Publish NapistuDataStore:

README.md

@@ -52,7 +52,7 @@ store = NapistuDataStore.from_huggingface(
 )
 
 # Use the store (read-only)
-napistu_data = store.load_napistu_data("edge_prediction")
+napistu_data = store.load_napistu_data("relation_prediction")
 ```
 
 ### Configure DataConfig
@@ -68,7 +68,7 @@ config = DataConfig(
     store_dir=Path("./local_store"),
     hf_repo_id="seanhacks/relation_prediction",
     hf_revision="main",
-    napistu_data_name="edge_prediction",
+    napistu_data_name="relation_prediction",
 )
 
 # Use with NapistuDataStore.from_config()
@@ -76,48 +76,35 @@ from napistu_torch.napistu_data_store import NapistuDataStore
 store = NapistuDataStore.from_config(config)
 ```
 
-### Load Raw Data from GCS (Optional)
-
-If you need to create new artifacts, you can convert this read-only store to a non-read-only store
-by loading the raw data from GCS and enabling artifact creation:
+To make the store writable (non-read-only), provide paths to the raw data files:
 
 ```python
-from napistu_torch.napistu_data_store import NapistuDataStore
-from napistu.gcs.downloads import load_public_napistu_asset
-from napistu.gcs.constants import GCS_SUBASSET_NAMES
+from napistu_torch.configs import DataConfig
 from pathlib import Path
-import tempfile
 
-# Download raw data from GCS
-with tempfile.TemporaryDirectory() as temp_data_dir:
-    sbml_dfs_path = load_public_napistu_asset(
-        "human_consensus_no_rxns",
-        temp_data_dir,
-        subasset=GCS_SUBASSET_NAMES.SBML_DFS,
-        version="20251218",
-    )
-    napistu_graph_path = load_public_napistu_asset(
-        "human_consensus_no_rxns",
-        temp_data_dir,
-        subasset=GCS_SUBASSET_NAMES.NAPISTU_GRAPH,
-        version="20251218",
-    )
-    
-    # Load store from HuggingFace Hub
-    store = NapistuDataStore.from_huggingface(
-        repo_id="seanhacks/relation_prediction",
-        store_dir=Path("./local_store"),
-    revision="main"
-    )
-    
-    # Convert to non-read-only by enabling artifact creation
-    store.enable_artifact_creation(sbml_dfs_path, napistu_graph_path)
-    
-    # Now you can create new artifacts
-    store.ensure_artifacts(["new_artifact_name"])
+# 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"])
 ```
 
-Alternatively, you can use `from_huggingface` with paths directly:
+### Load Raw Data from GCS (Optional)
+
+If you need to create new artifacts, you can convert this read-only store to a non-read-only store
+by loading the raw data from GCS and passing the paths directly to `from_huggingface`:
 
 ```python
 from napistu_torch.napistu_data_store import NapistuDataStore
@@ -141,7 +128,7 @@ with tempfile.TemporaryDirectory() as temp_data_dir:
         version="20251218",
     )
     
-    # Load and convert in one step
+    # Load and convert to non-read-only in one step
     store = NapistuDataStore.from_huggingface(
         repo_id="seanhacks/relation_prediction",
         store_dir=Path("./local_store"),
@@ -149,6 +136,9 @@ with tempfile.TemporaryDirectory() as temp_data_dir:
         sbml_dfs_path=sbml_dfs_path,
         napistu_graph_path=napistu_graph_path,
     )
+    
+    # Now you can create new artifacts
+    store.ensure_artifacts(["new_artifact_name"])
 ```
 
 ## Note