tensorchord/envd
Some data may be outdated — see provenance labels.
🏕️ Reproducible development environment for humans and agents observed · 2026-09-30
Health v2 · maintenance only
98/100
- Activity 97
- Release rhythm 97
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-10-21. Adoption (stars, forks) is never an input.
- gap_med: 3
- age_days: 1653
- days_rel: 23
- days_push: 23
- n_releases_24m: 22
Adoption not part of the score
2236 stars · 168 forks observed · 2026-09-30
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
envd is a command-line tool that creates reproducible, container-based development environments for AI/ML work using a simple Python-like build.envd declaration instead of hand-written Dockerfiles. It builds OCI-compatible images with built-in support for Jupyter, VSCode remote, CUDA, and conda/pip dependencies, and can also provision environments for AI coding agents.
Use cases
- set up a reproducible python machine learning dev environment
- replace dockerfiles with a declarative build.envd
- create a container with cuda and pytorch dependencies
- spin up jupyter and vscode remote in an isolated container
- share and publish dev environments as OCI images
- provision consistent environments for AI coding agents like codex
- reuse environment build functions across a team via git includes
When to choose
- you do AI/ML development with complex Python, CUDA, and system dependencies
- you want reproducible, versioned dev environments without writing Dockerfiles
- your team needs to share and reuse environment definitions
- you want first-class Jupyter and VSCode remote support in containers
When to avoid
- you need a general-purpose CI/CD pipeline tool rather than a dev environment manager
- your project has no containerization or dependency complexity
- you cannot use Docker or an OCI-compatible runtime
- you need lightweight virtualenv/conda-only workflows without containers
Facets
cli-tool · maturity active
developer-tools container-runtime build-tool configuration-management deployment developer-tools machine-learning data-science windows cli python go development-environment buildkit reproducible-environments mlops llmops cuda jupyter vscode-remote oci-images ai-agents containers command-line linux macos docker
3 sources
- readme: https://github.com/tensorchord/envd · fetched 2026-09-30 · 5755faf29fff
- homepage: https://envd.tensorchord.ai/ · fetched 2026-08-29 · 6fd55d97a612
- site_page: https://envd.tensorchord.ai/guide/getting-started · fetched 2026-08-29 · 3e2c382b7f83
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| tensorchord/envd | main | 98 |
For agents
markdown · JSON · MCP: product_card(name="tensorchord/envd")
Data as of 2026-10-19T08:05:51.212177+00:00 · Report a problem