remove env var writing

lib/backend.py

@@ -5,7 +5,7 @@ import base64
 import subprocess
 import dataclasses
 import logging
-from asyncio import wait, sleep, gather, Semaphore, FIRST_COMPLETED, create_task, get_running_loop
+from asyncio import wait, sleep, gather, Semaphore, FIRST_COMPLETED, create_task
 from typing import Tuple, Awaitable, NoReturn, List, Union, Callable, Optional
 from functools import cached_property
 from distutils.util import strtobool
@@ -73,11 +73,9 @@ class Backend:
         self._total_pubkey_fetch_errors = 0
         self._pubkey = self._fetch_pubkey()
         self.__start_healthcheck: bool = False
-
-        # NEW: FIFO queue + worker count
-        self.request_queue: "asyncio.Queue[tuple[EndpointHandler[ApiPayload_T], web.Request, asyncio.Future]]" = asyncio.Queue()
-        # If parallel allowed, let multiple workers drain the queue (order preserved by FIFO per worker; overall start order is FIFO).
-        self._num_workers: int = 1 if not self.allow_parallel_requests else int(os.environ.get("WORKERS", "4"))
+        self._model_tail_start_time = None
+        self._model_loaded_time = None
+        self._first_healthcheck_ok = False
 
     @property
     def pubkey(self) -> Optional[RSA.RsaKey]:
@@ -96,22 +94,6 @@ class Backend:
         timeout = ClientTimeout(total=None)
         return ClientSession(self.model_server_url, timeout=timeout, connector=connector)
 
-    async def _worker(self):
-        while True:
-            handler, request, fut = await self.request_queue.get()
-            try:
-                # Skip if already cancelled while waiting in the queue
-                if fut.cancelled():
-                    continue
-                res = await self.__process_enqueued_request(handler, request)
-                if not fut.cancelled():
-                    fut.set_result(res)
-            except Exception as e:
-                if not fut.cancelled():
-                    fut.set_exception(e)
-            finally:
-                self.request_queue.task_done()
-
     def create_handler(
         self,
         handler: EndpointHandler[ApiPayload_T],
@@ -125,6 +107,7 @@ class Backend:
 
     #######################################Private#######################################
     def _fetch_pubkey(self):
+        t0 = time.time()
         command = ["curl", "-X", "GET", "https://run.vast.ai/pubkey/"]
         result = subprocess.check_output(command, universal_newlines=True)
         log.debug("public key:")
@@ -141,6 +124,8 @@ class Backend:
             self._total_pubkey_fetch_errors += 1
             if self._total_pubkey_fetch_errors >= MAX_PUBKEY_FETCH_ATTEMPTS:
                 self.backend_errored("Failed to get autoscaler pubkey")
+            else:
+                log.debug(f"pubkey fetch+parse took {time.time()-t0:.2f}s")
         return key
 
     async def __handle_request(
@@ -148,36 +133,7 @@ class Backend:
         handler: EndpointHandler[ApiPayload_T],
         request: web.Request,
     ) -> Union[web.Response, web.StreamResponse]:
-        """use this function to enqueue requests for FIFO processing"""
-        loop = get_running_loop()
-        fut: asyncio.Future = loop.create_future()
-
-        # If the client disconnects while waiting in the FIFO, cancel the future so the worker skips it
-        cancel_watch = create_task(request.wait_for_disconnection())
-        def _cancel_if_disconnected(_):
-            if not fut.done():
-                fut.cancel()
-        cancel_watch.add_done_callback(_cancel_if_disconnected)
-
-        try:
-            await self.request_queue.put((handler, request, fut))
-            return await fut
-        except asyncio.CancelledError:
-            # Propagate cancellation to ensure aiohttp doesn't expect a response body
-            raise
-        finally:
-            # Best-effort cleanup of the watcher
-            cancel_watch.cancel()
-
-    async def __process_enqueued_request(
-        self,
-        handler: EndpointHandler[ApiPayload_T],
-        request: web.Request,
-    ) -> Union[web.Response, web.StreamResponse]:
-        """
-        This contains the original __handle_request logic and is invoked by workers,
-        ensuring FIFO execution via asyncio.Queue.
-        """
+        """use this function to forward requests to the model endpoint"""
         try:
             data = await request.json()
             auth_data, payload = handler.get_data_from_request(data)
@@ -185,11 +141,8 @@ class Backend:
             return web.json_response(data=e.message, status=422)
         except json.JSONDecodeError:
             return web.json_response(dict(error="invalid JSON"), status=422)
-
         workload = payload.count_workload()
-        request_metrics: RequestMetrics = RequestMetrics(
-            request_idx=auth_data.request_idx, reqnum=auth_data.reqnum, workload=workload, status="Created"
-        )
+        request_metrics: RequestMetrics = RequestMetrics(request_idx=auth_data.request_idx, reqnum=auth_data.reqnum, workload=workload, status="Created")
 
