Add OCI LangChain support for hosted Nemotron workflows

ci/markdown-link-check-config.json

@@ -23,6 +23,9 @@
         },
         {
             "pattern": "^https://docs\\.cursor\\.com"
+        },
+        {
+            "pattern": "^https://docs\\.docker\\.com"
         }
     ]
 }

docs/source/build-workflows/llms/index.md

@@ -28,6 +28,7 @@ NVIDIA NeMo Agent Toolkit supports the following LLM providers:
 | [OpenAI](https://openai.com) | `openai` | OpenAI API |
 | [AWS Bedrock](https://aws.amazon.com/bedrock/) | `aws_bedrock` | AWS Bedrock API |
 | [Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/quickstart) | `azure_openai` | Azure OpenAI API |
+| [OCI Generative AI](https://docs.oracle.com/en-us/iaas/Content/generative-ai/home.htm) | `oci` | OCI Generative AI |
 | [LiteLLM](https://github.com/BerriAI/litellm) | `litellm` | LiteLLM API |
 | [Hugging Face](https://huggingface.co) | `huggingface` | Hugging Face API |
 | [Hugging Face Inference](https://huggingface.co/docs/api-inference) | `huggingface_inference` | Hugging Face Inference API, Endpoints, and TGI |
@@ -52,6 +53,15 @@ llms:
   azure_openai_llm:
     _type: azure_openai
     azure_deployment: gpt-4o-mini
+  oci_llm:
+    _type: oci
+    model_name: nvidia/Llama-3.1-Nemotron-Nano-8B-v1
+    region: us-chicago-1
+    compartment_id: ocid1.compartment.oc1..example
+    auth_type: API_KEY
+    auth_profile: DEFAULT
+    auth_file_location: ~/.oci/config
+    provider: meta
   litellm_llm:
     _type: litellm
     model_name: gpt-4o
@@ -118,6 +128,39 @@ The AWS Bedrock LLM provider is defined by the {py:class}`~nat.llm.aws_bedrock_l
 * `credentials_profile_name` - The credentials profile name to use for the model
 * `max_retries` - The maximum number of retries for the request
 
+### OCI Generative AI
+
+You can use the following fields to configure the OCI Generative AI LLM provider:
+
+* `region` - OCI region for the Generative AI service (defaults to `us-chicago-1`). The service endpoint is derived automatically.
+* `endpoint` - Optional explicit endpoint URL. Overrides the region-derived endpoint when set.
+* `compartment_id` - The OCI compartment OCID used for inference requests
+* `auth_type` - OCI SDK auth mode such as `API_KEY`, `SECURITY_TOKEN`, `INSTANCE_PRINCIPAL`, or `RESOURCE_PRINCIPAL`
+* `auth_profile` - OCI config profile name for file-backed auth
+* `auth_file_location` - Path to the OCI config file
+* `provider` - Optional provider override such as `meta`, `google`, `cohere`, or `openai`
+
+The OCI Generative AI LLM provider is defined by the {py:class}`~nat.llm.oci_llm.OCIModelConfig` class.
+
+* `model_name` - The name of the model to use
+* `region` - OCI region (defaults to `us-chicago-1`). The endpoint is derived from `https://inference.generativeai.{region}.oci.oraclecloud.com`.
+* `endpoint` - Optional explicit endpoint URL. Overrides the region-derived endpoint.
+* `compartment_id` - OCI compartment OCID
+* `auth_type` - OCI SDK auth type
+* `auth_profile` - OCI profile name for file-backed auth
+* `auth_file_location` - Path to the OCI config file
+* `provider` - Optional OCI provider override such as `meta`, `google`, `cohere`, or `openai`
+* `temperature` - The temperature to use for the model
+* `top_p` - The top-p value to use for the model
+* `max_tokens` - The maximum number of tokens to generate
+* `seed` - The seed to use for the model
+* `max_retries` - The maximum number of retries for the request
+* `request_timeout` - HTTP request timeout in seconds
+
+:::{note}
+This provider targets OCI Generative AI through the OCI SDK-backed `langchain-oci` path and does not enable the Responses API.
+:::
+
 ### Azure OpenAI
 
