샌드박스에서 OpenCode 실행하기

Run OpenCode against a repository in a CoreWeave sandbox. Send a task from your terminal, check the resulting files, and save the workspace for later. The agent process, workspace, and commands run in the sandbox. Model requests go to your configured provider.

Prerequisites

Before you begin, you need the following:

샌드박스 액세스에 사용할 W&B API 키. 이 예시에서는 W&B 인증을 사용합니다.
W&B Serverless Inference 또는 다른 OpenCode 공급자를 통한 모델 액세스 권한. 공급자 액세스 및 결제는 샌드박스 액세스와 별도로 관리됩니다.
공개 저장소 URL. 비공개 저장소를 사용하려면 샌드박스 내부에 Git 자격 증명이 필요합니다.
설치 안내에 따라 설치한 cws-agent.

로컬 터미널에서 [WANDB-API-KEY]를 전체 W&B API 키로 바꾸세요.

export WANDB_API_KEY="[WANDB-API-KEY]"
unset CWSANDBOX_API_KEY

cws-agent가 W&B 인증을 선택하게 하려면 CWSANDBOX_API_KEY 설정을 해제하세요.

Launch OpenCode with cws-agent

cws-agent를 사용해 샌드박스에 OpenCode를 설치하고, 저장소를 /workspace/project 디렉터리에 클론한 다음, 파일 시스템 스냅샷에 사용할 스냅샷 마운트를 설정하세요. Choose one of the following provider options. Replace [SANDBOX-NAME] with a session name containing 1 to 40 lowercase letters, digits, or hyphens. Start the name with a letter or digit. Replace [REPOSITORY-URL] with your public repository URL.

Use W&B Serverless Inference (recommended)

W&B Serverless Inference is the preferred provider for this guide. You can use it to access hosted open models. You can use any model and provider supported by OpenCode instead. Follow Use another model provider. Complete the W&B Serverless Inference prerequisites, including a W&B project, and check your available inference credits. This example selects GLM 5.2 explicitly:

cws-agent launch [SANDBOX-NAME] --agent opencode \
  --repo-url [REPOSITORY-URL] --lifetime 2h \
  --wandb --wandb-model zai-org/GLM-5.2 \
  --permission-mode native --detach

--wandb 프리셋은 W&B의 추론 엔드포인트를 설정하고, WANDB_API_KEY를 샌드박스로 전달하며, OpenCode가 해당 공급자만 사용하도록 제한합니다. 에이전트는 이 키 하나로 추론과 샌드박스에 모두 액세스할 수 있습니다. 다른 W&B 모델을 사용하려면 zai-org/GLM-5.2를 사용 가능한 모델 목록에 있는 ID로 바꾸세요.

Use another model provider

To use another provider, omit --wandb and --wandb-model when you create the sandbox. Export that provider’s API key locally. For example, choose one of these alternatives and replace the key placeholder:

Anthropic
OpenAI

export ANTHROPIC_API_KEY="[ANTHROPIC-API-KEY]"

export OPENAI_API_KEY="[OPENAI-API-KEY]"

Replace [PROVIDER-ID]/[MODEL-ID] in both fields with your OpenCode model identifier, using the anthropic/ or openai/ provider prefix as appropriate. The small_model field selects the model for lightweight tasks such as title generation. See OpenCode models.

export OPENCODE_CONFIG_CONTENT='{"model":"[PROVIDER-ID]/[MODEL-ID]","small_model":"[PROVIDER-ID]/[MODEL-ID]"}'
cws-agent launch [SANDBOX-NAME] --agent opencode \
  --repo-url [REPOSITORY-URL] --lifetime 2h \
  --env-passthrough OPENCODE_CONFIG_CONTENT \
  --permission-mode native --detach

If they’re set, cws-agent forwards ANTHROPIC_API_KEY and OPENAI_API_KEY. For providers whose keys aren’t forwarded automatically, follow their OpenCode provider configuration and use --env-passthrough [VARIABLE-NAME] for additional environment variables. Both launch options print session ready. after setup. --detach leaves the sandbox running without opening the terminal interface or importing local skills and Model Context Protocol (MCP) configuration. The 2-hour lifetime is a wall-clock limit, including setup. Stop compute when you finish.

