more logs

lib/backend.py

@@ -30,7 +30,7 @@ from lib.data_types import (
     BenchmarkResult
 )
 
-VERSION = "0.2.1"
+VERSION = "0.2.0"
 
 MSG_HISTORY_LEN = 100
 log = logging.getLogger(__file__)
@@ -235,10 +235,14 @@ class Backend:
             log.debug("No healthcheck endpoint defined, skipping healthcheck")
             return
 
+        first_healthcheck = True
         while True:
             await sleep(10)
             if self.__start_healthcheck is False:
                 continue
+            if first_healthcheck:
+                log.info(f"[healthcheck] First healthcheck starting (model is now loaded)")
+                first_healthcheck = False
             try:
                 log.debug(f"Performing healthcheck on {health_check_url}")
                 async with self.healthcheck_session.get(health_check_url) as response:
@@ -256,9 +260,22 @@ class Backend:
                 self.backend_errored(str(e))
 
     async def _start_tracking(self) -> None:
-        await gather(
-            self.__read_logs(), self.metrics._send_metrics_loop(), self.__healthcheck(), self.metrics._send_delete_requests_loop()
+        log.info("Starting tracking tasks (read_logs, send_metrics_loop, healthcheck, send_delete_requests_loop)")
+        task_names = ["read_logs", "send_metrics_loop", "healthcheck", "send_delete_requests_loop"]
+        results = await gather(
+            self.__read_logs(), 
+            self.metrics._send_metrics_loop(), 
+            self.__healthcheck(), 
+            self.metrics._send_delete_requests_loop(),
+            return_exceptions=True
         )
+        # If we get here, one or more tasks exited (they should run forever)
+        log.error(f"CRITICAL: _start_tracking gather returned! This should never happen. Results: {results}")
+        for name, result in zip(task_names, results):
+            if isinstance(result, Exception):
+                log.error(f"Tracking task '{name}' crashed with exception: {result}", exc_info=result)
+            elif result is not None:
+                log.warning(f"Tracking task '{name}' exited unexpectedly with result: {result}")
 
     def backend_errored(self, msg: str) -> None:
         self.metrics._model_errored(msg)
@@ -399,15 +416,20 @@ class Backend:
                         # await sleep(5)
                         try:
                             max_throughput = await run_benchmark()
+                            log.info(f"[benchmark] Benchmark complete, max_throughput={max_throughput}, setting healthcheck=True")
                             self.__start_healthcheck = True
                             self.metrics._model_loaded(
                                 max_throughput=max_throughput,
                             )
+                            log.info(f"[benchmark] _model_loaded() called, returning from handle_log_line")
                         except ClientConnectorError as e:
                             log.debug(
-                                f"failed to connect to comfyui api during benchmark"
+                                f"failed to connect to model api during benchmark"
                             )
                             self.backend_errored(str(e))
+                        except Exception as e:
+                            log.error(f"Unexpected error during benchmark: {e}", exc_info=True)
+                            self.backend_errored(f"Benchmark failed: {e}")
                     case LogAction.ModelError if msg in log_line:
                         log.debug(f"Got log line indicating error: {log_line}")
                         self.backend_errored(msg)
@@ -419,10 +441,14 @@ class Backend:
             log.debug(f"tailing file: {self.model_log_file}")
             async with await open_file(self.model_log_file, encoding='utf-8', errors='ignore') as f:
                 while True:
-                    line = await f.readline()
-                    if line:
-                        await handle_log_line(line.rstrip())
-                    else:
+                    try:
+                        line = await f.readline()
+                        if line:
+                            await handle_log_line(line.rstrip())
+                        else:
+                            await asyncio.sleep(LOG_POLL_INTERVAL)
+                    except Exception as e:
+                        log.error(f"Error processing log line: {e}", exc_info=True)
                         await asyncio.sleep(LOG_POLL_INTERVAL)
 
         ###########

lib/metrics.py

@@ -1,4 +1,5 @@
 import os
+import sys
 import time
 import logging
 import json
@@ -17,6 +18,14 @@ DELETE_REQUESTS_INTERVAL = 1
 log = logging.getLogger(__file__)
 
