apache-airflow-providers-openai
Provider package apache-airflow-providers-openai for Apache Airflow
Decision gist · record as of 2026-08-14
Yes, if you run Apache Airflow and need to call OpenAI APIs from DAGs. The package is actively maintained, has no known vulnerabilities, carries a permissive license, and integrates cleanly with Airflow's operator model. Install friction is low. Not relevant if you don't use Airflow or don't need OpenAI integration.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Apache Airflow >=2.11.0 and Python >=3.10; OpenAI API credentials must be configured in Airflow connections.
- Low install friction; pure Python wheel.
- Requires Apache Airflow >=2.11.0, apache-airflow-providers-common-compat >=1.12.0, and openai >=2.37.0.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most production environments.
last release 2026-08-08 (6 days) · last repo commit 2026-08-14 · 46,490 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 389,290 downloads/mo, #7,031 on PyPI
Alternatives
Verify before relying
pip install apache-airflow-providers-openai
from airflow.providers.openai.operators.openai import OpenAIOperator
from airflow import DAG
with DAG('openai_dag') as dag:
task = OpenAIOperator(task_id='call_openai')- Specific operators and hooks available beyond the basic OpenAI integration.
- Whether the package supports all OpenAI API endpoints or a subset.
- Performance characteristics and rate-limiting behavior when used at scale.
What it is and what it does
This is an Apache Airflow provider package that bridges Airflow DAGs and the OpenAI API. It allows you to define workflow tasks that call OpenAI services—such as text generation and embeddings—as native Airflow operators, making it straightforward to incorporate AI-powered steps into data pipelines and orchestration workflows.
The package depends on apache-airflow (>=2.11.0), apache-airflow-providers-common-compat (>=1.12.0), and openai (>=2.37.0). It supports Python 3.10 through 3.14 and is maintained as part of the Apache Airflow project, with active development and recent releases. Installation is low-friction—a simple pip install on top of an existing Airflow environment.
Use it for
- Build Airflow DAGs that call OpenAI for text summarization or content generation as part of a larger data pipeline.
- Embed OpenAI API calls into scheduled workflows to generate embeddings for documents or data records.
- Orchestrate multi-step AI workflows where OpenAI tasks are one step among many in a complex DAG.
- Integrate OpenAI capabilities into existing Airflow monitoring and data processing infrastructure.
- Create dynamic workflows that combine Airflow's scheduling with OpenAI's language models for batch processing.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you run Apache Airflow and need to call OpenAI APIs from DAGs.
The package is actively maintained, has no known vulnerabilities, carries a permissive license, and integrates cleanly with Airflow's operator model. Install friction is low. Not relevant if you don't use Airflow or don't need OpenAI integration.
Install
apache-airflow-providers-openai on PyPI
Before you install
Low install friction; pure Python wheel. Requires Apache Airflow >=2.11.0, apache-airflow-providers-common-compat >=1.12.0, and openai >=2.37.0. Package is actively maintained with a release 6 days old.
Requires Apache Airflow >=2.11.0 and Python >=3.10; OpenAI API credentials must be configured in Airflow connections.
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most production environments.
Quickstart
pip install apache-airflow-providers-openai
from airflow.providers.openai.operators.openai import OpenAIOperator
from airflow import DAG
with DAG('openai_dag') as dag:
task = OpenAIOperator(task_id='call_openai')Verify before relying
- Specific operators and hooks available beyond the basic OpenAI integration.
- Whether the package supports all OpenAI API endpoints or a subset.
- Performance characteristics and rate-limiting behavior when used at scale.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesapache-airflowapache-airflow-providers-common-compatopenai |
| Maintenance | Actively maintained 6 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 389,290 / month, #7,031 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableEnvironment :: ConsoleEnvironment :: Web EnvironmentFramework :: Apache AirflowFramework :: Apache Airflow :: ProviderIntended Audience :: DevelopersIntended Audience :: System AdministratorsProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: System :: Monitoring |
Evidence: apache_airflow_providers_openai-1.8.2-py3-none-any.whl
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See also airflow-provider-great-expectations · apache-airflow-providers-opensearch · apache-airflow-providers-asana · apache-airflow-client · apache-airflow-providers-git · apache-airflow-task-sdk · apache-airflow-providers-openfaas · apache-airflow-providers-neo4j · apache-airflow-providers-imap · airflow-code-editor