feat(models): Add OCI Generative AI provider for Google Gemini on OCI

[fede-kamel]

Closes #5069

What this PR does

Adds OCIGenAILlm — a first-class ADK model provider for Google Gemini models hosted on Oracle Cloud Infrastructure (OCI) Generative AI. Gemini 2.5 Flash, Gemini 2.5 Pro, and Gemini 2.5 Flash Lite are available as first-party models through OCI's inference endpoints — this is a native Google × OCI model partnership, not a third-party wrapper.

from google.adk.models.oci_genai_llm import OCIGenAILlm
from google.adk.agents import LlmAgent

agent = LlmAgent(
    model=OCIGenAILlm(
        model="google.gemini-2.5-flash",
        compartment_id="ocid1.compartment.oc1...",
    ),
    instruction="You are a helpful assistant.",
)

Why this belongs in adk-python, not a community package

1. This is a model provider primitive, not a tool or connector

The community repo and integrations catalog host tools and connectors — BigQuery, Chroma, MongoDB, ElevenLabs, Slack, etc. All 60+ entries in that catalog are tool integrations. There is zero precedent for a model provider (BaseLlm subclass) living in the community repo — the community repo itself only contains memory/ and sessions/ modules, no model providers.

Every existing model provider in ADK — Gemini, Gemma, Claude, LiteLlm, ApigeeLlm — lives in src/google/adk/models/ in this repo. This PR follows that exact pattern.

2. Model providers cannot be external without degrading the SDK

LLMRegistry, BaseLlm, and the model dispatch layer are core SDK primitives. A model provider sitting in a standalone package creates:

• Version drift — core changes to BaseLlm, LlmRequest, LlmResponse, or LLMRegistry can silently break an external provider with no CI coverage
• Broken type inference — external packages lose Pydantic model validation and IDE type narrowing that works seamlessly for in-tree providers
• Second-class developer experience — pip install google-adk[oci] (an optional extra, like [extensions] for Claude) is the established pattern; requiring a separate package for one cloud provider while others are built-in is an inconsistency that confuses users

3. OCI is an official Google model distribution channel

OCI Generative AI hosts Google's own Gemini models through a direct partnership. This is the same class of integration as Vertex AI or Apigee AI Gateway — a Google-authorized inference endpoint, not a community hobby project. AWS Bedrock and Azure are absent from the SDK because no one has contributed them yet, not because multi-cloud model providers belong in a tools catalog.

4. The implementation follows established precedent exactly

Aspect	AnthropicLlm (Claude)	OCIGenAILlm (this PR)
Subclasses BaseLlm	Yes	Yes
Registered in LLMRegistry	Yes	Yes
Optional dependency guard	try/except in __init__.py	Same pattern
Install extra	pip install google-adk[extensions]	pip install google-adk[oci]
Uses native SDK	anthropic package	oci package
No LangChain dependency	Correct	Correct
Streaming + non-streaming	Yes	Yes

Design

• Subclasses BaseLlm, registered in LLMRegistry for google.gemini-* and other OCI model patterns
• Uses the OCI Python SDK directly — no LangChain dependency
• Optional install: pip install google-adk[oci] (safe to import without oci installed)
• Non-streaming: _call_oci() runs the synchronous OCI SDK call in asyncio.to_thread
• Streaming: _call_oci_stream() collects OCI's OpenAI-compatible SSE events in a thread, then yields partial=True chunks followed by a partial=False final response with aggregated content and usage metadata
• Auth: API_KEY (default), INSTANCE_PRINCIPAL, RESOURCE_PRINCIPAL

Files changed

File	Description
src/google/adk/models/oci_genai_llm.py	New OCIGenAILlm implementation
src/google/adk/models/__init__.py	Optional registration in LLMRegistry
pyproject.toml	New [oci] optional dependency extra
tests/unittests/models/test_oci_genai_llm.py	37 unit tests (fully mocked)
tests/integration/models/test_oci_genai_llm.py	10 integration tests (skipped without OCI_COMPARTMENT_ID)

Test results (rebased on current main)

• 37/37 OCI unit tests passed — fully mocked, no OCI account needed
• 641/641 total model unit tests passed — zero regressions across the entire tests/unittests/models/ suite
• Integration tests verified against live OCI endpoint (google.gemini-2.5-flash, us-chicago-1): text generation, streaming, tool calls, system instructions, multi-turn, concurrent calls
• import google.adk succeeds without oci installed (optional dependency guard)

Request to maintainers

Issue #5069 is open, labeled models + needs review, and a maintainer (@sanketpatil06) confirmed it is "under review by our team." I am asking that this PR be reviewed on its technical merits and that the routing question (core vs. community) be evaluated against the evidence above — specifically the zero precedent for external model providers, the SDK degradation risks, and the partnership-level nature of OCI Gemini hosting.

Happy to address any code review feedback directly.