 
+def _flush_logs():
+    """Force flush all log handlers and stdout/stderr."""
+    for handler in logging.root.handlers:
+        handler.flush()
+    sys.stdout.flush()
+    sys.stderr.flush()
+
+
 @cache
 def get_url() -> str:
     use_ssl = os.environ.get("USE_SSL", "false") == "true"
@@ -119,22 +128,41 @@ class Metrics:
                 await self.__send_delete_requests_and_reset()
 
     async def _send_metrics_loop(self) -> Awaitable[NoReturn]:
+        loop_count = 0
+        first_loaded_send_done = False
         while True:
             await sleep(METRICS_UPDATE_INTERVAL)
+            loop_count += 1
             elapsed = time.time() - self.last_metric_update
+            # Log heartbeat every 30 seconds to confirm loop is running
+            if loop_count % 30 == 0:
+                log.debug(f"[heartbeat] metrics loop alive, loop_count={loop_count}, model_loaded={self.system_metrics.model_is_loaded}")
+                _flush_logs()
+            # Extra logging for first few iterations after model loads
+            if self.system_metrics.model_is_loaded and not first_loaded_send_done:
+                log.info(f"[transition] First iteration with model_loaded=True, loop_count={loop_count}, elapsed={elapsed:.1f}")
+                _flush_logs()
             if self.system_metrics.model_is_loaded is False and elapsed >= 10:
                 log.debug(f"sending loading model metrics after {int(elapsed)}s wait")
                 await self.__send_metrics_and_reset()
             elif self.update_pending or elapsed > 10:
                 log.debug(f"sending loaded model metrics after {int(elapsed)}s wait")
                 await self.__send_metrics_and_reset()
+                if self.system_metrics.model_is_loaded and not first_loaded_send_done:
+                    first_loaded_send_done = True
+                    log.info(f"[transition] First loaded metrics send complete, continuing to next iteration...")
+                    _flush_logs()
 
     def _model_loaded(self, max_throughput: float) -> None:
+        log.info(f"MODEL LOADED: Setting model_is_loaded=True, max_throughput={max_throughput}")
+        _flush_logs()
         self.system_metrics.model_loading_time = (
             time.time() - self.system_metrics.model_loading_start
         )
         self.system_metrics.model_is_loaded = True
         self.model_metrics.max_throughput = max_throughput
+        log.info(f"MODEL LOADED: model_loading_time={self.system_metrics.model_loading_time}")
+        _flush_logs()
 
     def _model_errored(self, error_msg: str) -> None:
         self.model_metrics.set_errored(error_msg)
@@ -271,6 +299,7 @@ class Metrics:
         ###########
 
         self.system_metrics.update_disk_usage()
+        had_loadtime = loadtime_snapshot is not None and loadtime_snapshot > 0
 
         sent = False
         for report_addr in self.report_addr:
@@ -279,8 +308,14 @@ class Metrics:
                 break
 
         if sent:
+            if had_loadtime:
+                log.info(f"FIRST LOADTIME METRICS SENT SUCCESSFULLY! loadtime={loadtime_snapshot}")
+                _flush_logs()
             # clear the one-shot loadtime only if we actually sent *this* value
             self.system_metrics.reset(expected=loadtime_snapshot)
             self.update_pending = False
             self.model_metrics.reset()
             self.last_metric_update = time.time()
+            if had_loadtime:
+                log.info(f"POST-SEND: reset complete, last_metric_update={self.last_metric_update}, continuing loop...")
+                _flush_logs()

lib/server.py

@@ -1,5 +1,7 @@
 import os
 import logging
+import signal
+import sys
 from typing import List
 import ssl
 from asyncio import run, gather
@@ -12,7 +14,25 @@ from aiohttp import web
 log = logging.getLogger(__file__)
 
