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-LAN- 90f093eb67
fix(json_in_md_parser): improve error messages for JSON parsing failures (#11948)
10 mesi fa
..
.idea fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) 1 anno fa
.vscode feat/enhance the multi-modal support (#8818) 1 anno fa
configs feat: add workflow parallel depth limit configuration (#11460) 10 mesi fa
constants fix: support mdx files close #11557 (#11565) 10 mesi fa
contexts feat/enhance the multi-modal support (#8818) 1 anno fa
controllers fix: refactor conversation pagination to use SQLAlchemy session manag… (#11956) 10 mesi fa
core feat(code_node): add more check (#11949) 10 mesi fa
docker feat: integrate opendal storage (#11508) 10 mesi fa
events chore: bump minimum supported Python version to 3.11 (#10386) 11 mesi fa
extensions chore(db): use a better way to export models and remove unused table (#11838) 10 mesi fa
factories fix(file_factory): validate upload_file_id before querying UploadFile (#11937) 10 mesi fa
fields Feat: Retry on node execution errors (#11871) 10 mesi fa
libs fix(json_in_md_parser): improve error messages for JSON parsing failures (#11948) 10 mesi fa
migrations chore: add retry index migration (#11887) 10 mesi fa
models fix: refactor conversation pagination to use SQLAlchemy session manag… (#11956) 10 mesi fa
schedule improve message clean logic (#11487) 10 mesi fa
services fix(app_dsl_service): handle missing app mode with a ValueError (#11945) 10 mesi fa
tasks fix: ExternalDatasetService.process_external_api wrong args (#11586) 10 mesi fa
templates Feat/new login (#8120) 1 anno fa
tests feat: add workflow parallel depth limit configuration (#11460) 10 mesi fa
.dockerignore build: support Poetry for depencencies tool in api's Dockerfile (#5105) 1 anno fa
.env.example feat: add workflow parallel depth limit configuration (#11460) 10 mesi fa
.ruff.toml fix: remove ruff ignore SIM300 (#11810) 10 mesi fa
Dockerfile chore(api/Dockerfile): Bump perl to 0.40.0-8 (#11234) 11 mesi fa
README.md chore: update base image to Python 3.12 in Dockerfile (#10358) 11 mesi fa
app.py feat(app_factory): speed up api startup (#11762) 10 mesi fa
app_factory.py feat: full support for opendal and sync configurations between .env and docker-compose (#11754) 10 mesi fa
commands.py fix: some typos using typos (#11374) 11 mesi fa
dify_app.py refactor: assembling the app features in modular way (#9129) 11 mesi fa
poetry.lock fix: memory leak by pypdfium2 close(maybe) #11510 (#11700) 10 mesi fa
poetry.toml build: initial support for poetry build tool (#4513) 1 anno fa
pyproject.toml fix: memory leak by pypdfium2 close(maybe) #11510 (#11700) 10 mesi fa
pytest.ini feat: Add support for TEI API key authentication (#11006) 11 mesi fa

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

   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
  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