# Multimodal LoRA Deployment with MinIO on Kubernetes

This guide explains how to deploy multimodal (vision-language) LoRA-enabled vLLM inference with S3-compatible storage backend on Kubernetes.

## Overview

This deployment pattern enables dynamic LoRA adapter loading from S3-compatible storage (MinIO) for vision-language models in a Kubernetes environment. It uses the aggregated single-worker architecture where the Rust OpenAIPreprocessor in the Frontend handles image URLs directly.

## Prerequisites

- Kubernetes cluster with GPU support
- Helm 3.x installed
- `kubectl` configured to access your cluster
- Dynamo Kubernetes Platform installed ([Installation Guide](../../../../../../docs/kubernetes/installation-guide.md))
- HuggingFace token for downloading base and LoRA adapters

## Files in This Directory

| File | Description |
|------|-------------|
| `agg_qwen_lora.yaml` | DynamoGraphDeployment for multimodal vLLM with LoRA support |
| `minio-secret.yaml` | Kubernetes secret for MinIO credentials |
| `sync-lora-job.yaml` | Job to download LoRA from HuggingFace and upload to MinIO |
| `lora-model.yaml` | DynamoModel CRD for registering LoRA adapters |

---

## Step 1: Set Up Environment Variables

```bash
export NAMESPACE=dynamo  # Your Dynamo namespace
export HF_TOKEN=your_hf_token  # Your HuggingFace token
```

---

## Step 2: Create Secrets

### Create HuggingFace Token Secret

```bash
kubectl create secret generic hf-token-secret \
  --from-literal=HF_TOKEN=${HF_TOKEN} \
  -n ${NAMESPACE}
```

### Create MinIO Credentials Secret

In this example, we are using the default credentials for MinIO.
You can change the credentials to point to your own S3-compatible storage.

```bash
kubectl apply -f minio-secret.yaml -n ${NAMESPACE}
```

---

## Step 3: Install MinIO

### Add MinIO Helm Repository

```bash
helm repo add minio https://charts.min.io/
helm repo update
```

### Deploy MinIO

```bash
helm install minio minio/minio \
  --namespace ${NAMESPACE} \
  --set rootUser=minioadmin \
  --set rootPassword=minioadmin \
  --set mode=standalone \
  --set replicas=1 \
  --set persistence.enabled=true \
  --set persistence.size=10Gi \
  --set resources.requests.memory=512Mi \
  --set service.type=ClusterIP \
  --set consoleService.type=ClusterIP
```

### Verify MinIO Installation

```bash
kubectl get pods -n ${NAMESPACE} | grep minio
kubectl get svc -n ${NAMESPACE} | grep minio
```

Expected output:
```text
minio-xxxx-xxxx   1/1     Running   0          1m
```

### (Optional) Access MinIO Console

```bash
kubectl port-forward svc/minio-console -n ${NAMESPACE} 9001:9001 9000:9000
```

Open http://localhost:9001 in your browser:
- Username: `minioadmin`
- Password: `minioadmin`

---

## Step 4: Upload LoRA Adapters to MinIO

Use the provided Kubernetes Job to download a vision LoRA adapter from HuggingFace and upload it to MinIO:

```bash
kubectl apply -f sync-lora-job.yaml -n ${NAMESPACE}
```

The default job syncs `Chhagan005/Chhagan-DocVL-Qwen3`, a document-understanding LoRA for Qwen3-VL-2B.

### Monitor the Job

```bash
# Watch job progress
kubectl get jobs -n ${NAMESPACE} -w

# Check job logs
kubectl logs job/sync-hf-lora-to-minio -n ${NAMESPACE} -f
```

Wait for the job to complete successfully.

