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44 Commits

Author SHA1 Message Date
Lucas Armand a7617162a7 spelling fix 2025-10-15 15:09:34 -07:00
Lucas Armand d8f51a2edc updated startserver 2025-10-15 12:14:31 -07:00
Lucas Armand ee57ed207b stat script 2025-10-14 17:38:06 -07:00
LucasArmandVast c98d661513 Merge pull request #39 from vast-ai/remove-time-divide
PyWorker fixes for cur_load and acks bug
2025-10-13 10:06:22 -07:00
Lucas Armand f6fd1c6ac1 merge 2025-10-09 18:15:55 -07:00
Lucas Armand 055e346c8c Send metrics on request start 2025-10-09 10:13:50 -07:00
Lucas Armand 1cedb28acf Removed division by elapsed time, since autoscaler cur_load in units of workload 2025-10-08 16:54:18 -07:00
Colter-Downing 0397af719d Merge pull request #37 from robballantyne/bugfix/healthcheck-endpoint
Fix healthcheck endpoint URL

Tested and merged by Colter
2025-10-06 15:11:27 -07:00
Rob Ballantyne 4fdc314fd9 Fix healthcheck endpoint URL 2025-10-06 22:16:09 +01:00
Colter-Downing 639d82f5b4 Merge pull request #35 from vast-ai/AUTO-664--Healthcheck-error
Fix healthcheck with separate session
2025-10-02 12:51:19 -07:00
Colter Downing 25db78e39d Fix healthcheck with separate session 2025-10-01 18:04:31 -07:00
Scott-Laytart 4e2f2311d0 Merge pull request #33 from vast-ai/comfy-blind-fix-override
undo the fix for comfy yesterday.
2025-09-03 11:50:07 -07:00
abiola-vastai 38782d89bc undo the fix for comfy yesterday. 2025-09-03 17:12:35 +00:00
Scott-Laytart 0185216ccb Merge pull request #32 from vast-ai/blindhotfix_comfy_ui_default_port
Blind hotfix to see if comfy UI default is needed. if it does work we…
2025-09-02 18:26:25 -07:00
abiola-vastai b20d9e714c Blind hotfix to see if comfy UI default is needed. if it does work we would revert back. 2025-09-03 01:20:09 +00:00
Rob Ballantyne b1eb65d75d Merge pull request #31 from vast-ai/bugfix/startup-script-20250901
Update uv venv creation command
2025-09-01 18:19:17 +01:00
Rob Ballantyne 1d09d7fe96 Update uv venv creation command 2025-09-01 16:55:20 +01:00
Colter-Downing 1b37054dec Merge pull request #28 from vast-ai/bugfix/backend-timeout-infinite
Bugfix/backend timeout infinite
2025-08-28 11:22:33 -07:00
Colter-Downing 1a1e4174b8 Merge pull request #29 from vast-ai/bugfix/comfyui-json-cost-fix
Set cost to 100
2025-08-28 11:22:21 -07:00
Rob Ballantyne b8377c4081 Set cost to 100 2025-08-28 16:13:17 +01:00
Rob Ballantyne 1e4fa87437 Prevent timeout and allow long running connections 2025-08-28 15:48:57 +01:00
Rob Ballantyne 4c5fa03c7b adds import for ClientTimeout 2025-08-27 20:54:27 +01:00
Rob Ballantyne a8fe74f771 Remove default 300s timeout 2025-08-27 18:34:45 +01:00
Rob Ballantyne b482de8394 Merge pull request #27 from vast-ai/feat/comfyui-api-s3-webhook
Adds new ComfyUI worker

Upload assets to s3 compatible storage via intermediate API wrapper
2025-08-26 14:22:05 +01:00
Rob Ballantyne 703435d10e Improve MODEL_SERVER_START_* messages 2025-08-26 12:42:04 +01:00
Rob Ballantyne 947fc5eea4 Improve benchmarking explanation 2025-08-26 12:41:30 +01:00
Rob Ballantyne 7c1a544b19 Improve error reporting when no ready workers 2025-08-26 12:41:05 +01:00
Rob Ballantyne 16b414676e Use count_workload() function for cost 2025-08-25 18:31:10 +01:00
Rob Ballantyne ba74ac8136 Use cost value 1 for all jobs 2025-08-25 17:58:22 +01:00
Rob Ballantyne 92ff412679 Use MODEL_SERVER_URL environment variable 2025-08-25 17:57:32 +01:00
Rob Ballantyne fc75a64684 Use MODEL_SERVER_URL environment variable 2025-08-25 17:56:27 +01:00
Rob Ballantyne b00bef547c Ensure uv env script is present before sourcing 2025-08-22 17:08:42 +01:00
Rob Ballantyne 3f4acb29fa Improved client exception handling 2025-08-22 15:20:15 +01:00
Rob Ballantyne 58b078f908 Fix modifier class 2025-08-20 18:06:02 +01:00
Rob Ballantyne f9fdf04884 Fix signature 2025-08-20 13:27:29 +01:00
Rob Ballantyne 636f17d27f Fix workflow modifier class 2025-08-20 09:57:07 +01:00
Rob Ballantyne 08c88f7527 Improve testability 2025-08-20 09:34:09 +01:00
Rob Ballantyne 8797b504af Initial ComfyUI implementation with updated wrapper 2025-08-19 17:59:20 +01:00
Nader Arbabian cd946b0a9f update report_addr to use new webserver endpoint with AS fallback 2025-08-12 13:31:19 -07:00
Nader Arbabian c595b42410 for benchmarking, use concurrent requests (#26) 2025-08-11 12:39:28 -07:00
Nader Arbabian 0bf3247a34 fix completions and interactive client 2025-08-11 12:37:53 -07:00
Nader Arbabian 52ac4c0c1a fix endpoint_util not using the correct instance's endpoint 2025-08-11 12:05:58 -07:00
Nader Arbabian 8804e17201 download vast.ai's root certificate in order to make pyworker requests (#25) 2025-08-08 17:04:16 -07:00
Nader Arbabian 4016cf9a53 redo metrics tracking for requests, fixes bug wherere some requests were marked as pending, even though they had finished (#24) 2025-08-08 17:01:21 -07:00
17 changed files with 766 additions and 70 deletions
