90,6 @@ class Backend:
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timeout = ClientTimeout(total=None)
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return ClientSession(self.model_server_url, timeout=timeout, connector=connector)
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async def _worker(self):
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while True:
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handler, request, fut = await self.request_queue.get()
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try:
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# Skip if already cancelled while waiting in the queue
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if fut.cancelled():
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continue
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res = await self.__process_enqueued_request(handler, request)
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if not fut.cancelled():
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fut.set_result(res)
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except Exception as e:
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if not fut.cancelled():
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fut.set_exception(e)
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finally:
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self.request_queue.task_done()
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def create_handler(
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self,
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handler: EndpointHandler[ApiPayload_T],
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@@ -148,36 +126,7 @@ class Backend:
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handler: EndpointHandler[ApiPayload_T],
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request: web.Request,
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) -> Union[web.Response, web.StreamResponse]:
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"""use this function to enqueue requests for FIFO processing"""
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loop = get_running_loop()
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fut: asyncio.Future = loop.create_future()
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# If the client disconnects while waiting in the FIFO, cancel the future so the worker skips it
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cancel_watch = create_task(request.wait_for_disconnection())
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def _cancel_if_disconnected(_):
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if not fut.done():
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fut.cancel()
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cancel_watch.add_done_callback(_cancel_if_disconnected)
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try:
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await self.request_queue.put((handler, request, fut))
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return await fut
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except asyncio.CancelledError:
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# Propagate cancellation to ensure aiohttp doesn't expect a response body
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raise
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finally:
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# Best-effort cleanup of the watcher
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cancel_watch.cancel()
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async def __process_enqueued_request(
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self,
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handler: EndpointHandler[ApiPayload_T],
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request: web.Request,
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) -> Union[web.Response, web.StreamResponse]:
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"""
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This contains the original __handle_request logic and is invoked by workers,
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ensuring FIFO execution via asyncio.Queue.
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"""
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"""use this function to forward requests to the model endpoint"""
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try:
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data = await request.json()
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auth_data, payload = handler.get_data_from_request(data)
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@@ -185,11 +134,8 @@ class Backend:
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return web.json_response(data=e.message, status=422)
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except json.JSONDecodeError:
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return web.json_response(dict(error="invalid JSON"), status=422)
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workload = payload.count_workload()
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request_metrics: RequestMetrics = RequestMetrics(
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request_idx=auth_data.request_idx, reqnum=auth_data.reqnum, workload=workload, status="Created"
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)
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request_metrics: RequestMetrics = RequestMetrics(request_idx=auth_data.request_idx, reqnum=auth_data.reqnum, workload=workload, status="Created")
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async def cancel_api_call_if_disconnected() -> web.Response:
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await request.wait_for_disconnection()
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@@ -230,8 +176,6 @@ class Backend:
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acquired = False
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try:
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self.metrics._request_start(request_metrics)
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# Preserve existing semaphore behavior for serializing requests when requested
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if self.allow_parallel_requests is False:
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log.debug(f"Waiting to aquire Sem for reqnum:{request_metrics.reqnum}")
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await self.sem.acquire()
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@@ -241,7 +185,6 @@ class Backend:
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)
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else:
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log.debug(f"Starting request for reqnum:{request_metrics.reqnum}")
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done, pending = await wait(
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[
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create_task(make_request()),
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@@ -309,14 +252,8 @@ class Backend:
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self.backend_errored(str(e))
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async def _start_tracking(self) -> None:
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# Start the FIFO workers alongside existing loops
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worker_tasks = tuple(self._worker() for _ in range(self._num_workers))
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await gather(
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self.__read_logs(),
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self.metrics._send_metrics_loop(),
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self.__healthcheck(),
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self.metrics._send_delete_requests_loop(),
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*worker_tasks,
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self.__read_logs(), self.metrics._send_metrics_loop(), self.__healthcheck(), self.metrics._send_delete_requests_loop()
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)
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def backend_errored(self, msg: str) -> None:
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@@ -395,26 +332,18 @@ class Backend:
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for run in range(1, self.benchmark_handler.benchmark_runs + 1):
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start = time.time()
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benchmark_requests = []
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tasks = []
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total_workload = 0
