aimake, an AI Pipeline Build Tool, Released

aimake, an incremental build system for AI application development, has been released. This tool builds a dependency graph for pipelines ranging from datasets to evaluation, and detects changes based on content-hash of input values.

Unlike existing timestamp-based caching, it only re-executes steps where the actual content has changed, so expensive operations such as embedding or vector index generation do not need to be re-run when modifying prompts. Unlike Airflow or DVC, it focuses on make-style dependency management and incremental builds.

Key features include:

• Fingerprint generation and caching based on content hash
• Support for parallel incremental builds
• Provides plan, build, and explain CLI commands
• Integration with S3 cache and plugins such as Hugging Face, DVC, Docker, Ollama, and W&B

It can be installed via pip install aimake and is useful for developers looking to improve the efficiency of RAG or evaluation pipelines.