+59 -31
View File
@@ -11,7 +11,7 @@ from functools import cached_property
from distutils.util import strtobool
from anyio import open_file
from aiohttp import web, ClientResponse, ClientSession, ClientConnectorError
from aiohttp import web, ClientResponse, ClientSession, ClientConnectorError, ClientTimeout, TCPConnector
import requests
from Crypto.Signature import pkcs1_15
@@ -75,7 +75,13 @@ class Backend:
@cached_property
def session(self):
log.debug(f"starting session with {self.model_server_url}")
return ClientSession(self.model_server_url)
connector = TCPConnector(
force_close=True, # Required for long running jobs
enable_cleanup_closed=True,
)
timeout = ClientTimeout(total=None)
return ClientSession(self.model_server_url, timeout=timeout, connector=connector)
def create_handler(
self,
@@ -184,18 +190,30 @@ class Backend:
log.debug(f"Exception in main handler loop {e}")
return web.Response(status=500)
@cached_property
def healthcheck_session(self):
"""Dedicated session for healthchecks to avoid conflicts with API session"""
log.debug("creating dedicated healthcheck session")
connector = TCPConnector(
force_close=True, # Keep this for isolation
enable_cleanup_closed=True,
)
timeout = ClientTimeout(total=10) # Reasonable timeout for healthchecks
return ClientSession(timeout=timeout, connector=connector)
async def __healthcheck(self):
health_check_url = self.benchmark_handler.healthcheck_endpoint
if health_check_url is None:
log.debug("No healthcheck endpoint defined, skipping healthcheck")
return
while True:
await sleep(10)
if self.__start_healthcheck is False:
continue
try:
log.debug(f"Performing healthcheck on {health_check_url}")
async with self.session.get(health_check_url) as response:
async with self.healthcheck_session.get(health_check_url) as response:
if response.status == 200:
log.debug("Healthcheck successful")
elif response.status == 503:
@@ -204,7 +222,6 @@ class Backend:
f"Healthcheck failed with status: {response.status}"
)
else:
# endpoint not ready yet so bail
log.debug(f"Healthcheck Endpoint not ready: {response.status}")
except Exception as e:
log.debug(f"Healthcheck failed with exception: {e}")
@@ -280,41 +297,52 @@ class Backend:
return float(f.readline())
except FileNotFoundError:
pass
log.debug("Initial run to trigger model loading...")
payload = self.benchmark_handler.make_benchmark_payload()
await self.__call_api(handler=self.benchmark_handler, payload=payload)
max_throughput = 0
last_throughput = 0
sum_throughput = 0
for run in range(self.benchmark_handler.benchmark_runs + 1):
concurrent_requests = 10 if self.allow_parallel_requests else 1
for run in range(1, self.benchmark_handler.benchmark_runs + 1):
start = time.time()
payload = self.benchmark_handler.make_benchmark_payload()
res = await self.__call_api(
handler=self.benchmark_handler, payload=payload
)
data = await res.json()
time_elapsed = time.time() - start
# first run triggers one-time loading of the model which is very slow, so we skip counting it
if run == 0:
continue
else:
workload = payload.count_workload()
last_throughput = workload / time_elapsed
sum_throughput += last_throughput
max_throughput = max(max_throughput, last_throughput)
log.debug(
"\n".join(
[
"#" * 60,
f"Run: {run}, workload: {workload} time_elapsed: {time_elapsed}, throughput: {last_throughput}",
"",
f"response: {data}",
"#" * 60,
]
)
tasks = []
total_workload = 0
for _ 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)
)
responses = await gather(*tasks)
time_elapsed = time.time() - start
throughput = total_workload / time_elapsed
sum_throughput += throughput
max_throughput = max(max_throughput, throughput)
# Log results for debugging
log.debug(
"\n".join(
[
"#" * 60,
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])}",
"#" * 60,
]
)
)
average_throughput = sum_throughput / self.benchmark_handler.benchmark_runs
log.debug(
f"benchmark result: avg {average_throughput} workload per second, max {max_throughput}"
)
# save max_throughput so we don't have to run benchmark again on restart of cold instances
with open(BENCHMARK_INDICATOR_FILE, "w") as f:
f.write(str(max_throughput))
return max_throughput
+14 -8
View File
@@ -45,6 +45,7 @@ class Metrics:
self.model_metrics.workload_received += workload
self.model_metrics.requests_recieved.add(reqnum)
self.model_metrics.requests_working.add(reqnum)
self.update_pending = True
def _request_end(self, workload: float, reqnum: int) -> None:
"""
@@ -78,10 +79,10 @@ class Metrics:
elapsed = time.time() - self.last_metric_update
if self.system_metrics.model_is_loaded is False and elapsed >= 10:
log.debug(f"sending loading model metrics after {int(elapsed)}s wait")
self.__send_metrics_and_reset(elapsed)
self.__send_metrics_and_reset()
elif self.update_pending or elapsed > 10:
log.debug(f"sending loaded model metrics after {int(elapsed)}s wait")
self.__send_metrics_and_reset(elapsed)
