apache-airflow-providers-common-ai

Changelog

Breaking change: operators with output_type=<BaseModel subclass> (LLMOperator, LLMAgentOperator, LLMFileAnalysisOperator, and their @task.llm / @task.agent / @task.llm_file_analysis decorators) now return the Pydantic model instance through XCom instead of dumping it to a dict, on Airflow versions whose worker registers operator-declared output classes for deserialization. Downstream tasks should type-hint the model class (def downstream(result: MyModel)) and use attribute access (result.field) instead of subscript access. The output class must be defined at module scope and bound to an attribute matching its __name__; classes that are nested, dynamically built, or otherwise non-importable by qualname cannot be re-imported and will fail to deserialize at the consumer.

The worker walks the loaded DAG and registers each declared class before any task runs, so same-DAG downstream tasks (including mapped .expand(...) producers) deserialize the model without any configuration change. The UI XCom viewer renders the value via the stringify path and works without configuration (it shows module.MyModel@version=1(field=value,...) rather than a pretty form). Cross-DAG xcom_pull consumers still need the class qualified name added to [core] allowed_deserialization_classes – the consumer DAG’s worker only loads its own DAG. On Airflow versions whose worker does not register declared classes, the operators dump to dict instead.

0.4.0

Release Date: 2026-06-07

Note

This release changes the return type of LLMOperator, LLMAgentOperator and LLMFileAnalysisOperator: structured output is now returned through XCom as Pydantic model instances instead of plain dict objects. Downstream tasks that consume these XCom values must be updated accordingly. As this provider is still pre-1.0, the breaking change ships in a minor release.

Breaking changes

  • Return Pydantic model instances through XCom for structured output (#67644)

Features

  • Add 'OpenTelemetry' tracing for 'common.ai' Pydantic AI agents (#67792)

  • Add a bridge to expose 'common.ai' toolsets as LangChain tools (#67791)

  • Add Agent Skills support to the Common AI provider (#67786)

  • Accept Sequence[UserContent] in common.ai TaskFlow decorators (#67389)

  • Add LlamaIndex operators to common.ai provider (#67121)

  • Add 'DocumentLoaderOperator' to 'common.ai' provider (#67120)

  • Add 'Langchain' hook to 'common-ai' provider (#67192)

Bug Fixes

  • Register operator-declared XCom classes from a worker-side DAG walk (#67875)

  • common-ai: Honour serialize_output=True on LLMFileAnalysisOperator (#67858)

Misc

  • Bump common.ai floor to pydantic-ai-slim>=1.71.0 and document capabilities passthrough (#67444)

  • Remove further findings from positional session check (#67712)

  • Add prek hook to enforce HTTPException is imported from fastapi (#67367)

  • Add prek hook enforcing the "example" tag on example DAGs (#67354)

0.3.0

Release Date: 2026-05-23

Features

  • Add 'LLMRetryPolicy' to common-ai provider (#65451)

Bug Fixes

  • Update dependencies to fix dependabot alarms in providers.common.ai (#66628)

0.2.0

Release Date: 2026-05-11

Features

  • Add UsageLimits support to common.ai operators (#66248)

Doc-only

  • Add Configuration Reference docs page to Common AI provider (#66024)

0.1.1

Release Date: 2026-04-26

Misc

  • Update dependencies to address Dependabot security alarms in providers.common.ai (#65048)

  • Bump vite (#64799)

0.1.0

Release Date: 2026-04-13

Note

This release of provider is only available for Airflow 3.0+ as explained in the Apache Airflow providers support policy.

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