Langflow — Visual AI Workflow Builder

What is Langflow?

Langflow is a low-code visual builder for AI workflows. It provides a drag-and-drop interface for assembling LLMs, vector stores, embedding models, tools, and agents into complex pipelines — then exports them as Python code or API endpoints. Built on LangChain with full Python extensibility.

Answer-Ready: Langflow is a low-code visual AI workflow builder with drag-and-drop components for LLMs, vector stores, tools, and agents. Export workflows as Python code or REST APIs. Built on LangChain with 50k+ GitHub stars.

Best for: Teams prototyping RAG pipelines and AI workflows visually. Works with: OpenAI, Anthropic, Google, HuggingFace, Ollama, Pinecone, Weaviate. Setup time: Under 3 minutes.

Core Features

1. Visual Flow Editor

Drag and drop components:

[Input] → [Claude Sonnet] → [Vector Search] → [Output]
                                    ↑
                            [Weaviate DB]

Components include: Chat models, embeddings, vector stores, tools, agents, retrievers, text splitters, and custom Python nodes.

2. Pre-Built Templates

Start from templates:

• Basic RAG: Upload docs → embed → retrieve → answer
• Multi-Agent Chat: Multiple specialized agents collaborating
• Data Pipeline: Ingest → transform → store → query
• Customer Support: Knowledge base + chat + escalation

3. API Export

Every flow becomes a REST API:

# After building your flow
curl -X POST http://localhost:7860/api/v1/run/your-flow-id \
  -H "Content-Type: application/json" \
  -d '{"input_value": "What is RAG?"}'

4. Custom Components

from langflow.custom import Component
from langflow.io import MessageTextInput, Output

class MyCustomNode(Component):
    display_name = "Custom Processor"
    inputs = [MessageTextInput(name="input_text", display_name="Input")]
    outputs = [Output(display_name="Output", name="output", method="process")]

    def process(self) -> str:
        text = self.input_text
        return text.upper()  # Your custom logic

5. Multi-Model Support

Deployment Options

# Local
langflow run

# Docker
docker run -p 7860:7860 langflowai/langflow

# Cloud
# DataStax Langflow (managed)

FAQ

Q: Is Langflow free? A: Open-source and free. DataStax offers a managed cloud version.

Q: Do I need to know Python? A: No for basic flows. Python knowledge helps for custom components and advanced configurations.

Q: How does it compare to n8n or Zapier? A: Langflow is AI-native — designed for LLM workflows, RAG pipelines, and agents. n8n/Zapier are general automation tools.