handle ratelimit

utils.py

@@ -3,6 +3,7 @@ import torch
 from skinmodels import IsSkinResnet, IsHealthySkinResnet, SkinDiseaseModelResnet
 from config import read_disease_step, read_label_decode, transform_img
 import openai
+import time
 from config_path import SKINMODEL1_PATH, SKINMODEL2_PATH, SKINMODEL3_PATH, SKINDISEASE_STEP_PATH, SKINLABEL_DECODE_PATH
 
 def diagnosis(img):
@@ -48,22 +49,34 @@ def diagnosis(img):
 
     return label_decode[disease], disease_to_link[label_decode[disease]], disease_to_step[label_decode[disease]]
 
-def getMessage(msg):
-    openRespon = openai.ChatCompletion.create(
-        model="gpt-3.5-turbo",
-        messages=msg,
-        temperature=0.5
-        )
-    reply = openRespon.choices[0].message.content
-    return reply
 
-def cekApikey():
+def getMessage(msg):
     try:
         openRespon = openai.ChatCompletion.create(
-            model="gpt-3.5-turbo",
-            messages=[{"role" : "user", "content": "i"}],
+        model="gpt-3.5-turbo",
+            messages=msg,
             temperature=0.5
             )
-        return True
+        reply = openRespon.choices[0].message.content
+        return reply
+    except openai.error.RateLimitError:
+        return "Dokter saat ini sedang sibuk, tolong tunggu beberapa saat lagi"
     except:
+        return "Maaf, sepertinya dokter tidak bisa menjawab saat ini. Silahkan refresh halaman. Jika masalah masih terus berlanjut, silahkan hubungi admin"
+
+last_apikey_check = int(round(time.time()*1000))-35*1000
+def cekApikey():
+    try:
+        global last_apikey_check
+        t_stamp = int(round(time.time())*1000)
+        if((t_stamp-last_apikey_check) > 30*1000):
+            openRespon = openai.ChatCompletion.create(
+                model="gpt-3.5-turbo",
+                messages=[{"role" : "user", "content": "i"}],
+                temperature=0.5
+                )
+            last_apikey_check = t_stamp
+        return True
+    except Exception as err:
+        print(err)
         return False