The backend require some middleware, including PostgreSQL, Redis, and Weaviate, which can be started together using docker-compose
.
cd ../docker
docker-compose -f docker-compose.middleware.yaml -p dify up -d
cd ../api
.env.example
to .env
Generate a SECRET_KEY
in the .env
file.
sed -i "/^SECRET_KEY=/c\SECRET_KEY=$(openssl rand -base64 42)" .env
secret_key=$(openssl rand -base64 42)
sed -i '' "/^SECRET_KEY=/c\\
SECRET_KEY=${secret_key}" .env
Create environment.
Dify API service uses Poetry to manage dependencies. You can execute poetry shell
to activate the environment.
Using pip can be found below.
=======
poetry env use 3.10
poetry install
In case of contributors missing to update dependencies for pyproject.toml
, you can perform the following shell instead.
poetry shell # activate current environment
poetry add $(cat requirements.txt) # install dependencies of production and update pyproject.toml
poetry add $(cat requirements-dev.txt) --group dev # install dependencies of development and update pyproject.toml
Before the first launch, migrate the database to the latest version.
poetry run python -m flask db upgrade
Start backend
poetry run python -m flask run --host 0.0.0.0 --port=5001 --debug
Start Dify web service.
Setup your application by visiting http://localhost:3000
...
If you need to debug local async processing, please start the worker service.
poetry run python -m celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail
The started celery app handles the async tasks, e.g. dataset importing and documents indexing.
Install dependencies for both the backend and the test environment
poetry install --with dev
Run the tests locally with mocked system environment variables in tool.pytest_env
section in pyproject.toml
cd ../
poetry run -C api bash dev/pytest/pytest_all_tests.sh
[!NOTE]
In the next version, we will deprecate pip as the primary package management tool for dify api service, currently Poetry and pip coexist.
The backend require some middleware, including PostgreSQL, Redis, and Weaviate, which can be started together using docker-compose
.
cd ../docker
docker-compose -f docker-compose.middleware.yaml -p dify up -d
cd ../api
.env.example
to .env
Generate a SECRET_KEY
in the .env
file.
sed -i "/^SECRET_KEY=/c\SECRET_KEY=$(openssl rand -base64 42)" .env
Create environment.
If you use Anaconda, create a new environment and activate it
conda create --name dify python=3.10
conda activate dify
Install dependencies
pip install -r requirements.txt
Run migrate
Before the first launch, migrate the database to the latest version.
flask db upgrade
Start backend:
flask run --host 0.0.0.0 --port=5001 --debug
Setup your application by visiting http://localhost:5001/console/api/setup or other apis...
If you need to debug local async processing, please start the worker service.
celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail
The started celery app handles the async tasks, e.g. dataset importing and documents indexing.