From fee999417b852ff4a8211a6d5cc97ed5f3c636c2 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Julio=20C=C3=A9sar?= <jc@juliocesar.io>
Date: Sat, 18 Oct 2025 11:19:33 -0500
Subject: [PATCH 1/3] added docker image

---
 Dockerfile | 17 +++++++++++++++++
 1 file changed, 17 insertions(+)
 create mode 100644 Dockerfile

diff --git a/Dockerfile b/Dockerfile
new file mode 100644
index 000000000..9b06692d7
--- /dev/null
+++ b/Dockerfile
@@ -0,0 +1,17 @@
+FROM nvidia/cuda:12.6.3-base-ubuntu24.04
+
+# Install required packages
+RUN apt-get update && apt-get install -y python3 python3-pip python3-venv
+
+# Copy application files
+COPY . /app
+WORKDIR /app
+
+# Create and activate virtual environment
+RUN python3 -m venv /opt/venv
+ENV PATH="/opt/venv/bin:$PATH"
+
+# Install dependencies in virtual environment
+RUN pip install -e .[cuda]
+
+CMD ["/bin/bash"]
\ No newline at end of file

From ea2bb30035501db9204c1afea4607c77ef6f7bde Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Julio=20C=C3=A9sar?= <jc@juliocesar.io>
Date: Sat, 18 Oct 2025 11:19:46 -0500
Subject: [PATCH 2/3] added docker instructions

---
 README.md | 16 ++++++++++++++++
 1 file changed, 16 insertions(+)

diff --git a/README.md b/README.md
index 450e0bdad..bae3d45ed 100644
--- a/README.md
+++ b/README.md
@@ -35,6 +35,13 @@ git clone https://github.com/jwohlwend/boltz.git
 cd boltz; pip install -e .[cuda]
 ```
 
+or using Docker:
+
+```bash
+docker build -t boltz-2 .
+```
+
+
 If you are installing on CPU-only or non-CUDA GPus hardware, remove `[cuda]` from the above commands. Note that the CPU version is significantly slower than the GPU version.
 
 ## Inference
@@ -45,6 +52,15 @@ You can run inference using Boltz with:
 boltz predict input_path --use_msa_server
 ```
 
+Using docker image:
+
+```bash
+docker run \
+    -it --gpus all \
+    boltz-2:latest \
+    bash -c "boltz predict input_path --use_msa_server"
+```
+
 `input_path` should point to a YAML file, or a directory of YAML files for batched processing, describing the biomolecules you want to model and the properties you want to predict (e.g. affinity). To see all available options: `boltz predict --help` and for more information on these input formats, see our [prediction instructions](docs/prediction.md). By default, the `boltz` command will run the latest version of the model.
 
 

From 2266f9a22b99a1094774ab138d286c4e24bb0565 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Julio=20C=C3=A9sar?= <jc@juliocesar.io>
Date: Sat, 18 Oct 2025 11:24:32 -0500
Subject: [PATCH 3/3] added nvidia toolkit info

---
 README.md | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/README.md b/README.md
index bae3d45ed..f50764a7b 100644
--- a/README.md
+++ b/README.md
@@ -52,7 +52,7 @@ You can run inference using Boltz with:
 boltz predict input_path --use_msa_server
 ```
 
-Using docker image:
+Using the docker image:
 
 ```bash
 docker run \
@@ -61,6 +61,8 @@ docker run \
     bash -c "boltz predict input_path --use_msa_server"
 ```
 
+Make sure to install [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html) to run with GPU support.
+
 `input_path` should point to a YAML file, or a directory of YAML files for batched processing, describing the biomolecules you want to model and the properties you want to predict (e.g. affinity). To see all available options: `boltz predict --help` and for more information on these input formats, see our [prediction instructions](docs/prediction.md). By default, the `boltz` command will run the latest version of the model.