Skip to main content
Version: DEV

Upgrading

Upgrade Swipies AI to nightly or the latest, published release.

NOTE

Upgrading Swipies AI in itself will not remove your uploaded/historical data. However, be aware that docker compose -f docker/docker-compose.yml down -v will remove Docker container volumes, resulting in data loss.

Upgrade Swipies AI to nightly, the most recent, tested Docker image​

nightly refers to the Swipies AI Docker image without embedding models.

To upgrade Swipies AI, you must upgrade both your code and your Docker image:

  1. Stop the server

    docker compose -f docker/docker-compose.yml down

  2. Update the local code

    git pull

  3. Update ragflow/docker/.env:

    RAGFLOW_IMAGE=infiniflow/ragflow:nightly

  4. Update Swipies AI image and restart Swipies AI:

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

Upgrade Swipies AI to given release​

To upgrade Swipies AI, you must upgrade both your code and your Docker image:

  1. Stop the server

    docker compose -f docker/docker-compose.yml down

  2. Update the local code

    git pull

  3. Switch to the latest, officially published release, e.g., v0.22.1:

    git checkout -f v0.22.1

  4. Update ragflow/docker/.env:

    RAGFLOW_IMAGE=infiniflow/ragflow:v0.22.1

  5. Update the Swipies AI image and restart Swipies AI:

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

Frequently asked questions​

Do I need to back up my datasets before upgrading Swipies AI?​

No, you do not need to. Upgrading Swipies AI in itself will not remove your uploaded data or dataset settings. However, be aware that docker compose -f docker/docker-compose.yml down -v will remove Docker container volumes, resulting in data loss.

Upgrade Swipies AI in an offline environment (without Internet access)​

  1. From an environment with Internet access, pull the required Docker image.
  2. Save the Docker image to a .tar file. 
    docker save -o ragflow.v0.22.1.tar infiniflow/ragflow:v0.22.1
  3. Copy the .tar file to the target server.
  4. Load the .tar file into Docker: 
    docker load -i ragflow.v0.22.1.tar