Add worker.pys

This commit is contained in:
Lucas Armand
2025-11-25 13:33:12 -08:00
parent 0339b471c5
commit 2ce0450809
5 changed files with 256 additions and 3 deletions
+1 -1
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@@ -8,4 +8,4 @@ Requests~=2.32
transformers~=4.52
utils==1.0.*
hf_transfer>=0.1.9
vastai-sdk>=0.2.0
git+https://github.com/vast-ai/vast-sdk.git@worker-sdk
+12 -1
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@@ -133,8 +133,19 @@ cd "$SERVER_DIR"
echo "launching PyWorker server"
set +e
python3 -m "workers.$BACKEND.server" |& tee -a "$PYWORKER_LOG"
# Try worker entrypoint first
echo "trying workers.${BACKEND}.worker"
python3 -m "workers.${BACKEND}.worker" |& tee -a "$PYWORKER_LOG"
PY_STATUS=${PIPESTATUS[0]}
# If that fails, fall back to server
if [ "${PY_STATUS}" -ne 0 ]; then
echo "workers.${BACKEND}.worker failed with status ${PY_STATUS}, trying workers.${BACKEND}.server"
python3 -m "workers.${BACKEND}.server" |& tee -a "$PYWORKER_LOG"
PY_STATUS=${PIPESTATUS[0]}
fi
set -e
if [ "${PY_STATUS}" -ne 0 ]; then
+84
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@@ -0,0 +1,84 @@
import random
import sys
from vastai import Worker, WorkerConfig, HandlerConfig, LogActionConfig, BenchmarkConfig
# ComyUI model configuration
MODEL_SERVER_URL = 'http://127.0.0.1'
MODEL_SERVER_PORT = 18288
MODEL_LOG_FILE = '/var/log/portal/comfyui.log'
MODEL_HEALTHCHECK_ENDPOINT = "/health"
# ComyUI-specific log messages
MODEL_LOAD_LOG_MSG = [
"To see the GUI go to: "
]
MODEL_ERROR_LOG_MSGS = [
"MetadataIncompleteBuffer",
"Value not in list: ",
"[ERROR] Provisioning Script failed"
]
MODEL_INFO_LOG_MSGS = [
'"message":"Downloading'
]
benchmark_prompts = [
"Cartoon hoodie hero; orc, anime cat, bunny; black goo; buff; vector on white.",
"Cozy farming-game scene with fine details.",
"2D vector child with soccer ball; airbrush chrome; swagger; antique copper.",
"Realistic futuristic downtown of low buildings at sunset.",
"Perfect wave front view; sunny seascape; ultra-detailed water; artful feel.",
"Clear cup with ice, fruit, mint; creamy swirls; fluid-sim CGI; warm glow.",
"Male biker with backpack on motorcycle; oilpunk; award-worthy magazine cover.",
"Collage for textile; surreal cartoon cat in cap/jeans before poster; crisp.",
"Medieval village inside glass sphere; volumetric light; macro focus.",
"Iron Man with glowing axe; mecha sci-fi; jungle scene; dynamic light.",
"Pope Francis DJ in leather jacket, mixing on giant console; dramatic.",
]
def parse_request(json_msg):
return {"input" : json_msg}
benchmark_dataset = [
{
"input": {
"request_id": f"test-{random.randint(1000, 99999)}",
"modifier": "Text2Image",
"modifications": {
"prompt": prompt,
"width": 512,
"height": 512,
"steps": 20,
"seed": random.randint(0, sys.maxsize)
}
}
} for prompt in benchmark_prompts
]
worker_config = WorkerConfig(
model_server_url=MODEL_SERVER_URL,
model_server_port=MODEL_SERVER_PORT,
model_log_file=MODEL_LOG_FILE,
model_healthcheck_url=MODEL_HEALTHCHECK_ENDPOINT,
handlers=[
HandlerConfig(
route="/generate/sync",
allow_parallel_requests=False,
max_queue_time=10.0,
request_parser=parse_request,
benchmark_config=BenchmarkConfig(
dataset=benchmark_dataset,
)
)
],
log_action_config=LogActionConfig(
on_load=MODEL_LOAD_LOG_MSG,
on_error=MODEL_ERROR_LOG_MSGS,
on_info=MODEL_INFO_LOG_MSGS
)
)
Worker(worker_config).run()
+77
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@@ -0,0 +1,77 @@
