Joe 1e7ef46e9c fix: update inner api proxies (#9174) преди 6 месеца
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.idea 7ae728a9a3 fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) преди 8 месеца
.vscode 0d4753785f chore: remove .idea and .vscode from root path (#7437) преди 8 месеца
configs c0b71f8286 feat: respect x-* headers for redirections (#9054) преди 6 месеца
constants 8c51d06222 feat: regenerate in `Chat`, `agent` and `Chatflow` app (#7661) преди 7 месеца
contexts 3571292fbf chore(api): Introduce Ruff Formatter. (#7291) преди 8 месеца
controllers 8204e0e14a fix: Count exception occurs when searching conversations (#8754) преди 6 месеца
core 5c76131d3d feat: add gte rerank for tongyi (#9153) преди 6 месеца
docker 8dfdb37de3 fix: use LOG_LEVEL for celery startup (#7628) преди 8 месеца
events 74f58f29f9 chore: bump ruff to 0.6.8 for fixing violation in SIM910 (#8869) преди 6 месеца
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fields 9d221a5e19 external knowledge api (#8913) преди 6 месеца
libs be2f1e59f2 improve: Refresh updated_at field of DataSourceOauthBinding model (#9173) преди 6 месеца
migrations 37d5c166ca fix(migrations): correct parent_message_id for service-api records (#9132) преди 6 месеца
models 9d221a5e19 external knowledge api (#8913) преди 6 месеца
schedule 9d221a5e19 external knowledge api (#8913) преди 6 месеца
services 1e7ef46e9c fix: update inner api proxies (#9174) преди 6 месеца
tasks 9d221a5e19 external knowledge api (#8913) преди 6 месеца
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tests 5c76131d3d feat: add gte rerank for tongyi (#9153) преди 6 месеца
.dockerignore 27f0ae8416 build: support Poetry for depencencies tool in api's Dockerfile (#5105) преди 10 месеца
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Dockerfile fede54be77 fix: Version '2.6.2-2' for 'expat' was not found (#8182) преди 7 месеца
README.md e75c33a561 Enhance Readme Documentation to Clarify the Importance of Celery Service (#8558) преди 7 месеца
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commands.py bef83a4d2e fix: typos and improve naming conventions: (#8687) преди 7 месеца
poetry.lock 05c1ef75c4 feat: add allow_llm_to_see_data flag for vanna (#9156) преди 6 месеца
poetry.toml f62f71a81a build: initial support for poetry build tool (#4513) преди 10 месеца
pyproject.toml 05c1ef75c4 feat: add allow_llm_to_see_data flag for vanna (#9156) преди 6 месеца
pytest.ini b933c9d206 chore: move testing env variables from pyproject.toml to pytest.ini (#9019) преди 6 месеца

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