Langflow is a powerful tool for building and deploying AI-powered agents and workflows.
http://www.langflow.org
99f2ef6115* chore: Update dependencies and improve platform markers in configuration files - Added 'hypothesis' version 6.123.17 to dev-dependencies in pyproject.toml. - Updated platform markers from 'sys_platform' to 'platform_system' for better compatibility in uv.lock, affecting multiple packages including 'jinxed', 'colorama', and 'appnope'. - Ensured consistency in platform checks across various dependencies to enhance cross-platform support. This update improves the project's dependency management and ensures better compatibility across different operating systems. * feat: Enhance ResultDataResponse serialization with truncation support - Introduced a new method `_serialize_and_truncate` to handle serialization and truncation of various data types, including strings, bytes, datetime, Decimal, UUID, and BaseModel instances. - Updated the `serialize_results` method to utilize the new truncation logic for both individual results and dictionary outputs. - Enhanced the `serialize_model` method to ensure all relevant fields are serialized and truncated according to the defined maximum text length. This update improves the handling of large data outputs, ensuring that responses remain concise and manageable. * fix: Reduce MAX_TEXT_LENGTH in constants.py from 99999 to 20000 This change lowers the maximum text length limit to improve data handling and ensure more manageable output sizes across the application. * test: Add comprehensive unit tests for ResultDataResponse and VertexBuildResponse - Introduced a new test suite in `test_api_schemas.py` to validate the serialization and truncation behavior of `ResultDataResponse` and `VertexBuildResponse`. - Implemented tests for handling long strings, special data types, nested structures, and combined fields, ensuring proper serialization and truncation. - Enhanced coverage for logging and output handling, verifying that all fields are correctly processed and truncated as per the defined maximum text length. - Utilized Hypothesis for property-based testing to ensure robustness and reliability of the serialization logic. This update significantly improves the test coverage for the API response schemas, ensuring better data handling and output management. |
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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.