 
+def _setup_signal_handlers():
+    """Setup signal handlers to log when process receives termination signals."""
+    def signal_handler(signum, frame):
+        sig_name = signal.Signals(signum).name
+        log.error(f"SIGNAL RECEIVED: {sig_name} ({signum}) - process is being terminated")
+        sys.stdout.flush()
+        sys.stderr.flush()
+        sys.exit(128 + signum)
+    
+    # Handle common termination signals
+    for sig in [signal.SIGTERM, signal.SIGINT, signal.SIGHUP]:
+        try:
+            signal.signal(sig, signal_handler)
+        except (OSError, ValueError):
+            pass  # Some signals may not be available
+
+
 def start_server(backend: Backend, routes: List[web.RouteDef], **kwargs):
+    _setup_signal_handlers()
     try:
         log.debug("getting certificate...")
         use_ssl = os.environ.get("USE_SSL", "false") == "true"

requirements.txt

@@ -8,4 +8,4 @@ Requests~=2.32
 transformers~=4.52
 utils==1.0.*
 hf_transfer>=0.1.9
-git+https://github.com/vast-ai/vast-sdk.git@worker-sdk
+vastai-sdk>=0.2.0

start_server.sh

@@ -133,19 +133,8 @@ cd "$SERVER_DIR"
 echo "launching PyWorker server"
 
 set +e
-
-# Try worker entrypoint first
-echo "trying workers.${BACKEND}.worker"
-python3 -m "workers.${BACKEND}.worker" |& tee -a "$PYWORKER_LOG"
+python3 -m "workers.$BACKEND.server" |& 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
@@ -182,4 +171,4 @@ JSON
   done
 fi
 
-echo "launching PyWorker server done"
+echo "launching PyWorker server done"

