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    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

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    "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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.. _howto/connection:pydanticai:

Pydantic AI Connection
======================

The `Pydantic AI <https://ai.pydantic.dev/>`__ connection type configures access
to LLM providers via the pydantic-ai framework. A single connection type works with
any provider that pydantic-ai supports: OpenAI, Anthropic, Google, Bedrock, Groq,
Mistral, Ollama, vLLM, and others.

Default Connection IDs
----------------------

The ``PydanticAIHook`` uses ``pydanticai_default`` by default.

Configuring the Connection
--------------------------

Model
    The model identifier in ``provider:model`` format. This field appears as a
    dedicated input in the connection form (via ``conn-fields``) and stores its
    value in ``extra["model"]``.

    Examples: ``openai:gpt-5.3``, ``anthropic:claude-sonnet-4-20250514``,
    ``bedrock:us.anthropic.claude-opus-4-6-v1:0``, ``google:gemini-2.0-flash``

    The model can also be overridden at the hook/operator level via the
    ``model_id`` parameter.

API Key (Password field)
    The API key for your LLM provider. Required for API-key-based providers
    (OpenAI, Anthropic, Groq, Mistral). Leave empty for providers using
    environment-based auth (Bedrock via ``AWS_PROFILE``, Vertex via
    ``GOOGLE_APPLICATION_CREDENTIALS``).

Host (optional)
    Base URL for the provider's API. Only needed for custom endpoints:

    - Ollama: ``http://localhost:11434/v1``
    - vLLM: ``http://localhost:8000/v1``
    - Azure OpenAI: ``https://<resource>.openai.azure.com/openai/deployments/<deployment>``
    - Any OpenAI-compatible API: the base URL of that service

Extra (JSON, optional)
    A JSON object with additional configuration. Programmatic users can set the
    model directly in extra:

    .. code-block:: json

        {"model": "openai:gpt-5.3"}

    When using the UI, the "Model" field above writes to this same location
    automatically.

Examples
--------

**OpenAI**

.. code-block:: json

    {
        "conn_type": "pydanticai",
        "password": "sk-...",
        "extra": "{\"model\": \"openai:gpt-5.3\"}"
    }

**Anthropic**

.. code-block:: json

    {
        "conn_type": "pydanticai",
        "password": "sk-ant-...",
        "extra": "{\"model\": \"anthropic:claude-opus-4-6\"}"
    }

**Ollama (local)**

.. code-block:: json

    {
        "conn_type": "pydanticai",
        "host": "http://localhost:11434/v1",
        "extra": "{\"model\": \"openai:llama3\"}"
    }

**AWS Bedrock**

Leave password empty and configure ``AWS_PROFILE`` or IAM role in the environment:

.. code-block:: json

    {
        "conn_type": "pydanticai",
        "extra": "{\"model\": \"bedrock:us.anthropic.claude-opus-4-6-v1:0\"}"
    }

**Google Vertex AI**

Leave password empty and configure ``GOOGLE_APPLICATION_CREDENTIALS`` in the environment:

.. code-block:: json

    {
        "conn_type": "pydanticai",
        "extra": "{\"model\": \"google:gemini-2.0-flash\"}"
    }

Model Resolution Order
----------------------

The hook reads the model from these sources in priority order:

1. ``model_id`` parameter on the hook/operator
2. ``model`` in the connection's extra JSON (set by the "Model" conn-field in the UI)
