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Hash Brown 57ec12eb6b
feat: regenerate history switch navigation (#8749)
1 year ago
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.idea fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) 1 year ago
.vscode feat/enhance the multi-modal support (#8818) 1 year ago
configs chore: update version to 0.10.1 (#9689) 1 year ago
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contexts feat/enhance the multi-modal support (#8818) 1 year ago
controllers feat: regenerate history switch navigation (#8749) 1 year ago
core fixed: variable reference error (#9722) 1 year ago
docker fix: use LOG_LEVEL for celery startup (#7628) 1 year ago
events feat/enhance the multi-modal support (#8818) 1 year ago
extensions feat: support user-defined configuration of log file size and retention count (#9610) 1 year ago
factories fix(api): enhance file factory URL handling (#9631) 1 year ago
fields feat(api): add video and audio file size limits to upload config (#9703) 1 year ago
libs refactor: use dify_config to replace legacy usage of flask app's config (#9089) 1 year ago
migrations feat/enhance the multi-modal support (#8818) 1 year ago
models fix(api): handle missing upload_file_id for tool_file messages (#9756) 1 year ago
schedule update dataset clean rule (#9426) 1 year ago
services feat(api): enhance file preview handling (#9674) 1 year ago
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tests feat(condition): add support for 'exists' and 'not exists' operators (#9687) 1 year ago
.dockerignore build: support Poetry for depencencies tool in api's Dockerfile (#5105) 1 year ago
.env.example feat: support user-defined configuration of log file size and retention count (#9610) 1 year ago
Dockerfile fix(dockerfile): update libsqlite3 package version (#9530) 1 year ago
README.md fix: poetry installation in CI jobs (#9336) 1 year ago
app.py refactor: use dify_config to replace legacy usage of flask app's config (#9089) 1 year ago
app_factory.py refactor: use dify_config to replace legacy usage of flask app's config (#9089) 1 year ago
commands.py feat: add upstash as a new vector database provider (#9644) 1 year ago
poetry.lock downgrade unstructured nltk version (#9726) 1 year ago
poetry.toml build: initial support for poetry build tool (#4513) 1 year ago
pyproject.toml downgrade unstructured nltk version (#9726) 1 year ago
pytest.ini chore: move testing env variables from pyproject.toml to pytest.ini (#9019) 1 year ago

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