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AAEE86 fe41e8bc18
feat: add siliconflow custom add model interface (#8745)
1 rok temu
..
.idea fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) 1 rok temu
.vscode chore: remove .idea and .vscode from root path (#7437) 1 rok temu
configs feat: respect x-* headers for redirections (#9054) 1 rok temu
constants feat: regenerate in `Chat`, `agent` and `Chatflow` app (#7661) 1 rok temu
contexts chore(api): Introduce Ruff Formatter. (#7291) 1 rok temu
controllers fix: Count exception occurs when searching conversations (#8754) 1 rok temu
core feat: add siliconflow custom add model interface (#8745) 1 rok temu
docker fix: use LOG_LEVEL for celery startup (#7628) 1 rok temu
events chore: bump ruff to 0.6.8 for fixing violation in SIM910 (#8869) 1 rok temu
extensions feat: respect x-* headers for redirections (#9054) 1 rok temu
fields external knowledge api (#8913) 1 rok temu
libs improve: Refresh updated_at field of DataSourceOauthBinding model (#9173) 1 rok temu
migrations fix(migrations): correct parent_message_id for service-api records (#9132) 1 rok temu
models external knowledge api (#8913) 1 rok temu
schedule external knowledge api (#8913) 1 rok temu
services fix: update inner api proxies (#9174) 1 rok temu
tasks external knowledge api (#8913) 1 rok temu
templates feat: implement forgot password feature (#5534) 1 rok temu
tests feat: add gte rerank for tongyi (#9153) 1 rok temu
.dockerignore build: support Poetry for depencencies tool in api's Dockerfile (#5105) 1 rok temu
.env.example feat: respect x-* headers for redirections (#9054) 1 rok temu
Dockerfile fix: Version '2.6.2-2' for 'expat' was not found (#8182) 1 rok temu
README.md Enhance Readme Documentation to Clarify the Importance of Celery Service (#8558) 1 rok temu
app.py feat: respect x-* headers for redirections (#9054) 1 rok temu
commands.py fix: typos and improve naming conventions: (#8687) 1 rok temu
poetry.lock feat: add allow_llm_to_see_data flag for vanna (#9156) 1 rok temu
poetry.toml build: initial support for poetry build tool (#4513) 1 rok temu
pyproject.toml feat: add allow_llm_to_see_data flag for vanna (#9156) 1 rok temu
pytest.ini chore: move testing env variables from pyproject.toml to pytest.ini (#9019) 1 rok temu

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