self.__send_metrics_and_reset()
def _model_loaded(self, max_throughput: float) -> None:
self.system_metrics.model_loading_time = (
@@ -96,13 +97,13 @@ class Metrics:
#######################################Private#######################################
def __send_metrics_and_reset(self, elapsed):
def __send_metrics_and_reset(self):
def compute_autoscaler_data() -> AutoScalaerData:
return AutoScalaerData(
id=self.id,
loadtime=(self.system_metrics.model_loading_time or 0.0),
cur_load=(self.model_metrics.workload_processing / elapsed),
cur_load=(self.model_metrics.workload_processing),
max_perf=self.model_metrics.max_throughput,
cur_perf=self.model_metrics.cur_perf,
error_msg=self.model_metrics.error_msg or "",
@@ -114,7 +115,7 @@ class Metrics:
url=self.url,
)
def send_data(report_addr: str) -> None:
def send_data(report_addr: str) -> bool:
data = compute_autoscaler_data()
full_path = report_addr.rstrip("/") + "/worker_status/"
log.debug(
@@ -129,21 +130,26 @@ class Metrics:
)
for attempt in range(1, 4):
try:
requests.post(full_path, json=asdict(data), timeout=1)
break
res = requests.post(full_path, json=asdict(data), timeout=1)
res.raise_for_status()
return True
except requests.Timeout:
log.debug(f"autoscaler status update timed out")
except Exception as e:
log.debug(f"autoscaler status update failed with error: {e}")
time.sleep(2)
log.debug(f"retrying autoscaler status update, attempt: {attempt}")
log.debug(f"failed to send update through {report_addr}")
return False
###########
self.system_metrics.update_disk_usage()
for report_addr in self.report_addr:
send_data(report_addr)
success = send_data(report_addr)
if success is True:
break
self.update_pending = False
self.model_metrics.reset()
self.system_metrics.reset()
+3
View File
@@ -10,6 +10,7 @@ from collections import Counter
from dataclasses import dataclass, field, asdict
from urllib.parse import urljoin
from utils.endpoint_util import Endpoint
from utils.ssl import get_cert_file_path
import requests
from lib.data_types import AuthData, ApiPayload
@@ -120,9 +121,11 @@ class ClientState:
self.url = worker_address
url = urljoin(worker_address, self.worker_endpoint)
self.status = ClientStatus.Generating
response = requests.post(
url,
json=req_data,
verify=get_cert_file_path(),
)
if response.status_code != 200:
self.infer_error.append(
+54 -24
View File
@@ -3,13 +3,12 @@
set -e -o pipefail
WORKSPACE_DIR="${WORKSPACE_DIR:-/workspace}"
SERVER_DIR="$WORKSPACE_DIR/vast-pyworker"
SERVER_DIR="$WORKSPACE_DIR/worker"
ENV_PATH="$WORKSPACE_DIR/worker-env"
DEBUG_LOG="$WORKSPACE_DIR/debug.log"
PYWORKER_LOG="$WORKSPACE_DIR/pyworker.log"
REPORT_ADDR="${REPORT_ADDR:-https://run.vast.ai}"
REPORT_ADDR="${REPORT_ADDR:-https://cloud.vast.ai/api/v0,https://run.vast.ai}"
USE_SSL="${USE_SSL:-true}"
WORKER_PORT="${WORKER_PORT:-3000}"
mkdir -p "$WORKSPACE_DIR"
@@ -22,49 +21,82 @@ function echo_var(){
echo "$1: ${!1}"
}
[ -z "$BACKEND" ] && echo "BACKEND must be set!" && exit 1
# Updated validation - BACKEND no longer required, but MODEL_LOG still is
[ -z "$MODEL_LOG" ] && echo "MODEL_LOG must be set!" && exit 1
[ -z "$HF_TOKEN" ] && echo "HF_TOKEN must be set!" && exit 1
[ "$BACKEND" = "comfyui" ] && [ -z "$COMFY_MODEL" ] && echo "For comfyui backends, COMFY_MODEL must be set!" && exit 1
echo "start_server.sh"
echo "start_server.sh - SDK Worker Version"
date
echo_var BACKEND
echo_var REPORT_ADDR
echo_var WORKER_PORT
echo_var WORKSPACE_DIR
echo_var SERVER_DIR
echo_var ENV_PATH
echo_var DEBUG_LOG
echo_var PYWORKER_LOG
echo_var MODEL_LOG
echo_var MODEL_SERVER_URL
echo_var PYWORKER_REPO
echo_var PYWORKER_REF
env | grep _ >> /etc/environment;
# Populate /etc/environment with quoted values
if ! grep -q "VAST" /etc/environment; then
env -0 | grep -zEv "^(HOME=|SHLVL=)|CONDA" | while IFS= read -r -d '' line; do
name=${line%%=*}
value=${line#*=}
printf '%s="%s"\n' "$name" "$value"
done > /etc/environment
fi
if [ ! -d "$ENV_PATH" ]
then
echo "setting up venv"
curl -LsSf https://astral.sh/uv/install.sh | sh
source ~/.local/bin/env
git clone https://github.com/vast-ai/pyworker "$SERVER_DIR"
if ! which uv; then
curl -LsSf https://astral.sh/uv/install.sh | sh
source ~/.local/bin/env
fi
uv venv --managed-python "$WORKSPACE_DIR/worker-env" -p 3.10
source "$WORKSPACE_DIR/worker-env/bin/activate"
if [[ ! -d $SERVER_DIR ]]; then
echo "Cloning worker repository..."
git clone --depth=1 "${PYWORKER_REPO:-https://github.com/vast-ai/pyworker}" "$SERVER_DIR"
fi
uv pip install -r vast-pyworker/requirements.txt
if [[ -n ${PYWORKER_REF:-} ]]; then
echo "Checking out ref: $PYWORKER_REF"
(
cd "$SERVER_DIR"
git fetch --depth=1 origin "$PYWORKER_REF"
git checkout "$PYWORKER_REF"
)
fi
uv venv --python-preference only-managed "$ENV_PATH" -p 3.10
source "$ENV_PATH/bin/activate"
# Install vast-sdk from server-side-sdk branch
echo "Installing vast-sdk from GitHub (server-side-sdk branch)..."
uv pip install "git+https://github.com/vast-ai/vast-sdk.git@server-side-sdk"
# Install requirements from worker repo if they exist
if [ -f "${SERVER_DIR}/requirements.txt" ]; then
echo "Installing additional dependencies from requirements.txt..."
uv pip install -r "${SERVER_DIR}/requirements.txt"
fi
touch ~/.no_auto_tmux
else
source ~/.local/bin/env
[[ -f ~/.local/bin/env ]] && source ~/.local/bin/env
source "$WORKSPACE_DIR/worker-env/bin/activate"
echo "environment activated"
echo "venv: $VIRTUAL_ENV"
fi
[ ! -d "$SERVER_DIR/workers/$BACKEND" ] && echo "$BACKEND not supported!" && exit 1
# Check that worker.py exists
if [ ! -f "$SERVER_DIR/worker.py" ]; then
echo "ERROR: worker.py not found in $SERVER_DIR"
echo "Please ensure your PYWORKER_REPO contains a worker.py file"
exit 1
fi
if [ "$USE_SSL" = true ]; then
@@ -102,9 +134,6 @@ EOF
POST "https://console.vast.ai/api/v0/sign_cert/?instance_id=$CONTAINER_ID" > /etc/instance.crt;
fi
export REPORT_ADDR WORKER_PORT USE_SSL UNSECURED
cd "$SERVER_DIR"
@@ -115,5 +144,6 @@ echo "launching PyWorker server"
# from the run prior to reboot. past logs are saved in $MODEL_LOG.old for debugging only
[ -e "$MODEL_LOG" ] && cat "$MODEL_LOG" >> "$MODEL_LOG.old" && : > "$MODEL_LOG"
(python3 -m "workers.$BACKEND.server" |& tee -a "$PYWORKER_LOG") &
echo "launching PyWorker server done"
# Launch the SDK-based worker instead of the old backend system
(python3 worker.py |& tee -a "$PYWORKER_LOG") &
echo "launching PyWorker server done"
+20 -2
View File
@@ -16,6 +16,24 @@ class Endpoint:
Utility class for handling endpoint operations.
"""
@staticmethod
def get_autoscaler_server_url(instance: str) -> str:
endpoints = {
"alpha": "run-alpha",
"candidate": "run-candidate",
"prod": "run",
}
return f"https://{endpoints[instance]}.vast.ai/"
@staticmethod
def get_server_url(instance: str) -> str:
endpoints = {
"alpha": "alpha",
"candidate": "candidate",
"prod": "console",
}
return f"https://{endpoints[instance]}.vast.ai/api/v0/endptjobs/"
@staticmethod
def get_endpoint_api_key(
endpoint_name: str, account_api_key: str, instance: str
@@ -30,13 +48,13 @@ class Endpoint:
Returns:
Endpoint API key if successful, None otherwise
"""
vast_console_url = "https://console.vast.ai/api/v0/endptjobs/"
headers = {"Authorization": f"Bearer {account_api_key}"}
try:
log.debug(f"Fetching endpoint API key for endpoint: {endpoint_name}")
response = requests.get(
f"{vast_console_url}?autoscaler_instance={instance}", headers=headers
f"{Endpoint.get_server_url(instance)}?autoscaler_instance={instance}",
headers=headers,
)
if response.status_code != 200:
+15
View File
@@ -0,0 +1,15 @@
import tempfile
from functools import cache
import requests
@cache
def get_cert_file_path():
cert_url = "https://console.vast.ai/static/jvastai_root.cer"
response = requests.get(cert_url)
response.raise_for_status()
# Use a temporary file that is not deleted on close
with tempfile.NamedTemporaryFile(delete=False, suffix=".cer", mode="wb") as f:
f.write(response.content)
return f.name
+210
View File
@@ -0,0 +1,210 @@
# ComfyUI PyWorker
This is the base PyWorker for ComfyUI. It provides a unified interface for running any ComfyUI workflow through a proxy-based architecture.
The cost for each request has a static value of `1`. ComfyUI does not handle concurrent workloads and there is no current provision to load multiple instances of ComfyUI per worker node.
## Requirements
This worker requires both [ComfyUI](https://github.com/comfyanonymous/ComfyUI) and [ComfyUI API Wrapper](https://github.com/ai-dock/comfyui-api-wrapper).
A docker image is provided but you may use any if the above requirements are met.
## Benchmarking
A simple image generation benchmark runs when each worker initializes to validate GPU performance and identify underperforming machines.
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 |
| -------------------- | ------------- | ----------- |
| BENCHMARK_TEST_WIDTH | 512 | Image width (pixels) |
| BENCHMARK_TEST_HEIGHT | 512 | Image height (pixels) |
| BENCHMARK_TEST_STEPS | 20 | Number of denoising steps |
Each benchmark run uses a random prompt from `misc/test_prompts.txt` and a random seed to ensure consistent GPU load patterns.
### 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.
**Example:** If your typical workflow should complete in 90 seconds on acceptable hardware:
```bash
# 1. Measure it/sec on your reference machine
# RTX 4090 typically achieves ~43 it/sec with SD1.5
# 2. Calculate required steps
# 90 seconds × 43 it/sec = 3870 steps
# 3. Configure benchmark
export BENCHMARK_TEST_STEPS=3870
# 4. Machines completing significantly slower than 90s indicate hardware issues
```
**Performance expectations:**
- Benchmark duration should remain consistent across identical GPU models
- Significant variation (>20%) may indicate thermal, power, or configuration issues
## Endpoint
The worker provides a single endpoint:
- `/generate/sync`: Processes ComfyUI workflows using either predefined modifiers or custom workflow JSON
## Request Format
The worker accepts requests in the following format. Choose either modifier mode OR custom workflow mode:
**Modifier Mode:**
```json
{
"input": {
"request_id": "uuid-string", // optional - UUID generated if not provided
"modifier": "RawWorkflow",
"modifications": {
"prompt": "a beautiful landscape",
"width": 1024,
"height": 1024,
"steps": 20,
"seed": 123456789
},
"s3": { ... }, // optional
"webhook": { ... } // optional
}
}
```
**Custom Workflow Mode:**
```json
{
"input": {
"request_id": "uuid-string", // optional - UUID generated if not provided
"workflow_json": {
// Complete ComfyUI workflow JSON
},
"s3": { ... }, // optional
"webhook": { ... } // optional
}
}
```
## Request Fields
### Required Fields
- **`input`**: Contains the main workflow data
- **`input.request_id`**: Unique identifier for the request
### Workflow Mode (Choose One)
You must provide either `modifier` OR `workflow_json`, but not both:
#### Option 1: Modifier Mode
- **`input.modifier`**: Name of the predefined workflow modifier (e.g., "Text2Image")
- **`input.modifications`**: Parameters to pass to the modifier
#### Option 2: Custom Workflow Mode
- **`input.workflow_json`**: Complete ComfyUI workflow JSON
### Optional Fields
- **`input.s3`**: S3 configuration for file storage
- **`input.webhook`**: Webhook configuration for notifications
These configurations can be provided in the request JSON or via environment variables. Request-level configuration takes precedence over environment variables.
#### S3 Configuration
**Via Request JSON:**
```json
"s3": {
"access_key_id": "your-s3-access-key",
"secret_access_key": "your-s3-secret-access-key",
"endpoint_url": "https://my-endpoint.backblaze.com",
"bucket_name": "your-bucket",
"region": "us-east-1"
}
```
**Via Environment Variables:**
```bash
S3_ACCESS_KEY_ID=your-key
S3_SECRET_ACCESS_KEY=your-secret
S3_BUCKET_NAME=your-bucket
S3_ENDPOINT_URL=https://s3.amazonaws.com
S3_REGION=us-east-1
```
#### Webhook Configuration
**Via Request JSON:**
```json
"webhook": {
"url": "your-webhook-url",
"extra_params": {
"custom_field": "value"
}
}
```
**Via Environment Variables:**
```bash
WEBHOOK_URL=https://your-webhook.com # Default webhook URL
WEBHOOK_TIMEOUT=30 # Webhook timeout in seconds
```
## Examples
### Basic Text-to-Image (Modifier Mode)
```json
{
"input": {
"modifier": "Text2Image",
"modifications": {
"prompt": "a cat sitting on a windowsill",
"width": 512,
"height": 512,
"steps": 20,
"seed": 42
}
}
}
```
### Custom Workflow Mode
```json
{
"input": {
"request_id": "67890", // optional - using custom ID for tracking
"workflow_json": {
"3": {
"inputs": {
"seed": 42,
"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"
}
}
}
}
```
## Client Libraries
See the test client examples for implementation details on how to integrate with the ComfyUI worker.
---
See Vast's serverless documentation for more details on how to use ComfyUI with autoscaler.
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+155
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@@ -0,0 +1,155 @@
import logging
import uuid
import random
from urllib.parse import urljoin
import json
import requests
from lib.test_utils import print_truncate_res
from utils.endpoint_util import Endpoint
from utils.ssl import get_cert_file_path
from .data_types import count_workload
logging.basicConfig(
level=logging.DEBUG,
format="%(asctime)s[%(levelname)-5s] %(message)s",
datefmt="%Y-%m-%d %H:%M:%S",
)
log = logging.getLogger(__file__)
def call_text2image_workflow(
endpoint_group_name: str, api_key: str, server_url: str
) -> None:
"""Simple Text2Image using the new modifier-based approach"""
def make_request(url: str, payload: dict, timeout: int = None, verify=True, context: str = "request"):
"""Helper function for making requests with consistent error handling"""
try:
response = requests.post(
url,
json=payload,
timeout=timeout,
verify=verify
)
response.raise_for_status()
return response.json()
except requests.exceptions.HTTPError as http_err:
log.error(f"HTTP error occurred during {context}: {http_err}")
log.error(f"Status Code: {response.status_code}")
log.error("Response content:", response.text)
return None
except requests.exceptions.Timeout:
log.error(f"Timeout occurred during {context}: {url}")
return None
except requests.exceptions.ConnectionError:
log.error(f"Connection error occurred during {context}: {url}")
return None
except json.JSONDecodeError as json_err:
log.error(f"Failed to decode JSON response during {context}: {json_err}")
if 'response' in locals():
print("Response content:", response.text)
return None
except Exception as err:
log.error(f"An unexpected error occurred during {context}: {err}")
if 'response' in locals():
log.error("Response content (if available):", response.text)
return None
WORKER_ENDPOINT = "/generate/sync"
# This worker has concurrency = 1. All workloads have cost value 1.0
COST = count_workload()
# Route to get worker URL
route_payload = {
"endpoint": endpoint_group_name,
"api_key": api_key,
"cost": COST,
}
# First request - get routing information
route_response = make_request(
url=urljoin(server_url, "/route/"),
payload=route_payload,
timeout=4,
context="route request"
)
if route_response is None:
return None
if "url" not in route_response or not route_response["url"]:
log.error("Error: No worker in 'Ready' state. Please wait while the serverless engine removes errored workers or finishes loading new workers.")
return None
if "status" in route_response:
print(f"Autoscaler status: {route_response['status']}")
return None
# Extract data from route response
url = route_response["url"]
auth_data = dict(
signature=route_response["signature"],
cost=route_response["cost"],
endpoint=route_response["endpoint"],
reqnum=route_response["reqnum"],
url=route_response["url"],
)
# Build the payload for the worker request
worker_payload = {
"input": {
"request_id": str(uuid.uuid4()),
"modifier": "Text2Image",
"modifications": {
"prompt": "a beautiful landscape with mountains and lakes",
"width": 1024,
"height": 1024,
"steps": 20,
"seed": random.randint(0, 2**32 - 1)
},
"workflow_json": {} # Empty since using modifier approach
}
}
req_data = dict(payload=worker_payload, auth_data=auth_data)
worker_url = urljoin(url, WORKER_ENDPOINT)
print(f"url: {worker_url}")
# Second request - call the worker endpoint
worker_response = make_request(
url=worker_url,
payload=req_data,
verify=get_cert_file_path(),
context="worker request"
)
return worker_response
if __name__ == "__main__":
from lib.test_utils import test_args
args = test_args.parse_args()
endpoint_api_key = Endpoint.get_endpoint_api_key(
endpoint_name=args.endpoint_group_name,
account_api_key=args.api_key,
instance=args.instance,
)
if endpoint_api_key:
result = call_text2image_workflow(
api_key=endpoint_api_key,
endpoint_group_name=args.endpoint_group_name,
server_url=args.server_url,
)
if result is None:
log.error("Text2Image workflow failed")
else:
print(result)
else:
log.error(f"Failed to get API key for endpoint {args.endpoint_group_name}")
+60
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@@ -0,0 +1,60 @@
import os
import sys
import random
import dataclasses
from typing import Dict, Any
from functools import cache
from math import ceil
from lib.data_types import ApiPayload, JsonDataException
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
# Results will indicate % or a job completed per second. Avoids sub 0.1 sec performance indication
return 100.0
@dataclasses.dataclass
class ComfyWorkflowData(ApiPayload):
input: dict
@classmethod
def for_test(cls):
"""
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)
"""
test_prompt = random.choice(test_prompts).rstrip()
return cls(
input={
"request_id": f"test-{random.randint(1000, 99999)}",
"modifier": "Text2Image",
"modifications": {
"prompt": test_prompt,
"width": os.getenv('BENCHMARK_TEST_WIDTH', 512),
"height": os.getenv('BENCHMARK_TEST_HEIGHT', 512),
"steps": os.getenv('BENCHMARK_TEST_STEPS', 20),
"seed": random.randint(0, sys.maxsize),
}
}
)
def generate_payload_json(self) -> Dict[str, Any]:
# input is already a dict, just return it wrapped in the expected structure
return {"input": self.input}
def count_workload(self) -> float:
return count_workload()
@classmethod
def from_json_msg(cls, json_msg: Dict[str, Any]) -> "ComfyWorkflowData":
# Extract required fields
if "input" not in json_msg:
raise JsonDataException({"input": "missing parameter"})
return cls(
input=json_msg["input"]
)
@@ -0,0 +1,34 @@
cartoon character of a person with a hoodie , in style of cytus and deemo, ork, gold chains, realistic anime cat, dripping black goo, lineage revolution style, thug life, cute anthropomorphic bunny, balrog, arknights, aliased, very buff, black and red and yellow paint, painting illustration collage style, character composition in vector with white background
stardew valley, fine details
2D Vector Illustration of a child with soccer ball Art for Sublimation, Design Art, Chrome Art, Painting and Stunning Artwork, Highly Detailed Digital Painting, Airbrush Art, Highly Detailed Digital Artwork, Dramatic Artwork, stained antique yellow copper paint, digital airbrush art, detailed by Mark Brooks, Chicano airbrush art, Swagger! snake Culture
realistic futuristic city-downtown with short buildings, sunset
seascape by Ray Collins and artgerm, front view of a perfect wave, sunny background, ultra detailed water
inspired by realflow-cinema4d editor features, create image of a transparent luxury cup with ice fruits and mint, connected with white, yellow and pink cream, Slow - High Speed MO Photography, YouTube Video Screenshot, Abstract Clay, Transparent Cup , molecular gastronomy, wheel, 3D fluid,Simulation rendering, still video, 4k polymer clay futras photography, very surreal, Houdini Fluid Simulation, hyperrealistic CGI and FLUIDS & MULTIPHYSICS SIMULATION effect, with Somali Stain Lurex, Metallic Jacquard, Gold Thread, Mulberry Silk, Toub Saree, Warm background, a fantastic image worthy of an award.
biker with backpack on his back riding a motorcycle, Style by Ade Santora, Oilpunk, Cover photo, craig mullins style, on the cover of a magazine, Outdoor Magazine, inspired by Alex Petruk APe, image of a male biker, Cover of an award-winning magazine, the man has a backpack, photo for magazine, with a backpack, magazine cover
generate a collage-style illustration inspired by the Procreate raster graphic editor, photographic illustration with the theme, 2D vector, art for textile sublimation, containing surrealistic cartoon cat wearing a baseball cap and jeans standing in front of a poster, inspired by Sadao Watanabe, Doraemon, Japanese cartoon style, Eichiro Oda, Iconic high detail character, Director: Nakahara Nantenbō, Kastuhiro Otomo, image detailed, by Miyamoto, Hidetaka Miyazaki, Katsuhiro illustration, 8k, masterpiece, Minimize noise and grain in photo quality without lose quality and increase brightness and lighting,Symmetry and Alignment, Avoid asymmetrical shapes and out-of-focus points. Focus and Sharpness: Make sure the image is focused and sharp and encourages the viewer to see it as a work of art printed on fabric.
