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100 lines
3.9 KiB
Python
100 lines
3.9 KiB
Python
from typing import Any
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import structlog
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from celery import shared_task
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from ee.session_recordings.ai.embeddings_queries import (
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fetch_errors_by_session_without_embeddings,
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fetch_recordings_without_embeddings,
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)
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from ee.session_recordings.ai.embeddings_runner import (
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SessionEmbeddingsRunner,
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ErrorEmbeddingsPreparation,
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SessionEventsEmbeddingsPreparation,
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)
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from ee.session_recordings.ai.error_clustering import error_clustering
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from posthog import settings
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from posthog.models import Team
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from posthog.tasks.utils import CeleryQueue
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from django.core.cache import cache
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logger = structlog.get_logger(__name__)
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# rate limits are per worker, and this task makes multiple calls to open AI
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# we currently are allowed 500 calls per minute, so let's rate limit each worker
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# to much less than that
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@shared_task(ignore_result=False, queue=CeleryQueue.SESSION_REPLAY_EMBEDDINGS.value, rate_limit="75/m")
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def embed_batch_of_recordings_task(recordings: list[Any], team_id: int) -> None:
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try:
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team = Team.objects.get(id=team_id)
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runner = SessionEmbeddingsRunner(team=team)
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runner.run(recordings, embeddings_preparation=SessionEventsEmbeddingsPreparation)
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results = fetch_errors_by_session_without_embeddings(team.pk)
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runner.run(results, embeddings_preparation=ErrorEmbeddingsPreparation)
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except Team.DoesNotExist:
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logger.info(f"[embed_batch_of_recordings_task] Team {team} does not exist. Skipping.")
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pass
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@shared_task(ignore_result=True)
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def generate_recordings_embeddings_batch() -> None:
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# see https://docs.celeryq.dev/en/stable/userguide/canvas.html
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# we have three jobs to do here
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# 1. get a batch of recordings
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# 2. for each recording - ideally in parallel - generate an embedding
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# 3. update CH with the embeddings in one update operation
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# in Celery that's a chain of tasks
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# with step 2 being a group of tasks
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# chord(
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# embed_single_recording.si(recording.session_id, recording.team_id)
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# for recording in fetch_recordings_without_embeddings(int(team))
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# )(generate_recordings_embeddings_batch_on_complete.si())
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# but even the docs call out performance impact of synchronising tasks
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#
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# so, for now, we'll do that naively
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for team_id in settings.REPLAY_EMBEDDINGS_ALLOWED_TEAMS:
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try:
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recordings = fetch_recordings_without_embeddings(int(team_id))
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logger.info(
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f"[generate_recordings_embeddings_batch] Fetched {len(recordings)} recordings",
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recordings=recordings,
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flow="embeddings",
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team_id=team_id,
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)
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embed_batch_of_recordings_task.si(recordings, int(team_id)).apply_async()
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except Exception as e:
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logger.error(f"[generate_recordings_embeddings_batch] Error: {e}.", exc_info=True, error=e)
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pass
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@shared_task(ignore_result=True)
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def generate_replay_embedding_error_clusters() -> None:
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for team_id in settings.REPLAY_EMBEDDINGS_ALLOWED_TEAMS:
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try:
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cluster_replay_error_embeddings.si(int(team_id)).apply_async()
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except Exception as e:
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logger.error(f"[generate_replay_error_clusters] Error: {e}.", exc_info=True, error=e)
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pass
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@shared_task(ignore_result=True, queue=CeleryQueue.SESSION_REPLAY_EMBEDDINGS.value)
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def cluster_replay_error_embeddings(team_id: int) -> None:
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try:
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team = Team.objects.get(id=team_id)
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clusters = error_clustering(team)
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cache.set(f"cluster_errors_{team.pk}", clusters, settings.CACHED_RESULTS_TTL)
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logger.info(
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f"[generate_replay_error_clusters] Completed for team",
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flow="embeddings",
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team_id=team_id,
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)
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except Team.DoesNotExist:
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logger.info(f"[generate_replay_error_clusters] Team {team} does not exist. Skipping.")
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pass
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