workers/ace/worker.py

@@ -1,184 +0,0 @@
-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_lyrics = [
-    "[verse]\nGuardian cloaked in twilight hue\nShadows melt where he breaks through\nEchoes swirl in mystic flight\nHooded hero owns the night\n\n[verse]\nThrough the chaos shapes arise\nFeral whispers, glowing eyes\nOrcs and creatures side by side\nMarch within the inky tide\n\n[chorus]\nRise above the fear and gloom\nLet your courage fully bloom\nIn the darkness stand your ground\nHear the night proclaim your sound",
-    "[verse]\nMorning sun on fields of gold\nGentle stories unfold\nEvery breeze a quiet song\nWhere the peaceful hearts belong\n\n[verse]\nLanterns glow at stable doors\nRustling leaves on orchard floors\nSimple joys in every hand\nLife grows soft in fertile land\n\n[chorus]\nLet the day drift slow and free\nRoot your soul where you can be\nIn this haven warm and bright\nFeel the earth breathe pure delight",
-    "[verse]\nLittle feet on dusty ground\nChasing dreams without a sound\nSoccer ball in morning light\nHopes take wing in youthful flight\n\n[verse]\nChrome reflections paint the day\nSwagger in the steps that play\nCopper tones in shining air\nChildhood gleaming everywhere\n\n[chorus]\nKick the world with boundless cheer\nHold the magic close and near\nIn each moment bold and true\nLet the sky belong to you",
-    "[verse]\nSunset bleeds across the street\nGilded calm in summer heat\nLow-rise towers rimmed with fire\nDreams ignite as lights climb higher\n\n[verse]\nFootsteps scatter through the haze\nFutures shimmer in the blaze\nEvery window tells a tale\nFloating through a tangerine veil\n\n[chorus]\nLet the neon softly glow\nLet your restless heartbeat slow\nIn this city forged in light\nCarry hope into the night",
-    "[verse]\nOcean breathes in rolling arcs\nSprays of diamond, glowing sparks\nWaves unfold a perfect line\nNature’s rhythm feels divine\n\n[verse]\nSun above in golden sweep\nPaints the rise of every deep\nShimmer drifting through the blue\nWorld reborn in every view\n\n[chorus]\nLet the tide pull you along\nHear the water’s ancient song\nIn the cresting waves you’ll find\nQuiet peace for heart and mind",
-    "[verse]\nGlass aglow with swirling light\nFruits and mints in colors bright\nIcy whispers clink and chime\nFlowing forms suspend in time\n\n[verse]\nCreamy spirals drift within\nGentle currents slowly spin\nWarm reflections lingering sweet\nMixing flavors at your feet\n\n[chorus]\nSip the glow and let it rise\nTaste the sunset in disguise\nIn this moment clear and true\nLet the warmth flow into you",
-    "[verse]\nEngines rumble down the lane\nCopper clouds of steam and rain\nOilpunk dreams in metal shine\nRider drifting down the line\n\n[verse]\nLeather jacket, steady glare\nStories sparking in the air\nMagazine lights frame his face\nKing of roads in timeless grace\n\n[chorus]\nThrottle up beyond the bend\nFeel the force of steel ascend\nRide the night and hold on tight\nClaim the world in streaks of light",
-    "[verse]\nCut-out shapes in swirling play\nTextures dance in bold array\nCats in denim, grinning wide\nStrut across the patterned tide\n\n[verse]\nPosters hum with neon glow\nSurreal scenes begin to grow\nColors crisp as folded art\nPatchwork beating like a heart\n\n[chorus]\nLet the collage come alive\nWatch the vibrant pieces thrive\nIn this joyful, crafted space\nEvery shape finds its own place",
-    "[verse]\nTiny world in crystal glass\nAncient tales behind the mass\nVillage lights in winter gleam\nFrozen in a mystic dream\n\n[verse]\nLantern beams in swirling air\nSoft enchantment everywhere\nShadows drift with gentle grace\nMagic sealed within the space\n\n[chorus]\nHold the sphere and you will see\nEchoes of a memory\nIn the glow of fragile light\nLives a realm of pure delight",
-    "[verse]\nArmor hums with power bright\nChopping sparks in jungle night\nMecha spirits shift and scream\nThrough the ferns like shattered beams\n\n[verse]\nAxes blaze in glowing arcs\nLighting up the shadowed marks\nNature roars in trembling air\nClash of steel and cosmic flare\n\n[chorus]\nRaise the fire, strike the ground\nLet your legend shake the sound\nIn the wild where echoes roam\nForge the fight and carve your home",
-    "[verse]\nCrowds ignite in vibrant flare\nBeats explode through smoky air\nDJ robes replaced with flame\nPope on decks in holy frame\n\n[verse]\nLeather gleams in blinding light\nTurntables spin with sacred might\nChoirs echo in the bass\nHeaven pulses through the place\n\n[chorus]\nLift the roof and shake the floor\nSacred rhythm evermore\nLet the music take control\nFeel the blessing in your soul",
