How to use Dockerized Anything LLM

Use the Dockerized version of AnythingLLM for a much faster and complete startup of AnythingLLM.

Minimum Requirements

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Tip ➤➤ Running AnythingLLM on AWS/GCP/Azure?

➤ You should aim for at least 2GB of RAM. Disk storage is proportional to however much data

➤ You will be storing (documents, vectors, models, etc). Minimum 10GB recommended.

docker installed on your machine
yarn and node on your machine
access to an LLM running locally or remotely

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Note

➤ AnythingLLM by default uses a built-in vector database powered by LanceDB (opens in a new tab)

➤ AnythingLLM by default embeds text on instance privately Learn More

Recommend way to run dockerized AnythingLLM!

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Important!

➤ If you are running another service on localhost like Chroma, LocalAi, or LMStudio you will need to use http://host.docker.internal:xxxx to access the service from within the docker container using AnythingLLM as localhost:xxxx will not resolve for the host system

➤ Requires Docker v18.03+ on Win/Mac and 20.10+ on Linux/Ubuntu for host.docker.internal to resolve!

➤ Linux: add --add-host=host.docker.internal:host-gateway to docker run command for this to resolve.

➤ eg: Chroma host URL running on localhost:8000 on host machine needs to be http://host.docker.internal:8000 when used in AnythingLLM.

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Tip ➤➤ It is best to mount the containers storage volume to a folder on your host machine so that you can pull in future updates without deleting your existing data!

Pull in the latest image from docker. Supports both amd64 and arm64 CPU architectures.

 docker pull mintplexlabs/anythingllm

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Note --cap-add SYS_ADMIN is a required command if you want to scrape webpages. We use PuppeeteerJS (opens in a new tab) to scrape websites links and --cap-add SYS_ADMIN lets us use sandboxed Chromium across all runtimes for best security practices.

Mount the storage locally and run AnythingLLM in Docker

Go to http://localhost:3001 and you are now using AnythingLLM! All your data and progress will persist between container rebuilds or pulls from Docker Hub.

How to use the user interface

To access the full application, visit http://localhost:3001 in your browser.

About UID and GID in the ENV

The UID and GID are set to 1000 by default. This is the default user in the Docker container and on most host operating systems.
If there is a mismatch between your host user UID and GID and what is set in the .env file, you may experience permission issues.

Build locally from source not recommended for casual use

git clone this repo and cd anything-llm to get to the root directory.
touch server/storage/anythingllm.db to create empty SQLite DB file.
cd docker/
cp .env.example .env you must do this before building
docker-compose up -d --build to build the image - this will take a few moments.

Your docker host will show the image as online once the build process is completed. This will build the app to http://localhost:3001.

Integrations and one-click setups

The integrations below are templates or tooling built by the community to make running the docker experience of AnythingLLM easier.

Use the Midori AI Subsystem to Manage AnythingLLM

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Note! ➤➤ Midori AI Subsystem Manager is currently in BETA. If you encounter any issues with the Subsystem Manager, please contact their team (opens in a new tab)

The Midori AI Subsystem manager is not maintained by Mintplex Labs and is a community lead project. As such, any issues using this message should be directed to the discord link found in the link above.

Follow the setup found on Midori AI Subsystem guide (opens in a new tab) for your host OS.

After setting that up, install the AnythingLLM docker backend to the Midori AI Subsystem.

Once that is done, you are all set!

Common questions and fixes

1. Cannot connect to service running on localhost!

If you are in docker and cannot connect to a service running on your host machine running on a local interface or loopback:

localhost
127.0.0.1
0.0.0.0

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Important!

➤ On linux http://host.docker.internal:xxxx does not work.

➤ Use http://172.17.0.1:xxxx instead to emulate this functionality.

Then in docker you need to replace that localhost part with host.docker.internal. For example, if running Ollama on the host machine, bound to http://127.0.0.1:11434 you should put http://host.docker.internal:11434 into the connection URL in AnythingLLM.

2. API is not working, cannot login, LLM is "offline"?

You are likely running the docker container on a remote machine like EC2 or some other instance where the reachable URL is not http://localhost:3001 and instead is something like http://193.xx.xx.xx:3001 - in this case all you need to do is add the following to your frontend/.env.production before running docker-compose up -d --build

# frontend/.env.production
 GENERATE_SOURCEMAP=false
 VITE_API_BASE="http://<YOUR_REACHABLE_IP_ADDRESS>:3001/api"

For example, if the docker instance is available on 192.186.1.222 your VITE_API_BASE would look like VITE_API_BASE="http://192.186.1.222:3001/api" in frontend/.env.production.

3. Having issues with Ollama?

If you are getting errors like llama:streaming - could not stream chat. Error: connect ECONNREFUSED 172.17.0.1:11434 then visit this README (opens in a new tab).

Still not working?

Ask for help on our Discord Community Server (opens in a new tab)

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