596e98b9b7
* fix: URLComponent ignores proxy in async mode (#12285) The URLComponent fails to connect for users behind corporate proxies because its asynchronous mode does not recognize standard system proxy environment variables. The component defaults to use_async=True, which initializes the RecursiveUrlLoader; the underlying async loader does not natively respect system proxy environment variables, so the component attempts a direct connection and fails in restricted network environments. Detect standard proxy environment variables (http_proxy, HTTP_PROXY, https_proxy, HTTPS_PROXY) in URLComponent._create_loader. If a proxy is detected and use_async is enabled, override use_async to False so the loader uses its synchronous implementation, which natively respects system proxies. Empty and whitespace-only values are correctly evaluated as no-proxy and do not trigger the fallback. Closes #10297 * fix(URLComponent): broaden proxy detection and harden tests Address review findings on the proxy fix: - Add ALL_PROXY and all_proxy to the detected env vars. ALL_PROXY is commonly set in corporate and container environments (curl, git, many Unix tools honour it), and is sometimes the only proxy var configured. - Replace the unused proxy_url string with a single boolean any() over the env var keys, since only the presence of a proxy is consulted. - Reorganize the proxy tests under TestURLComponentProxyHandling with a shared default-attributes helper, parametrize over all six env var spellings, and add coverage for multiple-simultaneous-proxies and the use_async=False path (which should not log a warning). * [autofix.ci] apply automated fixes * fix: remove no_proxy="*" macOS startup hack so corporate proxies work Two startup paths set `os.environ["no_proxy"] = "*"` on macOS, which disables proxy use for every HTTP client in the process and every child gunicorn worker (httpx, requests, urllib3 — and therefore the OpenAI, Anthropic, Groq, etc. SDKs that wrap them). For users behind corporate proxies on macOS this made every external LLM call unroutable, even with HTTPS_PROXY properly set. The override traces to commit history with no concrete justification — the only artifact is a Stack Overflow link about a uWSGI segfault, but Langflow uses gunicorn, not uWSGI. Bench-verified that gunicorn boots cleanly and serves requests on macOS without it (1 worker via LangflowApplication, OBJC_DISABLE_INITIALIZE_FORK_SAFETY=YES retained, HTTPS_PROXY survives intact in parent and child). Verification: - gunicorn worker spawns and serves /health (200 OK), exits cleanly - httpx, urllib, requests all resolve HTTPS_PROXY after the macOS init (previously: all three returned empty proxy maps because of no_proxy=*) - OBJC_DISABLE_INITIALIZE_FORK_SAFETY=YES still set — the actual fork-safety fix is preserved Closes the macOS half of #10297. Companion fix for the async URLComponent half is in #12285 / branch pr-12285-rebased. * [autofix.ci] apply automated fixes * [autofix.ci] apply automated fixes (attempt 2/3) * [autofix.ci] apply automated fixes (attempt 3/3) * Orjson update --------- Co-authored-by: Diogo Veiga <diogo.veiga@tecnico.ulisboa.pt> 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 3.10–3.13 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.
🛡️ 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.