takatost 0bf4817474 fix: _convert_prompt_message_to_dict parameters err (#5716) преди 1 година
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configs 17d2f0bb0d fix(api/configs): Ignore empty environment variables when loading config. (#5647) преди 1 година
constants 2e718b85e9 fix(api): language list (#5649) преди 1 година
controllers 4c0a31d38b FR: #4048 - Add color customization to the chatbot (#4885) преди 1 година
core 0bf4817474 fix: _convert_prompt_message_to_dict parameters err (#5716) преди 1 година
docker e8b8f6c6dd Feat/fix ops trace (#5672) преди 1 година
events d160d1ed02 feat: support opensearch approximate k-NN (#5322) преди 1 година
extensions 3cc6093e4b feat: introduce pydantic-settings for config definition and validation (#5202) преди 1 година
fields 4c0a31d38b FR: #4048 - Add color customization to the chatbot (#4885) преди 1 година
libs dcb72e0067 chore: apply flake8-comprehensions Ruff rules to improve collection comprehensions (#5652) преди 1 година
migrations e8b8f6c6dd Feat/fix ops trace (#5672) преди 1 година
models d30c13891b feat: add fix-app-site-missing command (#5711) преди 1 година
schedule 6c4e6bf1d6 Feat/dify rag (#2528) преди 1 година
services dcb72e0067 chore: apply flake8-comprehensions Ruff rules to improve collection comprehensions (#5652) преди 1 година
tasks e8b8f6c6dd Feat/fix ops trace (#5672) преди 1 година
templates 3d92784bd4 fix: email template style (#1914) преди 1 година
tests dcb72e0067 chore: apply flake8-comprehensions Ruff rules to improve collection comprehensions (#5652) преди 1 година
.dockerignore 27f0ae8416 build: support Poetry for depencencies tool in api's Dockerfile (#5105) преди 1 година
.env.example 964f0e1400 fix: Modify the incorrect configuration name for Google storage (#5595) преди 1 година
Dockerfile 73ce945d40 Feat/add json process tool (#5555) преди 1 година
README.md f9e4b4e74c Fix docker command (#5681) преди 1 година
app.py 017d2c804b fix: do not remove (#5706) преди 1 година
commands.py 8e5569f773 fix: fix-app-site-missing command (#5714) преди 1 година
poetry.lock 73ce945d40 Feat/add json process tool (#5555) преди 1 година
poetry.toml f62f71a81a build: initial support for poetry build tool (#4513) преди 1 година
pyproject.toml 73ce945d40 Feat/add json process tool (#5555) преди 1 година

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
   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.

```bash for Linux sed -i "/^SECRET_KEY=/c\SECRET_KEY=$(openssl rand -base64 42)" .env


   ```bash for Mac
   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 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,ops_trace

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