diff --git a/lib/backend.py b/lib/backend.py index dc1f52c..e55ce59 100644 --- a/lib/backend.py +++ b/lib/backend.py @@ -26,7 +26,8 @@ from lib.data_types import ( LogAction, ApiPayload_T, JsonDataException, - RequestMetrics + RequestMetrics, + BenchmarkResult ) VERSION = "0.1.0" @@ -332,18 +333,26 @@ class Backend: for run in range(1, self.benchmark_handler.benchmark_runs + 1): start = time.time() - tasks = [] - total_workload = 0 + benchmark_requests = [] - for _ in range(concurrent_requests): + for i in range(concurrent_requests): payload = self.benchmark_handler.make_benchmark_payload() - total_workload += payload.count_workload() - tasks.append( - self.__call_api(handler=self.benchmark_handler, payload=payload) + workload = payload.count_workload() + task = self.__call_api(handler=self.benchmark_handler, payload=payload) + benchmark_requests.append( + BenchmarkResult(request_idx=i, workload=workload, task=task) ) - responses = await gather(*tasks) + responses = await gather(*[br.task for br in benchmark_requests]) + for br, response in zip(benchmark_requests, responses): + br.response = response + + total_workload = sum(br.workload for br in benchmark_requests if br.is_successful) time_elapsed = time.time() - start + successful_responses = sum([1 for br in benchmark_requests if br.is_successful]) + if successful_responses == 0: + self.backend_errored("No successful responses from benchmark") + log.debug(f"benchmark failed: {successful_responses}/{concurrent_requests} successful responses") throughput = total_workload / time_elapsed sum_throughput += throughput @@ -357,7 +366,7 @@ class Backend: f"Run: {run}, concurrent_requests: {concurrent_requests}", f"Total workload: {total_workload}, time_elapsed: {time_elapsed}s", f"Throughput: {throughput} workload/s", - f"Successful responses: {len([r for r in responses if r.status == 200])}", + f"Successful responses: {successful_responses}/{concurrent_requests}", "#" * 60, ] ) diff --git a/lib/data_types.py b/lib/data_types.py index d2cf0c2..af1bbd5 100644 --- a/lib/data_types.py +++ b/lib/data_types.py @@ -3,7 +3,7 @@ import logging from dataclasses import dataclass, field from enum import Enum from abc import ABC, abstractmethod -from typing import Dict, Any, Union, Tuple, Optional, Set, TypeVar, Generic, Type +from typing import Dict, Any, Union, Tuple, Optional, Set, TypeVar, Generic, Type, Awaitable from aiohttp import web, ClientResponse import inspect @@ -206,6 +206,17 @@ class RequestMetrics: status: str success: bool = False +@dataclass +class BenchmarkResult: + request_idx: int + workload: float + task: Awaitable[ClientResponse] + response: Optional[ClientResponse] = None + + @property + def is_successful(self) -> bool: + return self.response is not None and self.response.status == 200 + @dataclass class ModelMetrics: """Model specific metrics""" @@ -246,7 +257,7 @@ class ModelMetrics: def wait_time(self) -> float: if (len(self.requests_working) == 0): return 0.0 - return sum([request.workload for request in self.requests_working.values()]) / self.max_throughput + return sum([request.workload for request in self.requests_working.values()]) / max(self.max_throughput, 0.00001) @property def cur_load(self) -> float: diff --git a/lib/test_utils.py b/lib/test_utils.py index 8635027..d64a4b6 100644 --- a/lib/test_utils.py +++ b/lib/test_utils.py @@ -292,12 +292,12 @@ def test_load_cmd( args = arg_parser.parse_args() if hasattr(args, "comfy_model"): os.environ["COMFY_MODEL"] = args.comfy_model - server_url = dict( - prod="https://run.vast.ai", - alpha="https://run-alpha.vast.ai", - candidate="https://run-candidate.vast.ai", - local="http://localhost:8080", - )[args.instance] + server_url = { + "prod": "https://run.vast.ai", + "alpha": "https://run-alpha.vast.ai", + "candidate": "https://run-candidate.vast.ai", + "local": "http://localhost:8080", + }.get(args.instance, "http://localhost:8080") run_test( num_requests=args.num_requests, requests_per_second=args.requests_per_second, diff --git a/utils/endpoint_util.py b/utils/endpoint_util.py index 37930af..927262e 100644 --- a/utils/endpoint_util.py +++ b/utils/endpoint_util.py @@ -1,5 +1,6 @@ import logging -from typing import Any, Dict, Optional +import time +from typing import Any, Dict, Optional, Tuple import requests @@ -16,6 +17,38 @@ class Endpoint: Utility class for handling endpoint operations. """ + @staticmethod + def get_endpoint_info( + endpoint_name: str, account_api_key: str, instance: str + ) -> Optional[Dict[str, Any]]: + headers = {"Authorization": f"Bearer {account_api_key}"} + url = f"{Endpoint.get_server_url(instance)}?autoscaler_instance={instance}" + # Retry a few times to smooth over transient propagation/network delays + for attempt in range(4): + try: + response = requests.get(url, headers=headers, timeout=8) + if response.status_code != 200: + # brief backoff and retry + time.sleep(0.3 * (attempt + 1)) + continue + try: + data = response.json() + except Exception: + # JSON parse failed; backoff and retry + time.sleep(0.3 * (attempt + 1)) + continue + result = data.get("results", []) if isinstance(data, dict) else [] + endpoint = next( + (item for item in result if item.get("endpoint_name") == endpoint_name), + None, + ) + if endpoint and endpoint.get("id") and endpoint.get("api_key"): + return {"id": endpoint.get("id"), "api_key": endpoint.get("api_key")} + except Exception: + # network or other transient error; retry + time.sleep(0.3 * (attempt + 1)) + return None + @staticmethod def get_autoscaler_server_url(instance: str) -> str: endpoints = { @@ -23,7 +56,10 @@ class Endpoint: "candidate": "run-candidate", "prod": "run", } - return f"https://{endpoints[instance]}.vast.ai/" + host = endpoints.get(instance) + if host: + return f"https://{host}.vast.ai/" + return "http://localhost:8080" @staticmethod def get_server_url(instance: str) -> str: @@ -32,7 +68,8 @@ class Endpoint: "candidate": "candidate", "prod": "console", } - return f"https://{endpoints[instance]}.vast.ai/api/v0/endptjobs/" + host = endpoints.get(instance, "alpha") + return f"https://{host}.vast.ai/api/v0/endptjobs/" @staticmethod def get_endpoint_api_key( @@ -55,6 +92,7 @@ class Endpoint: response = requests.get( f"{Endpoint.get_server_url(instance)}?autoscaler_instance={instance}", headers=headers, + timeout=8, ) if response.status_code != 200: @@ -64,14 +102,14 @@ class Endpoint: try: data = response.json() - except requests.exceptions.JSONDecodeError as e: + except Exception as e: log.debug(f"Failed to parse JSON response: {e}") return None result = data.get("results", []) endpoint: Optional[Dict[str, Any]] = next( - (item for item in result if item["endpoint_name"] == endpoint_name), + (item for item in result if item.get("endpoint_name") == endpoint_name), None, ) if not endpoint: diff --git a/workers/openai/data_types/server.py b/workers/openai/data_types/server.py index 92f204b..e549864 100644 --- a/workers/openai/data_types/server.py +++ b/workers/openai/data_types/server.py @@ -119,14 +119,25 @@ class GenericHandler(EndpointHandler[GenericData], ABC): class CompletionsData(GenericData): @classmethod def for_test(cls) -> "CompletionsData": - prompt = " ".join(random.choices(WORD_LIST, k=int(250))) + 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))) model = os.environ.get("MODEL_NAME") if not model: raise ValueError("MODEL_NAME environment variable not set") test_input = { "model": model, - "prompt": prompt, + "prompt": f"{system_prompt}\n\n{unique_question}", "temperature": 0.7, "max_tokens": 500, } @@ -153,7 +164,18 @@ class ChatCompletionsData(GenericData): @classmethod def for_test(cls) -> "ChatCompletionsData": - prompt = " ".join(random.choices(WORD_LIST, k=int(250))) + 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))) model = os.environ.get("MODEL_NAME") if not model: raise ValueError("MODEL_NAME environment variable not set") @@ -161,7 +183,10 @@ class ChatCompletionsData(GenericData): # Chat completions use messages format instead of prompt test_input = { "model": model, - "messages": [{"role": "user", "content": prompt}], + "messages": [ + {"role": "system", "content": system_prompt}, # Shared prefix + {"role": "user", "content": unique_question} # Unique per request + ], "temperature": 0.7, "max_tokens": 500, } diff --git a/workers/openai/test_load.py b/workers/openai/test_load.py index 0c45524..9cb5f37 100644 --- a/workers/openai/test_load.py +++ b/workers/openai/test_load.py @@ -1,8 +1,395 @@ -from lib.test_utils import test_load_cmd, test_args +from lib.test_utils import test_args +from utils.endpoint_util import Endpoint +from utils.ssl import get_cert_file_path +from lib.data_types import AuthData from .data_types.server import CompletionsData -import os -WORKER_ENDPOINT = "/v1/completions" +import os +import time +import threading +import requests +from dataclasses import dataclass +from collections import Counter +from urllib.parse import urljoin, urlparse +import re + +# Headless plotting +import matplotlib +matplotlib.use("Agg") +import logging +logging.getLogger("matplotlib.font_manager").setLevel(logging.WARNING) +import matplotlib.pyplot as plt +import numpy as np +from concurrent.futures import ThreadPoolExecutor, wait, FIRST_COMPLETED +from requests.adapters import HTTPAdapter + +def get_incremented_path(path: str) -> str: + base, ext = os.path.splitext(path) + if not os.path.exists(path): + return path + i = 1 + while os.path.exists(f"{base}-{i}{ext}"): + i += 1 + return f"{base}-{i}{ext}" + +WORKER_ENDPOINT = "/v1/completions" # This will return the full text output at once. Latency metrics reflect that (ie not measuring TTFT) + +@dataclass +class ReqResult: + worker_url: str + route_ms: float + worker_ms: float + total_ms: float + ok: bool + error: str = "" + status_code: int = 0 + t_start: float = 0.0 + t_end: float = 0.0 + workload: float = 0.0 + +def do_one(endpoint_name: str, + endpoint_id: int, + endpoint_api_key: str, + server_url: str, + worker_endpoint: str, + payload, + results_list, + t0, + status_samples, + route_session, + worker_session): + try: + workload = payload.count_workload() + route_payload = {"endpoint": endpoint_name, "api_key": endpoint_api_key, "cost": workload} + headers = {"Authorization": f"Bearer {endpoint_api_key}"} + start = time.time() + r0 = route_session.post(urljoin(server_url, "/route/"), json=route_payload, headers=headers, timeout=4) + t_after_route = time.time() + if r0.status_code != 200: + results_list.append(ReqResult(worker_url="", + route_ms=(t_after_route - start) * 1000.0, + worker_ms=0.0, + total_ms=(t_after_route - start) * 1000.0, + ok=False, + error=f"route error {r0.reason} {r0.text}", + status_code=r0.status_code, + t_start=start - t0, + t_end=t_after_route - t0, + workload=workload)) + return + msg = r0.json() + + # 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()) + idle = max(tot - loading - standby - err, 0) + status_samples.append((time.time() - t0, idle)) + + # 2) If we got a worker, send the request + if worker_url: + req = dict(payload=payload.__dict__, auth_data=AuthData.from_json_msg(msg).