Run a task and check the result

From your local terminal, ask OpenCode to write and read a file:

cws-agent run [SANDBOX-NAME] \
  'Create sandbox-proof.txt in the current directory containing exactly Hello from CoreWeave followed by a newline, then read it back. Do not commit or push anything.' \
  --permission-mode native

This runs OpenCode without an interactive terminal. --permission-mode native keeps OpenCode’s configured permissions. Without it, cws-agent defaults to accepting approval requests. If your OpenCode policy requires approval for the task, use an interactive session to approve it. See OpenCode permissions. Check the actual file independently of the agent’s response:

cws-agent exec [SANDBOX-NAME] 'cat /workspace/project/sandbox-proof.txt'

The output should be Hello from CoreWeave. Before you stop compute, retrieve a local copy:

cws-agent exec [SANDBOX-NAME] 'cat /workspace/project/sandbox-proof.txt' > sandbox-proof.txt

Optional: Work interactively

From an interactive terminal on macOS or Linux, open OpenCode in the same workspace:

cws-agent connect [SANDBOX-NAME] --permission-mode native --no-config-sync

The --no-config-sync flag skips local skills and MCP imports. Send prompts and approve actions in OpenCode, then use /exit to return to your local terminal. When you exit OpenCode, the sandbox continues to run. Repeat the connection command to open OpenCode again. It doesn’t automatically select a previous conversation. For conversation history and resume commands, see cws-agent sessions.

Save, stop, and restore

After the agent finishes, snapshot the workspace and stop compute:

cws-agent down [SANDBOX-NAME]

down saves the /workspace directory before stopping the sandbox. If the snapshot fails, the sandbox remains running. Inspect the error and retry after resolving it. To stop without waiting for an explicit snapshot, run:

cws-agent down [SANDBOX-NAME] --no-snapshot

Don’t rely on this command to save changes. Copy results elsewhere or confirm a completed snapshot before stopping. Restore requires a completed snapshot. To return to a workspace saved with W&B inference, make sure WANDB_API_KEY is still exported in your local terminal, then run:

cws-agent restore [SANDBOX-NAME] --wandb --wandb-model zai-org/GLM-5.2 --lifetime 2h --no-config-sync

Use the same --wandb-model value you launched with. If you omit it while using --wandb, restore selects the preset’s default model. For another provider, re-export its key and OPENCODE_CONFIG_CONTENT, then run:

cws-agent restore [SANDBOX-NAME] --env-passthrough OPENCODE_CONFIG_CONTENT --lifetime 2h --no-config-sync

Restore creates a new sandbox from the saved workspace. Supply environment-only credentials again. Snapshots can contain saved OpenCode logins and conversation data, but they don’t preserve running processes. Run the file check again to confirm the sandbox-proof.txt file survived. Continue with cws-agent run or the interactive connection command. Stop the restored sandbox with cws-agent down when you finish.

Troubleshoot

If setup or a task fails, use the following checks:

샌드박스 인증에 실패하는 경우: 전체 W&B API 키와 샌드박스 액세스 권한을 확인하세요.
W&B 모델 요청이 실패하는 경우: 추론 액세스 권한, 크레딧, 모델 ID를 확인하세요. 샌드박스 액세스 권한이 있다고 해서 추론 액세스 권한이 부여되지는 않습니다.
다른 공급자를 사용할 수 없는 경우: --wandb 없이 새 세션을 시작하세요. W&B 프리셋은 워크스페이스에 저장되므로 복원할 때 --wandb를 생략해도 프리셋은 제거되지 않습니다. 기존 워크스페이스는 W&B 프리셋 설정을 참조하세요.
헤드리스 작업에 승인이 필요한 경우: 대화형으로 연결해 OpenCode의 승인 프롬프트에 응답한 후 계속 진행하세요.

Next steps

For more information, see these guides:

Run agents on CoreWeave sandboxes explains agent execution models and workspace lifetimes.
OpenCode configuration covers model, provider, and project settings.
Use the Sandbox SDK explains how to manage command execution directly from your application.

​Prerequisites

​Launch OpenCode with cws-agent

​Use W&B Serverless Inference (recommended)

​Use another model provider

​Run a task and check the result

​Optional: Work interactively

​Save, stop, and restore

​Troubleshoot

​Next steps