Lee-W commented on code in PR #69552: URL: https://github.com/apache/airflow/pull/69552#discussion_r3550002188
########## providers/common/ai/docs/quickstart.rst: ########## @@ -0,0 +1,94 @@ + .. Licensed to the Apache Software Foundation (ASF) under one + or more contributor license agreements. See the NOTICE file + distributed with this work for additional information + regarding copyright ownership. The ASF licenses this file + to you under the Apache License, Version 2.0 (the + "License"); you may not use this file except in compliance + with the License. You may obtain a copy of the License at + + .. http://www.apache.org/licenses/LICENSE-2.0 + + .. Unless required by applicable law or agreed to in writing, + software distributed under the License is distributed on an + "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + KIND, either express or implied. See the License for the + specific language governing permissions and limitations + under the License. + +.. _howto/quickstart: + +Quick start +=========== + +Go from zero to a running LLM task in three steps: install the provider, +configure a connection, and write a Dag. + +1. Install +---------- + +.. code-block:: bash + + pip install apache-airflow-providers-common-ai + +2. Configure the connection +---------------------------- + +Every LLM call goes through a Pydantic AI connection (``conn_type`` ``pydanticai``, +default connection id ``pydanticai_default``). The model is set in ``provider:model`` +format and the API key goes in the password field. See :ref:`howto/connection:pydanticai` +for the full reference, including providers that +don't need an API key (Bedrock, Vertex AI). + +The quickest way to set one up is an environment variable: + +.. code-block:: bash + + export AIRFLOW_CONN_PYDANTICAI_DEFAULT='{"conn_type": "pydanticai", "password": "sk-...", "extra": "{\"model\": \"openai:gpt-5.3\"}"}' + +Or add it through the Airflow UI (``Admin > Connections``) or the CLI (``airflow connections add``). + +3. Write your first Dag +------------------------ + +The ``@task.llm`` decorator turns a function that returns a prompt string into +a task that sends that prompt to the LLM and returns its response: + +.. code-block:: python Review Comment: Moved this Dag into `example_quickstart.py`. Thanks! -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
