feat: worker affinity (#819)

* worker affinity

* worker affinity

* worker affinity

---------

Co-authored-by: Igor Loskutov <igor.loskutoff@gmail.com>

docker-compose.yml

@@ -34,7 +34,7 @@ services:
     environment:
       ENTRYPOINT: beat
 
-  hatchet-worker:
+  hatchet-worker-cpu:
     build:
       context: server
     volumes:
@@ -43,7 +43,20 @@ services:
     env_file:
       - ./server/.env
     environment:
-      ENTRYPOINT: hatchet-worker
+      ENTRYPOINT: hatchet-worker-cpu
+    depends_on:
+      hatchet:
+        condition: service_healthy
+  hatchet-worker-llm:
+    build:
+      context: server
+    volumes:
+      - ./server/:/app/
+      - /app/.venv
+    env_file:
+      - ./server/.env
+    environment:
+      ENTRYPOINT: hatchet-worker-llm
     depends_on:
       hatchet:
         condition: service_healthy

server/reflector/hatchet/run_workers.py

@@ -1,77 +0,0 @@
-"""
-Run Hatchet workers for the multitrack pipeline.
-Runs as a separate process, just like Celery workers.
-
-Usage:
-    uv run -m reflector.hatchet.run_workers
-
-    # Or via docker:
-    docker compose exec server uv run -m reflector.hatchet.run_workers
-"""
-
-import signal
-import sys
-
-from hatchet_sdk.rate_limit import RateLimitDuration
-
-from reflector.hatchet.constants import LLM_RATE_LIMIT_KEY, LLM_RATE_LIMIT_PER_SECOND
-from reflector.logger import logger
-from reflector.settings import settings
-
-
-def main() -> None:
-    """Start Hatchet worker polling."""
-    if not settings.HATCHET_ENABLED:
-        logger.error("HATCHET_ENABLED is False, not starting workers")
-        sys.exit(1)
-
-    if not settings.HATCHET_CLIENT_TOKEN:
-        logger.error("HATCHET_CLIENT_TOKEN is not set")
-        sys.exit(1)
-
-    logger.info(
-        "Starting Hatchet workers",
-        debug=settings.HATCHET_DEBUG,
-    )
-
-    # Import here (not top-level) - workflow modules call HatchetClientManager.get_client()
-    # at module level because Hatchet SDK decorators (@workflow.task) bind at import time.
-    # Can't use lazy init: decorators need the client object when function is defined.
-    from reflector.hatchet.client import HatchetClientManager  # noqa: PLC0415
-    from reflector.hatchet.workflows import (  # noqa: PLC0415
-        daily_multitrack_pipeline,
-        subject_workflow,
-        topic_chunk_workflow,
-        track_workflow,
-    )
-
-    hatchet = HatchetClientManager.get_client()
-
-    hatchet.rate_limits.put(
-        LLM_RATE_LIMIT_KEY, LLM_RATE_LIMIT_PER_SECOND, RateLimitDuration.SECOND
-    )
-
-    worker = hatchet.worker(
-        "reflector-pipeline-worker",
-        workflows=[
-            daily_multitrack_pipeline,
-            subject_workflow,
-            topic_chunk_workflow,
-            track_workflow,
-        ],
-    )
-
-    def shutdown_handler(signum: int, frame) -> None:
-        logger.info("Received shutdown signal, stopping workers...")
-        # Worker cleanup happens automatically on exit
-        sys.exit(0)
-
-    signal.signal(signal.SIGINT, shutdown_handler)
-    signal.signal(signal.SIGTERM, shutdown_handler)
-
-    logger.info("Starting Hatchet worker polling...")
-    worker.start()
-
-
-if __name__ == "__main__":
-    main()

server/reflector/hatchet/run_workers_cpu.py

@@ -0,0 +1,48 @@
+"""
+CPU-heavy worker pool for audio processing tasks.
+Handles ONLY: mixdown_tracks
+
+Configuration:
+- slots=1: Only mixdown (already serialized globally with max_runs=1)
+- Worker affinity: pool=cpu-heavy
+"""
+
+from reflector.hatchet.client import HatchetClientManager
+from reflector.hatchet.workflows.daily_multitrack_pipeline import (
+    daily_multitrack_pipeline,
+)
+from reflector.logger import logger
+from reflector.settings import settings
+
+
+def main():
+    if not settings.HATCHET_ENABLED:
+        logger.error("HATCHET_ENABLED is False, not starting CPU workers")
+        return
+
+    hatchet = HatchetClientManager.get_client()
+
+    logger.info(
+        "Starting Hatchet CPU worker pool (mixdown only)",
+        worker_name="cpu-worker-pool",
+        slots=1,
+        labels={"pool": "cpu-heavy"},
+    )
+
+    cpu_worker = hatchet.worker(
+        "cpu-worker-pool",
+        slots=1,  # Only 1 mixdown at a time (already serialized globally)
+        labels={
+            "pool": "cpu-heavy",
+        },
+        workflows=[daily_multitrack_pipeline],
+    )
+
+    try:
+        cpu_worker.start()
+    except KeyboardInterrupt:
+        logger.info("Received shutdown signal, stopping CPU workers...")
+
+
+if __name__ == "__main__":
+    main()

