Giannis Kepas dc5839b6bb feat: Update AWS Bedrock supported regions (#8992) 6 hónapja
..
.idea 7ae728a9a3 fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) 8 hónapja
.vscode 0d4753785f chore: remove .idea and .vscode from root path (#7437) 8 hónapja
configs 1f5cc071f8 chore(version): bump to 0.9.1 (#8945) 6 hónapja
constants 8c51d06222 feat: regenerate in `Chat`, `agent` and `Chatflow` app (#7661) 7 hónapja
contexts 3571292fbf chore(api): Introduce Ruff Formatter. (#7291) 8 hónapja
controllers 5f8a27074e fix: chat API is not bringing the conversation/session history (#8965) 6 hónapja
core dc5839b6bb feat: Update AWS Bedrock supported regions (#8992) 6 hónapja
docker 8dfdb37de3 fix: use LOG_LEVEL for celery startup (#7628) 8 hónapja
events 74f58f29f9 chore: bump ruff to 0.6.8 for fixing violation in SIM910 (#8869) 6 hónapja
extensions d96f5ba1ca add storage error log (#8556) 7 hónapja
fields 9d221a5e19 external knowledge api (#8913) 6 hónapja
libs 4373777871 Update json_in_md_parser.py (#8983) 6 hónapja
migrations 9d221a5e19 external knowledge api (#8913) 6 hónapja
models 9d221a5e19 external knowledge api (#8913) 6 hónapja
schedule 9d221a5e19 external knowledge api (#8913) 6 hónapja
services 625e4c4c72 fix multiple retrieval in knowledge node (#8942) 6 hónapja
tasks 9d221a5e19 external knowledge api (#8913) 6 hónapja
templates 00b4cc3cd4 feat: implement forgot password feature (#5534) 9 hónapja
tests 3af65b2f45 feat(api): add version comparison logic (#8902) 6 hónapja
.dockerignore 27f0ae8416 build: support Poetry for depencencies tool in api's Dockerfile (#5105) 10 hónapja
.env.example 55e6123db9 feat: add min-connection and max-connection for pgvector (#8841) 6 hónapja
Dockerfile fede54be77 fix: Version '2.6.2-2' for 'expat' was not found (#8182) 7 hónapja
README.md e75c33a561 Enhance Readme Documentation to Clarify the Importance of Celery Service (#8558) 7 hónapja
app.py 9ca2e2c968 chore: remove windows platform timezone set (#8712) 7 hónapja
commands.py bef83a4d2e fix: typos and improve naming conventions: (#8687) 7 hónapja
poetry.lock 9d221a5e19 external knowledge api (#8913) 6 hónapja
poetry.toml f62f71a81a build: initial support for poetry build tool (#4513) 10 hónapja
pyproject.toml 9d221a5e19 external knowledge api (#8913) 6 hónapja

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