Port the complete infrastructure for agent sandbox execution and skill system: Sandbox & Virtual Environment (core/sandbox/, core/virtual_environment/): - Sandbox entity with lifecycle management (ready/failed/cancelled states) - SandboxBuilder with fluent API for configuring providers - 5 VM providers: Local, SSH, Docker, E2B, AWS CodeInterpreter - VirtualEnvironment base with command execution, file transfer, transport layers - Channel transport: pipe, queue, socket implementations - Bash session management and DifyCli binary integration - Storage: archive storage, file storage, noop storage, presign storage - Initializers: DifyCli, AppAssets, DraftAppAssets, Skills - Inspector: file browser, archive/runtime source, script utils - Security: encryption utils, debug helpers Skill & App Assets (core/skill/, core/app_assets/, core/app_bundle/): - Skill entity and manager - App asset accessor, builder pipeline (file, skill builders) - App bundle source zip extractor - Storage and converter utilities API Endpoints: - CLI API blueprint (controllers/cli_api/) for sandbox callback - Sandbox provider management (workspace/sandbox_providers) - Sandbox file browser (console/sandbox_files) - App asset management (console/app/app_asset) - Skill management (console/app/skills) - Storage file endpoints (controllers/files/storage_files) Services: - Sandbox service, provider service, file service - App asset service, app bundle service Config: - CliApiConfig, CreatorsPlatformConfig, CollaborationConfig - FILES_API_URL for sandbox file access Note: Controller route registration temporarily commented out (marked TODO) pending resolution of deep dependency chains (socketio, workflow_comment, command node, etc.). Core sandbox modules are fully ported and syntax-validated. 110 files changed, 10,549 insertions. Made-with: Cursor
Dify Backend API
Setup and Run
Important
In the v1.3.0 release,
poetryhas been replaced withuvas the package manager for Dify API backend service.
uv and pnpm are required to run the setup and development commands below.
Using scripts (recommended)
The scripts resolve paths relative to their location, so you can run them from anywhere.
-
Run setup (copies env files and installs dependencies).
./dev/setup -
Review
api/.env,web/.env.local, anddocker/middleware.envvalues (see theSECRET_KEYnote below). -
Start middleware (PostgreSQL/Redis/Weaviate).
./dev/start-docker-compose -
Start backend (runs migrations first).
./dev/start-api -
Start Dify web service.
./dev/start-web./dev/setupand./dev/start-webinstall JavaScript dependencies through the repository root workspace, so you do not need a separatecd web && pnpm installstep. -
Set up your application by visiting
http://localhost:3000. -
Start the worker service (async and scheduler tasks, runs from
api)../dev/start-worker -
Optional: start Celery Beat (scheduled tasks).
./dev/start-beat
Environment notes
Important
When the frontend and backend run on different subdomains, set COOKIE_DOMAIN to the site’s top-level domain (e.g.,
example.com). The frontend and backend must be under the same top-level domain in order to share authentication cookies.
-
Generate a
SECRET_KEYin the.envfile.bash for Linux
sed -i "/^SECRET_KEY=/c\\SECRET_KEY=$(openssl rand -base64 42)" .envbash for Mac
secret_key=$(openssl rand -base64 42) sed -i '' "/^SECRET_KEY=/c\\ SECRET_KEY=${secret_key}" .env
Testing
-
Install dependencies for both the backend and the test environment
cd api uv sync --group dev -
Run the tests locally with mocked system environment variables in
tool.pytest_envsection inpyproject.toml, more can check Claude.mdcd api uv run pytest # Run all tests uv run pytest tests/unit_tests/ # Unit tests only uv run pytest tests/integration_tests/ # Integration tests # Code quality ./dev/reformat # Run all formatters and linters uv run ruff check --fix ./ # Fix linting issues uv run ruff format ./ # Format code uv run basedpyright . # Type checking