Langflow is a powerful tool for building and deploying AI-powered agents and workflows.
http://www.langflow.org
d77686d9d2* refactor: Simplify parameter building in Vertex class using ParameterHandler * feat: Add unit tests for ParameterHandler class and organize test structure * refactor: rename openai.py to openai_chat_model.py to avoid overlapping names - Introduced a new OpenAIModelComponent class to facilitate text generation using OpenAI's language models. - Implemented various input fields including max_tokens, model_kwargs, json_mode, model_name, openai_api_base, api_key, temperature, and seed for enhanced configurability. - Added methods for building the model and handling exceptions from OpenAI API calls. - This component enhances the existing framework by integrating OpenAI's capabilities, allowing users to generate text with customizable parameters. * refactor: update OpenAIModelComponent import paths to use openai_chat_model - Changed import statements in model_input_constants.py, __init__.py, and test_tool_calling_agent.py to reflect the new OpenAIModelComponent location. - This refactor improves code organization and clarity by ensuring consistent usage of the updated component structure. * fix(param_handler): add error handling for invalid field types - Introduced a ValueError exception for invalid field types in the ParameterHandler class. - This change enhances robustness by ensuring that only valid field types are processed, improving error reporting for developers. * feat: Support list-based file path handling in ParameterHandler * test: Add comprehensive tests for ParameterHandler field processing * feat: Enhance field skipping logic in ParameterHandler Add support for skipping fields with type "other" in the parameter handling process * refactor: Simplify storage service initialization and edge parameter processing * refactor: Modernize parameter handling with pattern matching Improve type handling and conversion in ParameterHandler by: - Replacing conditional logic with pattern matching - Simplifying type conversion for various field types - Reducing nested conditionals - Enhancing code readability and maintainability * refactor: Update type hints for CycleEdge in parameter handling --------- Co-authored-by: Ítalo Johnny <italojohnnydosanjos@gmail.com> |
||
|---|---|---|
| .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.RU.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.