Langflow is a powerful tool for building and deploying AI-powered agents and workflows.
http://www.langflow.org
95ceb52fa3* Added TabMixin * Added Tab component on inputs * Added Tab component to initializations * Added tests for tab input * Added Tab Component type * Added options and active tab to input field type * Added tab component on frontend * Instantiate tab component * Update package lock * Refactor input classes and imports for consistency - Reordered imports to maintain consistency across files. - Simplified class definitions by removing unnecessary line breaks. - Updated the `__all__` list in `__init__.py` files to include `TableInput` consistently. - Adjusted test cases for cleaner syntax without altering functionality. * Add constants for tab options limits in input mixin - Introduced `MAX_TAB_OPTIONS` and `MAX_TAB_OPTION_LENGTH` constants for better maintainability. - Updated validation logic in `TabMixin` to use these constants for clearer and more flexible error messages. * Refactor tab input validation tests for improved clarity - Replaced individual test cases for invalid tab inputs with a parameterized test function. - Enhanced test coverage by including cases for too many options, exceeding character limits, and non-string values. - Improved documentation within the test function for better understanding of validation scenarios. * Enhance tab input validation tests with parameterization - Refactored `test_tab_input_valid` to use `pytest.mark.parametrize` for improved test coverage and clarity. - Included multiple scenarios for valid tab inputs, such as standard, fewer options, and empty options. - Updated assertions to reflect the expected outcomes based on parameterized inputs. * Enhance TabInput validation to ensure value is a string and one of the specified options - Updated the `validate_value` method to enforce that the input value is a string. - Added a check to validate that the value is among the allowed options, raising a ValueError with a descriptive message if not. - Improved error handling for better user feedback on invalid inputs. * Fix optional chaining in error handling within CodeAreaModal - Updated the error check in the `delayedFunction` to use optional chaining for safer access to the error detail. - This change ensures that the code handles cases where `detail` may be undefined, improving robustness. * Add 'TAB' field type to schema and update direct types list - Included 'TAB' as a valid field type in the schema conversion dictionary. - Updated the DIRECT_TYPES list to include 'tab', ensuring consistency across type definitions. - These changes enhance the flexibility of the input handling for tab components. * Add unit test * Re-added noqa * fix: unit tests * [autofix.ci] apply automated fixes --------- Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@langflow.org> Co-authored-by: italojohnny <italojohnnydosanjos@gmail.com> Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com> |
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Langflow is a powerful tool for building and deploying AI-powered agents and workflows. It provides developers with both a visual authoring experience and a built-in API server that turns every agent into an API endpoint 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 to get started quickly and iterate.
- Access to Code so developers can tweak any component using Python.
- Playground to immediately test and iterate on their flows with step-by-step control.
- Multi-agent orchestration and conversation management and retrieval.
- Deploy as an API or export as JSON for Python apps.
- Observability with LangSmith, LangFuse and other integrations.
- Enterprise-ready security and scalability.
⚡️ Quickstart
Langflow works with Python 3.10 to 3.13.
Install with uv (recommended)
uv pip install langflow
Install with pip
pip install langflow
📦 Deployment
Self-managed
Langflow is completely open source and you can deploy it to all major deployment clouds. Follow this guide to learn how to use Docker to deploy Langflow.
Fully-managed by DataStax
DataStax Langflow is a full-managed environment with zero setup. Developers can sign up for a free account to get started.
⭐ 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.