dify/api
2024-04-22 19:32:41 +08:00
..
.vscode chore: replace outdated config in vscode debug settings (#3106) 2024-04-05 17:49:09 +08:00
constants FEAT: NEW WORKFLOW ENGINE (#3160) 2024-04-08 18:51:46 +08:00
controllers get dict key indexing_technique in DocumentAddByFileApi (#3615) 2024-04-19 09:37:11 +08:00
core fix: incorrect type parser (#3682) 2024-04-22 19:32:41 +08:00
docker improvement: introduce Super-Linter actions to check style for shell script, dockerfile and yaml files (#1966) 2024-01-09 10:31:52 +08:00
events fix: delete tool parameters cache when sync draft workflow for run workflow use new parameter change in draft workflow (#3637) 2024-04-22 11:12:00 +08:00
extensions feat: Deprecate datetime.utcnow() in favor of datetime.now(timezone.utc).replace(tzinfo=None) for better timezone handling (#3408) (#3416) 2024-04-12 16:22:24 +08:00
fields FEAT: NEW WORKFLOW ENGINE (#3160) 2024-04-08 18:51:46 +08:00
libs chore: apply ruff rules on tests and app.py (#3605) 2024-04-18 20:24:05 +08:00
migrations fix: in alembic's offline mode (db migrate with --sql option), skip data operations (#3533) 2024-04-21 09:44:35 +08:00
models Feat/enterprise sso (#3602) 2024-04-18 17:33:32 +08:00
schedule Feat/dify rag (#2528) 2024-02-22 23:31:57 +08:00
services fix: delete tool parameters cache when sync draft workflow for run workflow use new parameter change in draft workflow (#3637) 2024-04-22 11:12:00 +08:00
tasks feat: Deprecate datetime.utcnow() in favor of datetime.now(timezone.utc).replace(tzinfo=None) for better timezone handling (#3408) (#3416) 2024-04-12 16:22:24 +08:00
templates fix: email template style (#1914) 2024-01-04 16:53:11 +08:00
tests chore: apply ruff rules on tests and app.py (#3605) 2024-04-18 20:24:05 +08:00
.dockerignore build: fix .dockerignore file (#800) 2023-08-11 18:19:44 +08:00
.env.example feat: support relyt vector database (#3367) 2024-04-15 11:52:34 +08:00
app.py feat: add file log (#3612) 2024-04-20 08:59:49 +08:00
commands.py feat: support relyt vector database (#3367) 2024-04-15 11:52:34 +08:00
config.py version to 0.6.4 (#3670) 2024-04-22 12:13:31 +08:00
Dockerfile improvement: speed up dependency installation in docker image rebuilds by mounting cache layer (#3218) 2024-04-10 22:49:04 +08:00
pyproject.toml chore: apply ruff rules on tests and app.py (#3605) 2024-04-18 20:24:05 +08:00
README.md test: add scripts for running tests on api module both locally and CI jobs (#3497) 2024-04-18 13:43:15 +08:00
requirements-dev.txt test: add scripts for running tests on api module both locally and CI jobs (#3497) 2024-04-18 13:43:15 +08:00
requirements.txt python 3.12 support (#3652) 2024-04-22 11:41:13 +08:00

Dify Backend API

Usage

  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
    docker-compose -f docker-compose.middleware.yaml -p dify up -d
    cd ../api
    
  2. Copy .env.example to .env

  3. Generate a SECRET_KEY in the .env file.

    sed -i "/^SECRET_KEY=/c\SECRET_KEY=$(openssl rand -base64 42)" .env
    
  4. If you use Anaconda, create a new environment and activate it

    conda create --name dify python=3.10
    conda activate dify
    
  5. Install dependencies

    pip install -r requirements.txt
    
  6. Run migrate

    Before the first launch, migrate the database to the latest version.

    flask db upgrade
    

    ⚠️ If you encounter problems with jieba, for example

    > flask db upgrade
    Error: While importing 'app', an ImportError was raised:
    

    Please run the following command instead.

    pip install -r requirements.txt --upgrade --force-reinstall
    
  7. Start backend:

    flask run --host 0.0.0.0 --port=5001 --debug
    
  8. Setup your application by visiting http://localhost:5001/console/api/setup or other apis...

  9. If you need to debug local async processing, please start the worker service by running celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail. The started celery app handles the async tasks, e.g. dataset importing and documents indexing.

Testing

  1. Install dependencies for both the backend and the test environment

    pip install -r requirements.txt -r requirements-dev.txt
    
  2. Run the tests locally with mocked system environment variables in tool.pytest_env section in pyproject.toml

    dev/pytest/pytest_all_tests.sh