-]
-
-benchmark_dataset = [
-    {
-        "input": {
-            "request_id": "",
-            "workflow_json": {
-                "14": {
-                "inputs": {
-                    "tags": "funk, pop, soul, rock, melodic, guitar, drums, bass, keyboard, percussion, 105 BPM, energetic, upbeat, groovy, vibrant, dynamic",
-                    "lyrics": lyrics,
-                    "lyrics_strength": 0.99,
-                    "clip": ["40", 1]
-                },
-                "class_type": "TextEncodeAceStepAudio",
-                "_meta": {
-                    "title": "TextEncodeAceStepAudio"
-                }
-                },
-                "17": {
-                "inputs": {
-                    "seconds": 180,
-                    "batch_size": 1
-                },
-                "class_type": "EmptyAceStepLatentAudio",
-                "_meta": {
-                    "title": "EmptyAceStepLatentAudio"
-                }
-                },
-                "18": {
-                "inputs": {
-                    "samples": ["52", 0],
-                    "vae": ["40", 2]
-                },
-                "class_type": "VAEDecodeAudio",
-                "_meta": {
-                    "title": "VAE Decode Audio"
-                }
-                },
-                "40": {
-                "inputs": {
-                    "ckpt_name": "ace_step_v1_3.5b.safetensors"
-                },
-                "class_type": "CheckpointLoaderSimple",
-                "_meta": {
-                    "title": "Load Checkpoint"
-                }
-                },
-                "44": {
-                "inputs": {
-                    "conditioning": ["14", 0]
-                },
-                "class_type": "ConditioningZeroOut",
-                "_meta": {
-                    "title": "ConditioningZeroOut"
-                }
-                },
-                "49": {
-                "inputs": {
-                    "model": ["51", 0],
-                    "operation": ["50", 0]
-                },
-                "class_type": "LatentApplyOperationCFG",
-                "_meta": {
-                    "title": "LatentApplyOperationCFG"
-                }
-                },
-                "50": {
-                "inputs": {
-                    "multiplier": 1.15
-                },
-                "class_type": "LatentOperationTonemapReinhard",
-                "_meta": {
-                    "title": "LatentOperationTonemapReinhard"
-                }
-                },
-                "51": {
-                "inputs": {
-                    "shift": 6,
-                    "model": ["40", 0]
-                },
-                "class_type": "ModelSamplingSD3",
-                "_meta": {
-                    "title": "ModelSamplingSD3"
-                }
-                },
-                "52": {
-                "inputs": {
-                    "seed": "__RANDOM_INT__",
-                    "steps": 65,
-                    "cfg": 4,
-                    "sampler_name": "er_sde",
-                    "scheduler": "linear_quadratic",
-                    "denoise": 1,
-                    "model": ["49", 0],
-                    "positive": ["14", 0],
-                    "negative": ["44", 0],
-                    "latent_image": ["17", 0]
-                },
-                "class_type": "KSampler",
-                "_meta": {
-                    "title": "KSampler"
-                }
-                },
-                "59": {
-                "inputs": {
-                    "filename_prefix": "audio/ComfyUI",
-                    "quality": "V0",
-                    "audioUI": "",
-                    "audio": ["18", 0]
-                },
-                "class_type": "SaveAudioMP3",
-                "_meta": {
-                    "title": "Save Audio (MP3)"
-                }
-                }
-            }
-        }
-    } for lyrics in benchmark_lyrics
-]
-
-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,
-            benchmark_config=BenchmarkConfig(
-                dataset=benchmark_dataset,
-                runs=1
-            ),
-            workload_calculator= lambda _ : 1000.0
-        )
-    ],
-    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()

