8b83cf686c
* checkout fe disable retries files from fe-retries branch
* refactor(frontend): tighten retry helpers and broaden their tests
Address review feedback on the retry rework in UseRequestProcessor:
- Use axios.isAxiosError as a type guard instead of an `as AxiosError`
cast, so non-axios errors (TypeErrors thrown by queryFn, etc.) are
classified by structure rather than by an unsafe shape assertion.
- Hoist makeRetry(5) / makeRetry(3) to module scope as queryRetry /
mutationRetry. They're pure factories and don't need to be rebuilt on
every render of the hook; matches how retryDelay was already scoped.
- Honor a caller-provided options.retryDelay on the mutate path
(`options.retryDelay ?? retryDelay`). Previously the explicit
retryDelay was set after `...options`, silently clobbering any
override — inconsistent with the query path where `...options` wins.
Tests:
- Rename capture vars to mockCapturedQueryOptions /
mockCapturedMutationOptions so they comply with jest's mock-prefix
hoisting rule for variables referenced from a jest.mock factory.
- Have setup() throw a clear error if the wrapped hook was never called,
instead of NPE-ing on `const { retry } = null`.
- Mark axios fixtures with `isAxiosError: true` so they actually pass
the new type guard. Add an explicit axiosNetworkError() helper and a
nonAxiosError() case to lock in the "non-axios = transient = retry"
branch.
- Add coverage for caller-provided options.retryDelay on both query and
mutate paths to prevent the previous regression from coming back.
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.
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🖥️ 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.
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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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