Import AITURK IDE 1.0.0-beta.1 from Hermes 63279301; preserve MIT license

plugins/model-providers/vertex/__init__.py

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+"""Google Vertex AI provider profile.
+
+vertex: Gemini models via Google Cloud's OpenAI-compatible endpoint.
+
+Auth is OAuth2 — short-lived access tokens minted from a service-account JSON
+or Application Default Credentials (ADC), NOT a static API key. Token
+resolution and refresh live in ``agent/vertex_adapter.py``; runtime_provider.py
+calls it to obtain a fresh ``(token, base_url)`` pair, then hands the token to
+the standard OpenAI client as ``api_key``. Because the wire format is the
+OpenAI-compatible chat/completions surface, no message translation is needed —
+the only Gemini-specific concern is the ``thinking_config`` reasoning hook,
+which is emitted here exactly as the ``gemini`` provider does for its
+OpenAI-compat subpath (``extra_body.google.thinking_config``).
+
+``auth_type="vertex"`` marks this as an OAuth-token provider (resolved
+specially, like bedrock's ``aws_sdk``) so it is never treated as an
+api_key provider that would mistake a credentials-file path for a key.
+"""
+
+from typing import Any
+
+from providers import register_provider
+from providers.base import ProviderProfile
+
+
+class VertexProfile(ProviderProfile):
+    """Vertex AI — reuse Gemini's thinking_config translation for extra_body."""
+
+    def build_extra_body(
+        self, *, session_id: str | None = None, **context: Any
+    ) -> dict[str, Any]:
+        """Emit ``extra_body.google.thinking_config`` for the OpenAI-compat
+        Vertex surface, mirroring the ``gemini`` provider's behavior.
+        """
+        from agent.transports.chat_completions import (
+            _build_gemini_thinking_config,
+            _snake_case_gemini_thinking_config,
+        )
+
+        model = context.get("model") or ""
+        reasoning_config = context.get("reasoning_config")
+
+        raw_thinking_config = _build_gemini_thinking_config(model, reasoning_config)
+        if not raw_thinking_config:
+            return {}
+
+        thinking_config = _snake_case_gemini_thinking_config(raw_thinking_config)
+        if not thinking_config:
+            return {}
+        return {"extra_body": {"google": {"thinking_config": thinking_config}}}
+
+    def fetch_models(
+        self,
+        *,
+        api_key: str | None = None,
+        base_url: str | None = None,
+        timeout: float = 8.0,
+    ) -> list[str] | None:
+        """Vertex's OpenAI-compat endpoint has no ``/models`` listing route;
+        model discovery is not available. The setup wizard ships a curated list.
+        """
+        return None
+
+
+vertex = VertexProfile(
+    name="vertex",
+    aliases=("google-vertex", "vertex-ai", "gcp-vertex"),
+    api_mode="chat_completions",
+    env_vars=(),  # OAuth2 via service account / ADC — not a static key env var
+    base_url="https://aiplatform.googleapis.com",  # real base_url computed at runtime
+    auth_type="vertex",
+    default_aux_model="google/gemini-3.6-flash",
+)
+
+register_provider(vertex)

plugins/model-providers/vertex/plugin.yaml

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+name: vertex-provider
+kind: model-provider
+version: 1.0.0
+description: Google Vertex AI (Gemini via OpenAI-compatible endpoint, OAuth2)
+author: Steve Lawton (@slawt), Hermes Agent