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AnythingLLM: Own Your AI

Get a local-first agent experience with AnythingLLM, a powerful tool for founders, backed by 61k+ GitHub stars.
advancedโฑ 1-2 hours๐Ÿ’ต Free (self-hosted)
63,769 stars6,986 forksJavaScriptHealth Score 9/10Updated 7/23/2026100% free ยท open source
What it is

Run a powerful local AI agent on your own computer without renting intelligence.

What you can make with it

Automations like: when a new Stripe customer signs up, add them to Notion and send a welcome email via Resend.

How it helps

Control how and where your AI intelligence is used by keeping it on your local machine, and avoid relying on paid APIs.

Real use case example

"A solo developer builds a customer onboarding system by using AnythingLLM to integrate Stripe with Notion and Resend. They train the AI model on company data to personalize the onboarding process. The agent creates new customer profiles, sends welcome emails, and adds relevant tasks to their project."

If you're new

Start by building simple automations with pre-trained models when setting up your own local AI project.

If you're senior

Choose when integrating with a custom dataset, building a high-performance local AI environment, or creating complex automations requiring full control over model execution and hosting.

Common confusion cleared up

AnythingLLM is designed for building and integrating local AI models, not for using cloud-based AI services or platforms.

Best inside these AI tools
Claude DesktopSelf-hostedAny AI Client
Pairs with
Stripe webhookNotion databaseClaude API
Why we list it on WorkflowStacks: Open-source and free, making it a cost-effective option for building local-first agent experiences.
What it does

AnythingLLM allows you to own and run a local-first AI agent, giving you control over your intelligence and data without relying on cloud services

Install / run
git clone https://github.com/Mintplex-Labs/anything-llm.git && cd anything-llm
When to use it
  • โ€ขWhen you need to automate tasks with AI while keeping your data private
  • โ€ขWhen you want to integrate AI capabilities into your local applications without relying on external APIs
  • โ€ขWhen you need a customizable AI solution that can be tailored to your specific business needs
Quick start
  1. 1Run `npm install` to set up the project dependencies
  2. 2Configure your agent by modifying the `config.json` file to suit your needs
  3. 3 Train your model using the `train.js` script, specifying your dataset and hyperparameters as required
  4. 4Use the `agent.js` script to interact with your trained model, sending requests and receiving responses
  5. 5Modify the `index.js` file to integrate your AI agent with other local applications or services
Ready-to-paste prompt
node agent.js --prompt 'What are the potential applications of local-first AI agents in the enterprise?'
Heads up: Ensure you have Node.js (version 16 or higher) installed on your system before attempting to install or run AnythingLLM, as it is required to execute the JavaScript scripts
Saves to your device

Topics

agent-computer
agent-harness
agent-orchestration
agentic-ai
ai-agents
computer-use
hermes-agent
llm
local-ai
localai
multimodal
no-code
open-claw
rag
self-hosted-ai
vector-database
How AnythingLLM: Own Your AI works
Codeflow
Free to inspect

AnythingLLM: Own Your AI is a very large JavaScript project (~243k lines across 1236 code files, plus 37 test files). It is a full software project: use it through its install path rather than reading it end to end. Last commit this month, MIT license, has a test suite.

Size
Very large codebase
~243k lines ยท 1236 code files ยท days to read โ€” use, don't read
Setup
Developer setup
A real software project. Use it via its install path; don't expect to read it all.
Runs on
Node.js ยท Docker
No API keys detected
JavaScript 95%TypeScript 2%CSS 1%HTML 1%Shell 1%
Where to start reading
  1. 1
    README.md
    Start here โ€” what it does and how to install it
  2. 2
    server/index.js
    Where the program starts running
  3. 3
    package.json
    Dependencies and the commands it exposes
What's in each folder
frontend/Frontend / UI729 files
server/Backend / API562 files
open-computer/services/Backend / API52 files
open-computer/cli/Command-line entry points16 files
open-computer/master/Folder4079 files
collector/Folder74 files
cloud-deployments/Folder30 files
extras/Folder12 files
READMEHas testsDocumentedCI checksDocker readyMIT licenseUpdated this month
Quick Actions
Details
Creator
Mintplex-Labs
Language
JavaScript
Category
automation
Published
6/4/2023

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