Langflow is a powerful tool for building and deploying AI-powered agents and workflows.
http://www.langflow.org
55c9ee2eb2* refactor: Update _log_transaction_async to be asynchronous and improve task management - Changed _log_transaction_async method from synchronous to asynchronous to allow proper handling of transaction logging. - Added error handling for task cancellation and ensured that pending tasks are managed correctly. - Updated calls to _log_transaction_async in the ComponentVertex class to await the asynchronous method, ensuring proper flow execution and error handling. * refactor: Simplify _log_transaction_async method by removing redundant error handling - Streamlined the _log_transaction_async method to enhance readability and maintainability. - Removed unnecessary try-except blocks for task cancellation, as the async context already handles task management effectively. - Ensured that completed tasks are awaited and cleared properly, improving overall task management. * fix: Correctly handle vertex build response in asynchronous flow construction - Moved the retrieval of the vertex build response to occur after awaiting the build task, ensuring proper handling of task completion. - Improved error handling by maintaining the cancellation logic while ensuring the response is only accessed after the task is completed. - This change enhances the reliability of the flow construction process in the chat API. * fix: Improve task management in Vertex class by refining log transaction handling - Updated the log transaction handling in the Vertex class to await a single task instead of gathering all tasks, enhancing efficiency. - Removed the clearing of the task list, ensuring that only the most recent task is processed, which simplifies the task management logic. - This change aims to improve the reliability and performance of asynchronous logging in the flow execution. * refactor: Comment out log transaction handling in Vertex class for future review |
||
|---|---|---|
| .devcontainer | ||
| .github | ||
| .vscode | ||
| deploy | ||
| docker | ||
| docker_example | ||
| docs | ||
| scripts | ||
| src | ||
| test-results | ||
| .env.example | ||
| .eslintrc.json | ||
| .gitattributes | ||
| .gitignore | ||
| .pre-commit-config.yaml | ||
| CODE_OF_CONDUCT.md | ||
| CONTRIBUTING.md | ||
| DEVELOPMENT.md | ||
| eslint.config.js | ||
| LICENSE | ||
| Makefile | ||
| pyproject.toml | ||
| README.ES.md | ||
| README.FR.md | ||
| README.ja.md | ||
| README.KR.md | ||
| README.md | ||
| README.PT.md | ||
| README.zh_CN.md | ||
| render.yaml | ||
| uv.lock | ||
Langflow is a low-code app builder for RAG and multi-agent AI applications. It’s Python-based and agnostic to any model, API, or database.
Docs - Free Cloud Service - Self Managed
✨ Core features
- Python-based and agnostic to models, APIs, data sources, or databases.
- Visual IDE for drag-and-drop building and testing of workflows.
- Playground to immediately test and iterate workflows with step-by-step control.
- Multi-agent orchestration and conversation management and retrieval.
- Free cloud service to get started in minutes with no setup.
- Publish as an API or export as a Python application.
- Observability with LangSmith, LangFuse, or LangWatch integration.
- Enterprise-grade security and scalability with free DataStax Langflow cloud service.
- Customize workflows or create flows entirely just using Python.
- Ecosystem integrations as reusable components for any model, API or database.
📦 Quickstart
- Install with uv (recommended) (Python 3.10 to 3.12):
uv pip install langflow
- Install with pip (Python 3.10 to 3.12):
pip install langflow
- Cloud: DataStax Langflow is a hosted environment with zero setup. Sign up for a free account.
- Self-managed: Run Langflow in your environment. Install Langflow to run a local Langflow server, and then use the Quickstart guide to create and execute a flow.
- Hugging Face: Clone the space using this link to create a Langflow workspace.
⭐ 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.