         async def cancel_api_call_if_disconnected() -> web.Response:
             await request.wait_for_disconnection()
@@ -230,8 +183,6 @@ class Backend:
         acquired = False
         try:
             self.metrics._request_start(request_metrics)
-
-            # Preserve existing semaphore behavior for serializing requests when requested
             if self.allow_parallel_requests is False:
                 log.debug(f"Waiting to aquire Sem for reqnum:{request_metrics.reqnum}")
                 await self.sem.acquire()
@@ -241,7 +192,6 @@ class Backend:
                 )
             else:
                 log.debug(f"Starting request for reqnum:{request_metrics.reqnum}")
-
             done, pending = await wait(
                 [
                     create_task(make_request()),
@@ -296,6 +246,10 @@ class Backend:
                 log.debug(f"Performing healthcheck on {health_check_url}")
                 async with self.healthcheck_session.get(health_check_url) as response:
                     if response.status == 200:
+                        if not self._first_healthcheck_ok:
+                            if self._model_loaded_time:
+                                log.debug(f"first healthcheck OK after {time.time()-self._model_loaded_time:.2f}s since ModelLoaded")
+                            self._first_healthcheck_ok = True
                         log.debug("Healthcheck successful")
                     elif response.status == 503:
                         log.debug(f"Healthcheck failed with status: {response.status}")
@@ -309,14 +263,8 @@ class Backend:
                 self.backend_errored(str(e))
 
     async def _start_tracking(self) -> None:
-        # Start the FIFO workers alongside existing loops
-        worker_tasks = tuple(self._worker() for _ in range(self._num_workers))
         await gather(
-            self.__read_logs(),
-            self.metrics._send_metrics_loop(),
-            self.__healthcheck(),
-            self.metrics._send_delete_requests_loop(),
-            *worker_tasks,
+            self.__read_logs(), self.metrics._send_metrics_loop(), self.__healthcheck(), self.metrics._send_delete_requests_loop()
         )
 
     def backend_errored(self, msg: str) -> None:
@@ -377,17 +325,20 @@ class Backend:
                 with open(BENCHMARK_INDICATOR_FILE, "r") as f:
                     log.debug("already ran benchmark")
                     # trigger model load
-                    payload = self.benchmark_handler.make_benchmark_payload()
-                    _ = await self.__call_api(
-                        handler=self.benchmark_handler, payload=payload
-                    )
+                    # payload = self.benchmark_handler.make_benchmark_payload()
+                    # _ = await self.__call_api(
+                    #     handler=self.benchmark_handler, payload=payload
+                    # )
                     return float(f.readline())
             except FileNotFoundError:
                 pass
 
             log.debug("Initial run to trigger model loading...")
+            t_bench0 = time.time()
             payload = self.benchmark_handler.make_benchmark_payload()
             await self.__call_api(handler=self.benchmark_handler, payload=payload)
+            log.debug(f"warmup request took {time.time()-t_bench0:.2f}s")
+            t_benchmark_loop0 = time.time()
 
             max_throughput = 0
             sum_throughput = 0
@@ -412,9 +363,6 @@ class Backend:
                 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
@@ -438,6 +386,7 @@ class Backend:
             log.debug(
                 f"benchmark result: avg {average_throughput} workload per second, max {max_throughput}"
             )
+            log.debug(f"benchmark loop took {time.time()-t_benchmark_loop0:.2f}s")
             with open(BENCHMARK_INDICATOR_FILE, "w") as f:
                 f.write(str(max_throughput))
             return max_throughput
@@ -450,14 +399,17 @@ class Backend:
             for action, msg in self.log_actions:
                 match action:
                     case LogAction.ModelLoaded if msg in log_line:
-                        log.debug(
-                            f"Got log line indicating model is loaded: {log_line}"
-                        )
+                        now = time.time()
+                        elapsed = now - self._model_tail_start_time
+                        log.debug(f"ModelLoaded observed after {elapsed:.2f}s: {log_line}")
                         # some backends need a few seconds after logging successful startup before
                         # they can begin accepting requests
-                        await sleep(5)
+                        # await sleep(5)
                         try:
+                            t_bench0 = time.time()
                             max_throughput = await run_benchmark()
+                            self._model_loaded_time = time.time()
+                            log.debug(f"benchmark total took {self._model_loaded_time - t_bench0:.2f}s")
                             self.__start_healthcheck = True
                             self.metrics._model_loaded(
                                 max_throughput=max_throughput,
@@ -476,6 +428,7 @@ class Backend:
 
         async def tail_log():
             log.debug(f"tailing file: {self.model_log_file}")
+            self._model_tail_start_time = time.time()
             async with await open_file(self.model_log_file) as f:
                 while True:
                     line = await f.readline()

lib/data_types.py

@@ -257,7 +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()]) / max(self.max_throughput, 0.00001)
+        return sum([request.workload for request in self.requests_working.values()]) / self.max_throughput
     
