All 258 Dependencies
Every package Langflow depends on, ranked by repo health score.
Langflow is an open-source platform for constructing AI agents and Retrieval-Augmented Generation pipelines using a drag-and-drop visual canvas backed by editable Python source code. Every component in the flow is a live Python class — developers can inspect, customize, and extend any node without leaving the editor, then immediately test changes in the built-in interactive playground.
The platform supports all major LLM providers (OpenAI, Anthropic, Google Gemini, Ollama, Mistral, IBM WatsonX), vector databases (Weaviate, Qdrant, Pinecone, Chroma, Cassandra, OpenSearch), and data connectors spanning Notion, Slack, Google Drive, Hugging Face, Composio, and dozens more. Flows can be exported as REST APIs or deployed as Model Context Protocol (MCP) servers, making AI logic accessible from any framework or stack.
Langflow ships as a Python package (installable with `uv`), a Docker image, and a Langflow Desktop app for Windows and macOS that bundles all dependencies. Observability is built in through LangSmith, LangFuse, OpenTelemetry, and Arize Phoenix integrations. The project has accumulated over 149,000 GitHub stars and releases on a roughly bi-weekly cadence with active contributions from more than 300 developers.
The architecture is modular: the `lfx` core library provides the graph execution engine and component registry, `langflow-base` wraps it with FastAPI services, and the top-level `langflow` package assembles optional bundles (docling, DuckDuckGo, IBM, arXiv). This separation allows teams to use the execution engine programmatically via the SDK or deploy the full visual authoring environment.