__dict__) + t_before_worker = time.time() + r1 = worker_session.post( + urljoin(worker_url, worker_endpoint), + json=req, + verify=get_cert_file_path(), + timeout=(4, 120), + ) + t_after_worker = time.time() + if r1.status_code != 200: + results_list.append(ReqResult(worker_url=worker_url, + route_ms=(t_after_route - start) * 1000.0, + worker_ms=(t_after_worker - t_before_worker) * 1000.0, + total_ms=(t_after_worker - start) * 1000.0, + ok=False, + error=f"worker inference error {r1.reason} {r1.text}", + status_code=r1.status_code, + t_start=start - t0, + t_end=t_after_worker - t0, + workload=workload)) + return + # Success case + results_list.append(ReqResult(worker_url=worker_url, + route_ms=(t_after_route - start) * 1000.0, + worker_ms=(t_after_worker - t_before_worker) * 1000.0, + total_ms=(t_after_worker - start) * 1000.0, + ok=True, + error="", + status_code=200, + t_start=start - t0, + t_end=t_after_worker - t0, + workload=workload)) + + # 3) If so, sample via /get_endpoint_workers/ for eligible (idle) worker tracking + if worker_url: + try: + r_status = route_session.post( + urljoin(server_url, "/get_endpoint_workers/"), + json={"id": endpoint_id}, + headers={"Authorization": f"Bearer {endpoint_api_key}"}, + timeout=3, + ) + if r_status.status_code == 200: + workers = r_status.json() + idle = 0 + for w in workers: + st = str(w.get("status", "")).lower() + if (st in ("idle")): + idle += 1 + status_samples.append((time.time() - t0, idle)) + except Exception: + pass + except Exception as e: + t = time.time() + results_list.append(ReqResult(worker_url="", + route_ms=0.0, + worker_ms=0.0, + total_ms=0.0, + ok=False, + error=f"unknown error {e}", + status_code=0, + t_start=t - t0, + t_end=t - t0, + workload=0.0)) + +def run_load_with_metrics(num_requests: int, + requests_per_second: float, + endpoint_group_name: str, + account_api_key: str, + server_url: str, + worker_endpoint: str, + instance: str, + out_path: str): + + ep_info = Endpoint.get_endpoint_info(endpoint_name=endpoint_group_name, + account_api_key=account_api_key, + instance=instance) + if not ep_info or not ep_info.get("api_key") or not ep_info.get("id"): + print(f"Endpoint {endpoint_group_name} not found for API key") + return + endpoint_id = int(ep_info["id"]) + endpoint_api_key = ep_info["api_key"] + + t0 = time.time() + results = [] + status_samples = [] + max_concurrency = int(os.environ.get("MAX_CONCURRENCY", "8192")) + submit_queue_factor = 2 # cap queued tasks to reduce memory + + # Shared HTTP sessions with connection pooling (persistent connections) + def make_session(pool_connections: int, pool_maxsize: int) -> requests.Session: + sess = requests.Session() + adapter = HTTPAdapter(pool_connections=pool_connections, pool_maxsize=pool_maxsize, max_retries=0) + sess.mount("https://", adapter) + sess.mount("http://", adapter) + return sess + + # Router: mostly single host, small connection pool is sufficient + route_session = make_session(pool_connections=1, pool_maxsize=max_concurrency) + # Workers: many hosts; allow many pools and per-host concurrency up to max_concurrency + worker_session = make_session(pool_connections=64, pool_maxsize=max_concurrency // 8) + + # Fire requests using a thread pool, scheduling at requested RPS + inflight = set() + with ThreadPoolExecutor(max_workers=max_concurrency) as executor: + for i in range(num_requests): + # Pace submissions to RPS + target_time = t0 + i / max(requests_per_second, 1e-9) + sleep_s = target_time - time.time() + if sleep_s > 0: + time.sleep(min(sleep_s, 0.5)) # sleep in chunks to stay responsive + + payload = CompletionsData.for_test() + fut = executor.submit( + do_one, + endpoint_group_name, + endpoint_id, + endpoint_api_key, + server_url, + worker_endpoint, + payload, + results, + t0, + status_samples, + route_session, + worker_session, + ) + inflight.add(fut) + # Prevent unbounded queue growth + if len(inflight) >= max_concurrency * submit_queue_factor: + done, not_done = wait(inflight, return_when=FIRST_COMPLETED) + inflight = not_done + # Wait for all outstanding tasks + if inflight: + wait(inflight) + # Close sessions + try: + route_session.close() + finally: + worker_session.close() + + # Aggregate results + oks = [r for r in results if r.ok] + errs = [r for r in results if not r.ok] + total_reqs = len(results) + succ = len(oks) + + total_ms = np.array([r.total_ms for r in oks]) if succ else np.array([]) + worker_ms = np.array([r.worker_ms for r in oks]) if succ else np.array([]) + route_ms = np.array([r.route_ms for r in oks]) if succ else np.array([]) + + avg_total = float(np.mean(total_ms)) if succ else 0.0 + avg_worker = float(np.mean(worker_ms)) if succ else 0.0 + avg_route = float(np.mean(route_ms)) if succ else 0.0 + p50_total, p95_total = (float(np.percentile(total_ms, 50)), float(np.percentile(total_ms, 95))) if succ else (0.0, 0.0) + + # Distribution over workers (by host:port) + hosts = [urlparse(r.worker_url).netloc for r in oks if r.worker_url] + dist = Counter(hosts) + + # Idle over time (mode per second) + idle_ts, idle_vals = [], [] + if status_samples: + buckets = {} + for ts, idle in status_samples: + k = int(ts) + buckets.setdefault(k, []).append(idle) + keys = sorted(buckets.keys()) + idle_ts = keys + # Use the most frequent sampled value per second (mode) to keep integer counts + idle_vals = [] + for k in keys: + vals_k = [int(v) for v in buckets[k]] + if vals_k: + cnt = Counter(vals_k) + idle_vals.append(cnt.most_common(1)[0][0]) + else: + idle_vals.append(0) + + print(f"\nResults: total={total_reqs} success={succ} errors={len(errs)}") + print(f"Avg latency (ms): {avg_total:.1f} p50: {p50_total:.1f} p95: {p95_total:.1f}") + print(f"Avg route latency (ms): {avg_route:.1f} Avg worker latency (ms): {avg_worker:.1f}") + if errs: + print("Sample errors:") + for e in errs[:5]: + print(f" {e.status_code} {e.error}") + + # Plot: 2x3 grid + fig, axes = plt.subplots(2, 3, figsize=(15, 8)) + fig.suptitle(f"Load test: {endpoint_group_name} n={total_reqs}, rps={requests_per_second}, success={succ}") + + # Dist per worker + ax0 = axes[0, 0] + if dist: + items = sorted(dist.items(), key=lambda kv: kv[1], reverse=True) + labels, counts = zip(*items) + ax0.bar(range(len(labels)), counts) + ax0.set_xticks(range(len(labels))) + ax0.set_xticklabels(labels, rotation=45, ha="right", fontsize=8) + ax0.set_title("Request distribution over workers") + ax0.set_ylabel("count") + + # Latency histogram (total) + ax1 = axes[0, 1] + if succ: + ax1.hist(total_ms, bins=30) + ax1.set_title("Total latency (ms)") + ax1.set_xlabel("ms") + ax1.set_ylabel("freq") + + # Eligible workers over time + ax_idle = axes[0, 2] + if idle_ts: + ax_idle.plot(idle_ts, idle_vals, "-o", ms=3) + ax_idle.set_title("Eligible workers over time") + ax_idle.set_xlabel("time (s)") + ax_idle.set_ylabel("eligible count") + + # Throughput over time (completions/sec) + ax_idle = axes[1, 0] + ax_idle.clear() + if succ: + per_sec = {} + for r in oks: + s = int(r.t_end) + per_sec[s] = per_sec.get(s, 0) + 1 + ts = sorted(per_sec.keys()) + vals = [per_sec[t] for t in ts] + ax_idle.plot(ts, vals, "-o", ms=3) + ax_idle.set_title("Completions per second") + ax_idle.set_xlabel("time (s)") + ax_idle.set_ylabel("completions / sec") + + # Summary text + ax3 = axes[1, 1] + ax3.axis("off") + text = ( + f"Total requests: {total_reqs}\n" + f"Success: {succ} Errors: {len(errs)}\n" + f"Avg total latency: {avg_total:.1f} ms\n" + f"p50: {p50_total:.1f} ms p95: {p95_total:.1f} ms\n" + f"Avg route latency: {avg_route:.1f} ms\n" + f"Avg worker latency: {avg_worker:.1f} ms\n" + f"300 errors: {len([r for r in errs if r.status_code >= 300 and r.status_code < 400])}\n" + f"429 errors: {len([r for r in errs if r.status_code == 429])}\n" + f"500 errors: {len([r for r in errs if