import nltk
import random
import os
from vastai import Worker, WorkerConfig, HandlerConfig, LogActionConfig, BenchmarkConfig
# vLLM model configuration
MODEL_SERVER_URL = 'http://127.0.0.1'
MODEL_SERVER_PORT = 18000
MODEL_LOG_FILE = '/var/log/portal/vllm.log'
MODEL_HEALTHCHECK_ENDPOINT = "/health"
# vLLM-specific log messages
MODEL_LOAD_LOG_MSG = [
"Application startup complete.",
]
MODEL_ERROR_LOG_MSGS = [
"INFO exited: vllm",
"RuntimeError: Engine",
"Traceback (most recent call last):"
]
MODEL_INFO_LOG_MSGS = [
'"message":"Download'
]
nltk.download("words")
WORD_LIST = nltk.corpus.words.words()
def completions_benchmark_generator() -> dict:
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")
benchmark_data = {
"model": model,
"prompt": prompt,
"temperature": 0.7,
"max_tokens": 500,
}
return benchmark_data
worker_config = WorkerConfig(
model_server_url=MODEL_SERVER_URL,
model_server_port=MODEL_SERVER_PORT,
model_log_file=MODEL_LOG_FILE,
model_healthcheck_url=MODEL_HEALTHCHECK_ENDPOINT,
handlers=[
HandlerConfig(
route="/v1/completions",
workload_calculator= lambda data: data.get("max_tokens", 0),
allow_parallel_requests=True,
max_queue_time=60.0,
benchmark_config=BenchmarkConfig(
generator=completions_benchmark_generator,
concurrency=100
)
),
HandlerConfig(
route="/v1/chat/completions",
workload_calculator= lambda data: data.get("max_tokens", 0),
allow_parallel_requests=True,
max_queue_time=60.0,
)
],
log_action_config=LogActionConfig(
on_load=MODEL_LOAD_LOG_MSG,
on_error=MODEL_ERROR_LOG_MSGS,
on_info=MODEL_INFO_LOG_MSGS
)
)
Worker(worker_config).run()
+81
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@@ -0,0 +1,81 @@
import nltk
import random
from vastai import Worker, WorkerConfig, HandlerConfig, LogActionConfig, BenchmarkConfig
# TGI model configuration
MODEL_SERVER_URL = 'http://0.0.0.0'
MODEL_SERVER_PORT = 5001
MODEL_LOG_FILE = "/workspace/infer.log"
MODEL_HEALTHCHECK_ENDPOINT = "/health"
# TGI-specific log messages
MODEL_LOAD_LOG_MSG = [
'"message":"Connected","target":"text_generation_router"',
'"message":"Connected","target":"text_generation_router::server"',
]
MODEL_ERROR_LOG_MSGS = [
"Error: WebserverFailed",
"Error: DownloadError",
"Error: ShardCannotStart",
]
MODEL_INFO_LOG_MSGS = [
'"message":"Download'
]
nltk.download("words")
WORD_LIST = nltk.corpus.words.words()
def benchmark_generator() -> dict:
prompt = " ".join(random.choices(WORD_LIST, k=int(250)))
benchmark_data = {
"inputs": prompt,
"parameters": {
"max_new_tokens": 128,
"temperature": 0.7,
"return_full_text": False
}
}
return benchmark_data
def parse_request(json_msg):
return {"input" : json_msg}
worker_config = WorkerConfig(
model_server_url=MODEL_SERVER_URL,
model_server_port=MODEL_SERVER_PORT,
model_log_file=MODEL_LOG_FILE,
model_healthcheck_url=MODEL_HEALTHCHECK_ENDPOINT,
handlers=[
HandlerConfig(
route="/generate",
allow_parallel_requests=True,
max_queue_time=60.0,
request_parser=parse_request,
benchmark_config=BenchmarkConfig(
generator=benchmark_generator,
concurrency=50
),
workload_calculator= lambda x: x["parameters"]["max_new_tokens"]
),
HandlerConfig(
route="/generate_stream",
allow_parallel_requests=True,
max_queue_time=60.0,
request_parser=parse_request,
workload_calculator= lambda x: x["parameters"]["max_new_tokens"]
)
],
log_action_config=LogActionConfig(
on_load=MODEL_LOAD_LOG_MSG,
on_error=MODEL_ERROR_LOG_MSGS,
on_info=MODEL_INFO_LOG_MSGS
)
)
Worker(worker_config).run()