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

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