f4a07fac69* ✨ (webhookFieldComponent): Add support for ENABLE_DATASTAX_LANGFLOW feature flag to conditionally show generate token button 🐛 (use-get-config): Set default value for webhook polling interval if not provided in data ♻️ (custom-secret-key-modal-button): Refactor to pass modal props as a separate object to improve readability and maintainability 🔧 (use-generate-token): Add new file for generating token function 🔧 (secretKeyModal): Refactor to use generate token function based on ENABLE_DATASTAX_LANGFLOW flag and separate modal props into a dedicated interface * ✨ (constants.ts): add default polling interval and timeout constants for better code readability and maintainability ♻️ (use-get-config.ts): refactor to use the newly added default constants for polling interval and timeout to improve code consistency and reduce duplication * 🐛 (typescript_test.yml): update the maximum shard count calculation to be 25 instead of 10 to improve test distribution and efficiency * ⚙️ (typescript_test.yml): adjust optimal shard count calculation to ensure a maximum of 10 shards for test execution ♻️ (index.tsx): refactor modalConfigProps assignment to handle cases where modalProps is null or undefined --------- Co-authored-by: Mike Fortman <michael.fortman@datastax.com> |
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| deploy | ||
| docker | ||
| docker_example | ||
| docs | ||
| scripts | ||
| src | ||
| test-results | ||
| .composio.lock | ||
| .env.example | ||
| .eslintrc.json | ||
| .gitattributes | ||
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| .pre-commit-config.yaml | ||
| CODE_OF_CONDUCT.md | ||
| CONTRIBUTING.md | ||
| DEVELOPMENT.md | ||
| eslint.config.js | ||
| LICENSE | ||
| Makefile | ||
| pyproject.toml | ||
| README.md | ||
| render.yaml | ||
| uv.lock | ||
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.