Visual multi-agent builder

Managed Langflow hosting

Langflow is the visual, Python-native framework for building multi-agent and RAG applications. Connect 100+ components on a canvas, customize any node with Python, and deploy production flows — all without managing infrastructure.

Backed by DataStax, open-source, and now available as fully managed hosting on HostAgentes from $9.99/mo.

What is Langflow?

Langflow is an open-source, Python-native framework for building multi-agent and retrieval-augmented generation (RAG) applications through a visual node canvas. Originally forked from React Flow-style graph editors and now backed by DataStax, Langflow lets developers drag LLM nodes, memory stores, vector retrievers, and custom Python components onto a canvas and connect them into working pipelines — no boilerplate wiring required. Every node on the canvas is a Python class, so the jump from visual prototype to customized production code is a single step.

HostAgentes managed Langflow hosting deploys your Langflow instance on dedicated infrastructure with automatic SSL, daily backups, and zero-downtime updates. Plans start at $9.99/mo (Basic, 1 vCPU) and scale to $29.99/mo (Pro, 2 vCPU, integrated vector store) and $79.99/mo (Scale, 4 vCPU, enterprise SLA). Unlike DataStax Langflow Cloud, HostAgentes does not require AstraDB — choose any vector store supported by Langflow.

Deployment takes under 5 minutes. No Docker, no pip install, no managing Python virtual environments or LangChain dependency conflicts.

Popular Langflow projects on HostAgentes

What teams are actually building with Langflow's visual multi-agent canvas.

01

Multi-agent research workflow

A supervisor agent dispatches sub-agents for web search, summarization, and fact-checking. Results are merged and returned as a structured report. Useful for competitive intelligence and market research.

02

SQL + Python data analysis agent

Natural-language questions translated into SQL queries, executed against a Postgres database, and then processed by a Python node for charting or anomaly detection before the answer is returned.

03

Document processing pipeline with OCR and entity extraction

PDFs or scanned images ingested via a document loader, text extracted and chunked, then passed through an entity-extraction prompt to pull out names, dates, and amounts for downstream use.

04

Code generation agent with tool use

An agent that writes code, runs it in a sandboxed Python node, observes the output, and iterates until tests pass — all within a single Langflow flow, without leaving the canvas.

05

Customer support routing to specialist agents

Incoming messages classified by a routing agent and forwarded to product, billing, or technical specialist agents, each with their own system prompt, memory, and knowledge base.

06

Voice-to-insights pipeline

Audio transcribed via a Whisper node, transcript split into semantic chunks, embedded into a vector store, and queried by a QA agent to surface key decisions or action items from meetings.

Simple, transparent pricing

No run limits. No AstraDB dependency. Pay for compute, not for executions.

Basic

$9.99 /mo

For experimenting with Langflow and building your first visual multi-agent flows.

  • 1 vCPU, 2 GB RAM
  • 20 GB storage
  • Unlimited flows
  • Unlimited runs
  • 100+ built-in components
  • SSL and automatic backups
  • Community support
Get started
Most popular

Pro

$29.99 /mo

For teams building production multi-agent and RAG apps with Python customization.

  • Everything in Basic
  • 2 vCPU, 4 GB RAM
  • 50 GB storage
  • Team management + roles
  • Integrated vector store
  • Email support
  • Automatic updates
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Scale

$79.99 /mo

For organizations running multiple high-traffic Langflow projects in production.

  • Everything in Pro
  • 4 vCPU, 8 GB RAM
  • 100 GB storage
  • Multiple workspaces
  • Enterprise SSO
  • Priority support
  • Uptime SLA
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7-day money-back guarantee. Cancel at any time.

The price you see is the price you pay. No renewal surprises, no hidden fees.

Built for the Python-native builder

Visual speed with code-level control. No compromises.

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Visual flow canvas with Python node editing

Drag components onto the canvas and connect them visually. Every node exposes a Python code editor — swap out the default logic, add pre/post-processing, or wire in any library from PyPI.

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Multi-agent orchestration primitives

Build systems where agents call other agents, share tool outputs, and hand off work across session boundaries. Langflow's agent node handles routing, memory, and tool selection natively.

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100+ built-in components

LLMs (OpenAI, Anthropic, Gemini, Mistral, Ollama), memory stores, web search, document loaders, retrievers, code execution, and more — ready to wire together without writing boilerplate.

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Astra DB vector store + any alternative

DataStax Astra DB is natively integrated for vector storage and RAG retrieval. Prefer Pinecone, Weaviate, Chroma, or FAISS? Those work too — HostAgentes does not lock you into any specific provider.

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Custom Python escape hatch

When 100+ built-in components are not enough, write a Custom Component in pure Python. Define inputs, outputs, and logic — Langflow renders it as a first-class node on your canvas.

