ModelsLab/modelq
ModelQ is a lightweight, battle-tested Python library for scheduling and queuing machine learning inference tasks. It's designed as a faster and simpler alternative to Celery for ML workloads, using Redis and threading to efficiently run background tasks.
ModelQ helps machine learning engineers and MLOps professionals manage and execute ML inference tasks reliably in the background. You provide your Python functions that perform AI model predictions, and ModelQ queues and runs them efficiently, providing structured results, real-time status updates, and even auto-generated APIs. This is ideal for anyone deploying AI models where predictions need to happen asynchronously.
Use this if you need a lightweight, Python-native solution to run machine learning inference tasks in the background, reliably handle task failures, and potentially expose them as easily consumable APIs.
Not ideal if your primary use case involves processing large volumes of streaming data with very low latency requirements or if your team is already heavily invested in a complex distributed task queue system.
Stars
18
Forks
2
Language
Python
License
MIT
Category
Last pushed
Mar 26, 2026
Commits (30d)
0
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