Github · GitHub Repository Radar
langflow-ai langflow
Langflow is a powerful tool for building and deploying AI-powered agents and workflows.
Stars
154
Forks
10,013
Watchers: 154,199
Language
License: MIT License
Repository Radar Score
52 / 100
Growth
- 7d
- +0
- 30d
- +0
- %
- 0.0%
Last observed: 1 week ago
Score breakdown
- popularity 52
- growth 0
- activity 90
- freshness 100
- community 86
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Langflow is a powerful platform for building and deploying AI-powered agents and workflows. It provides developers with both a visual authoring experience and built-in API and MCP servers that turn every workflow into a tool that can be integrated into applications built on any framework or stack. Langflow comes with batteries included and supports all major LLMs, vector databases and a growing library of AI tools.
- Visual builder interface to quickly get started and iterate.
- Source code access lets you customize any component using Python.
- Interactive playground to immediately test and refine your flows with step-by-step control.
- Multi-agent orchestration with conversation management and retrieval.
- Deploy as an API or export as JSON for Python apps.
- Deploy as an MCP server and turn your flows into tools for MCP clients.
- Observability with LangSmith, LangFuse and other integrations.
- Enterprise-ready security and scalability.
Langflow Desktop is the easiest way to get started with Langflow. All dependencies are included, so you don't need to manage Python environments or install packages manually. Available for Windows and macOS.
Requires Python 3.10–3.14 and uv (recommended package manager).
From a fresh directory, run:
uv pip install langflow -UThe latest Langflow package is installed. For more information, see Install and run the Langflow OSS Python package.
To start Langflow, run:
uv run langflow runLangflow starts at http://127.0.0.1:7860.
That's it! You're ready to build with Langflow! 🎉
If you've cloned this repository and want to contribute, run this command from the repository root:
make run_cliFor more information, see DEVELOPMENT.md.
Start a Langflow container with default settings:
docker run -p 7860:7860 langflowai/langflow:latestLangflow is available at http://localhost:7860/. For configuration options, see the Docker deployment guide.
For security information, see our Security Policy.
Langflow is completely open source and you can deploy it to all major deployment clouds. To learn how to deploy Langflow, see our Langflow deployment guides.
Star Langflow on GitHub to be instantly notified of new releases.
We welcome contributions from developers of all levels. If you'd like to contribute, please check our contributing guidelines and help make Langflow more accessible.
Repository Radar analysis
Deterministic insights derived from public metadata and our observations — not personal testing or reviews.
Why this repository is interesting
- Maintained recently (last push 2 weeks ago).
Who should use it
- Developers working primarily with Python
- Teams exploring AI tooling, agents, or ML infrastructure
- Frontend engineers comparing UI frameworks and tools
Potential use cases
- Reference or evaluate Python open-source approaches in this domain
- Prototype AI/agent workflows or study reference architectures
Strengths
- Recent repository activity
- README present in our index
- Declared license: MIT License
- Substantial fork count (10,013) suggests reuse and contribution interest
Limitations / considerations
- Insights are derived from public metadata and our observations — not a substitute for code review
What to watch
- Re-check last push, issues, and releases on GitHub before production adoption
Strong signals: Active maintenance
Source: GitHub (public metadata) + Repository Radar analysis. We do not claim ownership of third-party repositories.