30c9aaef30
* feat: mark Text Input and Text Output components as legacy Chat Input already handles text input natively, and the current API paradigm forwards all terminal node outputs automatically, making the Text Input and Text Output components redundant. Mark both as legacy and point users to their modern replacements: - TextInput -> ChatInput (replacement = ["input_output.ChatInput"]) - TextOutput -> ChatOutput (replacement = ["input_output.ChatOutput"]) Migrate starter templates off the Text Input component: - Knowledge Retrieval: convert the search-query Text Input to Chat Input - Blog Writer, Instagram Copywriter, Portfolio Website Code Generator, Twitter Thread Generator: inline preset Text Input values directly into their target Prompt/LLM fields and remove the now-redundant input nodes Also drop stale root-level width/height from non-note nodes in Basic Prompting, fixing a pre-existing test_width_height_at_node_level failure. Update .secrets.baseline line numbers for the edited starter templates (component code_hash false positives shifted by the node changes). * [autofix.ci] apply automated fixes * test: enable legacy toggle in Playwright specs that drag Text Input/Output Text Input and Text Output are now legacy, so they are hidden from the component sidebar by default (showLegacy=false). Specs that drag them from the sidebar must first enable the legacy toggle via the existing addLegacyComponents() helper (as freeze.spec.ts already does). Add the helper call to the 8 specs that added Text Input/Output without it, fixing the Playwright shard failures on this PR. * test: fix Blog Writer starter spec for inlined instructions field Blog Writer no longer has a separate "Instructions" Text Input node; the value is now an inlined field on the Prompt component (Text Input is legacy). Fill the Prompt's instructions field (textarea_str_instructions) instead of the removed node's textarea_str_input_value. * test: force clicks past legacy banner overlap in similarity & fileUpload specs Marking Text Input/Output legacy adds a "Legacy" warning bar that increases node height. In these two tightly-packed layouts the bar/body now overlaps an adjacent node's handle/button and intercepts the click. Force the affected clicks past the overlay (consistent with existing force-click usage in fileUploadComponent). Fixes the Shard 34 (similarity) and Shard 43 (fileUpload "use text input for file paths") failures introduced by the legacy marking. * test: dismiss legacy warning bars instead of force-clicking through them The previous force-click fix was wrong: Playwright's force click still dispatches the event at the target's coordinates, which the browser routes to the topmost element there (the overlapping "Legacy" warning bar), so the real click never reached the covered handle/button (similarity's inspection modal never opened). Add a dismissLegacyWarnings() helper and call it before the affected interactions in similarity and fileUpload. Dismissing the bars removes the extra node height, restoring the compact pre-legacy layout so the normal click lands on its intended target. * [autofix.ci] apply automated fixes --------- Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[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.