pydantic_ai.models

Logic related to making requests to an LLM.

The aim here is to make a common interface for different LLMs, so that the rest of the code can be agnostic to the specific LLM being used.

KnownModelName module-attribute

KnownModelName = TypeAliasType(
    "KnownModelName",
    Literal[
        "anthropic:claude-3-7-sonnet-latest",
        "anthropic:claude-3-5-haiku-latest",
        "anthropic:claude-3-5-sonnet-latest",
        "anthropic:claude-3-opus-latest",
        "claude-3-7-sonnet-latest",
        "claude-3-5-haiku-latest",
        "bedrock:amazon.titan-tg1-large",
        "bedrock:amazon.titan-text-lite-v1",
        "bedrock:amazon.titan-text-express-v1",
        "bedrock:us.amazon.nova-pro-v1:0",
        "bedrock:us.amazon.nova-lite-v1:0",
        "bedrock:us.amazon.nova-micro-v1:0",
        "bedrock:anthropic.claude-3-5-sonnet-20241022-v2:0",
        "bedrock:us.anthropic.claude-3-5-sonnet-20241022-v2:0",
        "bedrock:anthropic.claude-3-5-haiku-20241022-v1:0",
        "bedrock:us.anthropic.claude-3-5-haiku-20241022-v1:0",
        "bedrock:anthropic.claude-instant-v1",
        "bedrock:anthropic.claude-v2:1",
        "bedrock:anthropic.claude-v2",
        "bedrock:anthropic.claude-3-sonnet-20240229-v1:0",
        "bedrock:us.anthropic.claude-3-sonnet-20240229-v1:0",
        "bedrock:anthropic.claude-3-haiku-20240307-v1:0",
        "bedrock:us.anthropic.claude-3-haiku-20240307-v1:0",
        "bedrock:anthropic.claude-3-opus-20240229-v1:0",
        "bedrock:us.anthropic.claude-3-opus-20240229-v1:0",
        "bedrock:anthropic.claude-3-5-sonnet-20240620-v1:0",
        "bedrock:us.anthropic.claude-3-5-sonnet-20240620-v1:0",
        "bedrock:anthropic.claude-3-7-sonnet-20250219-v1:0",
        "bedrock:us.anthropic.claude-3-7-sonnet-20250219-v1:0",
        "bedrock:cohere.command-text-v14",
        "bedrock:cohere.command-r-v1:0",
        "bedrock:cohere.command-r-plus-v1:0",
        "bedrock:cohere.command-light-text-v14",
        "bedrock:meta.llama3-8b-instruct-v1:0",
        "bedrock:meta.llama3-70b-instruct-v1:0",
        "bedrock:meta.llama3-1-8b-instruct-v1:0",
        "bedrock:us.meta.llama3-1-8b-instruct-v1:0",
        "bedrock:meta.llama3-1-70b-instruct-v1:0",
        "bedrock:us.meta.llama3-1-70b-instruct-v1:0",
        "bedrock:meta.llama3-1-405b-instruct-v1:0",
        "bedrock:us.meta.llama3-2-11b-instruct-v1:0",
        "bedrock:us.meta.llama3-2-90b-instruct-v1:0",
        "bedrock:us.meta.llama3-2-1b-instruct-v1:0",
        "bedrock:us.meta.llama3-2-3b-instruct-v1:0",
        "bedrock:us.meta.llama3-3-70b-instruct-v1:0",
        "bedrock:mistral.mistral-7b-instruct-v0:2",
        "bedrock:mistral.mixtral-8x7b-instruct-v0:1",
        "bedrock:mistral.mistral-large-2402-v1:0",
        "bedrock:mistral.mistral-large-2407-v1:0",
        "claude-3-5-sonnet-latest",
        "claude-3-opus-latest",
        "cohere:c4ai-aya-expanse-32b",
        "cohere:c4ai-aya-expanse-8b",
        "cohere:command",
        "cohere:command-light",
        "cohere:command-light-nightly",
        "cohere:command-nightly",
        "cohere:command-r",
        "cohere:command-r-03-2024",
        "cohere:command-r-08-2024",
        "cohere:command-r-plus",
        "cohere:command-r-plus-04-2024",
        "cohere:command-r-plus-08-2024",
        "cohere:command-r7b-12-2024",
        "deepseek:deepseek-chat",
        "deepseek:deepseek-reasoner",
        "google-gla:gemini-1.0-pro",
        "google-gla:gemini-1.5-flash",
        "google-gla:gemini-1.5-flash-8b",
        "google-gla:gemini-1.5-pro",
        "google-gla:gemini-2.0-flash-exp",
        "google-gla:gemini-2.0-flash-thinking-exp-01-21",
        "google-gla:gemini-exp-1206",
        "google-gla:gemini-2.0-flash",
        "google-gla:gemini-2.0-flash-lite-preview-02-05",
        "google-gla:gemini-2.0-pro-exp-02-05",
        "google-gla:gemini-2.5-pro-exp-03-25",
        "google-gla:gemini-2.5-pro-preview-03-25",
        "google-vertex:gemini-1.0-pro",
        "google-vertex:gemini-1.5-flash",
        "google-vertex:gemini-1.5-flash-8b",
        "google-vertex:gemini-1.5-pro",
        "google-vertex:gemini-2.0-flash-exp",
        "google-vertex:gemini-2.0-flash-thinking-exp-01-21",
        "google-vertex:gemini-exp-1206",
        "google-vertex:gemini-2.0-flash",
        "google-vertex:gemini-2.0-flash-lite-preview-02-05",
