Flowise: The Complete Guide to Building AI Agents Visually
What if you could build powerful AI agents, chatbots, and RAG pipelines by simply dragging and dropping components on a canvas? That's Flowise. With 50,500+ GitHub stars, 310 contributors, and 80 releases, Flowise is one of the most popular open-source platforms for visually building LLM-powered applications — no coding required.
What Is Flowise?
Flowise is an open-source, low-code/no-code platform that lets you build AI agents, chatbots, and LLM workflows using a visual drag-and-drop interface. Built on LangChain.js, it provides a canvas where you connect modular nodes to create complex AI applications.
- Language: TypeScript
- License: Apache 2.0
- Stars: 50,500+ ⭐
- Forks: 23,900+
- Contributors: 310
- Releases: 80
Core Features
🎨 Visual Drag-and-Drop Builder
The heart of Flowise is its canvas. Connect LLM nodes, prompt templates, memory modules, vector stores, tools, and agent types to create sophisticated AI workflows — all visually, no code needed.
🤖 AI Agent Builder
Build agentic workflows with:
- ReAct agents — Reasoning + Acting loops
- Function calling agents — Tool-use with OpenAI-style function calls
- Multi-agent systems — Orchestrate multiple agents
- Conversational agents — Chatbot-style interactions with memory
📚 RAG Pipeline Builder
Create Retrieval-Augmented Generation pipelines by connecting:
- Document loaders — PDF, CSV, JSON, web scraping, APIs
- Text splitters — Chunk documents for embedding
- Vector stores — Pinecone, Qdrant, Weaviate, Chroma, and more
- Embeddings — OpenAI, Cohere, HuggingFace, local models
- Retrieval chains — Conversational retrieval with memory
🔧 Extensive Integrations
- LLMs: OpenAI, Anthropic, Google, Azure, Ollama, local models
- Vector Databases: Pinecone, Qdrant, Weaviate, Chroma, Milvus, Supabase
- Tools: Web search, Calculator, API calls, Custom tools
- Memory: Buffer, Window, Summary, Redis, DynamoDB
- Document Loaders: PDF, CSV, Confluence, Notion, GitHub, S3
🔌 API & Embed
Every flow you build automatically gets:
- REST API — Access your flow programmatically
- Embed widget — Drop a chat widget into any website
- SDK — Python and JavaScript SDKs
🔐 Authentication & Authorization
- API key management
- Credential management for LLM providers
- Chat flow-level permissions
Quick Start
npm (Recommended)
npm install -g flowise
npx flowise start
Open http://localhost:3000.
Docker
docker compose up -d
Docker Image
docker run -d --name flowise -p 3000:3000 flowiseai/flowise
Self-Hosting Options
Flowise supports deployment on virtually any platform:
- AWS — EC2, ECS, Lambda
- Azure — App Service, Container Instances
- Google Cloud — Cloud Run, Compute Engine
- DigitalOcean — App Platform, Droplets
- Alibaba Cloud
- Railway — One-click deploy
- Render — One-click deploy
- Northflank — One-click deploy
- HuggingFace Spaces
- Elestio, Sealos, RepoCloud
Or use Flowise Cloud at flowiseai.com for a fully managed experience.
Use Cases
Chatbots
Build customer support bots, FAQ assistants, and conversational interfaces. Connect to your knowledge base, add memory, and deploy with the embed widget.
Document Q&A (RAG)
Upload documents (PDFs, CSVs, websites), create embeddings, store in a vector database, and build a conversational Q&A system — all visually.
Coding Assistants
Connect code repositories, documentation, and LLMs to build specialized coding assistants.
Data Analysis Agents
Create agents that can query databases, process spreadsheets, and generate reports using tool-calling patterns.
Workflow Automation
Combine LLM reasoning with external APIs and tools to automate complex business processes.
Flowise vs Alternatives
Category: This tool is a visual/low-code builder for AI agents and LLM workflows.
| Feature | Flowise | Langflow | Dify |
|---|---|---|---|
| Focus | Visual AI agent builder | Python visual AI builder | Production-ready LLM platform |
| Stars | 50.5K ⭐ | 145.3K ⭐ | 131.5K ⭐ |
| License | Apache 2.0 | MIT | Custom |
| Language | TypeScript | Python | TypeScript |
| Drag-and-Drop | ✅ | ✅ | ✅ |
| LangChain Based | ✅ LangChain.js | ✅ LangChain Python | ❌ Own framework |
| RAG Pipeline | ✅ | ✅ | ✅ Built-in knowledge base |
| Agent Builder | ✅ | ✅ Multi-agent | ✅ Agentic workflows |
| npm Install | ✅ One command | ❌ (pip) | ❌ (Docker) |
| Embed Widget | ✅ Built-in | ❌ | ✅ |
| REST API | ✅ Auto-generated | ✅ | ✅ |
| Self-Host | ✅ 10+ platforms | ✅ | ✅ |
| Cloud Service | ✅ Flowise Cloud | ✅ DataStax Langflow | ✅ Dify Cloud |
| Debugging | Basic | ✅ Better debugging | ✅ Excellent debugging |
| LLMOps | ❌ | ❌ | ✅ Observability, monitoring |
| MCP Support | ❌ | ❌ | ✅ |
| Python Flexibility | ❌ | ✅ Custom Python components | ✅ |
| Contributors | 310 | 270+ | 600+ |
| Team | FlowiseAI | langflow-ai (DataStax) | LangGenius |
When to choose Flowise: You want the simplest, fastest way to build AI agents and chatbots visually. One npm install command, LangChain.js ecosystem, built-in embed widget, and 10+ self-hosting options. Best for rapid prototyping, internal tools, and deploying chatbots quickly.
When to choose Langflow: You want Python flexibility with a visual interface. Built on LangChain Python, custom Python components, better debugging. Best for Python developers who want visual prototyping with code-level control.
When to choose Dify: You need a production-ready platform with LLMOps, observability, agentic workflows, built-in knowledge base, and enterprise features. Best for teams shipping production AI applications where governance matters.
Conclusion
Flowise is the go-to platform for quickly building AI agents and LLM workflows visually. Its simplicity (one npm command), LangChain.js foundation, built-in embed widget, and massive deployment flexibility make it ideal for rapid prototyping and deploying chatbots. With 50.5K stars and 310 contributors, it has a proven, active community.