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.idea 7ae728a9a3 fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) пре 8 месеци
.vscode e61752bd3a feat/enhance the multi-modal support (#8818) пре 6 месеци
configs 033ab5490b feat: support LLM understand video (#9828) пре 5 месеци
constants 3e9d271b52 nltk security issue and upgrade unstructured (#9558) пре 6 месеци
contexts e61752bd3a feat/enhance the multi-modal support (#8818) пре 6 месеци
controllers 919275cc58 Fix conversation response issue (#10450) пре 5 месеци
core 4fe5297e35 feat: add cogVideo tool (#10456) пре 5 месеци
docker 8dfdb37de3 fix: use LOG_LEVEL for celery startup (#7628) пре 8 месеци
events e61752bd3a feat/enhance the multi-modal support (#8818) пре 6 месеци
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factories 7962101e5e fix: iteration none output error (#10295) пре 5 месеци
fields 6e23903c63 Conversation delete issue (#10423) пре 5 месеци
libs 574c4a264f chore(lint): Use logging.exception instead of logging.error (#10415) пре 5 месеци
migrations bf048b8d7c refactor(migration/model): update column types for workflow schema (#10160) пре 5 месеци
models 249b897872 feat(model): add validation for custom disclaimer length (#10287) пре 5 месеци
schedule 07ad362854 fix: Cannot find declaration to go to CLEAN_DAY_SETTING (#10157) пре 5 месеци
services 888d7e6422 fix segment enable service api (#10445) пре 5 месеци
tasks aa3da0e24c fix(ops_tracing): enhance error handle in celery tasks. (#10401) пре 5 месеци
templates 4fd2743efa Feat/new login (#8120) пре 6 месеци
tests 438ad8148b fix(http_request): send form data (#10431) пре 5 месеци
.dockerignore 27f0ae8416 build: support Poetry for depencencies tool in api's Dockerfile (#5105) пре 10 месеци
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Dockerfile 87c1de66f2 chore(Dockerfile): upgrade zlib arm64 (#10244) пре 5 месеци
README.md eafe5a9d8f chore(ci): bring back poetry cache to speed up CI jobs (#10347) пре 5 месеци
app.py 0e8ab0588f fix: (#10437 followup) fix conditions with DEBUG config (#10438) пре 5 месеци
app_factory.py 0e8ab0588f fix: (#10437 followup) fix conditions with DEBUG config (#10438) пре 5 месеци
commands.py 878d13ef42 Added OceanBase as an option for the vector store in Dify (#10010) пре 5 месеци
poetry.lock 7c2a9b0744 celery worker log format following LOG_FORMAT env#9404 (#10016) пре 5 месеци
poetry.toml f62f71a81a build: initial support for poetry build tool (#4513) пре 10 месеци
pyproject.toml 7c2a9b0744 celery worker log format following LOG_FORMAT env#9404 (#10016) пре 5 месеци
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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 -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