Langflow is a powerful tool for building and deploying AI-powered agents and workflows.
http://www.langflow.org
749768fdb7* feat(agent): enhance structured output handling with new input fields and validation - Added and inputs to the AgentComponent for improved structured output formatting. - Introduced method to streamline agent setup and memory data retrieval. - Enhanced method to support structured output validation against a defined schema. - Implemented error handling for JSON parsing and validation, ensuring robust output processing. This update improves the flexibility and reliability of the agent's structured response capabilities. * feat(agent): enhance structured output handling with new input fields and validation - Added `format_instructions` and `output_schema` inputs to the AgentComponent for improved structured output formatting. - Introduced `get_agent_requirements` method to streamline agent setup and memory data retrieval. - Enhanced `json_response` method to support structured output validation against a defined schema. - Implemented error handling for JSON parsing and validation, ensuring robust output processing. This update improves the flexibility and reliability of the agent's structured response capabilities. * feat(agent): add new input fields for enhanced agent configuration - Introduced , , and inputs to the AgentComponent for improved agent configuration and interaction. - Updated the handling of combined instructions to ensure clarity in agent behavior and output formatting. - Enhanced JSON schema extraction process with clearer instructions for better structured output. This update enhances the flexibility and usability of the agent component, allowing for more tailored interactions. * feat(agent): add new input fields for enhanced agent configuration - Introduced `agent_llm`, `system_prompt`, and `n_messages` inputs to the AgentComponent for improved agent configuration and interaction. - Updated the handling of combined instructions to ensure clarity in agent behavior and output formatting. - Enhanced JSON schema extraction process with clearer instructions for better structured output. This update enhances the flexibility and usability of the agent component, allowing for more tailored interactions. * template udpate * test update * refactor(tests): streamline mocking of get_agent_requirements in test_agent_component - Consolidated the mocking of the `get_agent_requirements` method in multiple test cases for improved readability and consistency. - Simplified the instantiation of `MockResult` objects to enhance clarity in test setup. This refactor enhances the maintainability of the test code by reducing redundancy. * [autofix.ci] apply automated fixes * add new logging * [autofix.ci] apply automated fixes * update templates * Update test_agent_component.py --------- Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com> Co-authored-by: Carlos Coelho <80289056+carlosrcoelho@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.