The outcome

Learn the interaction loop using a small task with a clear outcome.

LobeHub is a Open-source AI workspace centered on LobeChat, with multi-provider chat, agents, knowledge bases, files, plugins, MCP, and self-hosting. Using multiple AI providers in one workspace, building reusable assistants with files and knowledge, and operating a private multi-user LobeChat service with controlled extensions. This guide narrows that broad capability into one repeatable outcome, with checkpoints that keep the source material and your judgment in the loop.

Before you begin

Set the boundary before the tool starts.

Choose one real task, identify who will use the result, and decide what evidence or test will make the result acceptable. Gather only the source material needed for that task. If the work contains confidential, personal, regulated, or client-owned information, confirm that the platform and account are approved before sharing it.

Troiana principle

AI should make the work easier to inspect. If the workflow removes the source, the owner, or the review step, redesign the workflow.

Step by step

A workflow you can repeat.

  1. 01

    Define users, deployment model, data classes, providers, model rights, authentication, storage, knowledge, tools, retention, availability, budget, and backup and recovery requirements.

  2. 02

    Choose hosted or desktop access for individual use, or a database-backed self-hosted deployment with SSO, PostgreSQL and vector support, object storage, HTTPS, and restricted registration for teams.

  3. 03

    Configure scoped provider credentials and an allowlisted model set, create one narrowly instructed assistant, and test chat, file, knowledge, sync, and tool behavior with non-sensitive data.

  4. 04

    Review provider data paths, tenant isolation, retrieval quality, plugin and MCP permissions, traces, failures, cost, backups, and restore, then pin and canary updates with rollback.

Working standard

What good use looks like.

  • State the outcome before the background.
  • Provide the real source material.
  • Review the result before expanding the task.

Self-hosting the interface does not make remote model, embedding, search, storage, sync, or plugin traffic local. A database deployment adds authentication, database, vector, object-storage, migration, backup, and patch responsibilities. Never expose an unauthenticated instance or provider key; isolate tenants and knowledge, vet plugins and MCP servers, restrict registration and networks, redact observability, and test restores before upgrades.

Official references

Check the current product documentation.

Features, plan limits, availability, and data controls change. These official pages are the starting points used for this collection.