In simple English
This tool helps you run artificial intelligence programs on remote servers without managing the servers yourself. You write simple Python code and the system handles scaling up when busy and scaling down to zero when idle. It gives you fast start times for containers and supports powerful graphics cards. You can use their managed cloud service or self-host the open-source engine for free. The project uses the AGPL-3.0 licence, which means if you modify and host it as a service, you must share your changes.
What it is
Beam is a fast, open-source runtime and orchestration engine for serverless AI workloads, sandboxes, and background tasks. It provides a Python client library and a Go-based backend to deploy and scale containerized applications on GPUs or CPUs.
What it is good for
Solo builders who want to deploy machine learning models, large language models, or isolated code sandboxes without setting up complex Kubernetes clusters or cloud infrastructure.
- Launches containers quickly using custom scheduling and embedded caching.
- Offers a simple Python-based decorator interface for endpoints and background tasks.
- Supports both managed cloud hosting and free self-hosting.
- Requires an understanding of containerization and cloud infrastructure if self-hosting.
- Demands access to server hardware with a GPU for heavy artificial intelligence workloads.
- The AGPL-3.0 licence places restrictions on network services if you modify the source code.
manual server management or complex cloud orchestration tools
FastAPI
- modal-labs/modal-client528 stars
Runs serverless functions and artificial intelligence workloads on remote cloud infrastructure using Python decorators.
- deepset-ai/haystack27k stars
A Python framework for joining language models, document search and tools into one working pipeline.
- Giskard-AI/giskard-oss5.9k stars
A Python library that writes tests for language-model programs and tries to break them on purpose.
- ggml-org/llama.cpp132k stars
A C and C++ library and command-line tool for running language models locally.
pip install beam-client