Description:
Reproducible development environment for AI/ML
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Type: Formula
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Latest Version: 1.3.2@0
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Tracked Since: Dec 17, 2025
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Links:
Homepage |
@tensorchord |
formulae.brew.sh
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Category: Ai ml
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Tags:
ai
ml
dev-environments
reproducibility
docker
python
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Install:
brew install envd
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About:
envd is a command-line tool that builds reproducible, isolated development environments for AI and machine learning workflows. It abstracts away complex dependencies like CUDA drivers and Python libraries into a simple, version-controlled configuration. This ensures consistent setups across local machines, remote servers, and cloud platforms, eliminating the 'works on my machine' problem.
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Key Features:
- Declarative environment configuration using Starlark
- Automatic management of CUDA, cuDNN, and GPU drivers
- Seamless integration with Jupyter, VS Code, and SSH
- Built-in layer caching for fast environment rebuilds
- Portable environments that work across different hosts
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Use Cases:
- Standardizing ML development environments across a team
- Reproducible experiments for research papers and model training
- Setting up cloud-based development environments (e.g., on AWS EC2)
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Alternatives:
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Docker
– Docker is more general-purpose, while envd is specifically optimized for the dependencies and workflows of AI/ML development.
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Conda
– Conda manages Python packages but does not handle system-level dependencies like CUDA or provide full environment isolation.
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Poetry
– Poetry is excellent for Python dependency management but lacks support for non-Python system libraries and GPU drivers.
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License: Apache-2.0
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Bottles available for: arm64_tahoe, arm64_sequoia, arm64_sonoma, sonoma, arm64_linux, x86_64_linux
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