
Alembic's offline mode generates SQL from SQLAlchemy migration operations, providing developers with a clear view of database schema changes without requiring an active database connection. However, some migration versions (specifically bbadea11becb and d7999dfa4aae) were performing database schema introspection, which fails in offline mode since it requires an actual database connection. This commit: - Adds offline mode support by detecting context.is_offline_mode() - Skips introspection steps when in offline mode - Adds warning messages in SQL output to inform users that assumptions were made - Prompts users to review the generated SQL for accuracy These changes ensure migrations work consistently in both online and offline modes. Close #19284.
Dify Backend API
Usage
Important
In the v1.3.0 release,
poetry
has been replaced withuv
as the package manager for Dify API backend service.
-
Start the docker-compose stack
The backend require some middleware, including PostgreSQL, Redis, and Weaviate, which can be started together using
docker-compose
.cd ../docker cp middleware.env.example middleware.env # change the profile to other vector database if you are not using weaviate docker compose -f docker-compose.middleware.yaml --profile weaviate -p dify up -d cd ../api
-
Copy
.env.example
to.env
cp .env.example .env
-
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
-
Create environment.
Dify API service uses UV to manage dependencies. First, you need to add the uv package manager, if you don't have it already.
pip install uv # Or on macOS brew install uv
-
Install dependencies
uv sync --dev
-
Run migrate
Before the first launch, migrate the database to the latest version.
uv run flask db upgrade
-
Start backend
uv run flask run --host 0.0.0.0 --port=5001 --debug
-
Start Dify web service.
-
Setup your application by visiting
http://localhost:3000
. -
If you need to handle and debug the async tasks (e.g. dataset importing and documents indexing), please start the worker service.
uv run celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail,ops_trace,app_deletion
Testing
-
Install dependencies for both the backend and the test environment
uv sync --dev
-
Run the tests locally with mocked system environment variables in
tool.pytest_env
section inpyproject.toml
uv run -P api bash dev/pytest/pytest_all_tests.sh