        "google-vertex:gemini-2.0-pro-exp-02-05",
        "google-vertex:gemini-2.5-pro-exp-03-25",
        "google-vertex:gemini-2.5-pro-preview-03-25",
        "gpt-3.5-turbo",
        "gpt-3.5-turbo-0125",
        "gpt-3.5-turbo-0301",
        "gpt-3.5-turbo-0613",
        "gpt-3.5-turbo-1106",
        "gpt-3.5-turbo-16k",
        "gpt-3.5-turbo-16k-0613",
        "gpt-4",
        "gpt-4-0125-preview",
        "gpt-4-0314",
        "gpt-4-0613",
        "gpt-4-1106-preview",
        "gpt-4-32k",
        "gpt-4-32k-0314",
        "gpt-4-32k-0613",
        "gpt-4-turbo",
        "gpt-4-turbo-2024-04-09",
        "gpt-4-turbo-preview",
        "gpt-4-vision-preview",
        "gpt-4.1",
        "gpt-4.1-2025-04-14",
        "gpt-4.1-mini",
        "gpt-4.1-mini-2025-04-14",
        "gpt-4.1-nano",
        "gpt-4.1-nano-2025-04-14",
        "gpt-4o",
        "gpt-4o-2024-05-13",
        "gpt-4o-2024-08-06",
        "gpt-4o-2024-11-20",
        "gpt-4o-audio-preview",
        "gpt-4o-audio-preview-2024-10-01",
        "gpt-4o-audio-preview-2024-12-17",
        "gpt-4o-mini",
        "gpt-4o-mini-2024-07-18",
        "gpt-4o-mini-audio-preview",
        "gpt-4o-mini-audio-preview-2024-12-17",
        "gpt-4o-mini-search-preview",
        "gpt-4o-mini-search-preview-2025-03-11",
        "gpt-4o-search-preview",
        "gpt-4o-search-preview-2025-03-11",
        "groq:distil-whisper-large-v3-en",
        "groq:gemma2-9b-it",
        "groq:llama-3.3-70b-versatile",
        "groq:llama-3.1-8b-instant",
        "groq:llama-guard-3-8b",
        "groq:llama3-70b-8192",
        "groq:llama3-8b-8192",
        "groq:whisper-large-v3",
        "groq:whisper-large-v3-turbo",
        "groq:playai-tts",
        "groq:playai-tts-arabic",
        "groq:qwen-qwq-32b",
        "groq:mistral-saba-24b",
        "groq:qwen-2.5-coder-32b",
        "groq:qwen-2.5-32b",
        "groq:deepseek-r1-distill-qwen-32b",
        "groq:deepseek-r1-distill-llama-70b",
        "groq:llama-3.3-70b-specdec",
        "groq:llama-3.2-1b-preview",
        "groq:llama-3.2-3b-preview",
        "groq:llama-3.2-11b-vision-preview",
        "groq:llama-3.2-90b-vision-preview",
        "mistral:codestral-latest",
        "mistral:mistral-large-latest",
        "mistral:mistral-moderation-latest",
        "mistral:mistral-small-latest",
        "o1",
        "o1-2024-12-17",
        "o1-mini",
        "o1-mini-2024-09-12",
        "o1-preview",
        "o1-preview-2024-09-12",
        "o3-mini",
        "o3-mini-2025-01-31",
        "openai:chatgpt-4o-latest",
        "openai:gpt-3.5-turbo",
        "openai:gpt-3.5-turbo-0125",
        "openai:gpt-3.5-turbo-0301",
        "openai:gpt-3.5-turbo-0613",
        "openai:gpt-3.5-turbo-1106",
        "openai:gpt-3.5-turbo-16k",
        "openai:gpt-3.5-turbo-16k-0613",
        "openai:gpt-4",
        "openai:gpt-4-0125-preview",
        "openai:gpt-4-0314",
        "openai:gpt-4-0613",
        "openai:gpt-4-1106-preview",
        "openai:gpt-4-32k",
        "openai:gpt-4-32k-0314",
        "openai:gpt-4-32k-0613",
        "openai:gpt-4-turbo",
        "openai:gpt-4-turbo-2024-04-09",
        "openai:gpt-4-turbo-preview",
        "openai:gpt-4-vision-preview",
        "openai:gpt-4.1",
        "openai:gpt-4.1-2025-04-14",
        "openai:gpt-4.1-mini",
        "openai:gpt-4.1-mini-2025-04-14",
        "openai:gpt-4.1-nano",
        "openai:gpt-4.1-nano-2025-04-14",
        "openai:gpt-4o",
        "openai:gpt-4o-2024-05-13",
        "openai:gpt-4o-2024-08-06",
        "openai:gpt-4o-2024-11-20",
        "openai:gpt-4o-audio-preview",
        "openai:gpt-4o-audio-preview-2024-10-01",
        "openai:gpt-4o-audio-preview-2024-12-17",
        "openai:gpt-4o-mini",
        "openai:gpt-4o-mini-2024-07-18",
        "openai:gpt-4o-mini-audio-preview",
        "openai:gpt-4o-mini-audio-preview-2024-12-17",
        "openai:gpt-4o-mini-search-preview",
        "openai:gpt-4o-mini-search-preview-2025-03-11",
        "openai:gpt-4o-search-preview",
        "openai:gpt-4o-search-preview-2025-03-11",
        "openai:o1",
        "openai:o1-2024-12-17",
        "openai:o1-mini",
        "openai:o1-mini-2024-09-12",
        "openai:o1-preview",
        "openai:o1-preview-2024-09-12",
        "openai:o3-mini",
        "openai:o3-mini-2025-01-31",
        "test",
    ],
)

