Automation
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Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+…
★ 206.6k starsCustom (check repo)
View guide →Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or…
Dify is an open-source rag & knowledge project by langgenius (langgenius/dify on GitHub). It has 157,773 GitHub stars and 24,895 forks, is released under the Custom (check repo) license, and was last updated on GitHub on 3 October 2026.
Link the services you already use — chat, email, sheets, CRMs, databases — through built-in integrations or generic webhooks and API calls.
Drag triggers and actions onto a canvas: when this happens, do that. Branch on conditions, loop over items, and transform data between steps.
Pipe steps through language models for classification, extraction, summarising, or drafting — most platforms here treat AI as just another node.
Turn the workflow on, watch executions in the run history, and get alerted when something fails.
Design automations on a canvas instead of writing glue code for every integration.
Prebuilt connectors for popular apps plus HTTP, webhooks, and database nodes for everything else.
Your credentials and execution data stay on your infrastructure — no third-party middleman.
Call LLMs mid-workflow for decisions, extraction, and content generation.
Cron schedules, webhooks, and event triggers keep flows running around the clock.
Open-source means the automation itself is free; you only pay for your own server.
Download the source and move into the project folder.
git clone https://github.com/langgenius/dify.git
cd difyUse the package manager the project specifies (check for pnpm or yarn lockfiles).
npm installLaunch the dev server or build, per the README.
npm run devThe core software is open-source and free to self-host. Managed cloud versions exist for most of these if you would rather not run a server.
Most flows are built visually. Light expressions or code nodes help for advanced logic, but simple automations need none.
It is an open-source project at langgenius/dify with 24,895 forks. Check the repo's contributors and recent commits to see how active maintenance is.
Same idea — triggers and actions across apps — but self-hosted, with AI steps first-class and no per-task pricing.
Typically Docker and a small VPS or home server; several offer one-command installs.
Yes — LLM nodes are standard, working with hosted APIs or your own local models.
Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+…
The open source Zapier alternative. Build workflow automation without spending time and money
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All-in-one AI framework for semantic search, LLM orchestration and language model workflows.
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A knowledge-base platform with visual AI workflows — build Q&A systems on your own documents
The most-starred other RAG & Knowledge projects in the LibreAI catalogue — the realistic shortlist if Dify is not the right fit.
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Complete API layer for private AI apps on local models: RAG, skills, tools, MCP and text-to-SQL
Free and open — grab the source, star the repo, and start creating.