r.status_code >= 500])}\n" + f"Other errors: {len([r for r in errs if r.status_code not in [300, 429, 500]])}\n" + ) + ax3.set_title("Summary") + ax3.text(0.02, 0.98, text, va="top", ha="left", fontsize=11, transform=ax3.transAxes) + + # Error count over time + ax_errors = axes[1, 2] + all_end_times = [int(r.t_end) for r in results if r.t_end > 0] + if all_end_times: + min_second = min(all_end_times) + max_second = max(all_end_times) + # Count errors per second + errors_per_second = {} + for result in errs: + second = int(result.t_end) + errors_per_second[second] = errors_per_second.get(second, 0) + 1 + # Create complete timeline including zeros + time_seconds = list(range(min_second, max_second + 1)) + error_counts = [errors_per_second.get(sec, 0) for sec in time_seconds] + ax_errors.plot(time_seconds, error_counts, "-o", ms=3) + ax_errors.set_title("Errors per second") + ax_errors.set_xlabel("time (s)") + ax_errors.set_ylabel("errors / sec") + + # Ensure unique output path and create directory if needed + final_out_path = get_incremented_path(out_path) + out_dir = os.path.dirname(final_out_path) + if out_dir: + os.makedirs(out_dir, exist_ok=True) + + plt.tight_layout(rect=[0, 0, 1, 0.96]) + plt.savefig(final_out_path, dpi=120) + print(f"Saved report to: {final_out_path}") + + # Per-worker latency boxplot (top 12 by volume) + groups = {} + for r in oks: + host = urlparse(r.worker_url).netloc + groups.setdefault(host, []).append(r.total_ms) + items = sorted(groups.items(), key=lambda kv: len(kv[1]), reverse=True)[:12] + if items: + labels, data = zip(*items) + fig2, axb = plt.subplots(1, 1, figsize=(12, 5)) + axb.boxplot(data, showfliers=False) + axb.set_xticklabels(labels, rotation=45, ha="right", fontsize=8) + axb.set_title("Per-worker latency (ms)") + axb.set_ylabel("ms") + plt.tight_layout() + extra_out = get_incremented_path(os.path.splitext(out_path)[0] + "-workers.png") + plt.savefig(extra_out, dpi=120) + fig2.tight_layout() + fig2.savefig(extra_out, dpi=120) + print(f"Saved worker latency plot to: {extra_out}") if __name__ == "__main__": # Check if MODEL_NAME environment variable is set @@ -16,13 +403,32 @@ if __name__ == "__main__": help="Model to use for completions request (required if MODEL_NAME env var not set)", ) - # Parse known args to get model early, before test_load_cmd adds its args + # Parse known args to get model early, before adding load args known_args, _ = test_args.parse_known_args() - - # Set environment variable if model was provided if hasattr(known_args, "model") and known_args.model: os.environ["MODEL_NAME"] = known_args.model print(f"Set MODEL_NAME environment variable to: {known_args.model}") - # Now call test_load_cmd normally - it will add its own args and re-parse - test_load_cmd(CompletionsData, WORKER_ENDPOINT, arg_parser=test_args) + # Load test args + test_args.add_argument("-n", dest="num_requests", type=int, required=True, help="total number of requests") + test_args.add_argument("-rps", dest="requests_per_second", type=float, required=True, help="requests per second") + test_args.add_argument("--out", dest="out_path", type=str, default="load_test_report.png", help="path to save the report image") + args = test_args.parse_args() + + server_url = { + "prod": "https://run.vast.ai", + "alpha": "https://run-alpha.vast.ai", + "candidate": "https://run-candidate.vast.ai", + "local": "http://localhost:8080" + }.get(args.instance, "http://localhost:8080") + + run_load_with_metrics( + num_requests=args.num_requests, + requests_per_second=args.requests_per_second, + endpoint_group_name=args.endpoint_group_name, + account_api_key=args.api_key, + server_url=server_url, + worker_endpoint=WORKER_ENDPOINT, + instance=args.instance, + out_path=args.out_path, + ) \ No newline at end of file