Align VLM caption model and MinIO defaults with runtime

docs/docs/extraction/nv-ingest-python-api.md

@@ -372,7 +372,7 @@ You can use this to generate descriptions of unstructured images, infographics,
 
 !!! note
 
-    To use the `caption` option, enable the `vlm` profile when you start the NeMo Retriever Library services. The default model used by `caption` is `nvidia/llama-3.1-nemotron-nano-vl-8b-v1`. For more information, refer to [Profile Information in the Quickstart Guide](quickstart-guide.md#profile-information).
+    To use the `caption` option, enable the `vlm` profile when you start the NeMo Retriever Library services. The default model used by `caption` is `nvidia/nemotron-nano-12b-v2-vl`. For more information, refer to [Profile Information in the Quickstart Guide](quickstart-guide.md#profile-information).
 
 ### Basic Usage
 
@@ -389,7 +389,7 @@ To specify a different API endpoint, pass additional parameters to `caption`.
 ```python
 ingestor = ingestor.caption(
     endpoint_url="https://integrate.api.nvidia.com/v1/chat/completions",
-    model_name="nvidia/llama-3.1-nemotron-nano-vl-8b-v1",
+    model_name="nvidia/nemotron-nano-12b-v2-vl",
     api_key="nvapi-"
 )
 ```

docs/docs/extraction/python-api-reference.md

@@ -464,7 +464,7 @@ You can use this to generate descriptions of unstructured images, infographics,
 
 !!! note
 
-    To use the `caption` option, enable the `vlm` profile when you start the NeMo Retriever Library services. The default model used by `caption` is `nvidia/llama-3.1-nemotron-nano-vl-8b-v1`. For more information, refer to [Profile Information in the Quickstart Guide](quickstart-guide.md#profile-information).
+    To use the `caption` option, enable the `vlm` profile when you start the NeMo Retriever Library services. The default model used by `caption` is `nvidia/nemotron-nano-12b-v2-vl`. For more information, refer to [Profile Information in the Quickstart Guide](quickstart-guide.md#profile-information).
 
 ### Basic Usage
 
@@ -481,7 +481,7 @@ To specify a different API endpoint, pass additional parameters to `caption`.
 ```python
 ingestor = ingestor.caption(
     endpoint_url="https://integrate.api.nvidia.com/v1/chat/completions",
-    model_name="nvidia/llama-3.1-nemotron-nano-vl-8b-v1",
+    model_name="nvidia/nemotron-nano-12b-v2-vl",
     api_key="nvapi-"
 )
 ```
@@ -570,11 +570,11 @@ The `store` task uses [fsspec](https://filesystem-spec.readthedocs.io/) for stor
 | Amazon S3 | `s3://` | `s3://my-bucket/extracted-images` |
 | Google Cloud Storage | `gs://` | `gs://my-bucket/images` |
 | Azure Blob Storage | `abfs://` | `abfs://container@account.dfs.core.windows.net/images` |
-| MinIO (S3-compatible) | `s3://` | `s3://nemo-retriever/artifacts/store/images` (default) |
+| MinIO (S3-compatible) | `s3://` | `s3://nv-ingest/artifacts/store/images` (default) |
 
 !!! tip
 
-    `storage_uri` defaults to the server-side `IMAGE_STORAGE_URI` environment variable (commonly `s3://nemo-retriever/...`). If you change that variable—for example to a host-mounted `file://` path—restart the NeMo Retriever Library runtime so the container picks up the new value.
+    `storage_uri` defaults to the server-side `IMAGE_STORAGE_URI` environment variable (commonly `s3://nv-ingest/...`). If you change that variable—for example to a host-mounted `file://` path—restart the NeMo Retriever Library runtime so the container picks up the new value.
 
 When `public_base_url` is provided, the metadata returned from `ingest()` surfaces that HTTP(S) link while still recording the underlying storage URI. Leave it unset when the storage endpoint itself is already publicly reachable.
 

docs/docs/extraction/quickstart-guide.md

@@ -395,7 +395,7 @@ You can specify multiple `--profile` options.
 | `retrieval`           | Core     | Enables the embedding NIM and (optional) GPU-accelerated Milvus. Omit this profile to use the default LanceDB backend.           | 
 | `audio`               | Advanced | Use [Riva](https://docs.nvidia.com/deeplearning/riva/user-guide/docs/index.html) for processing audio files. For more information, refer to [Audio Processing](audio.md). | 
 | `nemotron-parse`      | Advanced | Use [nemotron-parse](https://build.nvidia.com/nvidia/nemotron-parse), which adds state-of-the-art text and table extraction. For more information, refer to [Advanced Visual Parsing](nemoretriever-parse.md). | 
-| `vlm`                 | Advanced | Use [llama 3.1 Nemotron 8B Vision](https://build.nvidia.com/nvidia/llama-3.1-nemotron-nano-vl-8b-v1/modelcard) for image captioning of unstructured images and infographics. This profile enables the `caption` method in the Python API to generate text descriptions of visual content. For more information, refer to [Use Multimodal Embedding](vlm-embed.md) and [Extract Captions from Images](nv-ingest-python-api.md#extract-captions-from-images). | 
+| `vlm`                 | Advanced | Use [Nemotron Nano 12B v2 VL](https://build.nvidia.com/nvidia/nemotron-nano-12b-v2-vl/modelcard) for image captioning of unstructured images and infographics. This profile enables the `caption` method in the Python API to generate text descriptions of visual content. For more information, refer to [Use Multimodal Embedding](vlm-embed.md) and [Extract Captions from Images](nv-ingest-python-api.md#extract-captions-from-images). | 
 
 ### Example: Using the VLM Profile for Infographic Captioning