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for i in range(concurrent_requests):
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for _ in range(concurrent_requests):
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payload = self.benchmark_handler.make_benchmark_payload()
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workload = payload.count_workload()
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task = self.__call_api(handler=self.benchmark_handler, payload=payload)
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benchmark_requests.append(
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BenchmarkResult(request_idx=i, workload=workload, task=task)
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total_workload += payload.count_workload()
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tasks.append(
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self.__call_api(handler=self.benchmark_handler, payload=payload)
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)
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responses = await gather(*[br.task for br in benchmark_requests])
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for br, response in zip(benchmark_requests, responses):
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br.response = response
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total_workload = sum(br.workload for br in benchmark_requests if br.is_successful)
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responses = await gather(*tasks)
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time_elapsed = time.time() - start
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successful_responses = sum([1 for br in benchmark_requests if br.is_successful])
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if successful_responses == 0:
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self.backend_errored("No successful responses from benchmark")
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log.debug(f"benchmark failed: {successful_responses}/{concurrent_requests} successful responses")
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throughput = total_workload / time_elapsed
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sum_throughput += throughput
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@@ -428,7 +357,7 @@ class Backend:
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f"Run: {run}, concurrent_requests: {concurrent_requests}",
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f"Total workload: {total_workload}, time_elapsed: {time_elapsed}s",
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f"Throughput: {throughput} workload/s",
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f"Successful responses: {successful_responses}/{concurrent_requests}",
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f"Successful responses: {len([r for r in responses if r.status == 200])}",
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"#" * 60,
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]
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)
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+2
-13
@@ -3,7 +3,7 @@ import logging
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from dataclasses import dataclass, field
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from enum import Enum
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from abc import ABC, abstractmethod
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from typing import Dict, Any, Union, Tuple, Optional, Set, TypeVar, Generic, Type, Awaitable
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from typing import Dict, Any, Union, Tuple, Optional, Set, TypeVar, Generic, Type
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from aiohttp import web, ClientResponse
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import inspect
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@@ -206,17 +206,6 @@ class RequestMetrics:
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status: str
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success: bool = False
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@dataclass
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class BenchmarkResult:
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request_idx: int
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workload: float
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task: Awaitable[ClientResponse]
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response: Optional[ClientResponse] = None
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@property
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def is_successful(self) -> bool:
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return self.response is not None and self.response.status == 200
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@dataclass
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class ModelMetrics:
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"""Model specific metrics"""
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@@ -257,7 +246,7 @@ class ModelMetrics:
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def wait_time(self) -> float:
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if (len(self.requests_working) == 0):
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return 0.0
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return sum([request.workload for request in self.requests_working.values()]) / max(self.max_throughput, 0.00001)
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return sum([request.workload for request in self.requests_working.values()]) / self.max_throughput
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@property
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def cur_load(self) -> float:
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+8
-33
@@ -145,56 +145,31 @@ class Metrics:
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#######################################Private#######################################
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async def __send_delete_requests_and_reset(self):
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async def post(report_addr: str, idxs: list[int], success_flag: bool) -> bool:
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async def send_data(report_addr: str, success: bool) -> bool:
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data = {
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"worker_id": self.id,
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"request_idxs": idxs,
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"success": success_flag,
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"request_idxs": [r.request_idx for r in self.model_metrics.requests_deleting if r.success == success],
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"success": success
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}
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log.debug(
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f"Deleting requests that {'succeeded' if success_flag else 'failed'}: {data['request_idxs']}"
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)
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full_path = report_addr.rstrip("/") + "/delete_requests/"
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for attempt in range(1, 4):
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try:
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session = await self.http()
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async with session.post(full_path, json=data) as res:
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log.debug(f"delete_requests response: {res.status}")
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res.raise_for_status()
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return True
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except asyncio.TimeoutError:
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log.debug("delete_requests timed out")
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log.debug(f"delete_requests timed out")
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except (ClientResponseError, Exception) as e:
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log.debug(f"delete_requests failed with error: {e}")
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await asyncio.sleep(2)
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log.debug(f"retrying delete_request, attempt: {attempt}")
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return False
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# Take a snapshot of what we plan to send this tick.
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# New arrivals after this snapshot will remain in the queue for the next tick.
