init

app.py

@@ -40,23 +40,23 @@ def get_restaurants(search, location, meters):
 
     
     chat_response = openai_client.chat.completions.create(
-        model="gpt-3.5-turbo",
+        model="gpt-3.5-turbo-0125",
         messages=[
-            {"role": "system", "content": "You are a helpful restaurant assistant."},
+            {"role": "system", "content": "You are a helpful restaurant assistant. You will get a context if the  context is not relevat to the user query please address that and not provide by default the restaurants as is."},
             { "role": "user", "content": f"Find me the 2 best restaurant and why based on {search} and  {restaurant_docs}. explain trades offs and why I should go to each one. You can mention the third option as a possible alternative."}
         ]
         )
 
     trips_collection.delete_many({"searchTrip": newTrip})
+    if len(restaurant_docs) == 0:
+        return "No restaurants found", '<iframe style="background: #FFFFFF;border: none;border-radius: 2px;box-shadow: 0 2px 10px 0 rgba(70, 76, 79, .2);" width="640" height="480" src="https://charts.mongodb.com/charts-paveldev-wiumf/embed/charts?id=65c24b0c-2215-4e6f-829c-f484dfd8a90c&filter={\'restaurant_id\':\'\'}&maxDataAge=3600&theme=light&autoRefresh=true"></iframe>', str(pre_agg), str(vectorQuery)
 
     first_restaurant = restaurant_docs[0]['restaurant_id']
     second_restaurant = restaurant_docs[1]['restaurant_id']
     third_restaurant = restaurant_docs[2]['restaurant_id']
+    restaurant_string = f"'{first_restaurant}', '{second_restaurant}', '{third_restaurant}'"
 
-    if (first_restaurant or second_restaurant or third_restaurant) is None:
-        return "No restaurants found", '<iframe style="background: #FFFFFF;border: none;border-radius: 2px;box-shadow: 0 2px 10px 0 rgba(70, 76, 79, .2);" width="640" height="480" src="https://charts.mongodb.com/charts-paveldev-wiumf/embed/charts?id=65c24b0c-2215-4e6f-829c-f484dfd8a90c&filter={\'restaurant_id\':\'\'}&maxDataAge=3600&theme=light&autoRefresh=true"></iframe>'
-    else:
-        restaurant_string = f"\'{first_restaurant}\', \'{second_restaurant}\', \'{third_restaurant}\'"
+   
     iframe = '<iframe style="background: #FFFFFF;border: none;border-radius: 2px;box-shadow: 0 2px 10px 0 rgba(70, 76, 79, .2);" width="640" height="480" src="https://charts.mongodb.com/charts-paveldev-wiumf/embed/charts?id=65c24b0c-2215-4e6f-829c-f484dfd8a90c&filter={\'restaurant_id\':{$in:['  + restaurant_string  + ']}}&maxDataAge=3600&theme=light&autoRefresh=true"></iframe>'
 
     return chat_response.choices[0].message.content, iframe,str(pre_agg), str(vectorQuery)
@@ -88,7 +88,7 @@ def pre_aggregate_meters(location, meters):
     result = restaurants_collection.aggregate(pre_aggregate_pipeline);
 
     print(trips_collection.count_documents({"searchTrip": tripId}));
-    sleep(1)
+    sleep(5)
 
     return tripId, pre_aggregate_pipeline
 
@@ -106,18 +106,18 @@ with gr.Blocks() as demo:
         [
          
             gr.Textbox(placeholder="What type of dinner are you looking for?"),
-         gr.Radio([("work",{
+         gr.Radio([("Timesquare Manhattan",{
             "type": "Point",
             "coordinates": [
             -73.98527039999999,
             40.7589099
             ]
-        }), ("home",{
+        }), ("Westside Manhattan",{
             "type": "Point",
             "coordinates": [
             -74.013686, 40.701975
             ]
-        }), ("park", {
+        }), ("Downtown Manhattan", {
             "type": "Point",
             "coordinates": [ -74.000468,40.720777
             ]