bug fix

app.py

@@ -8,12 +8,24 @@ import sqlite3
 import pandas as pd
 from tqdm import tqdm
 
+# Define the SentenceTransformer model globally
+model = SentenceTransformer('paraphrase-MiniLM-L6-v2')
+
 # Get the Groq API key from environment variables
 client = Groq(
     api_key="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"
 )
 
 
+# Generate user embedding using the globally defined model
+def get_user_embedding(query):
+    try:
+        return model.encode(query)
+    except Exception as e:
+        print(f"Error generating embedding: {e}")
+        return np.zeros(384)  # Return a zero-vector of the correct size if there is an error
+
+
 con = sqlite3.connect("file::memory:?cache=shared", check_same_thread=False)
 con.row_factory = sqlite3.Row
 cur = con.cursor()
@@ -47,12 +59,11 @@ if cur.fetchone() is None:
     )
     con.commit()
 
-# Compute and store embeddings
+# Compute and store embeddings for places using the same model
 def compute_and_store_embeddings():
-    model = SentenceTransformer('paraphrase-MiniLM-L6-v2')
     cur.execute("SELECT Place_Id, Place_Name, Category, Description, City FROM places")
     places = cur.fetchall()
-    
+
     for place in places:
         text = f"{place[1]} {place[2]} {place[3]} {place[4]}"
         embedding = model.encode(text)