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app.py

@@ -15,8 +15,23 @@ Environment variables:
 """
 
 import os
+import subprocess
+import sys
 from pathlib import Path
 
+# Install diffviews from git to bypass pip cache issues
+_REPO_URL = "https://github.com/mckellcarter/diffviews.git"
+_REPO_BRANCH = os.environ.get("DIFFVIEWS_BRANCH", "feature/modal-transition")
+_REPO_DIR = "/tmp/diffviews"
+
+if not os.path.exists(_REPO_DIR):
+    print(f"Cloning diffviews from {_REPO_BRANCH}...")
+    subprocess.run(
+        ["git", "clone", "--depth=1", "-b", _REPO_BRANCH, _REPO_URL, _REPO_DIR],
+        check=True,
+    )
+sys.path.insert(0, _REPO_DIR)
+
 import spaces
 
 # Data source configuration
@@ -83,6 +98,14 @@ def download_checkpoint(output_dir: Path, model: str) -> None:
         print("  Generation will be disabled without checkpoint")
 
 
+def get_pca_components() -> int | None:
+    """Read PCA pre-reduction setting from env. None = disabled."""
+    val = os.environ.get("DIFFVIEWS_PCA_COMPONENTS", "50")
+    if val.lower() in ("0", "none", "off", ""):
+        return None
+    return int(val)
+
+
 def regenerate_umap(data_dir: Path, model: str) -> bool:
     """Regenerate UMAP pickle for a model to ensure numba compatibility.
 
@@ -122,24 +145,26 @@ def regenerate_umap(data_dir: Path, model: str) -> bool:
         with open(json_path, "r") as f:
             umap_params = json.load(f)
 
+    pca_components = get_pca_components()
     print(f"  Regenerating UMAP for {model}...")
-    print(f"    Params: n_neighbors={umap_params.get('n_neighbors', 15)}, min_dist={umap_params.get('min_dist', 0.1)}")
+    print(f"    Params: n_neighbors={umap_params.get('n_neighbors', 15)}, min_dist={umap_params.get('min_dist', 0.1)}, pca={pca_components}")
 
     try:
         # Load activations
         activations, metadata_df = load_dataset_activations(activation_dir, metadata_path)
-        print(f"    Loaded {activations.shape[0]} activations")
+        print(f"    Loaded {activations.shape[0]} activations ({activations.shape[1]} dims)")
 
-        # Compute UMAP
-        embeddings, reducer, scaler = compute_umap(
+        # Compute UMAP (with optional PCA pre-reduction)
+        embeddings, reducer, scaler, pca_reducer = compute_umap(
             activations,
             n_neighbors=umap_params.get("n_neighbors", 15),
             min_dist=umap_params.get("min_dist", 0.1),
             normalize=True,
+            pca_components=pca_components,
         )
 
         # Save (overwrites existing pickle with compatible version)
-        save_embeddings(embeddings, metadata_df, csv_path, umap_params, reducer, scaler)
+        save_embeddings(embeddings, metadata_df, csv_path, umap_params, reducer, scaler, pca_reducer)
         print(f"    UMAP pickle regenerated: {pkl_path}")
         return True
 

requirements.txt

@@ -1,6 +1,6 @@
 # DiffViews - HuggingFace Spaces Requirements
 # Requires Python 3.10+
-git+https://github.com/mckellcarter/diffviews.git@920ef67  
+# Package installed via git clone in app.py (bypasses pip cache)
 
 # Core dependencies
 torch>=2.0.0