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snapshot = list(self.model_metrics.requests_deleting)
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success_idxs = [r.request_idx for r in snapshot if r.success is True]
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failed_idxs = [r.request_idx for r in snapshot if r.success is False]
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if not success_idxs and not failed_idxs:
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return # nothing to do
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for report_addr in self.report_addr:
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sent_success = True
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sent_failed = True
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if success_idxs:
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sent_success = await post(report_addr, success_idxs, True)
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if failed_idxs:
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sent_failed = await post(report_addr, failed_idxs, False)
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if sent_success and sent_failed:
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# Remove only the items we actually sent from the live queue.
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sent_set = set(success_idxs) | set(failed_idxs)
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self.model_metrics.requests_deleting[:] = [
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r for r in self.model_metrics.requests_deleting
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if r.request_idx not in sent_set
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]
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success = await send_data(report_addr, success=True) and await send_data(report_addr, success=False)
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if success is True:
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self.model_metrics.requests_deleting.clear()
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break
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|
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@@ -12,21 +12,9 @@ A docker image is provided but you may use any if the above requirements are met
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|
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## Benchmarking
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### Custom Benchmark Workflows
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A simple image generation benchmark runs when each worker initializes to validate GPU performance and identify underperforming machines.
|
||||
|
||||
You can provide a custom ComfyUI workflow for benchmarking by creating `workers/comfyui-json/misc/benchmark.json`. This allows you to test performance using your preferred models and workflow complexity.
|
||||
|
||||
**Ways to provide the benchmark file:**
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- Fork this repository and add your `benchmark.json` file
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- Write the file during worker provisioning (onstart script or setup phase)
|
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|
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An example file is provided in the repository. To ensure varied generations, use the placeholder `__RANDOM_INT__` in place of static seed values - it will be replaced with a random integer for each benchmark run.
|
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|
||||
### Default Benchmark (Fallback)
|
||||
|
||||
If `benchmark.json` is not available, a simple image generation benchmark runs when each worker initializes. This validates GPU performance and helps identify underperforming machines.
|
||||
|
||||
The default benchmark uses Stable Diffusion v1.5 with ComfyUI's standard text-to-image workflow. Configure it using these environment variables:
|
||||
The benchmark uses Stable Diffusion v1.5 with ComfyUI's default text-to-image workflow. Configure the benchmark complexity and duration using these variables:
|
||||
|
||||
| Environment Variable | Default Value | Description |
|
||||
| -------------------- | ------------- | ----------- |
|
||||
@@ -36,7 +24,7 @@ The default benchmark uses Stable Diffusion v1.5 with ComfyUI's standard text-to
|
||||
|
||||
Each benchmark run uses a random prompt from `misc/test_prompts.txt` and a random seed to ensure consistent GPU load patterns.
|
||||
|
||||
#### Calibrating Fallback Benchmark Duration
|
||||
### Calibrating Benchmark Duration
|
||||
|
||||
To screen for underperforming hardware, set `BENCHMARK_TEST_STEPS` to match your expected production workflow duration. This allows you to identify machines that won't meet performance requirements.
|
||||
|
||||
|
||||
@@ -5,13 +5,12 @@ import dataclasses
|
||||
from typing import Dict, Any
|
||||
from functools import cache
|
||||
from math import ceil
|
||||
from pathlib import Path
|
||||
import json
|
||||
import logging
|
||||
|
||||
from lib.data_types import ApiPayload, JsonDataException
|
||||
|
||||
log = logging.getLogger(__file__)
|
||||
|
||||
with open("workers/comfyui/misc/test_prompts.txt", "r") as f:
|
||||
test_prompts = f.readlines()
|
||||
|
||||
def count_workload() -> float:
|
||||
# Always 100.0 where there is a single instance of ComfyUI handling requests
|
||||
@@ -25,32 +24,9 @@ class ComfyWorkflowData(ApiPayload):
|
||||
@classmethod
|
||||
def for_test(cls):
|
||||
"""
|
||||
If the user has provided a benchmark workflow we can use it here to properly gauge performance.
