Google Vertex AI¶

The same Gemini models as the AI Studio API, over the same protocol, with enterprise addressing and Google Cloud authentication. AnyInfer reuses the Gemini adapter's translation wholesale: Vertex changes where requests go and how they are signed, not what they look like.

streaming structured output tool calls reasoning discovery (no listing endpoint)

Setup¶

import anyinfer as ai

client = ai.Client(
    [
        ai.ProviderSettings.of(
            "vertex",
            options={"project": "my-gcp-project", "location": "global"},
        ),
    ]
)

result = client.generate(prompt, target="vertex:gemini-2.5-flash")

project is required; it is part of the request path, not a header. location defaults to global; newer models are served only from the global endpoint, while a regional value (us-central1) selects that region's host.

vertex-ai: and google-vertex: are accepted aliases.

Authentication¶

Vertex takes an OAuth access token, not an API key, so the credential is acquired and refreshed instead of configured once. Three ways, in precedence order:

Application default credentialsA service-account keyA pre-acquired token

Install google-auth, then let its standard credential chain select metadata-server, workload-identity, or local gcloud credentials:

pip install google-auth

ai.ProviderSettings.of("vertex", options={"project": "my-project"})

AnyInfer uses google-auth when it is installed. The library is optional because it is not needed for the explicit-token or service-account paths.

pip install "anyinfer[vertex]"

ai.ProviderSettings.of(
    "vertex",
    options={
        "project": "my-project",
        "credentials_file": "/secrets/sa.json",
    },
)

Falls back to GOOGLE_APPLICATION_CREDENTIALS. The JWT is signed and exchanged in-house, so this works without google-auth (though signing needs an RSA implementation, and the error says so if none is available).

ai.ProviderSettings.of(
    "vertex", api_key="env://GCP_ACCESS_TOKEN", options={"project": "my-project"}
)

From gcloud auth print-access-token. Used verbatim and never refreshed; its lifetime is the caller's to manage. Note this is an access token, not a Gemini API key; the two are not interchangeable.

Acquired tokens are cached until two minutes before expiry, so a long-running client pays for one exchange per hour, not one per request.

Everything Else Is Gemini¶

Thinking levels, response schemas, function calling, and usage accounting all behave exactly as on the Gemini page, including output_tokens counting answer plus thinking:

result = client.generate(prompt, target="vertex:gemini-2.5-pro", reasoning="high")
print(result.usage.reasoning_tokens)

Discovery¶

Vertex exposes no listing endpoint comparable to AI Studio's, so client.models("vertex") returns an empty list; under the provenance rules, an invented inventory must not be presented as discovery. Name models explicitly in the target, and supply capability_overrides to make their windows known.

Health checks that a token can be acquired, without spending a generation.

Embeddings¶

Embeddings do not reuse the Gemini shape: Vertex's own text-embeddings API uses a predict verb with an instances/parameters body, so VertexAdapter overrides embedding translation instead of Gemini's batchEmbedContents:

result = client.embed(
    ["first text", "second text"],
    target="vertex:text-embedding-005",
)

gemini-embedding-001 accepts only one input per request (a documented Vertex limit), so the core's batching policy fans a multi-text call into one request per input. text-embedding-005 and text-multilingual-embedding-002 accept up to five. dimensions= requests native truncation via outputDimensionality; input_type= maps to Vertex's task_type (query→RETRIEVAL_QUERY, document→RETRIEVAL_DOCUMENT, classification→CLASSIFICATION, clustering→CLUSTERING).

Claude on Vertex¶

Vertex also serves Anthropic models, but through a different surface (rawPredict/streamRawPredict with the Messages body). This adapter does not cover it; point the Anthropic adapter at that endpoint instead.

Wire Contract¶

For the exact request/response fields this adapter depends on, see contracts/vertex.md.