Yeuoly 3799d40937 feat: support docker deployment for plugin 6 mēneši atpakaļ
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.idea 7ae728a9a3 fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) 10 mēneši atpakaļ
.vscode e61752bd3a feat/enhance the multi-modal support (#8818) 8 mēneši atpakaļ
configs 3799d40937 feat: support docker deployment for plugin 6 mēneši atpakaļ
constants 56e15d09a9 feat: mypy for all type check (#10921) 6 mēneši atpakaļ
contexts a1cdca02e3 fix: formatter 6 mēneši atpakaļ
controllers d2ff8a2381 fix: bugs 6 mēneši atpakaļ
core 3799d40937 feat: support docker deployment for plugin 6 mēneši atpakaļ
docker 8d4bb9b40d feat: integrate opendal storage (#11508) 7 mēneši atpakaļ
events 107e44c8fb Merge branch 'main' into fix/chore-fix 6 mēneši atpakaļ
extensions adf7eea7fe fix: ruff 6 mēneši atpakaļ
factories 78664c8903 Merge branch 'main' into fix/chore-fix 6 mēneši atpakaļ
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models a5555f90c6 fix: models 6 mēneši atpakaļ
schedule cf00ee42f5 send knowledge base auto disable notification (#12126) 6 mēneši atpakaļ
services 71e0bfcbd8 fix: updating tool credentials does not works as expected 6 mēneši atpakaļ
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templates 74d3320519 feat: account delete (#11829) 6 mēneši atpakaļ
tests 3799d40937 feat: support docker deployment for plugin 6 mēneši atpakaļ
.dockerignore 7c83d5ce76 feat: add dockerignore items 9 mēneši atpakaļ
.env.example 3799d40937 feat: support docker deployment for plugin 6 mēneši atpakaļ
.ruff.toml 72ae414da4 chore(lint): correct allowed-unused-imports settings for cleanup unused imports in tests (#11922) 6 mēneši atpakaļ
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README.md da601f0bef chore: update base image to Python 3.12 in Dockerfile (#10358) 7 mēneši atpakaļ
app.py 63a0b8ba79 feat: integrate psycogreen for gevent compatibility in PostgreSQL (#12253) 6 mēneši atpakaļ
app_factory.py 99f40a9682 feat: full support for opendal and sync configurations between .env and docker-compose (#11754) 6 mēneši atpakaļ
commands.py d2ff8a2381 fix: bugs 6 mēneši atpakaļ
dify_app.py 9b46b02717 refactor: assembling the app features in modular way (#9129) 7 mēneši atpakaļ
mypy.ini 56e15d09a9 feat: mypy for all type check (#10921) 6 mēneši atpakaļ
poetry.lock 63a0b8ba79 feat: integrate psycogreen for gevent compatibility in PostgreSQL (#12253) 6 mēneši atpakaļ
poetry.toml f62f71a81a build: initial support for poetry build tool (#4513) 1 gadu atpakaļ
pyproject.toml 63a0b8ba79 feat: integrate psycogreen for gevent compatibility in PostgreSQL (#12253) 6 mēneši atpakaļ
pytest.ini 096c0ad564 feat: Add support for TEI API key authentication (#11006) 7 mēneši atpakaļ

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
   cp .env.example .env 
  1. Generate a SECRET_KEY in the .env file.

bash for Linux ```bash for Linux sed -i "/^SECRET_KEY=/c\SECRET_KEY=$(openssl rand -base64 42)" .env

   bash for Mac
   ```bash for Mac
   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 3.12
   poetry install
  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 -C api --with dev
  1. Run the tests locally with mocked system environment variables in tool.pytest_env section in pyproject.toml
   poetry run -C api bash dev/pytest/pytest_all_tests.sh