Add OCI Generative AI new model support (#22880)

- [x] PR title: 
community: Add OCI Generative AI new model support
 
- [x] PR message:
- Description: adding support for new models offered by OCI Generative
AI services. This is a moderate update of our initial integration PR
16548 and includes a new integration for our chat models under
/langchain_community/chat_models/oci_generative_ai.py
    - Issue: NA
- Dependencies: No new Dependencies, just latest version of our OCI sdk
    - Twitter handle: NA


- [x] Add tests and docs: 
  1. we have updated our unit tests
2. we have updated our documentation including a new ipynb for our new
chat integration


- [x] Lint and test: 
 `make format`, `make lint`, and `make test` run successfully

---------

Co-authored-by: RHARPAZ <RHARPAZ@RHARPAZ-5750.us.oracle.com>
Co-authored-by: Arthur Cheng <arthur.cheng@oracle.com>

libs/community/tests/unit_tests/chat_models/test_imports.py

@@ -27,6 +27,7 @@ EXPECTED_ALL = [
     "ChatMlflow",
     "ChatMLflowAIGateway",
     "ChatMLX",
+    "ChatOCIGenAI",
     "ChatOllama",
     "ChatOpenAI",
     "ChatPerplexity",

libs/community/tests/unit_tests/chat_models/test_oci_generative_ai.py

@@ -0,0 +1,105 @@
+"""Test OCI Generative AI LLM service"""
+from unittest.mock import MagicMock
+
+import pytest
+from langchain_core.messages import HumanMessage
+from pytest import MonkeyPatch
+
+from langchain_community.chat_models.oci_generative_ai import ChatOCIGenAI
+
+
+class MockResponseDict(dict):
+    def __getattr__(self, val):  # type: ignore[no-untyped-def]
+        return self[val]
+
+
+@pytest.mark.requires("oci")
+@pytest.mark.parametrize(
+    "test_model_id", ["cohere.command-r-16k", "meta.llama-3-70b-instruct"]
+)
+def test_llm_chat(monkeypatch: MonkeyPatch, test_model_id: str) -> None:
+    """Test valid chat call to OCI Generative AI LLM service."""
+    oci_gen_ai_client = MagicMock()
+    llm = ChatOCIGenAI(model_id=test_model_id, client=oci_gen_ai_client)
+
+    provider = llm.model_id.split(".")[0].lower()
+
+    def mocked_response(*args):  # type: ignore[no-untyped-def]
+        response_text = "Assistant chat reply."
+        response = None
+        if provider == "cohere":
+            response = MockResponseDict(
+                {
+                    "status": 200,
+                    "data": MockResponseDict(
+                        {
+                            "chat_response": MockResponseDict(
+                                {
+                                    "text": response_text,
+                                    "finish_reason": "completed",
+                                }
+                            ),
+                            "model_id": "cohere.command-r-16k",
+                            "model_version": "1.0.0",
+                        }
+                    ),
+                    "request_id": "1234567890",
+                    "headers": MockResponseDict(
+                        {
+                            "content-length": "123",
+                        }
+                    ),
+                }
+            )
+        elif provider == "meta":
+            response = MockResponseDict(
+                {
+                    "status": 200,
+                    "data": MockResponseDict(
+                        {
+                            "chat_response": MockResponseDict(
+                                {
+                                    "choices": [
+                                        MockResponseDict(
+                                            {
+                                                "message": MockResponseDict(
+                                                    {
+                                                        "content": [
+                                                            MockResponseDict(
+                                                                {
+                                                                    "text": response_text,  # noqa: E501
+                                                                }
+                                                            )
+                                                        ]
+                                                    }
+                                                ),
+                                                "finish_reason": "completed",
+                                            }
+                                        )
+                                    ],
+                                    "time_created": "2024-09-01T00:00:00Z",
+                                }
+                            ),
+                            "model_id": "cohere.command-r-16k",
+                            "model_version": "1.0.0",
+                        }
+                    ),
+                    "request_id": "1234567890",
+                    "headers": MockResponseDict(
+                        {
+                            "content-length": "123",
+                        }
+                    ),
+                }
+            )
+        return response
+
+    monkeypatch.setattr(llm.client, "chat", mocked_response)
+
+    messages = [
+        HumanMessage(content="User message"),
+    ]
+
+    expected = "Assistant chat reply."
+    actual = llm.invoke(messages, temperature=0.2)
+    assert actual.content == expected

libs/community/tests/unit_tests/llms/test_oci_generative_ai.py

@@ -4,7 +4,7 @@ from unittest.mock import MagicMock
 import pytest
 from pytest import MonkeyPatch
 
-from langchain_community.llms import OCIGenAI
+from langchain_community.llms.oci_generative_ai import OCIGenAI
 
 
 class MockResponseDict(dict):
@@ -16,12 +16,12 @@ class MockResponseDict(dict):
 @pytest.mark.parametrize(
     "test_model_id", ["cohere.command", "cohere.command-light", "meta.llama-2-70b-chat"]
 )
-def test_llm_call(monkeypatch: MonkeyPatch, test_model_id: str) -> None:
-    """Test valid call to OCI Generative AI LLM service."""
+def test_llm_complete(monkeypatch: MonkeyPatch, test_model_id: str) -> None:
+    """Test valid completion call to OCI Generative AI LLM service."""
     oci_gen_ai_client = MagicMock()
     llm = OCIGenAI(model_id=test_model_id, client=oci_gen_ai_client)
 
-    provider = llm._get_provider()
+    provider = llm.model_id.split(".")[0].lower()
 
     def mocked_response(*args):  # type: ignore[no-untyped-def]
         response_text = "This is the completion."
@@ -71,6 +71,5 @@ def test_llm_call(monkeypatch: MonkeyPatch, test_model_id: str) -> None:
             )
 
     monkeypatch.setattr(llm.client, "generate_text", mocked_response)
-
     output = llm.invoke("This is a prompt.", temperature=0.2)
     assert output == "This is the completion."