All 253 Dependencies
Every package Flowise depends on, ranked by repo health score.
Flowise is an open-source, low-code platform for visually building and deploying AI agents and agentic workflows. Teams use its node-based canvas to wire together LLMs, retrieval pipelines, tools, memory, and human-review steps without writing boilerplate integration code—yet every node is backed by real TypeScript logic you can inspect and extend.
The platform ships as a TypeScript monorepo with a Node.js/Express backend, a React frontend, and a standalone components package that houses over 200 integrations: 20+ chat model providers (OpenAI, Anthropic, Gemini, Mistral, Ollama, Bedrock, and more), 20+ vector stores (Pinecone, Chroma, Qdrant, Postgres, Milvus, FAISS), and dozens of document loaders, memory adapters, and tool nodes. AgentFlow, Flowise's second-generation agent runtime, replaces the older LangChain chain abstraction with purpose-built visual node types—LLM, Agent, Tool, Condition, Loop, HumanInput, ExecuteFlow, HTTP—each rendered and executed uniformly on the canvas.
Flows are serialised as JSON and exposed as REST API endpoints the moment you hit deploy, with auto-generated Swagger docs and official Python and TypeScript SDKs. The server supports SQLite out of the box and switches to MySQL, MariaDB, or PostgreSQL via environment variables. For production scale, an optional Redis + BullMQ queue layer decouples predictions and upsert jobs from the HTTP request cycle. OpenTelemetry and Prometheus metrics endpoints ship standard, and the enterprise tier adds RBAC, SSO (OAuth2/SAML), workspaces, audit logs, and a managed Flowise Cloud offering.
Deployment is documented for AWS, Azure, GCP, Digital Ocean, Railway, Render, Northflank, Hugging Face Spaces, Elestio, and Sealos, and a production-ready Docker Compose file is included in the repository. With 53,000+ GitHub stars and over 80 releases since its 2023 launch, Flowise has become one of the most-adopted open-source tools in the LLM application stack.
