Nam Vu a3155e0613 Update expat version (#10686) 5 kuukautta sitten
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.idea 7ae728a9a3 fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) 8 kuukautta sitten
.vscode e61752bd3a feat/enhance the multi-modal support (#8818) 6 kuukautta sitten
configs 9550b884f7 chore: update version to 0.11.1 across all configurations and Docker images (#10539) 5 kuukautta sitten
constants 3e9d271b52 nltk security issue and upgrade unstructured (#9558) 6 kuukautta sitten
contexts e61752bd3a feat/enhance the multi-modal support (#8818) 6 kuukautta sitten
controllers 06d2520db2 fix(api): replace Raw field with FilesContainedField in MessageListApi inputs (#10472) 5 kuukautta sitten
core 317ae9233e feat: add json response format for siliconflow models (#10657) 5 kuukautta sitten
docker 931e76e3d1 fix: remove unused queue `generation` (#10532) 5 kuukautta sitten
events e61752bd3a feat/enhance the multi-modal support (#8818) 6 kuukautta sitten
extensions 16db2c4e57 Fix: Set Celery LOG_File only when available, always log to console (#10563) 5 kuukautta sitten
factories 70c2ec8ed5 feat(variable-handling): enhance variable and segment conversion (#10483) 5 kuukautta sitten
fields 6e23903c63 Conversation delete issue (#10423) 5 kuukautta sitten
libs 574c4a264f chore(lint): Use logging.exception instead of logging.error (#10415) 5 kuukautta sitten
migrations 78a380bcc4 fix(migrations): correct schema reference in service API history migration (#10452) 5 kuukautta sitten
models 25ca0278dd refactor(core): Remove extra_config from File. (#10203) 5 kuukautta sitten
schedule 445dcfe4d0 add create tidb serverless job control (#10467) 5 kuukautta sitten
services 16b9665033 refactor(api): improve handling of `tools` field and cleanup variable usage (#10553) 5 kuukautta sitten
tasks 70b9e4caf5 check dataset is none (#10682) 5 kuukautta sitten
templates 4fd2743efa Feat/new login (#8120) 6 kuukautta sitten
tests 70c2ec8ed5 feat(variable-handling): enhance variable and segment conversion (#10483) 5 kuukautta sitten
.dockerignore 27f0ae8416 build: support Poetry for depencencies tool in api's Dockerfile (#5105) 10 kuukautta sitten
.env.example eb6c0b8027 Fix/log tz (#10473) 5 kuukautta sitten
Dockerfile a3155e0613 Update expat version (#10686) 5 kuukautta sitten
README.md eafe5a9d8f chore(ci): bring back poetry cache to speed up CI jobs (#10347) 5 kuukautta sitten
app.py 3e04c92ff9 chore(api): remove setting of expired remember_token cookie in after_request (#10582) 5 kuukautta sitten
app_factory.py 0e8ab0588f fix: (#10437 followup) fix conditions with DEBUG config (#10438) 5 kuukautta sitten
commands.py 878d13ef42 Added OceanBase as an option for the vector store in Dify (#10010) 5 kuukautta sitten
poetry.lock 7c2a9b0744 celery worker log format following LOG_FORMAT env#9404 (#10016) 5 kuukautta sitten
poetry.toml f62f71a81a build: initial support for poetry build tool (#4513) 10 kuukautta sitten
pyproject.toml 7c2a9b0744 celery worker log format following LOG_FORMAT env#9404 (#10016) 5 kuukautta sitten
pytest.ini 0ebd985672 feat: add models for gitee.ai (#9490) 5 kuukautta sitten

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 -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