e08080507b
* feat: Add langflow-stepflow package Introduces a new workspace package `src/langflow-stepflow/` that ports the Stepflow integration from the Stepflow repository into the Langflow codebase. The package has two submodules: - `translation/`: translates Langflow flow JSON to Stepflow flow definitions (ported from integrations/langflow/converter/) - `worker/`: a Stepflow worker that executes individual Langflow components via lfx (ported from integrations/langflow/executor/) Entry point: `python -m langflow_stepflow.worker` starts the HTTP worker server for use by a Stepflow orchestrator. No changes to existing Langflow code in this commit. * fix: Address review feedback on langflow-stepflow package - Widen Python version to >=3.10,<3.14 to match langflow-base - Fix import sorting (ruff I001) and unused variable (ruff F841) - Replace sk- prefixed test strings to avoid Gitleaks false positives - Remove placeholder step reference resolution in component_tool (orchestrator resolves these before reaching the worker) - Let exceptions propagate from component_tool_executor instead of returning error dicts that look like successful results - Skip secret/password field defaults in tool input schemas - Use LRU-style bounded cache (128) for compiled components - Use asyncio.to_thread for sync component methods to avoid blocking - Fix mutable NamedTuple default (list→tuple) in PlaceholderGraph - Warn and skip deps with missing field mappings instead of silently falling back to "input" (which overwrites on multiple deps) - Tighten _is_data_list to check __class_name__ == "Data" specifically - Add comment explaining intentional teardown-before-init sequence - Add integration test for example flows * chore: Upgrade to Stepflow SDK 0.12.0 and adapt to lfx 0.3+ renames - Bump stepflow-py and stepflow-orchestrator from >=0.10.0 to >=0.12.0 - Remove Python 3.11 environment markers (SDK now supports 3.10+) - Replace server.run() with gRPC pull transport (run_grpc_worker) matching the upstream stepflow-langflow integration pattern - Update Flow serialization from Pydantic model_dump to msgspec.to_builtins - Remove Pydantic ValueExpr/actual_instance unwrapping (now plain dicts) - Add _langflow_type_name() to map lfx 0.3+ class renames (JSON→Data, Table→DataFrame) back to canonical Langflow type names - Fix DataFrame isinstance checks for lfx Table subclass - Add missing README.md, tests/__init__.py, helpers package - Add skip conditions for missing fixture files * change to lfx schema * [autofix.ci] apply automated fixes * [autofix.ci] apply automated fixes * chore: Align langflow-stepflow ruff config with repo and format - Set line-length = 120 to match root pyproject.toml (was 88, causing conflicts between pre-commit format hook and check hook) - Run ruff format across all source and test files - Add pragma: allowlist secret on test fixtures with fake API keys * [autofix.ci] apply automated fixes * [autofix.ci] apply automated fixes (attempt 2/3) * chore: Rebuild component index * [autofix.ci] apply automated fixes * fix(langflow-stepflow): allow Python 3.14 in requires-python Lift requires-python from <3.14 to <3.15 to match the rest of the workspace and the lockfile. Without this, uv sync on Python 3.14 fails the Unit/LFX/Integration test jobs and the Docker build. * [autofix.ci] apply automated fixes --------- Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com> Co-authored-by: ogabrielluiz <gabriel@langflow.org> Co-authored-by: Jordan Frazier <jordan.frazier@datastax.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.