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chore: Regenerate all playbooks

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2
nvidia/txt2kg/README.md
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@ -70,7 +70,7 @@ In a terminal, clone the txt2kg repository and navigate to the project directory
```bash
git clone https://github.com/NVIDIA/dgx-spark-playbooks
cd dgx-spark-playbook/nvidia/txt2kg/assets
cd dgx-spark-playbooks/nvidia/txt2kg/assets
```
## Step 2. Start the txt2kg services

95
nvidia/vss/README.md
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@ -30,11 +30,12 @@ You will deploy NVIDIA's VSS AI Blueprint on NVIDIA Spark hardware with Blackwel
## Prerequisites
- NVIDIA Spark device with ARM64 architecture and Blackwell GPU
- NVIDIA DGX OS 7.2.3 or higher
- Driver version 580.95.05 or higher installed: `nvidia-smi | grep "Driver Version"`
- DGX OS (suggested: 7.4.0 or higher)
- Driver version 580.126.09 or higher installed: `nvidia-smi | grep "Driver Version"`
- CUDA version 13.0 installed: `nvcc --version`
- Docker installed and running: `docker --version && docker compose version`
- Access to NVIDIA Container Registry with [NGC API Key](https://org.ngc.nvidia.com/setup/api-keys)
- NVIDIA Container Toolkit
- [Optional] NVIDIA API Key for remote model endpoints (hybrid deployment only)
- Sufficient storage space for video processing (>10GB recommended in `/tmp/`)
@ -52,9 +53,9 @@ You will deploy NVIDIA's VSS AI Blueprint on NVIDIA Spark hardware with Blackwel
* Network configuration conflicts if shared network already exists
* Remote API endpoints may have rate limits or connectivity issues (hybrid deployment)
* **Rollback:** Stop all containers with `docker compose down`, remove shared network with `docker network rm vss-shared-network`, and clean up temporary media directories.
* **Last Updated:** 10/18/2025
* **Last Updated:** 1/21/2026
* Update required OS and Driver versions
* Add instructions to fully local VSS deployment
* Support for VSS 2.4.1 with Cosmos Reason 2 VLM
## Instructions
@ -65,7 +66,7 @@ Check that your system meets the hardware and software prerequisites.
```bash
## Verify driver version
nvidia-smi | grep "Driver Version"
## Expected output: Driver Version: 580.82.09 or higher
## Expected output: Driver Version: 580.126.09 or higher
## Verify CUDA version
nvcc --version
@ -152,10 +153,10 @@ docker login nvcr.io
Choose between two deployment options based on your requirements:
| Deployment Scenario | VLM (Cosmos-Reason1-7B) | LLM (Llama 3.1 70B) | Embedding/Reranker | CV Pipeline |
|----------------------|--------------------------|---------------------|--------------------|-------------|
| VSS Event Reviewer | Local | Not Used | Not Used | Local |
| Standard VSS (Hybrid)| Local | Remote | Remote | Optional |
| Deployment Scenario | VLM (Cosmos-Reason2-8B)| LLM (Llama 3.1) | Embedding / Reranker | CV Pipeline |
|---------------------- |------------------------|-------------------------------|----------------------|--------------|
| VSS Event Reviewer | Local | Not Used | Not Used | Local |
| Standard VSS | Local | Remote (70B) or Local (8B) | Remote / Local | Optional |
Proceed with **Option A** for Event Reviewer or **Option B** for Standard VSS.
@ -171,22 +172,25 @@ Change to the directory containing the Event Reviewer Docker Compose configurati
cd deploy/docker/event_reviewer/
```
**8.2 Configure NGC API Key**
**8.2 Configure NGC API Key and HF Token**
Update the environment file with your NGC API Key. You can do this by editing the `.env` file directly, or by running the following command:
Update the environment file with your NGC API Key and HF Token. You can do this by editing the `.env` file directly, or by running the following commands:
> [!NOTE]
> To deploy the default VLM (**Cosmos-Reason2 8B**) from Hugging Face, you must accept the model’s terms and conditions on the Hugging Face model page before downloads will work.