Known model names that can be used with the model parameter of Agent.

KnownModelName is provided as a concise way to specify a model.

ModelRequestParameters dataclass

Configuration for an agent's request to a model, specifically related to tools and output handling.

Source code in pydantic_ai_slim/pydantic_ai/models/__init__.py

@dataclass
class ModelRequestParameters:
    """Configuration for an agent's request to a model, specifically related to tools and output handling."""

    function_tools: list[ToolDefinition]
    allow_text_output: bool
    output_tools: list[ToolDefinition]

Model

Bases: ABC

Abstract class for a model.

Source code in pydantic_ai_slim/pydantic_ai/models/__init__.py

class Model(ABC):
    """Abstract class for a model."""

    @abstractmethod
    async def request(
        self,
        messages: list[ModelMessage],
        model_settings: ModelSettings | None,
        model_request_parameters: ModelRequestParameters,
    ) -> tuple[ModelResponse, Usage]:
        """Make a request to the model."""
        raise NotImplementedError()

    @asynccontextmanager
    async def request_stream(
        self,
        messages: list[ModelMessage],
        model_settings: ModelSettings | None,
        model_request_parameters: ModelRequestParameters,
    ) -> AsyncIterator[StreamedResponse]:
        """Make a request to the model and return a streaming response."""
        # This method is not required, but you need to implement it if you want to support streamed responses
        raise NotImplementedError(f'Streamed requests not supported by this {self.__class__.__name__}')
        # yield is required to make this a generator for type checking
        # noinspection PyUnreachableCode
        yield  # pragma: no cover

    def customize_request_parameters(self, model_request_parameters: ModelRequestParameters) -> ModelRequestParameters:
        """Customize the request parameters for the model.

        This method can be overridden by subclasses to modify the request parameters before sending them to the model.
        In particular, this method can be used to make modifications to the generated tool JSON schemas if necessary
        for vendor/model-specific reasons.
        """
        return model_request_parameters

    @property
    @abstractmethod
    def model_name(self) -> str:
        """The model name."""
        raise NotImplementedError()

    @property
    @abstractmethod
    def system(self) -> str:
        """The system / model provider, ex: openai.

