feat: add rocm image build support and fix cuda (#292)

Signed-off-by: rmdg88 <rmdg88@gmail.com>
Signed-off-by: Rui-Dias-Gomes <rui.dias.gomes@ibm.com>
Co-authored-by: Rui-Dias-Gomes <rui.dias.gomes@ibm.com>
This commit is contained in:
Rui Dias Gomes
2025-07-31 13:22:42 +01:00
committed by GitHub
parent ce15e0302b
commit fd1b987e8d
16 changed files with 1205 additions and 923 deletions

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@@ -0,0 +1,21 @@
# AMD ROCm deployment
services:
docling-serve:
image: ghcr.io/docling-project/docling-serve-rocm:main
container_name: docling-serve
ports:
- "5001:5001"
environment:
DOCLING_SERVE_ENABLE_UI: "true"
ROCR_VISIBLE_DEVICES: "0" # https://rocm.docs.amd.com/en/latest/conceptual/gpu-isolation.html#rocr-visible-devices
## This section is for compatibility with older cards
# HSA_OVERRIDE_GFX_VERSION: "11.0.0"
# HSA_ENABLE_SDMA: "0"
devices:
- /dev/kfd:/dev/kfd
- /dev/dri:/dev/dri
group_add:
- 44 # video group GID from host
- 992 # render group GID from host
restart: always

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@@ -1,15 +0,0 @@
services:
docling:
image: ghcr.io/docling-project/docling-serve-cu124
container_name: docling-serve
ports:
- 5001:5001
environment:
- DOCLING_SERVE_ENABLE_UI=true
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: all # nvidia-smi
capabilities: [gpu]

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@@ -0,0 +1,20 @@
# NVIDIA CUDA deployment
services:
docling-serve:
image: ghcr.io/docling-project/docling-serve-cu126:main
container_name: docling-serve
ports:
- "5001:5001"
environment:
DOCLING_SERVE_ENABLE_UI: "true"
NVIDIA_VISIBLE_DEVICES: "all" # https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/docker-specialized.html
# deploy: # This section is for compatibility with Swarm
# resources:
# reservations:
# devices:
# - driver: nvidia
# count: all
# capabilities: [gpu]
runtime: nvidia
restart: always

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@@ -4,16 +4,17 @@ This document provides deployment examples for running the application in differ
Choose the deployment option that best fits your setup.
- **[Local GPU](#local-gpu)**: For deploying the application locally on a machine with a NVIDIA GPU (using Docker Compose).
- **[Local GPU NVIDIA](#local-gpu-nvidia)**: For deploying the application locally on a machine with a supported NVIDIA GPU (using Docker Compose).
- **[Local GPU AMD](#local-gpu-amd)**: For deploying the application locally on a machine with a supported AMD GPU (using Docker Compose).
- **[OpenShift](#openshift)**: For deploying the application on an OpenShift cluster, designed for cloud-native environments.
---
## Local GPU
## Local GPU NVIDIA
### Docker compose
Manifest example: [compose-gpu.yaml](./deploy-examples/compose-gpu.yaml)
Manifest example: [compose-nvidia.yaml](./deploy-examples/compose-nvidia.yaml)
This deployment has the following features:
@@ -22,7 +23,7 @@ This deployment has the following features:
Install the app with:
```sh
docker compose -f docs/deploy-examples/compose-gpu.yaml up -d
docker compose -f docs/deploy-examples/compose-nvidia.yaml up -d
```
For using the API:
@@ -56,7 +57,7 @@ Docs:
<details>
<summary><b>Steps</b></summary>
1. Check driver version and which GPU you want to use (0/1/2/3.. and update [compose-gpu.yaml](./deploy-examples/compose-gpu.yaml) file or use `count: all`)
1. Check driver version and which GPU you want to use 0/1/2/n (and update [compose-nvidia.yaml](./deploy-examples/compose-nvidia.yaml) file or use `count: all`)
```sh
nvidia-smi
@@ -117,7 +118,75 @@ Docs:
5. Run the container:
```sh
docker compose -f docs/deploy-examples/compose-gpu.yaml up -d
docker compose -f docs/deploy-examples/compose-nvidia.yaml up -d
```
</details>
## Local GPU AMD
### Docker compose
Manifest example: [compose-amd.yaml](./deploy-examples/compose-amd.yaml)
This deployment has the following features:
- AMD rocm enabled
Install the app with:
```sh
docker compose -f docs/deploy-examples/compose-amd.yaml up -d
```
For using the API:
```sh
# Make a test query
curl -X 'POST' \
"localhost:5001/v1/convert/source/async" \
-H "accept: application/json" \
-H "Content-Type: application/json" \
-d '{
"http_sources": [{"url": "https://arxiv.org/pdf/2501.17887"}]
}'
```
<details>
<summary><b>Requirements</b></summary>
- debian/ubuntu/rhel/fedora/opensuse
- docker
- AMDGPU driver >=6.3
- AMD ROCm >=6.3
Docs:
- [AMD ROCm installation](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/quick-start.html)
</details>
<details>
<summary><b>Steps</b></summary>
1. Check driver version and which GPU you want to use 0/1/2/n (and update [compose-amd.yaml](./deploy-examples/compose-amd.yaml) file)
```sh
rocm-smi --showdriverversion
rocminfo | grep -i "ROCm version"
```
2. Find both video group GID and render group GID from host (and update [compose-amd.yaml](./deploy-examples/compose-amd.yaml) file)
```sh
getent group video
getent group render
```
3. Build the image locally (and update [compose-amd.yaml](./deploy-examples/compose-amd.yaml) file)
```sh
make docling-serve-rocm-image
```
</details>