mlrun

Overview of mlrun

What it is

MLRun is an open source AI orchestration platform for building and managing continuous (gen) AI applications across their lifecycle. It integrates into development and CI/CD environments, automating the delivery of production data, ML pipelines, and online applications. The platform aims to reduce engineering effort, time to production, and computation resources. It supports choosing any IDE locally or in the cloud, and breaks silos between data, ML, software, and DevOps/MLOps teams.

Key features

• Data management: batch or realtime processing at scale, data lineage and versioning, structured and unstructured data.
• Development: automated ML pipelines for data collection, preprocessing, training, and model evaluation.
• Deployment: productize trained models as serverless functions using real-time auto-scaling Nuclio serverless functions.
• Live Ops: monitor resources, data, model, and application metrics; identify risks, control costs, and measure business KPIs.
• Open architecture: supports various data stores, development tools, services, and platforms as listed in the official ecosystem documentation.

Use cases

• Building and managing continuous AI applications, including generative AI tasks.
• Processing unstructured data with LLMs, using vector databases, and applying guardrails for data management.
• Developing RAG workflows, evaluating and fine-tuning LLMs.
• Deploying LLMs as serverless functions with real-time serving graphs and GPU utilization.
• Monitoring model performance and enabling governance and explainability in production.

Getting started

See the repository README for tutorials, examples, and client environment setup instructions.

License and pricing

The project is licensed under Apache-2.0 and is open source. Pricing is not stated in the provided metadata.

Based on the project's public README and repository metadata.