        Use to populate the `gen_ai.system` OpenTelemetry semantic convention attribute,
        so should use well-known values listed in
        https://opentelemetry.io/docs/specs/semconv/attributes-registry/gen-ai/#gen-ai-system
        when applicable.
        """
        raise NotImplementedError()

    @property
    def base_url(self) -> str | None:
        """The base URL for the provider API, if available."""
        return None

    def _get_instructions(self, messages: list[ModelMessage]) -> str | None:
        """Get instructions from the first ModelRequest found when iterating messages in reverse."""
        for message in reversed(messages):
            if isinstance(message, ModelRequest):
                return message.instructions

request abstractmethod async

request(
    messages: list[ModelMessage],
    model_settings: ModelSettings | None,
    model_request_parameters: ModelRequestParameters,
) -> tuple[ModelResponse, Usage]

Make a request to the model.

Source code in pydantic_ai_slim/pydantic_ai/models/__init__.py

@abstractmethod
async def request(
    self,
    messages: list[ModelMessage],
    model_settings: ModelSettings | None,
    model_request_parameters: ModelRequestParameters,
) -> tuple[ModelResponse, Usage]:
    """Make a request to the model."""
    raise NotImplementedError()

request_stream async

request_stream(
    messages: list[ModelMessage],
    model_settings: ModelSettings | None,
    model_request_parameters: ModelRequestParameters,
) -> AsyncIterator[StreamedResponse]

Make a request to the model and return a streaming response.

Source code in pydantic_ai_slim/pydantic_ai/models/__init__.py

@asynccontextmanager
async def request_stream(
    self,
    messages: list[ModelMessage],
    model_settings: ModelSettings | None,
    model_request_parameters: ModelRequestParameters,
) -> AsyncIterator[StreamedResponse]:
    """Make a request to the model and return a streaming response."""
    # This method is not required, but you need to implement it if you want to support streamed responses
    raise NotImplementedError(f'Streamed requests not supported by this {self.__class__.__name__}')
    # yield is required to make this a generator for type checking
    # noinspection PyUnreachableCode
    yield  # pragma: no cover

customize_request_parameters

customize_request_parameters(
    model_request_parameters: ModelRequestParameters,
) -> ModelRequestParameters

Customize the request parameters for the model.

This method can be overridden by subclasses to modify the request parameters before sending them to the model. In particular, this method can be used to make modifications to the generated tool JSON schemas if necessary for vendor/model-specific reasons.

Source code in pydantic_ai_slim/pydantic_ai/models/__init__.py

def customize_request_parameters(self, model_request_parameters: ModelRequestParameters) -> ModelRequestParameters:
    """Customize the request parameters for the model.

    This method can be overridden by subclasses to modify the request parameters before sending them to the model.
    In particular, this method can be used to make modifications to the generated tool JSON schemas if necessary
    for vendor/model-specific reasons.
    """
    return model_request_parameters

model_name abstractmethod property

model_name: str

The model name.

system abstractmethod property

system: str

The system / model provider, ex: openai.

Use to populate the gen_ai.system OpenTelemetry semantic convention attribute, so should use well-known values listed in https://opentelemetry.io/docs/specs/semconv/attributes-registry/gen-ai/#gen-ai-system when applicable.

base_url property

base_url: str | None

The base URL for the provider API, if available.

StreamedResponse dataclass

Bases: ABC

Streamed response from an LLM when calling a tool.

Source code in pydantic_ai_slim/pydantic_ai/models/__init__.py

@dataclass
class StreamedResponse(ABC):
    """Streamed response from an LLM when calling a tool."""

    _parts_manager: ModelResponsePartsManager = field(default_factory=ModelResponsePartsManager, init=False)
    _event_iterator: AsyncIterator[ModelResponseStreamEvent] | None = field(default=None, init=False)
    _usage: Usage = field(default_factory=Usage, init=False)

    def __aiter__(self) -> AsyncIterator[ModelResponseStreamEvent]:
        """Stream the response as an async iterable of [`ModelResponseStreamEvent`][pydantic_ai.messages.ModelResponseStreamEvent]s."""
        if self._event_iterator is None:
            self._event_iterator = self._get_event_iterator()
        return self._event_iterator

    @abstractmethod
    async def _get_event_iterator(self) -> AsyncIterator[ModelResponseStreamEvent]:
        """Return an async iterator of [`ModelResponseStreamEvent`][pydantic_ai.messages.ModelResponseStreamEvent]s.

        This method should be implemented by subclasses to translate the vendor-specific stream of events into
        pydantic_ai-format events.

