Update app.py

app.py

@@ -99,7 +99,7 @@ examples = [
     ]},
     {"code": "003", "examples": [
         "Alih kepemilikan kendaraan dengan plat F 3344 PQR",
-        "Proses balik nama untuk kendaraan plat W 5566 STU",
+        "Balik nama untuk kendaraan plat W 5566 STU",
         "Perubahan pemilik pada kendaraan plat AD 7788 VWX"
     ]},
     {"code": "004", "examples": [
@@ -228,7 +228,7 @@ model_id = model_ids[-1]
 model = SentenceTransformer(model_id, trust_remote_code=True)
 
 # codes_emb = model.encode([x[6:] for x in codes])
-codes_emb = model.encode([x["examples"] for x in examples])#.mean(axis=0)
+codes_emb = model.encode([x["examples"] for x in examples]).mean(axis=1)
 
 
 def censor_middle(number, num_to_hide=4):
@@ -302,16 +302,17 @@ def build_outputs(results, descriptions, result_details, plate_number):
 
     for i, (res,desc,detail) in enumerate(zip(results, descriptions, result_details)):
         harga_jual = vehicle["harga_jual"]
-        out += f"{i+1}. {detail}\nRumus: {desc}\nDetail perhitungan: {desc.replace('harga_jual', harga_jual)} = {res}\n"
+        res_str = "{:,}".format(res)
+        out += f"{i+1}. {detail}\nRumus: {desc}\nDetail perhitungan: {desc.replace('harga_jual', harga_jual)} = Rp{res_str}\n"
 
     # out += "----------------------------\nEstimasi biaya: "
     out += "\n\n\nEstimasi Biaya: "
 
     if len(results) > 1:
         out += " + ".join(["Rp{:,}".format(x) for x in results])
-        out += " = {:,}".format(sum(results))
+        out += " = Rp{:,}".format(sum(results))
     else:
-        out += "{:,}".format(results[0])
+        out += "Rp{:,}".format(results[0])
 
     out += "\n\n----------------------------"
     # out += "\n----------------------------\n\n--------------------------------"
@@ -501,7 +502,7 @@ def reload(chosen_model_id):
         model = SentenceTransformer(chosen_model_id, trust_remote_code=True)
         model_id = chosen_model_id
         # codes_emb = model.encode([x[6:] for x in codes])
-        codes_emb = model.encode([x["examples"] for x in examples])#.mean(axis=0)
+        codes_emb = model.encode([x["examples"] for x in examples]).mean(axis=1)
         return f"Model {chosen_model_id} has been succesfully loaded!"
     return f"Model {chosen_model_id} is ready!"