Você não pode selecionar mais de 25 tópicos Os tópicos devem começar com uma letra ou um número, podem incluir traços ('-') e podem ter até 35 caracteres.
Yash Parmar 6ccde0452a
feat: Added hindi translation i18n (#5240)
1 ano atrás
..
.vscode build: initial support for poetry build tool (#4513) 1 ano atrás
constants feat: Added hindi translation i18n (#5240) 1 ano atrás
controllers Feat/firecrawl data source (#5232) 1 ano atrás
core feat(Tools): Add Serply Web/Job/Scholar/News Search tool for more options (#5186) 1 ano atrás
docker improvement: introduce Super-Linter actions to check style for shell script, dockerfile and yaml files (#1966) 1 ano atrás
events fix: initialize site with customized icon and icon_background (#5227) 1 ano atrás
extensions add aws s3 iam check (#5174) 1 ano atrás
fields fix: workspace member's last_active should be last_active_time, but not last_login_time (#4906) 1 ano atrás
libs Feat/firecrawl data source (#5232) 1 ano atrás
migrations Feat/firecrawl data source (#5232) 1 ano atrás
models Feat/firecrawl data source (#5232) 1 ano atrás
schedule Feat/dify rag (#2528) 1 ano atrás
services Feat/firecrawl data source (#5232) 1 ano atrás
tasks Feat/firecrawl data source (#5232) 1 ano atrás
templates fix: email template style (#1914) 1 ano atrás
tests Feat/firecrawl data source (#5232) 1 ano atrás
.dockerignore build: fix .dockerignore file (#800) 2 anos atrás
.env.example Feat/firecrawl data source (#5232) 1 ano atrás
Dockerfile improvement: speed up dependency installation in docker image rebuilds by mounting cache layer (#3218) 1 ano atrás
README.md Update README.md (#5228) 1 ano atrás
app.py refactor: config file (#3852) 1 ano atrás
commands.py feat: support tencent vector db (#3568) 1 ano atrás
config.py version to 0.6.11 (#5224) 1 ano atrás
poetry.lock feat: support tencent vector db (#3568) 1 ano atrás
poetry.toml build: initial support for poetry build tool (#4513) 1 ano atrás
pyproject.toml version to 0.6.11 (#5224) 1 ano atrás
requirements-dev.txt chore: skip explicit installing jinja2 as testing dependency (#4845) 1 ano atrás
requirements.txt feat: support tencent vector db (#3568) 1 ano atrás

README.md

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
  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
  1. Create environment.

Dify API service uses Poetry to manage dependencies. You can execute poetry shell to activate the environment.

Using pip can be found below.

  1. Install dependencies
   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 debug local async processing, please start the worker service.
   poetry run python -m 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
   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

Usage with pip

[!NOTE]
In the next version, we will deprecate pip as the primary package management tool for dify api service, currently Poetry and pip coexist.

  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
  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
  1. Create environment.

If you use Anaconda, create a new environment and activate it

   conda create --name dify python=3.10
   conda activate dify
  1. Install dependencies
   pip install -r requirements.txt
  1. Run migrate

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

   flask db upgrade
  1. Start backend: bash flask run --host 0.0.0.0 --port=5001 --debug
  2. Setup your application by visiting http://localhost:5001/console/api/setup or other apis…
  3. If you need to debug local async processing, please start the worker service. bash 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