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gcgj-dify-1.7.0/api
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listeng 696efe494e
fix: Ignore some emtpy page_content when append to split_documents (#2898) 		2 years ago
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constants
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controllers Fix/compatible to old tool config (#2839) 2 years ago
core fix: Ignore some emtpy page_content when append to split_documents (#2898) 2 years ago
docker
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events fix: The generate conversation name was not saved (#2836) 2 years ago
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fields
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libs SMTP authentication is optional (#2765) 2 years ago
migrations add tenant id index for document and document_segment table (#2873) 2 years ago
models add tenant id index for document and document_segment table (#2873) 2 years ago
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services Feat/support tool credentials bool schema (#2875) 2 years ago
tasks fix enable annotation reply when collection is None (#2877) 2 years ago
templates fix: email template style (#1914) 2 years ago
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app.py
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config.py
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pyproject.toml
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requirements.txt Bump tiktoken to 0.6.0 to support text-embedding-3-* in encoding_for_model (#2891) 2 years ago

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

  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

3.5 If you use annaconda, 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

  2. 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

  3. Start backend:

    flask run --host 0.0.0.0 --port=5001 --debug

  4. Setup your application by visiting http://localhost:5001/console/api/setup or other apis...

  5. If you need to debug local async processing, you can run celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail, celery can do dataset importing and other async tasks.