Files
dify/api
Charles YaoandClaude Opus 5 2fb51857ce fix(workflow): name the node in every node-config error
A graph-init failure surfaced as "2 validation errors for
HttpRequestNodeData ..." -- pydantic names the model class, never the
node. graphon logs the node id and re-raises the raw error, so the error
frame the Builder received (ESQ1-302) could not say which node was
wrong, and its repair agent had to guess.

DifyNodeFactory.create_node now re-raises every ValueError from the
validation stage (shared-shape validation, class resolution, concrete
NodeData re-validation) prefixed "node '<id>' (<type>): ". This runs for
EVERY workflow start, so the error text of every graph-init failure
changes, not only the Builder's. The wrapped error is a plain ValueError,
so app_generator's handling takes its ValueError branch (log only under
DEBUG) instead of the ValidationError branch; the published error is the
same.

validate_node_config runs the same three validation steps with no
factory instance and no runtime state -- the dry Graph.init a draft can
be put through before it is written or run.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-09-21 21:07:44 -07:00
..
2026-09-19 09:26:15 +00:00
…
…

Dify Backend API

Setup and Run

Important

In the v1.3.0 release, poetry has been replaced with uv as the package manager for Dify API backend service.

uv and pnpm are required to run the setup and development commands below.

The scripts resolve paths relative to their location, so you can run them from anywhere.

  1. Run setup (copies env files and installs dependencies).

    ./dev/setup
    
  2. Review api/.env, web/.env.local, and docker/middleware.env values (see the SECRET_KEY note below).

  3. Start middleware (PostgreSQL/Redis/Weaviate).

    ./dev/start-docker-compose
    
  4. Start backend (runs migrations first).

    ./dev/start-api
    
  5. Start Dify web service.

    ./dev/start-web
    

    ./dev/setup and ./dev/start-web install JavaScript dependencies through the repository root workspace, so you do not need a separate cd web && pnpm install step.

  6. Set up your application by visiting http://localhost:3000.

  7. Start the worker service (async and scheduler tasks, runs from api).

    ./dev/start-worker
    
  8. 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_KEY in the .env file.

    bash for Linux

    sed -i "/^SECRET_KEY=/c\\SECRET_KEY=$(openssl rand -base64 42)" .env
    

    bash for Mac

    secret_key=$(openssl rand -base64 42)
    sed -i '' "/^SECRET_KEY=/c\\
    SECRET_KEY=${secret_key}" .env
    

Testing

  1. Install dependencies for both the backend and the test environment

    cd api
    uv sync --group dev
    
  2. Run the tests locally with mocked system environment variables in tool.pytest_env section in pyproject.toml, more can check AGENTS.md

    Continue in the api directory from the previous step.

    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 pyrefly check         # Type checking
    

Generate TS stub

uv run dev/generate_swagger_specs.py --output-dir openapi

use https://jsontotable.org/openapi-to-typescript to convert to typescript