OpenShift follow-up for NVBug 6218358

docs/docs/extraction/deployment-options.md

@@ -22,16 +22,9 @@ Build and run the NeMo Retriever service image with the [Docker service image gu
 3. **Published Library Helm charts (supported):** cluster install and upgrade procedures are covered in the [NeMo Retriever Library](https://docs.nvidia.com/nemo/retriever/latest/extraction/overview/) — use alongside the NeMo Retriever chart README for your release
 4. [Environment variables](environment-config.md) and [Troubleshoot](troubleshoot.md) as needed
 
-**Core NIMs for the default extraction pipeline** (26.05): `page_elements`, `table_structure`, `ocr`, and `vlm_embed` (`llama-nemotron-embed-vl-1b-v2:1.12.0`). These four are auto-wired into the retriever service. **Nemotron Parse**, **Nemotron 3 Nano Omni**, the **VL reranker**, and **Parakeet ASR** are optional and not auto-wired. For a minimal GPU footprint, disable optional keys you do not need (see [Recommended minimal install (26.05)](https://github.com/NVIDIA/NeMo-Retriever/blob/26.05/nemo_retriever/helm/README.md#recommended-minimal-install-2605)). See [Pre-Requisites & Support Matrix — Default Helm NIMs](prerequisites-support-matrix.md#default-helm-nims).
+**Core NIMs for the default extraction pipeline** (26.05): `page_elements`, `table_structure`, `ocr`, and `vlm_embed` (`llama-nemotron-embed-vl-1b-v2:1.12.0`). These four are auto-wired into the retriever service. **Nemotron Parse**, **Nemotron 3 Nano Omni**, the **VL reranker**, and **Parakeet ASR** are optional and not auto-wired. For a minimal GPU footprint, disable optional keys you do not need (refer to [Recommended minimal install (26.05)](https://github.com/NVIDIA/NeMo-Retriever/blob/26.05/nemo_retriever/helm/README.md#recommended-minimal-install-2605)). Refer to [Pre-Requisites & Support Matrix — Default Helm NIMs](prerequisites-support-matrix.md#default-helm-nims).
 
-
-For audio and video extraction in Kubernetes, set `service.installFfmpeg=true`
-so the service container installs `ffmpeg` and `ffprobe` at startup. This
-runtime install requires package-repository network egress, a writable root
-filesystem, and security policy that allows the image's scoped sudo use. If
-your cluster blocks startup package installation (for example air-gapped
-environments), use a custom service image that already contains `ffmpeg` and
-`ffprobe`, then set `service.image.repository` and `service.image.tag`.
+For audio and video dependencies and OpenShift-specific Helm configuration, refer to [Audio and video (Parakeet ASR)](https://github.com/NVIDIA/NeMo-Retriever/blob/main/nemo_retriever/helm/README.md#audio-video-parakeet) and [OpenShift deployment](https://github.com/NVIDIA/NeMo-Retriever/blob/main/nemo_retriever/helm/openshift.md) in the Helm chart directory.
 
 ### I want examples and notebooks
 

docs/docs/extraction/prerequisites-support-matrix.md

@@ -11,8 +11,7 @@ Before you begin using [NeMo Retriever Library](overview.md), confirm your softw
 - For audio and video, `ffmpeg` and `ffprobe` must be on `PATH` (for example
   `sudo apt-get install -y --no-install-recommends ffmpeg` on Debian/Ubuntu).
   `ffmpeg-python` and `nemo-retriever[multimedia]` do not install these binaries.
-  On Helm with package-repo access, set `service.installFfmpeg=true`. For
-  air-gapped clusters, see [Air-gapped and disconnected deployment](deployment-options.md#air-gapped-deployment).
+  For container and Kubernetes guidance, refer to [Audio and video](audio-video.md).
 - For PDF extraction with `extract_method="nemotron_parse"`, install the Nemotron Parse
   client dependencies with `pip install "nemo-retriever[nemotron-parse]"` (pulls
   `open-clip-torch`, which provides the `open_clip` module required by the Nemotron Parse
@@ -72,20 +71,20 @@ The production Helm chart enables these NIM microservices **by default** (for ex
 |-----------|-----|------|
 | `page_elements` | [nemotron-page-elements-v3](https://huggingface.co/nvidia/nemotron-page-elements-v3) | Page layout and element detection |
 | `table_structure` | [nemotron-table-structure-v1](https://huggingface.co/nvidia/nemotron-table-structure-v1) | Table structure extraction |
-| `ocr` | [nemotron-ocr-v1](https://huggingface.co/nvidia/nemotron-ocr-v1) | Image OCR |
+| `ocr` | [nemotron-ocr-v2](https://huggingface.co/nvidia/nemotron-ocr-v2) | Image OCR |
 | `vlm_embed` | [llama-nemotron-embed-vl-1b-v2](https://huggingface.co/nvidia/llama-nemotron-embed-vl-1b-v2) | Multimodal (VL) embedding |
 
 ### OCR artifacts (Helm vs local Hugging Face) { #nemotron-ocr-v2-language-mode }
 
 !!! note
 
-    **Helm / NIM:** The production chart deploys **Nemotron OCR v1** under `nimOperator.ocr` (`nvcr.io/nim/nvidia/nemotron-ocr-v1:1.3.0`). For image defaults and upgrade notes, see [OCR NIM configuration](https://github.com/NVIDIA/NeMo-Retriever/blob/26.05/nemo_retriever/helm/README.md#ocr-nim-configuration) in the Helm chart README.
+    **Helm / NIM:** The production chart deploys **Nemotron OCR v2** under `nimOperator.ocr` (`nvcr.io/nim/nvidia/nemotron-ocr-v2:1.4.0`). For image defaults and upgrade notes, refer to [OCR NIM configuration](https://github.com/NVIDIA/NeMo-Retriever/blob/main/nemo_retriever/helm/README.md#ocr-nim-configuration) in the Helm chart README.
 
