aa3d8e621e
* fix: update run_map in LoopComponent to ensure correct predecessor tracking - Added logic to update the run_map when a new predecessor is added to the run_predecessors list. This ensures that the remove_from_predecessors() function works correctly by maintaining accurate dependencies in the graph's run manager. * feat: add execution path validation tests for graph flows - Introduced a new test file to validate execution paths in graph flows using predefined test data. - Implemented tests to ensure that both async_start and arun execution paths yield identical results. - Added fixtures and helper functions to facilitate testing without external dependencies. - Enhanced error reporting for execution mismatches to aid in debugging. * feat: add DataFrame import to constants.py - Introduced import for DataFrame from lfx.schema.dataframe to enhance functionality in field typing. * chore: update component index * refactor: update TEST_DATA_DIR path in execution path validation tests - Changed the TEST_DATA_DIR definition to use a relative path based on the current file's location, improving portability and ensuring the tests can locate the necessary data files regardless of the environment. * [autofix.ci] apply automated fixes * chore: update component index * feat: add execution path equivalence tests This commit introduces a new test suite for validating the equivalence of execution paths between `async_start` and `arun`. The tests ensure that both paths produce identical results, execute components in compatible orders, and handle loops correctly. The `ExecutionTrace` and `ExecutionTracer` classes have been implemented to capture detailed runtime behavior and state changes during graph execution. * refactor: simplify import statements and enhance test fixture usage This commit refactors the import statements in the test_execution_path_validation.py file for improved readability by consolidating multiple imports from the same module into a single line. Additionally, it updates the test_flow_execution_equivalence function to include the "client" fixture, enhancing the test's setup for better execution context. * update component index * [autofix.ci] apply automated fixes * chore: update component index --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
Caution
- Langflow versions 1.6.0 through 1.6.3 have a critical bug where
.envfiles are not read, potentially causing security vulnerabilities. DO NOT upgrade to these versions if you use.envfiles for configuration. Instead, upgrade to 1.6.4, which includes a fix for this bug.- Windows users of Langflow Desktop should not use the in-app update feature to upgrade to Langflow version 1.6.0. For upgrade instructions, see Windows Desktop update issue.
- Users must update to Langflow >= 1.3 to protect against CVE-2025-3248
- Users must update to Langflow >= 1.5.1 to protect against CVE-2025-57760
For security information, see our Security Policy and Security Advisories.
Langflow is a powerful tool 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.
⚡️ Quickstart
Install locally (recommended)
Requires Python 3.10–3.13 and uv (recommended package manager).
Install
$ uv pip install langflow -U
Installs the latest Langflow package.
Run
$ uv run langflow run
Starts the Langflow server at http://127.0.0.1:7860.
That's it! You're ready to build with Langflow 🎉
Other install options
Install from repo
If you're contributing or running from source, see DEVELOPMENT.md for setup instructions.
📦 Deployment
Langflow is completely open source and you can deploy it to all major deployment clouds. To learn how to use Docker to deploy Langflow, see the Docker deployment guide.
⭐ 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.