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.idea 7ae728a9a3 fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) 8 hónapja
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constants 8c51d06222 feat: regenerate in `Chat`, `agent` and `Chatflow` app (#7661) 7 hónapja
contexts 3571292fbf chore(api): Introduce Ruff Formatter. (#7291) 8 hónapja
controllers 8204e0e14a fix: Count exception occurs when searching conversations (#8754) 6 hónapja
core 6b6e94da08 Fix code indentation errors (#9164) 6 hónapja
docker 8dfdb37de3 fix: use LOG_LEVEL for celery startup (#7628) 8 hónapja
events 74f58f29f9 chore: bump ruff to 0.6.8 for fixing violation in SIM910 (#8869) 6 hónapja
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migrations 37d5c166ca fix(migrations): correct parent_message_id for service-api records (#9132) 6 hónapja
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README.md e75c33a561 Enhance Readme Documentation to Clarify the Importance of Celery Service (#8558) 7 hónapja
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commands.py bef83a4d2e fix: typos and improve naming conventions: (#8687) 7 hónapja
poetry.lock b360feb4c1 refactor: introduce storage factory and speed up api startup by importing storage client on demand (#9086) 6 hónapja
poetry.toml f62f71a81a build: initial support for poetry build tool (#4513) 10 hónapja
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README.md

Dify Backend API

Usage

[!IMPORTANT] In the v0.6.12 release, we deprecated pip as the package management tool for Dify API Backend service and replaced it with poetry.

  1. 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
  1. Copy .env.example to .env
  2. 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
  1. Create environment.

Dify API service uses Poetry to manage dependencies. You can execute poetry shell to activate the environment.

  1. Install dependencies
   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
  1. Run migrate

Before the first launch, migrate the database to the latest version.

   poetry run python -m flask db upgrade
  1. Start backend
   poetry run python -m flask run --host 0.0.0.0 --port=5001 --debug
  1. Start Dify web service.
  2. Setup your application by visiting http://localhost:3000...
  3. If you need to handle and debug the async tasks (e.g. dataset importing and documents indexing), please start the worker service.
   poetry run python -m celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail,ops_trace,app_deletion

Testing

  1. Install dependencies for both the backend and the test environment
   poetry install --with dev
  1. 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