```bash
## Edit the .env file and update NGC_API_KEY
echo "NGC_API_KEY=<YOUR_NGC_API_KEY>" >> .env
echo "HF_TOKEN=<YOUR_HF_TOKEN>" >> .env # To download Cosmos-Reason2-8B VLM
```
**8.3 Update the VSS Image path**
**8.3 (Optional) Remove the VST volume data**
Update `VSS_IMAGE` to `nvcr.io/nvidia/blueprint/vss-engine-sbsa:2.4.0` in `.env`.
When upgrading from older versions of VSS, remove the VST volume data
```bash
## Edit the .env file and update VSS_IMAGE
echo "VSS_IMAGE=nvcr.io/nvidia/blueprint/vss-engine-sbsa:2.4.0" >> .env
rm -rf vst/vst_volume/*
```
**8.4 Start VSS Event Reviewer services**
@ -194,8 +198,11 @@ echo "VSS_IMAGE=nvcr.io/nvidia/blueprint/vss-engine-sbsa:2.4.0" >> .env
Launch the complete VSS Event Reviewer stack including Alert Bridge, VLM Pipeline, Alert Inspector UI, and Video Storage Toolkit.
```bash
## DGX Spark tuning: improves Q&A responsiveness/behavior for the Event Reviewer workflow
export VLM_DEFAULT_NUM_FRAMES_PER_CHUNK=8
## Start VSS Event Reviewer with ARM64 and SBSA optimizations
IS_SBSA=1 IS_AARCH64=1 ALERT_REVIEW_MEDIA_BASE_DIR=/tmp/alert-media-dir docker compose up
IS_SBSA=1 ALERT_REVIEW_MEDIA_BASE_DIR=/tmp/alert-media-dir docker compose up
```
> [!NOTE]
@ -209,44 +216,35 @@ In a new terminal session, navigate to the computer vision event detector config
cd video-search-and-summarization/examples/cv-event-detector
```
**8.6 Update the NV_CV_EVENT_DETECTOR_IMAGE Image path**
Update `NV_CV_EVENT_DETECTOR_IMAGE` to `nvcr.io/nvidia/blueprint/nv-cv-event-detector-sbsa:2.4.0` in `.env`.
```bash
## Edit the .env file and update NV_CV_EVENT_DETECTOR_IMAGE
echo "NV_CV_EVENT_DETECTOR_IMAGE=nvcr.io/nvidia/blueprint/nv-cv-event-detector-sbsa:2.4.0" >> .env
```
**8.7 Start DeepStream CV pipeline**
**8.6 Start DeepStream CV pipeline**
Launch the DeepStream computer vision pipeline and CV UI services.
```bash
## Start CV pipeline with ARM64 and SBSA optimizations
IS_SBSA=1 IS_AARCH64=1 ALERT_REVIEW_MEDIA_BASE_DIR=/tmp/alert-media-dir docker compose up
IS_SBSA=1 ALERT_REVIEW_MEDIA_BASE_DIR=/tmp/alert-media-dir docker compose up
```
**8.8 Wait for service initialization**
**8.7 Wait for service initialization**
Allow time for all containers to fully initialize before accessing the user interfaces.
```bash
## Monitor container status
docker ps
## Verify all containers show "Up" status and VSS backend logs (vss-engine-sbsa:2.4.0) show ready state "Uvicorn running on http://0.0.0.0:7860"
## Verify all containers show "Up" status and VSS backend logs (vss-engine:2.4.1-sbsa) show ready state "Uvicorn running on http://0.0.0.0:7860"
## In total, there should be 8 containers:
## nvcr.io/nvidia/blueprint/nv-cv-event-detector-ui:2.4.0
## nvcr.io/nvidia/blueprint/nv-cv-event-detector-sbsa:2.4.0
## nvcr.io/nvidia/blueprint/nv-cv-event-detector-ui:2.4.1
## nvcr.io/nvidia/blueprint/nv-cv-event-detector:2.4.0-sbsa
## nginx:alpine
## nvcr.io/nvidia/blueprint/vss-alert-inspector-ui:2.4.0
## nvcr.io/nvidia/blueprint/vss-alert-inspector-ui:2.4.1
## nvcr.io/nvidia/blueprint/alert-bridge:0.19.0-multiarch
## nvcr.io/nvidia/blueprint/vss-engine-sbsa:2.4.0
## nvcr.io/nvidia/blueprint/vst-storage:2.1.0-25.07.1
## nvcr.io/nvidia/blueprint/vss-engine:2.4.1-sbsa
## nvcr.io/nvidia/blueprint/vst-storage:2.1.0-25.11.1.1
## redis/redis-stack-server:7.2.0-v9
```
**8.9 Validate Event Reviewer deployment**
**8.8 Validate Event Reviewer deployment**
Access the web interfaces to confirm successful deployment and functionality.
@ -300,24 +298,19 @@ cd deploy/docker/remote_llm_deployment/
Update the environment file with your API keys and deployment preferences. You can do this by editing the `.env` file directly, or by running the following commands:
> [!NOTE]
> To deploy the default VLM (**Cosmos-Reason2 8B**) from Hugging Face, you must accept the model’s terms and conditions on the Hugging Face model page before downloads will work.
```bash
## Edit .env file with required keys
echo "NVIDIA_API_KEY=<YOUR_NVIDIA_API_KEY>" >> .env
echo "NGC_API_KEY=<YOUR_NGC_API_KEY>" >> .env
echo "HF_TOKEN=<YOUR_HF_TOKEN>" >> .env # To download Cosmos-Reason2-8B VLM
echo "DISABLE_CV_PIPELINE=true" >> .env # Set to false to enable CV
echo "INSTALL_PROPRIETARY_CODECS=false" >> .env # Set to true to enable CV
```
**9.4 Update the VSS Image path**
Update `VIA_IMAGE` to `nvcr.io/nvidia/blueprint/vss-engine-sbsa:2.4.0` in `.env`.
```bash
## Edit the .env file and update VIA_IMAGE
echo "VIA_IMAGE=nvcr.io/nvidia/blueprint/vss-engine-sbsa:2.4.0" >> .env
```
**9.5 Review model configuration**
**9.4 Review model configuration**
Verify that the config.yaml file contains the correct remote endpoints. For NIMs, it should be set to `https://integrate.api.nvidia.com/v1 `.
@ -326,11 +319,11 @@ Verify that the config.yaml file contains the correct remote endpoints. For NIMs
cat config.yaml | grep -A 10 "model"
```
**9.6 Launch Standard VSS deployment**
**9.5 Launch Standard VSS deployment**
```bash
## Start Standard VSS with hybrid deployment
docker compose up
IS_SBSA=1 docker compose up
```
> [!NOTE]
@ -383,13 +376,13 @@ To completely remove the VSS deployment and free up system resources:
```bash
## For Event Reviewer deployment
cd deploy/docker/event_reviewer/
IS_SBSA=1 IS_AARCH64=1 ALERT_REVIEW_MEDIA_BASE_DIR=/tmp/alert-media-dir docker compose down
IS_SBSA=1 ALERT_REVIEW_MEDIA_BASE_DIR=/tmp/alert-media-dir docker compose down
cd ../../examples/cv-event-detector/
IS_SBSA=1 IS_AARCH64=1 ALERT_REVIEW_MEDIA_BASE_DIR=/tmp/alert-media-dir docker compose down
IS_SBSA=1 ALERT_REVIEW_MEDIA_BASE_DIR=/tmp/alert-media-dir docker compose down
## For Standard VSS deployment
cd deploy/docker/remote_llm_deployment/
docker compose down
IS_SBSA=1 docker compose down
## Remove shared network (if using Event Reviewer)
docker network rm vss-shared-network
@ -421,7 +414,7 @@ With VSS deployed, you can now:
|---------|--------|-----|
| Container fails to start with "pull access denied" | Missing or incorrect nvcr.io credentials | Re-run `docker login nvcr.io` with valid credentials |
| Network creation fails | Existing network with same name | Run `docker network rm vss-shared-network` then recreate |
| Services fail to communicate | Incorrect environment variables | Verify `IS_SBSA=1 IS_AARCH64=1` are set correctly |
| Services fail to communicate | Incorrect environment variables | Verify `IS_SBSA=1` are set correctly |
| Web interfaces not accessible | Services still starting or port conflicts | Wait 2-3 minutes, check `docker ps` for container status |
> [!NOTE]