Geek Out Time: Exploring Opensource AnythingLLM — The All-in-One, Easy AI Platform for Local RAG and Intelligent Agents with Just a Click

(Also on Constellar tech blog https://medium.com/the-constellar-digital-technology-blog/geek-out-time-exploring-opensource-anythingllm-the-all-in-one-easy-ai-platform-for-local-rag-edd9fa2971a0)

What is AnythingLLM?

Imagine having an AI tool that’s both powerful and effortless to set up — no coding required, no infrastructure hassles, just advanced AI features ready to go. That’s AnythingLLM. This all-in-one open-source and free-to-use AI platform allows you to run Retrieval-Augmented Generation (RAG), create AI-driven agents, and explore other capabilities, all with just a few clicks. https://github.com/Mintplex-Labs/anything-llm

I wanted to see how seamless the process truly was. It is an intuitive platform that simplifies running RAG and AI workflows locally. Whether you’re experimenting with RAG, automating tasks with agents, or integrating AI into your projects, AnythingLLM makes it incredibly easy to get started and achieve impactful results.

Getting Started: Installing AnythingLLM on macOS

Download and Install

To get started, visit the AnythingLLM website and download the .dmg installer for macOS. https://anythingllm.com/

1. Open the downloaded .dmg file.
2. Drag and drop the AnythingLLM icon into your Applications folder.

Launching the App

• Open your Applications folder and double-click on AnythingLLM to launch the app.
• If macOS warns you about an unidentified developer, go to System Preferences > Security & Privacy > General and click Open Anyway.

Choosing an LLM Provider

During the first launch, you’ll be prompted to configure an LLM provider. For a private and local setup, I chose System Default, where there are various options like OpenAI, Ollama etc

I chose the Llama 3.2 3B, small enough to run on my Macbook.

Setting Up a Workspace

Creating a Workspace

The first step is to create a workspace. Here’s what I did:

• Clicked New Workspace on the main screen “Nedved_Testing”

Ready to go, pretty fast right? Even faster then running the command line of Ollama.

Uploading Documents

Uploading files was simple — just drag and drop PDFs, text files, or Word documents into the workspace. AnythingLLM processed these automatically, generating embeddings for quick retrieval.

Configuring Chat Settings

I switched to Chat Mode in the workspace settings to mix general AI conversations with document-specific queries. Here you also can configure the chat history.

Exploring Local RAG

This is where AnythingLLM truly shines. Retrieval-Augmented Generation (RAG) allows you to combine document retrieval with AI generation for meaningful and context-aware answers.

• I uploaded documents and asked question about the document.
• The AI retrieved relevant data from a local vector database (default is LanceDB)and provided concise, accurate responses.

Since all processing happens locally, the system maintains complete privacy. Even better, it works offline, allowing me to query my files without an internet connection.

Experimenting with AI Agents and Web Search

AnythingLLM comes with a library of Agents with various Skills. Defaults ones are “RAG & long-term memory”, “View & summarize documents” and “Scrape websites”. You can turn on other skills like “Web search” etc…And you can create your own custom skills.

Interesting thoughts: Local RAG and Hybrid Scalability

One of the most exciting aspects of AnythingLLM is its ability to combine local RAG with a hybrid approach. This means:

• Privacy: Sensitive data remains on your device, which is ideal for industries like healthcare, legal, or personal productivity.
• Offline Functionality: You can search, retrieve, and interact with your documents even without internet access.
• Scalability: For complex queries or larger datasets, AnythingLLM seamlessly offloads processing to a backend, maintaining performance and efficiency.

This hybrid model opens up possibilities for mobile apps, enterprise systems, and beyond.

Final Thoughts

It is quite an amazing tool for anyone looking to dive into AI without the usual complexities. From running local RAG to creating AI-driven agents, it simplifies advanced workflows into a click-and-go experience.

For me, the highlights were its ease of use and privacy-first design. Everything from document uploading to querying was intuitive, and the ability to work offline or scale with backend support makes it incredibly versatile.

Whether you’re a developer, researcher, or productivity enthusiast, AnythingLLM offers an accessible, powerful way to leverage AI. Give it a try, have fun!