ed9fedfa28
The component scanner (lfx.interface.components._process_single_module)
discovers a component class, instantiates it, and then re-evaluates the
class's *source code* via lfx.custom.validate.create_class to extract
its frontend template. That re-evaluation runs the module body in a
flat namespace — there is no package context, so relative imports
('from .constants import …') resolve to a non-existent top-level
'constants' module and raise ModuleNotFoundError.
The exception is swallowed silently inside _process_single_module
(it appends to a per-module failed_count and continues), so the
scanner returns an EMPTY component dict for the triggers package and
the entire category disappears from the frontend palette — exactly
the symptom: build_component_index / LFX_DEV scans complete with no
'triggers' key in the result.
Fix: switch to absolute import (lfx.components.triggers.constants).
Mirrors the convention used by every other built-in component;
relative imports of sibling helpers are not safe in this codebase
because of how the validator re-evaluates the source.
Verified via _process_single_module('lfx.components.triggers.cron_trigger'):
returns ('triggers', {'CronTrigger': <template>}) — the category now
surfaces to the frontend. 63/63 unit tests still pass.
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 3.10–3.13 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.
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For security information, see our Security Policy.
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