### Verify Upload (Optional)

```bash
# Port-forward MinIO API
kubectl port-forward svc/minio -n ${NAMESPACE} 9000:9000 &

# Check uploaded files
export AWS_ACCESS_KEY_ID=minioadmin
export AWS_SECRET_ACCESS_KEY=minioadmin
export AWS_ENDPOINT_URL=http://localhost:9000
aws s3 ls s3://my-loras/ --recursive
```

### Customizing the LoRA Adapter

To upload a different LoRA adapter, edit `sync-lora-job.yaml` and change the `MODEL_NAME` environment variable:

```yaml
env:
- name: MODEL_NAME
  value: your-org/your-vision-lora-adapter
```

---

## Step 5: Deploy Multimodal vLLM with LoRA Support

### Update the Image (if needed)

Edit `agg_qwen_lora.yaml` to use your container image:

```bash
# Using yq to update the image
export FRAMEWORK_RUNTIME_IMAGE=your-registry/your-image:tag
yq '.spec.services[].extraPodSpec.mainContainer.image = env(FRAMEWORK_RUNTIME_IMAGE)' agg_qwen_lora.yaml > agg_qwen_lora_updated.yaml
```

### Deploy the LoRA-enabled Multimodal Graph

```bash
kubectl apply -f agg_qwen_lora.yaml -n ${NAMESPACE}
```

### Verify Deployment

```bash
# Check pods
kubectl get pods -n ${NAMESPACE}

# Watch worker logs
kubectl logs -f deployment/agg-qwen-multimodal-lora-vllmworker -n ${NAMESPACE}
```

Wait for the worker to show "Application startup complete".

### Test the Deployment

```bash
# Port-forward the frontend
kubectl port-forward svc/agg-qwen-multimodal-lora-frontend -n ${NAMESPACE} 8000:8000 &

# List available models
curl http://localhost:8000/v1/models | jq .
```

---

## Step 6: Using DynamoModel CRD

The `lora-model.yaml` file demonstrates how to register a LoRA adapter using the DynamoModel Custom Resource:

```bash
kubectl apply -f lora-model.yaml -n ${NAMESPACE}
```

This creates a declarative way to manage LoRA adapters in your cluster. The model CRD references:
- **modelName**: `Chhagan005/Chhagan-DocVL-Qwen3` (the adapter identity)
- **baseModelName**: `Qwen/Qwen3-VL-2B-Instruct` (the base VLM)
- **source.uri**: `s3://my-loras/Chhagan005/Chhagan-DocVL-Qwen3` (MinIO location)

---

## Step 7: Run Inference

### Inference with the LoRA Adapter

```bash
curl -X POST http://localhost:8000/v1/chat/completions -H "Content-Type: application/json" \
  -d '{
    "model": "Chhagan005/Chhagan-DocVL-Qwen3",
    "messages": [{"role": "user", "content": [
      {"type": "text", "text": "Describe this image in detail"},
      {"type": "image_url", "image_url": {"url": "https://vllm-public-assets.s3.us-west-2.amazonaws.com/vision_model_images/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"}}
    ]}],
    "max_tokens": 300,
    "temperature": 0.0
  }' | jq .
```

### Inference with the Base Model

```bash
curl -X POST http://localhost:8000/v1/chat/completions -H "Content-Type: application/json" \
  -d '{
    "model": "Qwen/Qwen3-VL-2B-Instruct",
    "messages": [{"role": "user", "content": [
      {"type": "text", "text": "Describe this image in detail"},
      {"type": "image_url", "image_url": {"url": "https://vllm-public-assets.s3.us-west-2.amazonaws.com/vision_model_images/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"}}
    ]}],
    "max_tokens": 300,
    "temperature": 0.0
  }' | jq .
```

---

## Configuration Reference

### Environment Variables

| Variable | Description | Default |
|----------|-------------|---------|
| `DYN_REQUEST_PLANE` | Transport plane (TCP for multimodal to avoid NATS 1MB limit) | `tcp` |
| `DYN_LORA_ENABLED` | Enable LoRA support | `true` |
| `DYN_LORA_PATH` | Local cache path for LoRA files | `/tmp/dynamo_loras_multimodal` |
| `DYN_SYSTEM_ENABLED` | Enable system management API | `true` |
| `DYN_SYSTEM_PORT` | Port for LoRA management API | `9090` |
| `AWS_ENDPOINT` | MinIO/S3 endpoint URL | `http://minio:9000` |
| `AWS_ACCESS_KEY_ID` | MinIO access key | From secret |
| `AWS_SECRET_ACCESS_KEY` | MinIO secret key | From secret |
| `AWS_REGION` | AWS region (required for S3 SDK) | `us-east-1` |
| `AWS_ALLOW_HTTP` | Allow HTTP connections | `true` |
| `BUCKET_NAME` | MinIO bucket name | `my-loras` |

