Langflow is a powerful tool for building and deploying AI-powered agents and workflows.
http://www.langflow.org
a1629a7553* refactor: Enhance logging configuration with structured logging and buffer support * feat: Add structlog dependency for enhanced logging support * refactor: Update ruff dependency to version 0.12.7 and remove unused pylint references * Refactor logging imports to use langflow.logging.logger - Replaced instances of loguru logger with langflow.logging.logger across multiple files. - Updated logging calls to use asynchronous methods where applicable (e.g., await logger.awarning). - Ensured consistent logging practices throughout the codebase by standardizing the logger import. * refactor: Add missing docstring rule to ruff configuration * [autofix.ci] apply automated fixes * [autofix.ci] apply automated fixes (attempt 2/3) * [autofix.ci] apply automated fixes * fix: update logger calls to use async methods in DatabaseService * fix: update logger calls to use async methods in initialize_database and session_getter * fix: update logger calls to use async methods in LangflowRunnerExperimental * fix: update logger calls to use async methods across various services * Refactor logging to use asynchronous logger methods across multiple components - Updated logging calls in to use async logger methods for error handling and debugging. - Modified to utilize async logging for error messages during file deletion. - Changed logging in , , and other agent-related files to use async methods for error and debug messages. - Refactored logging in various components including , , , and others to ensure consistent use of async logging. - Updated , , and to replace synchronous logging with asynchronous counterparts. - Ensured all logging changes maintain the original message structure while enhancing performance with async capabilities. * [autofix.ci] apply automated fixes * fix: update logger calls to use async methods in various components * feat: add InterceptHandler to route standard logging messages to structlog * refactor: remove async_file parameter from logger configuration * fix: correct log level mapping and enhance log rotation validation * refactor: remove unused logging import and streamline schema imports * Refactor logging in AssemblyAI components and other modules to use exc_info for better error tracing - Updated logging statements in AssemblyAI components (e.g., assemblyai_get_subtitles, assemblyai_lemur, assemblyai_list_transcripts, etc.) to use logger.debug with exc_info=True for improved error context. - Modified logging in various helper and utility functions to enhance error reporting. - Ensured consistent logging practices across the codebase for better maintainability and debugging. * refactor: remove InterceptHandler from logger configuration to avoid recursion * refactor: enhance test coverage for logger module with comprehensive test cases * refactor: add rule to ignore mutable objects without __hash__ method in linter * fix various lint issues * refactor: update function signatures to improve clarity and consistency * refactor: streamline import statements and enhance response handling in voice mode * refactor: simplify lifespan cleanup logic * refactor: remove unused caplog fixture and improve graph test clarity * fix: specify logger type as BoundLogger for clarity * [autofix.ci] apply automated fixes * refactor: remove unused logger and correct return statement in arun_flow_from_json * refactor: update logger usage to support async methods in tests * fix: correct datetime bounds for hypothesis strategies to avoid timezone issues * fix: update warning message for invalid string input type in tests * refactor: simplify message handling tests by removing database session mocks * refactor: remove redundant comment from test_max_size function in test_logger.py * fix: update patch target for DEV setting in remove_exception_in_production test * fix: update patch target for DEV setting in remove_exception_in_production test * fix: update patching of DEV setting in remove_exception_in_production tests to use module import --------- Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com> |
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Caution
Users must update to Langflow >= 1.3 to protect against CVE-2025-3248.
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.