Add provider for Anthropic's Vertexai Client

[ehaca]

Hello folks,
I had some time and started drafting a possible implementation for this issue: #960.
There's still lots of work to do, but I was feeling kind of insecure about my approach and wanted to get some (both general and concrete) feedback if possible before investing more time on it :)

My main questions are:

1. Is the idea about creating yet another extra something of your liking?
2. The Pycharm typing issue about

 def __init__(
        self,
        model_name: AnthropicModelName,
        *,
        # breaking this in multiple lines breaks pycharm type recognition. However, I was unable to stop ruff from
        # doing it - # fmt: skip etc didn't work  :(
        provider: Literal['anthropic', 'anthropic-vertex']
        | Provider[AsyncAnthropicVertex]
        | Provider[AsyncAnthropic] =  # fmt: skip
        'anthropic',
    ):

2. Now I am getting some static typing errors for test_init in tests/models/test_anthropic.py, how should I handle this?

Thank you very much for your feedback and help and have a nice day :)

[Kludex]

I think you need to do # fmt: off and # fmt: on after.

[acostajohn]

Maybe you should also add an entry to the KnownModelName literal at models/__init__.py

[Kludex]

This is tricky. If you want google-vertex:<anthropic-model>, the agent should be able to infer this provider instead of the other... Maybe the provider should offer different clients depending on the model?

Right now, the GoogleVertexProvider is a generic on the client, which currently is httpx.AsyncClient. What the provider can offer a client via method?

class GoogleVertexProvider(Provider):
    def get_client(self, tp: type[T]) -> T:
        if isinstance(tp, httpx.AsyncClient):
            return self.httpx_client
        elif isinstance(tp, AsyncAnthropicVertex):
            return self.anthropic_client
        else:
            raise ValueError('not supported')

[Jflick58]

@Kludex really want to see this happen - I would propose the following options:

1. Kick out VertexAI to its own top level provider - e.g. Bedrock - and let the VertexAI model class handle Anthropic/Mistral/Llama/Gemini VertexAI providers. This would be pretty clean, as the string would be google-vertex: <model name> which should route to the hypothetical VertexAI model class instead of a GeminiModel class.
2. Have routing logic based on google-vertex: <model> that would be responsible for routing to Pydantic-supported model types - e.g. it may only support Mistral/Gemini/Anthropic.
3. Change the naming convention for VertexAI Gemini models from google-vertexai to gemini-vertexai to support a model-provider model name format.

Personally, I like number 1 as I think it would be the cleanest from a top-level abstraction standpoint.

[Kludex]

This PR is fine, we need to get around on how to choose this client when passing the model string to the agent.

[RoyLeviLangware]

For those stuck on this too, here is a temporary solution:

model_obj = AnthropicModel(
        "claude-3-7-sonnet@20250219",
        provider=AnthropicProvider(
            anthropic_client=AsyncAnthropicVertex(
                project_id="PROJECT_ID",
                region="us-east5",
            )  # type: ignore
        ),
    )

[acehand]

For those stuck on this too, here is a temporary solution:

model_obj = AnthropicModel(
        "claude-3-7-sonnet@20250219",
        provider=AnthropicProvider(
            anthropic_client=AsyncAnthropicVertex(
                project_id="PROJECT_ID",
                region="us-east5",
            )  # type: ignore
        ),
    )

When i do this, i get cannot import name 'AsyncAnthropicVertex' from 'pydantic_ai.providers.anthropic, am i doing something wrong ? i am loading the latest (0.2.11) pydantic-ai

[DouweM]

@acehand AsyncAnthropicVertex is not provided by pydantic_ai, you'll have to import it from anthropic.

[andaag]

Worth noting on this that prompt caching does not work with antropic python sdk + python... anthropics/anthropic-sdk-python#653 😢

[DouweM]

@Kludex Just putting this back on your radar!

[github-actions]

This PR is stale, and will be closed in 3 days if no reply is received.

[github-actions]

Closing this PR as it has been inactive for 10 days.

[github-actions]

This PR is stale, and will be closed in 3 days if no reply is received.

[github-actions]

Closing this PR as it has been inactive for 10 days.

[github-actions]

This PR is stale, and will be closed in 3 days if no reply is received.

[github-actions]

Closing this PR as it has been inactive for 10 days.

[cristiandley]

this is my approach just in case anyone finds it useful

import os
from anthropic import AsyncAnthropicVertex
from pydantic_ai.models.anthropic import AnthropicModel


def create_vertex_model(
    model_name: str = "claude-opus-4",
    project_id: str = "app-prod",
    region: str = "us-east5",
    credentials_file: str | None = None
):
    """
    Usage:
        model = create_vertex_model("claude-opus-4")
        agent = Agent(model, system_prompt="You are helpful")
        
        @agent.tool_plain
        def my_tool(x: int): return x * 2
        
        result = await agent.run("Hello")
    """
    
    # Set credentials if provided
    if credentials_file:
        os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = credentials_file
    
    # Create Vertex client
    vertex = AsyncAnthropicVertex(
        project_id=project_id,
        region=region
    )
    
    # Add the missing attributes that AnthropicModel expects
    # This is the key trick - expose vertex itself as 'client'
    vertex.client = vertex
    vertex.model_profile = None  # Default profile
    vertex.name = "anthropic_vertex"  # Provider name
    
    return AnthropicModel(model_name, provider=vertex)

[DouweM]

@cristiandley Did you try this approach? #1392 (comment) That shouldn't require manually setting any attributes

[github-actions]

This PR is stale, and will be closed in 3 days if no reply is received.

[DouweM]

Not necessary anymore now that we have #3292