# BioNeMo Framework

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NVIDIA BioNeMo Framework is a is a comprehensive suite of programming tools, libraries, and models designed for computational drug discovery.

It accelerates the most time-consuming and costly stages of building and adapting biomolecular AI models by providing

domain-specific, optimized models and tooling that are easily integrated into GPU-based computational resources for the

fastest performance on the market. You can access BioNeMo Framework as a free community resource here in this repository

or learn more at <https://www.nvidia.com/en-us/clara/bionemo/> about getting an enterprise license for improved

expert-level support.

BioNeMo Framework is part of a larger ecosystem of NVIDIA Biopharma products. Get notified of new releases, bug fixes, critical security updates, and more for biopharma. [Subscribe.](https://www.nvidia.com/en-us/clara/biopharma/product-updates/)

## Structure of the Framework

The `bionemo-framework` is organized into independently installable namespace packages. These are located under the

`sub-packages/` directory. Please refer to [PEP 420 – Implicit Namespace Packages](https://peps.python.org/pep-0420/)

for details.

## Documentation Resources

- **Official Documentation:** For user guides, API references, and troubleshooting, visit our [official documentation](https://docs.nvidia.com/bionemo-framework/latest/).

- **In-Progress Documentation:** To explore the latest features and developments, check the documentation reflecting the current state of the `main` branch [here](https://nvidia.github.io/bionemo-framework/). Note that this may include references to features or APIs that are not yet finalized.

## Getting Started with BioNeMo Framework

Full documentation on using the BioNeMo Framework is provided in our documentation:

<https://docs.nvidia.com/bionemo-framework/latest/user-guide/>. To simplify the integration of optimized third-party dependencies, BioNeMo is primarily distributed as a containerized library. You can download the latest released container for the BioNeMo Framework from

[NGC](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/clara/containers/bionemo-framework). To launch a pre-built container, you can use the brev.dev launchable [![ Click here to deploy.](https://uohmivykqgnnbiouffke.supabase.co/storage/v1/object/public/landingpage/brevdeploynavy.svg)](https://console.brev.dev/launchable/deploy/now?launchableID=env-2pPDA4sJyTuFf3KsCv5KWRbuVlU) or execute the following command:

```bash

docker run --rm -it \

  --gpus=all --ipc=host --ulimit memlock=-1 --ulimit stack=67108864 \

  nvcr.io/nvidia/clara/bionemo-framework:nightly \

  /bin/bash

```

### Setting up a local development environment

#### Initializing 3rd-party dependencies as git submodules

The NeMo and Megatron-LM dependencies are included as git submodules in bionemo2. The pinned commits for these submodules represent the "last-known-good" versions of these packages

that are confirmed to be working with bionemo2 (and those that are tested in CI).

To initialize these sub-modules when cloning the repo, add the `--recursive` flag to the git clone command:

```bash

git clone --recursive git@github.com:NVIDIA/bionemo-framework.git

cd bionemo-framework

```

To download the pinned versions of these submodules within an existing git repository, run

```bash

git submodule update --init --recursive

```

Different branches of the repo can have different pinned versions of these third-party submodules. Ensure submodules are automatically updated after switching branches or pulling updates by configuring git with:

```bash

git config submodule.recurse true

```

**NOTE**: this setting will not download **new** or remove **old** submodules with the branch's changes.

You will have to run the full `git submodule update --init --recursive` command in these situations.

#### Build the Docker Image Locally

With a locally cloned repository and initialized submodules, build the BioNeMo container using:

```bash

docker buildx build . -t my-container-tag

```

#### VSCode Devcontainer for Interactive Debugging

We distribute a [development container](https://devcontainers.github.io/) configuration for vscode

(`.devcontainer/devcontainer.json`) that simplifies the process of local testing and development. Opening the

bionemo-framework folder with VSCode should prompt you to re-open the folder inside the devcontainer environment.

> [!NOTE]

> The first time you launch the devcontainer, it may take a long time to build the image. Building the image locally

> (using the command shown above) will ensure that most of the layers are present in the local docker cache.

### Quick Start

See the [tutorials pages](https://docs.nvidia.com/bionemo-framework/latest/user-guide/examples/bionemo-esm2/pretrain/)

for example applications and getting started guides.