# Add Install Docker CI E2e > Add Install Docker CI E2e is an Agent Skill for devops & security published in the RLinf/RLinf repository on GitHub: a SKILL.md instruction file an AI agent can load to do this task. Adds install command in install script, Docker build stage in Dockerfile, and CI jobs for docker build and embodied e2e test when introducing a new model or environment in RLinf. Use when adding a new embodied model (e.g. dexbotic), new env (e.g. maniskill_libero), or new model+env combination that should be installable, dockerized, and tested in CI. - Skill name: `add-install-docker-ci-e2e` - Category: [DevOps & Security](https://www.openparable.com/skill/devops-security/1) - Source: https://github.com/RLinf/RLinf/blob/HEAD/.claude/skills/add-install-docker-ci-e2e/SKILL.md - Repository: RLinf/RLinf (4,124 GitHub stars when collected) ## SKILL.md # Add Install, Docker Build, and CI for a New Model or Environment Use this skill when adding a **new model** or **new environment** (or combination) to RLinf so that: (1) users can install it via `requirements/install.sh`, (2) a Docker image can be built for it (optional), (3) CI runs a Docker build and an end-to-end test. --- ## 1. Install script (`requirements/install.sh`) - **Register model or env** - New **model**: add to `SUPPORTED_MODELS` (e.g. `"dexbotic"`). - New **environment**: add to `SUPPORTED_ENVS` (e.g. `"maniskill_libero"`). - **Implement install logic** - **New model**: add `install__model()` that switches on `ENV_NAME` and for each supported env: create venv, install common embodied deps, env-specific deps, and the model. Call it from the main `case "$MODEL"` (add a new `model_name)` branch that runs `install__model`). - **New env only** (no new model): either add a new env branch inside an existing `install_*_model()` or add `install__env()` and call it from the relevant model installers. If the env is used by `install_env_only`, add a branch in `install_env_only` for that env. - **Help text** `print_help` shows `SUPPORTED_MODELS` and `SUPPORTED_ENVS`; no change needed if you only added to those arrays. See [reference.md](reference.md) for exact variable names and code patterns. --- ## 2. Dockerfile (`docker/Dockerfile`) - **Base image** If the combo needs a different base (e.g. Ubuntu 20 for ROS/Franka), add: `FROM AS base-image-embodied-` Otherwise reuse: `FROM nvidia/cuda:12.4.1-cudnn-devel-ubuntu22.04 AS base-image-embodied-`. - **Build stage** Add a stage: - `FROM embodied-common-image AS embodied--image` - **Single RUN for all installs**: If the image installs **multiple** envs (multiple model+env or venvs), chain every `install.sh` call in **one** `RUN` with `&&`. Splitting installs across multiple `RUN` layers breaks uv’s hardlink mode (`UV_LINK_MODE=hardlink`), because the cache from the previous layer is not in the same layer for hardlinking. Example: `RUN bash requirements/install.sh embodied --venv openvla --model openvla --env maniskill_libero && \` then ` bash requirements/install.sh embodied --venv openpi --model openpi --env maniskill_libero`. - Any asset download/link in the same or a following RUN; then `RUN echo "source \${UV_PATH}//bin/activate" >> ~/.bashrc` for default env. - **Final stage** The last stage is `FROM ${BUILD_TARGET}-image AS final-image`. Valid `BUILD_TARGET` values are those that have a matching `*-image` stage (e.g. `reason`, `embodied-maniskill_libero`, `embodied-dexbotic-maniskill_libero`). Adding a new stage makes the new target valid; no change to the final stage line. Naming: `BUILD_TARGET` is typically `embodied-` (e.g. `embodied-maniskill_libero`) or `embodied--` when one image combines multiple models (e.g. behavior-openvlaoft). Match the pattern used by existing stages. --- ## 3. CI: Docker build (`.github/workflows/docker-build.yml`) Add a job that builds the new image: - Job id: `build-embodied-` (same `` as in Dockerfile stage name, e.g. `build-embodied-maniskill_libero`). - Reuse the same steps as existing jobs: maximize storage, checkout, setup Docker Buildx, then build with `BUILD_TARGET=embodied-`, `NO_MIRROR=true`, `outputs: type=cacheonly`, and a tag like `rlinf:embodied-`. Copy an existing `build-embodied-*` job and replace the target name. See [reference.md](reference.md). --- ## 4. CI: Embodied e2e test (`.github/workflows/embodied-e2e-tests.yml`) - **Test config** Add a YAML config under `tests/e2e_tests/embodied/` (e.g. `__.yaml`). The e2e runner is `train_embodied_agent.py` with `--config-name `; the config name is the filename without `.yaml`. - **Workflow job** Add a job (e.g. `embodied---test`): - Checkout. - Create embodied environment: set `UV_*`, any required path env vars (e.g. `LIBERO_PATH`, `GR00T_PATH`), then `bash requirements/install.sh embodied --model --env `. - Run test: `source .venv/bin/activate`, set `REPO_PATH`, then `bash tests/e2e_tests/embodied/run.sh ` (or `run_async.sh` if the test is async). Use a reasonable `timeout-minutes`. - Clean up: `rm -rf .venv`, `uv cache prune`, and any test-specific cleanup. Use `runs-on: embodied` so the job runs on a runner with GPU/datasets. See existing jobs in the file for env vars and step order. --- ## Checklist - [ ] **Install script**: Model in `SUPPORTED_MODELS` and/or env in `SUPPORTED_ENVS`; `install_*` function and `case "$MODEL"` (or env) updated. - [ ] **Dockerfile**: `base-image-embodied-` if needed; `embodied--image` stage with `install.sh` and default venv. If multiple envs: all install.sh calls chained in one RUN (for uv hardlink). - [ ] **docker-build.yml**: New job `build-embodied-` with `BUILD_TARGET=embodied-`. - [ ] **E2e**: Config YAML in `tests/e2e_tests/embodied/`; new job in `embodied-e2e-tests.yml` (install env, run `run.sh `, clean up). --- Source: https://www.openparable.com/skill/devops-security/add-install-docker-ci-e2e (OpenParable). Cite the canonical URL above.