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* fix(security): gate PythonREPL execution on allow_custom_components (GHSA-8qpj-27x8-pwpq) The Python Interpreter component (PythonREPLComponent) and the legacy Python REPL tool execute arbitrary user-supplied Python. They are sanitized and blocked on the unauthenticated public path, but an authenticated user could run code even in deployments locked down with allow_custom_components=false. Add ensure_code_execution_enabled(), which refuses execution when allow_custom_components is False (consistent with the custom-component policy), and call it from both components before any sanitize/exec. When no settings service is present (lfx standalone CLI), execution is allowed as a local/trusted context. * [autofix.ci] apply automated fixes * [autofix.ci] apply automated fixes (attempt 2/3) * Update src/lfx/src/lfx/components/utilities/python_repl_core.py Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com> * fix: broad exception to import error * [autofix.ci] apply automated fixes * fix(security): fail closed on null settings service in code-exec gate Address review feedback on the PythonREPL exec gate (GHSA-8qpj-27x8-pwpq): - ensure_code_execution_enabled() now fails closed when get_settings_service() returns None (registered-but-failed stack), matching the sibling validate_flow_for_current_settings. get_service swallows init errors into None, so the previous return-allow could silently bypass the gate. - Add per-component tests asserting run_python_repl and run_python_code refuse execution when allow_custom_components=False, locking in the gate wiring. - Add a gate test that a non-ImportError from get_settings_service() propagates rather than failing open; flip the None case to assert fail-closed. - Drop a duplicated comment pair in python_repl_core.py and resync the embedded copy + sha256 in component_index.json. * [autofix.ci] apply automated fixes * Update component_index.json --------- Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com> Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.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.