aaf36c4316* feat: enhance output processing to maintain order * feat: add async output resolution method with caching support * test: Update component outputs in test_component_events.py Enhance the test for component build results by adding output definitions for 'text_output' and 'tool_output' to ensure comprehensive coverage of output handling during the build process. * 📝 Add docstrings to `order-outputs` (#8280) Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com> * [autofix.ci] apply automated fixes * fix: Update output retrieval in Component class to handle missing outputs gracefully Modified the output retrieval logic in the Component class to use `get` method for accessing `_outputs_map`, providing a default value of a deepcopy of the output. This change enhances robustness by preventing KeyError exceptions when an output is not found in the map. * refactor: Enhance output processing logic in Component class Updated the _get_outputs_to_process method to first process outputs in the order defined by self.outputs, followed by any remaining outputs from _outputs_map. This change improves the output handling logic and ensures that all relevant outputs are considered for processing. * refactor: Improve docstring clarity in test_component_events.py Updated the docstring for the test_component_build_results function to enhance clarity and readability. The changes ensure that the purpose and expectations of the test are clearly communicated, improving documentation quality. --------- Co-authored-by: Edwin Jose <edwin.jose@datastax.com> Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.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.