ee659ca38c
The first 1.11.0.dev0 nightly failed its "Test Langflow Main CLI" step: the fork bump's sync_bundle_lfx_pin.py re-synced every bundle floor to lfx>=1.11.0, and PEP 440 sorts the nightly's 1.11.0.dev0 BELOW 1.11.0, so the workspace-built bundles (whose metadata shadows the satisfiable PyPI lfx-arxiv 0.1.1 during `uv pip install dist/*.whl`) reject the branch's own lfx while langflow-base pins it exactly — unresolvable. Floor at lfx>=X.Y.0.dev0,<(X+1).0.0 instead: X.Y.0.dev0 is the lowest version PEP 440 admits in the minor line, so every devN / rcN / final satisfies the floor while older lines and the next major stay excluded. This closes the NIGHTLY.md activation-gate hole structurally — future minor forks re-sync to a floor their own nightlies already satisfy. - sync_bundle_lfx_pin.py: lfx_floor_spec emits the .dev0 floor - port_bundle.py: mirrored _current_lfx_floor kept in step - bundle pyprojects restamped via the script (arxiv/docling/duckduckgo/ibm) - test_bundle_lfx_pin.py expectations updated (20/20 passing) - NIGHTLY.md gate section annotated with the post-activation fix uv.lock is unaffected (workspace lfx is recorded as an editable source with no specifier — which is also why uv sync/lock passed in the same job). The release.yml RC floor-relax sed still matches the new form; now redundant but harmless. No bundle version bump needed: published 0.1.1 floors >=1.10.0.rc0, satisfiable by the whole 1.11 line.
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.
✨ Highlight features
- 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
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.
⚡️ Quickstart
Install locally (recommended)
Requires Python 3.10–3.14 and uv (recommended package manager).
Install
From a fresh directory, run:
uv pip install langflow -U
The latest Langflow package is installed. For more information, see Install and run the Langflow OSS Python package.
Run
To start Langflow, run:
uv run langflow run
Langflow starts at http://127.0.0.1:7860.
That's it! You're ready to build with Langflow! 🎉
📦 Other install options
Run from source
If you've cloned this repository and want to contribute, run this command from the repository root:
make run_cli
For more information, see DEVELOPMENT.md.
Docker
Start a Langflow container with default settings:
docker run -p 7860:7860 langflowai/langflow:latest
Langflow is available at http://localhost:7860/. For configuration options, see the Docker deployment guide.
🛡️ Security
For security information, see our Security Policy.
🚀 Deployment
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.
⭐ Stay up-to-date
Star Langflow on GitHub to be instantly notified of new releases.
👋 Contribute
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.