Common AI Hooks

The common-ai provider ships hooks that bridge an Airflow connection to a specific LLM framework’s model objects. Each hook is a thin adapter: it reads credentials and config from the connection, then returns native framework objects (a pydantic_ai Agent / Model, a LangChain BaseChatModel or Embeddings, an MCP client, …). Operators and @task decorators in this provider use these hooks internally.

Choosing a hook

Hook

When to use

PydanticAIHook

Default for common.ai operators (LLMOperator, AgentOperator, LLMBranchOperator, …). Returns a pydantic-ai Agent / Model.

LangChainHook

Direct LangChain access for tasks that compose Runnable\s, use the LangChain agent surface, or need LangChain-native chat / embedding model objects. Independent of the pydantic-ai-backed operators.

LlamaIndexHook

Backs the LlamaIndex LlamaIndexEmbeddingOperator and LlamaIndexRetrievalOperator. Returns LlamaIndex-native BaseEmbedding / LLM objects (OpenAI by default). For non-OpenAI vendors, pass a pre-built BaseEmbedding / LLM instance straight to the operator and bypass the hook.

Hook guides

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