Publish NapistuDataStore:

README.md

@@ -17,10 +17,10 @@ This store was created from GCS asset: **human_consensus_no_rxns** (version: **2
 ### NapistuData (1)
 - `relation_prediction`
 
-### VertexTensors (1)
+### VertexTensor (1)
 - `comprehensive_pathway_memberships`
 
-### pandas DataFrames (5)
+### Pandas DataFrame (5)
 - `edge_strata_by_node_species_type`
 - `edge_strata_by_edge_sbo_terms`
 - `species_identifiers`
@@ -50,48 +50,26 @@ napistu_data = store.load_napistu_data("relation_prediction")
 
 ### Configure DataConfig
 
-You can also use this dataset in your `DataConfig` for PyTorch Lightning experiments:
+You can also use this dataset in your `DataConfig` YAML for PyTorch Lightning experiments:
 
-```python
-from napistu_torch.configs import DataConfig
-from pathlib import Path
-
-# Configure DataConfig to load from HuggingFace Hub
-config = DataConfig(
-    store_dir=Path("./local_store"),
-    hf_repo_id="seanhacks/relation_prediction",
-    hf_revision="main",
-    napistu_data_name="relation_prediction",
-)
-
-# Use with NapistuDataStore.from_config()
-from napistu_torch.napistu_data_store import NapistuDataStore
-store = NapistuDataStore.from_config(config)
+```yaml
+data:
+  store_dir: "./local_store"
+  hf_repo_id: "seanhacks/relation_prediction"
+  hf_revision: "main"
+  napistu_data_name: "relation_prediction"
 ```
 
 To make the store writable (non-read-only), provide paths to the raw data files:
 
-```python
-from napistu_torch.configs import DataConfig
-from pathlib import Path
-
-# Configure DataConfig to load from HuggingFace Hub and enable artifact creation
-config = DataConfig(
-    store_dir=Path("./local_store"),
-    hf_repo_id="seanhacks/relation_prediction",
-    hf_revision="main",
-    sbml_dfs_path=Path("/path/to/sbml_dfs.pkl"),
-    napistu_graph_path=Path("/path/to/napistu_graph.pkl"),
-    napistu_data_name="relation_prediction",
-)
-
-# Use with NapistuDataStore.from_config()
-# This will load from HF and convert to non-read-only automatically
-from napistu_torch.napistu_data_store import NapistuDataStore
-store = NapistuDataStore.from_config(config)
-
-# Now you can create new artifacts
-store.ensure_artifacts(["new_artifact_name"])
+```yaml
+data:
+  store_dir: "./local_store"
+  hf_repo_id: "seanhacks/relation_prediction"
+  hf_revision: "main"
+  sbml_dfs_path: "/path/to/sbml_dfs.pkl"
+  napistu_graph_path: "/path/to/napistu_graph.pkl"
+  napistu_data_name: "relation_prediction"
 ```
 
 ### Load Raw Data from GCS (Optional)
@@ -134,6 +112,12 @@ with tempfile.TemporaryDirectory() as temp_data_dir:
     store.ensure_artifacts(["new_artifact_name"])
 ```
 
+## Links
+
+- 🌐 [Napistu](https://napistu.com)
+- 💻 [GitHub Repository](https://github.com/napistu/Napistu-Torch)
+- 📚 [Napistu Wiki](https://github.com/napistu/napistu/wiki)
+
 ## Citation
 
 If you use this dataset, please cite: