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pydantic_ai.models.ollama

Setup

For details on how to set up authentication with this model, see model configuration for Ollama.

Ollama model implementation using OpenAI-compatible API.

OllamaModel

Bases: OpenAIChatModel

A model that uses Ollama’s OpenAI-compatible Chat Completions API.

Self-hosted Ollama (v0.5.0+) honors response_format with json_schema via llama.cpp’s grammar-constrained decoder, so NativeOutput produces schema-valid output at generation time.

Ollama Cloud currently accepts response_format with json_schema without error but does not enforce the schema upstream (see pydantic-ai#4917 and ollama/ollama#12362). When this model detects a Cloud path — either a base_url on ollama.com or a model name ending in -cloud — it disables supports_json_schema_output on the resolved profile. With that flag off, NativeOutput raises a clear UserError so users pick a mode that actually works on Cloud (ToolOutput — the default — and PromptedOutput are both verified to work).

Apart from __init__, all methods are inherited from the base class.

Methods

__init__ 
def __init__(
    model_name: str,
    provider: Literal['ollama'] | Provider[AsyncOpenAI] = 'ollama',
    profile: ModelProfileSpec | None = None,
    settings: ModelSettings | None = None,
)

Initialize an Ollama model.

Parameters

model_name : str

The name of the Ollama model to use (e.g. 'qwen3', 'llama3.2').

provider : Literal[‘ollama’] | Provider[AsyncOpenAI] Default: 'ollama'

The provider to use. Defaults to 'ollama'.

profile : ModelProfileSpec | None Default: None

The model profile to use. Defaults to a profile picked by the provider based on the model name, adjusted to disable supports_json_schema_output when the request routes through Ollama Cloud.

settings : ModelSettings | None Default: None

Model-specific settings that will be used as defaults for this model.