fantasy medieval village world inside a glass sphere , high detail, fantasy, realistic, light effect, hyper detail, volumetric lighting, cinematic, macro, depth of field, blur, red light and clouds from the back, highly detailed epic cinematic concept art cg render made in maya, blender and photoshop, octane render, excellent composition, dynamic dramatic cinematic lighting, aesthetic, very inspirational, world inside a glass sphere by james gurney by artgerm with james jean, joe fenton and tristan eaton by ross tran, fine details
Iron Man, (Arnold Tsang, Toru Nakayama), Masterpiece, Studio Quality, 6k , toa, toaair, 1boy, glowing, axe, mecha, science_fiction, solo, weapon, jungle , green_background, nature, outdoors, solo, tree, weapon, mask, dynamic lighting, detailed shading, digital texture painting
(Pope Francis) wearing leather jacket is a DJ in a nightclub, mixing live on stage, giant mixing table, a masterpiece
Pope Francis wearing biker (leather jacket), a masterpiece
Luke Skywalker ordering a burger and fries from the Death Star canteen.
I want to generate a group avatar for a Feishu group chat. The role of this group is daily software technical communication. Now the subject technology stacks that members of this group discuss daily include: algorithms, data structures, optimization, functional programming, and the programming languages often discussed are: TypeScript, Java, python, etc. I hope this avatar has a simple aesthetic, this avatar is a single person avatar
portrait Anime black girl cute-fine-face, pretty face, realistic shaded Perfect face, fine details. Anime. realistic shaded lighting by Ilya Kuvshinov Giuseppe Dangelico Pino and Michael Garmash and Rob Rey, IAMAG premiere, WLOP matte print, cute freckles, masterpiece
young Disney socialite wearing a beige miniskirt, dark brown turtleneck sweater, small neckless, cute-fine-face, anime. illustration, realistic shaded perfect face, brown hair, grey eyes, fine details, realistic shaded lighting by ilya kuvshinov giuseppe dangelico pino and michael garmash and rob rey, iamag premiere, wlop matte print, a masterpiece
Cute small cat sitting in a movie theater eating chicken wiggs watching a movie ,unreal engine, cozy indoor lighting, artstation, detailed, digital painting,cinematic,character design by mark ryden and pixar and hayao miyazaki, unreal 5, daz, hyperrealistic, octane render
Cute small dog sitting in a movie theater eating popcorn watching a movie ,unreal engine, cozy indoor lighting, artstation, detailed, digital painting,cinematic,character design by mark ryden and pixar and hayao miyazaki, unreal 5, daz, hyperrealistic, octane render
fox bracelet made of buckskin with fox features, rich details, fine carvings, studio lighting
crane buckskin bracelet with crane features, rich details, fine carvings, studio lighting
london luxurious interior living-room, light walls
Parisian luxurious interior penthouse bedroom, dark walls, wooden panels
cute girl, crop-top, blond hair, black glasses, stretching, with background by greg rutkowski makoto shinkai kyoto animation key art feminine mid shot
houses in front, houses background, straight houses, digital art, smooth, sharp focus, gravity falls style, doraemon style, shinchan style, anime style
Simplified technical drawing, Leonardo da Vinci, Mechanical Dinosaur Skeleton, Minimalistic annotations, Hand-drawn illustrations, Basic design and engineering, Wonder and curiosity
High quality 8K painting impressionist style of a Japanese modern city street with a girl on the foreground wearing a traditional wedding dress with a fox mask, staring at the sky, daylight
a landscape from the Moon with the Earth setting on the horizon, realistic, detailed
Isometric Atlantis city,great architecture with columns, great details, ornaments,seaweed, blue ambiance, 3D cartoon style, soft light, 45° view
A hyper realistic avatar of a guy riding on a black honda cbr 650r in leather suit,high detail, high quality,8K,photo realism
the street of amedieval fantasy town, at dawn, dark, highly detailed
overwhelmingly beautiful eagle framed with vector flowers, long shiny wavy flowing hair, polished, ultra detailed vector floral illustration mixed with hyper realism, muted pastel colors, vector floral details in background, muted colors, hyper detailed ultra intricate overwhelming realism in detailed complex scene with magical fantasy atmosphere, no signature, no watermark
a highly detailed matte painting of a man on a hill watching a rocket launch in the distance by studio ghibli, makoto shinkai, by artgerm, by wlop, by greg rutkowski, volumetric lighting, octane render, 4 k resolution, trending on artstation, masterpiece | hyperrealism| highly detailed| insanely detailed| intricate| cinematic lighting| depth of field
electronik robot and ofice ,unreal engine, cozy indoor lighting, artstation, detailed, digital painting,cinematic,character design by mark ryden and pixar and hayao miyazaki, unreal 5, daz, hyperrealistic, octane render
exquisitely intricately detailed illustration, of a small world with a lake and a rainbow, inside a closed glass jar.