server/reflector/hatchet/run_workers_llm.py

@@ -0,0 +1,56 @@
+"""
+LLM/I/O worker pool for all non-CPU tasks.
+Handles: all tasks except mixdown_tracks (transcription, LLM inference, orchestration)
+"""
+
+from reflector.hatchet.client import HatchetClientManager
+from reflector.hatchet.workflows.daily_multitrack_pipeline import (
+    daily_multitrack_pipeline,
+)
+from reflector.hatchet.workflows.subject_processing import subject_workflow
+from reflector.hatchet.workflows.topic_chunk_processing import topic_chunk_workflow
+from reflector.hatchet.workflows.track_processing import track_workflow
+from reflector.logger import logger
+from reflector.settings import settings
+
+SLOTS = 10
+WORKER_NAME = "llm-worker-pool"
+POOL = "llm-io"
+
+
+def main():
+    if not settings.HATCHET_ENABLED:
+        logger.error("HATCHET_ENABLED is False, not starting LLM workers")
+        return
+
+    hatchet = HatchetClientManager.get_client()
+
+    logger.info(
+        "Starting Hatchet LLM worker pool (all tasks except mixdown)",
+        worker_name=WORKER_NAME,
+        slots=SLOTS,
+        labels={"pool": POOL},
+    )
+
+    llm_worker = hatchet.worker(
+        WORKER_NAME,
+        slots=SLOTS,  # not all slots are probably used
+        labels={
+            "pool": POOL,
+        },
+        workflows=[
+            daily_multitrack_pipeline,
+            topic_chunk_workflow,
+            subject_workflow,
+            track_workflow,
+        ],
+    )
+
+    try:
+        llm_worker.start()
+    except KeyboardInterrupt:
+        logger.info("Received shutdown signal, stopping LLM workers...")
+
+
+if __name__ == "__main__":
+    main()

server/reflector/hatchet/workflows/daily_multitrack_pipeline.py

@@ -23,7 +23,12 @@ from pathlib import Path
 from typing import Any, Callable, Coroutine, Protocol, TypeVar
 
 import httpx
-from hatchet_sdk import Context
+from hatchet_sdk import (
+    ConcurrencyExpression,
+    ConcurrencyLimitStrategy,
+    Context,
+)
+from hatchet_sdk.labels import DesiredWorkerLabel
 from pydantic import BaseModel
 
 from reflector.dailyco_api.client import DailyApiClient
@@ -467,6 +472,20 @@ async def process_tracks(input: PipelineInput, ctx: Context) -> ProcessTracksRes
     parents=[process_tracks],
     execution_timeout=timedelta(seconds=TIMEOUT_AUDIO),
     retries=3,
+    desired_worker_labels={
+        "pool": DesiredWorkerLabel(
+            value="cpu-heavy",
+            required=True,
+            weight=100,
+        ),
+    },
+    concurrency=[
+        ConcurrencyExpression(
+            expression="'mixdown-global'",
+            max_runs=1,  # serialize mixdown to prevent resource contention
+            limit_strategy=ConcurrencyLimitStrategy.GROUP_ROUND_ROBIN,  # Queue
+        )
+    ],
 )
 @with_error_handling(TaskName.MIXDOWN_TRACKS)
 async def mixdown_tracks(input: PipelineInput, ctx: Context) -> MixdownResult:

server/reflector/hatchet/workflows/topic_chunk_processing.py

@@ -7,7 +7,11 @@ Spawned dynamically by detect_topics via aio_run_many() for parallel processing.
 
 from datetime import timedelta
 
-from hatchet_sdk import ConcurrencyExpression, ConcurrencyLimitStrategy, Context
+from hatchet_sdk import (
+    ConcurrencyExpression,
+    ConcurrencyLimitStrategy,
+    Context,
+)
 from hatchet_sdk.rate_limit import RateLimit
 from pydantic import BaseModel
 
@@ -34,11 +38,13 @@ hatchet = HatchetClientManager.get_client()
 topic_chunk_workflow = hatchet.workflow(
     name="TopicChunkProcessing",
     input_validator=TopicChunkInput,
-    concurrency=ConcurrencyExpression(
-        expression="'global'",  # constant string = global limit across all runs
-        max_runs=20,
-        limit_strategy=ConcurrencyLimitStrategy.GROUP_ROUND_ROBIN,
-    ),
+    concurrency=[
+        ConcurrencyExpression(
+            expression="'global'",  # constant string = global limit across all runs
+            max_runs=20,
+            limit_strategy=ConcurrencyLimitStrategy.GROUP_ROUND_ROBIN,
+        )
+    ],
 )
 
 

server/runserver.sh

@@ -7,8 +7,10 @@ elif [ "${ENTRYPOINT}" = "worker" ]; then
     uv run celery -A reflector.worker.app worker --loglevel=info
 elif [ "${ENTRYPOINT}" = "beat" ]; then
     uv run celery -A reflector.worker.app beat --loglevel=info
-elif [ "${ENTRYPOINT}" = "hatchet-worker" ]; then
-    uv run python -m reflector.hatchet.run_workers
+elif [ "${ENTRYPOINT}" = "hatchet-worker-cpu" ]; then
+    uv run python -m reflector.hatchet.run_workers_cpu
+elif [ "${ENTRYPOINT}" = "hatchet-worker-llm" ]; then
+    uv run python -m reflector.hatchet.run_workers_llm
 else
     echo "Unknown command"
 fi