 You can use the following environment variables to configure the Azure OpenAI LLM provider:

docs/source/components/integrations/index.md

@@ -23,4 +23,5 @@ limitations under the License.
 ./frameworks.md
 ./a2a.md
 AWS Bedrock <./integrating-aws-bedrock-models.md>
-```
+OCI Generative AI <./integrating-oci-generative-ai-models.md>
+```

docs/source/components/integrations/integrating-oci-generative-ai-models.md

@@ -0,0 +1,99 @@
+<!--
+SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+SPDX-License-Identifier: Apache-2.0
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+-->
+
+# NVIDIA NeMo Agent Toolkit OCI Integration
+
+The NeMo Agent Toolkit supports integration with multiple [LLM](../../build-workflows/llms/index.md) providers, including OCI Generative AI. The `oci` provider uses OCI SDK authentication and is designed for OCI Generative AI model and endpoint access. For workflow parity with the AWS Bedrock path, the toolkit also includes a LangChain wrapper built on `langchain-oci`.
+
+To view the full list of supported LLM providers, run `nat info components -t llm_provider`.
+
+## Configuration
+
+### Prerequisites
+Before integrating OCI, ensure you have:
+
+- access to OCI Generative AI in the target region
+- a valid OCI auth method such as `API_KEY`, `SECURITY_TOKEN`, `INSTANCE_PRINCIPAL`, or `RESOURCE_PRINCIPAL`
+- the target compartment OCID
+- the target OCI region (defaults to `us-chicago-1`) or a custom endpoint URL
+
+Common deployment patterns include:
+
+- OCI Generative AI regional endpoints
+- custom OCI Generative AI endpoints
+- OCI-hosted inference for NVIDIA Nemotron used as a live integration target
+
+### Example Configuration
+Add the OCI LLM configuration to your workflow config file:
+
+```yaml
+llms:
+  oci_llm:
+    _type: oci
+    model_name: nvidia/Llama-3.1-Nemotron-Nano-8B-v1
+    region: us-chicago-1
+    compartment_id: ocid1.compartment.oc1..example
+    auth_type: API_KEY
+    auth_profile: DEFAULT
+    temperature: 0.0
+    max_tokens: 1024
+    top_p: 1.0
+    request_timeout: 60
+```
+
+### Configurable Options
+* `model_name`: The name of the OCI-hosted model to use (required)
+* `region`: OCI region for the Generative AI service (defaults to `us-chicago-1`). The service endpoint is derived automatically.
+* `endpoint`: Optional explicit service endpoint URL. Overrides the region-derived endpoint when set.
+* `compartment_id`: OCI compartment OCID
+* `auth_type`: OCI SDK auth type
+* `auth_profile`: OCI profile name for file-backed auth
+* `auth_file_location`: Path to the OCI config file
+* `provider`: Optional OCI provider override such as `meta`, `google`, `cohere`, or `openai`
+* `temperature`: Controls randomness in the output (0.0 to 1.0)
+* `max_tokens`: Maximum number of tokens to generate
+* `top_p`: Top-p sampling parameter (0.0 to 1.0)
+* `seed`: Optional random seed
+* `max_retries`: Maximum number of retries for the request
+* `request_timeout`: HTTP request timeout in seconds
+
+### Limitations
+* This provider targets OCI Generative AI through the OCI SDK-backed `langchain-oci` path.
+* The Responses API is not enabled for this provider in the current release.
+
+## Nemotron On OCI
+
+One strong OCI deployment pattern is NVIDIA Nemotron hosted on OCI and exposed through an OpenAI-compatible route. In that setup, the toolkit can validate live integration behavior against the OCI-hosted Nemotron endpoint while the official provider and LangChain wrapper cover the OCI Generative AI path.
+
+## Usage
+Reference the OCI LLM in your configuration:
+
+```yaml
+llms:
+  oci_llm:
+    _type: oci
+    model_name: nvidia/Llama-3.1-Nemotron-Nano-8B-v1
+    region: us-chicago-1
+    compartment_id: ocid1.compartment.oc1..example
+    auth_profile: DEFAULT
+```
+
+## Troubleshooting
+* `401 Unauthorized`: verify the OCI profile, signer, and IAM permissions for Generative AI.
+* `404 Not Found`: confirm the regional endpoint or custom endpoint URL is correct.
+* `Connection errors`: verify OCI networking and that the regional endpoint is reachable.
+* `Tool calling issues`: verify the served model supports tool calling and that the serving stack is configured for it.

docs/source/conf.py

@@ -379,6 +379,8 @@ def _build_api_tree() -> Path:
         '/extend/custom-components/gated-fields.html',
     'extend/integrating-aws-bedrock-models':
         '/components/integrations/integrating-aws-bedrock-models.html',
+    'extend/integrating-oci-generative-ai-models':
+        '/components/integrations/integrating-oci-generative-ai-models.html',
     'extend/memory':
         '/extend/custom-components/memory.html',
     'extend/object-store':

docs/source/get-started/installation.md

@@ -27,6 +27,7 @@ The following [LLM](../build-workflows/llms/index.md) API providers are supporte
 - OpenAI
 - AWS Bedrock
 - Azure OpenAI
+- OCI Generative AI
 
 ## Packages