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PCA_model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:18ff5b016631eb3c04cdd00842865d0c4e135e6ce65e6f143177fbde78c9bff7
+size 6316307

app_federal.py

@@ -200,6 +200,7 @@ def run_retrieval(query):
     print ("query", query)
 
     query_embeddings = run_dense_retrieval(query)
+    query_embeddings = pca_model.transform(query_embeddings)
     D, I = faiss_index.search(query_embeddings, 45)
     scores_embeddings = D[0]
     indices_embeddings = I[0]
@@ -242,6 +243,10 @@ ds = ds.with_format("np")
 faiss_index = load_faiss_index(ds["embeddings"])
 
 
+with open('PCA_model.pkl', 'rb') as f:
+    pca_model = pickle.load(f)
+
+
 with open("Federal_caselaw_metadata.json") as f:
     metadata = json.load(f)
  
@@ -259,6 +264,8 @@ if "NV" in model_name:
 
 examples = ["Can officers always order a passenger out of a car?"]
 
+
+
 css = """
 .svelte-i3tvor {visibility: hidden}
 .row.svelte-hrj4a0.unequal-height {