Langflow
Visual builder for AI agents and RAG flows that you can deploy as APIs or MCP servers.
Activity data comes from GitHub and was last refreshed Oct 22, 2026.
What it does
Langflow is a Python-based visual editor for composing LLM pipelines, agents and RAG flows from components, then exposing them as an API. It is aimed at teams with some technical skill who want to prototype quickly and still drop down to code.
Where it fits in a 10–200 person business
- Prototype a document-Q&A or lead-qualification agent before building it properly
- Expose an internal AI flow as an API for other systems
- Experiment with different models and retrievers side by side
These use cases are our editorial suggestions, not claims made by the project.
License: can a business use it?
| License | MIT |
|---|---|
| Type | Permissive: MIT / Apache-2.0: use, modify and sell with few obligations. |
| Internal business use | Allowed under the license text |
| What to watch | Permissive. Internal and commercial use allowed; keep the copyright notice. |
This is a plain-English summary of the license text, not legal advice. Third-party models you run with it have their own licenses.
Hardware requirements
| Minimum | 1 vCPU · 1.5 GB RAM |
|---|---|
| Recommended | 2 vCPU · 4 GB RAM |
Kubernetes guidance: the backend needs at least 1 GiB RAM and 0.5 CPU, the frontend 512 MiB and 0.3 CPU. A production runtime example uses 4 GiB and 2 CPU per replica. Figures here are rounded from those.
Estimated monthly hosting cost
| Minimum spec | 1 vCPU · 1.5 GB RAM → CPX12 (1 vCPU, 2 GB, 40 GB disk) €11.99/mo |
|---|---|
| Recommended spec | 2 vCPU · 4 GB RAM → CPX22 (2 vCPU, 4 GB, 80 GB disk) €19.99/mo |
How we got this: we took the cheapest Hetzner Cloud Regular Performance (shared AMD vCPU) plan with at least the RAM and vCPU the project lists, using prices read from www.hetzner.com/cloud/regular-performance on 2026-10-22. "From" monthly price cap shown by Hetzner, excluding VAT. Prices vary by location. Covers the server only; it excludes LLM API usage, backups, extra storage, GPUs and your time. Disk is not matched; add a volume if you need more than the plan includes.
How to deploy
Method: Docker
docker run -p 7860:7860 \
-e LANGFLOW_AUTO_LOGIN=false \
-e LANGFLOW_SUPERUSER_PASSWORD=<strong-password> \
langflowai/langflow:latestFrom the official instructions: docs.langflow.org/deployment-docker. Always check the source for the current version before you run it.
Known gotchas
Alternatives in AI app & agent builders
- Dify Visual platform for building LLM apps, RAG chatbots, agents and workflows. Compare Dify vs Langflow
- Flowise Drag-and-drop builder for LLM agents and chatflows (archived August 2026).
- Coze Studio Open-source edition of ByteDance's Coze agent-building platform. Compare Coze Studio vs Langflow
Facts on this page were checked against the project's own repository and docs on 2026-10-22. Spotted something out of date? Tell us.