|
||||
Otherwise, use the variables available to simulate workflows of the required running time
|
||||
Use the variables available to simulate workflows of the required running time
|
||||
Example: SD1.5, simple image gen 10000 steps, 512px x 512px will run for approximately 9 minutes @ ~18 it/s (RTX 4090)
|
||||
"""
|
||||
# Try to load benchmark.json
|
||||
benchmark_file = Path("workers/comfyui-json/misc/benchmark.json")
|
||||
|
||||
if benchmark_file.exists():
|
||||
try:
|
||||
with open(benchmark_file, "r") as f:
|
||||
benchmark_workflow = json.load(f)
|
||||
return cls(
|
||||
input={
|
||||
"request_id": f"test-{random.randint(1000, 99999)}",
|
||||
"workflow_json": benchmark_workflow
|
||||
}
|
||||
)
|
||||
except (json.JSONDecodeError, IOError):
|
||||
# JSON is malformed or file can't be read, fall through to default
|
||||
log.error(f"Failed to benchmark using {benchmark_file}")
|
||||
|
||||
# Fallback: read prompts and construct payload
|
||||
log.info("Using fallback method for benchmarking")
|
||||
with open("workers/comfyui-json/misc/test_prompts.txt", "r") as f:
|
||||
test_prompts = f.readlines()
|
||||
|
||||
test_prompt = random.choice(test_prompts).rstrip()
|
||||
return cls(
|
||||
input={
|
||||
|
||||
@@ -1,107 +0,0 @@
|
||||
{
|
||||
"3": {
|
||||
"inputs": {
|
||||
"seed": "__RANDOM_INT__",
|
||||
"steps": 20,
|
||||
"cfg": 8,
|
||||
"sampler_name": "euler",
|
||||
"scheduler": "normal",
|
||||
"denoise": 1,
|
||||
"model": [
|
||||
"4",
|
||||
0
|
||||
],
|
||||
"positive": [
|
||||
"6",
|
||||
0
|
||||
],
|
||||
"negative": [
|
||||
"7",
|
||||
0
|
||||
],
|
||||
"latent_image": [
|
||||
"5",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "KSampler",
|
||||
"_meta": {
|
||||
"title": "KSampler"
|
||||
}
|
||||
},
|
||||
"4": {
|
||||
"inputs": {
|
||||
"ckpt_name": "v1-5-pruned-emaonly-fp16.safetensors"
|
||||
},
|
||||
"class_type": "CheckpointLoaderSimple",
|
||||
"_meta": {
|
||||
"title": "Load Checkpoint"
|
||||
}
|
||||
},
|
||||
"5": {
|
||||
"inputs": {
|
||||
"width": 512,
|
||||
"height": 512,
|
||||
"batch_size": 1
|
||||
},
|
||||
"class_type": "EmptyLatentImage",
|
||||
"_meta": {
|
||||
"title": "Empty Latent Image"
|
||||
}
|
||||
},
|
||||
"6": {
|
||||
"inputs": {
|
||||
"text": "beautiful scenery nature glass bottle landscape, , purple galaxy bottle,",
|
||||
"clip": [
|
||||
"4",
|
||||
1
|
||||
]
|
||||
},
|
||||
"class_type": "CLIPTextEncode",
|
||||
"_meta": {
|
||||
"title": "CLIP Text Encode (Prompt)"
|
||||
}
|
||||
},
|
||||
"7": {
|
||||
"inputs": {
|
||||
"text": "text, watermark",
|
||||
"clip": [
|
||||
"4",
|
||||
1
|
||||
]
|
||||
},
|
||||
"class_type": "CLIPTextEncode",
|
||||
"_meta": {
|
||||
"title": "CLIP Text Encode (Prompt)"
|
||||
}
|
||||
},
|
||||
"8": {
|
||||
"inputs": {
|
||||
"samples": [
|
||||
"3",
|
||||
0
|
||||
],
|
||||
"vae": [
|
||||
"4",
|
||||
2
|
||||
]
|
||||
},
|
||||
"class_type": "VAEDecode",
|
||||
"_meta": {
|
||||
"title": "VAE Decode"
|
||||
}
|
||||
},
|
||||
"9": {
|
||||
"inputs": {
|
||||
"filename_prefix": "ComfyUI",
|
||||
"images": [
|
||||
"8",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "SaveImage",
|
||||
"_meta": {
|
||||
"title": "Save Image"
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -19,7 +19,6 @@ MODEL_SERVER_START_LOG_MSG = "To see the GUI go to: "
|
||||
MODEL_SERVER_ERROR_LOG_MSGS = [
|
||||
"MetadataIncompleteBuffer", # This error is emitted when the downloaded model is corrupted
|
||||
"Value not in list: ", # This error is emitted when the model file is not there at all
|
||||
"[ERROR] Provisioning Script failed", # Error inserted by provisioning script if models/nodes fail to download
|
||||
]
|
||||
|
||||
|
||||
|
||||
@@ -119,25 +119,14 @@ class GenericHandler(EndpointHandler[GenericData], ABC):
|
||||
class CompletionsData(GenericData):
|
||||
@classmethod
|
||||
def for_test(cls) -> "CompletionsData":
|
||||
system_prompt = """You are a helpful AI assistant. You have access to the following knowledge base:
|
||||
|
||||
Zebras (US: /ˈziːbrəz/, UK: /ˈzɛbrəz, ˈziː-/)[2] (subgenus Hippotigris) are African equines
|
||||
with distinctive black-and-white striped coats. There are three living species: Grévy's zebra
|
||||
(Equus grevyi), the plains zebra (E. quagga), and the mountain zebra (E. zebra). Zebras share the
|
||||
genus Equus with horses and asses, the three groups being the only living members of the family
|
||||
Equidae. Zebra stripes come in different patterns, unique to each individual. Zebras inhabit eastern
|
||||
and southern Africa and can be found in a variety of habitats such as savannahs, grasslands,
|
||||
woodlands, shrublands, and mountainous areas.
