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49 lines
2.3 KiB
Markdown
49 lines
2.3 KiB
Markdown
# How to deploy a private AnythingLLM instance on AWS
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With an AWS account you can easily deploy a private AnythingLLM instance on AWS. This will create a url that you can access from any browser over HTTP (HTTPS not supported). This single instance will run on your own keys and they will not be exposed - however if you want your instance to be protected it is highly recommend that you set a password one setup is complete.
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**Quick Launch (EASY)**
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1. Log in to your AWS account
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2. Open [CloudFormation](https://us-west-1.console.aws.amazon.com/cloudformation/home)
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3. Ensure you are deploying in a geographic zone that is nearest to your physical location to reduce latency.
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4. Click `Create Stack`
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5. Use the file `cloudformation_create_anythingllm.json` as your JSON template.
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6. Click Deploy.
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7. Wait for stack events to finish and be marked as `Completed`
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8. View `Outputs` tab.
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9. Wait for all resources to be built. Now wait until instance is available on `[InstanceIP]:3001`.
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This process may take up to 10 minutes. See **Note** below on how to visualize this process.
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The output of this cloudformation stack will be:
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- 1 EC2 Instance
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- 1 Security Group with 0.0.0.0/0 access on port 3001
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- 1 EC2 Instance Volume `gb2` of 10Gib minimum - customizable pre-deploy.
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**Requirements**
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- An AWS account with billing information.
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## Please read this notice before submitting issues about your deployment
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**Note:**
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Your instance will not be available instantly. Depending on the instance size you launched with it can take 5-10 minutes to fully boot up.
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If you want to check the instance's progress, navigate to [your deployed EC2 instances](https://us-west-1.console.aws.amazon.com/ec2/home) and connect to your instance via SSH in browser.
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Once connected run `sudo tail -f /var/log/cloud-init-output.log` and wait for the file to conclude deployment of the docker image.
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You should see an output like this
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```
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[+] Running 2/2
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⠿ Network docker_anything-llm Created
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⠿ Container anything-llm Started
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```
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Additionally, your use of this deployment process means you are responsible for any costs of these AWS resources fully. |