461d3776db
* fix: accept Data and Message inputs in LoopComponent LoopComponent.input_types only listed DataFrame and Table, rejecting connections from Data- and Message-producing components at build time. The class description and _convert_message_to_data method already intended to support these types. - Add Data and Message to input_types on the data HandleInput - Add types=["Data"] to Item output, types=["DataFrame", "Table"] to Done output - Convert Message to Data in _validate_data before calling validate_data_input Fixes #13636 * fix: normalize mixed Message/DataFrame lists in Loop._validate_data Addresses the CodeRabbit review on #13646. The list branch converted Message items to Data but left DataFrame items untouched, so a mixed [Message, DataFrame] input became [Data, DataFrame] — which validate_data_input rejects because DataFrame is not a Data subclass. Normalize each list item: convert Message via _convert_message_to_data and expand DataFrame/Table to its rows via to_data_list(), so any accepted input shape (including a mixed list) yields a homogeneous list[Data]. Add lfx regression tests covering the input/output type metadata, the connect-time type-compatibility check, and _validate_data across single Message/Data/DataFrame, list[Message], the mixed-list case, and rejection of lists with non-coercible items. * chore: regenerate Loop component index, starter project, and locale Rebuild the component index, the "Research Translation Loop" starter project, and the en.json locale string for the Loop input_types / output types / info changes on release-1.10.1. * chore: trigger CI re-run --------- Co-authored-by: dymux <putramkti@users.noreply.github.com> Co-authored-by: Eric Hare <ericrhare@gmail.com>
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.