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layout default
title AnythingLLM Tutorial
nav_order 91
has_children true
format_version v2

AnythingLLM Tutorial: Self-Hosted RAG and Agents Platform

Learn how to deploy and operate Mintplex-Labs/anything-llm for document-grounded chat, workspace management, agent workflows, and production use.

GitHub Repo License Docs

Why This Track Matters

AnythingLLM is one of the most widely adopted self-hosted applications for enterprise-style document chat and configurable agent workflows.

This track focuses on:

  • setting up document-to-chat pipelines with strong privacy controls
  • configuring model providers and vector backends for different workloads
  • operating workspace-based RAG systems for teams
  • deploying and maintaining the platform in production environments

Current Snapshot (auto-updated)

Mental Model

flowchart LR
    A[Documents and Data Sources] --> B[Ingestion Pipeline]
    B --> C[Embedding and Vector Store]
    D[User Workspace Query] --> E[Retriever]
    C --> E
    E --> F[LLM Orchestration]
    F --> G[Chat and Agent Response]
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Chapter Guide

Chapter Key Question Outcome
01 - Getting Started How do I install and configure AnythingLLM? Working platform baseline
02 - Workspaces How should I organize projects and knowledge boundaries? Repeatable workspace strategy
03 - Document Upload How do I ingest and prepare heterogeneous sources? Reliable ingestion workflows
04 - LLM Configuration How do I choose and tune model providers? Provider configuration playbook
05 - Vector Stores How do I pick vector storage for my scale and latency needs? Better storage architecture decisions
06 - Agents How do I run built-in agent capabilities effectively? Practical agent execution patterns
07 - API and Integration How do I integrate AnythingLLM into existing systems? Programmatic integration baseline
08 - Production Deployment How do I deploy and operate at production quality? Operations and security baseline

What You Will Learn

  • how to design secure, self-hosted RAG systems with AnythingLLM
  • how to connect multiple LLM providers and vector backends
  • how to operationalize workspace and agent workflows for teams
  • how to deploy and monitor the platform in production

Source References

Related Tutorials

Start with Chapter 1: Getting Started.

Navigation & Backlinks

Full Chapter Map

  1. Chapter 1: Getting Started with AnythingLLM
  2. Chapter 2: Workspaces - Organizing Your Knowledge
  3. Chapter 3: Document Upload and Processing
  4. Chapter 4: LLM Configuration - Connecting Language Models
  5. Chapter 5: Vector Stores - Choosing and Configuring Storage Backends
  6. Chapter 6: Agents - Intelligent Capabilities and Automation
  7. Chapter 7: API & Integration - Programmatic Access and System Integration
  8. Chapter 8: Production Deployment - Docker, Security, and Scaling

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