Update app.py

app.py

@@ -22,17 +22,17 @@ def generate_embeddings(texts, model_id, hf_token):
     embeddings = response.json()
     return embeddings
 AP_Bio = load_dataset('vjain/biology_AP_embeddings')
-dataset_embeddings1 = torch.from_numpy(AP_bio["train"].to_pandas().to_numpy()).to(torch.float)
+dataset_embeddings1 = torch.from_numpy(AP_Bio["train"].to_pandas().to_numpy()).to(torch.float)
 
 
-AP_Physics = load_dataset('vjain/AP_physics_embeddings')
-df2 = pd.DataFrame(AP_Physics['train'])
-df2["similarity"] = 0
+#AP_Physics = load_dataset('vjain/AP_physics_embeddings')
+#df2 = pd.DataFrame(AP_Physics['train'])
+#df2["similarity"] = 0
 
-dataframes = {
-    "AP_Bio": df1,
-    "AP_Physics": df2
-}
+#dataframes = {
+#    "AP_Bio": df1,
+#    "AP_Physics": df2
+#}
 
 #df = pd.read_csv("TA_embeddings.csv")
 #df["embedding"]=df["embedding"].apply(eval).apply(np.array)