+116
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@@ -0,0 +1,116 @@
import os
import logging
import dataclasses
import base64
from typing import Optional, Union, Type
from aiohttp import web, ClientResponse
from lib.backend import Backend, LogAction
from lib.data_types import EndpointHandler
from lib.server import start_server
from .data_types import ComfyWorkflowData
MODEL_SERVER_URL = os.getenv("MODEL_SERVER_URL", "http://127.0.0.1:18288")
# This is the last log line that gets emitted once comfyui+extensions have been fully loaded
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
]
logging.basicConfig(
level=logging.DEBUG,
format="%(asctime)s[%(levelname)-5s] %(message)s",
datefmt="%Y-%m-%d %H:%M:%S",
)
log = logging.getLogger(__file__)
async def generate_client_response(
client_request: web.Request, model_response: ClientResponse
) -> Union[web.Response, web.StreamResponse]:
# Check if the response is actually streaming based on response headers/content-type
is_streaming_response = (
model_response.content_type == "text/event-stream"
or model_response.content_type == "application/x-ndjson"
or model_response.headers.get("Transfer-Encoding") == "chunked"
or "stream" in model_response.content_type.lower()
)
if is_streaming_response:
log.debug("Detected streaming response...")
res = web.StreamResponse()
res.content_type = model_response.content_type
await res.prepare(client_request)
async for chunk in model_response.content:
await res.write(chunk)
await res.write_eof()
log.debug("Done streaming response")
return res
else:
log.debug("Detected non-streaming response...")
content = await model_response.read()
return web.Response(
body=content,
status=model_response.status,
content_type=model_response.content_type
)
@dataclasses.dataclass
class ComfyWorkflowHandler(EndpointHandler[ComfyWorkflowData]):
@property
def endpoint(self) -> str:
return "/generate/sync"
@property
def healthcheck_endpoint(self) -> Optional[str]:
return f"{MODEL_SERVER_URL}/health"
@classmethod
def payload_cls(cls) -> Type[ComfyWorkflowData]:
return ComfyWorkflowData
def make_benchmark_payload(self) -> ComfyWorkflowData:
return ComfyWorkflowData.for_test()
async def generate_client_response(
self, client_request: web.Request, model_response: ClientResponse
) -> Union[web.Response, web.StreamResponse]:
return await generate_client_response(client_request, model_response)
backend = Backend(
model_server_url=MODEL_SERVER_URL,
model_log_file=os.environ["MODEL_LOG"],
allow_parallel_requests=False,
benchmark_handler=ComfyWorkflowHandler(
benchmark_runs=3, benchmark_words=100
),
log_actions=[
(LogAction.ModelLoaded, MODEL_SERVER_START_LOG_MSG),
(LogAction.Info, "Downloading:"),
*[
(LogAction.ModelError, error_msg)
for error_msg in MODEL_SERVER_ERROR_LOG_MSGS
],
],
)
async def handle_ping(_):
return web.Response(body="pong")
routes = [
web.post("/generate/sync", backend.create_handler(ComfyWorkflowHandler())),
web.get("/ping", handle_ping),
]
if __name__ == "__main__":
start_server(backend, routes)
+8
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@@ -0,0 +1,8 @@
from lib.test_utils import test_load_cmd, test_args
from .data_types import ComfyWorkflowData
WORKER_ENDPOINT = "/generate/sync"
if __name__ == "__main__":
test_load_cmd(ComfyWorkflowData, WORKER_ENDPOINT, arg_parser=test_args)
+3
View File
@@ -5,6 +5,7 @@ import requests
from lib.test_utils import print_truncate_res
from utils.endpoint_util import Endpoint
from utils.ssl import get_cert_file_path
"""
NOTE: this client example uses a custom comfy workflow compatible with SD3 only
@@ -51,6 +52,7 @@ def call_default_workflow(
response = requests.post(
url,
json=req_data,
verify=get_cert_file_path(),
)
response.raise_for_status()
print_truncate_res(str(response.json()))
@@ -141,6 +143,7 @@ def call_custom_workflow_for_sd3(
response = requests.post(
url,
json=req_data,
verify=get_cert_file_path(),
)
response.raise_for_status()
print_truncate_res(str(response.json()))
+1 -1
View File
@@ -13,7 +13,7 @@ from lib.server import start_server
from .data_types import DefaultComfyWorkflowData, CustomComfyWorkflowData
MODEL_SERVER_URL = "http://0.0.0.0:38188"
MODEL_SERVER_URL = "http://127.0.0.1:18288" # API Wrapper Service
# This is the last log line that gets emitted once comfyui+extensions have been fully loaded
MODEL_SERVER_START_LOG_MSG = "To see the GUI go to: http://127.0.0.1:18188"
+8 -3
View File
@@ -6,6 +6,7 @@ from urllib.parse import urljoin
from typing import Dict, Any, Optional, Iterator, Union, List
import requests
from utils.endpoint_util import Endpoint
from utils.ssl import get_cert_file_path
from .data_types.client import CompletionConfig, ChatCompletionConfig
logging.basicConfig(
@@ -90,9 +91,13 @@ class APIClient:
# Make the request using the specified method
if method.upper() == "POST":
response = requests.post(url, json=req_data, stream=stream)
response = requests.post(
url, json=req_data, stream=stream, verify=get_cert_file_path()
)
elif method.upper() == "GET":
response = requests.get(url, params=req_data, stream=stream)
response = requests.get(
url, params=req_data, stream=stream, verify=get_cert_file_path()
)
else:
raise ValueError(f"Unsupported HTTP method: {method}")
@@ -562,7 +567,7 @@ def main():
client = APIClient(
endpoint_group_name=args.endpoint_group_name,
api_key=args.api_key,
server_url=args.server_url,
server_url=Endpoint.get_autoscaler_server_url(args.instance),
endpoint_api_key=endpoint_api_key,
)
+6 -1
View File
@@ -4,6 +4,7 @@ import json
from urllib.parse import urljoin
import requests
from utils.endpoint_util import Endpoint
from utils.ssl import get_cert_file_path
logging.basicConfig(
level=logging.DEBUG,
@@ -42,7 +43,11 @@ def call_generate(endpoint_group_name: str, api_key: str, server_url: str) -> No
req_data = dict(payload=payload, auth_data=auth_data)
url = urljoin(url, WORKER_ENDPOINT)
print(f"url: {url}")
response = requests.post(url, json=req_data)
response = requests.post(
url,
json=req_data,
verify=get_cert_file_path(),
)
response.raise_for_status()
res = response.json()
print(res)