     @property
     def cur_load(self) -> float:

lib/metrics.py

@@ -145,15 +145,14 @@ class Metrics:
     #######################################Private#######################################
 
     async def __send_delete_requests_and_reset(self):
-        async def post(report_addr: str, idxs: list[int], success_flag: bool) -> bool:
+
+        async def send_data(report_addr: str, success: bool) -> bool:
             data = {
                 "worker_id": self.id,
-                "request_idxs": idxs,
-                "success": success_flag,
+                "request_idxs": [r.request_idx for r in self.model_metrics.requests_deleting if r.success == success],
+                "success": success
             }
-            log.debug(
-                f"Deleting requests that {'succeeded' if success_flag else 'failed'}: {data['request_idxs']}"
-            )
+            log.debug(f"Deleting requests that {'succeeded' if success else 'failed'}: {data['request_idxs']}")
             full_path = report_addr.rstrip("/") + "/delete_requests/"
             for attempt in range(1, 4):
                 try:
@@ -163,38 +162,16 @@ class Metrics:
                         res.raise_for_status()
                     return True
                 except asyncio.TimeoutError:
-                    log.debug("delete_requests timed out")
+                    log.debug(f"delete_requests timed out")
                 except (ClientResponseError, Exception) as e:
                     log.debug(f"delete_requests failed with error: {e}")
                 await asyncio.sleep(2)
                 log.debug(f"retrying delete_request, attempt: {attempt}")
-            return False
-
-        # Take a snapshot of what we plan to send this tick.
-        # New arrivals after this snapshot will remain in the queue for the next tick.
-        snapshot = list(self.model_metrics.requests_deleting)
-        success_idxs = [r.request_idx for r in snapshot if r.success is True]
-        failed_idxs  = [r.request_idx for r in snapshot if r.success is False]
-
-        if not success_idxs and not failed_idxs:
-            return  # nothing to do
 
         for report_addr in self.report_addr:
-            sent_success = True
-            sent_failed  = True
-
-            if success_idxs:
-                sent_success = await post(report_addr, success_idxs, True)
-            if failed_idxs:
-                sent_failed = await post(report_addr, failed_idxs, False)
-
-            if sent_success and sent_failed:
-                # Remove only the items we actually sent from the live queue.
-                sent_set = set(success_idxs) | set(failed_idxs)
-                self.model_metrics.requests_deleting[:] = [
-                    r for r in self.model_metrics.requests_deleting
-                    if r.request_idx not in sent_set
-                ]
+            success = await send_data(report_addr, success=True) and await send_data(report_addr, success=False)
+            if success is True:
+                self.model_metrics.requests_deleting.clear()
                 break
 
 

start_server.sh

@@ -2,6 +2,9 @@
 
 set -e -o pipefail
 
+log() { echo "$(date +'%Y-%m-%d %H:%M:%S') $*"; }
+step(){ _t0=$(date +%s); eval "$1"; _dt=$(($(date +%s)-_t0)); log "$2 took ${_dt}s"; }
+
 WORKSPACE_DIR="${WORKSPACE_DIR:-/workspace}"
 
 SERVER_DIR="$WORKSPACE_DIR/vast-pyworker"
@@ -41,33 +44,28 @@ echo_var DEBUG_LOG
 echo_var PYWORKER_LOG
 echo_var MODEL_LOG
 
-# 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
+# # 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"
-    if ! which uv; then
-        curl -LsSf https://astral.sh/uv/install.sh | sh
-        source ~/.local/bin/env
-    fi
+    step 'if ! which uv; then curl -LsSf https://astral.sh/uv/install.sh | sh; source ~/.local/bin/env; fi' "uv install"
 
     # Fork testing
-    [[ ! -d $SERVER_DIR ]] && git clone "${PYWORKER_REPO:-https://github.com/vast-ai/pyworker}" "$SERVER_DIR"
-    if [[ -n ${PYWORKER_REF:-} ]]; then
-        (cd "$SERVER_DIR" && git checkout "$PYWORKER_REF")
-    fi
+    step '[[ ! -d $SERVER_DIR ]] && git clone "${PYWORKER_REPO:-https://github.com/vast-ai/pyworker}" "$SERVER_DIR"' "git clone"
+    step 'if [[ -n ${PYWORKER_REF:-} ]]; then (cd "$SERVER_DIR" && git checkout "$PYWORKER_REF"); fi' "git checkout"
 