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Fully managed infrastructure

Automatic SSL, daily backups, zero-downtime version updates, and a persistent database for flow storage. No Docker, no pip, no virtual environments to manage on your side.

Custom Python components in Langflow

When the 100+ built-in components do not cover your use case, write a CustomComponent in Python. Define typed inputs and outputs, and Langflow renders it as a native node on your canvas. The example below creates a web scraper node that fetches a URL and returns a LangChain Document — ready to connect to any retriever or embedding node.

web_scraper_component.py
from langflow.custom import CustomComponent
from langchain.schema import Document
from typing import Optional
import httpx

class WebScraperComponent(CustomComponent):
    display_name = "Web Scraper"
    description = "Fetches a URL and returns its text content as a Document."

    def build_config(self):
        return {
            "url": {"display_name": "URL", "info": "Target URL to scrape"},
            "timeout": {"display_name": "Timeout (s)", "value": 10},
        }

    def build(self, url: str, timeout: int = 10) -> Document:
        response = httpx.get(url, timeout=timeout, follow_redirects=True)
        response.raise_for_status()
        return Document(page_content=response.text, metadata={"source": url})

Once saved, this component appears on the Langflow canvas under "Custom Components" and accepts connections like any built-in node. No restart required.

From sign-up to first flow in 5 minutes

1

Choose your plan

Basic at $9.99/mo is enough to experiment with multi-agent flows and RAG. Upgrade to Pro when you need an integrated vector store and team management.

2

Your instance deploys automatically

Langflow, its Python runtime, a persistent database for flow storage, and SSL are all configured without any action on your part. No Docker, no pip install, no virtual environments.

3

Open the canvas and build

Drag an Agent node, connect a web search tool, add a memory store, and wire in your LLM of choice. Hit Run. Iterate visually, drop into Python when you need more control.

The managed Langflow host that gets out of your way

Your flows are the product. The infrastructure should be invisible.

No AstraDB lock-in

DataStax Langflow Cloud nudges you toward AstraDB as the vector store. With HostAgentes, every Langflow-supported vector store is a first-class option — Pinecone, Weaviate, Chroma, FAISS, Qdrant, or our integrated store.

Flat pricing — not per-run fees

Other managed platforms charge per flow execution or per LLM call routed through their proxy. HostAgentes charges for dedicated compute. Run as many flows as your instance can handle.

Persistent flow storage

Flows, component configurations, and run history are stored in a managed database. Nothing is lost on restart. Export your flows as JSON at any time.

Paperclip integration

Langflow flows are callable as REST APIs. Wire them as tool actions inside Paperclip's multi-agent orchestration layer for higher-level goal planning across specialized Langflow sub-agents.

Frequently asked questions

How is Langflow different from Flowise or Dify?
Langflow is Python-native and built for developers who want visual iteration speed without giving up code-level control. Every node on the canvas exposes a Python editor — you can override the built-in logic with any Python code or PyPI library. Flowise is built on Node.js and targets LangChain chains more directly. Dify focuses on LLM app deployment with a product-oriented UI (prompt IDE, API publishing, conversation analytics) rather than graph-based flow composition. If you are comfortable with Python and need multi-agent coordination or custom component logic, Langflow is the strongest fit.
Can I write custom Python components in Langflow?
Yes. Langflow's Custom Component API lets you define a Python class with typed inputs and outputs. Langflow renders it as a native drag-and-drop node on your canvas, indistinguishable from built-in components. You can import any library available in the Python environment — including pandas, scikit-learn, httpx, or your own internal packages. On HostAgentes, you can also request additional Python dependencies be installed in your environment.
Does Langflow work with Paperclip for orchestration?
Yes. Langflow exposes every flow as a REST API endpoint. Paperclip, HostAgentes's multi-agent orchestration product, can call those endpoints as tool actions within a larger agent graph. A common pattern is to build specialized sub-agents in Langflow (document retrieval, code execution, data analysis) and then wire them together as tools inside Paperclip's orchestration layer for higher-level goal planning.
What vector stores are supported?
Langflow ships with built-in components for DataStax Astra DB, Pinecone, Weaviate, Chroma, FAISS, Qdrant, Redis, and others. On HostAgentes you are free to use any of these — there is no mandatory provider. The Pro and Scale plans include an integrated local vector store so you can start building RAG pipelines without any external account.
Can I export a Langflow flow as standalone Python?
Langflow flows can be exported as JSON and re-executed via the Langflow Python SDK or CLI outside the visual editor. For full standalone scripts, the recommended path is to use the exported JSON with langflow run or to call the REST API from your own application. The visual canvas and the Python runtime are two views of the same flow definition, so your logic is never trapped behind a proprietary format.

Build your first multi-agent flow with Langflow

Visual canvas, Python-level control, and managed infrastructure. Your instance is live in under 5 minutes from $9.99/mo.