Langflow is a powerful tool for building and deploying AI-powered agents and workflows.
http://www.langflow.org
836faa73d6* 📝 (endpoints.py): Add get_webhook_user function to handle webhook user authentication 🔧 (endpoints.py): Update webhook_run_flow endpoint to use get_webhook_user for authentication 🔧 (utils.py): Add get_webhook_user function to handle webhook user authentication in services.auth ✅ (test_webhook.py): Add tests for webhook endpoint authentication and authorization * Update src/backend/base/langflow/services/auth/utils.py Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com> * [autofix.ci] apply automated fixes * Update src/backend/base/langflow/services/auth/utils.py Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@langflow.org> * 🔧 (utils.py): refactor authentication logic to use existing api_key_security function for better code reuse and readability * [autofix.ci] apply automated fixes * 📝 (endpoints.py): Update ConfigResponse class to include webhook_auth_enable field and modify from_settings method to accept auth_settings parameter 📝 (endpoints.py): Update get_config function to pass auth_settings to ConfigResponse.from_settings method 📝 (utils.py): Update get_webhook_user function to use WEBHOOK_AUTH_ENABLE setting for authentication logic 📝 (auth.py): Add WEBHOOK_AUTH_ENABLE setting to AuthSettings class 📝 (index.tsx): Add webhookAuthEnable state and setWebhookAuthEnable function to utilityStore 📝 (use-get-config.ts): Update useGetConfig hook to set webhook_auth_enable value from API response 📝 (get-curl-code.tsx): Update getCurlWebhookCode function to use webhookAuthEnable instead of isAuth parameter 📝 (utilityStore.ts): Add webhookAuthEnable state and setWebhookAuthEnable function to utilityStore 📝 (index.ts): Update GetCodeType type to use webhookAuthEnable instead of isAuth parameter * refactor: Simplify error messages in get_webhook_user function - Updated HTTPException messages for flow not found and access denied scenarios to be more concise and user-friendly. - Improved logging for invalid API key validation to enhance clarity. * 🐛 (test_webhook.py): fix test descriptions to accurately reflect the conditions being tested 📝 (test_webhook.py): update test descriptions to improve clarity and consistency with actual test conditions * 🐛 (utils.py): Fix issue where HTTPException was not properly handled when flow owner is not found in get_webhook_user function. Added explicit check and raise HTTPException with appropriate status code and detail message. * 📝 (test_mcp_util.py): add conditional skip for test when DeepWiki server is rate limiting requests --------- Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com> Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com> Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@langflow.org> |
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Caution
- Users must update to Langflow >= 1.3 to protect against CVE-2025-3248
- Users must update to Langflow >= 1.5.1 to protect against CVE-2025-57760
For security information, see our Security Policy and Security Advisories.
Langflow is a powerful tool for building and deploying AI-powered agents and workflows. It provides developers with both a visual authoring experience and built-in API and MCP servers that turn every workflow into a tool 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 interface to quickly get started and iterate .
- Source code access lets you customize any component using Python.
- Interactive playground to immediately test and refine your flows with step-by-step control.
- Multi-agent orchestration with conversation management and retrieval.
- Deploy as an API or export as JSON for Python apps.
- Deploy as an MCP server and turn your flows into tools for MCP clients.
- Observability with LangSmith, LangFuse and other integrations.
- Enterprise-ready security and scalability.
⚡️ Quickstart
Langflow requires Python 3.10 to 3.13 and uv.
- To install Langflow, run:
uv pip install langflow -U
- To run Langflow, run:
uv run langflow run
- Go to the default Langflow URL at
http://127.0.0.1:7860.
For more information about installing Langflow, including Docker and Desktop options, see Install Langflow.
📦 Deployment
Langflow is completely open source and you can deploy it to all major deployment clouds. To learn how to use Docker to deploy Langflow, see the Docker deployment guide.
⭐ 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.