-    uv venv --python-preference only-managed "$ENV_PATH" -p 3.10
-    source "$ENV_PATH/bin/activate"
 
-    uv pip install -r "${SERVER_DIR}/requirements.txt"
+    step 'uv venv --python-preference only-managed "$ENV_PATH" -p 3.10' "venv create"
+    step 'source "$ENV_PATH/bin/activate"' "venv activate"
+    step 'uv pip install -r "${SERVER_DIR}/requirements.txt"' "pip install requirements"
 
     touch ~/.no_auto_tmux
 else
@@ -80,39 +78,8 @@ fi
 [ ! -d "$SERVER_DIR/workers/$BACKEND" ] && echo "$BACKEND not supported!" && exit 1
 
 if [ "$USE_SSL" = true ]; then
-
-    cat << EOF > /etc/openssl-san.cnf
-    [req]
-    default_bits       = 2048
-    distinguished_name = req_distinguished_name
-    req_extensions     = v3_req
-
-    [req_distinguished_name]
-    countryName         = US
-    stateOrProvinceName = CA
-    organizationName    = Vast.ai Inc.
-    commonName          = vast.ai
-
-    [v3_req]
-    basicConstraints = CA:FALSE
-    keyUsage         = nonRepudiation, digitalSignature, keyEncipherment
-    subjectAltName   = @alt_names
-
-    [alt_names]
-    IP.1   = 0.0.0.0
-EOF
-
-    openssl req -newkey rsa:2048 -subj "/C=US/ST=CA/CN=pyworker.vast.ai/" \
-        -nodes \
-        -sha256 \
-        -keyout /etc/instance.key \
-        -out /etc/instance.csr \
-        -config /etc/openssl-san.cnf
-
-    curl --header 'Content-Type: application/octet-stream' \
-        --data-binary @//etc/instance.csr \
-        -X \
-        POST "https://console.vast.ai/api/v0/sign_cert/?instance_id=$CONTAINER_ID" > /etc/instance.crt;
+  step 'openssl req -newkey rsa:2048 -subj "/C=US/ST=CA/CN=pyworker.vast.ai/" -nodes -sha256 -keyout /etc/instance.key -out /etc/instance.csr -config /etc/openssl-san.cnf' "openssl csr"
+  step 'curl --header "Content-Type: application/octet-stream" --data-binary @//etc/instance.csr -X POST "https://console.vast.ai/api/v0/sign_cert/?instance_id=$CONTAINER_ID" > /etc/instance.crt' "sign cert"
 fi
 
 
@@ -122,11 +89,11 @@ export REPORT_ADDR WORKER_PORT USE_SSL UNSECURED
 
 cd "$SERVER_DIR"
 
-echo "launching PyWorker server"
+log "launching PyWorker server"
 
 # if instance is rebooted, we want to clear out the log file so pyworker doesn't read lines
 # 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"
+_t0=$(date +%s); (python3 -m "workers.$BACKEND.server" |& tee -a "$PYWORKER_LOG") & _dt=$(($(date +%s)-_t0)); log "PyWorker spawn took ${_dt}s"
+log "launching PyWorker server done"

workers/comfyui-json/README.md

@@ -12,21 +12,9 @@ A docker image is provided but you may use any if the above requirements are met
 
 ## Benchmarking
 
-### Custom Benchmark Workflows
+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:**
-- Fork this repository and add your `benchmark.json` file
-- Write the file during worker provisioning (onstart script or setup phase)
-
-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.
-
-### 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.
 

workers/comfyui-json/data_types.py

@@ -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={

workers/comfyui-json/misc/benchmark.json.example

@@ -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"
-        }
-    }
-}

workers/comfyui-json/server.py

@@ -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
 ]
 
 

workers/openai/data_types/server.py

@@ -6,10 +6,13 @@ from typing import Union, Type, Dict, Any, Optional
 from aiohttp import web, ClientResponse
 import nltk
 import logging
+import time
 
+log = logging.getLogger(__name__)
+t0 = time.time()
 nltk.download("words")
 WORD_LIST = nltk.corpus.words.words()
-log = logging.getLogger(__name__)
+print(f"{time.strftime('%Y-%m-%d %H:%M:%S')} NLTK words download+load took {time.time()-t0:.2f}s")
 
 """
 Generic dataclass accepts any dictionary in input.