### vLLM Arguments

| Argument | Description |
|----------|-------------|
| `--enable-multimodal` | Enable multimodal (vision) support |
| `--enable-lora` | Enable LoRA adapter support |
| `--max-lora-rank` | Maximum LoRA rank (must be >= your adapter's rank) |
| `--max-loras` | Maximum number of LoRAs to load simultaneously |
| `--gpu-memory-utilization` | Fraction of GPU memory to use (default 0.85) |
| `--max-model-len` | Maximum sequence length (default 8192) |
| `--max-num-batched-tokens` | Maximum batched tokens (default 8192) |

---

## Cleanup

### Remove vLLM Deployment

```bash
kubectl delete -f agg_qwen_lora.yaml -n ${NAMESPACE}
```

### Remove DynamoModel CRD

```bash
kubectl delete -f lora-model.yaml -n ${NAMESPACE}
```

### Remove Sync Job

```bash
kubectl delete -f sync-lora-job.yaml -n ${NAMESPACE}
```

### Remove MinIO

```bash
helm uninstall minio -n ${NAMESPACE}
```

### Remove Secrets

```bash
kubectl delete -f minio-secret.yaml -n ${NAMESPACE}
kubectl delete secret hf-token-secret -n ${NAMESPACE}
```

---

## Troubleshooting

### LoRA Fails to Load

1. **Check MinIO connectivity from worker**:
   ```bash
   kubectl exec -it deployment/agg-qwen-multimodal-lora-vllmworker -n ${NAMESPACE} -- \
     curl http://minio:9000/minio/health/live
   ```

2. **Verify LoRA exists in MinIO**:
   ```bash
   kubectl port-forward svc/minio -n ${NAMESPACE} 9000:9000 &
   aws --endpoint-url=http://localhost:9000 s3 ls s3://my-loras/ --recursive
   ```

3. **Check worker logs**:
   ```bash
   kubectl logs deployment/agg-qwen-multimodal-lora-vllmworker -n ${NAMESPACE}
   ```

4. **Verify adapter compatibility**: Ensure the LoRA adapter was trained for the same base model architecture (Qwen3-VL-2B) and that `max-lora-rank` (default 64) is >= the adapter's rank.

### Sync Job Fails

1. **Check job logs**:
   ```bash
   kubectl logs job/sync-hf-lora-to-minio -n ${NAMESPACE}
   ```

2. **Verify HuggingFace token**:
   ```bash
   kubectl get secret hf-token-secret -n ${NAMESPACE} -o yaml
   ```

3. **Check MinIO is accessible**:
   ```bash
   kubectl get svc minio -n ${NAMESPACE}
   ```

### OOM During Inference

- Qwen VL models use dynamic resolution: a 2560px image can produce 5000+ tokens
- Reduce `--max-model-len` in `agg_qwen_lora.yaml` args
- Add `--mm-processor-kwargs '{"max_pixels": 1003520}'` to cap image resolution
- Lower `--gpu-memory-utilization` to `0.80`

### MinIO Connection Refused

- Ensure MinIO pods are running: `kubectl get pods -n ${NAMESPACE} | grep minio`
- Check MinIO service: `kubectl get svc minio -n ${NAMESPACE}`
- Verify the `AWS_ENDPOINT` URL matches the service name

## Further Reading

- [Multimodal LoRA Launch Guide](../../../launch/lora/multimodal/README.md) - Local launch with shell scripts
- [LLM LoRA Deployment](../README.md) - Text-only LoRA deployment pattern
- [Dynamo Kubernetes Guide](../../../../../../docs/kubernetes/README.md) - Platform setup
- [Installation Guide](../../../../../../docs/kubernetes/installation-guide.md) - Platform installation