        It should use the `_parts_manager` to handle deltas, and should update the `_usage` attributes as it goes.
        """
        raise NotImplementedError()
        # noinspection PyUnreachableCode
        yield

    def get(self) -> ModelResponse:
        """Build a [`ModelResponse`][pydantic_ai.messages.ModelResponse] from the data received from the stream so far."""
        return ModelResponse(
            parts=self._parts_manager.get_parts(), model_name=self.model_name, timestamp=self.timestamp
        )

    def usage(self) -> Usage:
        """Get the usage of the response so far. This will not be the final usage until the stream is exhausted."""
        return self._usage

    @property
    @abstractmethod
    def model_name(self) -> str:
        """Get the model name of the response."""
        raise NotImplementedError()

    @property
    @abstractmethod
    def timestamp(self) -> datetime:
        """Get the timestamp of the response."""
        raise NotImplementedError()

__aiter__

__aiter__() -> AsyncIterator[ModelResponseStreamEvent]

Stream the response as an async iterable of ModelResponseStreamEvents.

Source code in pydantic_ai_slim/pydantic_ai/models/__init__.py

def __aiter__(self) -> AsyncIterator[ModelResponseStreamEvent]:
    """Stream the response as an async iterable of [`ModelResponseStreamEvent`][pydantic_ai.messages.ModelResponseStreamEvent]s."""
    if self._event_iterator is None:
        self._event_iterator = self._get_event_iterator()
    return self._event_iterator

get

get() -> ModelResponse

Build a ModelResponse from the data received from the stream so far.

Source code in pydantic_ai_slim/pydantic_ai/models/__init__.py

def get(self) -> ModelResponse:
    """Build a [`ModelResponse`][pydantic_ai.messages.ModelResponse] from the data received from the stream so far."""
    return ModelResponse(
        parts=self._parts_manager.get_parts(), model_name=self.model_name, timestamp=self.timestamp
    )

usage

usage() -> Usage

Get the usage of the response so far. This will not be the final usage until the stream is exhausted.

Source code in pydantic_ai_slim/pydantic_ai/models/__init__.py

def usage(self) -> Usage:
    """Get the usage of the response so far. This will not be the final usage until the stream is exhausted."""
    return self._usage

model_name abstractmethod property

model_name: str

Get the model name of the response.

timestamp abstractmethod property

timestamp: datetime

Get the timestamp of the response.

ALLOW_MODEL_REQUESTS module-attribute

ALLOW_MODEL_REQUESTS = True

Whether to allow requests to models.

This global setting allows you to disable request to most models, e.g. to make sure you don't accidentally make costly requests to a model during tests.

The testing models TestModel and FunctionModel are no affected by this setting.

check_allow_model_requests

check_allow_model_requests() -> None

Check if model requests are allowed.

If you're defining your own models that have costs or latency associated with their use, you should call this in Model.request and Model.request_stream.

Raises:

Type	Description
RuntimeError	If model requests are not allowed.

Source code in pydantic_ai_slim/pydantic_ai/models/__init__.py

def check_allow_model_requests() -> None:
    """Check if model requests are allowed.

    If you're defining your own models that have costs or latency associated with their use, you should call this in
    [`Model.request`][pydantic_ai.models.Model.request] and [`Model.request_stream`][pydantic_ai.models.Model.request_stream].

    Raises:
        RuntimeError: If model requests are not allowed.
    """
    if not ALLOW_MODEL_REQUESTS:
        raise RuntimeError('Model requests are not allowed, since ALLOW_MODEL_REQUESTS is False')

override_allow_model_requests

override_allow_model_requests(
    allow_model_requests: bool,
) -> Iterator[None]

Context manager to temporarily override ALLOW_MODEL_REQUESTS.

Parameters:

Name	Type	Description	Default
allow_model_requests	bool	Whether to allow model requests within the context.	required

Source code in pydantic_ai_slim/pydantic_ai/models/__init__.py

@contextmanager
def override_allow_model_requests(allow_model_requests: bool) -> Iterator[None]:
    """Context manager to temporarily override [`ALLOW_MODEL_REQUESTS`][pydantic_ai.models.ALLOW_MODEL_REQUESTS].

    Args:
        allow_model_requests: Whether to allow model requests within the context.
    """
    global ALLOW_MODEL_REQUESTS
    old_value = ALLOW_MODEL_REQUESTS
    ALLOW_MODEL_REQUESTS = allow_model_requests  # pyright: ignore[reportConstantRedefinition]
    try:
        yield
    finally:
        ALLOW_MODEL_REQUESTS = old_value  # pyright: ignore[reportConstantRedefinition]