-    **Local Hugging Face inference:** When you deploy locally with HuggingFace model weights (for example `pip install "nemo-retriever[local]"` and GPU inference without remote OCR NIM URLs), the default OCR engine is **Nemotron OCR v2**, which runs in **multilingual** mode by default. For CLI flags and API parameters, see [Nemotron OCR v2 — language mode](https://github.com/NVIDIA/NeMo-Retriever/blob/main/nemo_retriever/docs/cli/README.md#nemotron-ocr-v2-language-mode). Remote OCR NIM endpoints use their own model and language behavior; local OCR language selectors are not sent on remote requests.
+    **Local Hugging Face inference:** When you deploy locally with HuggingFace model weights (for example `pip install "nemo-retriever[local]"` and GPU inference without remote OCR NIM URLs), the default OCR engine is **Nemotron OCR v2**, which runs in **multilingual** mode by default. For CLI flags and API parameters, refer to [Nemotron OCR v2 — language mode](https://github.com/NVIDIA/NeMo-Retriever/blob/main/nemo_retriever/docs/cli/README.md#nemotron-ocr-v2-language-mode). Remote OCR NIM endpoints use their own model and language behavior; local OCR language selectors are not sent on remote requests.
 
 Default OCR NIM container for release Helm deployments:
 
-- **Image:** `nvcr.io/nim/nvidia/nemotron-ocr-v1:1.3.0`
+- **Image:** `nvcr.io/nim/nvidia/nemotron-ocr-v2:1.4.0`
 
 Default VL embedder container and model for release deployments:
 
@@ -94,7 +93,7 @@ Default VL embedder container and model for release deployments:
 
 ### Optional Helm NIMs (not auto-wired) { #optional-helm-nims-not-auto-wired-by-default }
 
-These NIM microservices are **optional** for the default extraction pipeline. The retriever service does **not** call them until you enable the matching pipeline stage (reranker, Nemotron Parse, caption, or audio). For **26.05 production**, disable keys you do not need (see [Recommended minimal install (26.05)](https://github.com/NVIDIA/NeMo-Retriever/blob/26.05/nemo_retriever/helm/README.md#recommended-minimal-install-2605)). Set `nimOperator.<key>.enabled=true` when you want that NIM reconciled. Chart keys are in the [NeMo Retriever Helm chart README](https://github.com/NVIDIA/NeMo-Retriever/blob/26.05/nemo_retriever/helm/README.md#nim-operator-sub-stack).
+These NIM microservices are **optional** for the default extraction pipeline. The retriever service does **not** call them until you enable the matching pipeline stage (reranker, Nemotron Parse, caption, or audio). For **26.05 production**, disable keys you do not need (refer to [Recommended minimal install (26.05)](https://github.com/NVIDIA/NeMo-Retriever/blob/26.05/nemo_retriever/helm/README.md#recommended-minimal-install-2605)). Set `nimOperator.<key>.enabled=true` when you want that NIM reconciled. Chart keys are in the [NeMo Retriever Helm chart README](https://github.com/NVIDIA/NeMo-Retriever/blob/26.05/nemo_retriever/helm/README.md#nim-operator-sub-stack).
 
 | Helm flag | NIM | Role |
 |-----------|-----|------|
@@ -127,7 +126,7 @@ For published NIM model IDs and deployment-specific constraints, use the product
 NeMo Retriever Library supports the following GPU hardware given system constraints in the table.
 
 - **HF model weights** — approximate Hugging Face checkpoint footprint (files such as `model*.safetensors`, `weights.pth`, or other published weight bundles in the model repository). Values are rounded from the current public file listing and can change when the repository is updated.
-- **NIM disk space** — approximate container and on-disk model cache for self-hosted NIM microservices (not the same as HF download size). For Nemotron 3 Nano Omni captioning, see the [NVIDIA NIM for Vision Language Models support matrix](https://docs.nvidia.com/nim/vision-language-models/latest/support-matrix.html#nemotron-3-nano-omni-30b-a3b-reasoning).
+- **NIM disk space** — approximate container and on-disk model cache for self-hosted NIM microservices (not the same as HF download size). For Nemotron 3 Nano Omni captioning, refer to the [NVIDIA NIM for Vision Language Models support matrix](https://docs.nvidia.com/nim/vision-language-models/latest/support-matrix.html#nemotron-3-nano-omni-30b-a3b-reasoning).
 
 Model repositories and NIM references are linked in [Core and Advanced Pipeline Features](#core-and-advanced-pipeline-features) above.
 

docs/mkdocs.yml

@@ -84,6 +84,7 @@ nav:
       - "Authentication and API keys": extraction/api-keys.md
   - "3. Deployment options":
       - "Compare deployment options": extraction/deployment-options.md
+      - "OpenShift deployment (Helm)": https://github.com/NVIDIA/NeMo-Retriever/blob/main/nemo_retriever/helm/openshift.md
       - "Helm chart (Kubernetes)": https://github.com/NVIDIA/NeMo-Retriever/tree/main/nemo_retriever/helm
       - "Docker service image": https://github.com/NVIDIA/NeMo-Retriever/blob/main/nemo_retriever/docker.md
   - "4. Core workflows":