BioNemo demo (#84)

* Add BioNeMo integration, single demo for now
---------

Co-authored-by: JMLizano <[email protected]>
Co-authored-by: Daniel Darabos <[email protected]>

lynxkite-app/src/lynxkite_app/__main__.py

@@ -6,7 +6,13 @@ import os
 def main():
     port = int(os.environ.get("PORT", "8000"))
     reload = bool(os.environ.get("LYNXKITE_RELOAD", ""))
-    uvicorn.run("lynxkite_app.main:app", host="0.0.0.0", port=port, reload=reload)
+    uvicorn.run(
+        "lynxkite_app.main:app",
+        host="0.0.0.0",
+        port=port,
+        reload=reload,
+        loop="asyncio",
+    )
 
 
 if __name__ == "__main__":

lynxkite-app/web/src/workspace/nodes/NodeWithVisualization.tsx

@@ -10,8 +10,8 @@ const NodeWithVisualization = (props: any) => {
     if (!opts || !chartsRef.current) return;
     chartsInstanceRef.current = echarts.init(chartsRef.current, null, {
       renderer: "canvas",
-      width: 250,
-      height: 250,
+      width: 800,
+      height: 800,
     });
     chartsInstanceRef.current.setOption(opts);
     const onResize = () => chartsInstanceRef.current?.resize();

lynxkite-graph-analytics/README.md

@@ -11,3 +11,44 @@ pip install lynxkite lynxkite-graph-analytics
 ```
 
 Run LynxKite with `NX_CUGRAPH_AUTOCONFIG=True` to enable GPU-accelerated graph data science operations.
+
+
+## BioNemo
+
+If you want to use BioNemo operations, then you will have to use the provided Docker image, or
+install BioNemo manually in your environment.
+Take into account that BioNemo needs a GPU to work, you can find the specific requirements
+[here](https://docs.nvidia.com/bionemo-framework/latest/user-guide/getting-started/pre-reqs/).
+
+The import of BioNemo operations is gate keeped behing the `LYNXKITE_BIONEMO_INSTALLED` variable.
+BioNemo operations will only be imported if this environment variable is set to true.
+
+To build the image:
+
+```bash
+# in lynxkite-graph-analytics folder
+$ docker build -f Dockerfile.bionemo -t lynxkite-bionemo ..
+```
+
+Take into account that this Dockerfile does not include the lynxkite-lynxscribe package. If you want to include it you will
+need to set up git credentials inside the container.
+
+Then, inside the image you can start LynxKite as usual.
+
+If you want to do some development, then it is recommend to use the [devcontainers](https://code.visualstudio.com/docs/devcontainers/containers)
+vscode extension. The following is a basic configuration to get started:
+
+```json
+// .devcontainer/devcontainer.json
+{
+	"name": "Existing Dockerfile",
+	"runArgs": [
+		"--gpus=all",
+		"--shm-size=4g"
+	],
+	"build": {
+		"context": "..",
+		"dockerfile": "../lynxkite-graph-analytics/Dockerfile.bionemo"
+	}
+}
+```

lynxkite-graph-analytics/src/lynxkite_graph_analytics/__init__.py

@@ -14,3 +14,6 @@ from .core import *  # noqa (easier access for core classes)
 from . import lynxkite_ops  # noqa (imported to trigger registration)
 from . import networkx_ops  # noqa (imported to trigger registration)
 from . import pytorch_model_ops  # noqa (imported to trigger registration)
+
+if os.environ.get("LYNXKITE_BIONEMO_INSTALLED", "").strip().lower() == "true":
+    from . import bionemo_ops  # noqa (imported to trigger registration)