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Zven a9fc85027d
chore: update the description for storage_type (#9492)
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.idea fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) pirms 1 gada
.vscode chore: remove .idea and .vscode from root path (#7437) pirms 1 gada
configs chore: update the description for storage_type (#9492) pirms 1 gada
constants feat: regenerate in `Chat`, `agent` and `Chatflow` app (#7661) pirms 1 gada
contexts chore(api): Introduce Ruff Formatter. (#7291) pirms 1 gada
controllers chore: disable chat service API passing `parent_message_id` (#8984) pirms 1 gada
core add yuqye(https://www.yuque.com)tools (#8960) pirms 1 gada
docker fix: use LOG_LEVEL for celery startup (#7628) pirms 1 gada
events chore: bump ruff to 0.6.8 for fixing violation in SIM910 (#8869) pirms 1 gada
extensions refactor: remove unnecessary 'closing' usage for boto3 client (#9343) pirms 1 gada
fields external knowledge api (#8913) pirms 1 gada
libs Feat/implement-refresh-tokens (#9233) pirms 1 gada
migrations fix(migrations): correct parent_message_id for service-api records (#9132) pirms 1 gada
models external knowledge api (#8913) pirms 1 gada
schedule update dataset clean rule (#9426) pirms 1 gada
services refactor: Add an enumeration type and use the factory pattern to obtain the corresponding class (#9356) pirms 1 gada
tasks external knowledge api (#8913) pirms 1 gada
templates feat: implement forgot password feature (#5534) pirms 1 gada
tests feat: Add volcengine tos storage test (#9495) pirms 1 gada
.dockerignore build: support Poetry for depencencies tool in api's Dockerfile (#5105) pirms 1 gada
.env.example chore: update the description for storage_type (#9492) pirms 1 gada
Dockerfile fix: Version '2.6.2-2' for 'expat' was not found (#8182) pirms 1 gada
README.md fix: poetry installation in CI jobs (#9336) pirms 1 gada
app.py fix: resolve the error with the db-pool-stat endpoint (#9478) pirms 1 gada
app_factory.py controller test (#9469) pirms 1 gada
commands.py fix: add missing vector type to migrate command (#9470) pirms 1 gada
poetry.lock fix: Azure OpenAI o1 max_completion_token and get_num_token_from_messages error (#9326) pirms 1 gada
poetry.toml build: initial support for poetry build tool (#4513) pirms 1 gada
pyproject.toml fix: Azure OpenAI o1 max_completion_token and get_num_token_from_messages error (#9326) pirms 1 gada
pytest.ini chore: move testing env variables from pyproject.toml to pytest.ini (#9019) pirms 1 gada

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