Langflow is a powerful tool for building and deploying AI-powered agents and workflows.
http://www.langflow.org
6febae599b* Add async support and dependencies to pyproject.toml files - Added `asgi-lifespan>=2.1.0` to dependencies. - Configured `asyncio_mode` and `asyncio_default_fixture_loop_scope` for pytest. - Updated `tool.uv` section with `asgi-lifespan` in dev-dependencies. * Convert test fixtures to async and use AsyncClient for HTTP requests * Handle 'ImportFrom' nodes in AST validation to support module attribute imports * Convert test cases to use async HTTP client - Updated test cases in `test_database.py`, `test_endpoints.py`, `test_user.py`, `test_variable.py`, `test_files.py`, `test_chat_endpoint.py`, `test_misc.py`, `test_messages_endpoints.py`, `test_api_key.py`, `test_webhook.py`, and `test_login.py` to use `httpx.AsyncClient` instead of `fastapi.TestClient`. - Modified test functions to be asynchronous and use `await` for HTTP requests. - Adjusted fixtures and helper functions to support asynchronous operations. - Ensured consistency in endpoint paths and request methods across all test cases. * Refactor string concatenation to f-string in test_chat_endpoint.py * [autofix.ci] apply automated fixes * Refactor import validation to use pattern matching for AST nodes * Set `startup_timeout` and `shutdown_timeout` to `None` in `LifespanManager` for test files. * Convert test functions to async in `test_messages_endpoints.py` * Add `api_key_required` marker to assistant component tests --------- Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com> |
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| .github | ||
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| deploy | ||
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| docker_example | ||
| docs | ||
| scripts | ||
| src | ||
| .env.example | ||
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| .pre-commit-config.yaml | ||
| CODE_OF_CONDUCT.md | ||
| CONTRIBUTING.md | ||
| eslint.config.js | ||
| LICENSE | ||
| Makefile | ||
| poetry.lock | ||
| pyproject.toml | ||
| README.ES.md | ||
| README.ja.md | ||
| README.KR.md | ||
| README.md | ||
| README.PT.md | ||
| README.zh_CN.md | ||
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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 pip (Python 3.10 or greater):
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.