Low-code AI application platform
How to use
Dify.
Building low-code AI workflows, chatflows, agents, RAG applications, model integrations, plugins, and deployable APIs with operational visibility.
Dify is a open-source low-code platform for AI applications, workflows, agents, knowledge, and LLM operations. Building low-code AI workflows, chatflows, agents, RAG applications, model integrations, plugins, and deployable APIs with operational visibility. This guide covers the whole path in one place: official access, a first session that produces something reviewable, the checks that make output trustworthy, and the permissions worth limiting before you connect real work.
AI should make the work easier to inspect. If the workflow removes the source, the owner, or the review step, redesign the workflow.
Access & setup
Find, install, and sign in to Dify
Get into the official Dify experience with the right account and a setup you understand.
- 01
Start at https://dify.ai/ and confirm the domain before entering account or payment information.
- 02
Availability: Dify is available as a hosted cloud service and as an open-source self-hosted web platform, with application APIs, plugins, and development tooling.
- 03
A Dify workspace or maintained self-hosted deployment, configured model provider, protected credentials, and approved data and tool integrations.
- 04
Sign in with the account you intend to keep using, then review plan, data, notification, and permission settings.
- 05
Run one low-risk test task before connecting sensitive files, repositories, or workspace data.
- Use official download pages.
- Review permissions during setup.
- Keep installers and applications updated.
First session
Your first useful Dify session
Learn the interaction loop using a small task with a clear outcome.
- 01
Create a development workspace and connect one model with a restricted project key.
- 02
Build a blank Workflow with a typed input, one constrained LLM node, and an Output node.
- 03
Add a deterministic validation branch and test normal, malformed, and adversarial inputs.
- 04
Review node logs, model usage, output structure, and failure behavior before publishing a test version.
- State the outcome before the background.
- Provide the real source material.
- Review the result before expanding the task.
Quality control
Check the quality of Dify output
Turn generated code into a change you would put your name on in review.
- 01
Restate the intended behaviour and the acceptance criteria before reading a single generated line.
- 02
Read the diff rather than the chat summary; the summary describes intent, the diff describes what actually changed.
- 03
Run the test suite, then write a test that would fail if the change were wrong, and confirm it passes for the right reason.
- 04
Check the edges the model tends to skip: error paths, null and empty cases, concurrency, and migration or rollback behaviour.
- 05
Trace every new dependency, network call, and file write, and confirm each one is genuinely required.
- Review the diff, never the description of the diff.
- A passing test suite proves the tests pass, not that the change is correct.
- Keep changes small enough that a human can actually review them.
Privacy & permissions
Use Dify safely
Give the tool enough repository access to help, and no more than that.
- 01
Decide what the tool may read and what it may write before connecting a repository.
- 02
Scope tokens and integrations to the narrowest repository, branch, and permission set that still works.
- 03
Keep secrets out of the context window: use environment variables and secret stores, never inline credentials.
- 04
Require review before generated code touches authentication, payments, permissions, migrations, or deletion paths.
- 05
Audit what the integration retained after the session, and revoke access that is no longer needed.
- Dify workflows can connect models, knowledge, code, plugins, webhooks, and external tools that carry different data and execution risks. Isolate workspaces, protect provider and app keys, prefer deterministic nodes for fixed rules, validate every input and output, treat plugins as code, restrict tools and knowledge access, inspect logs and retention, test failure and pause paths, pin self-hosted versions, and keep exports and rollback procedures.
- Follow your organisation's approved-use policy.
- Never treat fluent output as authorization to act.
Core workflows
Step-by-step ways to use Dify for the work it does best.
Each workflow is a separate guide with its own steps and review checkpoints.
Combine typed inputs, deterministic branches, model calls, tools, templates, and outputs with explicit failure handling.
↗ 02 WorkflowCreate an access-aware Dify knowledge applicationIngest approved documents, tune retrieval, and measure citation support without exposing unrelated workspace data.
↗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 guide.