|
||||
|
||||
Please answer the following question based on the above context."""
|
||||
unique_question = " ".join(random.choices(WORD_LIST, k=int(100)))
|
||||
prompt = " ".join(random.choices(WORD_LIST, k=int(250)))
|
||||
model = os.environ.get("MODEL_NAME")
|
||||
if not model:
|
||||
raise ValueError("MODEL_NAME environment variable not set")
|
||||
|
||||
test_input = {
|
||||
"model": model,
|
||||
"prompt": f"{system_prompt}\n\n{unique_question}",
|
||||
"prompt": prompt,
|
||||
"temperature": 0.7,
|
||||
"max_tokens": 500,
|
||||
}
|
||||
@@ -164,18 +153,7 @@ class ChatCompletionsData(GenericData):
|
||||
|
||||
@classmethod
|
||||
def for_test(cls) -> "ChatCompletionsData":
|
||||
system_prompt = """You are a helpful AI assistant. You have access to the following knowledge base:
|
||||
|
||||
Zebras (US: /ˈziːbrəz/, UK: /ˈzɛbrəz, ˈziː-/)[2] (subgenus Hippotigris) are African equines
|
||||
with distinctive black-and-white striped coats. There are three living species: Grévy's zebra
|
||||
(Equus grevyi), the plains zebra (E. quagga), and the mountain zebra (E. zebra). Zebras share the
|
||||
genus Equus with horses and asses, the three groups being the only living members of the family
|
||||
Equidae. Zebra stripes come in different patterns, unique to each individual. Zebras inhabit eastern
|
||||
and southern Africa and can be found in a variety of habitats such as savannahs, grasslands,
|
||||
woodlands, shrublands, and mountainous areas.
|
||||
|
||||
Please answer the following question based on the above context."""
|
||||
unique_question = " ".join(random.choices(WORD_LIST, k=int(100)))
|
||||
prompt = " ".join(random.choices(WORD_LIST, k=int(250)))
|
||||
model = os.environ.get("MODEL_NAME")
|
||||
if not model:
|
||||
raise ValueError("MODEL_NAME environment variable not set")
|
||||
@@ -183,10 +161,7 @@ class ChatCompletionsData(GenericData):
|
||||
# Chat completions use messages format instead of prompt
|
||||
test_input = {
|
||||
"model": model,
|
||||
"messages": [
|
||||
{"role": "system", "content": system_prompt}, # Shared prefix
|
||||
{"role": "user", "content": unique_question} # Unique per request
|
||||
],
|
||||
"messages": [{"role": "user", "content": prompt}],
|
||||
"temperature": 0.7,
|
||||
"max_tokens": 500,
|
||||
}
|
||||
|
||||
@@ -82,7 +82,6 @@ def do_one(endpoint_name: str,
|
||||
# 1) Check if we got a worker back from route
|
||||
worker_url = msg.get("url", "")
|
||||
if not worker_url:
|
||||
status = msg.get("status", "")
|
||||
m = re.search(r"total workers:\s*(\d+).*loading workers:\s*(\d+).*standby workers:\s*(\d+).*error workers:\s*(\d+)", status, re.I | re.S)
|
||||
if m:
|
||||
tot, loading, standby, err = map(int, m.groups())
|
||||
|
||||
Reference in New Issue
Block a user