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I don't want to cut down your wings and excitement, but this is a deliberate choice that Airflow UI does not allow to author DAGs. This is a security feature. And our security model https://airflow.apache.org/docs/apache-airflow/stable/security/security_model.html is very clear that "UI users" do not have (and should not have) capabilities of authoring DAGs (not as Python code - that allows arbitrary code execution). Maybe (and that is something we might consider in the future) if there is a declarative way of creating DAGs which does not allow to provide arbitrary code, we could allow that, but we have not even settled on the idea of having a single declarative way of creating Dags. Also Airflow DAGS are just Python Code placed in a folder. And there is absolutely nothing stopping you to open your IDE with Claude , Cursor, Copilot, use the prompt of your choice and ... generate DAGs with LLM. There is absolutely no need to have a UI for that.- all the IDEs out there already have a fantastic LLM integration, with capability of adding prompt, using MCP servers (there are even several MCP servers for Airflow created by the community and we are discussing about creating our own MCP server https://lists.apache.org/thread/xgd66v6s7zf0xkvy3c7ysqvn4csgmw0 - those IDEs have code completion, syntax check, allow you to interact with the Agents and approve/reject proposals when you are using agents to create your DAGs. They even allow you to use your own models that can be RAG-ified based - for example - on the private DAGs your company might have. This all works **today**. I don't think personally there is any benefit of creating a similar feature in Airflow UI. I can't see any to be honest. Maybe others have a different opinion or maybe you can explain what benefits you see by adding such a "UI feature" to Airflow itself (and also the problem about security is extremely important and a huge blocker for the whole idea - until this is somewhat addressed the whole idea is basically impossible to be accepted by the community. J. On Mon, Jul 7, 2025 at 8:37 AM Harikrishnan Girikumar < harikrishnangiriku...@gmail.com> wrote: > Hello Team, > > My name is Harikrishnan(Hari), I have an idea/improvement proposal for > Airflow. > LLM-powered feature within Apache Airflow to significantly enhance the DAG > authoring experience. Users would be able to provide natural language > descriptions or queries and leverage Large Language Models (LLMs) to > automatically generate and modify Airflow DAGs. This aims to democratize > DAG creation, reduce the learning curve for new users, and accelerate the > development of complex workflows. For example: We can have a UI tab in > Airflow where users can add their respective authentication credentials for > the LLMs they want to use (OpenAI, Claude or their personal model serving > link etc.) they can select their AI from drop down and a chat window to > input queries like: Create a DAG to copy my data from S3 to Postgres and > the code generated would be copied to DAG folder. We can restrict the > Prompts to be strictly for DAG generation for initial trial, further down > the line a RAG feature could be added where a Vectorized version of Airflow > documentation is used to improve the accuracy of DAG creation. > > I am really excited about this feature, this would reduce the learning > curve and improve the interaction for new users. Let me know your thoughts, > looking forward to hearing from the team. > > Regards, > Hari >
