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apache-airflow-providers-cohere

Provider package apache-airflow-providers-cohere for Apache Airflow

apache-airflow-providers-cohere v1.6.7 203.3K downloads/30d#9,631 on PyPI46,490
Permissive license Apache-2.0 Active released

What it is and what it does

This is an Apache Airflow provider package that bridges Airflow's workflow orchestration engine with Cohere's language model services. It exposes Cohere's APIs as Airflow operators, hooks, and sensors, allowing you to build data pipelines that call Cohere as part of larger automated workflows. The package depends on apache-airflow (>=2.11.0), cohere (>=5.13.4), apache-airflow-providers-common-compat, and fastavro for serialization.

You install it alongside an existing Airflow deployment to add Cohere capabilities to your DAGs. It supports Python 3.10, 3.11, 3.12, 3.13, and 3.14, and is actively maintained by the Apache Airflow project. The package is production-stable and carries no known security vulnerabilities.

Use it for:

  • Build Airflow DAGs that call Cohere APIs as workflow steps within larger data pipelines.
  • Orchestrate batch processing of documents through Cohere within Airflow pipelines.
  • Chain Cohere API calls with other Airflow tasks to create end-to-end automated workflows.
  • Monitor and log Cohere API interactions as part of Airflow's native task execution.
  • Integrate Cohere-powered tasks into existing Airflow infrastructure without custom integration code.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Integrates Cohere's language model APIs into Apache Airflow workflows as operators and hooks for task orchestration.

Yes, if you run Apache Airflow >=2.11.0 and need to integrate Cohere's APIs into your workflows. The package is actively maintained, carries no known vulnerabilities, uses a permissive Apache-2.0 license, and has low install friction. Install it only if you have an Airflow deployment and an actual use case for Cohere within your orchestration pipelines.

Install

apache-airflow-providers-cohere on PyPI

pip

pip install apache-airflow-providers-cohere

uv

uv add apache-airflow-providers-cohere

poetry

poetry add apache-airflow-providers-cohere

Installing apache-airflow-providers-cohere

Before you install

Low install friction with a pure Python wheel. Actively maintained—released 6 days ago with 46490 repository stars. Requires Apache Airflow >=2.11.0 and cohere >=5.13.4.

License in practice

Apache-2.0 license permits commercial and private use with minimal restrictions; suitable for most production environments.

Quickstart

pip install apache-airflow-providers-cohere

from airflow.providers.cohere.operators import CohereOperator
from airflow import DAG

with DAG('cohere_workflow') as dag:
    task = CohereOperator(task_id='cohere_task')

Requires Apache Airflow >=2.11.0 and Python 3.10 or later; cohere >=5.13.4 must be installed.

Verify before relying

  • Which specific Cohere API operations are exposed as Airflow operators, hooks, or sensors.
  • Whether authentication to Cohere is handled via environment variables, Airflow connections, or both.
  • Performance characteristics and rate-limiting behavior when orchestrating high-volume Cohere requests.

Package facts

License Apache-2.0 (permissive)
Python support supports the current Python release (>=3.10)
Install friction low — pure-Python wheel
Runtime dependencies 4 — apache-airflow, apache-airflow-providers-common-compat, cohere, fastavro
Maintenance actively maintained — 6 days since the last release
Last repo commit
First released
Downloads 203,340/month — #9,631 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: apache_airflow_providers_cohere-1.6.7-py3-none-any.whl

Keywords: airflow-provider, cohere, airflow, integration

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

Tags

airflow cohere providerairflow language model integrationcohere airflow operatorairflow llm orchestrationcohere airflow tasksairflow ai provider
airflow-providerllm-integrationworkflow-orchestration

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