Overview
AnythingLLM 1.17.0 lets teams load documents and web pages into workspaces and ask questions about them with a large language model (retrieval-augmented generation). This AMI is for teams that want that workbench inside their own account, with data on an EBS volume they control and the UI kept off the public internet.
What you get: AnythingLLM listening on localhost port 3001, a per-instance admin password generated at first boot (/etc/anythingllm/admin.password, readable only with sudo), persistent document storage under /var/lib/anythingllm, and a separately pinned Chrome for Testing runtime for the built-in web page collector. No provider keys or model weights are included. Configure your LLM and embedding providers in the UI after launch.
Getting started takes a few minutes: launch t3.medium (4 GiB RAM, 40 GiB encrypted gp3 or larger), attach an instance profile with AmazonSSMManagedInstanceCore, allow outbound HTTPS and keep the security group free of inbound rules. Connect with Session Manager, run sudo -iu ubuntu bash /opt/sushi/docs/demo.sh, then start a Session Manager port-forwarding session to port 3001 and open that port on localhost in your browser. To chat, choose the Generic OpenAI provider with any OpenAI-compatible endpoint, including Amazon Bedrock through its OpenAI-compatible endpoint for your Region (see the Bedrock documentation) with a Bedrock API key, and set each workspace's chat mode to Chat for plain document Q&A.
Pricing: a software fee of USD 0.02 per running t3.medium instance-hour. An optional five-day free trial for one concurrent instance changes software billing only and then converts to the hourly fee; the same full software is installed before and after it. This is not a separate trial or evaluation edition, and there is no product-imposed time, user or usage limit. Additional concurrent instances incur software fees. EC2, EBS, data transfer and any model-provider charges are billed separately, including during the free trial. No annual offer is configured.
This is a repackaged open source software product wherein additional charges apply for independent packaging, validation, maintenance and setup documentation. Mintplex Labs authors AnythingLLM under the MIT license. Software Sushi supplies the AMI recipe, derived runtime and setup guide without claiming upstream endorsement. Google Chrome terms apply separately to the bundled browser. Back up /var/lib/anythingllm and /etc/anythingllm together before replacing an instance.
Highlights
- Chat with your own documents and web pages (RAG) using the LLM and embedding providers you choose, including Amazon Bedrock through its OpenAI-compatible endpoint.
- Documents persist on your EBS volume, and each instance creates its own admin password on first boot.
- The UI stays off the internet: it binds to localhost and you reach it through Session Manager port forwarding.
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Pricing
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Dimension | Cost/hour |
|---|---|
t3.medium Recommended | $0.02 |
Vendor refund policy
We offer a full refund of software charges for the first 48 hours billing starts if the product does not perform as described. To request a refund, email info@softwaresushi.com with your EC2 instance ID and a description of the issue. AWS infrastructure costs (EC2, EBS, data transfer) are billed by AWS and are not eligible for refund by us.
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
AnythingLLM v1.17.0 (MIT, by Mintplex Labs) on Ubuntu 24.04 LTS, packaged by Software Sushi with a Sushi-derived runtime and a separately pinned Chrome for Testing browser for the web page collector. The UI listens on 127.0.0.1:3001 and is reached through Session Manager port forwarding; the admin password is generated at first boot. Documents persist under /var/lib/anythingllm. Includes a guided walkthrough (sudo -iu ubuntu bash /opt/sushi/docs/demo.sh). No provider keys or model weights are included.
Additional details
Usage instructions
- Launch t3.medium (4 GiB RAM, 40 GiB or larger encrypted gp3, IMDSv2) with AmazonSSMManagedInstanceCore and outbound HTTPS. No inbound rules are needed.
- Connect: aws ssm start-session --target <instance-id>. After cloud-init finishes, run: sudo -iu ubuntu bash /opt/sushi/docs/demo.sh (expect SUSHI_CUSTOMER_DEMO_PASSED).
- Read the admin password: sudo cat /etc/anythingllm/admin.password
- From your workstation: aws ssm start-session --target <instance-id> --document-name AWS-StartPortForwardingSession --parameters '{"portNumber":["3001"],"localPortNumber":["3001"]}', open http://127.0.0.1:3001 and sign in.
- LLM: in Settings > LLM choose Generic OpenAI with any OpenAI-compatible endpoint and key. For Amazon Bedrock use Base URL https://bedrock-runtime.us-east-1.amazonaws.com/openai/v1 , a Bedrock API key and a model such as openai.gpt-oss-20b-1:0. The built-in AWS Bedrock option needs keys and does not use the instance role.
- New workspaces start in automatic (agent) mode; set Chat mode to Chat in workspace settings for plain document chat. Docs: https://docs.anythingllm.com . Back up /var/lib/anythingllm and /etc/anythingllm together.
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Vendor support
Software Sushi provides installation and configuration guidance for this image. Contact info@softwaresushi.com with your product version and the steps you took; never send credentials or private documents. Guaranteed response times require a separate agreement. This offer does not include Mintplex Labs or Google support.
AWS infrastructure support
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