workers/comfyui-json/worker.py

@@ -1,81 +0,0 @@
-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.",
-]
-
-
-
-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,
-            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()

workers/openai/server.py

@@ -11,7 +11,6 @@ MODEL_SERVER_START_LOG_MSG = [
     "llama runner started",  # Ollama
     '"message":"Connected","target":"text_generation_router"',  # TGI
     '"message":"Connected","target":"text_generation_router::server"',  # TGI
-    "main: model loaded" # llama.cpp
 ]
 
 MODEL_SERVER_ERROR_LOG_MSGS = [

workers/openai/worker.py

@@ -1,78 +0,0 @@
-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,
-                runs=2
-            )
-        ),
-        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()

workers/tgi/worker.py

@@ -1,76 +0,0 @@
-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
-
-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,
-            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,
-            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()

workers/wan/worker.py

@@ -1,288 +0,0 @@
-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.",
-]
-
-benchmark_dataset = [
-    {
-        "input": {
-            "workflow_json": {
-                "90": {
-                    "inputs": {
-                    "clip_name": "umt5_xxl_fp8_e4m3fn_scaled.safetensors",
-                    "type": "wan",
-                    "device": "default"
-                    },
-                    "class_type": "CLIPLoader",
-                    "_meta": {
-                    "title": "Load CLIP"
-                    }
-                },
-                "91": {
-                    "inputs": {
-                    "text": "色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走，裸露，NSFW",
-                    "clip": [
-                        "90",
-                        0
-                    ]
-                    },
-                    "class_type": "CLIPTextEncode",
-                    "_meta": {
-                    "title": "CLIP Text Encode (Negative Prompt)"
-                    }
-                },
-                "92": {
-                    "inputs": {
-                    "vae_name": "wan_2.1_vae.safetensors"
-                    },
-                    "class_type": "VAELoader",
-                    "_meta": {
-                    "title": "Load VAE"
-                    }
-                },
-                "93": {
-                    "inputs": {
-                    "shift": 8.000000000000002,
-                    "model": [
-                        "101",
-                        0
-                    ]
-                    },
-                    "class_type": "ModelSamplingSD3",
-                    "_meta": {
-                    "title": "ModelSamplingSD3"
-                    }
-                },
-                "94": {
-                    "inputs": {
-                    "shift": 8,
-                    "model": [
-                        "102",
-                        0
-                    ]
-                    },
-                    "class_type": "ModelSamplingSD3",
-                    "_meta": {
-                    "title": "ModelSamplingSD3"
-                    }
-                },
-                "95": {
-                    "inputs": {
-                    "add_noise": "disable",
-                    "noise_seed": 0,
-                    "steps": 20,
-                    "cfg": 3.5,
-                    "sampler_name": "euler",
-                    "scheduler": "simple",
-                    "start_at_step": 10,
-                    "end_at_step": 10000,
-                    "return_with_leftover_noise": "disable",
-                    "model": [
-                        "94",
-                        0
-                    ],
-                    "positive": [
-                        "99",
-                        0
-                    ],
-                    "negative": [
-                        "91",
-                        0
-                    ],
-                    "latent_image": [
-                        "96",
-                        0
-                    ]
-                    },
-                    "class_type": "KSamplerAdvanced",
-                    "_meta": {
-                    "title": "KSampler (Advanced)"
-                    }
-                },
-                "96": {
-                    "inputs": {
-                    "add_noise": "enable",
-                    "noise_seed": "__RANDOM_INT__",
-                    "steps": 20,
-                    "cfg": 3.5,
-                    "sampler_name": "euler",
-                    "scheduler": "simple",
-                    "start_at_step": 0,
-                    "end_at_step": 10,
-                    "return_with_leftover_noise": "enable",
-                    "model": [
-                        "93",
-                        0
-                    ],
-                    "positive": [
-                        "99",
-                        0
-                    ],
-                    "negative": [
-                        "91",
-                        0
-                    ],
-                    "latent_image": [
-                        "104",
-                        0
-                    ]
-                    },
-                    "class_type": "KSamplerAdvanced",
-                    "_meta": {
-                    "title": "KSampler (Advanced)"
-                    }
-                },
-                "97": {
-                    "inputs": {
-                    "samples": [
-                        "95",
-                        0
-                    ],
-                    "vae": [
-                        "92",
-                        0
-                    ]
-                    },
-                    "class_type": "VAEDecode",
-                    "_meta": {
-                    "title": "VAE Decode"
-                    }
-                },
-                "98": {
-                    "inputs": {
-                    "filename_prefix": "video/ComfyUI",
-                    "format": "auto",
-                    "codec": "auto",
-                    "video": [
-                        "100",
-                        0
-                    ]
-                    },
-                    "class_type": "SaveVideo",
-                    "_meta": {
-                    "title": "Save Video"
-                    }
-                },
-                "99": {
-                    "inputs": {
-                    "text":prompt,
-                    "clip": [
-                        "90",
-                        0
-                    ]
-                    },
-                    "class_type": "CLIPTextEncode",
-                    "_meta": {
-                    "title": "CLIP Text Encode (Positive Prompt)"
-                    }
-                },
-                "100": {
-                    "inputs": {
-                    "fps": 16,
-                    "images": [
-                        "97",
-                        0
-                    ]
-                    },
-                    "class_type": "CreateVideo",
-                    "_meta": {
-                    "title": "Create Video"
-                    }
-                },
-                "101": {
-                    "inputs": {
-                    "unet_name": "wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors",
-                    "weight_dtype": "default"
-                    },
-                    "class_type": "UNETLoader",
-                    "_meta": {
-                    "title": "Load Diffusion Model"
-                    }
-                },
-                "102": {
-                    "inputs": {
-                    "unet_name": "wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors",
-                    "weight_dtype": "default"
-                    },
-                    "class_type": "UNETLoader",
-                    "_meta": {
-                    "title": "Load Diffusion Model"
-                    }
-                },
-                "104": {
-                    "inputs": {
-                    "width": 640,
-                    "height": 640,
-                    "length": 81,
-                    "batch_size": 1
-                    },
-                    "class_type": "EmptyHunyuanLatentVideo",
-                    "_meta": {
-                    "title": "EmptyHunyuanLatentVideo"
-                    }
-                }
-            }
-        }
-    } 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,
-            benchmark_config=BenchmarkConfig(
-                dataset=benchmark_dataset,
-                runs=1
-            ),
-            workload_calculator= lambda _ : 10000.0
-        )
-    ],
-    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()