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Documentation Index

Fetch the complete documentation index at: https://docs.orchagent.io/llms.txt

Use this file to discover all available pages before exploring further.

Agents with runtime.command (code runtime) or loop config (managed loop) run in E2B sandboxes. The platform automatically selects the right base image based on your agent’s entrypoint:
EntrypointBase ImageIncludes
.py filesPython basePython 3.11, pip
.js filesNode.js baseNode.js 20, npm, Python 3
JavaScript agents get a dedicated Node.js sandbox template with both Node.js and Python pre-installed. Dependencies from package.json are installed automatically via npm ci (when a lockfile is present) or npm install. Custom environments let you add dependencies beyond the defaults.

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Predefined Environments

Four ready-to-use environments are available to all users:
NamePackages
python-mlnumpy, pandas, scikit-learn, matplotlib, seaborn
python-ffmpegffmpeg-python, moviepy, imageio-ffmpeg
python-imagepillow, opencv-python-headless
python-scrapingrequests, beautifulsoup4, lxml, httpx

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Set as Workspace Default

All agents in your workspace can use a default environment: Via CLI: 
orch env list                        # Find environment ID
orch env set-default <environment-id>
Via Web UI: Settings → Workspace → Default Environment Agents without their own Dockerfile use this default.

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Custom Environments

Need specific packages? Include a Dockerfile in your agent directory.

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Quick Start

FROM e2bdev/code-interpreter:latest
RUN pip install numpy pandas scikit-learn --no-cache-dir
Publish with the --docker flag: 
orch publish --docker
The platform builds your custom environment. First build takes 2-5 minutes; subsequent publishes with the same Dockerfile reuse the cached build.
You don’t need Docker installed locally. The platform handles all building.

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Dockerfile Guidelines

Base image (required): 
FROM e2bdev/code-interpreter:latest
What works: 
# Python packages
RUN pip install package1 package2 --no-cache-dir

# System packages
RUN apt-get update && apt-get install -y ffmpeg && rm -rf /var/lib/apt/lists/*

# Environment variables
ENV MY_VAR=value
What doesn’t work: 
COPY ./data /app   # Rejected - no build context available
ADD ./file /app    # Rejected - no build context available
EXPOSE 8080        # Rejected - sandboxes don't expose ports
ENTRYPOINT [...]   # Ignored - overridden by sandbox
CMD [...]          # Ignored - overridden by sandbox
COPY and ADD commands are rejected because Dockerfiles are built in isolation without access to your bundle files. Install dependencies via pip/apt instead, or download files at runtime in your agent code.

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Example: Video Processing Agent

FROM e2bdev/code-interpreter:latest
RUN pip install ffmpeg-python moviepy imageio-ffmpeg --no-cache-dir
Prefer pip install over apt-get when possible. Many system packages (like ffmpeg) have pure-Python alternatives (like imageio-ffmpeg) that work better in cloud sandboxes.

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CLI Commands

orch env list                          # List available environments
orch env status <id>                   # Check build status
orch env create -f Dockerfile -n name  # Create from Dockerfile
orch env delete <id>                   # Delete (if no agents use it)
orch env set-default <id>              # Set workspace default
orch env clear-default                 # Clear workspace default

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Environment Priority

When running an agent in a sandbox:
  1. Agent-specific — Dockerfile in bundle creates dedicated environment
  2. Workspace default — Falls back to workspace’s default environment
  3. Base image — Uses E2B’s base code-interpreter if neither set
Dynamic workspace defaults: Changing your workspace default immediately affects all agents that don’t have their own Dockerfile. Existing agents without agent-specific environments will use the new default on their next run.

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Service Environments

Always-on services use a different runtime from on-demand runs:
On-demand (orch run)Always-on (orch service deploy)
RuntimeE2B sandboxCloud Run container
Base imagee2bdev/code-interpreterService runner (Python 3.11 + Node.js 20)
DependenciesInstalled per runInstalled once at deploy time
Custom DockerfileYes (orch publish --docker)Not yet supported
EntrypointPlatform-managedAuto-detected or --command flag
Service dependencies are installed from your requirements.txt or package.json during deployment. The service runner pre-installs common tools (pip, npm, git).
Custom Dockerfiles are not yet supported for services. If your service needs system packages beyond the defaults, use a run_command in your manifest that installs them at startup.