ogabrielluiz 8cba565bd2 fix(api/v2): enforce no-code-execution gate on public workflow endpoint
The v2 public endpoint only ran validate_flow_for_current_settings and
skipped validate_public_flow_no_code_execution, which the v1
build_public_tmp path applies. A public flow containing a Python
interpreter/REPL (or the legacy Python Code Structured tool, Smart
Transform lambda) was therefore an unauthenticated server-side
code-execution primitive (report H1-3754930).

Mirror v1: import the validator and call it right after the
public-access gate. PublicFlowValidationError subclasses
CustomComponentValidationError, so the existing handler already
sanitizes it to a 400 'This flow cannot be executed.' without leaking
the blocked component class names.

Add a non-mocking test that builds a public flow with a real
PythonREPLComponent and asserts the sanitized 400 (verified RED: returns
200 without the gate).

LE-1389
2026-06-09 15:13:27 -03:00
2025-03-20 00:05:55 +00:00
2026-04-23 17:49:53 -07:00
2024-06-04 09:26:13 -03:00

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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.

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.

📥 Download Langflow Desktop

Quickstart

Requires Python 3.103.14 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.

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👋 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.


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Langflow is a powerful tool for building and deploying AI-powered agents and workflows.
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