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Version: v0.22.1

Launch service from source

A guide explaining how to set up a Swipies AI service from its source code. By following this guide, you'll be able to debug using the source code.

Target audience​

Developers who have added new features or modified existing code and wish to debug using the source code, provided that their machine has the target deployment environment set up.

Prerequisites​

  • CPU ≥ 4 cores
  • RAM ≥ 16 GB
  • Disk ≥ 50 GB
  • Docker ≥ 24.0.0 & Docker Compose ≥ v2.26.1
NOTE

If you have not installed Docker on your local machine (Windows, Mac, or Linux), see the Install Docker Engine guide.

Launch a service from source​

To launch a Swipies AI service from source code:

Clone the Swipies AI repository​

git clone https://github.com/infiniflow/Swipies AI.git
cd Swipies AI/

Install Python dependencies​

  1. Install uv:

    pipx install uv

  2. Install Python dependencies:

    uv sync --python 3.10 # install Swipies AI dependent python modules

    A virtual environment named .venv is created, and all Python dependencies are installed into the new environment.

Launch third-party services​

The following command launches the 'base' services (MinIO, Elasticsearch, Redis, and MySQL) using Docker Compose:

docker compose -f docker/docker-compose-base.yml up -d

Update host and port Settings for Third-party Services​

  1. Add the following line to /etc/hosts to resolve all hosts specified in docker/service_conf.yaml.template to 127.0.0.1:

    127.0.0.1       es01 infinity mysql minio redis

  2. In docker/service_conf.yaml.template, update mysql port to 5455 and es port to 1200, as specified in docker/.env.

Launch the Swipies AI backend service​

  1. Comment out the nginx line in docker/entrypoint.sh.

    # /usr/sbin/nginx

  2. Activate the Python virtual environment:

    source .venv/bin/activate
    export PYTHONPATH=$(pwd)

  3. Optional: If you cannot access HuggingFace, set the HF_ENDPOINT environment variable to use a mirror site:

    export HF_ENDPOINT=https://hf-mirror.com

  4. Check the configuration in conf/service_conf.yaml, ensuring all hosts and ports are correctly set.

  5. Run the entrypoint.sh script to launch the backend service:

    JEMALLOC_PATH=$(pkg-config --variable=libdir jemalloc)/libjemalloc.so;
    LD_PRELOAD=$JEMALLOC_PATH python rag/svr/task_executor.py 1;
    python api/Swipies AI_server.py;

Launch the Swipies AI frontend service​

  1. Navigate to the web directory and install the frontend dependencies:

    cd web
    npm install

  2. Update proxy.target in .umirc.ts to http://127.0.0.1:9380:

    vim .umirc.ts

  3. Start up the Swipies AI frontend service:

    npm run dev

    The following message appears, showing the IP address and port number of your frontend service:

Access the Swipies AI service​

In your web browser, enter http://127.0.0.1:<PORT>/, ensuring the port number matches that shown in the screenshot above.

Stop the Swipies AI service when the development is done​

  1. Stop the Swipies AI frontend service:

    pkill npm

  2. Stop the Swipies AI backend service:

    pkill -f "docker/entrypoint.sh"