7cd1673b72
* feat(bundles): add lfx-bundles metapackage skeleton Creates the manifest-less lfx-bundles distribution (the langchain-community model) that the long-tail providers will move into. Empty skeleton for now; the bulk move (scripts/migrate/consolidate_bundles.py) populates the provider folders + per-provider extras later. - src/bundles/lfx-bundles: a single pyproject declaring the lfx.bundles entry-point (lfx_bundles = "lfx_bundles"), an lfx>=1.10.0,<2.0.0 pin, and a generated (currently empty) `all` extra; plus a bare lfx_bundles namespace package and a README documenting the model + install stories - wired into the root workspace via the existing bundle marker blocks: dep lfx-bundles[all]>=1.0,<2.0, uv source, and member - hyphen dir name so release.yml's src/bundles/*/pyproject.toml glob builds it with zero workflow change Verified: the wheel builds (entry_points.txt carries the lfx.bundles group); load_lfx_bundles_extensions (PR-1) discovers the entry point and the empty skeleton registers zero providers with no error. * fix(ci): nightly bundle rename follows [extras] refs and self-refs Two gaps in update_bundle_versions.py around extras suffixes, both fatal or silently wrong for the first nightly carrying the lfx-bundles metapackage: - update_root_pyproject_for_bundle's dep regex required the version specifier immediately after the name, so "lfx-bundles[all]>=1.0,<2.0" (a MAIN dep) was left unrewritten while the workspace member was renamed to lfx-bundles-nightly; uv lock then tries to resolve stable lfx-bundles from PyPI, where it does not exist. The same gap silently left "lfx-docling[local]>=0.1.0" optional-dep refs pointing at the stable distribution. The regex now tolerates an [extras] group and carries it into the replacement. - rename_bundle_pyproject skipped self-referencing extras, so the metapackage's generated `all` extra kept 45 "lfx-bundles[<provider>]" members after the rename, pulling the stable distribution (same lfx_bundles import package, install collision) once published. Self refs now follow the rename, idempotently. Tests drive the real script module, mirroring test_bundle_lfx_pin.py. This closes the PR-2 audit item flagged when the metapackage was introduced. The canonical-pre-release cutover would retire the nightly rename entirely; until it lands, the rename must be correct. * fix(bundles): address review — drop orphaned nightly bundle-rename script, fix README install stories - Delete scripts/ci/update_bundle_versions.py and its tests: the nightly bundle-rename track it served was retired by the canonical pre-release cutover (src/bundles/NIGHTLY.md) and no workflow or Makefile target on main or any release branch invokes it. Stale doc references in sync_bundle_lfx_pin.py and test_bundle_lfx_pin.py updated to match. - README: split the install section into what works today (langflow, bare lfx) vs what arrives with the bulk move / engine-only split (lfx[bundles], per-provider lfx-bundles[<provider>] extras), and note the generated all extra is empty until the first provider tranche lands.
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.