Persistent flows
Saved graphs and custom components survive restarts and releases.
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Install Langflow
Low-code AI workflowsLangflow
Install Langflow
on managed AI hosting.
Design, test, and deploy agent flows using reusable drag-and-drop components and Python-based integrations. Darwa adds the managed runtime, HTTPS, persistent storage, and lifecycle tracking around it.
One-click deploymentAlways-on runtimePersistent storage
Why Langflow
Drag-and-drop components with real Python underneath
Langflow keeps the visual graph and the code honest with each other. Every component is a Python class you can read, fork, or replace, which makes it the fastest way to test an idea you intend to hand to engineers.
- Interface
- Visual AI flow builder
- Deployment
- Managed container
- Source
- Open source on GitHub
Langflow features prepared for a managed deployment.
The visible capabilities come from the verified catalog entry; secrets and signed installer assets remain private to the backend.
Generated administrator secret
The first admin credential is generated per deployment rather than left at a published default.
HTTPS routing
A working address with a valid certificate from the first health check, no manual TLS setup.
Health verification
The deployment is only marked live once the application answers a real health probe.
Reusable components
Typed building blocks for models, memory, and tools that snap together on a canvas.
Python customization
Components are real Python classes you can read, fork, or replace.
What Langflow talks to.
A selection of what the upstream project supports. Credentials for any third-party service are yours to add and revoke.
- LangChain
- OpenAI
- Anthropic
- Ollama
- Chroma
- Pinecone
- Qdrant
- AstraDB
- Cohere
- Hugging Face
- Serper
- Wikipedia
- Python REPL
- Vector Store
- Prompt
- Memory
How a Langflow graph is served.
Each saved flow becomes a callable endpoint, so the graph you tested in the editor is the same one your application invokes.
Useful starting points for Langflow.
Agent prototyping
Assemble and test prompts, models, memory, tools, and retrieval before integrating an application.
RAG workflows
Connect document processing, vector search, model calls, and answer generation visually.
Developer handoff
Turn an approved graph into an API-backed workflow that a product can call.
What Darwa runs so you do not have to.
The hosting layer is the same for every agent, which is what makes a one-click install honest.
Verified manifest
Deployments run from a reviewed catalog entry rather than an arbitrary image you have to trust.
Isolated runtime
Each agent gets its own workload boundary, not a shared container with an unrelated website.
Persistent storage
Plan storage is allocated up front so application state survives restarts and releases.
Managed HTTPS
A working address with a certificate from the first health check, with custom domains where supported.
Health tracking
Runtime and resource signals come from the actual workload, so a failure is visible rather than silent.
Subscription lifecycle
Grace, suspension, retention, and restoration follow the plan instead of an untracked server.
Plans that can run Langflow.
One AI Agent subscription covers the managed runtime, storage, and endpoint. Model provider usage is billed by that provider.
Live pricing is temporarily unavailable. Langflow needs at least 1 vCPU, 4 GB RAM, and 10 GB of storage.
View AI agent plansFrom catalog page to a running Langflow service.
- 1
Choose Install
Darwa keeps Langflow selected when the authenticated launch flow opens.
- 2
Confirm a plan
Use an active agent subscription or choose a plan with enough compute and storage.
- 3
Choose an address
Start with an agents.darwa.co address or select an eligible verified custom domain.
- 4
Launch and track
The backend verifies the manifest, creates the runtime, and records its service and container identities.
Langflow questions.
Darwa hosts the open-source application independently; upstream licensing and product behavior remain with its project.
Can I write my own components?+
Yes. Custom components are Python classes, and code you add is stored on the deployment's persistent volume so it survives restarts.
Is a flow callable from my application?+
Yes. Published flows expose an API endpoint over the managed HTTPS address, authenticated with a key you generate in the interface.
Does Langflow store conversation memory?+
Memory components persist to the deployment's storage. Which conversations are retained, and for how long, is determined by the components you place in the graph.
Should I use Langflow or n8n?+
Use Langflow when the hard part is the AI graph itself, and n8n when the hard part is connecting many business systems around it. They are frequently deployed side by side.
What does Darwa manage for Langflow?+
Darwa manages the verified deployment manifest, isolated runtime, persistent storage allocation, HTTPS endpoint, health tracking, usage visibility, and paid-plan lifecycle. You manage the agent's models, credentials, tools, content, and decisions.
How do I install Langflow?+
Choose Install Langflow, sign in, and select an AI Agent plan if the workspace does not already have one. The launch flow keeps Langflow selected while you choose its address and start the managed deployment.
What resources does Langflow require?+
The current catalog minimum is 1 vCPU, 4 GB RAM, and 10 GB of storage. Real requirements depend on concurrency, models, document volume, integrations, and enabled features.
Does Langflow data survive restarts?+
Darwa allocates persistent storage according to the selected plan. Important application data should still follow the backup and recovery practices required by your business.
Can Langflow use a custom domain?+
The application can start with a managed Darwa address. A domain you own can be selected when custom-domain support is available for the launch flow and its DNS is verified.
Is Darwa affiliated with Langflow?+
No affiliation is implied. Langflow is a third-party open-source project. Darwa provides independent managed hosting and links to the upstream repository for project information and licensing.
Ready when you are
Sign-in and an active Darwa AI Agent plan are required before deployment.Deploy Langflow in one click.
Sign in, pick a plan with enough resources, and Darwa builds the managed runtime around it.
