Charles YaoandClaude Opus 5
d2e204f133
Two defects, both introduced by the streaming switch in 3838db8aa7, which
together livelocked every Builder test run.
1. Self-deadlock. run_draft executes inside the Celery task
dify_builder_advance_task.advance_session. Streaming mode does not run
the workflow in place: it enqueues workflow_based_app_execution_task
via delay() on first subscribe (app_generate_service.py:322-324) and
returns a Redis subscription. The advance task then blocked on events
from a task needing the worker slot the advance task was holding.
Observed live: advance_session "succeeded in 300.59s" (the idle
timeout) four times over, while each workflow_run finished in under 2s.
Deadlocks every time at worker concurrency 1, and as soon as N test
runs are in flight at concurrency N.
2. Lost outcome. Blocking mode returns a Mapping
{"task_id", "workflow_run_id", "data"}, but the rewrite consumed the
response with `for chunk in response`, which walks a dict's KEYS as
strings. Probed against the real service: 3 chunks, 0 run-id matches,
0 terminal matches. So every run was recorded status="running" with an
empty dify_run_id, and the "running" branch bounced the user back to
build.execution -- forever. The pre-3838db8aa7 code read
response["data"] directly; the rewrite dropped that path.
Blocking mode restored, Mapping responses handled, and the shared tail
factored into _finish_run so the two paths cannot disagree about an
outcome. The stream-consumption path is kept and still tested, for a
future consumer that is NOT a worker -- which is what live per-node
streaming to the frontend will require.
Verified end to end on a local stack: one test run, status succeeded with
a real run id, advance_session 0.04-31.8s, and the session reaching
build.review instead of looping.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
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 AGENTS.mdContinue in the
apidirectory 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