4.0 KiB
Dify Backend API
Usage
-
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 docker-compose -f docker-compose.middleware.yaml -p dify up -d cd ../api
-
Copy
.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.
Dify API service uses Poetry to manage dependencies. You can execute
poetry shell
to activate the environment.Using pip can be found below.
-
Install dependencies
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 $(cat requirements-dev.txt) --group dev # install dependencies of development and update pyproject.toml
-
Run migrate
Before the first launch, migrate the database to the latest version.
poetry run python -m flask db upgrade
-
Start backend
poetry run python -m flask run --host 0.0.0.0 --port=5001 --debug
-
Start Dify web service.
-
Setup your application by visiting
http://localhost:3000
... -
If you need to debug local async processing, please start the worker service.
poetry run python -m celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail
The started celery app handles the async tasks, e.g. dataset importing and documents indexing.
Testing
-
Install dependencies for both the backend and the test environment
poetry install --with dev
-
Run the tests locally with mocked system environment variables in
tool.pytest_env
section inpyproject.toml
cd ../ poetry run -C api bash dev/pytest/pytest_all_tests.sh
Usage with pip
Note
In the next version, we will deprecate pip as the primary package management tool for dify api service, currently Poetry and pip coexist.
-
Start the docker-compose stack
The backend require some middleware, including PostgreSQL, Redis, and Weaviate, which can be started together using
docker-compose
.cd ../docker docker-compose -f docker-compose.middleware.yaml -p dify up -d cd ../api
-
Copy
.env.example
to.env
-
Generate a
SECRET_KEY
in the.env
file.sed -i "/^SECRET_KEY=/c\SECRET_KEY=$(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.
Testing
-
Install dependencies for both the backend and the test environment
pip install -r requirements.txt -r requirements-dev.txt
-
Run the tests locally with mocked system environment variables in
tool.pytest_env
section inpyproject.toml
dev/pytest/pytest_all_tests.sh